Environmental Health:Economic Costs of Environmental Damage And Suggested Priority Interventions

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Environmental Health: Economic Costs of Environmental Damage

And Suggested Priority Interventions

A Contribution to the Philippines Country Environmental Analysis

Submitted to

The World Bank

Final Report March 31, 2009

Agustin L. Arcenas1

1 World Bank Consultant. The findings, interpretations, and conclusions expressed herein are those of the author’s, and do not necessarily reflect the views of the World Bank and its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent. Please email comments about the report to the author at [email protected]. The author would like to acknowledge and thank the following individuals and groups of individuals for all the help, assistance and comments and suggestions they generously shared in the conduct of the research and writing of this report: Dr. Jan Bojo and Ms. Maya Villaluz; the author’s research assistants, Ralph Bulatao and Iva Sebastian; Dr. Bjorn Larsen and Dr. Maureen Cropper; Prof. Elma Torres; Mr. Karl Galing; Dr. Dennis Batangan; The Manila Observatory; Dr. Bernardino Aldaba, Dr. Carlo Panelo, Mr. Carlos Tan, Mr. Paul Mariano and the HPDP group based at U.P. School of Economics; the staff at PhilHealth and the Department of Health; Dr. Stella Quimbo; and finally, Dr. Aleli Kraft.

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LIST OF ABBREVIATIONS 4-STC Four Stroke Tricycles ADB Asian Development Bank AF Attributable Fractions ALRI Acute Lower Respiratory Infection BCA Benefit-Cost Analysis CH4 Methane COPD Chronic Obstructive Pulmonary Diseases CO Carbon Monoxide CO2 Carbon Dioxide COC Certificate of Compliance COI Cost of Illness DALY Disability-Adjusted Life-Year DENR Department of Environment and Natural Resources DHS Demographic and Health Survey ECC Environmental Compliance Certificate EMB Environmental Management Board EO Executive Order ESI Economic Impacts of Sanitation in the Philippines FHSIS Field Health Surveillance Information System GNI Gross National Income GS Good Shepherd HCA Human Capital Approach HCV Human Capital Value HECS Household Energy Consumption Survey IAP Indoor Air Pollution I/M Inspection and Maintenance LC Local Currency LPG Liquefied Petroleum Gas LRT Light Rail Transit LTO Land Transportation Agency MMAQISDP Metro Manila Air Quality Improvement Sector Development

Program MMDA Metro Manila Development Authority MO Manila Observatory MRT Metro Rail Transit MT/T motorcycles and tricycles MVIS Motor Vehicle Inspection System NDHS National Demographic and Health Survey NGO Non-governmental Organization NO Nitrogen Oxide NO2 Nitrogen Dioxide NOx Nitrogen Oxides NPO National Press Office OAP Outdoor Air Pollution

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PEM Philippine Environmental Monitor PETC Private Emission Testing Center PGH Philippine General Hospital PhP Philippine Peso PHS Philippine Health Statistics PM Particulate Matter PNRI Philippine Nuclear Research Institute RR Relative Risk SOx Sulfur Oxide SPM Suspended Particulate Matter TOGs Total Organic Gases USAID United States Agency for International Development USD United States Dollar UV Ultraviolet VOC Volatile Organic Compound VSL Value of Statistical Life WHO World Health Organization WPR Western Pacific Region WSH Water Pollution, Sanitation and Hygiene WSP Water Pollution, Sanitation and Hygiene Project

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List of Figures

Figure 1 - Comparative Summary of the Economic Costs of WSH, IAP and OAP-

Related Illnesses, 2003 Figure 2 - Annual Average PM10 Levels in cities in Metro Manila and in Antipolo City Figure 3 - Annual Average PM2.5 Levels in Metro Manila Figure 4 - OAP Cost to Households of Treatment (Net of Public Health Care Subsidy),

2003 Figure 5 - Government Health Care Subsidy per OAP-Illness, 2003 Figure 6 - Lost Income Due to OAP-related Illnesses, 2003 Figure 7 - Total Economic Cost of OAP-related Morbidity, 2003 Figure 8 - Mortality Cases Due to OAP, Grouped According to Working and Non-

working Age Groups, 2003 Figure 9 - Cost of Premature Deaths due to OAP, 2003 Figure 10 - New Vehicle Registration (All Types) Trend, 2007 Figure 11 - Percentage of Households Use of the Type of Cooking Fuel, 2004 Figure 12 - Household Fuel Use by Urbanity, 1995 Figure 13 - Household Use of Solid Fuel by Income Class, 2004 Figure 14- Primary Cooking Fuel for Households, 2004 Figure 15 - Households Exposed to Indoor Air Pollution (in percentage) Figure 16 - Morbidity Cases Attributable to IAP, By Gender, 2003 Figure 17 - IAP Cost to Households of Treatment (Net of Public Health Care Subsidy),

2003 Figure 18 - Government Health Care Subsidy per IAP-Illness, 2003 Figure 19 - Lost Income Due to IAP-related Illnesses, 2003 Figure 20 - Total Economic Cost of IAP-related Morbidity, 2003 Figure 21 - Cost of Premature Deaths due to IAP, 2003 (HCV) Figure 22 - Mortality Cases Due to IAP Grouped According to Working and Non-

working Age Groups, 2003 Figure 23 - Household Access to Improved Water Supply and Sanitation, 2003 (National) Figure 24 - Household Access to Improved Water Supply and Sanitation, 2003 (Metro

Manila) Figure 25 - WSH Cost to Households of Treatment (Net of Public Health Care Subsidy),

2003 Figure 26 - WSH Cost to Households of Treatment (Net of Public Health Care Subsidy),

2003 per Illness Figure 27 - Government Health Care Subsidy per WSH-Illness, 2003 Figure 28 - Lost Income due to WSH-related Illnesses, 2003 Figure 29 - Total Economic Cost of Morbidity from WSH, 2003 Figure 30 - Mortality Cases Due to WSH Grouped According to Working and Non-

working Age Groups, 2003 Figure 31 - Cost of Premature Deaths due to WSH, 2003 (HCV) Figure 32 - Median Construction Cost of Water Supply Facilities for Select Regions (in

USD) Figure 33 - Percent Reduction in Diarrhea Morbidity of Different Water and Sanitation

Interventions

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Figure 34 - Cost-effectiveness of Water Supply, Sanitation, and Hygiene Promotion (USD/DALY)

Figure 35 - Median Construction Cost of Sanitation Technologies in Select Regions (in USD)

List of Tables Table 1 - Summary Table of Economic Costs Breakdown per Sector (USD’000) Table 2 - Summary of Mortality Cases Per Sector and Age Group, 2003 Table 3 - Summary of Morbidity Cases Per Sector and Age Group, 2003 Table 4 - Attributable Fractions (AF) for OAP-related Morbidity, 2003 Table 5 - Cases of OAP-related Illnesses by Age Group, 2003 Table 6 - Relative Risk Ratios and Corresponding Attributable Fractions for Specific

Illnesses Table 7 - Mortality Cases due to OAP, by Specific Age Group, 2003 Table 8 - BCA-ratios for Cases of Retro-fitting of In-use Diesel Vehicles in the

Philippines Table 9 - Light Rail Transits Lines in the Philippines Table 10 - Proposed Railway Projects with project costs (in USD millions) Table 11 - Financial Summary of MRT Line 3 Operations (in million pesos) Table 12 - Cost Estimates for the Metro Manila Air Quality Improvement Sector

Development Program (MMAQISDP) (in USD millions) Table 13 - Particulate Emissions from Household Cooking, 2004 Table 14 - Attributable Fractions Used for Morbidity Cases per Illness Table 15 - Cases of IAP-related Illnesses by Age Group, 2003 Table 16 - Attributable Fractions Used for Mortality Cases per Illness Table 17 - Mortality Cases Due to IAP by Specific Age Group, 2003 Table 18 - Overview of Costs and Impacts, Time Horizon of Modeled Impacts Table 19 - Benefit-Cost Ratios of Converting to a New Stove Technology to Control IAP

in the Philippines. Table 20 - Levels of Households According to Access to Water and Sanitation Facilities Table 21 - Responses to the Demographic and Health Survey, 2003 Table 22 - Attributable Fractions (AF) for WSH-related Illnesses, 2003 Table 23 - Total Cases of WSH-related Illnesses, 2003 Table 24 - Number of Cases of Diarrhea by Age Group, 2003 Table 25 - Number of Cases of WSH-related Illnesses (excluding Diarrhea) by Age

Group, 2003 Table 26.A -Mortality Cases due to WSH by Specific Age Group, 2003 Table 26.B -Mortality Cases due to WSH by Specific Age Group, 2003 Table 26.C - Mortality Cases for Malnutrition caused by Diarrhea for Children under 5

years old, 2003 Table 27 - Malnutrition-related Mortality Resulting from Diarrheal Infection, 2003

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Summary

Perhaps one of the most important and urgent issues that the Philippines faces today is that of environmental health. Defined to be the area of health concerns due to pollution and unsanitary conditions, it has caught the attention of government, prompting the national leadership to create an inter-agency committee focusing on these health issues; to bring forward an agenda of technical collaboration, information collection and dissemination, and policy review.

This study on environmental health issues in the Philippines was conducted to provide guidance—in terms of information and suggestions on policy interventions—to policy managers and researchers, and donor agencies. There are three areas of focus: urban outdoor air pollution (OAP), household indoor air pollution (IAP), and water pollution, sanitation and hygiene (WSH)(including WSH-related child malnutrition). It gathered the available data from different published data sources in the Philippines on morbidity and mortality, to calculate the number of cases, and the corresponding economic costs to the country in terms of lost productivity, direct costs to households, and public funds used to subsidize treatment costs. A comparative summary of the economic valuation of the environmental health costs of these three is presented below in Figure 1:

Figure 1 – Comparative Summary of the Economic Costs of WSH, IAP, and OAP Health Effects, 2003

PhP 4.7 B($0.1 B)

PhP 23.6 B($0.4 B)

PhP 5.1 B($0.1 B)

PhP 60.6 B($1.1 B)

PhP 51.0 B($ 0.9 B)

PhP 102.5 B($1.9 B)

0 20 40 60 80 100 120

Indoor Air Pollution

Outdoor Air Pollution

Water, Sanitation andHygiene (including u5

Malnutrition)

Morbidity + Mortality (HCA) Morbidity + Mortality (VSL)

Source: Author’s calculations

As reflected in Figure 1, two methods were used to calculate the economic costs of premature deaths: the human capital value (HCV) and the value of statistical life (VSL)—the results were used as the lower and upper bounds of the economic cost of

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mortality. The HCV is the economic cost to society of premature death in terms of lost contribution to production of an individual. The VSL , on the other hand, is based on individuals’ willingness-to-pay for a reduction in the risk of death. The cost-of-illness (COI) approach is used to estimate the cost of morbidity and is based on the costs of treatment and the lost income from being ill. It must be noted that this report made additional calculations to estimate the economic costs of malnutrition-related deaths resulting from diarrhea in children under 5 years old. The analysis was limited to this age group as there were no data on the other age groups that could be used to estimate premature deaths from diarrhea-induced malnutrition mortality for these groups of individuals.

The results indicate that the economic costs of pollution and sanitation-related health effects are high and cannot be ignored. The combined costs for all three sectors in 2003 totaled PhP 42.4 billion (USD 783.2 million) in lost productivity due to premature deaths or PhP 168.4 billion (USD 3.1 billion) in terms of value of statistical life (Table 1). In addition, the cost of morbidity was PhP 18.3 billion (USD 337.6 million), comprising of loss in productivity totaling PhP 10.4 billion (USD 191.3 million), direct costs to Filipino households to treat these illnesses totaling PhP 6.4 billion (USD 118.7 million), and the cost to the government health care insurance system—representing the subsidy for PhilHealth members’ hospitalization costs—and for general government subsidy for publicly-owned health facilities was close to PhP 1.5 billion (USD 27.6 million).

Table 1 – Summary Table of Economic Costs Breakdown per Sector (USD’000)

Source: Author’s calculations based on published data sets and empirical studies. The information on malnutrition was based on the calculations of B. Larsen.



Water, Sanitation and

Hygiene (including u5 Malnutrition)

All Sectors

Economic Cost (in USD‘000) Morbidity 18,727 11,327 307,583 337,638Mortality (HCV) 68,017 82,702 632,474 783,192Mortality (VSL) 415,975 1,107,532 1,584,394 3,107,900Morbidity and Mortality (HCV) 86,744 94,029 940,057 1,120,830

Morbidity and Mortality (VSL) 434,702 1,118,859 1,891,977 3,445,538

Economic Cost as Percentage of GNI Morbidity 0.02 0.01 0.31 0.34Morbidity and Mortality (HCV) 0.09 0.09 0.94 1.12

Morbidity and Mortality (VSL) 0.43 1.12 1.89 3.45

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A comparison of the economic costs for all three sectors (including malnutrition- related health effects in children under 5 years old from WSH) indicates that the most pressing issue in environmental health is water, sanitation and hygiene, costing the Philippine society almost USD 1-2 billion per year (HCV and VSL estimates for cost of deaths) representing more than 33 million cases of illness and 22 thousand deaths in 2003. Outdoor air pollution comes in second with USD 94 million to USD 1 billion in economic costs, registering close to one million cases of respiratory illness and over 15 thousand premature deaths. Indoor air pollution comes next, costing the Philippine society USD 87 to 434 million in 2003, resulting from nearly half a million cases of IAP-related illnesses and almost 6 thousand deaths due to exposure to indoor air pollution from household use of solid fuels for cooking. (Details of these figures are in Tables 2 and 3). Tables 2 and 3 show us that OAP and IAP-related deaths are heavily skewed toward adult and working age groups, while deaths resulting from WSH are in the youngest members of society. This has implications in terms of vulnerability assessment, policy prioritization, and target-setting.

Table 2 – Summary of Mortality Cases per Sector and Age Group, 2003

Age Group Indoor Air Pollution



Hygiene

Under-5 Malnutrition from WSH

All Sectors

Younger than 1 653 199 2,048 3,719 6,6201 to 4 632 194 8,502 3,897 13,2255 to 14 0 0 1,637 0 1,63715 to 19 19 0 135 0 15420 to 29 82 0 189 0 27130 to 64 1,890 5,588 1,043 0 8,52065 and older 2,492 9,369 851 0 12,711Age not reported 4 17 2 0 23All Age Groups 5,772 15,367 14,406 7,616 43,161 Sources: The author calculated the mortality cases for OAP, IAP and WSH. For the malnutrition-related numbers, this report used B. Larsen’s calculations. Note: Those entries with zeroes do not mean that there were no cases, but simply that there were no available data which could be used to calculate the number of cases for these age groups.

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Table 3 – Summary of Morbidity Cases per Sector and Age Group, 2003

Age Group Indoor Air Pollution



Hygiene All Sectors

Younger than 1 147,517 259,966 4,766,078 5,173,561 1 to 4 244,185 441,859 14,704,145 15,390,189 5 to 14 0 256,578 6,170,901 6,427,479 15 to 19 716 8,474 277,625 286,815 20 to 29 1,173 13,891 455,031 470,095 30 to 64 47,746 40,415 6,610,177 6,698,338 65 and older 16,435 16,856 478,527 511,818 All Age Groups 457,772 1,038,039 33,462,483 34,958,294


Suggested interventions were culled from the existing literature. For outdoor air pollution, the interventions in discussion are those that address emissions from mobile sources such as improved traffic management to lessen travel time, improved inspection and maintenance systems, additional investments in affordable mass transport systems, and affordable pollution control devices for tricycles and motorcycles. For indoor air pollution and water, sanitation and hygiene, it is apparent that interventions must target behavior—cooking practices and ventilation for indoor air2; and hygiene of household members to prevent water and sanitation illnesses. Interventions to involve the communities to create and promote low-cost alternative stoves to the current solid fuel-using stoves are suggested. Additional initiatives to increase the access of households especially in the rural areas and the urban poor to a sewage system and clean water are needed in order to decrease the exposure of the population to pathogens that cause diseases.

2 It must be noted that cases of indoor air pollution-related illnesses due to cigarette smoking is not part of the study. Hence, cigarette-smoking as a risk factor is not mentioned.

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Introduction

One of the clearest indicators of the state of the environment in the Philippines is perhaps the magnitude of the cases of pollution-related illnesses. The Philippines, being a country with increasing productive activities fueled by a growing population, is squarely confronted with the impacts of pollution on human welfare—a pollution-welfare nexus—which take on several forms: availability of income opportunities, access to environmental services, and in recent times, on human health. Among the areas of concern within the pollution-welfare nexus, it is the human health angle that has captured the attention and alarm of policy managers because of its growing incidence, and the burden that it forces the poorest members of society to shoulder as a result of it.

Environmental health—the area of health concerns arising from poor environmental quality, causing disease, injuries and deaths—is a serious and pressing issue in countries such as the Philippines, which is still finding that point of sustainable economic growth. It is an important enough issue that the Philippine government enacted and adopted Executive Order (E.O.) 489 which created an inter-agency committee on environmental health to establish and bring forward an agenda of technical collaboration, information collection and dissemination, and policy review.

As part of the support for the country to plan and develop programs that are consistent with addressing the problems in environmental health in the Philippines, the information and analyses contained in this study have been carefully collected. The objective is to aid policy makers understand how the country is faring in environmental health issues; and determine what these health problems are costing the country in terms of loss in productivity and direct costs to households. This study on environmental health quantifies and analyzes the bio-physical dimensions of environmental degradation and likewise determines the social costs of environmental degradation; and the potential economic benefit of environmental improvement as they relate to environment-related health effects. In addition, potential priority interventions—as suggested by the existing literature— is examined to determine the feasibility of each in addressing the environmental health issues in the Philippines.

These health effects of poor environmental quality negatively impact human welfare (and ultimately, the welfare of society) by lowering the quality of life for individuals afflicted with these health effects—which is represented by the lost income opportunities as a result of being ill, and the opportunity cost of income that has to be spent on treatment and care—and the loss of valuable and productive members of society—as measured either by a permanent loss in productivity as a result of death (the human capital value), or by the willingness-to-pay of individuals to reduce the risk of deaths resulting from these illnesses (the value of statistical life approach).

There are three areas of specific interests that will be discussed: 1) urban outdoor air pollution; 2) household indoor air pollution; and finally, 3) water pollution, sanitation and hygiene. The primary research objectives are to determine and quantify the economic costs of environmental degradation—focusing on these three areas—in terms of their impacts on the health of the citizens of the country, and to evaluate the economic

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feasibility and efficiency of potential interventions. There is a particular interest in evaluating environmental health in the context of poverty and other high risk groups such as women and children. The poor are the most susceptible members of society to the health risks posed by a degraded environmental quality, because they lack the necessary resources for disease prevention and treatment. Women and children are in a similar risky position because they do not have the same health-care opportunities and access to education and information that adult men possess.

To calculate the economic impacts of morbidity arising from environment-related illnesses, the fundamental approach used was the cost-of-illness (COI) valuation method. This necessitated a determination of the different treatment-seeking behaviors of Filipinos, and an estimation of the corresponding medical costs attributable to each. In addition, productivity losses were calculated by estimating a reduction in gross national income as a result of missed days from work resulting from illness. To these numbers, the public expenditures on subsidies for health treatment were added to determine the total economic costs of environment-related morbidity.

The computation of the economic costs of premature deaths caused by pollution and unsanitary practices proved to be more challenging than the calculations for morbidity costs. This is due to the differing perspectives among scholars on how best to estimate the value of a lost human life. To capture these differences, this study calculated lower and upper bounds values based on the human capital value approach (HCV) and the value of statistical life (VSL). The HCV estimates the value of loss of life based on an individual’s foregone contribution to aggregate income as a result of premature death—measured in terms of per capita gross national income. The VSL, on the other hand, is a measure of one life lost in terms of how much money people are willing to pay to reduce the risk of death. Which of these two approaches better approximates the cost of loss of human life as a consequence of environment-related illnesses is not for this report to decide on. But whichever that may be, the fact remains that many people could have lived a longer, healthier and more productive life if the risks to life were not increased as a result of a degraded environment. The estimated values of the lives lost presented in this report—both the HCV and VSL—merely provide a benchmark by which the gravity of these environment-related health causes are represented.

The organization of this report is based according to the issues within the areas of environmental health mentioned earlier. The basic idea is to present estimates of the environmental health effects of the degradation of the natural environment to aid policy managers. This information is crucial in evaluating the feasibility of potential policy interventions and determining which among these interventions promise to deliver the highest net benefit at the least cost. To the maximum extent possible, the methodologies and assumptions used to calculate the number of cases of illness and deaths and the corresponding economic costs were harmonized with the existing World Bank studies such as the Philippine Environmental Monitor (PEM) and the Economics of Sanitation Initiative in the Philippines (ESI). There were many instances, however, when new information were uncovered that could refine the computations in these studies. In these cases, this study expanded the set of assumptions and modified the methodologies to build on the results of these existing research reports. A great deal of effort was exerted to list all the numerous assumptions to guide the reader in understanding the process by

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which the calculations in this study were made. It is strongly suggested that the readers refer to Annex 1 for clarifications on the computations.

It must be emphasized that great effort was undertaken to review the existing empirical studies on environmental health issues in the Philippines. Whenever appropriate, comments on the drafts of this report were solicited from some of the authors of these studies to determine any points of contention and contradiction between the information contained in this study and the existing literature on environmental health in the country. The conclusion is that there are some differences in the numbers of cases and valuation, but these differences are due to the differing scopes of work, assumptions, methodologies used in this report and the other empirical works. This report made detailed assumptions and modified the standard dose-response methodologies to capture the different treatment-seeking behavior of Filipinos to estimate morbidity figures. The result is a general methodological framework of valuation and analysis that is unique to the situation in the Philippines.

As a final note, the issue of how different is this report from the PEM and ESI—the two most recent initiatives of the World Bank dealing with environmental health—must be squarely addressed. The data used in this study are the same basic data used by the PEM and the ESI, but its approach in filling data gaps is different because of recent information that were not available to the authors of those studies during the time they were conducting the research. In addition, this report also has a different scope of analysis than the PEM and ESI—the PEM focusing solely on the determination of the number of cases of illness and deaths while this report took the next step of economic valuation; the ESI’s economic analysis, on the other hand, was more encompassing than this report in relation to sanitation and hygiene, as it included the impacts on non-production activities such as tourism. It is important that the readers and users of this report keep these differences in mind, so as not to pit the findings and conclusions of this report against those of PEM’s and the ESI’s.


The deterioration of urban outdoor air quality in the Philippines is at a level where one can visually observe air pollution in major cities such as those in Metro Manila. An individual only needs to take public transportation any time of the day and see black fumes spew out of decade-old buses to get a sense of the tight spot that the country faces when it comes to air quality. The threat of poor air quality has already reached the attention of law makers and the average Filipino, prompting Congress to pass the Clean Air Act in 1999 in order to properly address the impacts of mounting air pollution in the country. It is expected that the implementation of the law will translate into concrete steps both by the public and private sectors to reverse the deterioration of the nation’s air quality.

There are generally two types of air pollution: outdoor (mobile, stationary and area sources) and indoor (stoves and cigarette-smoking). Outdoor air pollution is an external (to the household) pollutant and often large-scale in its presence, affecting

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multiple sectors and crossing geographical boundaries. Indoor air pollution is a household issue attributable to proximity to indoor air pollutants such as smoke from cooking, and cigarette smoke. Between the two types, it is outdoor air pollution that attracts greater public attention. Not surprisingly, this has resulted in a greater awareness among the citizens and a heightened sentiment of urgency to address. In most instances, however, the discussion on outdoor air pollution has been confined to the experience and issues of mega-cities, specifically, the high-profile cities in Metro Manila. This due to the fact that based on the existing data, the highest concentration of outdoor air pollutant sources—e.g., production plants and factories, private vehicles, buses, public jeepneys and other modes of public transportation—is in Metro Manila.

The main driver of outdoor air pollution is the rapid urbanization, transport and increasing expansion of manufacturing activities and industrial production in the country. The ADB (2006) reports that the industrial sector in the Philippines grew by an average of 3.2 percent between 1988 and 2002; and the National Statistics Office (2006) reports that close to half (47 percent) of the manufacturing activities in the country occur in Metro Manila, and more than a third (32 percent) are located in the urban centers around or close to Metro Manila. This trend, along with the increasing migration from the rural areas to the urban centers, has caused a heightened demand for services and transport that—in the absence of effective air pollution management—resulted in degradation of outdoor air quality in the cities and other urban areas.

It is difficult to pin down in exact terms what the state of air quality is in the Philippines because of the very limited data collected. The law requires the Environmental Management Board (EMB) to monitor air quality in the country, and to establish an inventory of air emissions every three years. The monitoring, however, has been limited to a review of studies conducted by non-government and international development agencies, limited field surveys, and collation of information from self-monitoring reports submitted by industry members.3 The latest emissions inventory (the 2001 Philippine Emissions Inventory) included particulate matter (PM), sulfur oxide (SOx), nitrogen oxide (NO), carbon monoxide (CO), volatile organic compounds, and total organic gases (TOGs) from mobile sources (ADB, 2006). The report estimates that CO contributes the heaviest to total pollution load at 39 percent, followed by NO at 35 percent, SOx and PM at 8 percent, TOG at 7 percent and finally, VOC at 2 percent. Regular source apportionment4 analyses, however, are not done by EMB. Apportionment studies, instead, are being conducted by two institutions: the Philippine Nuclear Research Institute (PNRI, a government facility) and the Manila Observatory (a non-government institution). Both of these institutions’ regular apportionment analyses, however, are only on the small particulate matter: PM10 and PM2.5 or particulate matters that measure less than 10 and 2.5 micrometers in diameter respectively; and the samples are gathered from stations which are (at present) only in Metro Manila or in close proximity to the area. The

3 The law requires that industry members submit periodic self-monitoring reports as part of the conditions contained in their Environmental Compliance Certificate (ECC). 4 Source apportionment analysis determines what the contribution of each source of pollutant to a specific location.

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air quality of a few cities5outside of Metro Manila has been monitored by EMB but has since stopped in 2006.

Given the data availability, this study can only focus on the health impacts that are associated with particulate matter of sizes 10 and 2.5 micrometers. While it is recognized that the other pollutants cited earlier have potentially significant impacts on the health of Filipinos, the data gaps that characterize these other outdoor air pollutants are too wide to be overcome. Nevertheless, a meaningful assessment—albeit limited—on the economic impacts of health problems arising from is possible, because there is sufficient information on PM10 and PM2.5 levels available; and there is sufficient supply of technical data—raw PM levels and epidemiological studies that establish the “dose-response” connections between long-term exposure to particulate matter and specific identified illnesses such as respiratory and cardiovascular ailments.

If the reported levels of particulate matter were to be indicators of the state of health effects in Filipinos exposed to particulate matter, then there is indeed a cause for concern. This report’s estimates on PM10 and PM2.5

6 in Metro Manila indicate a population-weighted average of 72 μg/m3 and 48 μg/m3, respectively for 2003. For urban areas outside of Metro Manila, the estimates also show values of 38 μg/m3 for PM10 and 18 μg/m3 for PM2.5 for the same year. There are no PM values for the rural areas because of insufficient data. These numbers are significantly above the guidelines set by the World Health Organization (WHO) of 20 μg/m3 for PM10, and 10 μg/m3 for PM2.5.

