Comparative Risk Assessment and the Burden of Disease from ...
Transcript of Comparative Risk Assessment and the Burden of Disease from ...
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UCB - KR Smith et al
Comparative Risk Assessment and
the Burden of Disease from Indoor Air Pollution
Kirk R. Smith, Sumi MehtaUniversity of California, Berkeley
Mirjam FeuzSwiss Federal Office of Public Health, Basel
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How Much Ill-Health is Attributable to Air Pollution?
Need to define:• Ill-health• Attributable• Air pollution
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Only recently there has been a C4 Database for health
• Complete– Much of the world was unrepresented– Many important disabilities were unaccounted
• Consistent definitions of disease states • Coherent
– Deaths by disease add to total– Statistics match by age and sex
• Combined mortality and morbidity
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Combined Measure of Ill-health
• Death is most common– Easy to determine– Commonly tabulated
• Severe problems– Everyone dies– Health never achieved– Age is clearly important
• Deaths + Disability = ?
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Combined Measure
• Most fundamental deprivation is loss of time: life length shared by all humans
• Can be used for disabilities, but need to weight relative severity of disabilities
• Other issues common to any measure– Count impacts differently in different groups?
• No, only age and sex counts– What about impacts in different times?
• 3% discount rate applied
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UCB - KR Smith et al
Quality Adjusted Life YearsQALY
• Basically the number of fully healthy life years lost to a particular disease or risk factor.
• Considers the age at which the disease or death occurs and the duration and severity of any disability created.
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Global Burden of Disease Database
• Developed at Harvard University originally for the World Bank
• Extended greatly in the mid-1990s and now adopted by the World Health Organization
• Dozens of countries, states, and cities now have National Burdens of Disease
• Uses a variation of QALY, the DALY
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UCB - KR Smith et al
World - Deaths
0 2 4 6 8 10 12 14
Malaria
Road Traffic
Child Cluster
TB
Diarrhea
Perinatal
HIV
COPD
ARI
Stroke
Cancer
Heart
Percent of Total
2000
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World - DALYs
0 2 4 6 8
Falls
TB
COPD
Road Traffic
Malaria
Malnutrition
Stroke
Child Cluster
Heart
Diarrhea
Depression
Cancer
HIV
Perinatal
ARI
Percent of Total
2000
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UCB - KR Smith et al
Characteristics of Attributable Risk
• All attributable risks for a disease often add up to much more than 100%
• Size of attributable risk for a particular risk factor depends on order that different factors are examined
• Presumes the existence of a feasible intervention (counterfactual level) to lower exposure.
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UCB - KR Smith et al
840,000ARI Deaths in
Children Under 5
Case-management65% Vaccines
25%
Measles10%
Diarrhea20%
Breastfeeding10%
Malnutrition35%Better Housing
40%
Air Pollution30%
Attributable Risks
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UCB - KR Smith et al
Malnutrition
AlcoholTobacco
Illicit Drugs
Unsafe Sex/Unwanted PregnancyHypertension
Physical Inactivity
Water/sanitationAir PollutionOccupation
0 5 10 15 20
Percent of Total
Major Risk FactorsDraft Revision of 1990 Estimates: WHO, 1999
Global Burden of Disease in 1995
80% Indoor
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UCB - KR Smith et al
Risk Factors in GBD-2000 Comparative Risk Assessment
• Hypertension• Cholesterol• Physical inactivity• Unsafe sex• Lack of fruit & veg• Malnutrition• Unsafe injection• Child sexual abuse• Obesity/BMI• Lack of breast feeding
• Illicit drugs • Active Smoking• Alcohol• Lead• Indoor air pollution
– ETS– Solid fuel use
• Outdoor air pollution• Water/hygiene/sanitation• Climate change• Occupational hazards
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UCB - KR Smith et al
CRA Method• Estimate prevalence of exposure
(Actual - Counterfactual) Exposures = Pe
• Relative risk estimates from epidemiological studies = RR
• Population Attributable Risk (PAR)
PAR= Pe(RR-1) / (1+ Pe(RR-1))
• Morbidity and Mortality, preferably from a Burden of Disease study (C4 compatible) = M
• Burden = PAR * M
• Sum over exposure levels (distribution) and age-sex groups.
