Social, Economic, and Resource Predictors of Variability in Household Air Pollution from Cookstove Emissions
and Resource Predictors of Variability in Household Air Pollution from
Cookstove Emissions. PLoS ONE 7(10): e46381. doi:10.1371/journal.pone.0046381
Social, Economic, and Resource Predictors of Variability in Household Air Pollution from Cookstove Emissions
Gautam N. Yadama 0
John Peipert 0
Manoranjan Sahu 0
Pratim Biswas 0
Venkat Dyda 0
Matjaz Perc, University of Maribor, Slovenia
0 1 George Warren Brown School of Social Work, Washington University in St. Louis, St. Louis, Missouri, United States of America, 2 Division of General Medical Sciences, Washington University School of Medicine, Washington University in St. Louis, St. Louis, Missouri, United States of America, 3 Advanced Energy Technology Initiative, University of Illinois at Urbana-Champaign, Urbana-Champaign, Illinois, United States of America, 4 Aerosol and Air Quality Research Laboratory, Department of Energy, Environmental and Chemical Engineering , Washington University in St. Louis, St. Louis , Missouri, United States of America, 5 Foundation for Ecological Security, Papagni Regional Cell , Madanapalle , India
We examine if social and economic factors, fuelwood availability, market and media access are associated with owning a modified stove and variation in household emissions from biomass combustion, a significant environmental and health concern in rural India. We analyze cross-sectional household socio-economic data, and PM2.5 and particulate surface area concentration in household emissions from cookstoves (n = 100). This data set combines household social and economic variables with particle emissions indexes associated with the household stove. The data are from the Foundation for Ecological Society, India, from a field study of household emissions. In our analysis, we find that less access to ready and free fuelwood and higher wealth are associated with owning a replacement/modified stove. We also find that additional kitchen ventilation is associated with a 12% reduction in particulate emissions concentration (p,0.05), after we account for the type of stove used. We did not find a significant association between replacement/modified stove on household emissions when controlling for additional ventilation. Higher wealth and education are associated with having additional ventilation. Social caste, market and media access did not have any effect on the presence of replacement or modified stoves or additional ventilation. While the data available to us does not allow an examination of direct health outcomes from emissions variations, adverse environmental and health impacts of toxic household emissions are well established elsewhere in the literature. The value of this study is in its further examination of the role of social and economic factors and available fuelwood from commons in type of stove use, and additional ventilation, and their effect on household emissions. These associations are important since the two direct routes to improving household air quality among the poor are stove type and better ventilation.
Funding: Seed funding for data analysis is provided by a grant from the McDonnell Academy Global Energy and Environment Partnership, Washington University
in St. Louis. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing Interests: The authors have declared that no competing interests exist.
Around the globe, 2.7 billion people depend on traditional
biomass fuels to meet their daily household energy needs for
cooking and heating, and the estimates are for this number is to
rise to 2.8 billion by 2030 . Burning wood, crop waste, grasses,
shrubs, and dung is inefficient, unhealthy, and has adverse effects
on the environment. Mounting interest from governments and
international multilateral agencies in sustainably replacing
traditional cookstoves with improved stoves and substitute cleaner fuels
for solid biomass is motivated by the potential to improve human
health and local environments as well as climate benefits .
Approximately 2 million people die annually because of indoor
air pollution from solid biomass combustion, and 99 percent of
these deaths occur in developing countries , with 570,000
annual deaths in India [4,5]. Adverse health conditions associated
with exposure to biomass emissions include: chronic bronchitis ;
chronic obstructive pulmonary disease (COPD) and asthma [6,7],
acute respiratory infections [7,8]; decreased lung function ;
tuberculosis , nasopharyngeal, laryngeal, and lung cancer
, pneumonia , and low birth weight among children .
Recent studies suggest that biomass combustion is an even greater
risk factor for COPD than cigarette smoking, particularly in India
where 156 million households still depend on solid biomass for
cooking and heating . The urgency to address the health of
millions is reflected in the newly formed Global Alliance for Clean
Cookstoves to promote improved biomass cookstoves .