Figures 2 and 3 below illustrate the PM levels data gathered from the different stations in Metro Manila and one baranggay right outside of Metro Manila (baranggay Inarawan in Antipolo; the Good Shepherd (GS) is another station located also in Antipolo). The sites that the Manila Observatory (MO) uses to test and collect data on PM concentrations in Metro Manila show a consistently high level—even if the level has somewhat declined through the years—of PM concentrations. It must be pointed out that the different sites vary in characteristics; the MO categorizes the sites as high, medium, and low mobile source presence. As to be expected, the site at the National Press Office (NPO), which has the heaviest vehicle-density, has the highest PM concentrations; the Good Shepherd site in the city of Antipolo—categorized as the low mobile source presence—registered the lowest PM concentrations. While this is not conclusive evidence, it does provide some basis to the assertion that vehicles are very likely to be a major contributor to the high PM levels in the Metro Manila, as well as to the other urban areas in the country.

5 These cities are Indang (Cavite), Batangas City (Batangas), Angeles City (Pampanga), and Los Baños, Laguna. Cebu city is also monitored but only for NO2, SO2, O3, benzene, toluene, and xylene only. (Source: EMB’s National Air Quality Status Report, 2003, as cited in the discussion draft of the Country Synthesis Report on Urban Air Quality Management in the Philippines by ADB). 6 The PM10 and PM2.5 average estimates for Metro Manila were calculated using actual data collected by the Manila Observatory, and weighted according to population around the stations. These stations were Manila Observatory (MO), National Printing Office (NPO), Philippine General Hospital (PGH), Good Shepherd (GS in Antipolo), Pasig, Las Pinas, Valenzuela, Pateros, Taguig, and Inarawan (in Antipolo). The MO’s data collection was part of the ADB/WHO/DOH project in 2003-04.

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Figure 2 - Annual Average PM10 Concentrations in cities in Metro Manila and in Antipolo City

0

25

50

75

100

MONP

OPG

H GS

Las P

inas

Valenz

uela

Inar

awan

Tagu

ig

Site

PM

10 L

evel

(ug/m

3)

2001 2002 2003

Source: Manila Observatory, 2004

Figure 3 - Annual Average PM2.5 Concentrations in Metro Manila

Annual Average PM2.5 Levels, Metro ManilaSource: Manila Observatory

0

25

50

75

MO NPO PGH GS Pasig Las Pinas Valenzuela

Site

PM

2.5

Level

(ug/m

3)

20002001200220032004

Source: Manila Observatory 2004

Economic Costs of OAP-related Morbidity

To estimate the health effects and economic burden caused by exposure to particulate matter (PM), it is necessary to identify the illnesses that can be feasibly included, and to determine the attributable fractions7 (AFs) of these illnesses from PM. The decision as to which illness to include in this analysis is fundamentally about data availability. Two considerations are at hand: the availability of information regarding risks of becoming ill (for each disease) from exposure to PM, and the availability of reliable information on the frequency or incidence for each disease. Unfortunately, the information is wanting, and this study is thus limited to analyzing the economic burden of disease of two health endpoints: acute lower respiratory infection (ALRI, including 7 Attributable fractions are defined simply as the fraction or ratio of incidence of illness that can be accounted or attributed to a certain health risk such as exposure to particulate matter.

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pneumonia), and acute bronchitis.8 Other diseases that could not be included due to data gaps are chronic obstructive pulmonary diseases (COPD), cardiovascular disease, exacerbation of asthma, lung cancer and possibly tuberculosis. The data on risk ratios were sufficient to compute the AFs for specific ALRI illnesses, as summarized below in Table 4:

Table 4 – Attributable Fractions (AF) for OAP-related Morbidity, 2003

Source: Author’s calculations based on Galassi et al (2000)

Note: The AFs for pneumonia are adopted from the AFs for respiratory diseases. It must be noted also that the AFs were calculated only for Metro Manila and other urban areas. AFs for the rural areas could not be compute due to insufficient data.

The data presented above frame the discussion on the elevated levels of PM concentration in the country. Comparing the data with the guidelines set by the WHO, it is apparent that the concentrations of particulate matter has consistently been above the guidelines of 10 μg/m3 for PM2.5 and 20 μg/m3 for PM10 during the period the data were collected. In the absence of mitigating measures that could shield the population from long-term exposure, continuously high levels of PM10 and PM2.5 have taken their toll on the health and consequently, the productivity and welfare of Filipinos. The calculations show that the total number of people who have been ill due to outdoor air pollution—specifically from PM emissions—reached more than 1 million Filipinos in 2003. This cost the national economy in lost productivity a total of PhP 254.7 million (equivalent to USD 4.7 million9, as shown in Figure 6) from lost days due to illnesses related to outdoor air pollution (including the lost income of parents who have missed work days to care for their sick children). The burden on the households resulting from these illnesses reached PhP 289.1 million (USD 5.3 million), and an additional PhP 70.0 million (USD 1.3 million) in health care subsidy10 from the national government. Table 5 below summarizes the morbidity cases of OAP-related illnesses by each group. 8 Technically, acute bronchitis is included in ALRI. The data from the Department of Health (DOH), however, list ALRI and acute bronchitis separately. This report is consistent with the distinction between the two. 9 The foreign exchange rate used was PhP 54.2 = USD 1.0 which was based on the average exchange rate for the year 2003. 10 The health care subsidy represents PhilHealth payments to its members and subsidy to patients who are admitted in public-owned hospitals for treatment.

Health Outcome Attributable Fractions

Pneumonia* - Hospital cases - Non-hospital cases

0.02555 0.11297

Acute Bronchitis, under 5 0.42343

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Table 5 – Cases of OAP-related Illnesses by Age Group, 2003

ALRI (including Pneumonia) Acute Bronchitis

Younger than 1 104,494 155.471Age 1 to 4 169,618 272,240Age 5 to 14 60,766 195,812Age 15 to 19 8,464 10Age 20 to 29 13,875 16Age 30 to 64 40,374 4165 and older 16,844 12TOTAL 414,437 623,602


Figure 4 – OAP Cost to Households of Treatment (Net of Public Health Care Subsidy), 2003

ALRI and PneumoniaPhP 190 M

66%

Acute BronchitisPhP 100 M

34%


18

Figure 5 – Government Health Care Subsidy per OAP-Illness, 2003

ALRI and Pneumonia

PhP 61 M87%

Acute Bronchitis

PhP 9 M13%

Source: Author’s calculations Figure 6 – Lost Income Due to OAP-related Illnesses, 2003


33% ALRI and

PneumoniaPhP 170 M

67%


19

Figure 7 - Total Economic Cost of OAP-related Morbidity, 2003


32%


68%


The data in Table 5 indicate that it is the youngest members of society (those that are 14 years old and younger) that carry the heaviest burden of lower respiratory infections due to outdoor air pollution. This is alarming because it hits the potential productive members of society during their formative stage, and may impact the productivity of the future labor force in the Philippines. It should however be noted that these estimates are limited to ALRI and acute bronchitis due to data limitations, and do not include cardiovascular disease, chronic bronchitis and other diseases that predominantly affect the adult population.

Economic Costs of Premature Deaths due to OAP

The calculations of the value premature deaths for all the mortality cases attributable to OAP (as well as for IAP and WSH-related illnesses) were done under two sets of definitions of value of premature deaths: 1) value in terms of the lost contribution of the individual to economic activity (HCV or human capital value); 2) value of statistical life as measured by how much individuals are willing to pay to reduce the risk of dying. These two approaches yield two different valuations, but it is difficult to assert if one is superior to the other. As a way to establish a range of values of economic or welfare loss to society as a result of premature death, both of the values computed using the HCV and the VSL approaches are presented. The lower bound of the range is represented by HCV figures, while the VSL numbers are used as the upper bound. As a starting point to determine this range of values, the mortality cases attributable to OAP are computed, the results of which are presented in Figure 8. Mortality cases per age group is also summarized and presented in Table 7. The number of cases is calculated

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using AFs derived from relative risk ratios (RRs) which are computed using the data from MO. The RRs and the AFs used for this section are summarized in Table 6 below: Table 6 – Relative Risk Ratios and Corresponding Attributable Fractions for Specific Illnesses

Source: Author’s calculations based on collected information on PM concentrations from the Manila Observatory, published data from the government, and methodology for estimating mortality adopted from Ostro, 2004. There are no estimates for the age group 5-29 because of insufficient data.

Figure 8 – Mortality Cases Due to OAP, Grouped According to Working and Non-working Age Groups, 2003


Relative Risks Health Outcome Metro

Manila Urban Rural

Attributable Fractions (National)

Respiratory Mortality, under 5 1.10006 1.03980 1.00000 0.03058 Cardiopulmonary Mortality, older than 30 1.31085 1.13199 1.00000 0.08431 Lung Cancer, older than 30 1.49940 1.20386 1.00000 0.12683

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Table 7 – Mortality Cases due to OAP, by Specific Age Group, 2003

Lung Cancer Cardiopulmonary Diseases (including respiratory diseases )11

Younger than 1 0 199Age 1 to 4 0 194Age 5 to 14 0 0Age 15 to 19 0 0Age 20 to 29 0 0Age 30 to 64 498 5,09065 and older 413 8,956Not Reported 0 17Total 911 14,456


The computations show that in 2003, the total loss in productivity (Figure 9) due to premature deaths resulting from illnesses caused by outdoor air pollution reached close to PhP 4.5 billion (USD 82.7 million) or PhP 60.0 billion (USD 1.1 billion) in terms of VSL. These figures were calculated based on pre-computed attributable fractions and applied to the total prevalence of each cause of death. The breakdown of the cost of premature deaths (using HCVand VSL (in parentheses)) is indicated in the bar-graph below (Figure 9):

11 This is listed as: cancer of trachea, bronchus and lung; Hypertension with and without heart involvement; Angina pectoris, Other forms of ischaemic heart disease; Acute myocardial infarction; Disease of pulmonary circulation and other forms of heart disease; Complications and ill-defined description of heart disease; Cerebrovascular disease; aterosclerosis; Acute upper respiratory infections; Influenza; Pneumonia; Acute bronchitis and bronchiolitis; Chronic obstructive pulmonary disease and allied conditions; Pneumoconioses and chemical effects; Pneumonitis due to solids and liquids; Other diseases of respiratory system

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Figure 9 - Cost of Premature Deaths due to OAP, 2003

Source: Author’s calculations. The Value of Statistical Life (VSL) estimates are in parentheses. Suggested Interventions

Mohanty et al (2004) concluded that particulate matter levels are influenced by several factors namely: “vehicle and fuel characteristics, fleet characteristics and operating characteristics”. Similarly, the PEM (2007) reported that the bulk of the total quantity of particulate matter in Metro Manila (84 percent) is from mobile sources. The data shows that the volume of vehicles that are added yearly into the highways and roads in country is rising as can be concluded from Figure 10 below. The growth of the number of vehicles every year has been steady at an average of 12 percent per year, or roughly 50,000 new vehicles each year.

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Figure 10 – New Vehicle Registration (New and Used vehicles) Trend, 2007

Source: Land Transportation Office (www.lto.gov.ph/stats.html)

It becomes apparent therefore, that one of the necessary interventions in order to limit PM emissions (and lessen the number of cases of OAP-related illnesses and premature deaths) must include vehicle management. This is not to diminish the importance of stationary sources management to lessen PM emissions, but merely to highlight a choice in policy interventions based on greater urgency.

Inspection and maintenance (I/M) programs

A well functioning inspection and maintenance (I/M) program is one of the most cost effective interventions in abating outdoor air pollution. Vehicle inspection in particular strengthens the enforcement of emission standards as well as increases in the demand for vehicle repair and maintenance (Kojima and Lovei, 2001). Subida, et al (2005) report that for Metro Manila, maintenance of vehicles and inspection system (MVIS) is one of the more effective interventions they have examined.

The implementation of an effective I/M program is not without cost as it entails specific activities to make it work. Gwilliam, et al (2005) conclude that an I/M program must be able to target gross polluters, which requires an examination of the characteristics of the vehicle fleet. The program therefore requires superior management and technical backstopping. All of these necessitate that a successful I/M program an investment on training and regular data collection. In addition, the I/M program must be complemented by laws and checks and balance to ensure that it is not tainted by corruption and politicking. Like any program, corruption and politicking would weaken the enforcement of any of the I/M program’s policies, and will surely result in an eventual breakdown.

A review of the existing initiatives in the Philippines that address outdoor air pollution indicates that positive steps have been taken. Indeed, there have been marked

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declines in the PM levels in Metro Manila despite the increasing number of vehicles in the region. This is attributed mainly to the government’s phase out of leaded gasoline which has been successfully implemented. In addition, the emission standards were tightened to comply with Euro 2 standards. The government also continues to review and revise the allowable emission limits for vehicles equipped with compression ignition and spark ignition. This should significantly limit increases in particulate matter levels from the mobile sources.

Currently, the country also has an existing Motor Vehicle Inspection System (MVIS) which requires motor vehicles to pass emission testing prior to registration. Emission testing is performed either by private emission testing centers (PETCs) or by the LTO. For private vehicles, there are over 300 PETCs all over the country that conduct the emission testing while for public utility vehicles, the LTO MVIS is offering emission testing services at lower costs (EMB-DENR, 2005).

The Philippines also has an existing smoke belching program that was established to enforce motor vehicle emission standards through roadside inspection and apprehension of violators. Teams which were trained by a multi-agency group led by MMDA and LTO implements the initiative (EMB-DENR, 2003). On the ground, this program could be improved with solid support from the local government units. Local ordinances, capacity building, and roadside apprehension are best handled by the municipal and city governments.

The benefit-transfer BCA of an inspection and maintenance program for diesel vehicles done for the Philippines by Larsen (2008) reflects a B-C ratio of 3.9. This indicates that in terms of health benefits (averted loss in human lives), sound maintenance and inspection program delivers almost four times the cost of implementing such a program. This supports conventional wisdom regarding the need for sufficient and effective vehicle emission monitoring and regulation to address air pollution from mobile sources. From two-stroke tricycles to four-stroke tricycles

The popularity of the two-stroke tricycles in the country is a major concern, air pollution-wise. Many motorcycle-drivers prefer the two-stroke over its four-stroke counterpart because they are more powerful, and often times less expensive. Tricycles—which oftentimes are two-stroke, and a very popular mode of public transportation—are ubiquitous and will most likely remain popular in generations to come. The social cost of using two-stroke tricycles, however, remains unaddressed satisfactorily. Aside from the noise pollution they create, a significant volume of particulate matter is from these two-stroke tricycles. The challenge is how to approach this emission problem and create an incentive system to entice two-stroke drivers and owners to switch to less polluting modes of transportation, or at the very least, to properly maintain their motorcycles and reduce emissions. With barely minimum wage, the tricycle drivers do not have enough money for tricycle maintenance. There is also very little incentive to conduct maintenance operations since most tricycle drivers do not own the units they drive. More often than not, an operator owns the tricycle units and a single unit is being shared by three to four drivers (Camagay, et al, 2005).

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The social benefit of the switch is potentially large. In the strategy scenarios evaluated by Subida et al (2005), switching from the two-stroke to the four stroke tricycles (4-STC) under several assumptions will result in an 80 percent reduction in PM emissions from these vehicles. Realistically, however, switching from 2-stroke to 4-stroke tricycles for the Philippines is very difficult, although not impossible. The biggest issue is cost, not just in terms of providing the funds to help finance the switch, but also to promote the acceptability of the program among the citizens by providing information and awareness. In the short-run, the government can do a bit more drastic action by, for example, banning the introduction of new two-stroke tricycles into the system while providing inspection and maintenance services to the existing two-stroke tricycles. Owners of “retiring” two-stroke vehicles should also be encouraged to make the switch; but this entails financing. As an example, the city government of San Fernando in La Union offered a loan package to encourage the shift from two-stroke tricycles to 4-STCs. Tricycle operators were offered an interest-free loan amounting to P9,000 payable within one year for the down payment on the purchase of 4-STCs. Old two-stroke tricycles with age ranging from 20 years old and above were phased out (San Fernando City Government, undated). As of July 2005, a total of 643 two-stroke units were converted into 4-strokes, of which 97 units received financial assistance (Ortega, undated). Installation of pollution control devices

Larsen (2008) used benefit-transfer to determine if retro-fitting of in-use diesel vehicles with diesel oxidation catalysts (DOC) or diesel particulate filters (DPF) makes economic sense for the Philippines12 (Refer to Annex 2 for the complete paper). Using the experience of Mexico, Peru, and Senegal as the basis for the analysis, the benefit-cost analysis indicates that the benefits (in terms of the economic values of averted premature deaths calculated using VSL) of a retro-fitting program more than outweigh the average costs of adopting the technologies for diesel vehicles. A summary of the BCA results for retro-fitting of in-use diesel vehicles in the Philippines is shown below13:

12 Effective functioning of DOCs and DPFs requires diesel with a maximum sulfur content of 500 and 50 ppm, respectively. 13 Larsen applies a VSL of US$109,000 to the Philippines (reflecting GNI per capita in 2007) for valuation of mortality.

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Table 8 - BCA-ratios for Cases of Retro-fitting of In-use Diesel Vehicles in the Philippines

Diesel Oxidation Catalysts (DOC) BCA RatioOld buses 6.54 Large buses 6.74 Buses 4.12 Newer buses 2.97 Old delivery trucks 2.23 Newer delivery trucks 1.81 Diesel Particulate Filters (DPF) High usage taxis 5.30 Old buses 2.80 Large buses 2.89 Newer buses and delivery trucks 1.47

Source: Larsen, 2008.

Vehicle emission technologies are useful short term interventions while the country is building capacity, awareness and adoption of cleaner fuels. As such, a national program that requires vehicles (new and in-use), especially public utility vehicles such as the jeeps, buses and tricycles—to install pollution control devices must be implemented.

There are several pollution control devices being offered in the market today. Kojima and Lovei (2001) note that for gasoline powered vehicles, catalytic converters are the most effective in reducing exhaust emissions. As much as 95% reduction in CO and hydrocarbon emissions and around 75% NOx reduction can be achieved if the three-way catalytic converters are efficiently used. However, according to Kojima and Lovei (2001), there are several pre-requisites for this option to work successfully: wide use of unleaded gasoline; low sulfur level in gasoline; emission standards and adjustment period to meet these standards; and effective I/M programs. Along with improvement in fuel specifications, particulate traps or filters can also be used for diesel powered engines. Buses and jeepneys can be fitted with particulate traps to reduce emissions.

Cost is one of the main concerns regarding the implementation of this intervention. Vehicle emission technologies entail additional costs to vehicle owners. Moreover, given certain technologies, lower emissions come at the price of fuel efficiency making installation of emission technologies even more costly. While newer vehicle imports come with installed catalytic converters, the problem lies with older vehicles (Gwilliam, et al., 2005). One way to encourage owners of vehicles (especially the old units) to install pollution control devices is to strictly implement compliance with emission standards. If emission standards are being strictly enforced through a well functioning I/M system, vehicles owners are left with no choice but to install pollution control devices to avoid apprehension or the risk of the vehicle units not being registered.

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In addition, the government can remove the barriers that prevent the entry of anti-pollution technologies or impose lower tariffs (if not zero) on the importation of emission technologies to help ease the price in the domestic market (Kojima and Lovei, 2001).

Rehabilitation of Current Traffic Management System

Traffic congestion is a ubiquitous phenomenon in the major cities in the Philippines. The length of time a vehicle is on the road is the most significant factor in the contribution of the vehicle to particulate matter emission. As such, the minimization of traffic in the country will improve the level of particulate matter released by vehicle combustion in the air. The current traffic management system in the Philippines has improved the traffic situation in the country—especially in Metro Manila—but additional efforts are needed to completely eliminate regular traffic congestion in the major cities. To illustrate the potential of traffic management, a study conducted in Bangkok and Kuala Lumpur in 2004 revealed that the reduction in emissions from the installation of 3-way catalytic converters in 50% of the cars in these cities can be achieved by increasing vehicle speed from 12-15 km per hour to 30 km per hour (Kojima and Lovei, 2001).

Strategies that can greatly improve flow of traffic include the following: coordinated signals/traffic lights, channelization, reversible lanes, one-way street pairs, and other traffic control device, area licensing schemes, parking controls, exclusive pedestrian zones, vehicle bans (Faiz, et. al, 1990); and segregated busways (Gwilliam, et. al, 2005).

Potential of traffic management in reducing pollution is no doubt very effective in the short run but caution should be exercised in the long run. Reduced travel time encourages more trips and thus translates into higher emissions. For example, after increasing capacity of road networks in United Kingdom and United States additional traffic was generated. About half of the 2.7 percent growth in traffic in the US can be attributed to the additional roads that were constructed. Traffic management is only effective to the extent that it does not create additional traffic. When it does, policies to redirect traffic flow, especially away from environmentally sensitive locations should be enforced (Kojima and Lovei, 2001). Investments in Additional Mass Transport System

Investments in additional mass transport systems such as additional electric trains will significantly reduce the public’s reliance on jeepneys and tricycles which are notorious for outdoor air pollution emissions. Currently, there are three light rail transit lines in operation/available in Metro Manila, which service the population of the metropolis daily as described below in Table 9:

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Table 9 - Light Rail Transits Lines in the Philippines Length/Ridership LRT Line 1 15-km line / 300,000 passengers per day LRT Line 2 13-km / 200,000 passengers per day EDSA-MRT 17-km / 400,000 passengers per day Source: ADB, 2006.

A number of authors have suggested the use of trains and railways as an effective strategy combating air pollution (Gwilliam, et al., 2005; Ostro, 2004; Kojima and Lovei, 2001; Subida, et al., 2005). By expanding the railway network, it is expected that the number of commuters using the LRT/MRT will increase. With a larger number of the population using non-motorized transport, volume of traffic will be reduced and thus help in lessening outdoor air pollution. The projections made by Subida, et al (2005) show that in 2015 (under several assumptions), the use of metro railways will generate 18.2 percent and 13 percent reduction in SPM and CO2 emissions respectively. The costs of this intervention, on the other hand, are summarized below in Table 10: Table 10 - Proposed Railway Projects with project costs (in USD millions) Railway Line

Route Distance (km)

Fixed Cost Variable Cost (Operating and Maintenance)

TOTAL

LRT line 6 South extension of line 1

30 km 600 750 1,350

MRT line 3 extension

North Ave-Navotas; Taft-Reclamation

12 km 306 261 567

MRT line 2 (east west extension)

Recto-North harbor; Santolan-Masinag

15.7 km 351 182 533

MRT line 2 Masinag-Antipolo 22.8 km 288 150 438 MRT line 4 Recto-Novaliches 26 km 724 646 1370 North Rail PNR line 45.5 km 589 649 1238 MCX PNR Line 554 996 1550 Total Cost 3,412 3,634 7,046 Source: JICA in Subida, et al, 2005.

However, there are several issues that need to be addressed when implementing this intervention. First, MRT and LRT operations are financed heavily by government subsidies. The Inquirer reported that MRT for example receives approximately P6.8

29

billion subsidies per year. This put a lot of pressure on the fiscal position of the government. Therefore, to prevent perverse use of subsidies, great caution should be exercised during project conceptualization and contract design. For the proposed railway projects, the government should avoid taking on risks beyond its control to prevent incurring huge amount of contingent liabilities.

Second issue is the setting of fare rates. In theory, the fare rate should reflect the true costs of service being provided. However, this is not a viable option in practice for several reasons: political and demand elasticity considerations.

Focusing on the MRT, the fare rate has been set very low, revenues from which are not enough to cover the operating expenses. Table 11 shows the financial summary of MRT Line 3 Operations. Table 11 - Financial Summary of MRT Line 3 Operations (in million pesos) CY 2003 CY 2004 CY 2005 Total Expenses 6,500.00 6,700.00 8,000.00 Revenues Development Rights revenues Farebox revenues

1,600.00 12percent 88percent



Amount being subsidized by the Government per passenger

P44.23 $0.88

P39.94 $0.8

P49.57 $0.99

Total Ridership 112,653,067 122,483,642 121,753,952 Source: Morales-Mariano (http://www.cleanairnet.org/baq2006/1757/docs/SW7_2.ppt)

In order to make the operation of an additional MRT feasible, it would be necessary to increase the current fare and reduce the subsidy that the government pays to keep it afloat. Morales-Mariano (http://www.cleanairnet.org/baq2006/1757/docs/SW7_2.ppt) suggested that the optimal fare rate is around PhP 14.40-19.90. The average optimal fare of P17.15 generates the lowest subsidy required (PhP 6.449 billion). Increasing the fare to an average of P17.15 will not result to increase traffic volume and road congestion. However, beyond this amount, revenues will begin to decrease as 52 percent of the passengers will shift to buses and around 2 percent will shift to cars.

Martinez and Tolentino (2007) estimated the optimal fare using a sensitivity analysis. Their study revealed that the optimal fare is around PhP18.15 in 2007. This fare rate maximizes farebox revenues and minimizes the subsidy. Beyond this amount, subsidies begin to increase as revenues fall. It is expected that there will be opposition against building another MRT that will be subsidized heavily by government, especially if the subsidy is substantial. Without the subsidy, however, the MRT fare would be more expensive than the jeepneys and buses that ply the same route, dampening the impact of the expansion of the electric train on the particulate matter emission. Additional studies must therefore be done to find a solution to the fare increase problem.

Finally, a summary of activities related to reducing outdoor air pollution was done by the Metro Manila Air Quality Improvement Sector Development Program

30

(MMAQISDP) in 2003. These figures were inflated to reflect the current costs of creating the same projects, as shown below in Table 12:

Table 12 - Cost Estimates for the Metro Manila Air Quality Improvement Sector Development Program (MMAQISDP) in million USD

2003 Prices 2007 Prices Item FE LC Total FE LC Total

Road Rehabilitation 19.52 19.52 39.04 28.13506 28.13506 56.2701Traffic Engineering Management 9.01 11.64 20.65 12.98652 16.77726 29.7638Ambient Air Quality Management 10.59 1.96 12.55 15.26385 2.825037 18.0889Public Health Monitoring 0.15 0.01 0.16 0.216202 0.014413 0.23062Anti-smoke Belching 0.5 0.05 0.55 0.720673 0.072067 0.79274Capacity Building 7.46 5.36 12.82 10.75244 7.72561 18.478Consulting 6.06 5.06 11.12 8.734552 7.293207 16.0278Program Administration 4.61 4.61 0 6.644601 6.6446Contingencies 6.43 6.52 12.95 9.26785 9.397571 18.6654Interest and Other Charges 7.86 7.86 11.32897 0 11.329 TOTAL 67.58 54.73 122.31 97.40611 78.88482 176.291Note: FE- foreign exchange; LC- local currency

Source: 2002 National Air Quality Status Report. The 2007 prices are the author’s own computation given annual inflation rate and exchange rate data from BSP and the 2003 data from the 2002 National Air Quality Status Report.


The WHO estimates indoor air pollution as the 8th most significant risk factor in the global burden of diseases. It contributes around 3.7 percent of the disease burden in developing countries and ranks fourth behind malnutrition, unprotected sex, and water, sanitation and hygiene, as the main causes of premature deaths (WHO websites: http://www.who.int/ indoorair/health_impacts/burden_global/en/index.html; http://www.who.int/mediacentre/factsheets/fs292/en/).