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UCB - KR Smith et al
Estimating Exposure Levels(what is air pollution?)
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Pollutants in Biomass Smoke (many hundred)
• Small particles, CO, NO2
• Formaldehyde, Acrolein, Benzene, 1,3-Butadiene, Toluene, Styrene, etc.
• Polyaromatic hydrocarbons• Coal has all the above plus SO2 and toxic
elements such as As, Pb, Hg, and Fl.• Both produce significant non-CO2 greenhouse
gases (GHGs), such as CH4
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Component Mechanisms of health effects WHOguidelines(mg/m3)
(mg/m3)
CO
§ Absorption into blood from lungs§ ↑ HbCO levels§ ↓ oxygen to body tissues§ Possible impact on lung clearance
10 150
Particulates§ Inhalation into respiratory system§ Deposition in respiratory tract
irritation and toxicity0.1 3.3
Benzene§ Absorption into blood from lungs§ Leukaemia
0.002 0.8
Formaldehyde
§ Irritation of mucosa§ Toxicity to cilia§ Reduction in lung clearance
ability§ Possible carcinogen
0.1 0.7
Indoor pollution from Indian chula burning wood
Note: Emissions from 1 kg of wood / hr in 40 m3 kitchen
TypicalIndoorLevels
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UCB - KR Smith et al Saksena & Smith, 2000
Mean ~700 µg/m3
Distributionof 24-hour PM10measurementsIn NorthIndian villagehouseholds
US Standard50 µg/m3
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Pyramid of Exposure Assessment
• Biomarkers • Personal monitoring• Microenvironmental
monitoring• Questionnaires
• Secondary information
Uncertainty
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UCB - KR Smith et al
Emissions Along the Household Energy Ladder
05
10152025303540
Dung
Crop R
esidu
es Wood
Kerose
ne Gas
Electric
ity
00.20.40.60.811.21.41.61.8
Grams Per Meal
CO
PM10
CleanDirty
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UCB - KR Smith et al
Estimating Risk Factor Levels: Solid Fuel Use
Binary classification of exposure • Exposed:
– Households using solid fuels (wood, dung, agricultural residues, coal, charcoal) as primary source of energy for cooking
• Unexposed: – Households not using solid fuels as primary
cooking fuel (counterfactual level)
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Households Using Biomass Fuels
National Burden of Disease from IAP in India
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Obtaining estimates where data exist: Household Fuels Database
• 52 countries in 10 WHO regions• Sources of data include: national
population and housing censuses, household energy surveys, FAO
• Estimates for each region are population weighted averages of available data
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Household Fuel-Use Prediction Model
As countries develop, people shift from solid to cleaner fuels – All countries with 1999 GNP/capita >$5000
assumed to have made complete transition to cleaner cooking fuels
– Avoid over-extrapolation of model: highest 1999 GNP/capita in household fuels database: Brazil ($4420)
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Fuel Prediction Model:
Modelling Technique:• Stepwise linear regression
Criteria for Model Parameters: • Stable over a several year period (solid fuel use patterns are
relatively stable over several years)• Available on a national level for most countries across most
regions• Routinely updated• From a reliable source
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UCB - KR Smith et al
Final Fuel Prediction Model• Parameters:
• Model Summary:– R: 0.8637– R2: 0.7460– Adjusted R2: 0.7244– Standard Error of the Estimate: 0.1891
• Model meets assumptions of normalcy, constant variance.• Collinearity and Tolerance also assessed.
