Air Pollution, Poverty, and Health (APPH*) in Ho Chi Minh City: Assessing Inequalities in Exposure and Health Effects - PowerPoint PPT Presentation


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Air Pollution, Poverty, and Health (APPH*) in Ho Chi Minh City: Assessing Inequalities in Exposure and Health Effects


Air Pollution, Poverty, and Health (APPH*) in Ho Chi Minh City: Assessing Inequalities in Exposure and Health Effects Sumi Mehta and Vu Xuan Dan – PowerPoint PPT presentation

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Title: Air Pollution, Poverty, and Health (APPH*) in Ho Chi Minh City: Assessing Inequalities in Exposure and Health Effects

Air Pollution, Poverty, and Health (APPH) in Ho
Chi Minh City Assessing Inequalities in
Exposure and Health Effects
  • Sumi Mehta and Vu Xuan Dan
  • (on behalf of all APPH collaborators)

TA 4714-VIE, funded by ADB, Health Effects
Institute (HEI), and Government of Vietnam
Why the poor may suffer more health effects from
air pollution (global perspective)
  • The poor may suffer higher exposures to air
  • Roadside exposures (occupational, commuting,
  • Small and medium scale enterprises / Cottage
  • Use of solid fuels for cooking
  • The poor may be more susceptible to air pollution
  • Poorer nutrition / immunosuppression
  • Higher incidence of diseases of poverty
  • Lack of timely or comprehensive access to health

Limited evidence from the West, but clear need to
explore in Asia
  • Extrapolation of developed-country research to
    other populations is challenging, often
  • Different pollution sources and mixes
  • Different competing risk factors
  • Population characteristics addressed / overlooked
  • Health effects addressed / overlooked
  • Epidemiologic evidence base often only at low end
    of the exposure-response curve
  • HEI reanalysis of US Cohort studies

Studying APPH Why HCMC?
  • High quality data on air, health, and SEP
  • Qualified and enthusiastic local collaborators
  • Dept of Public Health
  • HCMC Environmental Protection Agency (HEPA)
  • Childrens Hospitals
  • Bureau of Statistics
  • A rapidly developing country in the midst of the
    environmental risk transition

Smith and Ezzati, 2005
Ho Chi Minh City
  • Over 9 million people
  • Rapid growth 200,000 people / year from 1999 -
  • gt50 pop in Vietnam lt 25 years of age
  • 3 million motorcycles, 500,000 cars
  • Consistently high temperature (28.19C,SD 1.41),
    humidity (73.7, SD 7.48)

Studying APPH in HCMC Objectives
  • Develop feasible approaches to studying air
    pollution, poverty, and health
  • Methods appropriate for HCMC context
  • Methods suitable for use in other cities -
    promote building an evidence base across Asian
  • Develop infrastructure for future studies of the
    health effects of air pollution in HCMC
  • Technical capacity (epidemiologic methods,
    exposure assessment, analysis)
  • Resources (data integration, equipment)

Studies on the health effects of air pollution in
Asia, 1980 Sep 2007
  • Public Health and Air Pollution in Asia
    Science Access on the Net (PAPA-SAN)

2 Project Components
  • C1. Hospital Study
  • Routinely collected data from 2003-2005
  • C2. Household Study
  • Prospective data collection from 2007-08

Summary of hypotheses tested
  • H1 the poor experience greater health impacts
    from ambient air pollution (C1 and C2)
  • H2 the poor live in areas with more ambient
    air pollution (C2)
  • H3 exposures of the poor are more closely
    linked to ambient air pollution (C2)
  • H4 the poor are more vulnerable to ambient
    air pollution (C1)
  • H5 the poor are more exposed to air pollution

C1 Hospital Study
  • Assess the effects of short-term exposure to air
    pollution on hospital admissions from 2003-2005
    for acute lower respiratory infections (ALRI) in
    young children (lt5 years of age) of HCMC
  • ALRI is a leading cause of death in young
    children of developing countries
  • Over 28,000 admissions for ALRI in children
    during the study period
  • Assess whether there are there different effects
    by socio-economic position (SEP), i.e. in poor
    children vs. other children