Indoor air pollution-related illnesses result from both short and long-term exposure to smoke inside the home—smoke that originates from cooking with solid fuels, cigarette smoking and other sources. In this study, however, the focus in is only on households’ solid fuel use as the source of indoor air pollution. The choice of solid fuel use as the basis of the analysis is borne of the practical consideration—the data are available on solid fuel use, but no sufficient data on cigarette smoking inside the home—

31

and the appropriateness and rationale for intervention. The WHO reports that the impact of indoor air pollution (from solid fuel use for cooking) on individuals’ health is significant, causing an estimated 1.6 million deaths globally due to respiratory diseases and lung cancer.

Public health specialists who were interviewed for this report believe that cigarette smoke is the largest contributor to indoor air pollution; even as they acknowledge that smoke from cooking fuel is a significant source of IAP as well. There is no sufficient data on cigarette smoking—i.e., epidemiological studies that estimated the relative risk ratios for cigarette smoking in the Philippines—in the household to conduct an economic analysis. As such, this study is limited to analyzing the impacts of exposure to smoke from fuel used for cooking even as the author acknowledges the importance of cigarette smoke on the deterioration of human health in the Philippines14. But despite the idea that solid fuel is only secondary to cigarette smoke as the sources of indoor air pollution, its impact on health and life is huge. It is expected, however, that as more data become available (particularly, technical and household data on the impacts of exposure to cigarette smoking in the homes) that these valuations will be revised to include these information.

We begin the formal discussion by characterizing solid fuels—at least based on how it is defined in this report. Desai, et al. (2004) defines solid fuel use as “the household consumption of biomass (dung, charcoal, wood, or crop residues), or coal.” Results of the 2004 Household Energy Consumption Survey (HECS) show that the percentage of households using electricity and LPG increased from 1995 to 2004 while the percentage of household using fuelwood, charcoal, kerosene and other biomass fuels declined as illustrated in Figure 11 below: Figure 11 – Percentage of Households Use of the Type of Cooking Fuel, 2004

0

25

50

75

100

Electricity LPG Gasoline Diesel Kerosene Fuelwood Charcoal OtherBiomassResidue

1995 2004

Source: Household Energy Consumption Survey, 2004

14 Another limitation of the study is that it does not include the incidence of IAP-related illnesses in the workplace. The focus of this section is solely on the household members’ exposure to smoke from cooking, which in turn is based on the use of cooking fuel, cooking practices and ventilation of the home.

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The literature on indoor air pollution suggests that the bulk of the environmental burden of disease due to solid fuel is borne by low-income households in rural and peri-urban areas—sectors that typically have inadequate access to clean and affordable fuels. The results of the 1995 HECS presented in Figure 12 show that solid fuel use is indeed high in rural areas. The 2004 HECS data however, do not include a classification of households according to urbanity, but nevertheless supports the claim that a big portion of poor households use solid fuel such as wood, charcoal and other biomass residue (Figure 13). Additional information is needed to verify if it is the rural poor or the urban poor that is exposed to air pollutants from solid fuel use. Anecdotal evidence, however, point to the incidence of solid fuel use to be higher in the rural areas this is the traditional use of fuel in the rural sector, and this is also the cheapest and most accessible cooking fuel available.

Figure 12 – Household Fuel Use by Urbanity, 1995

Household Fuel Use, By Urbanity, 1995

0%

25%

50%

75%

100%

Electricity LPG Gasoline Diesel Kerosene Fuelwood Charcoal BiomassResidues

Perc

en

tag

e o

f h

ou

seh

old

s

PhilippinesUrbanRural

Source: Household Energy Consumption Survey, 1995.

33

Figure 13 – Household Use of Solid Fuel by Income Class, 2004

0% 25% 50% 75% 100%

Less than PhP5,000

PhP5,000-9,999

PhP10,000-14,999

PhP15,000-24,999

PhP25,000 and over

Fuelwood Charcoal Other Biomass Residue

Source: Household Energy Consumption Survey (HECS), 2004.

The data on PM emissions from solid fuel use is wanting in the Philippines. One major source is the ADB (2004) which looked at the indoor PM10 levels in rural and urban households. It did not have, however, a definitive conclusion on the sources of PM levels within the household. It is also difficult to assess without additional analysis if the PM levels found inside homes are from the “trans-boundary” movements of fumes from outdoor air pollution sources.

Based on the available information reviewed for this report, it is hard to make a definitive conclusion on indoor air PM levels especially since the sites included in the studies are few—the data collection on the PM10 levels from the indoor sources are done regularly but not at the ideal level of frequency. Some deductive results, however, can be made and used to paint a general picture of the link between solid fuel use and exposure to particulate matter. Using data from HECS and combined with emission factors collected from the different technical literature available, an estimate of PM emissions from solid fuel use of households is calculated. Table 13 summarizes these calculations.

Table 13 – Particulate Emissions from Household Cooking, 2004

Fuel Type 2004 Consumption PM Emission Factor

Total PM Emissions

Fuelwood 10.694 M tons 15.30 g/kg 163,618 tonsCharcoal 0.888 M tons 36 mg/kg 32 tonsBiomass Residues 1.351 M tons 7.40 g/kg 9,997 tons Source: Author’s estimates based on HECS data.

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Most health outcomes that have been associated with exposure to indoor air pollution have been limited to children younger than 5, women older than 30, and to some extent, men older than 30. This trend is borne of the fact that the individuals who belong to these age groups are the most likely to spend the most time inside the home. With this information at the forefront, particular attention to young children and adult women is given, since they are the people most likely to suffer from illnesses caused by indoor air pollution. The estimates done on the number of cases of IAP-related illnesses support this conclusion, as the discussion in this section will illustrate later.

To start off the discussion, this study looks at the existing data on household fuel use, and found that 42 percent of households in the Philippines use fuel wood as their primary cooking fuel (Figure 14). To calculate the population that has been exposed to indoor air pollution, we first exclude from the households that used any of the three solid fuels of interest in 2004, but used other energy sources as their primary cooking fuel a year prior to the actual survey. Figure 15 shows that a little more than 48 percent of the households in the country are exposed to indoor air pollution, based on solid fuels used as the primary cooking fuel. As expected, the proportion is much higher in the rural areas where cooking using biomass and fuel wood, is the traditional and practical method—solid fuel is easily accessible and cheaper in the rural areas than LPG and other cooking fuel. Figure 14– Primary Cooking Fuel for Households, 2004

LPG42.7%

Kerosene4.8%

Fuelwood42.0%

Charcoal7.2%

Others2.1%

Electricity1.3%

Source: Household Energy Consumption Survey (HECS), 2004.

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Figure 15 – Households Exposed to Indoor Air Pollution (in percentage)

Source: Author’s estimates based on HECS data.

The numbers in Figure 15 illustrate the prevalence of the use of solid fuel in rural areas, and that a relatively small proportion of households in Metro Manila can be considered exposed to indoor air pollution. However, there is a need to adjust these figures by the associated ventilation factors because cooking practices and the structural characteristics of houses in the Philippines may mitigate the exposure of Filipino households to indoor air pollution and the subsequent health outcomes. Desai, et al. (2004) suggest using a ventilation factor of 0.25 for households that use improved stoves or cook outside, and a ventilation factor of 1.00 for those that use traditional stoves. A ventilation factor of 0.25 means that the health effects of indoor air pollution emanating from cooking fuel are expected to be reduced by three quarters as result of the ventilation conditions. Saksena et al. (2005) summarized these mitigating ventilation conditions to be based on a variety of factors including the distance of rooms and walls, height of ceiling, size of windows, materials used to build the house, and whether the household uses improved stoves or not. Taking into account the “airiness” of the areas where cooking is done even if the stoves were traditional, a ventilation factor of 0.25 is used for urban and rural areas outside Metro Manila as households in these areas typically do their cooking outside their houses. Metro Manila households that use solid fuel, however, are assigned a ventilation factor of 0.5 since they would normally be found in informal settlements where houses are crammed together.

With the above assumptions, the proportion of the cases of the health outcomes outlined above that can be attributed to exposure to indoor air pollution is computed. To accomplish this, attributable factors were estimated based on the relative risk ratios—calculated based on gender, age, and specific illness—obtained from several

36

epidemiological studies are used. The pollutant in discussion is PM resulting from the smoke from solid fuel use in the households. Adjustments on the potency of exposure to smoke are made by integrating the (significant) impact of household ventilation on the degree of exposure. The computed weighted-AFs for each health endpoint used in this study are summarized in Table 14.

Table 14 – Attributable Fractions Used for Morbidity Cases per Illness

Health Endpoint Risk

RatiosVentilation

Factor Attributable

Fractions Acute lower respiratory infections, children younger than 5 and women older than 30.

1.8 0.25 0.1009

Chronic obstructive pulmonary diseases, women >= 30

3.2 0.25 0.2359

Chronic obstructive pulmonary diseases, men >= 30

1.8 0.25 0.1009

Tuberculosis, all >= 15 1.5 0.25 0.0656

Sources: AFs calculated by author, based on risk ratios from Desai, et al (2004) and Dherani et al (2008).

The results of the calculations for morbidity cases are shown in Figure 16. Table 15 shows in more detail the number of cases of acute bronchitis, ALRI and pneumonia, COPD and respiratory tuberculosis, given the different age groups. It must be emphasized that the estimates of cases (as well as the inclusion of the specific diseases) were based on the available data on relative risk ratios (and the consequent computation for attributable fractions) and on the total number of cases of each of the diseases. Figure 16 – Morbidity Cases Attributable to IAP, By Gender, 2003

Source: Author’s calculations. COPD refers to chronic obstructive pulmonary disease.

37

Table 15 - Cases of IAP-related Illnesses by Age Group, 2003

Acute Bronchitis

ALRI and Pneumonia COPD Tuberculosis

Age 0 to 4 101,949 289,753 0 0Age 5 to 14 0 0 0 0Age 15 to 19 0 0 0 716Age 20 to 29 0 0 0 1,173Age 30 to 64 18,630 22,842 2,670 3,60465 and older 4,900 8,839 1,558 1,139TOTAL 125,479 321,434 4,228 6,631


The Economic Costs of IAP-related Morbidity

As with the calculations for the economic costs of OAP, the estimates for the costs to society and the economy of indoor air pollution related illnesses include direct costs to households (based on treatment-seeking behavior) and the indirect costs (lost income due to days off from work due to illness). The estimates of economic burden include the cost to the government health care system in terms of subsidy to PhilHealth members’ medical costs15 and the per-patient hospitalization subsidy for government-owned hospitals. Figure 17 illustrates the direct treatment costs to households for the indoor air pollution-related illnesses in 2003, while Figure 18 describes the costs that are shouldered by the government.

15 It must be noted that only 70 percent of cases in Metro Manila and in urban areas, and 20 percent of cases in rural areas, are subsidized by the government through PhilHealth. The PhilHealth also indicated that only (an average of) 35 percent of costs incurred by its members are paid by the agency.

38

Figure 17 – IAP Cost to Households of Treatment (Net of Public Health Care Subsidy), 2003


89%

Respiratory Tuberculosis

PhP 19 M4%

COPDPhP 13 M

3%


4%

Source: Author’s calculations. Figure 18 - Government Health Care Subsidy per IAP-Illness, 2003


93%


PhP 6 M3%

COPDPhP 5 M

3%

Acute Bronchitis

PhP 2 M1%

Source: Author’s calculations.

It is also estimated that the Philippine economy loses the productive contribution of working-age patients when they take time off to get treatment, or to take care of a sick child. Lost productivity resulting from IAP-related illnesses is calculated based on the 2003 per capita GNI of the Philippines, with the figures adjusted for stay-at-home

39

mothers. Figure 19 illustrates the computed indirect costs from the diseases mentioned above.

Figure 19 – Lost Income Due to IAP-related Illnesses, 2003


55%


PhP 33 M9%


14%

COPDPhP 79 M

22% Source: Author’s calculations.

Total foregone income due to indoor air pollution amounted to PhP 360 million

(USD 6.6 million) in 2003, a significant amount for a country like the Philippines, especially if we consider the fact that majority of these cases occurred in the rural areas where most of the poor reside. In total (treatment cost and foregone income and time losses), the calculations show that IAP-related illnesses cost the Philippine economy in 2003 a total of PhP 1.0 billion (USD 19.0 million) in morbidity costs (Figure 20). Figure 20 – Total Economic Cost of IAP-related Morbidity, 2003


77%


PhP 56 M5%

COPDPhP 114 M

11%


7%


40

Figure 20 also provides insights as to which diseases are more likely have the most economic impacts as a consequence of IAP. This should be used as the basis for any mitigation and adaptation strategies of policy managers. Economic Costs of Premature Deaths due to IAP

This study used the AFs calculated for morbidity cases to estimate mortality from IAP. A summary of the AFs calculated used to calculate the cases of premature deaths from IAP-related illnesses is shown in Table 16. The details of the adjustments are contained in Annex 1. The total number of mortality cases was calculated using the mortality data from the Philippine Health Statistics (PHS) as base figure. The PHS base data were adjusted by 2.42 (based on WHO estimates) for children under 5 five years old and 1.05 for the other age groups. This was done in consideration of the fact that reporting of deaths in the Philippines is understated.

Table 16 – Attributable Fractions Used for Mortality Cases per Illness

Health Endpoint Risk

RatiosVentilation

Factor Attributable

Fractions Acute lower respiratory infections, children younger than 5. 1.8 0.25 0.1009Chronic obstructive pulmonary diseases, women >= 30 3.2 0.25 0.2359Chronic obstructive pulmonary diseases, men >= 30 1.8 0.25 0.1009Lung cancer (from exposure to biomass smoke), women >=30 1.5 0.25 0.0656Tuberculosis, all >= 15 1.5 0.25 0.0656

Source: AFs are the author’s estimates based on RR’s from Desai, et al (2004) and B. Larsen (2008).

It is estimated that premature deaths accruing to IAP-related causes cost the Philippine economy PhP 3.7 billion (USD 68.0 million) in lost productivity, or PhP 23.6 billion (USD 434.7 million) when VSL is used for valuation of mortality. These results are detailed in Figure 21 below, wherein each illness considered for this section is shown. NOTE: According to your summary table at the beginning of the report, this VSL usd figure seems to be both mortality and morbidity. Please check.

41

Figure 21 - Cost of Premature Deaths due to IAP, 2003 (HCV)

PhP 927 M(PhP 6.8 B)

PhP 38 M(PhP 463 M)

PhP 2.1 B(PhP 5.0 B)

PhP 20 M(PhP 48 M)

PhP 613 M(PhP 10.2 B)

0

500

1,000

1,500

2,000

2,500

Tuberculosis Lung Cancer Pneumonia Acute Bronchitis COPD

Source: Author’s calculations. The figures in parentheses are VSL estimates.

The data also show that the most productive members of society (age group 20-64 years old) comprise a significant share of the deaths (34 percent of 5,772 premature deaths) related to IAP, as shown in Figure 21 and Table 17. An alarming observation that can also be made from the result is the high number of cases of children who died in 2003 due to IAP-related pneumonia. Since pneumonia is generally treatable and non-fatal if addressed properly, the high number of cases suggests that many cases of pneumonia are either dismissed by parents as “nothing to worry about”, or, more likely, treatment is inaccessible because of poverty or distance from health service providers. Additional information is needed to verify if these hypotheses are correct, but the response to this issue from policy makers is vital. Figure 22 – Mortality Cases Due to IAP Grouped According to Working and Non-working Age Groups, 2003

Source: Author’s calculations based on Philippine labor data.

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Table 17 - Mortality Cases Due to IAP by Specific Age Group, 2003


Lung Cancer Pneumonia Acute

Bronchitis COPD

Younger than 1 0 0 645 9 0Age 1 to 4 0 0 629 3 0Age 5 to 14 0 0 0 0 0Age 15 to 19 19 0 0 0 0Age 20 to 29 82 0 0 0 0Age 30 to 64 937 59 0 0 89465 and older 707 60 0 0 1,725Not Reported 2 0 0 0 1Total 1,745 119 1,273 12 2,620

Source: Author’s calculations. The number of mortality cases for age groups 30 and older was also not estimated because of the insufficiency of information.

Another significant result is that the highest number of cases of deaths from COPD due to indoor air pollution is among the elderly—double the number of COPD cases among the working-age group. Additional information, however, is needed to verify if the number of cases is purely due to exposure to indoor air pollutants, or if there are mitigating circumstances that have made the elderly more vulnerable to fatal cases of COPD. The working-age adults, on the other hand, suffer mostly from IAP-related respiratory tuberculosis—an illness which is pathological, unlike the other illnesses in discussion which are primarily due to exposure to particulate matter. This is explained by the fact that since the cause of the IAP-related illnesses included in this study is long term exposure to solid fuel from cooking, the exposed population is majority composed of the non-working age groups who are at home and potentially exposed to smoke from cooking. It must be noted that occupational exposure—a significant factor in IAP-related illnesses, according to public health experts—is also not included in the analysis due to insufficiency of epidemiological data.

Suggested Interventions

Since the analysis on indoor air pollution impacts centers solely on the solid fuel

use, the suggested interventions in this section address the exposure to the smoke from solid fuel that is generated from the home. These interventions are therefore limited to three basic groups: improvement of ventilation, change in cooking practices, or change of the kind of stoves used in the home.

43

Promoting improved household living environment

Household living environment (i.e. house structure, room layout) is one of the most important factors affecting the level of exposure of a household to indoor air pollution. House lay out design greatly affects the concentration and distribution of pollutants inside the homes. There are significant differences in pollutant concentration based on the location of cooking areas and kitchen (Zhang and Smith, undated; Jin et al 2005; and Qin, et al ,1991). It is apparent, therefore, that a simple but logical solution to the issue of indoor air pollution inhalation is to have an outside kitchen. This is not always possible, however, because of the costs. Since most of the users of solid fuel belong to the poor with very small dwellings, to have a separate kitchen for cooking is not an option for the very poor.

There are other ways to increase ventilation without being too costly or inconvenient. These include “increasing the number of windows/openings in the kitchen, providing gaps between the roof and the walls, or moving the stove out of the living area” (Desai, et al 2004). Remarkable benefits from a “cooking window” or a “fume cupboard” have been noted by Nystrom (as cited in WHO, 2000). The usefulness of hoods with flues, enlarging and repositioning windows and enlarging eaves in rural Kenya has been studied. These interventions (especially the use of hoods) which have been developed with the participation of local women were very effective in reducing pollution and personal exposure to harmful pollutants (WHO, 2000). In order to promote the adoption of these interventions among the target households, an information drive—a campaign to inform, educate and communicate to the target sector—about these alternatives must be communicated to the households. If done correctly, this could change the behavior of household members regarding indoor cooking and the use of solid fuel.

It must be emphasized that behavior change is the key element in the adoption of the interventions. To motivate people to adopt certain technologies and to alter their behavior, the change must make sense to them; the benefits derived from these changes must be obvious to the target sectors.

Intervention in the form of marketing, advertising, and education come into play when influencing behavior. Education in particular is very important in conveying the value of cleaner kitchens and air to households and thus can help reduce the impact of indoor air pollution (Desai, et al., 2004). This intervention, however, needs careful planning as it must be accompanied by pricing strategy to make the alternative cooking technologies affordable for the target households. Promoting improved stoves

Studies on indoor air pollution exposure prevention have concluded that the use of improved stoves lessens exposure to indoor air pollution (Mehta and Shaphar, 2004). Others have highlighted the economic benefit that a household gains from using LPG or

44

kerosene. . Biomass stoves approximately costs USD 50-100 per DALY16 averted according to Smith (1998) while Hughes et al., (2001) estimated that introduction of kerosene or LPG stoves in rural areas costs around USD 150-200 per DALY averted.

There is empirical evidence and theoretic bases to the idea that households will only be enticed to switch technologies when their perceived benefits outweigh the costs of adoption of the new and better technology. While households can directly observe the reduction of emissions or greater fuel efficiency of improved stoves, the monetary value of these benefits are less apparent (Larson and Rosen, 2000). It is essential, therefore, to communicate this information to the target households clearly and in no uncertain terms through an information and education campaign. It could help if the community is engaged in designing an improve stove design and technology as this will facilitate familiarity of the target households with the proposed changes.

Choosing the correct stove to promote is therefore essential to the proposed intervention. As a guide, information from various sources on the cost effectiveness of improved stoves is presented in this section. Foremost among these is the study done by Hutton, et al (2006) which evaluated the cost and benefits of household energy and health interventions using data from 11 developing and middle-income WHO sub-regions. Net intervention costs include intervention costs less fuel savings while economic benefits include health benefits and savings on health care costs, productivity gains due to reduced morbidity, time savings and environmental benefits. The study assumed a 35 percent reduction in personal exposure based on Naeher, et al, (2000), Bruce et al, (2002), and Bruce et al, (2004) as proxy for the possible reductions in health outcomes. The estimate, however, is likely to be very conservative since the 35 percent reduction represents the average personal exposure of children in homes using open fires and not the cook’s (i.e. the mother’s) personal exposure. The “improved stove” referred to in this study is the chimneyless rocket stove (a type of stove used in Latin America, some parts of Asia, and Africa) which is relatively cheap—compared to other improved stoves available (approximately USD 6.0 acquisition cost per piece)—with an estimated useful life of 3 years (Hutton et al, 2006). Table 18 - Overview of Costs and Impacts, Time Horizon of Modeled Impacts Variable Immediate cost or impact Delayed cost or impact Intervention costs Investment costs, such as

stove purchase cost and cost of house alterations

Not applicable

Recurrent costs, such as fuel cost and programme costs

Health benefits and savings on health care costs

ALRI Lung Cancer

Chronic obstructive pulmonary disease (COPD)

16 WHO describes the DALY (disability-adjusted life year) as a time-based measure of burden of disease. With DALY, the number of years of life lost due to premature death is added to the years of life an individual lives in states of less than full health.

45

Productivity gains due to reduced morbidity

NA Related to acute lower respiratory infections (ALRI) for children, and to COPD and lung cancer for all age groups

Time savings Fuel collection time and cooking time

Not applicable

Environmental benefits Local and global environmental benefits

Not applicable

*Future costs and impacts are discounted at a 3 percent discount Source: Hutton et al, 2006

Larsen (2008) calculated benefit-cost ratios (See Annex 2) for programs that promote the conversion to improved wood stoves and LPG stoves from unimproved wood stoves:17

- Scenario I: Conversion to improved wood stove from unimproved wood

stove (with an assumption of a 50 percent reduction in health risks as a result of the conversion of households)

- Scenario II: Conversion to LPG from unimproved wood stove (with the assumption that the conversion will result in the elimination of all health risks from the use of solid fuel)

- Scenario III: Conversion to LPG from improved wood stove (with the assumption that the conversion will result in the elimination of all health risks from the use of solid fuel)

Table 19 - Benefit-Cost Ratios of Converting to a New Stove Technology to Control IAP in the Philippines.

Valuation Method VSL & COI HCV & COI

Ventilation factor (VF) VF=1 VF=0.25 VF=1 VF=0.25 Scenario I Improved wood stove (health benefits only) 14.5 5.02 3.08 1.00

Improved wood stove (health & time savings) 18.8 9.32 7.38 5.30

Scenario II LPG from unimproved stove (health benefits only) 2.03 0.70 0.43 0.14

17 Unimproved wood stoves refer to low fuel-efficiency wood stoves whose smoke is uncontrolled and directly emitted into the immediate environment. Improved stoves, on the other hand, are stoves with higher fuel-efficiency and have provisions to reduce immediate exposure to smoke.

46

LPG from unimproved stove (health & time savings) 2.63 1.30 1.03 0.74

LPG from unimproved stove (health & wood cost savings) 2.83 1.50 1.23 0.94

Scenario III LPG from improved stove (health benefits only) 1.02 0.35 0.21 0.07

LPG from improved stove (health & time savings) 1.32 0.65 0.52 0.37

LPG from improved stove (health & wood cost savings) 1.42 0.75 0.62 0.47

Source: Larsen (2008). Refer to Annex 2 for the complete paper.

Larsen’s results show that the intervention with the highest return in the Philippines per unit of cost will be the conversion of households from using unimproved stoves to improved stoves. This is primarily due to the fact that the conversion to improved stoves is less expensive than the conversion to LPG (even if the health benefits from switching from unimproved stoves to LPG are higher). This highlights the significance of the cost to switch to the new stove-technology as an important consideration in intervention efforts. Note that in the analysis, the calculations were adjusted by the associated ventilation factors (VFs) based on the assumptions regarding the cooking practices and structural characteristics of houses in the Philippines. Two VF-scenarios are assumed as suggested by the literature: 0.25 for households that use improved stoves or cook outdoor; and 1.0 for households that use traditional stoves. (See the Annex for further discussion on ventilation factors and the corresponding AFs).

There are several improved stoves being promoted in the Philippines. These include the Mayon Turbo Stove (advanced conical rice hull stove) developed by REAP Canada (Samson and Lem, undated), rice husk gas stove developed by Engr. Alexis T. Belonio (Belonio, 2005), and Maligaya rice hull stove developed by Philippine Rice Research Institute (PhilRice, 1995 ). Studies done on these stoves show significant reduction in smoke emitted. There is still, however, an insufficiency in data/documentation on how much reduction in PM, IAP exposure and risk can be associated with the use of these improved stoves. Currently, these stoves are being packaged and promoted as an intervention to reduce green house gas emissions because of their potential to decrease CO, CO2, N2O and CH4 emissions. By converting agricultural wastes like rice hull into fuel, agricultural waste burning is mitigated. In addition, these improved stoves are relatively fuel efficient than the traditional stoves being employed. However, availability of rice hull, the main source of fuel can be one limitation. Promotion and adoption of these stoves will only be successful in areas where sources of fuel are readily available. The rice husk gas stove, developed by Engr. Belonio needs electricity to run, which could limit its adoption. Thus, there is a need to further improve stove designs to make them flexible enough to suit local conditions—i.e. can run without electricity, can use agricultural wastes other than rice hull, and are easy to use compared to traditional stoves.

47

Water Pollution, Sanitation and Hygiene

There are seven water pollution, sanitation, and hygiene-related diseases that are examined in this report, namely: diarrhea, helminthiasis, schistosomiasis, typhoid and paratyphoid, cholera, and viral hepatitis (Hepatitis A). All of these diseases are pathogenic and are widely accepted as attributable to contaminated water and poor sanitation and hygiene.

The number of cases of the illnesses in discussion is examined according to the Philippine households’ access to clean water supply for sanitation and hygiene purposes; and described according to the category levels defined by the WHO based on the paper by Prüss-Üstün, et al. (2004). Table 20 below summarizes these levels with a description of each level as a quick reference: Table 20 – Levels of Households According to Access to Water and Sanitation Facilities

Level Description Environmental

fecal-oral pathogen load

VI Population not served with improved water supply and no improved sanitation in countries which are not extensively covered by those services (less than 98 percent coverage), and where water supply is not likely to be routinely controlled

Very high

Vb Population having access to improved water supply but not served with improved sanitation in countries which are not extensively covered by those services, and where water supply is not likely to be routinely controlled (less than 98 percent coverage)

Very high

Va Population having access to improved sanitation but no improved water supply in countries where less than 98 percent of the population is served by water supply and sanitation services, and where water supply is likely not to be routinely controlled

High

IV Population having access to improved water supply and improved sanitation in countries where less than 98 percent of the population is served by water supply and sanitation services, and where water supply is likely not to be routinely controlled

High

III IV and improved access/quality to drinking water; or IV and improved personal hygiene; or IV and drinking water disinfected at point of use, etc.

