Country Presentation:Country Presentation:Experience on the HIAExperience on the HIA

Dr Stefan MaEpidemiology & Disease Control Division

1st Health Impact Assessment for ASEAN Workshop“Understanding Health Impact Assessment (HIT): A Foundation for the Well-being of the ASEAN Community”13-14 February 2012, Phuket Thailand

Case Study

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Study On The Effects And Impacts Of Global Climate Change On Singapore

Phase 1 Study

• To study, analyze and project the effect of climate change and sea level rise on Singapore over the next 100 years.

• Focus: Impact and vulnerability.• Adaptation measures are NOT included.

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Scope of Phase 1 Study

• Climate: Rainfall, Temperature, Winds • Regional Coastal Hydrodynamics• Coastal Erosion• Land Loss due to Submergence / Erosion• Saline Water Intrusion• Drainage Network System• Slope Stability• Land Cover Mapping and Study of Temporal

Variations of Environmental Parameters Using Satellite Data

Phase 2 Study

• Biodiversity & greenery

• Energy demand & Urban infrastructure

• Public Health

Biodiversity & greenery• Study to map all slopes with biodiversity and

greenery

• Preparedness (in terms of vulnerabilities/adaptations to impacts on biodiversity, greenery and landforms on which they occur)

Energy demand & Urban infrastructure

• Study of effect of temperature change on sectoral energy demand

Public Health

• Study of impacts of climate change on the following identified public health issues:

• Dengue fever

• Health disorders

• Respiratory diseases, e.g. air pollution, asthma

• Vulnerabilities and Adaptations

Risk Assessment Plan

• In-depth literature review and research strategy planning

• Establish models and analyze influencing factors• Project long-term climate changes on studied public

health issues

Health impact of air Health impact of air pollution in Singaporepollution in Singapore

A study of the short-term effects of A study of the short-term effects of air pollution on morbidity and air pollution on morbidity and mortality in Singapore using local mortality in Singapore using local daily time-series health and air daily time-series health and air quality dataquality data

DataData• Death data:• Extracted individual cases of death from the data

provided by RBD for the years 1994 to 2005.• There were a total of 174,323, 31,804, and 67,396

registered deaths for all causes (non-accidental), respiratory diseases, and cardiovascular diseases, respectively, during the period (outcome variables).

• The daily death counts were aggregated based on date of death in each case and cause of death (in ICD-9 codes).

DataData• Hospital admission data:• Also extracted individual cases of hospitalizations

from the Central Claims Processing System (CCPS) database maintained by MOH for the years 1994 to 2005.

• There were a total of 400,224 and 474,952 hospitalizations for respiratory diseases and cardiovascular diseases, respectively, during the period (outcome variables).

• The daily admission counts were aggregated based on date of admission and discharge diagnosis (in ICD-9 CM codes).

DataData• Pollution data:• Daily instead of hourly concentrations of 6 air

pollutants measured by 30 monitoring stations provided by the Pollution Control Department of the NEA.

• Excluded 5 stations which monitor kerbside air quality by sampling air very close to the outermost traffic lane, from the study.

• This is because the concentration measured is not representative of the exposure of the general population.

DataData• Pollution data:

DataData• Meteorological data:• Obtained daily means of dry bulb temperature, dew

point temperature, relative humidity and wind speed, and daily totals of rainfall by monitoring station from years 1994 to 2005 from the Meteorological Services Division of NEA.

• Selected 5 stations located as close as possible to some of the air pollution monitoring sites.

MethodologyMethodology• Method is in line with that recommended by the

APHEA (Air Pollution and Health: a European Approach).

• This approach is based on development of a Core Model, using smoothing function with different windows and fitting linear and non-linear terms until no patterns and no auto-correlations are found in the residuals.

• The core model is to model daily counts by a set of covariates as close as possible.

• log(expected daily counts) = [Core Model: Trends + Seasonality + Meteorological variables + ...] + Pollutant levels

• Estimate effects of air pollution on health by adding pollutant variable into the core model.

MethodologyMethodology• Health effects were obtained per 10 g/m3

change in pollutant levels (per 0.1 mg/m3 change for CO) measured by current day and up to previous 3 days, called the best lagged day, to be determined by Akaike’s Information Criterion (AIC) with the minimum value.

• Health effects due to co-pollutants were estimated by putting the other pollutants one by one in the model. Effect with adjustment for a co-pollutant which was associated with the maximum adjustment was used.