Replacement cookstoves designed for high efficiency and low
emissions, and modifications to ventilation in the cooking area, are
two solutions to reducing exposure to harmful household air
pollution. The available evidence suggests that a households
behavioral response to interventions depends on livelihood
strategies, household characteristics, variability in solid biomass
availability, culture-based preferences around food preparation,
and the cost of obtaining traditional fuels [16,17]. There is some
initial evidence that when traditional fuels are abundant,
households are less likely to adopt new and cleaner energy
Social and economic class of a household is a significant factor
in the type of fuel used, and how efficiently that fuel is combusted.
The type of fuel and efficiency of combustion determine the
subsequent harmful impacts on the household. There has been
greater attention to understanding health outcomes across social
and economic groups , including a focus on how access to
type of fuel and exposure to varying environmental conditions
differ by social and economic class and drive variations in health
. The poor primarily use polluting fuels like wood, crop-waste,
and dung cakes obtained from common lands pastures and
forests that are not privately owned and accessible to all
members of a community for resource extraction . The
dependence of poor on such freely available solid fuels will more
likely expose them to higher levels of emissions.
Although many studies have analyzed household cookstove
emissions in rural India and throughout the developing world, few
examine how social and economic and other contextual factors,
such as access to fuelwood from commons, access to markets place
households at a continued risk of using traditional stoves and solid
biomass fuels . One study that directly analyzes the relationship
between socio-economic variables and emissions levels by
Dasgupta, et al. concludes that households with higher income
and education have lower levels of PM10 exposure . The study
further investigates factors associated with socio-economic status
that affect the level of emissions exposure of household members,
including stove type and ventilation. A systematic review of stove
research concludes that there is evidence for positive income and
education effect on uptake of cleaner stoves and fuels, but it is not
across the board, and the need for more evidence on an expanded
set of context variables such as fuelwood availability and proximity
to markets in addition to income and education on stoves and
household air pollution .
This paper is in part a response to such calls with a particular
focus on testing if social and economic factors, open access to
biomass fuel, easy access of village to markets, and media exposure
affect the type of household stove used and likelihood of additional
ventilation, and their relationship to level of emissions in a
household. A particular focus on these factors is especially timely
given that India is poised to launch a new, large-scale program
the initiative on improved biomass stoves in which millions of
stoves will be disseminated with the objective of reducing
household air pollution . Understanding how socio-economic
factors, and access to fuelwood, markets, and media are related to
the likelihood of a traditional or an improved stove, and associated
levels of cookstove emissions will help in identifying potential
barriers to reducing harmful household emissions in biomass
dependent rural households .
We analyze the importance of these factors on household air
quality in rural Andhra Pradesh and Karnataka, India. Particulate
emissions indices described in Sahu et al have been calculated for
each household and combined with data on social, market access,
media exposure, and fuelwood availability from commons to
examine variation in emissions levels across households as a
function of these variables . The National Institutes of Health
has underscored the need for better understanding of such
contextual factors on household air pollution from cookstoves in
addition to more research on health risks associated with such
emissions . The data available to us do not provide health
information and therefore is not possible to associate variations in
emissions to specific household health outcomes. In this paper,
however, we offer additional empirical evidence for understanding
household air pollution, a significant factor in adverse health of the
poor, from household variability in social and economic privilege,
fuelwood access, market access, and media exposure.
Data come from a cross-sectional study of a random sample of
households by the energy team of the Foundation for Ecological
Security (FES), India. We have obtained a formal approval for this
study from Washington University Human Research Protection
Office (HRPO) and they have determined that it does not involve
activities that are subject to Institutional Review Board oversight.
The data obtained for this analysis are anonymized and therefore
this activity is not considered to meet federal definitions under the
jurisdiction of an IRB and therefore falls outside the purview of the
From February 2007 to March 2008, FES installed
Deenabhandu dome shaped biogas units in 400 households across 63 out
of a total 195 habitations of Thambalapalle-Kalicherla cluster of
Andhra Pradesh where they work. Similarly, FES installed Sarala
model chulas (Hindi for cookstoves) from November 2005 to
December 2008 in 1066 households across 45 habitations out of a
total 68 habitations where they work in the adjacent contiguous
region of Rayalpadu, Karnataka. The replaced stoves in this study
were approximately between 18 and 30 months old at the time of
data collection by FES. FES is engaged in these regions and these
habitations in a variety of ecological restoration projects including
the implementation of more efficient cookstoves.