High

II Population having access to improved water supply and Medium to low

48

sanitation services in countries where more than 98 percent of the population is served by those services; generally corresponds to regulated water supply and full sanitation coverage, with partial treatment for sewage, and is typical in developed countries

I Ideal situation, corresponding to the absence of transmission of diarrheal disease through WSH

Very low

Source: WHO-Prüss-Üstün, et al (2004).

The Department of Health, in its FHSIS 2003 Report, reports that 83 percent of households have access to safe drinking water, while 76 percent have access to sanitary toilets. This puts the whole Philippine population under scenarios IV to VI since national coverage is less than 98 percent. While the FHSIS data contain the number of households that have access to safe drinking water and sanitary toilets across geographical regions, this information is insufficient to be able to come up with the classifications suggested above. Hence, the results of the Philippines Demographic and Health Survey 2003 (DHS 2003) are used to come up with the proportions of the population for both national and Metro Manila figures that are exposed to the different scenarios.18

Improved water supplies are those that are generally accessible to people and for which some measures are taken to protect the water from contamination; improvements do not guarantee the safety of the water from these sources. Improvements in sanitation facilities involve better access and safer disposal of excreta (Hutton and Haller, 2004). Table 21 summarizes the groupings of the responses for these questions in the DHS. Table 21 - Responses to the Demographic and Health Survey, 2003

Source of Drinking Water Sanitation Facility Improved Unimproved Improved Unimproved

Piped into dwelling Piped into yard/plot Public tap Protected well Developed spring Rainwater

Open dug well Undeveloped springRiver, stream,

pond, lake, or dam Tanker truck or

peddler Bottled water or

refilling station

Flush toilet (own) Flush toilet (shared) Close pit

Open pit Drop/overhang No toilet/field/bush

Source: Created by the author based on the raw survey data and descriptions of the categories in DHS.

18 The DHS asks respondents to identify the source of their drinking water and the type of sanitation facility. Households are then grouped into the different categories using Hutton’s (2004) definition for improved water supply and improved sanitation.

49

Figures 23 and 24 illustrate the distribution of households in the country and in Metro Manila, respectively, according to the relative ease of access to improved water supply and sanitation. The data show that a larger percentage of the population in Metro Manila has access to both improved water supply and sanitation compared with the whole country. A closer examination of the DHS data also yields information that describes the distribution of the households in terms of urbanity. Figure 23 – Household Access to Improved Water Supply and Sanitation, 2003 (National)

Unimproved sanitation and water supply

5%

Improved water supply,

unimproved sanitation

10%

Improved sanitation,

unimproved water supply

11%

Improved water supply and sanitation

74%

Source: Author’s estimates based on DHS raw data. Figure 24 – Household Access to Improved Water Supply and Sanitation, 2003 (Metro Manila)

Improved water supply,

unimproved sanitation

1.4%

Unimproved sanitation and water supply

0.2%

Improved sanitation,

unimproved water supply

16.5%

Improved water supply and sanitation81.9%

Source: Author’s estimates based on DHS raw data.

50

Health endpoints for WSH related illnesses are adopted from the Economics of Sanitation Initiative (ESI) report of the Philippines by the Water Sanitation Program (WSP), World Bank. As earlier pointed out in this section, these illnesses—the basis of the calculations for the economic burden of disease for WSH-related maladies—include cholera, diarrhea, viral hepatitis, schistosomiasis, and, typhoid and paratyphoid fever. The estimates show that diarrhea cases comprise the significant majority of cases of water, sanitation and hygiene related-illnesses. The focus on diarrhea can not be avoided as it is the most prevalent—and yet preventable—illness due to a poor environmental and hygienic conditions. Utilizing the results of the ESI report and adjusting to integrate additional information collected in the field to determine the attributable fractions for each of the diseases mentioned above is estimated and adopted. Attributable fractions for diarrhea for Metro Manila and the whole country are computed using the proportions of the population exposed to the agent of illness, and the relative risks associated with the individual scenarios. The calculations show that 86 percent of all diarrhea cases in the country can be attributed to water, sanitation and hygiene conditions. A summary of these AFs is presented below in Table 22:

Table 22 - Attributable Fractions (AF) for WSH-related Illnesses, 2003

Disease Region Applied

Attributable Fraction Source

Cholera National 1.00 Pruss Ustun National 0.86 This author

Metro Manila 0.86 This author Urban 0.86 This author Diarrhea

Rural 0.87 This author Schistosomiasis National 1.00 Pruss Ustun Typhoid and Paratyphoid Fever National 0.50 Pruss Ustun

Viral Hepatitis National 0.50 Pruss Ustun

Morbidity figures from the Department of Health’s FHSIS Reports were used as the basis to estimate the number of cases of WSH-related diseases in 2003 excluding diarrhea. Figures for diarrhea were, in turn, computed using data from the DHS 2003 report for children u5 and from WHO regional estimates for population 5+ years of age. Applying the estimated AFs in Table 22 above, the calculations showed that nationally, a total of 33.5 million cases of WSH-related cases occurred in 2003 (Table 23).

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Table 23 - Total Cases of WSH-related Illnesses, 2003

National Metro Manila Urban Rural

Cholera 1,144 263 768 113Diarrhea 33,321,133 4,158,272 11,714,787 17,448,074Viral Hepatitis 23,172 2,455 8,095 12,622Schistosomiasis 51,684 0 5,344 46,340Typhoid and Paratyphoid Fever 65,349 1,854 28,728 34,767Total Cases of WSH 33,462,483 4,162,844 11,757,723 17,541,916


Approximately 77 percent of these cases were children 14 years of age and younger. As expected, diarrhea made up the majority of the WSH-related diseases, comprising approximately 99 percent of all cases. Table 24 below summarizes the diarrhea figures according to age group and urbanity, while Table 25 lists the morbidity figures for other WSH-related illnesses outside of diarrhea.

Table 24 - Number of Cases of Diarrhea by Age Group, 2003

Age Group National Metro Manila Urban Rural

Younger than 1 4,764,676 651,834 1,681,840 2,431,0021 to 4 14,691,955 1,867,656 5,176,062 7,648,2375 to 14 6,125,743 612,723 2,167,659 3,345,36115 to 19 264,366 30,223 92,378 141,76520 to 29 433,304 49,542 151,409 232,35330 to 64 6,567,969 902,905 2,276,773 3,388,29165 and older 473,119 43,389 168,665 261,066Total 33,321,133 4,158,272 11,714,787 17,448,074

Source: Author’s calculations based on the base data from NDHS (2003) for children under 5 years of age, and WHO regional data for the population 5+ years of age. For the details on the methodology, refer to the Annex.

52

Table 25 - Number of Cases of WSH-related Illnesses (excluding Diarrhea) by Age Group, 2003

Cholera Viral

Hepatitis Schistoso-

miasis

Typhoid and Paratyphoid

Fever Younger than 1 138 303 0 9621 to 4 339 2,102 1,230 8,5185 to 14 349 7,649 17,114 20,04515 to 19 41 2,216 4,889 6,11320 to 29 67 3,631 8,010 10,01830 to 64 142 6,603 17,788 17,67565 and older 70 667 2,653 2,018Total 1,144 23,172 51,684 65,349


It must be noted that the cases of diarrhea and other WSH-related illnesses that have been reported in the PHS are lowest in Metro Manila, and are highest in the rural areas. Another striking piece of information is the high prevalence of schistosomiasis19 in rural areas, while Metro Manila reported no cases of the illness and the other urban areas reported a low figure (only 3.5 percent of the cases in the rural areas). This insight is important because it highlights the “critical or high risk” areas that must be targeted by policy and program development if specific illnesses are a consideration.

Economic Costs of WSH-related Morbidity

Similar to what was done in the estimation of the economic costs of air pollution-related diseases, the economic impacts of WSH-based illnesses are divided into three: morbidity (which is composed of direct and indirect costs) , and the share of government in subsidizing the treatment of these diseases. The direct costs refer to the treatment costs each individual pays for, based on estimated treatment-seeking behavior. Indirect costs, on the other hand, refer to the lost income of working individuals and mothers who had to miss work as a result of the illnesses. Based on the same basic assumption to compute the economic costs of air pollution-related illnesses, the calculations indicate that diseases due to water, sanitation and hygiene cost society a total of PhP 5.7 billion (USD 104.8 million) in out-of-pocket treatment expenses, PhP 9.8 billion (USD 180.0 million) in lost income opportunities resulting from illness, and PhP 1.2 billion (USD 22.8 million) of government resources to subsidize hospitalization costs (including the subsidy for the patients treated within the public hospital system). These numbers are illustrated in Figure 25 which breaks down the direct costs to households according to the treatment-

19 Schistosomiasis is endemic in certain regions of the Philippines. Metro Manila is not one of these regions.

53

seeking behavior, and Figure 26 which shows the aggregate cost to all households in the Philippine economy to treat specific WSH-related illnesses:

Figure 25 – WSH Cost to Households of Treatment (Net of Public Health Care Subsidy), 2003

Treatment costs in health centers

PhP 408 M6.2%

Philhealth subsidyPhP 534 M

8.0%

Self-treatment expensesPhP 620 M

9.3%

Subsidy to government

hospitalsPhP 620 M

9.3%

Treatment costs from traditional

healersPhP 955 M

14.4%

Treatment costs from private

doctorsPhP 1.173 B

17.7%

Out-of-pocket hospital expenses

PhP 2.330 B35.1%

Source: Author’s calculations Figure 26 – WSH Cost to Households of Treatment (Net of Public Health Care Subsidy), 2003 per Illness

SchistosomiasisPhP 61 M

1%

Viral HepatitisPhP 34 M

1%

DiarrheaPhP 5.487 B

96%

Typhoid and Paratyphoid Fever

PhP 98 M2%

CholeraPhP 2 M

0%


Hospitalization treatment of WSH-related illnesses had levied a burden on public resources equivalent, slicing away 0.8 percent of the total health budget for the country in 2003. Figure 27 breaks down these costs to the government to subsidize treatment.

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Figure 27 - Government Health Care Subsidy per WSH-Illness, 2003


FeverPhP 43 M

3%

DiarrheaPhP 1.154 B

94%

Schisto-somiasisPhP 22 M

2%


1%

CholeraPhP 1 M

0%


The economic cost of environmental health also includes the cost to individuals in terms of missed opportunity to be productive which is measured in lost income. As with air pollution-related ailments, conservative assumptions are used in order to avoid overstating these costs. Lost productivity is measured in foregone per capita GNI and multiplied by the number of missed work days lost. The calculations show that WSH-related illnesses caused the Philippine economy PhP 9.8 billion (USD 180.0 million). This includes the value of potentially productive days of mothers who missed work to care for their sick children. Figures 28 and 29 illustrate the numbers, as shown below:

Figure 28 – Lost Income due to WSH-related Illnesses, 2003

DiarrheaPhp 9.653 B

99.0%

CholeraPhP 0.6 M

0.0%

Viral HepatitisPhP 11.5 M

0.1%

SchistosomiasisPhP 28.1 M

0.3%

Typhoid and Paratyphoid Fever

PhP 60.6 M0.6%


55

Figure 29 - Total Economic Cost of Morbidity from WSH, 2003

DiarrheaPhP 16.294 B

97.7% CholeraPhP 3 M0.0%


FeverPhP 201 M

1.2%


0.4%

SchistosomiasisPhP 112 M

0.7%


Economic Cost of Premature deaths due to WSH

As with the OAP and IAP cases, the economic costs of WSH-related diseases also include the value of lost productive lives resulting from premature deaths. Once more, the range of values is computed using the HCV (for the lower bound) and the VSL (for the upper bound). It is estimated that 14,407 Filipinos (Figure 30) died from WSH-related illnesses, causing the economy a total of PhP 21.8 billion (USD 401.98 million) in lost productive opportunities—the highest among the three sectors—or PhP 56.1 billion (USD 1.0 billion) in terms of value of statistical life. These are separate from the 7,616 children under the age of 5, who are estimated to have died of illnesses caused by diarrhea-induced malnutrition which is discussed in the succeeding section (See the section on malnutrition-related mortality). These figures are broken down for each WSH-related illnesses evaluated in this report in Figure 30 this is laid out further for the specific age groups in Table 26.A and 26.B.

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Figure 30 – Mortality Cases Due to WSH Grouped According to Working and Non-working Age Groups, 2003

Source: Author’s calculations Table 26.A – Mortality Cases due to WSH by Specific Age Group, 2003

Age Group Cholera Diarrhea Viral Hepatitis

Schisto-somiasis

Age 0-4 4 9,251 25 0Age 5 to 14 3 942 14 7Age 15 to 19 2 70 14 4Age 20 to 29 1 75 44 23Age 30 to 64 7 347 272 19765 and older 8 432 74 87Not Reported 0 0 1 0Total 27 11,116 443 319

Source: Author’s calculations Table 26.B – Mortality Cases due to WSH by Specific Age Group, 2003

Age Group Filariasis Helminthiasis Typhoid Fever

Age 0 to 4 0 247 1,023 Age 5 to 14 0 35 637 Age 15 to 19 0 1 43 Age 20 to 29 1 4 41 Age 30 to 64 6 23 190 65 and older 1 13 236 Not Reported 0 1 0 Total 8 323 2,169


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Malnutrition-related Mortality

An observation of concern based on the data above is the high incidence of diarrhea in children. It is widely accepted that frequent diarrhea cases in young children could contribute to malnutrition. It is likely then, that early childhood diarrhea could lead to increased risk of illness and mortality as a result of diarrhea-induced malnutrition. The impact of diarrhea-based malnutrition should be included in the economic burden of disease if at all the data is available. This report, however, could only generate mortality cases from diarrhea-induced malnutrition for children under 5 years old. As such, only malnutrition-related mortality for this age group is included in this report. Table 26.C summarizes the data as shown below:

Table 26.C - Mortality Cases for Malnutrition caused by Diarrhea for Children under 5 years old, 2003

Age Group Malnutrition Cases

Younger than 1 3,719 Age 1 to 4 3,897 Total 7,616

Source: Rodriguez, et al (2008).

It was possibly Scrimshaw, Taylor and Gordon in 1968 that first brought into the discussion the nutritional impacts of infections in young children (Brown, 2003). This sub-section on malnutrition-related mortality was added in recognition of the fact that these authors suggested: that chronic diarrhea and malnutrition are strongly linked; and that malnutrition resulting from chronic diarrhea could lead to other diseases and death. The epidemiological evidence shows that among the age groups, it is the very young children (those under 5 years old) that are most affected. With this in mind, this report adds the calculations done by Larsen (2008), who estimated the number of cases of premature deaths of children in this age group who died of illnesses caused by diarrhea-related malnutrition. The information on number of cases is summarized in Table 27 below: Table 27 – Malnutrition-related Mortality Resulting from Diarrheal Infection, 2003

Diseases Number of Deaths (children under 5) Attributable to the Environment

Acute Lower Respiratory Infections 4,828Malaria 880Measles 164Protein Energy Malnutrition 475Other Infectious Diseases 1,269Total 7,616

Source: Larsen (2008). See the Annex 3 for the complete paper.

58

It is quite easy to oversimplify the link between diarrhea and nutritional status in children, but in order to guide the readers to understand the issues at hand, such simplification can not be completely avoided. Diarrhea in young children causes loss of micronutrients, which combined with the anthropometric risk factors, could cause additional nutrition-related complications and illnesses that could lead to death. More importantly, diarrhea impairs the ability of body to absorb nutrients, making the child weak and susceptible to other diseases such as those listed in the above table. The risks are aggravated by the inappropriate dietary therapy for diarrhea patients, especially for young children.

The economic toll of premature deaths arising from illnesses caused by unclean water, poor sanitation and improper hygiene is the highest among the three sectors evaluated in this report. What make the results more distressing is that it is the children—the most vulnerable members of society; also the future human capital source—who are most afflicted. Diarrhea is the most prevalent causes of deaths in the WSH category, hitting children under 5 years old (more than 80 percent of all diarrhea-related cases). The cost of premature deaths arising from illnesses caused by unclean water, poor sanitation and hygiene ranges from PhP 21.6 billion (USD 402.0 million using HCV) to PhP 56.1 billion (USD 1.0 billion using VSL). The valuation also shows that the malnutrition-related cases associated with diarrheal infection cost the Philippine economy PhP 12.5 billion (USD 230.0 million) in lost productivity or PhP 29.8 billion (USD 548.9 million) in value of statistical life. These figures are added to the WSH calculations in the preceding section to complete the picture of the mortality impacts of WSH.

Figure 31 – Cost of Premature Deaths due to WSH, 2003 (HCV)

59

Suggested Interventions The proposed interventions to address the water pollution, sanitation, and hygiene

issues need not be grand. The empirical literature indicates that interventions promoting the simple washing of hands with soap have significant impacts on the reduction of diseases. In many cases, the most effective intervention, therefore, is to effect behavior change with complimentary programs and assistance that will encourage further shifts in individual behavior to adopt sanitary practices and hygiene. Access to clean water

As what has been pointed out, access to clean water is essential in preventing illnesses. Households are encouraged to use more water because there is empirical evidence that show that additional consumption of water is used for hygiene purposes. Curtis, et al. (1995), for instance, observed that the likelihood that a mother will wash her hands after cleaning her child’s anus increased by nearly a 100 percent with the provision of a yard tap. The likelihood that soiled linen (with feces) will be washed right away also increased by more than a 100 percent (Cairncross and Valdmanis, 2006).

Studies show that the piped water had the greatest impact on health when it comes to water supply provision. This can be attributed to the fact that the probability of contaminating water through handling and transportation is reduced when water is more accessible. Water consumption also increases with the availability of piped connections. ADB (2007) notes that in the Metro Manila, people who have pipe water connections tend to consume more than those relying on non-piped connections. It follows then that in order to make hygiene-promotion more effective, people need to have improved access to clean water whether for drinking or for hygiene and sanitation purposes. Educating people to wash their hands becomes an ineffective intervention when water to be used for such activities is unavailable or insufficient.

There is evidence that prove that access to water has a positive and significant impact on diseases. A study done by Bukenya and Nwokojo (1991) showed a 56 percent reduction in diarrhea in Papua New Guinea when household tap was used rather than public standposts (of good quality) in accessing clean water (Cairncross and Valdmanis, 2006).

In many cases, water may be available but the quality cannot be guaranteed. In such situations, the intervention calls for the implementation of household water treatment. Sobsey (2007) listed the most widespread and promising water treatment systems available that can be further developed, implemented and disseminated. These include: “boiling, solar disinfection by the combined action of heat and UV radiation, solar disinfection by heat alone (solar cooking), UV disinfection with lamps, chlorination plus storage in an appropriate vessel and combined systems of chemical coagulation-filtration and chlorine disinfection”. Household treatment of water according to Fewtrell, et al (2005) can reduce diarrheal morbidity up to 39 percent.

Arnold and Colford (2007) conducted a meta-analysis of the studies on health impacts of diarrhea on children and the effectiveness of point-of-use chlorine treatment. Their findings revealed that point-of-use of chlorine treatment compared to traditional

60

practices reduced risk child diarrhea (pooled relative risk: 0.71; 0.58–0.87) and risk of Escherichia coli- contamination of stored water (pooled relative risk: 0.20, 0.13–0.30). These suggest that for the portion of the population who do not have access to clean water due to financial constraints, household water treatment can be used as a temporary intervention while waiting for the water systems to be installed. The authors also observed varying results across studies on diarrhea and water quality impacts. Possible explanations for this observation include differences in cultural practices in different sites, pre-intervention conditions and underlying water exposure risk. Lastly, Arnold and Colford (2007) raised the question of whether health impacts observed during short term trials could also persist in the long run. People may gradually lose interest over long periods leading to lower compliance and eventual abandonment of the introduced intervention or intervention’s effectiveness may vary depending on the season it was implemented. All of these should be taken into consideration when formulating large-scale and long term interventions.

Concurrently, the costs of intervention have also been examined. Cairncross and Valdmanis (2006) estimated the costs of constructing water supply in facilities. The results are presented in Figure 32 which shows the median construction cost of water supply facilities in Africa, Asia and Latin America. Costs vary depending on the location. Focusing on Asia for instance, the least expensive facility is the construction of a borehole. Borehole costs USD 17 per capita while house connections proved to be the most expensive with USD 92 per capita construction cost.

Figure 32 - Median Construction Cost of Water Supply Facilities for Select Regions (in USD)

Source: Disease Control Priorities in Developing Countries, second edition, 2006, Figure 41.1.

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Sanitation and hygiene improvement and promotion

Other interventions to address the issue of water pollution and sanitation have also

been evaluated. Fewtrell, et al. (2005) conducted a systematic review and meta-analysis of the effectiveness of the different water, sanitation and hygiene interventions available in less developed countries. Figure 33 shows the percent reduction in diarrhea morbidity given the different water, sanitation and hygiene interventions analyzed: improved water supply which includes improved water delivery (piped supply or household connections); sanitation interventions which includes provision of latrines; improved hygiene which includes health and hygiene education and hand washing promotion; and household water treatment which includes point of use treatment (i.e. chemical treatment, boiling, pasteurisation, and solar disinfection). The benefits are clear: 1) with improved drinking water, diarrhea morbidity was reduced by 25 percent; 2). Hygiene improvement resulted in 45 percent reduction in diarrhea cases; 3) sanitation improvement resulted into 32 percent reduction; and 4) a 39 percent reduction from household water treatment activities (Fewtrell, et al., 2005; WHO/UNICEF, 2005). Figure 33 - Percent Reduction in Diarrhea Morbidity of Different Water and Sanitation Interventions (in %)

25%

32%

45%

39%

0%5%

10%15%20%25%30%35%40%45%50%

Improved drinkingw ater

Improved sanitation Improved hygiene Household w atertreatment

% R

educ

tion

Source: Fewtrell, et al., 2005 as discussed in WHO/UNICEF, 2005.

In Figure 34, Cairncross and Valdmanis (2006) present the cost-effectiveness of water, sanitation and hygiene interventions. Sanitation promotion costs USD11 per DALY averted while sanitation that includes promotion and construction of facilities costs about USD 270 per DALY averted.

62

Figure 34 - Cost-effectiveness of Water Supply, Sanitation, and Hygiene Promotion (USD/DALY)

Cost-effectiveness

$3

$11

$270

$47

$223

$94

Hygiene Promotion

Sanitation - Promotion Only

Sanitation - Construction and Promotion*

Water Sector Regulation and Advocacy

Water Supply - House Connection

Water Supply - Hand Pump or Standpost

*Construction and Promotion ≤ 270. Source: Disease Control Priorities in Developing Countries, second edition, 2006, Table 41.12.

Hygiene improvement (especially washing of hands with soap) can also prevent diseases other than water borne diseases. It must be pointed out that hygiene promotion (i.e., washing of hands) can also prevent acute lower respiratory infections like pneumonia. Luby et al. (2005) conducted a study on the effect of hand washing on child’s health using 600 hand washing promotion households and 300 control households in Karachi, Pakistan. The hand washing promotion households were either given plain or antibacterial soap and were subjected to an intensive education and encouragement methods. Major findings include: 50 percent lower pneumonia cases for children younger than 5 years; 53 percent lower diarrhea cases for children younger than 15 years and 34 percent lower impetigo incidence among households who received soap and hand washing promotion than controls. No significant difference in terms of disease incidence was observed between households who received plain soap versus those who received anti-bacterial ones.

Clasen, et al. (2007) conducted a meta-analysis on the effectiveness of interventions that improve the microbial quality of drinking water in preventing diarrhea. The study revealed that diarrhea can be effectively abated thru interventions directed at improving microbial quality of water. These interventions include water source intervention (e.g.,. protected wells, bore holes, or distribution to public tap stands) and household adaptation (e.g.,. improved water storage, chlorination, solar disinfection,

63

filtration, or combined flocculation and disinfection). Degree of effectiveness however, varies depending on different of conditions. Interestingly, it was reported that “…combining the intervention with instructions on basic hygiene, a water storage vessel, or improved sanitation or water supplies”, and presence of improved water supply did not improve the effectiveness of the interventions studied.

Construction of Latrines

The transmission of most endemic diarrhea is from person to person thru poor hygiene practices because the pathogens are not waterborne. Given this, it is also important include improvement of sanitation facilities in the list of possible interventions (Cairncross and Valdmanis, 2006). To make the provision of sanitation facilities more effective, an education and promotion campaign should be done (World Bank, 2007). This will educate the target beneficiaries of the potential benefits they will get from using the facilities and in return entice them to use the facilities. It must be kept in mind that no amount of physical intervention will be effective if the behavior regarding hygienic practices is not altered.

In any case, the availability and construction of sanitation facilities is a necessary intervention in combating diseases. As a guide, Figure 35 shows the average cost of constructing sanitation facilities in Africa, Asia and Latin America. In Asia, simple pit latrines are the cheapest option (USD 26 per pit) while sewer connection is the most expensive to construct (USD 154 per connection) (Cairncross and Valdmanis, 2006). Figure 35 - Median Construction Cost of Sanitation Technologies in Select Regions (in USD)

Source: Disease Control Priorities in Developing Countries, second edition, 2006, Figure 41.2

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It must be noted that sanitation facilities are not limited to latrines. Sewers and sewer connections fall under this category as well. In the rural areas in the Philippines,

and in most of the poor households, sewerage facilities are severely lacking, significantly increasing the risk of the spread of diseases. Without proper disposal of wastes,

contamination of food and water are likely to take place. Final intervention, therefore, could also be in public investment in alternative waste disposal facilities that the poor—

especially the urban poor—can have regular and inexpensive access to.

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ANNEX 1

Methodology and Assumptions

The economic valuation of the health-related consequences of pollution, sanitation and hygiene problems in the Philippines necessitated the adoption of specific assumptions, and the use of methodological approaches—the cost of illness (COI) for morbidity; and, the human capital value (HCV) and value of statistical life (VSL) for mortality. In order to attain accuracy and closeness to reality, detailed assumptions were adopted and used in the calculations. This section contains the details of the methodologies and computations that were mentioned in the body of the report.

General Methodology This sub-section is devoted to the discussion on the methodology and assumptions

that were used for all three areas—OAP, IAP, and WSH—discussed in the main text. Separate discussions on the illness-specific calculations are also done in the succeeding sub-sections.

I. Calculating the Number of Health Cases The estimation of the number of cases of illness and mortality related to the three

areas of concern begins by identifying the appropriate health-endpoints. This necessitated the review of the existing epidemiological studies and reports done by WHO and others. The next step is to examine the existing health statistics and data to see which illnesses had ample data for the calculations. The decision as to which disease to include depends on the availability of information regarding risks of becoming ill or dying from environmental health risk factors and the extent to which total morbidity and mortality incidence figures and treatment-seeking behavior breakdowns can be estimated for each disease.

In order to estimate the number of morbidity and mortality cases due to the environment from the total cases of the illnesses and mortality in the country, the attributable fractions (AFs) must be calculated or adopted from another study that is similar to the Philippines. The AFs are multiplied with the total number of cases in the Philippines per illness or cause of death to come up with the number of cases that are due to the environment. The specific calculations for each of the three areas of concern are discussed in detail at each sub-section dealing with each of these three.

II. Treatment-Seeking Behavior

In order to reflect the behavior of Filipino households with regard to illnesses in the estimations, this study laid out the costs of treatment in terms of the treatment-seeking

74

patterns of the general population. By treatment-seeking (or health-seeking as referred to in some literature) behaviors the reference is on the list below:

Self Treatment Health Centers Hospitals Traditional No treatment Medicine Rural Health

Centers Government-owned

Medicine

Visits to the Western-trained doctors

Baranggay Health Centers

Private Owned Visits to the Traditional clinic

The data used to derive treatment-seeking behavior for the diseases are taken from

the 2003 National Demographic and Health Survey and from key informant interviews. For each disease, the percentage of people who sought treatment from rural health centers and barangay health units was used to estimate the baseline data from the FHSIS figures. The baseline morbidity cases data are then appropriated to the treatment-seeking behaviors outlined for each disease.

III. Economic Valuation of Morbidity

Economic burden of morbidity is broken down into direct cost to household, government subsidies and indirect costs. The morbidity cost calculations are based on the assumptions and methodologies for direct and indirect costs as discussed in the succeeding sub-sections.

III.a Direct Costs

Direct cost to household is cost of treatment less PhilHealth contribution (35% of confinement costs). To determine the direct costs, the calculated number of cases for each disease attributable to a specific sector (i.e. OAP, IAP, or WSH) according to health seeking behavior was then multiplied by the associated total costs of health seeking behavior per disease. Associated costs include cost of confinement, consultation fees and medicines. These costs were mainly based on PhilHealth data and key informant interviews. The table below presents the associated costs per health seeking behavior and other assumptions regarding treatment costs.

75

Associated costs per health seeking behavior

Health Seeking Behavior

Cost

Health Center Cases

Government Hospital

Cases

Private Hospital

Cases

Private Doctor Cases

Self Treatment

Cases

Traditional Healer Cases

Cost of Confinement* None

Adjusted PhilHealth data

Adjusted PhilHealth data None None None

Consultation Fee P10

Included in the lump sum amount reported by PHilhealth


P500 MM and Urban P300 Rural None

P150 MM and Urban P90 Rural

Medicine cost** P12/day



P12/day P12/day P12/day

Notes: *Confinement cost include doctors’ fees, medicines, room and board. The cost is based on the lump sum figure from PhilHealth adjusted with assumption that PhilHealth shoulders only 35% of total cost per confinement

** Medicine cost per day is assumed to be the same for all diseases. Total medicine cost depends on the duration of the disease.

Total cost per disease according to health seeking behavior depends on the duration of the disease. The duration (treatment/confinement) of the diseases is presented in the succeeding table as well.

Average Number of Days of Treatment/Confinement

Disease

Health Center Cases

Government Hospital

Cases

Private Hospital

Cases

Private Doctor Cases

Self Treatment

Cases

Traditional Healer Cases

ALRI 8 3 3 8 8 8 Bronchitis 4 3 3 4 4 4 Cholera 10 8 8 10 10 10 Diarrhea 5 3 3 5 5 5 Hepatitis 7 6 6 7 7 7 Schistosomiasis 7 5 5 7 7 7 Tuberculosis 180 180 180 180 180 180 Typhoid 14 4 4 14 14 14

Source: PhilHealth and key informant interviews

76

Total confinement cost (net of PhilHealth contribution) for government hospitals cases is the basis for the computation of the government subsidy. This report assumes that 50 percent of the total cost (net of PhilHealth contribution) of confinement (mainly the daily room rate) in public hospitals is subsidized by the government.

Note that COPD is not included in the above table. This is due to the fact that the calculations for the treatment costs for COPD are essentially the costs of managing the symptoms throughout an individual’s lifetime. As such, the direct costs of COPD “treatment” are calculated to be the sum of all these direct costs every year from the year that the illness is contracted, throughout the expected lifetime of the individual. To express these total lifetime costs in present value terms, a discount rate of 3 percent was used. The number of years an individual is projected to live out his or her life with COPD is based on the projections per age group by Shibuya et al (2001). III.b Indirect Costs

The indirect costs of morbidity are described to be the lost income and value of time losses of the individual who had to miss work while getting treated. The assumptions regarding the indirect costs are listed below:

a. Lost income due to illness is calculated only for the members of the population

who belong to the 20-64 age group, and adjusted according to the employment rate as reflected in the source of the data (the Philippines DHS 2003). The full value of daily Gross National Income per capita is applied to the individuals who are employed, as a proxy for their income. Only 75 percent of the daily GNI is applied to those who are not formally employed, as it is assumed that those who are not formally employed still contribute to national welfare through the work they do in the household or through the informal sector.

b. Foregone income was also computed for parents of children under 5 years old. The values were adjusted according to employment rate of women.

c. The employment data from the DHS are used in this study to estimate the number

of cases of adult individuals who had to miss work because of illness, or because they had to care for a sick child. The table below lists the employment figures used:

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Percentages of employed and unemployed

Employed Unemployed Women 51.6 48.4 Men 80.1 19.9

Source: Tables 3.5.1 and 3.5.2 of the NDHS 2003. Note: These figures are based on the total number of employed in the last 12 months preceding the survey. The data did not have a breakdown by age group, but this was used to calculate the lost income due to illness for the 20-64 age groups.

The total lost income due to illness is the equal to the sum of lost income

computed for population age group 20-64 years old and lost income computed for the parents of children under 5 years old. The method is straightforward: number of cases per health seeking behavior is multiplied by the per capita GNI value (adjusted to 100 or 75 percent depending on employment status) and the number of days lost due to the illness. To estimate the days lost due to illness, the following are further assumed:

a. Mothers are presumably the ones who most often care for the sick children in

the household. Those who take care of their sick children are divided between working and non-working mothers. Per capita GNI is used as the basic cost, but for non-working parents, an assumption of informal work or foregone leisure (assumed to be 75 percent of per capita GNI) was made. The per capita GNI per day is pro-rated for the number of hours a mother takes care of a sick child per day. It is assumed that only young children (children under 5 years old) are cared-for by a parent when they are ill.

b. Assumptions about the amount of time a mother devotes to care for a sick child are as follows:

i. Outpatient care is 2 hours per day for the duration of the illness

ii. Hospitalization days are the total number of days a child is in the hospital

plus one extra day for home-recovery. The number of days hospitalized and illness duration is based on the information gathered from PhilHealth, and from interviews of public health experts in the Philippines.

iii. It is assumed that a mother will likely attend to a child who has fever-like symptoms more than to a child who has diarrhea. In the valuation of a mother’s time off from productive activities to care for a child, it is assumed that a mother will take at least a day off from work if the child is stricken with an illness that has fever-like symptoms, and may not take a day off to care for a child with diarrhea.

78

c. The treatment duration for tuberculosis assumed in this paper is 6 months (180 days). This report assumes that the patient will (on average) spend 5 days in the hospital, and will only be allowed to work after 2 months of continuous treatment. For the succeeding 4 months after the 2 months of continuous treatment, it is further assumed that the patient will still be under medication—incurring PhP 12 per day medicine cost.

d. Weekends are excluded from the computations of the number of days a person will miss days of work. As illustration, a person who is ill for 10 days is assumed to have missed only 8 days of work.

e. For diarrhea cases that are not treated, a 1 day loss of income is assumed for

the individuals who are working, and 75 percent of this one-day lost income for those are not employed or employed in the informal sector.

As a general rule, no calculations are done for cases of illnesses for which there

are no available data risk ratios or AFs. For those instances when only the data for a certain age group are available, the economic costs are calculated for that age group only. This report strives to be accurate based on what data are available, and refrains from cross-using the risk ratios of AFs. As such, if the available risk ratio datum is only for lung cancer, then that risk ratio figure is used only for cancer cases, and is not used as the basis for the number of cases for other illnesses even if these are similar to cancer.

In terms of medical facilities, this report also does not make a distinction between the quality of government and private facilities. This is a simplification in order to make the additional assumption that the full cost of treatment in a public health facility is equal to that of a private one.

IV. Economic Valuation of Mortality

The economic valuation of mortality employs the same straightforward approach done in the economic valuation of morbidity. Attributable fractions of mortality from environmental factors are multiplied with total mortality to arrive at the number of deaths associated with each of the three sectors. These figures are then multiplied by the the HCV or VSL.

To determine the HCV, the present value of lost potential lifetime earnings from premature death is calculated, using 2003 Philippine gross national income per capita (as reported in the World Bank database) as proxy for income losses in 2003. Philippine GNI per capita, reported to be USD 1070 in 2003, is assumed to grow at 2.1 percent (average GNI per capita growth rate from 1999 to 2006) per year in the future. Since life expectancy for Filipinos is 67 for men and 72 for women (as reported by the WHO), each premature death is assumed to reflect lost income from age 20 (average start of working life) until the mandatory retirement age in the Philippines of 65 years old. Future income is discounted at an annual rate of 3 percent. The average HCV for specific age groups and VSL figure (calculated by B. Larsen) are presented below:

79

Average HCV per Age Group

Average HCV (USD)

Age Group OAP IAP WSH

VSL

Age 0 to 4 years 30,263 30,247 30,340 72,021

Age 5 to 14 years - - 32,204 72,021

Age 15-64 11,734 14,625 21,347 72,021

Estimating the Attributable Fractions

The estimation of the attributable fractions of disease and mortality from

environmental factors often times necessitates careful analysis of the available data. Oftentimes, adjustments have to be made in order to extract the information that is needed for the calculations.

In general, the AFs for morbidity are not the same as those for mortality. There are, however, cases when they are the same; and this report relied on the existing literature and advice from epidemiological experts to determine when this is the case, and when it is not. In this subsection, the methodology and assumptions used to compute the AFs for the three environmental areas are discussed.

I. Attributable Fractions and Relative Risk Ratios for the Morbidity Cases

Outdoor Air Pollution (OAP) The attributable fraction for diseases that are related to outdoor air pollution, are

calculated using a general formula that is used in Ostro (2004):

∑

∑

=

=

−+

−= n

iii

n

iii

RRP

RRPAF

1

1

)1(1

)1( Equation 1

where Pi is the proportion of the sub-population that is exposed to outdoor air pollution and RRi, the respective relative risk a sub-population is exposed to a specific diseases.

There is sufficient empirical and epidemiological literature that discusses the impacts of outdoor air pollution on health. Most of the literature, however, either focuses on specific morbidity endpoints such as hospital admissions or missed workdays for a certain disease (inevitably ignoring other health seeking behaviors), or directly reports attributable fractions and/or relative risk ratios, with no discussion on how these relative risk ratios are computed.

80

Unlike for IAP and WSH, the author could not find studies that conducted a meta-analysis of morbidity for OAP-related illnesses, and a unified framework by which studies for other localities can be made using local particulate matter data. Hence, for OAP-related morbidity, the relative risk ratios used are calculated based on the relative risk ratios presented in Galassi et al (2000), and are listed in the table below. Health outcomes and relative risks (per 10 µg/m3 of PM10)

Cause Central Estimate

Lower Limit 95%

Upper Limit 95% Notes

Hospital admissions for CVD causes 1.009 1.006 1.013

Hospital admissions for respiratory disease* 1.016 1.013 1.020

Chronic bronchitis 1.093 1.009 1.180 Adults 25+ Acute bronchitis* 1.306 1.135 1.502 Children <15 Asthma exacerbation 1.051 1.047 1.055 Children <15 Asthma exacerbation 1.004 1.000 1.008 Adults 15+ Restricted Activity Days 1.094 1.079 1.109 Adults 20+ Occurrence of respiratory symptoms* 1.07 1.02 1.11

Source: Galassi et al (2000).

*Health outcomes applied in this report to the Philippines.

There is a need, however, to adjust the relative risk ratios in the table below as these represent the relative risk ratios per 10 μg/m3 deviation from the baseline level of PM10. It must be noted that the deviations from the baseline level of PM10 for the Philippines are much higher than 10 μg/m3. In the table above (of health outcomes and RRs), only the health endpoints marked with an * in the table above are used in the calculations for the Philippines as these are the only endpoints for which complete morbidity figures and full treatment-seeking behaviors can be estimated.

To compute the relative risk ratios for the diseases due to PM10 exposure,

population-weighted annual PM10 levels are substituted into

( )[ ]tualCounterfacActual PMPMRR ,10,10exp −= β Equation 2

using 15 μg/m3 as the counterfactual PM10 level. The β coefficients and the relative risk ratios for each of the health endpoints under consideration are outlined in the table below.

81

Relative Risks for OAP-related Illnesses, 2003

Relative Risks Health Outcome β Metro

Manila Urban Rural

Acute Bronchitis, under 5 0.0267 4.6356 1.8733 1.0000 Hospital Admissions for Respiratory Disease

0.0016 1.0955 1.0380 1.0000

Occurrence of Respiratory Symptoms 0.0068 1.4751 1.1804 1.0000

Note: The betas are from Galassi et al (2000). Also, the relative risk ratio for the rural area is assumed to be 1 in order to exclude the rural areas in the discussion. This is due to the fact that there are no available PM data for the rural areas.

The next table summarizes the attributable fractions that were computed using the relative risk ratios above; and in turn is used to estimate the number of cases of OAP-related diseases. Attributable Fractions Used to Calculate the OAP-related Illnesses

Health Outcome Attributable Fractions

Acute Bronchitis, under 5 0.42343 Hospital Admissions for Respiratory Disease 0.02555 Occurrence of Respiratory Symptoms 0.11297

It must be noted that the attributable fractions in the table above are for urban

areas as there was insufficient information on particulate matter levels in the rural areas.

Indoor Air Pollution (IAP)

As with OAP-related morbidity, the AFs used to estimate the number of cases of

illnesses resulting from exposure to IAP (assumptions and methodology are adapted from Desai et al (2004), are computed using Equation 1. Only those health outcomes associated with indoor air pollution for which there is sufficient information to support any relative risk generalizations (included in Desai et al’s (2004) meta-analysis) and for which Philippine data was accessible, is investigated. The table below outlines the relative risk ratios used for IAP-related morbidity. Note that health outcomes marked by ** are not included in the analysis because coal is not regularly used as a fuel for cooking in the Philippines. It must also be noted that the RRs used for cases of ALRI for children under 5 is 1.8 instead of 2.3 (as reported by Desai et al). The adjustment in the assumption with regard the RR for ALRI is from Dherani et al (2008).

82

Relative Risk Ratios Used to Calculate the Number of Cases of IAP-related Illnesses

Evidence Health Outcome Group (based on gender and

age)

Relative Risk

Ratios

CI

ALRI Children <5 2.3 (1.8) 1.9-2.7 COPD Women ≥ 30 3.2 2.3-4.8

Strong

Lung cancer (from exposure to coal smoke)**

Women ≥ 30 1.9 1.1-3.5

COPD Men ≥ 30 1.8 1.0-3.2 Moderate-I Lung cancer (from exposure to coal smoke)**

Men ≥ 30 1.5 1.0-2.5

Lung cancer (from exposure to biomass smoke)

Women ≥ 30 1.5 1.0-2.1 Moderate-II

Tuberculosis All ≥ 15 1.5 1.0-2.4 Source: Desai, et al (2004).

To be able to calculate the attributable fractions necessary to determine what fraction of all reported cases of the illnesses is due to IAP, it is necessary to determine the size of the population exposed to indoor air pollution.

One other important piece of information needed to calculate the AFs for IAP-related illnesses is the size of the population in the Philippines that is exposed (long-term) to IAP. The 2006 Philippine Environmental Monitor used the proportion of households that reports usage of charcoal, fuel wood and biomass residue during the duration of the HECS 2004 as the relevant portion of the population exposed to indoor air pollution. A more conservative (and more realistic) proportion to use, however, would be the percentage of the population that reported the use of these solid fuels as their primary cooking fuel. This information can be extracted from the 2004 HECS from the information on the households’ use of other energy sources as the primary cooking fuel during the year prior to the actual survey. Subtracting the cases of households that use three types of solid fuel from the data, the results show that 48 percent of household members are considered exposed to indoor air pollution. This is slightly lower than the 53 percent figure that is reflected in the main section of this report.

Data from the HECS on usage of solid fuel according to urbanity and regional classification allows us to get an idea as to what percentage of households in Metro Manila and urban and rural areas report fuel wood, charcoal and other biomass residue as their primary cooking fuel. These figures, however, need to be adjusted by the associated ventilation factors because cooking practices and the structural characteristics of houses in the Philippines may mitigate the exposure of Filipino households to indoor air pollution and the subsequent health outcomes. Desai, et al. (2004) suggests using a ventilation factor of 0.25 for households that use improved stoves or cook outside, and a ventilation factor of 1.00 for those that use traditional stoves. Taking into account the “airiness” of the areas where cooking is done even if the stoves were traditional, a ventilation factor of 0.25 is used for urban and rural areas outside Metro Manila—as

83

households in these areas typically do their cooking outside their houses. Metro Manila households that use solid fuel, however, are assigned a ventilation factor of 0.5 since these households would normally be found in informal settlement areas where houses are crammed together. With the above assumptions on ventilation factors, the proportion of the cases of the health outcomes outlined above that can be attributed to exposure to indoor air pollution is computed. The AFs used are summarized in the IAP section of this report.

Water, Sanitation and Hygiene (WSH)

The analysis on the burden of disease from water pollution, sanitation, and

hygiene included five diseases—diarrhea, cholera, schistosomiasis, typhoid and paratyphoid fever, and viral hepatitis—for which 2003 morbidity data are available, and for which there is sufficient information relating these illnesses to water pollution and sanitation issues: The table below, which is based on the Philippine Environmental Monitor 2006 (PEM) , lists the attributable fractions for these illnesses (excluding diarrhea for which a separate section is devoted to). Attributable Fractions for WSH-Related Diseases (Excluding Diarrhea)

Disease Attributable Fraction

Source

Cholera 100% Various literature (not good) Schistosomiasis 100% WHO, 2006b Typhoid and paratyphoid fever 50% Expert opinion of World Bank Staff Viral hepatitis 50% Expert opinion of World Bank Staff Source: PEM 2006 (World Bank, 2007)

For the readers’ reference, Pruss-Ustun et al (2006) lists more diseases that are related to water, namely: helminthiasis, malaria, intestinal nematode infections (ascariasis, trichuriasis, hookworm disease), trachoma, chagas disease, onchoceriasis, leishmaniasis, Japanese encephalitis, and dengue fever. These diseases, however, are excluded from this report either due to a lack of national data or lack of sufficient evidence linking the available AFs to inaccessibility of clean water supply of proper sanitation facilities. Diarrhea

The attributable fraction for diarrhea is computed using Equation 1, where Pi corresponds to the proportion of the population subject to a specific exposure category and RRi, the relative risk from lack of water sanitation and hygiene associated with that category. The exposure categories used for diarrhea are based on Pruss-Ustun, et al (2004), and are summarized in Table 7 in the WSH section.

84

The 2003 Field Health Surveillance Information System(FHSIS) Report indicates that 83 percent of households have access to safe drinking water, while 76 percent have access to sanitary toilets. Since national coverage is less than 98 percent, all households in the Philippines can be categorized under exposure scenarios IV, Va, Vb, and VI, as described in the text.

The FHSIS Reports contain national, regional, provincial, and city-level data on the number of households that have access to safe drinking water and sanitary toilets across the country. However, these data are insufficient to be able to come up with the number of households that are under the classifications suggested in the main body. To remedy this, results of the Philippines Demographic and Health Survey 2003 are used to come up with the national, Metro Manila, urban-area, and rural-area population proportions that are exposed to the four different exposure scenarios.

The DHS asks respondents to identify their source of drinking water and the type of sanitation facility. Categorizing Philippine households into the four applicable exposure scenarios makes use of Hutton, et al’s (2007) definitions for improved water supply and improved sanitation. Improved water supplies are those that are relatively accessible to people and for which some measures are taken to protect the water from contamination; improvements do not guarantee the safety of the water from these sources. Improvements in sanitation facilities involve better access and safer disposal of excreta (Hutton and Haller, 2004). Note that water supply and sanitation services may also be categorized as “unimproved” when they are unnecessarily costly, even when they are deemed of safe quality. Table 11 in the main body of this report on the responses to the demographic and health survey summarizes the groupings of the responses for these questions in the DHS.

The raw data of the DHS allows for a breakdown of the respondents according to urbanity and geographical region. The table below shows the proportion of the national population under the different exposure scenarios and the relative risk due to lack of water supply and sanitation.

Relative Risks and Population Proportions Used to Compute for Attributable Fraction for Diarrhea

Population Proportions Demographic and Health Survey 2003 Exposure

Scenario Relative

Risks National IV 6.9 74.21 Va 8.7 10.81 Vb 11.0 9.80 VI 11.0 5.18

Attributable fractions for diarrhea for Metro Manila and the whole country are computed using the proportions of the population exposed to the agent of illness, and the relative risks associated with the individual scenarios. The calculations show that 86

85

percent of all diarrhea cases in the country can be attributed to water and sanitation conditions. A summary of these AFs is presented below in the table below:

Attributable Fractions (AF) for WSH-related Illnesses, 2003

Disease Region Applied

Attributable Fraction Source

Cholera National 100.00% Pruss Ustun National 86.28% This author

Metro Manila 85.58% This author Urban 85.85% This author Diarrhea

Rural 86.59% This author Schistosomiasis National 100.00% Pruss Ustun Typhoid and Paratyphoid Fever National 50.00% Pruss Ustun

Viral Hepatitis National 50.00% Pruss Ustun

II. Attributable Fractions and Relative Risk Ratios for Mortality Cases

Attributable fractions and relative risks for OAP

The AFs for mortality were computed using equation (1). Unlike for morbidity, relative risks for mortality due to OAP-related diseases can be readily computed using local particulate matter data using the framework suggested by Ostro (2004). The following formulas are used to compute for locality-specific relative risks, depending on particulate matter exposure:

PM10 exposure: ( )[ ]tualCounterfacActual PMPMRR ,10,10exp −= β (3)

PM2.5 exposure: β

⎥⎥⎦

⎤

⎢⎢⎣

⎡

++

=1

1

,5.2

,5.2

tualCounterfac

Actual

PMPM

RR (4)

Tables 16 and 17 below outlines the β coefficients used, the resulting relative risk ratios and attributable fractions. Relevant Particular Matter and β Coefficient of RR Formula for OAP-Related Health Outcomes

Health Outcome Particulate Matter β Coefficient

Respiratory Mortality, under 5 PM10 0.00166 Cardiopulmonary Mortality, 30 and older PM2.5 0.15515 Lung Cancer, 30 and older PM2.5 0.23218

Source: Ostro (2004).

86

Relative Risk and Attributable Fraction for OAP-Related Health Outcomes

Relative Risk Health Outcome Metro

Manila Urban Rural Attributable

Fraction

Respiratory Mortality, under 5 1.10006 1.03980 1.00000 0.03058

Cardiopulmonary Mortality, 30 and older 1.31085 1.13199 1.00000 0.08298

Lung Cancer, 30 and older 1.49940 1.20386 1.00000 0.12472


Attributable fractions and relative risks for IAP and WSH For the IAP and WSH mortality cases, the study used the same AFs and RRs

calculated for morbidity. This is the same method used in the studies that were reviewed for this report.

III. Calculation of number of total deaths per disease The paper based estimates of baseline mortality figures on data reported by the

Department of Health in the 2003 Philippine Health Statistics Report. However, the paper acknowledges that the official number of deaths reported may significantly be underestimated due to underreporting (particularly in the rural areas and for under-5 deaths) and inaccurate reporting of cause of death. To address this, the published data on the number of deaths reported per disease were adjusted by age-specific adjustment factors in light of a u5-child mortality rate of 36 per 1,000 live births and a crude mortality rate of 5.0 per 1,000 population in the Philippines in 2003 Adjustment Factor Used to Adjust for Published Mortality Figures from PHS

Age Group Adjustment Factor Under 5 2.42 5 and older 1.05

These adjustment factors are applied to mortality figures (reported in the 2003

Philippine Health Statistics) to obtain baseline mortality data caused by all the diseases under consideration, except for diarrhea. For diarrhea, the mortality data from Rodriguez et al (2008) were used—which have already been adjusted for underreporting. The adjusted figures for diarrhea and the other WSH-related illnesses were then multiplied by

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the corresponding AF's to get the deaths attributable to each sector. These final mortality figures associated with each sector according to age group are those that were used and presented in the tables in each section to determine the economic valuation of premature deaths due to pollution and poor sanitation and hygiene in the Philippines. Data

The main data source for baseline morbidity cases for the diseases under consideration (except diarrhea, COPD, and tuberculosis, which are discussed separately below) is the 2003 Field Health Surveillance Information System Report (FHSIS) of the Department of Health; however, there is a need to adjust these data to reflect accurate estimates for baseline morbidity cases as the FHSIS only reports figures for those who sought treatment from rural health centers and baranggay health units. I. Diarrhea

Since almost all of the cases of WSH-related illnesses is attributable to diarrhea, a more detailed approach to calculating the number of cases is done. Computing the baseline cases figures for diarrhea in 2003 necessitate dividing the Philippine population into age groups for which Rodriguez (2008) provided information on the per capita diarrhea cases (see table below).

Per Capita Diarrheal Cases, 2003

Age Group Diarrhea Case per capita Source 0 to 1 2.75 NDHS, 2003 1 to 4 2.08 NDHS, 2003

5 to 14 0.33 (improved sanitation) 0.52 (unimproved sanitation) WHO, WPR-B

15 and older 0.16 (improved sanitation) 0.26 (unimproved sanitation) WHO, WPR-B

The figures for treatment-seeking behavior derived for diarrhea is then applied to

the baseline case figures for the breakdowns necessary for economic valuation. II. COPD

As in the case of diarrhea, 2003 Philippine population figures are divided into age groups for which COPD incidence per 1,000 people is available, as reported in Shibuya et al (2001). These incidence figures are outlined in the table below. Appropriate treatment-seeking figures were then applied to the baseline incidence data.

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COPD Incidence Rate for Each Age Group

Incidence Rate (per 1,000 population) Age Group

Male Female 0 to 4 0 0 5 to 14 0 0 15 to 29 0.03 0.06 30 to 44 0.36 0.44 45 to 59 1.21 0.38 60 to 69 4.44 1.75 70 to 79 5.19 2.07 80 and older 5.14 3.43 Total 0.55 0.32 Source: Appendix 2, SEARO-B of Shibuya et al (2001).