Daily Ambient Pollutant Concentrations (city
Daily Hospital Admissions for ALRI
Preliminary Results
  • PM10, Ozone, NO2 and SO2 associated with
    increased hospital admissions for ALRI in young
    children of HCMC.
  • Ozone effects consistently higher than PM
  • Results consistent across analytic techniques
    (time series and case crossover analyses)
  • Greatest challenge around 60 of ALRI
    admissions occur during the rainy season, highest
    pollutant concentrations are observed in the dry
  • How do we address negative confounding in the
    rainy season???

Do effects differ by SEP?
  • Impact of air pollution does not appear to differ
    by SEP (neither individual or group
    classification). However
  • Data from hospital financial records gives an
    underestimate of poverty status
  • Analysis uses a single, daily, city-wide average
    concentration to represent population average
  • If exposure measurement error differs by social
    class, the ability to assess differences by SEP
    will be compromised

Air Quality Monitoring Station, District 2, HCMC
A HCMC Neighborhood in Transition, 2006
C2 Household study the relationship between
personal and ambient exposures in HCMC
  • Estimate personal exposures to air pollution
    among the poor and the non-poor
  • ambient air pollution
  • other sources (cooking with solid fuels, cottage
  • Estimate prevalence of child and adult
    respiratory symptoms in HCMC
  • Assess local perceptions of environment

Issues Explored
  • What is the correlation between ambient air
    pollution concentrations and personal exposures?
  • Is this correlation different for the poor vs.
    the non-poor?
  • Are the mean total exposures of the poor higher?
  • Are the poors exposures to ambient air pollution
  • Are the poors personal exposures to other
    sources of air pollution higher?

Exposure Assessment
  • Focus primary caregivers of children lt 5
  • Repeated (lt10) measurements of daily average
    personal exposure over wet and dry seasons
  • PM2.5 and PM10
  • NO/NO2
  • Elemental carbon
  • Special attention to traffic exposure, incense,
    cottage industries (street food), tobacco smoke
  • Parallel monitoring at fixed site monitors for
    comparison of personal vs. ambient concentrations

Household Sampling Scheme
Are the poor more exposed?
Personal PM 2.5 Exposures, by District and SES
Results of first 6 household visits
How do exposures of the poor and non-poor
correlate with the ambient air quality data?
Intended Implications for Policy and Health
Impact Assessment
  • Global contribution
  • development of approaches to explore the
    relationship among air pollution, poverty, and
  • address key scientific questions higher
    exposures, different pollutant mixtures, climatic
    conditions, and disease distributions
  • Regional contribution
  • locally relevant base of air pollution and health
  • focus on ALRI, a disease of poverty responsible
    for a substantial burden of disease in children
  • increased local capacity for future research

HCMC well equipped to conduct future research on
health effects of air pollution
  • Targeted technical assistance training on study
    design, data management, statistical analysis
  • Necessary infrastructure for personal exposure
    assessment (monitoring and analysis)
  • Personal exposure monitoring
  • PM and elemental carbon (gravimetric samples)
  • NO/NO2 (passive samples)
  • Exposure Assessment laboratory (controlled
    temperature, relative humidity, glove box,
    microbalance, reflectometer, ion chromatography

(No Transcript)
What next?
  • Vietnam has addressed class-related disparities
    on many levels ?most inequities (i.e. nutritional
    deficiencies, differential access to health care)
    that confer increased susceptibility to air
    pollution may have been alleviated already
  • Will continued rapid economic growth broaden
    inequities in exposures (and health effects as a
    result) to air pollution?
  • What are the implications for replication of
    methods and /or design of multi-city or regional
  • Different patterns of poverty / inequality result
    in different manifestations of exposure and
  • How can targeted monitoring be used to
    characterize and estimate exposure
    misclassification in routinely collected data?

Thank you!
Sumi Mehta - Vu Xuan
Dan -