Households were selected through a stratified random sampling
of habitations from among all the habitations where a proportion
of the traditional stoves were replaced with new stoves in these two
regions. Households within the selected habitations were randomly
chosen. Thirty habitations were randomly selected from these
clusters of habitations 10 habitations each from Thambalapalle
and Kalicherla region of Andhra Pradesh, and another 10
habitations from Rayalpadu region of Karnataka. In all these 30
habitations, there are households that received improved stoves
and those with traditional stoves. In each habitation, four
households were selected for a total sample size of 120 households.
After excluding cases with missing data, our analysis in this paper
is based on 100 households with traditional and replacement
stoves. Data obtained for this analysis does not contain identifiable
information on households and the villages.
Social-economic data on age of respondent, caste, wealth,
livelihood strategies, availability of commons for biomass,
perceptions of fuelwood scarcity, whether household owns a TV (proxy
for media exposure), presence of an all weather road access to the
village (proxy for market access), and household air quality are
available for each household in this data (Table 1). Emissions
sampling was conducted concurrently with household surveys,
wherein PM2.5 concentration and particulate surface area
concentration were measured for cookstove emissions in these
households. PM2.5 concentration data were gathered using a
personal aerosol monitor the TSI SidePak AM 510, St. Paul,
MN, USA and a UCB monitor (designed at University of
California Berkeley). The real-time surface area concentration of
airborne particles deposited in the tracheobronchial and alveolar
regions of the lung were collected using a nanoparticle surface area
monitor, the TSI AEROTRAK 9000, St. Paul, MN, USA. PM2.5
and particulate surface area were measured for households with
traditional biomass stoves, replacement Deenabandhu model
biogas stoves, and Sarala model improved chulas with flue and
chimney. Particles deposited in tracheobronchial (TB) and alveolar
(A) regions of the lung were calculated using the established
deposition curves given by International Commission on
Radiological Protection (ICRP). Then the surface area size distributions
obtained from different stoves were weighted with the deposition
fraction (that depends on particle properties) is integrated for the
Household Owns Replacement/Modified Stove
Household Has Ventilation in Kitchen
Level of Caste Privilege
Quantity of Common Land Available
Household Perceives Fuelwood Scarcity
There Is an All-Weather to the Households Village
Particle Index Tracheobronchial
Particle Index - Alveolar
Age of Respondent (Years)
Land Owned in Hectares
Number of School Years for Household Head
desired size range of particles for determining the SA of particles
deposited in lung.
Emissions concentrations were sampled at two distances from
the stoves: Location 1 breathing-zone of the stove user (within
0.5 m away); Location 2 distances representing where
non-stoveusing members would carry out daily activities (between 15 m
away). We use only the Location 1 emissions data in our analysis.
A detailed description of the IAQ sampling methods and
development of emissions indices is provided in a previous
publication by Sahu et al . Sahu et al focus exclusively on
the utility of an emissions index for particles lodging in the
tracheobronchial and alveolar regions, and provide
methodological details for calculating such an index.
Emissions Indices Calculation
The emissions indices were calculated based on the measured
emission values normalized to the range between safety standard
and lowest emission level observed. The dose metric for which no
established safety standard is available, the highest value observed
during the field measurements and/or the upper limit of the
instrument was used for calculating the index. The index
calculations are formulated as described in Sahu et al  as,
Where, EI is the emissions index corresponding to the dose
metric selected, C is the Surface area concentration (in
tracheobronchial or alveolar region) in mm2/cm3 for calculating SA index
at TB and A region. CLO is the lowest concentration and CHI is
taken as the highest concentration. The normalized indices values
ranged between 0 to1, where 0 indicates the lowest emissions
and 1 indicates highest emissions. This indices approach was
used for comparison of emissions levels from all the cookstoves
studied in the field campaign. More details about the types of stove
and detailed explanation can be found from Sahu et al., as we
provide only a brief summary of the methodology for calculating
the indices used in our analysis. The primary objective of this
analysis is to use the emissions indices as outcome measures and
examine the key social, household, livelihood and other factors
related to household emissions harmful to human health.
