indoor air pollution in rural indian households: predicting exposures and cost-effective...
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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.