StandardizedCoefficients
95% ConfidenceInterval for B
Beta t Sig. Lower Upper(Constant) 3.1926 0.0025 0.4135 1.8223RURAL 0.3527 3.0938 0.0033 0.2312 1.0908EMR -0.2838 -3.4968 0.0010 -0.3904 -0.1053LNGNP -0.2646 -2.5648 0.0136 -0.1852 -0.0224per capita PetroleumUse -0.2244 -2.5454 0.0143 -0.0006 -0.0001
ln GNP/capPercent RuralPetroleum useEmerites
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UCB - KR Smith et al
Indoor air pollution defined here as unventilated use of household
use of solid fuels
What are the Exposure-ResponseRelationships?
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UCB - KR Smith et al
Pneumonia
Asthma
Low birthweight
Earlyinfantdeath
Chronic obstructivelung disease
Lung cancer
Blindness
Tuberculosis
Heart disease?
Diseases for which we havequantitative risk data
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UCB - KR Smith et al
Health Outcomes
Criteria for Causality
Acute Lower Respiratory Infections (ARI)
Chronic Obstructive Pulmonary Disease (COPD)
Lung Cancer (coal)**
Lung Cancer (biomass)
Asthma Blindness (cataracts)
Tuberculosis
Consistency? YES YES YES INC* INC* INC* INC*
Strength of association?
YES YES YES YES YES YES YES
Specificity? - - - - - - -
Dose-response relationship?
- - - - - - -
Temporal relationship?
YES YES YES YES YES YES YES
Biological plausibility?
YES YES YES YES YES YES YES
Coherence? YES YES YES INC* YES INC* INC*
Experiment? - - - - - - -
Evidence STRONG STRONG STRONG MODERATE MODERATE MODERATE MODERATE
Evidence of Causality
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Strong Evidence: Active & passive smoking; urban air pollution, biochemical/laboratory studies, and
multiple studies of solid-fuel use in developing countries
Selection Criteria for ARI Studies• Primary• Developing-country• Biomass-using households• Children under 5• Standard measure of outcome• Odds ratio calculated• Adjustment/evaluation of potential confounders• Written in English, German, or French
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IAP and Childhood ARI
• 9 Case-control: South Africa, Zimbabwe, *Nigeria, Tanzania, Gambia, *Brazil, *India, Argentina 6 adjusted for confounders; n = 4311; Odds Ratios = 2.2-9.9
• 3 Cohort: Nepal, Gambia 2 adjusted for confounders; n = 910; Odds Ratios = 2.2-6.0
• 1 Case-fatality: Nigeria Hospitalized patients; n= 103; Odds Ratio = 8.2
• 2 US Case-control; n = 206 Adjusted for confounders. Odds Ratios = 4.8
• Result of meta-analysis: 2.3 (CI 95%: 1.9, 2.7).
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COPD• 3 Case-control studies: Saudi Arabia; Columbia;Mexico 2 adjusted for confounders; 2 showexposure response with years of cooking; n = 498
Odds Ratios = 3.3 - 15• 5 Cross-sectional studies: Nepal ; India; Bolivia
All partly adjusted; 2 show exposure-response with years of cooking; n = 5528
Odds Ratios = 1.4 - 7.9• Women: 3.2 (CI 95%: 2.3, 4.8).• Men: 1.8 (CI 95%: 1.0, 2.8).
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Meta-analysis: Graph coal use studies - lung cancer
Women: 1.94 (CI 95%: 1.09, 3.47).Men: 1.5 (CI 95%: 1.0, 2.5).
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Moderate Evidence: active smoking, animal studies, and at least 3 studies of solid fuel use
in LDCs
• Blindness: Cataracts have been associated with biomass use in one national survey and two case-control studies in India. OR: 1.3-1.6
• TB: Shown to be associated with biomass use in one national and one local study in India and one case-control study in Mexico (occasionally reported to be associated with outdoor air pollution) OR: 1.5-2.7
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Weak Evidence: difficult to assign causality and to diagnose, but some studies available
in LDC households
• Asthma: Associated with urban outdoor and indoor pollution in MDCs. Typical solid-fuel smoke exposures are much higher. 3 studies in LDC solid fuel households. OR: 1.4-2.5
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UCB - KR Smith et al
Suggestive Evidence: active and passive smoking, urban air pollution, physiological
mechanisms being elucidated, but inadequate number of studies yet in LDC solid-fuel using
households
• Heart disease (ischaemic): Thought to be a major impact of smoking and urban pollution. Typical solid-fuel smoke exposures are intermediate. No LDC indoor studies.