Measures and Statistical Analysis
Social and economic privilege is status and associated benefits to
a household that directly flow from caste and wealth. The effect of
social and economic privilege on emissions is through the type of
stove or fuel a household uses. As households are socially
advantaged and economically secure they are able to afford stoves
that are efficient and even cleaner fuels. In addition, privilege
conferred by income or social caste increase household interaction
with the outside world, and the flow of new information, and may
increase the chances of adopting a new stove. Therefore, we first
examined the relationship between social and economic variables
and the type of stove used, and the presence of additional
ventilation in the household. We then tested the relationship
between stoves used, additional ventilation, and the level of
particulate concentration in the household. In doing so, we sought
to understand the associations between social and economic
privilege and household air pollution, harmful to the environment
and human health. We used Stata Version 10 for our statistical
We first fitted a multivariable logistic regression model using
stepwise selection to examine associations between social and
economic privilege of a household and owning a replacement/
modified cookstove - a stove with a flue or chimney to vent smoke
or a biogas unit that eliminates smoke. Traditional stoves used by
households include biomass stoves: 3-stone construction stoves, or
earthen chulhas without a chimney; and kerosene stoves. The
predictors of owning an improved stove include the respondents
age, household caste, the quantity of land owned by the household
in hectares, livestock ownership, the years of education of
household head, quantity of common land available for fuelwood
collection, whether the household perceives fuelwood scarcity,
whether the household owns a television, and if there is an
allweather road to the households village, a proxy for market access.
In this survey, the respondent was the household head. We
hypothesized that older household heads, more constrained by
social norms, may have a more difficult time adopting new, or
modifying extant cooking technology or ventilation. In addition,
older household heads may be less influenced by media to shift to
new technologies. Household caste variable was coded into four
categories of caste privilege based on consultation with FES about
local norms in the study villages. We relied on local experts
classification of castes and the privilege conferred from belonging
to these categories: (1) highly privileged; (2) somewhat privileged;
(3) under-privileged; and (4) extremely underprivileged. In our
analysis, the highly privileged and somewhat privileged groups
were collapsed into a single category, yielding a three-category
variable. We hypothesized that privileged caste households would
be more likely to have a replacement stove and additional
Quantity of land owned was defined in hectares of irrigated and
non-irrigated land owned by the household, a proxy for household
wealth. We log-transformed to obtain a normal distribution of
land-owned variable. Livestock-ownership index weights small
livestock (sheep and goats) at 0.1 and large livestock (cows, buffalo,
pigs, others) at 1.0, also a proxy for household wealth . We
hypothesized that households with more land and greater livestock
wealth would be more likely to have a replacement stove and
additional ventilation. The quantity of common land available to
households for collecting fuelwood was used as a proxy for
availability of free or low cost biomass fuel. Freely available
fuelwood lowers the opportunity costs to shifting to newer stoves
and is an important disincentive to adopt replacement stoves.
Access to more common land equates to greater availability of free
fuelwood, where 1 is greater than 400 hectares of common land
available, and 0 is 400 or less hectares of common land available.
Along with the quantity of common land available for fuelwood
collection, perception of fuelwood scarcity tracks the pressure
households may feel to adopt a replacement stove or modify their
own stove to improve combustion efficiency. We hypothesized
households with access to less common land (thereby less free
fuelwood) and households perceiving greater fuelwood scarcity
would be more likely to have a replacement stove.
Television ownership tracks the degree to which households
might be exposed to media or external information disseminating
better cookstove technologies which have been shown to impact
household energy decisions . We hypothesized that households
owning a television would be more likely to have a replacement
stove and have additional ventilation. All weather roads allow for
easier and more travel into and out of the households village. All
weather roads increase market penetration, but also of
government programs, and overall increase bi-directional interaction
between households and outside influences [29,30,31]. Travelling
out of the village may enable household members more easy access
to urban and peri-urban centers where new cooking technologies
are available. Further, if a village has an all-weather road,
extension workers from NGOs and other groups disseminating
emissions-reducing cooking technology and information will have
an easier time reaching the village regularly, raising awareness
about harmful stove emissions, and the benefits of new stoves.
