Household air pollution and angiogenic factors in pregnant Nigerian women: A randomized controlled ethanol cookstove intervention

Dutta, Anindita; Brito, Katherine; Khramstova, Galina; Mueller, Ariel; Chinthala, Sireesha; Alexander, Donee; Adu, Damilola; Ibigbami, Tope; Olamijulo, John; Odetunde, Abayomi; Adigun, Kehinde; Pruitt, Liese C.C.; Olopade, Olufunmilayo I.; Ojengbede, Oladosu; Rana, Sarosh; Olopade, Christopher O.

doi:10.1016/j.scitotenv.2017.05.130

Cited by 14 publications

(6 citation statements)

References 36 publications

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“…The use of polluting cooking fuels presents a serious global health risk due to household air pollution (HAP) exposure. Elevated levels of fine particulate matter of diameter <2.5 mm (PM 2.5 ) due to HAP (HAP-PM 2.5 ) have been linked to respiratory diseases (child pneumonia [3], COPD [4] and lung cancer [5]), adverse pregnancy outcomes [6,7], cataracts [8], precursors to cardiovascular diseases (CVD), including hypertension [9], and to CVD [10][11][12][13]. Exposure to HAP was the second highest environmental risk factor in the Global Burden of Disease 2017 [14], with an estimated 1.64 million attributable deaths [1,15].…”

Section: Introductionmentioning

confidence: 99%

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

Shupler

Hystad

Gustafson

et al. 2019

Environ. Res. Lett.

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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.

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Section: Introductionmentioning

confidence: 99%

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

Shupler

Hystad

Gustafson

et al. 2019

Environ. Res. