Indoor Air Pollution in Rural Indian

Households:

Predicting Exposures and Cost-Effective Interventions

Sumi Mehta, MPH, Ph.D

Overview

• Background/health effects of indoor air pollution (IAP)

• Predicting household concentrations in Andhra Pradesh,

India

• Choosing interventions: cleaner fuels vs. improved

ventilation and health

IAP = Solid fuels + Limited Ventilation

• Cooking and heating with solid fuels, including dung, wood, agricultural residues, and coal, is likely to be the largest traditional source of indoor air pollution (IAP) on a global scale.

– Around half of the world cooks with solid fuels, including more than 75% of India and China, and 50-75% in South America and Africa.

– Health damaging pollutants in the smoke include respirable particles, carbon monoxide, nitrogen and sulfur oxides, and benzene

– Exposures can be many times greater than WHO guidelines, and much higher than outdoor levels in cities with the highest air pollution levels.

– Women and young children are likely to have the highest burdens of exposure.

Health Effects of IAP from Solid Fuels

WeakChildrenAsthma

Ischaemic Heart Disease

Blindness (Cataracts)

Tuberculosis

Lung Cancer (coal only)

Chronic Obstructive Pulmonary Disease (COPD)

Acute Respiratory Illness (ARI)

Illness

SuggestiveWomen >15

ModerateWomen >15

ModerateWomen >15

Strong*Women >15

Strong*Adults >15

Strong*Children <5

EvidencePopulation

Health Effects

Currently, indoor smoke from solid fuels causes an estimated 1.6 million deaths each year (37.5% of LRI, 22.0% of COPD, and 1.5% of lung cancers).

The vast majority of deaths occur from LRI in young children under five years of age.

2.7% of the entire global burden of disease (loss of healthy life due to death or illness) is attributable to indoor smoke from solid fuels.

Over 30% of this burden is borne by the people of Africa and South/Southeast Asia

LRI Deaths From Solid Fuel Use in Children Under Five, 2000

0 20 40 60 80 100 120 140 160 180

WPR B

WPR A

SEAR D

SEAR B

EUR C

EUR B

EUR A

EMR D

EMR B

AMR D

AMR B

AMR A

AFR E

AFR D

Deaths in Thousands

Female

Male

How does this compare with other risk factors on a global scale?

% of total burden Deaths (millions)

Underweight 9.5 3.7

Unsafe sex 6.3 2.9

Blood pressure 4.4 7.1

Tobacco 4.1 4.9

Alcohol 4.0 1.8

Unsafe water/ sanitation 3.7 1.7

Cholesterol 2.8 4.4

I ndoor smoke 2.7 1.6

I ron def iciency 2.4 0.84

Overweight 2.2 2.6

~ 80% of Indian households cook with solid fuels

(1991 Census of India)

1. How can we quickly and cheaply identify households likely to have the highest exposures?

– How can we create refined regional and national exposure profiles with a minimal amount of air sampling?

– How do differences in housing/ventilation affect exposures?

– Can household characteristics be used to predict exposures?

2. What should be done to reduce exposures?

– What are possible strategies to reduce exposure?

– Choosing interventions that are cost-effective

03 = Warangal District20 = Rangareddy District22 = Nizamabad District

Predicting household concentrations in Andhra Pradesh, India

Brief Methodology

1) A household questionnaire is administered to collect information on housing type, kitchen type, stove type, ventilation, and other factors thought to be related to indoor air pollution. (IHS, Hyderabad)

2) Using respirable particulate matter as an indicator pollutant, 420 households are monitored for daily average concentrations of indoor air pollution in the kitchen and living areas and a subset is monitored on a real-time basis. (SRMC&RI, Chennai)

3) Models to predict concentrations based on housing characteristics are developed. (UC Berkeley)

Qualitative Exposure Assessment: Household Characteristics

• Information that parallels demographic surveys (Census and the National Family Health Survey)– Main cooking fuel– Housing materials

• Information on household characteristics not well characterized in demographic health surveys– Kitchen type – Mixed fuel use – Household ventilation– Fuel source, collection time, price, quantity

Quantitative Exposure Assessment: Respirable Particulate Matter

• Why sample for respirable particulate matter?– PM is an indicator pollutant often used in air pollution and

health research– Focus on combustion particles (bulk <1 μm)– Gradual cutoff (mean particle size range from 2–10 μm,

median 4 μm) useful for some human respiratory health hazards (excludes particles in same way airways prevent particles from reaching alveolar region)

• Average daily concentrations of respirable particulate matter– Kitchen– Living Area

Predictor Variables Used in Modeling

Description Values Kitchen concentration 0 = low

1 = high Living area concentration 0 = low

1 = high Cooking fuel 1 = wood

2 = mixed fuel 3 = kerosene or gas*

Kitchen type 1 = indoor with partition 2 = indoor without partition 3 = separate indoor kitchen outside the house 4 = open air kitchen outside the house*

Separate kitchen 0 = no separate kitchen 1 = separate kitchen*

Kitchen ventilation 1 = poor 2 = moderate 3 = good*

Time main cook spends cooking continuous variable Wall type 0 = kachcha

1 = pucca Floor type 0 = kachcha

1 = pucca Number of kitchen openings 0 = 0

1 = 1 2 = >1

Predicting Kitchen Concentrations

HOUSEHOLD CHARACTERISTIC ODDS RATIO (OR)

95% CI†

FUEL TYPE WOOD 28.2 (6.5, 121.6) MIXED 62.8 (13.6, 289.8) KEROSENE OR LPG 1.0 * -

KITCHEN TYPE INDOOR KITCHEN WITH PARTITION 3.4 (1.4, 8.2) INDOOR KITCHEN WITHOUT PARTITION

4.6 (1.8, 11.6)

SEPARATE INDOOR KITCHEN OUTSIDE THE HOUSE

4.1 (1.8, 9.6)

OUTDOOR KITCHEN 1.0 * - VENTILATION

POOR 2.3 (1.0, 5.0) MODERATE 1.1 (0.5, 2.3) GOOD 1.0 * -

*Reference Category† 95% Confidence Interval for the Odds Ratio

CART Kitchen Area Predictions

Low: 143High: 199

Low: 87High: 178

Low: 56High: 21

Low: 41High: 2

Low: 184High: 201

Fuel type = kerosene or gas

Fuel type = wood or mixed

Outdoorkitchen

Indoor Kitchen

Low: 143High: 199

Low: 87High: 178

Low: 56High: 21

Low: 41High: 2

Low: 184High: 201

Fuel type = kerosene or gas

Fuel type = wood or mixed

Outdoorkitchen

Indoor Kitchen

KEY TO CLASSIFICATION: High Concentration Low Concentration

Kitchen Concentrations: Summary

• Fuel type– Best predictor of high concentrations, but poor predictor of

low concentrations– Wide range of concentrations within fuel categories

• Kitchen type– Indoor kitchens more likely to have high concentrations

than outdoor kitchens

• Ventilation– Households with good kitchen ventilation are much less

likely to have high concentrations

Implications

• Fuel use the most important predictor of household air pollution

• Not all solid fuel using households experience high exposures, however

• Targeting ventilation can reduce exposure within solid fuel using households:– Improve ventilation in kitchen / housing (locally

appropriate interventions)– Improved stoves that vent to the outside

Internal Model Validation

Consistency: Same variables significant across CART and regression models

Stability: Results consistent across different high/low concentration cut-points

Cross Validation: Bootstrap aggregation (average of 50 re-samplings of data) did not improve model, suggesting model stability

External Model Validation: Tamil Nadu

% Predicted Accurately

Parameters utilized by

CART

Low Concentration High Concentration

Fuel type

Andhra

Pradesh 22% 99%

Tamil Nadu 30% 100%

Fuel type + Kitchen

Type

Andhra

Pradesh 53% 89%

Tamil Nadu 72% 95%

External Model Validation: Tamil Nadu

• The model performs even better on the Tamil Nadu data, where monitoring was conducted during cooking times

model could be used to identify households where cooks are likely to have higher exposures

differences in housing characteristics could influence peak exposures more than average exposures