MethodologyMethodology• Single pollutant model:• A model for each health outcome was fitted with

terms to account for all long-term and seasonal patterns and other possible confounding effects.

• Short-term daily variations were then studied and accounted for by daily variable in NO2, SO2, O3, PM10, PM2.5 and CO individually, based on data from Jan 1994 to Dec 2005. For PM2.5, measurements are only available from Jan 1998 onwards.

MethodologyMethodology• Co-pollutant model:• From each single pollutant model, the joint

effects of each pollutant with other pollutants were studied by putting them one by one in the model.

• Temporal patterns – Air pollutants

• Temporal patterns - mortality

• Temporal patterns – hospital admissions

SARS outbreak

• Exposure-response relationships of PM on mortality

• Exposure-response relationships of PM on hospitalisation admissions

ResultsResults • The estimates of excess daily risk, in all ages, showed

that an increase of 10 g/m3 concentration was associated with a 2.14% and 1.06% increase in respiratory deaths and respiratory admissions, respectively for PM2.5; 0.76% and 0.38% increase in cardiovascular deaths and respiratory admissions, respectively for PM10; and 0.57% and 0.83% increase in all non-accidental and cardiovascular deaths, respectively; and 0.65% increase in respiratory admissions for O3.

• Based on the risk of PM2.5 pollutant estimated from the database for the period 1994-2005, the excess number of respiratory deaths and respiratory hospital admissions attributable to each 10 g/m3 change in concentration of the pollutant would be 57 [95% confidence interval: (4, 110)] deaths and 354 respiratory admissions (130, 580) a year, respectively.

ConclusionsConclusions • The results from this study showed

detrimental short-term effects of air pollutants on health.

• NO2, SO2, and CO did not reach statistical significance.

• PM2.5 had impact on respiratory health (both deaths and hospital admissions).

• PM10 had effects on cardiovascular deaths and respiratory admissions.

• O3 had effects on all cause (non-accidental) and cardiovascular deaths and respiratory admissions.

• The excess number of health events attributable to each specific air pollutant is defined as the total number of health events multiplied by the excess risk.

• Mass intervention would reduce the level of multiple pollutants. Hence, the overall health gains could be even higher than that estimated from a single pollutant intervention.

Impact of pollution controlImpact of pollution control

• Comparison with other cities – mortality Mortality Singapore Hong Kong Asian cities 29 European cities 90 USA citiesNon-accidental

NO2 0.51 (-0.26,1.28) 0.64 (0.36,0.91)

SO2 0.60 (-0.03,1.23) 1.36 (0.92,1.78) 0.52 (0.30,0.74)

O3 0.57 (0.13,1.00) -0.11 (-0.37,0.16)

PM10 0.11 (-0.32,0.54) 0.24 (0.01,0.46) 0.49 (0.23,0.76) 0.62 (0.4,0.8) 0.41 (0.20,0.53)

Respiratory

NO2 0.27 (-1.54,2.12) 0.81 (0.24,1.38)

SO2 0.93 (-0.54,2.41) 1.62 (0.77,2.48)

O3 0.60 (-0.37,1.58) 0.62 (0.09,1.16)

PM10 0.24 (-0.76,1.26) 0.40 (-0.05,0.85)

Cardiovascular

NO2 1.27 (-0.17,2.72) 0.94 (0.44,1.44)

SO2 0.89 (-0.14,1.94) 1.61 (0.78,2.44)

O3 0.83 (0.08,1.60) -0.16 (-0.65,0.33)

PM10 0.76 (0.07,1.44) 0.37 (-0.03,0.77)

ER (95% CI)

• Comparison with other cities – hospital admissions Hospitalisation Singapore Hong Kong Asian cities

Respiratory

NO2 0.60 (-0.10,1.31) 0.54 (0.27,0.80) 0.95 (-0.05,1.94)

SO2 0.40 (-0.13,0.94) 0.76 (0.34,1.18) 0.16 (-0.46,0.77)

O3 0.65 (0.25,1.06) 0.55 (0.31,0.79)

PM10 0.38 (0.02,0.75) 0.50 (0.28,0.71)

CardiovascularNO2 0.19 (-0.45,0.83) 0.73 (0.48,0.98)

SO2 0.08 (-0.39,0.56) 1.08 (0.72,1.44)

O3 -0.05 (-0.42,0.32) 0.24 (0.01,0.47)

PM10 0.10 (-0.22,0.43) 0.37 (0.18,0.57)

ER (95% CI)

Burden of disease Burden of disease attributable to air attributable to air pollution in Singaporepollution in Singapore

Our estimates for urban air Our estimates for urban air pollution were based on long-pollution were based on long-term exposures and had term exposures and had considered mortality only.considered mortality only.

Singapore Burden of Disease in 2007

Burden of Disease by Broad Cause Group, Singapore 2007

• Total DALYs in 2007 = 393,229

• Highest disease burden – Cardiovascular diseases, followed by cancers, accounting for 37% of total DALYs

• Neurological, vision and hearing disorders, mental disorders and diabetes – another 34% of total DALYs

Notes: DALY refers to disability-adjusted life year.Musculoskeletal diseases include rheumatoid arthritis, osteoarthritis, low back pain and gout.

0 5000 10000 15000 20000 25000 30000 35000 40000 45000 50000

YLL YLD

High body mass

Cigarette smoking

High blood pressure

High blood cholesterol

Physical inactivity

Low fruit & vegetable consumption

Urban air pollution

Alcohol consumption

Occupational exposures & hazards

11.1%

7.4%

7.3%

6.6%

3.8%

2.7%

1.8%

1.3%

1.2%

0.3%

<0.01%

High dietary trans fatty acidsLow dietary poly-unsaturated fatty acids (PUFA)

DALYs

0 5000 10000 15000 20000 25000 30000 35000 40000 45000 50000

YLL YLD

High body mass

Cigarette smoking

High blood pressure

High blood cholesterol

Physical inactivity

Low fruit & vegetable consumption

Urban air pollution

Alcohol consumption

Occupational exposures & hazards

11.1%

7.4%

7.3%

6.6%

3.8%

2.7%

1.8%

1.3%

1.2%

0.3%

<0.01%

High dietary trans fatty acidsLow dietary poly-unsaturated fatty acids (PUFA)

DALYs

Percentage refers to the proportion of disease burden (in DALYs) contributed by the respective risk

29.0%

Burden of Disease by 11 Key Risk Factors, Singapore, 2007

Broad Cause GroupBroad Cause Group

All CausesAll CausesCVD Cancers Mental

Neuro-logical & sense

Injuries Diabetes Other

Total burden (in DALYs) 75707 70980 44437 52299 22380 39274 88151 393229

Attributable burden (%)(a)

High body mass 17.0% 3.3% - - - 69.4% 1.4% 11.1%

Cigarette smoking 11.3% 22.6% - 0.1% 0.1% - 5.0% 7.4%

High blood pressure 37.8% - - - - - - 7.3%

High blood cholesterol 34.2% - - - - - - 6.6%

Physical inactivity 12.0% 3.0% - - - 9.8% - 3.8%

Low fruit & vegetable consumption

11.8% 2.5% - - - - - 2.7%

Urban air pollution 6.3% 1.8% - - - - 1.3% 1.8%

Alcohol consumption

Harmful effects 0.2% 1.3% 3.6% - 13.5% - - 1.4%

Beneficial effects -1.0% - - - - - - -0.2%

Net effects -0.8% 1.3% 3.6% 0.0% 13.5% 0.0% 0.0% 1.3%

Occupational exposures & hazards

0.5% 1.8% - 2.2% 2.8% - 1.6% 1.2%

High dietary trans fat acids 1.3% - - 0.3%

Low dietary poly-unsaturated fatty acids

0.1% - - - - - - 0.0%

Joint effect (%) 64.3% 32.1% 3.6% 2.3% 15.9% 72.4% 8.8% 29.0%

Individual and Joint Burden (DALYs) Attributable to 11 Risk Factors, 2007

• About 2% of the total burden of disease (i.e. more than 7,000 DALYs were lost) was attributable to urban air pollution (i.e. PM10 and PM2.5) exposures in Singapore in 2007.

• 58% of the burden from urban air pollution was due to cardiovascular disease (ischaemic heart disease and stroke) and about another 18% was due to lung cancer. 6% cent of the burden from urban air pollution was experienced by males (data not shown).

• Compared with other risk factors, urban air pollution ranked 7th.

Disease Burden due to Urban Air Pollution(PM10 and PM2.5) in 2007

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