III. Tuberculosis

The 2003 FHSIS Report reports figures for visits to baranggay health units and rural health centers for respiratory tuberculosis. The general methodology used for the other diseases were applied to respiratory tuberculosis data to arrive at 2003 baseline morbidity figures, but no distinction is made as to whether these cases are new or old. The study adopts WHO estimates of 108,062 cases for the Philippines in 2003, while maintaining the treatment-seeking behavior ratios used for the 2003 baseline morbidity figures. IV. Estimated Number of Cases per Age Group

Based on the AFs and the morbidity prevalence data from published health statistical data in the Philippines, the number of cases per age group in 2003 was computed. The results for all three—OAP, IAP, and WSH—are summarized in the tables below:

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Cases of OAP-related Illnesses by Age Group, 2003

ALRI and Pneumonia Acute Bronchitis

Younger than 1 104,494 155.471Age 1 to 4 169,618 272,240Age 5 to 14 60,766 195,812Age 15 to 19 8,464 10Age 20 to 29 13,875 16Age 30 to 64 40,374 4165 and older 16,844 12TOTAL 414,437 623,602

Cases of IAP-related Illnesses by Age Group, 2003

Acute Bronchitis

ALRI and Pneumonia

COPD Respiratory Tuberculosis

Younger than 1 37,058 110,459 0 0Age 1 to 4 64,891 179,294 0 0Age 5 to 14 0 0 0 0Age 15 to 19 0 0 0 716Age 20 to 29 0 0 0 1,173Age 30 to 64 18,630 22,842 2,670 3,60465 and older 4,900 8,839 1,558 1,139TOTAL 125,479 321,433 4,228 6,631

Cases of Diarrhea by Age Group, 2003

Cases National Metro Manila Urban Rural

Younger than 1 4,764,676 651,834 1,681,840 2,431,0021 to 4 14,691,955 1,867,656 5,176,062 7,648,2375 to 14 6,125,743 612,723 2,167,659 3,345,36115 to 19 264,366 30,223 92,378 141,76520 to 29 433,304 49,542 151,409 232,35330 to 64 6,567,969 902,905 2,276,773 3,388,29165 and older 473,119 43,389 168,665 261,066Total 33,321,133 4,158,272 11,714,787 17,448,074

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Cases of WSH-related Illnesses (excluding Diarrhea) by Age Group, 2003

Cholera Viral

Hepatitis Schistoso-

miasis


Fever Younger than 1 138 303 0 9621 to 4 339 2,102 1,230 8,5185 to 14 349 7,649 17,114 20,04515 to 19 41 2,216 4,889 6,11320 to 29 67 3,631 8,010 10,01830 to 64 142 6,603 17,788 17,67565 and older 70 667 2,653 2,018Total 1,144 23,172 51,684 65,349

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Cost-Benefit Analysis of Selected Environmental Health Interventions International evidence and applications to the Philippines Prepared for the Philippines CEA, World Bank20 by Bjorn Larsen21 Economist Consultant January 2009

20 This report is a background document prepared for the Philippines CEA, the World Bank. Task team leader was Jan Bojo, Lead Economist, East Asia and Pacific Department, World Bank. The report relies on Arenas (2009) as a basis for estimating health benefits of interventions. The findings and conslusions in this report are solely those of the author, and not necessarily those of the World Bank, its affiliates, or member states. 21 Contact information: [email protected] or [email protected]

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TABLE OF CONTENT

List of abbreviations I. Introduction II. Outdoor air pollution Interventions Intervention effectiveness and unit costs Benefit-cost ratios III. Indoor air pollution Interventions and unit costs Benefit-cost ratos IV. Water, sanitation and hygiene Interventions and unit costs Benefit-cost ratios Hand washing promotion

Household drinking water disinfection promotion V. Summary and Conclusions References

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LIST OF ABBRIVATIONS AF Attributable Fraction ALRI Acute Lower Respiratory Infection ARI Acute Respiratory Infection BCR Benefit-Cost Ratio CBA Cost-Benefit Analysis CEA Cost Effectiveness Analysis COPD Chronic Obstructive Pulmonary Diseases COI Cost of Illness DALY Disability-Adjusted Life-Year DHS Demographic and Health Survey DOC Diesel Oxidation Catalyst DPF Diesel Patriculate Filter GDP Gross Domestic Product GNI Gross National Income HCA Human Capital Approach HCV Human Capital Value HECS Household Energy Consumption Survey NOx Nitrogen Oxides IAP Indoor Air Pollution I&M Inspection and Maintenance LPG Liquefied Petroleum Gas OAP Outdoor Air Pollution PM Particulate Matter ppm parts per million RR Relative Risk SOx Sulfur Oxides USEPA United States Environmental Protection Agency VF Ventilation Factor VSL Value of Statistical Life WSH Water, Sanitation and Hygiene WTP Willingness to Pay

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I. INTRODUCTION

A cost-benefit analysis (CBA) provides estimates of the costs and benefits of an intervention, such as an investment, a policy or regulation, or a program. The results can be expressed in terms of internal rate of return, net present value, or as a benefit-cost ratio. CBA is increasingly used in many countries for assessing the merits of potential environmental interventions. As such, a CBA can serve as an instrument to establish priorities and guide allocation of scarce public and private resources. Benefit-cost ratios for selected interventions to improve environmental health are presented in this paper for the following areas of intervention, generally found to be the areas with the largest environmental health effects in developing countries (WHO, 2002):

Outdoor air pollution (OAP) in major urban areas;

Indoor air pollution (IAP) from household use of solid fuels; and

Water supply, sanitation and hygiene (WSH).

Costs and benefits of environmental interventions are often difficult and time consuming to comprehensively and accurately quantify. This is especially the case for OAP control. Therefore, rather than embarking on conducting a CBA purely based on data from the Philippines, this paper presents some international evidence of benefit-cost ratios of selected OAP control interventions. Adjustments of the data used in estimating the benefit-cost ratios in the original studies have been undertaken to the extent possible to reflect the situation in the Philippines. A range of estimates of benefit-cost ratios are in some cases presented that reflect sometimes diverse situations within the Philippines. For IAP and WSH, the CBA presented here is based on data and recent estimates of health effects in the Philippines by Arcenas (2009). Health improvements and time savings are most often the main benefits of interventions addressing OAP, IAP and WSH. IAP control interventions, such as an improved wood stove or use of an LPG stove for cooking, also involve significant changes in fuel use. Improvements in water supply and sanitation, and use of improved stoves or LPG stoves, can provide additional benefits such as improved convenience and status, but these benefits are often not quantified in monetary terms in CBA studies. The focus of the CBA in this paper is therefore on health, time savings, and changes in fuel use.

II. OUTDOOR AIR POLLUTION

Arcenas (2009) estimates there were over 15,000 deaths and over 1 million cases of respiratory illness (pneumonia and bronchitis) from particulate matter (PM) air pollution in urban areas in the Philippines in year 2003. The annual cost of these health effects is estimated at US $0.1 – 1.1 billion, or about 0.1-1.1 percent of gross national income (GNI). The low end of the estimate is based on using the human capital approach (HCA) for valuation of mortality and the high end of the estimate is based on using a value of

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statistical life (VSL). In both cases, the cost-of-illness (COI) approach is used for valuation of morbidity. Cost-benefit analysis of interventions to improve outdoor air pollution (OAP) in urban areas have long been a tool used in the United States and increasingly in Europe and other high income countries. CBA studies from these countries may however not be applicable to the Philippines or other developing countries because of differences in technology levels. High income countries have for instance already implemented quite stringent fuel quality and emissions standards. This implies that the cost of further outdoor air quality improvements are often substantially higher than in most developing countries. There are however an increasing number of CBA studies from developing countries that can shed light on benefits and costs of OAP control interventions in the Philippines. These studies include Blumberg et al (2006) from China, Larsen (2005) from Bogota, Colombia, Stevens et al ( 2005) from Mexico City, Mexico, ECON (2006) from Lima, Peru, and Larsen (2007a) from Dakar, Senegal. The focus of these studies is on particulate matter (PM) as PM is considered the pollutant with the largest health effects in most urban areas (WHO, 2002). Interventions evaluated in these studies are control of emissions from motorized transport. There are also CBA studies in developing countries evaluating the control of emission from industry and power plants. Benefits and costs of emission control from these sources are however very location specific and therefore diffult to apply to the Philippines. In applying the transport sector CBA studies from China, Colombia, Mexico, Peru and Senegal to the Philippines, several adjustments to the data used in these studies should be considered. This includes potential differences in emission sources and dispersion, differences in baseline health status, and differences in valuaton of health improvements of interventions. Assessing differences in emission sources and dispersion would require detailed studies and is therefore not addressed here. This introduces a significant element of uncertainty. The benfit-cost ratios (BCRs) frrom the studies in the beforementioned countries can therefore only serve as an indication of the potential BCRs in the Philippines. Health effects of OAP are predominantly among the adult, elderly population. Baseline health status in this age group in major urban areas is quite similar in the Philippines, Colombia and Peru. No adjustments are therefore made to baseline health status. In China, a larger share of the population die from cardiopulmonary disease than in the Philippines, thus health benefits of air pollution control might be larger in China than in the Philippines. The opposite may be the case in Senegal vs the Philippines. The differences in China and Senegal should be taken into consideration when evaluating the benefit-cost ratios of interventions estimated for these countries. Valuation of estimated health improvements is adjusted in proportion to differences in income level between the study countries and the Philippines. Mortality is valued using a value of statistical life (VSL) and morbidity is valued using the cost-of-illness (COI) approach. A VSL of US $109,000 is applied which reflect gross national income (GNI) per capita in the Philippines in 2007.22 The human capital approach (HCA) could have been used for valuation of mortality. However, as most individuals dying from OAP are in age groups 60 years and older, the HCA would attach a very low or even zero value to 22 This is calculated by using a VSL benefit transfer from high income countries of US$ 2 million (Mrozek and Taylor, 2002), adjusted to the Philippines in proportion to per capita income differences.

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mortality. Most studies to date, however, provide evidence that elderly individuals are willing to pay significant amounts to reduce their risk of dying, and thus have a high VSL. The VSL approach is therefore likely to provide a more appropriate measure of the welfare benefits to society from improving outdoor air quality than the HCA. Interventions The CBA studies from China, Colombia, Mexico, Peru and Senegal provide benefit-cost ratios for the following transport sector interventions:

Low sulfur diesel (500 and 50 ppm sulfur content);

PM control technology for new vehicles (Euro 4 standards);

PM retrofit control technology for in-use diesel vehicles (diesel oxidation catalysts (DOC) and diesel particulate filters (DPF)); and

Inspection and maintenance (I & M) of diesel vehicles.

All these interventions address PM emissions from diesel vehicles, except for Euro 4 standards which are for both gasoline and diesel vehicles. PM emissions from diesel vehicles with no or limited control technology are many times higher than from gasoline vehicles. However, gasoline vehicles contribute significantly to secondary PM through atmospheric conversion of gasous emissions (such as NOx and SOx) to particulates (such as sulfates and nitrates). Euro 4 standards for gasoline vehicles are therefore likely to provide reductions in secondary PM. Lowering the sulfur content in diesel reduces PM emissions from diesel vehicles. Low sulfur diesel is also a prerequisite for proper functioning of PM control technology in new and in-use vehicles. Euro 4 technologies and diesel particulate filters (DPF) require a maximum sulfur content of 50 ppm. No higher than 500 ppm can be used for effective funtioning of Euro 2 technologies and diesel oxidation catalysts (DOC). The share of diesel fuel consumption in road transport in the Philippines was about 50 percent in 2005 (IEA, 2008). This was significantly higher than in Thailand (27%), but much lower than in India (71%) and Pakistan (85%). Intervention effectiveness and unit costs The following emission control effectiveness parameters are used in the CBA studies in the mentioned countries:

Low sulfur diesel (500 ppm) reduces PM by an average 20%;

Ultralow sulfur diesel (50 ppm) reduces PM by an average 33%;

Diesel oxidation catalysts (DOC) reduces PM by > 25%;

Diesel particulate filters (DPF) reduces PM by > 80%.

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Euro 4 standards reduce PM by 60-70% (relative to Euro 2).23 Unit costs of interventions used in the CBA studies are presented in table 1. Most of the studies use a range of cost. The costs in table 1 represent average costs used in each of the studies. Lowering the sulfur content from 500 to 50 ppm in diesel is more expensive than lowering the content from for instance 2,000 to 500 ppm, the cost of a DPF is higher than the cost of a DOC, and the cost of a DOC or DPF for a heavy duty vehicle is higher than the cost for a light duty vehicle. Unit cost figures applied in the studies do also vary across countries, based on various assumptions. The figures in table 1 are used here in the CBA that is adjusted to the Philippines. Table 1: Unit costs of interventions to control vehicle PM emissions US $ Study country Diesel (500 ppm sulfur) 1.6 US$/barrel (incremental cost) Colombia & Senegal Diesel (50 ppm sulfur) 2.6 US$/barrel (incremental cost) Senegal EURO 4 technology 150 light duty diesel vehicle China EURO 4 technology 2500 heavy duty diesel vehicle China DOC 435 buses & delivery trucks Mexico DOC 1000 large buses Senegal DPF 2300 older buses Mexico DPF 1600 newer buses & delivery trucks Mexico DPF 5000 buses Colombia DPF 5000 large buses Senegal DPF 850 taxis Senegal Retrofit PM control 3000 buses Peru Source: From Blumberg et al (2006), Larsen (2005), Stevens et al ( 2005), ECON (2006) and Larsen (2007a). Benefit-cost ratios Benefit-cost ratios (BCRs) of interventions to control PM emissions from road vehicles are presented in table 2. They are ratios adjusted to the Philippines from the original study countries. The BCRs should be considered applicable to major urban areas such as Greater Manila. The BCRs of low sulfur diesel is based on introducing such diesel in major urban areas. The BCRs of diesel with 500 ppm sulfur and subsequently 50 ppm are all greater than one (i.e., benefits > costs). The BCRs from the Senegal study adjusted to the Philippines are greater than those adjusted from the Colombia and Peru studies. This may largely result from very high road transport dieselization in Senegal and thus high share of PM emissions from diesel vehicles. The BCRs of vehicle PM control technologies, once low sulfur diesel is available, are also greater than one for the types of vehicles and technologies presented in table 2. The highest BCRs are for diesel oxidation catalysts (DOC) for diesel buses (large and old). The advantage of the DOCs is that only 500 ppm sulfur diesel is required for the proper functioning. With the exception of diesel particulate filters (DPF) for high usage diesel taxis, the BCRs are generally lower for DPFs than for DOCs, because of the higher cost

23 The reductions for heavy duty diesel vehicles is as high as 80-90% relative to Euro 2 standards.

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of DPFs. However, DPFs have the potential to reduce PM emissions substantially more than DOCs once 50 ppm sulfur diesel is available. The study from China, adjusted to the Philippines, importantly finds that Euro 4 standards for new vehicles (gasoline and diesel) provide a relatively high BCR. Such standards can be introduced once 50 ppm sulfur gasoline and diesel is available. However it would require that such gasoline and diesel is available nationwide if Euro 4 is mandated for vehicles that are also used outside urban areas, such as intercity buses and trucks and passenger vehicles. The adjusted BCR from the Peru study for Inspection & Maintenance program for diesel vehicles suggests very high benefits relative to costs. Poorly maintained diesel vehicles is a major contributor to PM emissions. An effective I & M program can therefore provide substantial benefits if properly implemented and monitored. In considering the BCRs presented in table 2, it should be remembered that health benefits are valued using VSL for mortality. As reduction in mortality is a significant share of health benefits from air pollution control, the BCRs would be less than one if the human capital approach (HCA) was used to value mortality. However, as argued previously, VSL is likely to better reflect social welfare gains from air pollution control than the HCA. The CBAs of PM emission controls did not consider two- and three-wheelers, street cleaning and control of construction dust. Two- and three-wheelers are major sources of PM emissions from the road transport sector in Asia, and 2-stroke engines cause substantially higher emissions than 4-stroke engines. CBA studies are however limited, but PM control measures for two- and three-wheelers are generally considered highly cost effective. Improved street cleaning is another intervention to control PM and is considered highly cost effective but CBA studies are limited. Without proper and frequent street cleaning, PM emissions are resuspended into the air from traffic and wind, and can be a significant source of PM ambient concentrations. Construction dust can also be a significant source of PM, but CBA studies are also limited for this source of PM. Foreign imports of second-hand diesel vehicles can be a major source of PM emissions. It is therefore important to ensure that such vehicles are equipped with Euro standards (or equivalents) suitable for the diesel fuel used in the Philippines. Table 2: Benefit-cost ratios of interventions to control PM emissions from road vehicles

Benefit-cost ratios Original study Low sulfur diesel

500 ppm diesel (Senegal) 5.06 Senegal 500 ppm diesel (Colombia) 1.62 Colombia 50 ppm diesel (Senegal) 4.09 Senegal 50 ppm diesel (Peru) 1.40 Peru

Control technology for new vehicles Euro 4 standards 2.10 China

Retrofitting of in-use diesel vehicles (DOC) Old buses 6.54 Mexico Large buses 6.74 Senegal

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Buses 4.12 Peru Newer buses 2.97 Mexico Old delivery trucks 2.23 Mexico Newer delivery trucks 1.81 Mexico

Retrofitting of in-use diesel vehicles (DPF) High usage taxis 5.30 Senegal Old buses 2.80 Mexico Large buses 2.89 Senegal Newer buses and delivery trucks 1.47 Mexico

Inspection & Maintenance Diesel vehicles 3.90 Peru

Source: Adjusted to the Philippines from the original studies by the author.

III. INDOOR AIR POLLUTION

Arcenas (2009) estimates there were nearly 5,800 deaths and nearly 500,000 cases of illness (ALRI, COPD and tuberculosis) from indoor air pollution (IAP) annually in the Philippines in year 2003. Around 1,300 of the deaths (ALRI) are in children u5, and 4,500 deaths (mainly COPD and tuberculosis) are in adults (15+ years of age). The annual cost of these mortality and morbidity health effects is estimated at US $87 – 435 million. The low end of the estimate is based on using the human capital approach (HCA) for valuation of mortality and the high end of the estimate is based on using a value of statistical life (VSL). In both cases, the cost-of-illness (COI) approach is used for valuation of morbidity. An increasing number of CBA studies from developing countries can shed light on potential benefits and costs of controling IAP from household use of solid fuels for cooking. The predominant solid fuel used in the Philippines for cooking is wood, although charcoal is also significant. Evaluation of benefits and costs of IAP control therefore focuses on replacing unimproved wood stoves with improved wood stoves, and replacing wood stoves with LPG stoves as the use of LPG has increased rapidly over the last decade. Switching from fuel wood to charcoal is not considered here, as few studies are available that provide estimates of health effects of using charcoal vs fuel wood. CBA studies of improved wood stoves and use of LPG include a global-regional study by Hutton et al (2006), Habermehl (2007) from Uganda, Larsen (2005) from Colombia, Larsen and Strukova (2006) from Peru, and a global-regional cost-effectiveness study by Mehta and Shapar (2004). Habermehl presents a CBA for improved wood and charcoal stoves, and the other studies look at improved wood stoves as well as switching to cleaner fuels such as LPG. These studies all find that the benefits of replacing unimproved wood stoves with improved wood stoves by far exceeds the cost of stoves and stove promotion programs. For replacing wood stoves with LPG stoves, the studies show however mixed results depending on estimates of time and fuel wood savings and valuation of these savings.

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The methodologival approach to estimate health benefits of interventions in most of the CBA studies is to apply the relative risks (RR) of disease from household use of solid fuels presented in the meta-analysis of international evidence in Desai et al (2004).24 These relative risks can be considered to reflect IAP in households using unimproved wood or biomass stoves in poorly ventilated indoor environments causing high exposure to solid fuel smoke. An unimproved solid fuel stove is a stove with low fuel efficiency and no control of smoke, with smoke emitted directly into the immediate environment. An improved solid fuel stove is a stove with higher fuel efficiency and cleaner fuel burning. The stove may be attached to a chimney or hood that vents the smoke to the outside from the indoor environment, which further reduces immediate exposure to smoke. Most of the CBA studies evaluates the health benefits of an improved wood stove that reduces the health effects of IAP from solid fuels by 30-70 percent relative to the use of an unimproved wood stove. Switching to an LPG stove from an improved wood stove would eliminate the remaining health effects of IAP from solid fuels. When estimating the potential health benefits of controlling IAP from household solid fuel use, considerations must be given to potential differences between the study countries in Desai et al and the Philippines in terms of cooking practices, smoke ventilation characteristics of dwellings, type of stoves used by households. Potential differences in cooking practices and smoke ventilation characteristics of dwellings (household air pollution exposure conditions) can be incorporated in a CBA by applying a ventilation factor (Desai et al, 2004). For the purposes of the CBA here, a ventilation factor (VF) of 1.0 represents indoor cooking with minimal separation of cooking and living areas and minimal venting of smoke from solid fuel use. If cooking with solid fuels is undertaken outdoors or in a well-ventilated area of the dwelling separated from living areas, the VF is assumed to be 0.25.25 These VFs are applied to the excess risk of health effects from use of solid fuels when estimating the disease burden from IAP.26 The estimates of health effects in Arcenas (2009) is based on a VF of 0.25. While this may be reflective of predominant exposure conditions in the Philippines, many households are likely to cook in conditions representing a VF of 1.0. To estimate potential benefits of IAP control in these households, the estimates of health effects in Arcenas are reestimated at VF=1.0.27 In order to provide a value of potential health benefits that are applicable if interventions were to be implemented now, the estimates in Arcenas are adjusted to year 2007 in proportion to changes in gross national income (GNI) per capita from 2003 to 2007. This implies a value of statistical life (VSL) of US $109,000 as used in the OAP section. At the low end, mortality is valued using the human capital value (HCV) equal to the present

24 Subsequent to the referenced CBA studies, a meta-analysis of the relative risk of pneumonia in young children was undertaken by Dherani et al (2008), finding a somewhat lower relative risk than reported in Desai et al (1.8 vs 2.3). The results in Dherani et al is applied here to the Philippines. 25 Even in such favorable conditions, use of solid fuels still result in household exposure to smoke (for the person cooking, nearby children, and from smoke entering the dwelling). A ventilation factor=0 is therefore practically non-existent when solid fuels are used for cooking and other purposes. 26 Excess risk of health effects is RR-1 where RR is risk of health effects relative to not using solid fuels. 27 Restimation was done by recalculating the attributable fractions (AFs) of disease and mortality from indoor air pollution, and valuing the atributable fractions using unit values from Arcenas, and adjusting to year 2007.

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value of life time income lost from premature mortality.28 For children under five year of age, the HCV is about ½ of the VSL. For adults, the HCV averages about US $7,800 or 4.8 times GNI per capita in 2007. Type of solid fuel stoves in the study countries in Desai et al may not be the same as in the Philippines. For practical purposes, solid fuel stoves are classified as unimproved and improved stoves. It is assumed here that the relative risk of health effects of an unimproved stove is the same across countries if used under the same cooking conditions. If cooking conditions are different, then the ventilation factor is applied to reflect these differences. Improved stoves may be different across countries. This is irrelevant in a CBA for an intervention replacing an unimproved stove with an improved stove, as long as the type of improved stove is charcterized. It is here assumed that the improved stove is of such a characteristic as to reduce excess risk of health effects from solid fuels by 50 percent. Type of improved solid fuel stoves currently in use in the Philippines is however important if they are to be replaced by for instance LPG. For practical purposes, the scenario considered here is replacing improved stoves that cause health effects at 50 percent of unimproved stoves. Thus switching from an improved stove to LPG would remove the remaining 50 percent of health effects from solid fuel used in unimproved stoves. Most of the CBA studies do also evaluate non-health benefits of improved solid fuel stoves or LPG stoves. These benefits may include time savings from reduced solid fuel collection or cost savings from reduced solid fuel purchases, time savings from reduced cooking time associated with improved stoves or LPG stoves, and potential environmental benefits arising from reduced need for fuel wood (see next section). Interventions and unit costs Three interventions are evaluated:

Switching to improved wood stove from unimproved wood stove (50% reduction in health effects relative to unimproved stoves);

Switching to LPG stove from unimproved wood stove (removes all health effects from solid fuels); and

Switching to LPG stove from improved wood stove (removes all health effects from solid fuels);

Each of these three interventions are evaluated for two different household conditions, one in which the ventilation factor is 1.0 (indoor cooking with no or minimal separation between cooking and living areas and no or minimal ventilation) and one in which the ventilation factor is 0.25 (outdoor cooking or cooking in well ventilated area separated from living area). Unit costs of interventions and key stove and fuel parameters used in the CBA are presented in table 3. Household fuel wood consumption is around 2 tons per year for an unimproved stove. This is estimated based on data in the Philippines HECS 2004 (NSO, 28 Studies of VSL are mostly for adults. As a substantial share of mortality from indoor air pollution is in children, a scenario using the HCV is also used.

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2005) and Samson et al (2001). There are various types of improved wood stoves of different prices. The type of improved stove evaluated here is more costly than many other simple improved stoves, and is assumed to have a useful life of 10 years and be twice as energy efficient as an unimproved stove, i.e., the use of the improved stove provides 50 percent fuel wood savings. This is consistent with or conservative relative to for instance findings in Samson et al (2001) and Habermehl (2007). LPG fuel cost changes with world prices. As of recently, the cost of LPG in the Philippines was about US $ 1 per kg. LPG fuel consumption for cooking is estimated at 100 kg per household per year (NSO, 2005; IEA, 2008; Samson et al, 2001). Fuel wood savings from introducing an improved wood stove or switching to an LPG stove is valued at 75 percent of wage rates for households that collect their fuel wood. An approximate rural wage rate of US$0.5 per hour is applied, as fuel wood collection is more predominant in rural areas. Hutton et al (2006) reports fuel wood collection time for 20 countries. The lowest average collection time is 30 minutes per day (Indonesia and Nigeria). To be conservative, 30 minutes is applied to the Philippines for households using unimproved wood stoves. Thus a household collecting its fuel wood, and switching from an unimproved to an improved wood stove, would save about 15 minutes per day in colletion time valued at US $35 per year. For households that purchase some or all of their fuel wood, savings will be greater. A market price of US$45 per ton of fuel wood is applied, which is similar to prices reported in Samson et al (2001). Table 3: Unit costs of interventions and key stove and fuel parameters Source: Wood consumption (unimproved stove) 2 Tons/household/year

Philippines (NSO (2005); Samson et al (2001).

Improved wood stove cost 20 US$ per stove Philippines (assumed) Fuel wood collection time (unimproved stove) 30 Minutes/household/day Philippines (assumed) Wood savings (improved stove) 50%

Relative to unimproved stove Based on change in stove efficiency

LPG stove cost 60 US$ per stove Philippines

LPG fuel cost 1 US$ per kg Philippines (November 2008)

LPG fuel consumption 100 Kg/household/year

Based on wood consumption, stove efficiencies, and NSO (2005) IEA (2008), Samson et al (2001).

Valuation of time savings 75% Of wage rates Using a rural wage rate of US$0.5 per hour

Promotion program 5 US$ per household per year Colombia & Peru

Note: Stove costs are annualized over 10 years at a discount rate of 10%. It is also assumed that a promotion program is needed to encourage households to switch to improved wood stoves or LPG, at a cost of US $5 per household per year.29 Thus

29 Program cost per household is cost per household that switches to improved wood stove or LPG stove. Program cost per household targeted by the program is substantially lower, as only a fraction of households respond to the program.

