Household, community, sub-national and country-level predictors of primary cooking fuel switching in nine countries from the PURE study

Abstract

Introduction. Switching from polluting (e.g. wood, crop waste, coal) to clean (e.g. gas, electricity) cooking fuels can reduce household air pollution exposures and climate-forcing emissions. While studies have evaluated specific interventions and assessed fuel-switching in repeated cross-sectional surveys, the role of different multilevel factors in household fuel switching, outside of interventions and across diverse community settings, is not well understood. Methods. We examined longitudinal survey data from 24 172 households in 177 rural communities across nine countries within the Prospective Urban and Rural Epidemiology study. We assessed household-level primary cooking fuel switching during a median of 10 years of follow up (∼2005-2015). We used hierarchical logistic regression models to examine the relative importance of household, community, sub-national and national-level factors contributing to primary fuel switching. Results. One-half of study households (12 369) reported changing their primary cooking fuels between baseline and follow up surveys. Of these, 61% (7582) switched from polluting (wood, dung, agricultural waste, charcoal, coal, kerosene) to clean (gas, electricity) fuels, 26% (3109) switched between different polluting fuels, 10% (1164) switched from clean to polluting fuels and 3% (522) switched between different clean fuels. Among the 17 830 households using polluting cooking fuels at baseline, household-level factors (e.g. larger household size, higher wealth, higher education level) were most strongly associated with switching from polluting to clean fuels in India; in all other countries, community-level factors (e.g. larger population density in 2010, larger increase in population density between 2005 and 2015) were the strongest predictors of polluting-to-clean fuel switching. Conclusions. The importance of community and sub-national factors relative to household characteristics in determining polluting-to-clean fuel switching varied dramatically across the nine countries examined. This highlights the potential importance of national and other contextual factors in shaping large-scale clean cooking transitions among rural communities in low-and middle-income countries.

Global Burden of Cardiovascular Diseases and Risk Factors, 1990–2019

“…In the interim, personal-level interventions, such as the use of portable air cleaners, may be effective ( 43 ). Continued reductions in HAP exposure through programs to improve access to clean energy sources will lead to both health and climate benefits ( 44 ).…”

Household and personal air pollution exposure measurements from 120 communities in eight countries: results from the PURE-AIR study

“…As PURE-AIR included communities originally recruited for a study not focused on household air pollution, the findings might be more representative of rural exposures than studies focused on household air pollution that generally selectively recruit from communities with a high prevalence of household air pollution. These recent measurements might also represent broader trends in lower exposures due to increasing use of cleaner cooking fuels 16 or reductions in family size, or both.…”

“…Given the pace of urbanisation during the 10–15-year follow-up period, some communities defined as rural according to baseline criteria might now be considered peri-urban. 16 As we were not able to collect information on participant refusals, personal measurements might not be representative of PURE-AIR participants within each community.…”

“…The PURE-AIR study was done in 120 rural communities in eight low-income and middle-income PURE countries (Bangladesh [16 communities], Chile [three], China [38], Colombia [18], India [32], Pakistan [six], Tanzania [five], and Zimbabwe [two]) where more than 10% of households used polluting fuels (wood, animal dung, agricultural waste, coal, charcoal, shrubs or grass, and kerosene) at baseline; these classifications were based on World Bank data during PURE study commencement (2003). 15 As a high amount of primary cooking fuel switching occurred between baseline assessment (which varied between countries; appendix p 2) and PURE-AIR monitoring, 16 communities were strategically selected for household air pollution monitoring to ensure a sufficient distribution of polluting fuel types among household samples. Although study recruitment included a higher proportion of households using clean primary fuels compared with baseline ( appendix p 3), stratified sampling by community-level baseline primary cooking fuel use statistics (eg, 60% wood, 40% liquefied petroleum gas, hereafter referred to as gas) was maintained to ensure variations in polluting cooking fuel types.…”

Health and Climate Impacts of Scaling Adoption of Liquefied Petroleum Gas (LPG) for Clean Household Cooking in Cameroon: A Modeling Study

“…It is important to note that in the health impact modeling, we are assuming uniform LPG primary adoption across all urban, peri-urban, and rural areas, which have different demographics and disease burden in Cameroon (Appendix 1). These differences did not account for the differential potential for LPG adoption according to different settings and socio-economic groups (Puzzolo et al 2016;Shupler et al 2019). We acknowledge that affordability to the household, prices of competing fuels, supply-chain reliability, and last-mile distribution are all potential factors that contribute to clean fuel adoption, even in best-case scenarios of plentiful cylinder refills available in the market (Rosenthal et al 2017;Puzzolo et al 2019).…”