• Future steps: Conduct similar modeling exercises in other regions (differences in climate, housing, cooking practices, fuel use)

An Indicator for Indoor Air Pollution

• ‘Access to water and sanitation’• Widely accepted household environmental health

indicator • Systematically collected at reported at regional and

national levels

• ‘Access to clean fuel and ventilation’

• The indoor air pollution parallel• Assessing kitchen type and / or kitchen ventilation is

low cost, easy to collect• Indicator of potential for increased exposure, not actual

household concentrations

Cost Effectiveness AnalysisMethodology developed by the World Health Organization WHO – CHOICE: CHOosing Interventions that are Cost-Effectivewww.who.int/evidence/cea

• Examine results for IAP using methodology consistent with other risk factors and diseases

• Sectoral, population-level cost-effectiveness analysis (CEA)

Enhances comparability between interventions 14 distinct epidemiological sub-regions - available for country-level

adaptation / analysis Effectiveness: DALYs averted (accounting for coverage and adherence)

• Results here are for WHO Region SEAR D (India comprises ~80% of this region)

Interventions addressed

– Cleaner fuels• LPG / Propane• Kerosene / Paraffin

– Improved ventilation (improved stoves)– Combined intervention scenario

• 50% cleaner fuels• remainder improved stoves

Cost Effectiveness Analysis: Effectiveness

Exposed Population = (Population using solid fuel)x(Ventilation Factor)

• Efficacy estimates based on meta-analyses of epidemiologic literature

• Assume improved stoves result in ventilation factor of 0.25

Lower Respiratory Infections (LRI)• reduction of LRI in young children < 5• RR = 2.3 (CI 95%: 1.9, 2.7)

Chronic Obstructive Pulmonary Disease (COPD)• decreased severity, postponed incidence of COPD in

nonsmoking adults• RR = 3.2 (CI 95%: 2.3, 4.8) women • RR = 1.8 (CI 95% 1.0, 3.2) men

Cost Effectiveness Analysis: Costs

• User and programme level costs included• Ingredients approach (separate specification of

quantities and prices)• Include training and maintenance components

– This is crucial for sustainability of improved stove programs!

Cost Effectiveness Analysis: Costs

Average annual cost in Sear D (‘000 International Dollars)

Propane /

LPG

Paraffi n /

Kerosene

Improved

Stoves

Cooking System*

16,031,000 2,988,000 852,000

Program Costs 27,600 27,600 80,200

Total 16,058,600 3,015,600 932,200

Cost Per

Household 90 20 5

*includes stove, cylinder (for Propane / LPG), fuel

Cost Effectiveness Analysis: Effectiveness Average annual healthy years gained in Sear D*

Cleaner Fuels 2,186,000

I mproved Stoves 1,516,000

Combined I ntervention 2,013,000

*discounted 3%, age weighted

Cost Effectiveness Ratios (CER) for Sear D

Intervention CER

(I$/healthy year gained)

LPG / Propane 7,350

Kerosene / Paraffin 1,380

Improved Stoves 610

Combination: LPG and improved stoves

4,280

Combination: kerosene and improved stoves

1,040

Limitations and Considerations:

• Kerosene will appear consistently more cost-effective than liquid petroleum gas (LPG) because it is cheaper. – concerns about kerosene use, including poisoning and possible

carcinogenic effects, should be carefully considered before recommending its use

• Effectiveness of improved stoves is dependent on proper training and maintenance.

• Intended for health policy decision makers, this focuses on health benefits alone. Other key non-health benefits include:– time savings– reduction of women’s drudgery– community development (improved stove programs)– longer term implications for climate change

Policy Implications

• People need access to cleaner fuels and improved

ventilation

• While cleaner fuels offer more benefits than improved

ventilation, it may be more feasible to reduce exposures

through improved ventilation in the short run, until the

longer-term goal of providing everyone with access to

cleaner fuels can be attained.