Therefore, we hypothesized that households in a village with an
all-weather road would be more likely to have a replacement stove
and have additional ventilation.
Previous studies have also shown that variation in indoor
emissions could be due to home ventilation unrelated to a stove
[32,33]. Therefore, we fitted a multivariable logistic regression
model using stepwise selection to estimate the effect of
socioeconomic privilege on the likelihood of having additional ventilation;
whether or not a household has additional ventilation in the
kitchen, or room where the stove is predominantly used. In this
model we used the same predictors as the model for having a
replacement stove. We extended our logistic regression analyses by
estimating the predicted probability of having a replacement/
modified cookstove for specific categories of households classified
by their socioeconomic privilege conferred by education, livestock
wealth index, and access to free fuelwood from local common
lands. The fit and performance of the logistic regression models
was assessed using the likelihood ratio x2 and c statistic.
We then in an Ordinary Least Squares (OLS) regression
analysis compared the relative impact of replacement/modified
cookstoves and additional ventilation on the two types of
particulate emission indices from cooking that are harmful to the
environment and respiratory health. The first index combines
measures of the mass concentration (PM2.5) of particulate matter
in cookstove emissions with the surface area concentration of
particulate emissions deposited in the tracheobronchial (TB)
region of the human lung (TB particle index). The second index
combines measures of the mass concentration (PM2.5) of cookstove
emissions with the surface area concentration of particulate
emissions deposited in the alveolar (A) region of the human lung
(A particle index). For both indices, scores range between 0 and 1,
and higher scores represent higher particulate emissions and
potential harm to health. The model F-test and the model R2 are
used to assess the fit and performance of the OLS regression
Likelihood of Owning a Replacement/modified
The likelihood of owning a replacement/modified cookstove
increased with livestock wealth and decreased as a household had
greater access to biomass from the commons such as forests and
other land. The logistic regression model predicting ownership of a
replacement/modified cookstove fit the data well: likelihood ratio
x2 (2, n = 100) = 18.6, p,0.0001; c-statistic = 0.73 (Table 2). The
livestock index, a proxy for wealth, was significantly associated
with owning a replacement/modified stove; the odds of owning a
replacement/modified cookstove increased with wealth as
measured by the number of livestock owned (OR = 1.10, 95% CI:
1.01, 1.21). The quantity of common land available for fuelwood
collection was also significantly associated with owning a
replacement/modified stove (OR = 0.20, 95% CI: 0.07, 0.85).
The odds of a household owning a replacement/modified
cookstove were 80% lower when a household had access to
commons and therefore more fuelwood. Perceptions of fuelwood
scarcity, access to all weather roads, ownership of a TV, age of
respondent, the number of school years for household head, the
quantity of land owned by the household, and caste of a household
did not have a significant effect on owning a replacement/
We then used the SPost utilities for logistic regression in Stata
 to compare the predicted probability of owning a
replacement/modified stove for households that had access to greater
than 400 ha of common land to collect fuelwood to those with less
than 400 ha or less of common land across various levels of
education and wealth (See Figure 1). Two trends were clear in the
predicted probabilities of owning a replacement/modified stove
across different levels of livestock wealth and years of education.
Among all households, as wealth and education increased, so did
the predicted probability of owning a replacement/modified stove.
Yet, even as this positive relationship between education and
wealth with the likelihood of owning a replacement/modified
stove held, those households with greater access to common lands,
therefore more free fuelwood and less fuelwood scarcity had a
consistently lower predicted probability of owning a replacement/
modified stove than households with less access to commons. This
finding underscores how, irrespective of caste and wealth
privileges, a households access to free fuelwood has a bearing
on the decision to replace traditional stoves with new stoves.