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program cost per household is significantly higher than the annualized cost of the improved stove, but only 5 percent of annual cost of LPG consumption per household. Benefit-cost ratios Benefit-cost ratios (BCRs) of interventions to control IAP from household use of solid fuels are presented in table 4. Ratios are presented for two valuation methods of health benefits (VSL for mortality and COI for morbidity; and HCV for mortality and COI for morbidity) and for two ventilation factors reflecting a range of household air pollution exposure conditions. The BCRs for replacing unimproved wood stoves with improved wood stoves are greater than one (i.e., benefits > costs) for both valuation methods under the whole range of household air pollution exposure conditions (VF: 0.25-1.0). This is the case even when only health benefits are included. When time savings from reduced fuel wood collection is included (resulting from increased energy efficiency of improved stoves), the BCRs for exposure conditions with VF=0.25 increase significantly. The BCRs for replacing unimproved wood stoves with LPG stoves are greater than one in the highest exposure conditions (VF=1) when mortality is valued using VSL or when time savings or fuel wood purchase savings are included as benefits. In low exposure conditions (VF=0.25), BCRs are only greater than one when mortality is valued using VSL and time savings are included (4-5 in table 4). BCRs for replacing improved wood stoves with LPG stoves are only greater than one in the highest exposure conditions and when mortality is valued using VSL (6-8 in table 4). Table 4: Benefit-cost ratios of interventions to control indoor air pollution from solid fuels

Valuation method VSL & COI HCV & COI Ventilation factor (VF) VF=1 VF=0.25 VF=1 VF=0.25

(1) Improved wood stove (health only) 14.5 5.02 3.08 1.00

(2) Improved wood stove (health & time savings) 18.8 9.32 7.38 5.30

(3) LPG from unimproved stove (health only) 2.03 0.70 0.43 0.14

(4) LPG from unimproved stove (health & time savings) 2.63 1.30 1.03 0.74

(5) LPG from unimproved stove (health & wood cost savings) 2.83 1.50 1.23 0.94

(6) LPG from improved stove (health only) 1.02 0.35 0.21 0.07

(7) LPG from improved stove (health & time savings) 1.32 0.65 0.52 0.37

(8) LPG from improved stove (health & wood cost savings) 1.42 0.75 0.62 0.47 Source: Estimated by the author. The BCRs presented in table 4 are likely to be conservative. Potential reductions in various respiratory health symptoms other than acute lower respiratory infections (ALRI) are not included. Winrock International (2005) in a study in the Philippines provides some perspectives on such symptoms in relation to household cooking fuel. The CBA studies from Colombia and Peru include upper and lower acute respiratory illness (ARI) and find that the monetized benefits are a substantial share of total health benefits,

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especially when mortality is valued using the HCA.30 Potential time savings from reduced cooking time is also not included in the BCRs in table 4. Hutton et al (2006) report that an improved wood stove and LPG stove can reduce cooking time by over 10 percent relative to an unimproved wood stove. This could therefore amount to 10-15 minutes per day for a typical household cooking three meals a day, which is close the fuel wood collection time savings from an improved wood stove and half of the collection time savings from switching from an unimproved wood stove to an LPG stove.31 Valuing reduced cooking time raises however issues as to the extent to which this frees up time for other activities for the person cooking. If the person can conduct other household activities while food is cooking, then there are no effective time savings from reduced cooking time. Because of this uncertainty, any benefits from reduced cooking time is therefore not included in this CBA for the Philippines.

IV. WATER SUPPLY, SANITATION AND HYGIENE

Arcenas (2009) estimates that there were 14,400 deaths and over 33 million cases of illness (mainly diarrhea) from inadeqate water supply, sanitation and hygiene (WSH) in the Philippines in year 2003. Over 10,500 of these deaths and over 19 million cases of illness were in children under-5. In addition, there were an estimated 7,600 malnutrition related deaths in children under-5 from WSH.32 The annual cost of these health effects is estimated at US $1 – 1.9 billion. The low end of the estimate is based on using the human capital approach (HCA) for valuation of mortality and the high end of the estimate is based on using a value of statistical life (VSL). In both cases, the cost-of-illness (COI) approach is used for valuation of morbidity. Interventions to improve WSH include upgrading of household water supply and sanitation from unimproved to improved water supply and toilet facilities, point-of-use household treatment of drinking water, and improved hygiene practices especially handwashing with soap by mothers or caretakers of young children.33 Several meta- 30 The health benefits of interventions in the Colombia and Peru studies were adjusted to the Philippines for illustration. This provided BCRs quite consistent with the BCRs in table 4. However, the adjusted BCRs from the Colombia and Peru studies tend to be higher than in table 4 when the HCA was used for valuation of mortality. 31 The data pesented in Hutton et al suggest there is no significant cooking time difference between an improved wood stove and an LPG stove. In this case there would be no additional time savings benefits (other than fuel wood collection time savings) from switching from an improved wood stove to an LPG stove. 32 Estimated by B. Larsen in Arcenas (2009). 33 Unimproved water supply includes direct use of surface water (rivers, lakes, ponds, etc), unprotected dug wells, unprotected springs, tanker trucks and carts with small drums/tanks, and unimproved rain water. Improved water supply includes protected dug wells, protected springs, boreholes/tubewells, public standpipes, piped water supply into dwelling or yard, and improved rain water (collected and stored in a closed tank and withdrawn from a tap). Unimproved sanitation includes open pit latrine/pit latrine without slab, hanging toilet/latrine, bucket, no toilet facility or bush or field, and flush/pour flush toilet draining to a place other than a piped sewer system, septic tank or pit latrine. Improved sanitation includes pit latrine with slab, composting toilet, ventilated improved pit latrine, and flush/pour flush toilet to a piped sewer system, septic tank or pit latrine. Point-of-use household treatment of water includes boiling of water, chemical disinfection of water (e.g., chlorination), solar disinfection, filtration, flocculation-disinfection.

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analyses have recently been undertaken of the international evidence of the effectiveness of these interventions in reducing diarrheal illness. Hand washing with soap and household point-of-use drinking water disinfection are generally found to be most effective in reducing diarrheal illness, followed by improved sanitation and water supply (table 5). Table 5: Reduction in diarrheal illness from water supply, sanitation and hygiene interventions Hand

washing with soap

Point-of-use drinking water

disinfection

Improved sanitation (improved toilet

facilities)

Improved water supply

Fewtrell et al (2005) 44% 26% (urban) 39% (rural)

32% 25%

Curtis and Cairncross (2003)

47%

Arnold and Colford (2007) 29% (chlorine)

Clasen et al (2007a) 30-40% (children u5)

35-50% (all ages)

Studies have also found that improved handwashing reduces the risk of respiratory infections. In a meta-analysis of available studies from developed countries, Rabie and Curtis (2006) found that improved handwashing on average reduced respiratory infections by 16 percent. In a randomised controlled trial in Karachi, Pakistan, Luby et al (2005) found that children under-5 in households that received handwashing promotion and soap had a 50 percent lower incidence of pneumonia than children in the control group that did not receive promotion and soap. CBA studies from developing countries have focused on various aspects of improving WSH. Most recently, they include a global-regional study by Hutton et al (2007), ECON (2006) from Egypt, Larsen (2005) from Colombia, Larsen and Strukova (2006) from Peru, Larsen (2007b) from Mexico, and Larsen (2007a) from Senegal. These studies present CBA for a range of interventions such as improved water supply and sanitation facilities, and improved hygiene and household drinking water disinfection. There are also CBA studies of wastewater treatment. Benefits of wastewater treatment are however very location specific and difficult to adapt to other settings or generalize to a national level. There are also several recent cost-effectiveness analysis (CEA) studies of WSH interventions. For instance, Clasen et al (2007b) and Clasen and Haller (2008) present a global-regional CEA of various household water treatment options at water source and point-of-use. Haller et al (2007) present a global-regional CEA of improved water supply and sanitation and household water treatment. Shrestha et al (2006) evaluates the health benefits of home-based chlorination and safe water storage in rural Uganda. Cairncross and Valdmanis (2006) presents a global CEA of household water supply, sanitation and hygiene promotion. Larsen (2003) presents a global-regional CEA of water, sanitation

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and hygiene interventions. These studies provide estimates of the cost of averting a disability adjusted life year (DALY) while Larsen estimates costs per death averted.34 All the CBA country studies as well as the global-regional study by Hutton et al (2007) evaluates both non-health and health benefits of WSH interventions. The main non-health benefit is time savings from improved access to water supply and sanitation facilities. Health benefits are reduced incidence of diarrheal illness and mortality. None of the CBA and CEA studies include potential improvements in child nutritional status (and associated health and non-health benefits) from reduced diarrheal illness. World Bank (2008) summarizes the international evidence of this link and concludes that 20-50 percent of child underweight may be caused by diarrheal infections in early childhood, mainly arising from inadequate WSH. As child underweight is an important indicator of increased risk of child mortality and disease (Fishman et al, 2004), Fewtrell et al (2007) estimates that the additional health burden of malnutrition related health effects from WSH in developing countries is 60 percent higher than previously estimated when only diarrheal mortality and illness from WSH is considered. Similarly, Larsen (2008) estimates that total mortality from WSH in several Asian countries is 60-80 percent higher than direct diarrheal mortality from WSH.35 Moreover, World Bank (2008) and Larsen (2007c) estimate that the annual cost of non-health effects of child malnutrition from WSH is nearly 4-5 percent of GDP in Ghana and Pakistan. This cost arises from the negative impact of malnutrition on children’s cognitive development, school performance, productivity and life time income. Although the prevalence of child malnutrition is lower in the Philippines than in Pakistan, the cost may be similar to that in Ghana, nearly 4 percent of GDP.36 Also, importantly, none of the CBA and CEA studies include potential reductions in respiratory infections from improved handwashing. This omission is likely to represent a significant underestimation of the benefits of handwashing programs, as improved handwashing was found to substantially reduce pneumonia in Pakistan (Luby et al, 2005), and to generally reduce respiratory infections in developed countries (Rabie and Curtis, 2006). In order to provide a value of potential health benefits that are applicable if interventions were to be implemented now, the estimates of health effects from WSH in Arcenas (2009) are adjusted to year 2007 in proportion to changes in gross national income (GNI) per capita from 2003 to 2007. This implies a value of statistical life (VSL) of US $109,000. At the low end, mortality is valued using the human capital value (HCV) equal to the present value of life time income lost from premature mortality.37 For children under five year of age, the HCV is nearly ½ of the VSL. For the population 5+

34 There ar also single intervention studies. For instance, Meddings et al (2004) presents a CEA of household sanitation (latrines) improvements in Kabul, Afghanistan. 35 In the Philippines, total mortality from WSH is estimated to be nearly 70 percent higher than only direct diarrheal mortality from WSH (see Larsen in Arcenas (2009). 36 Prevalence of child stunting, an indicator of chronic malnutrition and strongly associated with impaired school performance, is higher in the Philippines than in Ghana (see www.childinfo.org). Studies from Cebu in the Philippines find significant effects of early childhood stunting on school performance such as delayed primary school enrollment, increased drop-out rates and grade repetition, lower child learning productivity at school, and less years of schooling (Daniels and Adair , 2004; Glewwe et al, 2001). 37 Studies of VSL are mostly for adults. As a substantial share of mortality from WSH is in children, a scenario using the HCV is also used.

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years of age, the HCV averages about US $33,000 or 20 times GNI per capita in 2007. Baseline child mortality rate is also adjusted from 2003 to 2007, i.e., from 36 to 30 deaths per 1,000 live births, and child mortality from WSH is adjusted proportionately. In order to evaluate benefits and costs of hand washing and drinking water disinfection promotion programs in urban and rural areas, health effects in urban and rural areas are estimated from the national estimates in Arcenas in relation to urban and rural child mortality and morbidity rates.38 Interventions and unit costs In light of the results from the meta-analyses of the effectiveness of WSH interventions in reducing diarrheal illness, the focus here is a CBA of hand washing promotion and household point-of-use drinking water disinfection promotion. Benefits and costs are evaluated for hand washing promotion to mothers and caretakers of young children and to other household members separately. Hand washing by mothers and caretakers of young children involves hand washing with soap at critical times such as after going to the toilet, after cleaning a child, and before preparing meals and feeding a child. For disinfection, benefits and costs of boiling of drinking water are evaluated, and, as for hand washing, evaluations are undertaken for children u5 and older household members separately.39 Benefits of hand washing and drinking water disinfection promotion programs depends critically on household response rate to the programs and sustainability of improved hand washing practices and water disinfection among those responding to the program. Three hand washing programs that provide program costs and response rates are presented in table 6. Response rates, i.e. improved hand washing behavior, range from 10 to18 percent of target households. Program cost ranges from around US $0.4 to US $5 per target household, and from US $3.5 to US $28 per household with improved behavior.40 In terms of sustainability of behavioral change, a study of communities in six countries in Africa and Asia found that improved hygiene behavior from intervention programs is sustained several years after interventions (Shordt and Cairncross, 2004). The CBA here therefore presents benefits and costs of promotion programs with response rates ranging from 10-20 percent and 1-3 years of sustained improved hand washing practices and household water disinfection. Table 6: A Review of costs and effectiveness of hand-washing promotion programs Guatemala Thailand Burkino Faso Target area National Rural villages One City

38 According to the Philippines DHS 2003, the child mortality rate in urban and rural areas was 30 and 52 respectively. These figures are adjusted to reflect the national child mortality rate in 2007. Diarrheal prevalence rate in children u5 in urban and rural areas was the same. Thus no adjustments are made to morbidity. 39 Alternative disinfection or treatment methods could be evaluated, such as household chlorination, filtering, solar disinfection, and flocculation disinfection (see Clasen and Haller, 2008). Boiling of drinking water is however a common treatment method by households in many developing counries and is therefore evaluated here. 40 No studies were identified by the author of household point-of-use drinking water disinfection promotion program response rates and program cost per household.

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Targeted Households With children

under-5 All All With children

under-3 Number of Targeted Households 1570000 10000 6550 38600 Duration of Program Implementation 1 year 3-4 months 3-4 months 3 years Response rate (% of target population) 10% 11% 16% 18% Program Cost (000 US $) 560 6 7.7 194 Program Cost per Target Household (US $) 0.4 0.6 1.2 5.0 Program Cost per Target Household with Behavioral Change (US $) 3.6 5.4 7.4 28 Source: Derived from Saade et al (2001), Pinfold and Horan (1996), and Borghi et al (2002). Three hand washing promotion program scenarios are presented in table 7 in terms of household response rates and program costs in line with the findings from the review of programs in table 6. Program cost per target person (mother or caretaker of children u5) with behavioral change ranges from US $4 to $25. Reduction in diarrheal illness (and diarrheal mortality) in children u5 is assumed to be 45 percent (see table 5). Few studies have estimated soap consumption from improved hand washing practices. Borghi et al (2002) report soap consumption for hand washing to be about 7 balls of soap per household per year at US $0.5 per ball in households in Burkino Faso that responded to a hand washing promotion program.41 Consumption of 12 soaps per person per year at a cost of US $0.4 per soap is applied here. Increased water use for improved hand washing is from Borghi et al (2002). Cost of water is assumed to be US $0.5 per m3 in both urban and rural areas.42 Thus total private cost (soap and water) per person with behavioral change is US $5.35 per year. This is slightly higher than program cost per person with behavioral change in Scenario 1, and only 1/5th of program cost in Scenario 3. Table 7: Hand washing program response rates and unit costs Scenario 1 Scenario 2 Scenario 3 Program response rate (% of program targets with behavioral change) 10% 15% 20% Program cost per program target (US$) 0.40 1.20 5.00 Program cost per target person with behavioral change (US$) 4.00 8.00 25.00 Reduction in diarrheal illness from improved hand washing 45% 45% 45% Soap consumption (soaps/person/year) 12 12 12 Cost per soap (US$) 0.40 0.40 0.40 Cost of soap per person per year (US$) 4.80 4.80 4.80 Increased water use for improved hand washing (liters/person/day) 3 3 3 Cost of water (US$ per m3) 0.5 0.5 0.5 Cost of water per person per year (US$) 0.55 0.55 0.55 Private cost per person with behavioral change per year (US$) 5.35 5.35 5.35 Source: Assumptions and estimates by the author. Three household point-of-use drinking water promotion program scenarios are presented in table 8, identical to the hand washing scenarios in terms of household response rates

41 Borghi et al do not present soap consumption per household member with improved hand washing. However, as the hand washing promotion program targeted mothers with children, it may be assumed that most of the soap consumption was by mothers. 42 This implies that annual cost of water is around 10 percent of annual cost of soaps, thus the assumption has minimal impact on total costs.

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and program costs. Reduction in diarrheal illness (and diarrheal mortality) is assumed to be 25 percent in urban areas and 35 percent in rural areas (see table 5). Disinfection method evaluated is boiling of water. It is assumed that 1 liter is boiled per person per day for population aged 5+ years and 0.5 liters is boiled for children under 5 years of age. Estimated costs of boiling are presented in table 9. Estimates assume that water is boiled for 10 minutes.43 Cost of boiling with LPG assumes a stove efficiency of 50 percent. Cost of LPG is US $1.0 per kg, as per November 2008 in the Philippines. Cost of boiling with fuel wood assumes a stove efficiency of 15 percent. Implicit cost of fuel wood is US $45 per ton, based on household collection time of 30 minutes per day, annual household consumption of fuel wood of 2 tons per year for all purposes, and time valued at 75 percent of a rural wage rate of US $0.5 per hour (see table 3 in indoor air pollution section). Table 8: Household drinking water disinfection program response rates and unit costs Scenario 1 Scenario 2 Scenario 3 Program response rate (% of program targets with behavioral change) 10% 15% 20% Program cost per program target (US$) 0.40 1.20 5.00 Program cost per target person with behavioral change (US$) 4.00 8.00 25.00 Reduction in diarrheal illness from drinking water disinfection (urban) 25% 25% 25% Reduction in diarrheal illness from drinking water disinfection (rural) 35% 35% 35% Source: Assumptions by the author. Table 9: Cost of boiling drinking water (US$ per person per year) Fuel used for boiling of water

Children u5 years Population 5+ years

LPG (urban and rural) 3.1 6.2 Fuel wood (rural) 1.75 3.5 Source: Estimates by the author. Benefit-cost ratios Benefit-cost ratios (BCRs) for hand washing promotion and for household drinking water point-of-use disinfection promotion are estimated with and without child nutrition benefits. Nutrition benefits are reduced malnutrition (and thus reduced child mortality) from reduction in diarrheal incidence in early childhood. It is assumed that the health benefits are proportional to reduction in diarrheal incidence, and are therefore at best a very rough estimate. The BCRs with nutrition benefits should therefore be considered at the most as only indicative of additional benefits of hand washing not previously incorporated in benefit-cost analysis.44 43 Energy requirement and cost of bringing water to boiling point is estimated at about 10 times higher than the energy required to keep water boiling for 10 minutes. Thus length of boiling time has minimal impact on overall cost of boiling drinking water. 44 To improve the estimates of nutrition benefits, a functional form relating reduction in diarrheal incidence and nutritional status would need to be determined from the empirical literature to estimate counterfactual nutritional status. Secondly, relative risks of mortality from poor nutritional status (for severe, moderate, and mild underweight) in Fishman et al (2004) would need to be applied to counterfactual nutritional status to estimate health benefits. For the methodology and estimates of health effects of malnutrition from diarrheal infections, see annex in Arcenas (2009) by B. Larsen, or World Bank (2008) and Larsen (2007c).

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Hand washing promotion: BCRs of hand washing promotion targeting mothers and caretakers of children u5 in urban and rural areas are presented in tables 10-11. Benefits of the program are reduced diarrheal illness and mortality in children u5.45 BRCs are presented for promotion program response rates ranging from 10 to 20 percent, with improved hand washing sustained for 1 to 3 years, and for two valuation methods of health benefits (VSL for mortality and COI for morbidity; and HCV for mortality and COI for morbidity). The following can be observed: BCRs are higher in rural than in urban areas because of larger benefits related to child mortality in rural areas; BCRs increases with the length of time improved hand washing is sustained, based on the assumption that the promotion program cost is incurred in the first year; and BCRs decline with higher program response rate due to the higher unit cost per person to induce behavioral change (see table 7). BCRs are all greater than one, except for in urban areas if improved hand washing is not sustained for more than one year, nutrition benefits are not included, and the promotion program is of an intensitiy and high cost as to achieve a 20 percent response rate. Table 10: Benefit-cost ratios of hand washing promotion, urban areas

Valuation method VSL & COI HCV & COI Program response rate 10% 15% 20% 10% 15% 20%

Benefit-Cost Ratios (w/o child nutrition benefits) Improved hand washing is sustained for 1 year 4.6 3.2 1.4 2.7 1.9 0.8 Improved hand washing is sustained for 2 years 5.8 4.5 2.3 3.4 2.6 1.4 Improved hand washing is sustained for 3 years 6.3 5.2 3.0 3.7 3.0 1.7 Benefit-Cost Ratios (w/ child nutrition benefits) Improved hand washing is sustained for 1 year 7.0 4.9 2.1 3.7 2.6 1.1 Improved hand washing is sustained for 2 years 8.7 6.8 3.5 4.6 3.6 1.9 Improved hand washing is sustained for 3 years 9.5 7.9 4.5 5.0 4.1 2.4 Source: Estimated by the author. Benefits and costs are discounted at an annual rate of 10 percent. Table 11: Benefit-cost ratios of hand washing promotion, rural areas


Benefit-Cost Ratios (w/o child nutrition benefits) Improved hand washing is sustained for 1 year 7.0 4.9 2.2 3.7 2.6 1.1 Improved hand washing is sustained for 2 years 8.8 6.9 3.5 4.6 3.6 1.9 Improved hand washing is sustained for 3 years 9.6 7.9 4.5 5.1 4.2 2.4 Benefit-Cost Ratios (w/ child nutrition benefits) Improved hand washing is sustained for 1 year 11.1 7.8 3.4 5.4 3.8 1.7 Improved hand washing is sustained for 2 years 14.0 10.9 5.6 6.8 5.3 2.7 Improved hand washing is sustained for 3 years 15.2 12.6 7.2 7.4 6.1 3.5 Source: Estimated by the author. Benefits and costs are discounted at an annual rate of 10 percent.

45 Mothers and caretakers are also likely to benefit from improved hand washing in terms of reduced diarrheal illness. These benefits are not included here and thus the benefit-cost ratios are likely to be conservative.

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A hand washing promotion program targeting mothers and caretakers of young children may also induce improved hand washing practices in the population aged 5+ years, with or without additional program promotion cost. A CBA for this population is therefore also undertaken. In the case of no additional program costs, the BCR is about 0.4 when benefits are valued using the HCV and COI and about 0.7 when benefits are valued using VSL and COI.46 These estimates are based on the same benefit and cost parameters as for children u5, except that program promotion cost is assumed to be zero for this population group (see table 7).47 A promotion program may also be implemented that targets all population age groups (not only households with young children). If program cost per household is the same as the one targeting households with children, then, when valuing benefits with the HCV and COI, the BCRs for the population 5+ years of age are estimated at 0.35 for the 10% response rate scenario and 0.25 for the 20% response rate scenario for the case when improved hand washing is sustained for two years (in contrast to 0.4 when program cost is assumed zero). The corresponding BCRs using VSL and COI are 0.65 and 0.5. The reason for the low BCRs for the population 5+ years of age is the much lower incidence of diarrheal disease and mortality in this population group than in children u5. Benefits from reducing the disease burden is therefore proportionately lower in the population 5+ years. The BCR does however depend critically on soap consumption for improved hand washing. The BCR is greater than one if required soap consumption is less than 4 soaps per person per year (instead of 12), when benefits are valued using the HCV and COI. If VSL and COI are used to value benefits, then the BCR is greater than one if soap consumption is less than 8 soaps per year. Drinking water disinfection promotion: BCRs of household drinking water disinfection (boiling of drinking water) for children u5 in urban and rural areas are presented in tables 12-14. Benefits of the program are reduced diarrheal illness and mortality in children u5. Ratios are presented for promotion program response rates ranging from 10 to 20 percent, with drinking water disinfection sustained for 1 to 3 years, and for two valuation methods of health benefits (VSL for mortality and COI for morbidity; and HCV for mortality and COI for morbidity). Fuel for boiling of water is LPG in urban areas, and LPG or wood in rural areas. The following can be observed: BCRs are higher in rural than in urban areas because of larger healh benefits in rural areas;48 BCRs are higher for fuel wood than LPG (rural areas), because of fuel cost differentials;49 BCRs increases with the length of time drinking water disinfection is sustained, based on the assumption that the promotion

46 Data are not sufficiently available to estimate BCR for urban and rural areas separately for this population age group. 47 In this case, the BCR is independent of program response rate and period of sustained improved hand washing practice, and is determined solely by health benefits and private cost of hand washing (soap and water consumption). 48 This is from higher percentage reduction in diarrheal illness in rural areas (see table 8), and from higher baseline child mortality in rural areas. 49 It should be noted that use of fuel wood has air pollution health effects that are not reflected in the estimated BCRs. However, as seen in the indoor air pollution CBA section, benefits of switching from fuel wood to LPG generally only appear to exceed the incremental cost of LPG in households using stoves indoors in poorly ventilated environments.

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program cost is incurred in the first year; and BCRs decline with higher program response rate due to the higher unit cost per person to behavioral change (see table 8). BCRs are all greater than one, except for in urban areas if drinking water disinfection is not sustained for more than 1-2 years, nutrition benefits are not included, and the promotion program is of an intensitiy and high cost as to achieve a 20 percent response rate. Table 12: Benefit-cost ratios for drinking water disinfection promotion, urban children u5 (boiling of water using LPG)


Benefit-Cost Ratios (w/o child nutrition benefits) Disinfection is sustained for 1 year 3.3 2.1 0.8 2.0 1.2 0.5 Disinfection is sustained for 2 years 4.6 3.3 1.5 2.7 1.9 0.9 Disinfection is sustained for 3 years 5.2 3.9 1.9 3.0 2.3 1.1 Benefit-Cost Ratios (w/ child nutrition benefits) Disinfection is sustained for 1 year 5.1 3.3 1.3 2.7 1.7 0.7 Disinfection is sustained for 2 years 6.9 5.0 2.2 3.7 2.6 1.2 Disinfection is sustained for 3 years 7.9 6.0 3.0 4.2 3.2 1.6 Source: Estimated by the author. Benefits and costs are discounted at an annual rate of 10 percent. Table 13: Benefit-cost ratios for drinking water disinfection promotion, rural children u5 (boiling of water using LPG)


Benefit-Cost Ratios (w/o child nutrition benefits) Disinfection is sustained for 1 year 7.2 4.6 1.8 3.8 2.4 1.0 Disinfection is sustained for 2 years 9.8 7.0 3.1 5.2 3.7 1.7 Disinfection is sustained for 3 years 11.1 8.4 4.2 5.9 4.4 2.2 Benefit-Cost Ratios (w/ child nutrition benefits) Disinfection is sustained for 1 year 11.4 7.3 2.9 5.5 3.5 1.4 Disinfection is sustained for 2 years 15.5 11.1 5.0 7.6 5.4 2.4 Disinfection is sustained for 3 years 17.7 13.4 6.6 8.6 6.5 3.2 Source: Estimated by the author. Benefits and costs are discounted at an annual rate of 10 percent. Table 14: Benefit-cost ratios for drinking water disinfection promotion, rural children u5 (boiling of water using fuel wood)


Benefit-Cost Ratios (w/o child nutrition benefits) Disinfection is sustained for 1 year 8.8 5.2 1.9 4.7 2.7 1.0 Disinfection is sustained for 2 years 13.2 8.5 3.4 7.0 4.5 1.8 Disinfection is sustained for 3 years 15.8 10.9 4.7 8.3 5.7 2.5 Benefit-Cost Ratios (w/ child nutrition benefits) Disinfection is sustained for 1 year 14.0 8.3 3.0 6.8 4.0 1.5 Disinfection is sustained for 2 years 21.0 13.6 5.4 10.2 6.6 2.6 Disinfection is sustained for 3 years 25.1 17.2 7.4 12.2 8.4 3.6 Source: Estimated by the author. Benefits and costs are discounted at an annual rate of 10 percent.