OR: Cannot quantify
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UCB - KR Smith et al
Suggestive Evidence (cont.)• Adverse Pregnancy Outcomes (stillbirth, low
birthweight (LBW), neo-natal death, etc.): Stillbirth and LBW have been associated with biomass smoke exposure in pregnant women in India and Latin America. LBW and early infant death have been associated with much lower levels of urban air pollution in China and several developed countries.
OR: Not possible to quantify
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UCB - KR Smith et al
Figure 2. Major Diseases and Risk Factors in India
0 5 10 15
ARI
Diarrhea
Perinatal
TB
Heart Disease
Cancer
Road Accidents
Indoor Air Pollution
Malnutrition
Water/Sanitation
Unsafe Sex/Unwanted Pregnancy
Occupation
Alcohol
Hypertension
Tobacco
Percent of National Burden of Disease
Range of estimates
22.4 %
Indoor Air Pollution Comparedto Other MajorRisk Factorsin India
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UCB - KR Smith et al
Currently not included
• Indoor environments– Schools, vehicles, shops, workplaces, etc.
• Population groups– Men and Youth (5-15)
• Pollutants/Sources– Radon– Arsenic and fluorine in coal– Incense and mosquito coils– Biological agents (mold, mites, etc.)
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Not included (cont.)
• Disease endpoints– Adverse Pregnancy Outcomes– Aero-digestive cancer– Cor Pulmonale– Interstitial lung disease– Trachoma– Initiation/triggering of asthma – Coronary heart disease
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Not included (cont.)
• Sequelae– TB in the HIV-positive– ARI during perinatal period – Excess deaths in the blind– ARI-Malnutrition-Diarrhea connections
• Indirect Causal Pathways– Low birth weight– (Un) Healthy mother effect
• Counterfactual level not actual minimum– Liquid and gaseous fuels produce exposures
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The Unhealthy Mother Effect
Solid Fuel Use
Smoke Child ARI Child Health
FuelHarvesting
Maternal Health
Maternal Time and Energy
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UCB - KR Smith et al 0 5 1 0 1 5 2 0 2 5
1 0
1 0 0
1 0 0 0
Stove Lifetime - Years
$NP
V P
er D
ALY
3.0% Discount Rate 10% Discount Rate
Cost-Effectiveness of Health InterventionsImproved Biomass Stoves in India
Net Present Cost of ImprovedStoves (including all program costs) per Healthy Life Year Extended
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Avoidable Versus AttributableVersion 1
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40
60
80
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120
1970 1980 1990 2000 2010 2020 2030 2040 2050
Attributable Avoidable
Intervention
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Attributable versus AvoidableVersion 2
0
20
40
60
80
100
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1970 1980 1990 2000 2010 2020 2030 2040 2050
AttributableAvoidable
Exposure due to economic growth
Intervention
Population distribution
Competing risks
Baseline Changes Due toShifts in
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UCB - KR Smith based on Murray
Risk and Uncertainty
Attributable Risk
Avo
idab
le R
isk
Indoor Air Pollution
Outdoor Air Pollution
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UCB - KR Smith based on Murray
Risk and Uncertainty
Attributable Risk
Avo
idab
le R
isk
Indoor Air Pollution
Malnutrition
Tobacco
Outdoor Air Pollution
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UCB - KR Smith based on Murray
Risk and Uncertainty
Attributable Risk
Avo
idab
le R
isk
Indoor Air Pollution
Malnutrition
TobaccoClimateChange
Outdoor Air Pollution
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Thank you