Table 2. Adjusted odds ratios for household and village-level variables association with having replacement/modified stoves and
Level of Caste Privilege
Log of Land Owned (ha)
Log of Livestock Index
Household Perceives Fuelwood Scarcity
Number of School Years for Household Head
Quantity of Common Land Available (1 = .400 ha; 0 = #400 ha)
There Is an All-Weather to the Households Village
Likelihood of Additional Ventilation in the Kitchen
The logistic regression model predicting additional ventilation
had a good fit to the data: likelihood ratio x2 (2, n = 100) = 23.0,
p,0.0001); c statistic = 0.77 (Table 2). Years of education of
household head was significantly associated with having additional
ventilation in the kitchen (OR = 1.14, 95% CI: 1.02, 1.27); the
odds of a household having additional ventilation increased 14%
for each additional year of education of household head. Wealth,
as in land owned, was also significantly associated with having
additional ventilation: the odds of having additional ventilation
increased with amount of land owned (OR = 3.35, 95% CI: 1.74,
Effect of Owning a Replacement/modified Cookstove
and Having Additional Ventilation on Household
Predictors of particle emissions from household cookstoves, our
normative outcome measure of household emissions, were
estimated using OLS regressions. The effect on household
emissions from owning a replacement/modified cookstove and
additional household ventilation are shown in Table 3 (Models 1
3). Emissions were differentiated by their deposition in the
tracheobronchial region (TB particle index) and alveolar region
(A particle index). Additional ventilation in a home significantly
reduced emissions of the TB particle index (Table 3 Models 13).
Unadjusted, both having a replacement/modified stove and
additional ventilation were significantly associated with lower TB
particle index scores (Tables 3, Models 1 & 2). Having a
replacement/modified stove, however, was not significantly
associated with the TB particle index after controlling for
additional ventilation in the kitchen (Table 3 - Model 3).
Additional ventilation, after controlling for ownership of a
replacement/modified stove, was associated with a 12% reduction
in the TB particle index in a household. In the unadjusted
regression (Table 3 - Model 4), additional ventilation was
significantly associated with our second emissions index A
particle index. Multivariable regression analysis, however,
indicated that neither ventilation nor ownership of a replacement/
modified stove were significantly associated with this second
Adjusted Odds Ratio (95% CI)
Adjusted Odds Ratio (95% CI)
Our results indicate that the less wealthy households are
exposed to higher concentrations of particulate emissions.
Betteroff households were more likely to have additional ventilation and
having additional ventilation effectively reduced particulate
emissions concentrations. Even among these rural households,
the well-to-do modified their homes to improve ventilation and
potentially offset emissions from a poorly functioning stove over
time. Notably, reductions in emissions, in this study were not
observed from owning a replacement/modified cookstove.
Emissions were reduced due to additional ventilation that is unrelated
to the stove. One possibility is that the replacement biomass stoves
with chimneys may not have reduced particulate emissions
concentrations because of flues that functioned sub-optimally or
maintenance requirements that were beyond the capability of
households. FES teams in their routine community visits have
observed several replacement stoves with malfunctioning flues.
Informal interviews with such households by FES village teams
indicate that household members were unable to perform regular
maintenance which resulted in broken flues. Perhaps the level of
maintenance required for the stoves to work properly was beyond
the capability of a household. Our findings resonate with research
indicating high maintenance requirements seem unreasonable to
poor rural households, leading to disrepair of replacement stoves
[32,35]. Stoves, implemented by FES, at the time of study, were
approximately 30 months old, underscoring the need for
maintenance and support after installation as an important factor
for consideration in improving household air quality. More
nuanced research is warranted to understand how rural
households address household air quality through better maintenance
and proper functioning of stoves or through such other measures
as improved ventilation.
Another insight from this study that warrants greater attention
in future studies is the reduced propensity to shift to newer stoves
when households have greater access to free fuelwood from the
commons, as measured by amount of commons available to a
household. Ours is one of the few studies that examine the
Figure 1. Predicted Probability of Having a Clean Stove by Livestock Wealth and Access to Fuelwood from Commons (A) and by
Years of Education and Access to Fuelwood from Commons (B).
association between fuelwood availability and reduced likelihood
of shifting to new stoves. While we are cautious about this
conclusion given that our analysis is from cross-sectional data, this
association between abundant fuelwood from commons and
incentives to shift to new energy systems needs further study to
test for a causal connection.