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A drinking water disinfection promotion program targeting children u5 may also induce disinfection practices for the population aged 5+ years, with or without additional program promotion cost. A CBA for this population is therefore also undertaken. In the case of no additional program costs, the BCRs for the population 5+ years of age ranges from 0.2-0.45 when valuing health benefits with the HCV and COI, and 0.35-0.85 when valuing health benefits with VSL and COI. The low end reflects use of LPG for boiling of water in urban areas, and the high end reflects use of fuel wood in rural areas.50 A promotion program may also be implemented that targets all population age groups (not only households with young children). If program cost per household is the same as the one targeting households with children, then the BCRs for the population 5+ years of age ranges from 0.1-0.4 when valuing health benefits with the HCV and COI, and 0.2-0.8 when valuing health benefits with VSL and COI. The low end reflects use of LPG for boiling of water in urban areas, disinfection sustained for only one year, and program cost at a “high” per person level as to induce 20 percent behavioral response rate. The high end reflects use of fuel wood in rural areas, disinfection sustained for three years, and program cost at a “low” per person level as to induce 10 percent response rate. The reason for the low BCRs for the population 5+ years of age is the much lower incidence of diarrheal disease and mortality in this population group than in children u5. Benefits from reducing the disease burden is therefore proportionately lower in the population 5+ years.

V. SUMMARY AND CONCLUSIONS

This paper has provided an assessment of benefits and costs of selected environmental health interventions to control PM outdoor air pollution, indoor air pollution from household use of solid fuels for cooking, and promotion of improved hand washing and household point-of-use drinking water disinfection. Benefit-cost ratios (BCRs) for control of outdoor air pollution were based on adjustments of BCRs from studies in other developing countries, while the BCRs for indoor air pollution and the hygiene and drinking water interventions were based on data and analysis from the Philippines. The assessment found BCRs in the range of 1.4 to 6.7 for PM control interventions, BCRs in the range of 0.1 to 19 for indoor air pollution control interventions in a range of household exposure conditions, BCRs in the range of 0.25 to 15 for hand washing promotion among various age groups in urban and rural areas, and BCRs in the range of 0.1 to 25 for drinking water disinfection by boiling of water with LPG or fuel wood among various age groups in urban and rural areas. While the BCRs cannot always be compared across the three environmental health risk areas, some observations can be made. First of all, BCRs should be seen in light of potential under- or over-estmation of benefits and costs. Secondly, it is useful to compare BCRs for various interventions by age groups. As to potential under- or over-estimation of benefits and costs, it may first be noted that estimated benefits of outdoor air pollution control are likely to be conservative as only

50 In this case, the BCR is independent of program response rate and period of sustained drinking water disinfection, and is determined solely by health benefits and private cost of boiling drinking water.

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two morbidity health-end points were included in Arcenas (2009) because of data limitations. Also, estimated benefits of hand washing did not include potentially substantial benefits associated with reduced respiratory infections. Nor was potential school performance and consequent life time income effects of child malnutrition from frequent diarrheal infections in early childhood considered in the CBA for hand washing and drinking water disinfection. As regards costs of interventions, uncertainty about soap consumption for hand washing was noted. Cost of LPG, in terms of fuel switching to control indoor air pollution and for boiling of water, is also uncertain, as it is greatly influenced by petroleum price movements in world markets. Valuation of health effects also has a great influence on the estimated BCRs. Two valuation techniques were applied to value mortality, while cost-of-illness (COI) was used for valuation of morbidity. The use of VSL for valuation mortality gives substantially higher BCRs than when the HCV is applied. For adults it was noted in the outdoor air pollution section that the HCV would likely represent a substantial underestimation of benefits of mortality reduction. The VSL calculated for the Philippines is consistent with a recent study of VSL in China (Krupnick, et al., 2006), and is calculated using a benefit transfer base value that is substantially lower than the USEPA is applying in CBA in the United States. The COI approach used for valuing morbidity is likely to represent a very conservative estimate of benefits of interventions. Studies in many countries have found that individuals’ willingness-to-pay (WTP) to avoid an episode of acute illness is generally much higher than the cost of treatment and time losses (Alberini and Krupnick, 2000; Cropper and Oates, 1992; Dickie and Gerking, 2002; Wilson, 2003). In terms of age groups, it is predominantly adults that would benefit from outdoor air pollution control. Adults would also benefit more than children in terms of mortality from indoor air pollution control, while children would benefit more in terms of morbidity. However, children would be the predominant beneficiaries of hand washing promotion and drinking water disinfection promotion. This emerges from the esimates of environmental health effects in he Philippines by Arcenas (2009) and is consistent with studies worldwide. Comparing the estimated BCRs of the outdoor and indoor air pollution control interventions assessed in this study, from which adults are expected to benefit significantly, it emerges that the BCRs for household use of improved wood stoves are higher than for almost all the outdoor air pollution control interventions, even in households with relatively good ventilation or cooking outdoors. BCRs of outdoor air pollution control interventions are however larger than the BCRs for switching to LPG even in households with poor ventilation and indoor cooking.51 It also emerges that the BCRs of the outdoor air pollution control interventions and indoor air pollution interventions (both improved wood stoves and switching to LPG) are substantially larger than the BCRs of hand washing and drinking water disinfection promotion for the population group 5+ years of age.52

51 The comparison is made for BCRs based on the same valuation techniques of health benefits, i.e., VSL for mortality and COI for morbidity. Good ventilation or outdoor cooking reflects a ventilation factor of 0.25 and poor ventilation and indoor cooking a factor of 1.00 in the indoor air pollution section. 52 Health benefits are valued using VSL and COI.

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For the protection of u5 children’s health, the BCRs are quite similar for improved wood stoves, and hand washing and drinking water disinfection promotion to mothers and caretakers of young children. If however, additional benefits are included, as discussed above, the BCRs for hand washing and drinking water disinfection may be higher than for improved stoves. The comparison is however not straight forward because BCRs for improved stoves are not estimated separately for children and adults.

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REFERENCES Alberini, A. and Krupnick, A., 2000: Cost-of-illness and willingness-to-pay estimates of the benefits of improved air quality: evidence from Taiwan. Land Economics, Vol 76: 37-53. Arcenas, A., 2009: Environmental health: economic costs of environmental damage and suggested priority interventions. A contribution to the Philippines Environmental Analysis. Prepared for the World Bank. Arnold, B. and Colford, JM., 2007: Treating water with chlorine at point-of-use to improve water quality and reduce child diarrhea in developing countries: a systematic review and meta-analysis. American Journal of Tropical Medicine and Hygiene, vol 76(2): 354-364. Blumberg, K., He, K., Zhou, Y., Liu, H., and Yamaguchi, N., 2006: Costs and benefits of reduced sulfur in China. The International Council on Clean Transportation. December 2006. www.theicct.org. Borghi, J., Guinness, L, Ouedraogo, J., and Curtis, V., 2002: Is hygiene promotion cost-effective? A case study in Burkino Faso. Tropical Medicine and International Health, Vol 7 No11. November 2002. Cairncross, S. and Valdmanis, V., 2006: Water supply, sanitation, and hygiene promotion. In: Disease control priorities in developing countries, second edition, chapter 41, 771-92. Oxford University Press and the World Bank. Clasen, T. and Haller, L., 2008: Water quality interventions to prevent diarrhea: cost and cost-effectiveness. Public Health and the Environment, World Health Organization. Geneve. Clasen, T., Schmidt, W-P., Rabie, T., Roberts, I., and Cairncross, S., 2007a: Interventions to improve water quality for preventing diarrhoea: systematic review and meta-analysis. British Medical Journal, 334:782-. Clasen, T., Haller, L., Walker, D., Bartram, J., and Cairncross, S., 2007b: Cost-effectiveness of water quality interventions for preventing diarrhoeal disease in developing countries. Journal of Water and Health, 5(4): 599-608. Cropper, M. and Oates, W., 1992: Environmental Economics: A Survey. Journal of Economic Literature, Vol. XXX, pp. 675-740. Curtis, V. and Cairncross, S., 2003: Effect of Washing Hands with Soap on Diarrhoea Risk in the Community: A Systematic Review. Lancet Infectious Diseases, vol 3:275-81.

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Daniels, M. and Adair, L., 2004: Growth in young Filipino children predicts schooling trajectories through high school. The Journal of Nutrition, 134: 1439-1446. Desai, MA., Mehta, S., and Smith, K., 2004: Indoor Smoke from Solid Fuels: Assessing the Environmental Burden of Disease at National and Local Levels. Environmental Burden of Disease Series, No. 4. World Health Organization. Dherani, M., Pope, D., Mascarenhas, M., Smith, K., Weber, M., and Bruce, N., 2008: Indoor air pollution from unprocessed solid fuel use and pneumonia risk in children aged under five years: a systematic review and meta-analysis. Bulletin of the World Health Organization, 86:390-98. Dickie, M. and Gerking, S., 2002: Willingness to pay for reduced morbidity. Presented at “Economic Valuation of Health for Environmental Policy: Assessing Alternative Approaches.” March 18-19, 2002, Orlando, Florida, USA. ECON, 2006: Urban air pollution control in Peru. Prepared for the Peru Environmental Analysis, World Bank. ECON Analysis, Oslo, Norway.

Fewtrell, L., Prüss-Üstün, A., Bos, R., Gore, F., and Bartram, J., 2007: Water, sanitation and hygiene: quantifying the health impact at national and local levels in countries with incomplete water supply and sanitation coverage. WHO Environmental Burden of Disease Series No. 15. World Health Organization, Geneva. Fewtrell, L., Kaufmann, R., Kay, D., Enanoria, W., Haller, L., and Colford, JM., 2005: Water, sanitation, and hygiene interventions to reduce diarrhoea in less developed countries: a systematic review and meta-analysis. Lancet Infectious Diseases, vol 5:42-52. Fishman, M.S., Caulfield, L.E., De Onis, M., Blossner, M., Hyder, A.A., Mullany, L., and Black, R.E., 2004: Childhood and maternal underweight. In Ezzati, M., Lopez, A.D., Rodgers, A., and Murray, C.J.L. (Eds): Comparative quantification of health risks – global and regional burden of disease attributable to selected major risk factors. Vol. 1. World Health Organization. Glewwe, P., Jacoby, HG., and King, EM., 2001: Early childhood nutrition and academic achievement: a longitudinal analysis. Journal of Public Economics, 81: 345-68. IEA, 2008: Petroleum product consumption at http://www.iea.org/ Textbase/ stats/ prodresult. asp?PRODUCT=Oil. Habermehl, H., 2007: Economic evaluation of the improved household cooking stove dissemination programme in Uganda. German GTZ. Haller, L., Hutton, G., and Bartram, J., 2007: Estimating the costs and health benefits of water and sanitation improvements at global level. Journal of Water and Health, vol 5(4): 467-80.

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Hutton, G., Haller, L., and Bartram, J., 2007: Global cost-benefit analysis of water supply and sanitation interventions. Journal of Water and Health, vol 5(4): 481-502. Hutton G, Rehfuess E, Tediosi F and Weiss S., 2006: Global cost-benefit analysis of household energy and health interventions. Department for the Protection of the Human Environment, World Health Organization. Krupnick, A., Hoffmann, S., Larsen, B., et al., 2006: The Willingness to pay for mortality risk reductions in Shanghai and Chongqing, China. Prepared for the World Bank. Larsen, B., 2008: Malnutrition and mortality from water, sanitation and hygiene in Cambodia, Lao PDR and Vietnam. Prepared for the Poverty-Environment Nexus Study, World Bank. Larsen, B., 2007a: A cost-benefit analysis of environmental health interventions in urban Greater Dakar, Senegal. Paper for the Senegal Country Environmental Analysis, World Bank. Prepared from ECON/Roche Canada. Larsen, B., 2007b: Cost-benefit analysis of water supply, sanitation and hygiene interventions in Mexico. Prepared for the World Bank. Larsen, B., 2007c: Cost of environmental health risk in children u5: Accounting for malnutrition in Ghana and Pakistan. Background report prepared for the World Bank. Environment Department, World Bank. Larsen, B., 2005: Cost-benefit analysis of environmental protection in Colombia. Prepared for the Ministry of Environment, Housing and Land Development. Background paper for the Colombia Country Environmental Analysis: Colombia Mitigating Environmental Degradation to Foster Growth and Reduce Inequality. World Bank. Larsen, B., 2003: Hygiene and health in developing countries: defining priorities through cost-benefit assessments. International Journal of Environmental Health Research, 13: S37-46. Larsen, B. and Strukova, E., 2006: A cost-benefit analysis of improved water supply, sanitation and hygiene and indoor air pollution control in Peru. Prepared for the Peru Country Environmental Analysis: Environmental Sustainability a Key to Poverty Reduction in Peru. June 2007. Luby, S., Agboatwalla, M., Feikin, D., Painter, J., Ward Billheimer, MS., Altaf, A., and Hoekstra, R., 2005: Effect of handwashing on child health: a randomised controlled trial. Lancet, 366: 225-33.

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Meddings, D., Ronald, L., Marion, S., Pinera, J., and Oppliger, A., 2004: Cost effectiveness of a latrine revision programme in Kabul, Afghanistan. Bulletin of the World Health Organization, 82(4): 281-89. Mehta S and Shahpar C., 2004: The Health Benefits of Interventions to Reduce Indoor Air Pollution from Solid Fuel Use: A Cost-Effectiveness Analysis. Energy for Sustainable Development. 8(3): p. 53-59. Mrozek, J. and Taylor, L., 2002: What Determines the Value of Life? A Meta Analysis. Journal of Policy Analysis and Management, Vol 21 (2): 253-270. NSO, 2005: Household energy consumption survey 2004. National Statistics Office, the Philippines. Pinfold, J. and Horan, N., 1996: Measuring the effect of a hygiene behaviour intervention by indicators of behaviour and diarrhoeal disease. Transactions of the Royal Society of Tropical Medicine and Hygiene, Vol 90. Rabie, T. and Curtis, V., 2006: Handwashing and risk of respiratory infections: a quantitative systematic review. Tropical Medicine and International Health, vol 11(3): 258-67. Saade, C., Bateman, M., and Bendahmane, D., 2001: The story of a successful public-private partnership in Central America: Handwashing for diarrheal disease prevention. Published by BASICS II, EHP, Unicef, USAID, and World Bank. Samson, R., Helwig, T., Stohl, D., De Maio, A., Duxbury, P., Mendoza, T., and Elepano, A., 2001: Strategies for enhancing biomass energy utilization in the Philippines. National Renewable Energy Laboraty, Colorado, USA. Shordt, K., and Cairncross, S., 2004: Sustainability of hygiene behaviour and the effectiveness of change interventions: Findings and implications for water and sanitation programmes from a multi-country research study. IRC International Water and Sanitation Centre. The Netherlands. Shrestha, R., Marseille, E., Kahn, J., et al., 2006: Cost-effectiveness of home based chlorination and safe water storage in reducing diarrhea among HIV-affected households in rural Uganda. American Journal of Hygiene and Tropical Medicine, 74(5): 884-90. Stevens, G., A. Wilson, and J. Hammitt, 2005: A benefit-cost analysis of retrofitting diesel vehicles with particulate filters in the Mexico City Metropolitan Area. Risk Analysis, 25(4): 883-899. Wilson, C., 2003: Empirical evidence showing the relationships between three approaches for pollution control. Environmental and Resource Economics, Vol 24: 97-101.

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Winrock International, 2005: Exploratory study on household energy practices, indoor air pollution and health perceptions in southern Philippines. Winrock International/USAID. WHO, 2002: World Health Report 2002. World Health Organization. World Bank, 2008: Environmental health and child survival: Epidemiology, economics, experiences. Washington DC. USA.

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The Philippines

Malnutrition related mortality from water, sanitation and hygiene

- accounting for the effect of diarrheal infections on child malnutrition

Prepared for the Philippines CEA

World Bank

by Bjorn Larsen53

Consultant Economist54

Health and Environment

November, 2008

53 The estimates of disease burden provided here follows the methodology in Larsen (2007) and World Bank (2008). 54 Author’s contact information: [email protected] or [email protected].

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1. Introduction Water, sanitation and hygiene (WSH) is directly and indirectly affecting population health. Directly, poor WSH causes diarrheal infections and other health effects which in turn lead to mortality especially in young children. Indirectly, poor WSH contributes to child malnutrition through the effect of diarrheal infections on nutritional status. Malnutrition, or poor nutritional status, increases the risk of child mortality from disease as well as increases the incidence of disease (Fishman et al., 2004).55 This indirect effect of WSH mainly affects children under the age of five years old. The approach used here to estimate the indirect health effects of WSH in children is as follows:

(a) the effect of diarrheal infections on children’s nutritional status is first determined from a review of the research literature;

(b) counterfactual nutritional status is then estimated, i.e., the nutritional status that would have prevailed in the absence of diarrheal infections; and

(c) health effects of currently observed nutritional status and health effects of counterfactual nutritional status are estimated.

The difference in health effects of observed vs counterfactual nutritional status is then the indirect health effects of diarrheal infections, caused largely by poor WSH. Commonly used indicators of poor nutritional status are underweight, stunting and wasting.56 Underweight is measured as weight-for-age (WA) relative to an international reference population.57 Stunting is measured as height-for-age (HA), and wasting is measured as weight-for-height (WH). Underweight is an indicator of chronic or acute malnutrition or a combination of both. Stunting is an indicator of chronic malnutrition, and wasting an indicator of acute malnutrition. Underweight status is most commonly used in assessing the risk of mortality and morbidity from poor nutritional status (Fishman et al, 2004). A child is defined as mildly underweight if his or her weight is in the range of -1 to -2 standard deviations (SD) below the weight of the median child in the international reference population, moderately underweight if the weight is in the range of -2 to -3 SDs, and severely underweight if the child’s weight is below -3 SD from the weight of the median child in the reference population. The standard deviations are also called z-scores and noted as WAZ (weight-for-age z-score).

55 Malnutrition and poor nutritional status is here used interchangeably. 56 Micronutrient deficiencies are not explicitly evaluated here, but are found in other studies to have a significant cost (World Bank, 2006; Horton and Ross, 2003; Horton, 1999). Also, Alderman and Behrman (2006) find a significant cost associated with low birth weight, which in part is caused by low maternal pre-pregnancy body mass index (Fishman et al, 2004). 57 The international reference population is defined by the National Center for Health Statistics (NCHS standard), United States or by the World Health Organization’s international reference population.

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Repeated infections, and especially diarrheal infections, have been found to significantly impair weight gains in young children. Studies documenting and quantifying this effect have been conducted in communities with a wide range of infection loads in a diverse group of countries such as Bangladesh (Black et al, 1984; Bairagi et al, 1987; Becker et al, 1991), Gambia (Rowland et al, 1977; Rowland et al, 1988), Guatemala (Martorell et al, 1975), Guinea-Bissau (Molbak et al, 1997), Indonesia (Kolsteren et al, 1997), Mexico (Condon-Paoloni et al, 1977), Peru (Checkley et al, 1997), Philippines (Adair et al, 1993), Sudan (Zumrawi et al, 1987), and Tanzania (Villamor et al, 2004). World Bank (2008) provides a review of these studies. These studies typically find that diarrheal infections impair weight gains in the range of 20-50 percent. A mid-point – i.e., 35 percent of children’s weight deficit - is here attributed to diarrheal infections to estimate the indirect disease burden from WSH (Larsen, 2007).58 So in the absence of weight retarding infections, the weight-for-age z-score (WAZ) of an underweight child would be approximately 40 percent greater than the observed z-score (i.e., observed WAZ*(1-0.4)).59 For instance, if a child has a WAZ=-3, then in the absence of weight retarding infections, the child’s WAZ would be -1.8. 2. Nutritional Status Prevalence of underweight malnutrition rates in the Philippines are presented in table 1. Current rates are for the most recent year available. Prevalence of mild underweight is no officially reported. Mild underweight is however important in relation to increased risk of child mortality (Fishman et al., 2004). This rate was therefore estimated based on international comparisons. Counterfactual prevalence rates of underweight, i.e., prevalence rates in the absence of weight retarding infections where estimated based on estimations from comparator countries in Asia for which original survey data of child nutritional status are available. This was performed through the following procedure: Counterfactual WA z-scores were calculated for each underweight child in household survey using the formula discussed above (i.e., WAZ reported for each child in the survey multiplied by (1-0.4)). Counterfactual underweight prevalence rates were then tabulated using the counterfactual WA z-scores. The results are presented in table 1. In the absence of diarrheal infections, it is estimated that practically no children would be severely underweight and the prevalence of moderate underweight would be as low as 2 percent. The prevalence of mild underweight would increase somewhat as child nutrition status would change from severe/moderate underweight to mild underweight.

58 A child’s weight deficit is the difference in weight between the child’s observed weight and the weight of the median child in the international reference population. 59 This is calculated using the WHO Anthro 2005 software.

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Table 1 Current and estimated counterfactual underweight prevalence rates in children u5 Philippines

Current prevalence rates Severe underweight ( < - 3 SD) 8.8%* Moderate underweight (-2 to -3 SD) 19.2%* Mild underweight (-1 to -2 SD) 29.3%* Non-underweight ( > -1 SD 42.7%*

Counterfactual prevalence rates Severe underweight ( < - 3 SD) 0.10% Moderate underweight (-2 to -3 SD) 2.0% Mild underweight (-1 to -2 SD) 32.0% Non-underweight ( > -1 SD 65.9% Source: Current prevalence rate of underweight malnutrition is from Philippines National Nutrition Surveys 2003 (ENRI). * Moderate and severe underweight prevalence combined was 28% in the Philippines, and is not reported separately. Nor is the prevalence of mild underweight reported. Distribution of mild, moderate and severe underweight is therefore estimated by international comparison. 3. Health Effects of Poor Nutritional Status Various health and debilitating effects from malnutrition are documented in the research literature. This includes long term chronic illnesses from low birth weight, effects of iodine, vitamin and iron deficiencies, and impaired cognitive development (United Nations, 2004; World Bank, 2006). The focus here is on mortality in children < 5 years associated with underweight. Fishman et al (2004) present estimates of increased risk of cause-specific mortality and all-cause mortality in children u5 with mild, moderate and severe underweight from a review of available studies. Severely underweight children (WA < -3 SD) are five times more likely to die from measles, eight times more likely to die from ALRI, nearly 10 times more likely to die from malaria, and twelve times more likely to die from diarrhea than non-underweight children (WA > - 1 SD). Even mild underweight doubles the risk of death from major diseases in early childhood (table 2). Table 2 Relative risk of mortality from mild, moderate and severe underweight in children u5

Weight-for-age (WA) < - 3 SD -2 to -3 SD -1 to -2 SD > - 1 SD Pneumonia/ALRI 8.1 4.0 2.0 1.0 Diarrhea 12.5 5.4 2.3 1.0 Measles 5.2 3.0 1.7 1.0 Malaria 9.5 4.5 2.1 1.0 Other causes of mortality* 8.7 4.2 2.1 1.0 Source: Fishman et al (2004). * Only other infectious diseases are included here (see Fewtrell et al, 2007).

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4. Estimating the Health Effects of WSH These relative risk ratios can be applied to the underweight prevalence rates in table 1 to estimate attributable fractions (AF) of mortality from diarrheal infections through their effect on nutritional status (underweight status).60 The following formula is used to calculate attributable fractions of mortality from ALRI, measles, malaria, and “other infectious diseases” indirectly caused by diarrheal infections:

∑

∑∑

=

==

−= n

iii

n

ii

Ci

n

iii

RRP

RRPRRPAF

1

11 (1)

where RRi is relative risk of mortality for each of the WA categories (i) in table 2; Pi is the current underweight prevalence rate in each of the WA categories (i); and Pi

c is the counterfactual underweight prevalence rate in each of the WA categories (i). This formula is also called the “potential impact fraction” because it estimates the mortality that would have been avoided for a different counterfactual population distribution (e.g., less children being underweight) exposed to those levels of risk of mortality. For a further discussion of this formula, see Ezzati et al. (2004). For diarrheal mortality the AF estimation procedure would be different because there are two risk factors, i.e. the direct effect of WSH and the indirect effect through malnutrition. As already 88 percent of diarrheal infections and mortality is estimated to originate from WSH, the additional effect of malnutrition is minimal and is therefore ignored here.61 Annual cases of mortality from diarrheal infections caused by poor WSH, through the effect of infections on nutritional status, are estimated as follows:

∑=

=

=mj

jjj MAFcM

1

0 (2)

where AFj is the AF in eq. (1) for each cause of mortality “j”, Mj

0 is the current total annual cases of mortality in each of the categories in table 2, and “c” is the fraction of diarrheal infections caused by poor WSH (86.3% estimated for the Philippines from the Philippines DHS 2003). Most recent available estimates of annual cases of mortality (Mj

0) in children under-5 are presented in table 3. These estimates reflect u5 child mortality rates in 2003, and the structure of cause-specific deaths is estimated from WHO country estimates of cause-specific mortality in 2002 (WHO, 2004). 60 The attributable fraction of mortality from malnutrition is the percent of deaths (e.g., percent of ALRI deaths) caused by malnutrition. 61 See Larsen (2007) and World Bank (2008) for methodology and estimation of environmental health effects from multiple environmental risk factors in Ghana and Pakistan.

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Table 3 Estimated cause-specific annual deaths in children < 5 years in 2003 Philippines Diarrheal disease 10,700 ALRI 12,600 Measles 2,900 Malaria 400 PEM 1,100 LBW 8,600 Other perinatal conditions 16,500 Other infectious and parasitic 3,200 Other causes 18,500 Total 74,500 Source: Adjusted to 2003 from WHO country estimates of mortality by cause in 2002 (WHO, 2004), by applying child mortality rate in 2003. Table 4 Demographic and mortality data in 2005 Philippines Mortality rate, under-5 (per 1,000) 36 Population, total 81,172,000 Estimated annual births 2,069,886 Source: World Bank (2007) and Country population statistics. Applying equation (2) to the cases of mortality in table 3 provides an estimate of malnutrition related mortality from poor WSH (table 5). Mortality in children from protein-energy malnutrition (PEM) is estimated separately using the methodology in Fishman et al. (2004) and attributing a fraction of this mortality to WSH in proportion to the effect of diarrheal infections on malnutrition. In total, child mortality attributable to WSH from malnutrition (i.e., the indirect effect of infections through malnutrition) constitutes over 7,600 deaths per year, or over 10 percent of total u5 child mortality. Table 5 Estimated annual malnutrition related mortality in children u5 from poor WSH in 2003 Philippines ALRI 4828 Measles 880 Malaria 164 PEM 475 Other infectious diseases 1269 TOTAL 7616

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