We conjecture two important pathways by which biomass
access from commons play a significant role in the uptake and
sustained use of replacement cookstoves. First, sheer availability of
fuelwood, irrespective of quality, could significantly reduce the
opportunity cost of shifting to replacement cookstoves. Second, as
burden of fuelwood collection from the commons typically falls on
women and children, it could be a significant barrier for shifting to
newer efficient stoves. As households undervalue women and
childrens labor, the perceived opportunity cost of collecting freely
available biomass from commons to meet daily energy needs
Household Has Ventilation in the Kitchen
Tracheobronchial particle emissions index
Alveolar particle emissions index
remains low, and therefore potential economic and health gains
from shifting to either a biogas stove or cleaner burning woodstove
are possibly discounted by poor households. Social caste, age of
household head, perceptions of fuelwood scarcity, media and
market access were all not significant in having a replacement
stove or additional ventilation.
Our analysis points to some important associations, but is also
limited. First, our analysis is from cross-sectional data, and we
must caution against strict causal attributions. While such data
may yield useful insights on an understudied issue, generalizability
is less than if we used data with a much larger sample of
households representing greater regional variation. While on one
hand, our narrow geographical focus controls for household
socioeconomic and geographical factors that may differ across regions
of India, a larger-n study exploring similar research questions that
would be generalizable to larger geographical regions may yield a
higher impact on future household air pollution reduction
interventions. Second, data from a large, randomized control trial
directly comparing the effectiveness of replacement/modified
cookstoves to traditional stoves and ventilation in reducing indoor
emissions, isolating the effect of each intervention have much
greater purchase in testing the impact of new stoves. Such
randomized control studies are now being implemented in India,
and the results from this analysis are useful in providing insights
into productive hypotheses for testing such studies. Third, models
predicting exposure to cookstove emissions due to socio-economic
variables are under-developed in the scientific literature, and,
therefore, our models will likely suffer from a degree of inaccuracy.
More research including such variables will contribute to a better
understanding of the predictors of exposure to cookstove
emissions, refining theory, generating more parsimonious models,
and yielding evidence that is useful to the design of household air
pollution in the field. Our results and analysis in this paper should
be viewed in light of these limitations but also as evidence for some
robust associations that warrant pursuit in both large sample
household surveys and randomized control trials examining
sustainability of improved stoves in rural India. Our findings
while insightful are associational in nature, and therefore merit
further research to establish causal pathways to improved
household air quality and health outcomes.
Finally, as we stated previously, the relationship between the
emissions indices and actual health outcomes are not available in
this study. However, the emissions indices are useful presently as
indicators of health impact in as much as they: 1) indicate the scale
of particle deposition in two areas of the human lung; 2) can be
associated with the PM2.5 and surface area concentrations
reported in our previous work . We have now designed a
randomized control trial in rural India to examine the impact of
improved stoves on respiratory health outcomes of the poor, and it
will be a further test of the emission indices we used in this analysis.
Despite these limitations, our analysis yields important lessons
for the next generation of cookstove programs. While exposure to
emissions from cookstoves is presently a rural reality, social and
economic inequalities are an important dimension of exposure
variation. Variations in exposure to household emissions are likely
to increase from new efforts to disseminate clean fuel and stove
technologies that are without regard to who is likely to accept and
use them in a sustained manner. Our results resonate with findings
of a recent systematic review of cookstove studies that social and
economic variables are important in the uptake of clean stoves and
fuels. We also respond to their call to examine understudied
contextual factors such as social marginalization, market access,
abundance of fuelwood, possibly risking uptake and sustained use
of newer stoves and cleaner fuels . While our results do not
show any association between market and media access on uptake
of modified stoves, there is a need for sharper focus on barriers
that the poorest rural households face in adopting and sustaining
replacement cookstoves is urgent. Greater attention towards
inclusion of the poorest households is paramount, as findings in
our paper suggest that socio-economic and resource conditions are
closely coupled with household behavior around stove adoption
and use, which in turn determines exposure to household air
pollution and subsequent health outcomes .
Analyzed the data: GNY JP MS PB. Contributed reagents/materials/
analysis tools: MS PB VD. Wrote the paper: GNY JP MS PB. Supervised
Energy Team at FES: VD. Provided background data on FES stove
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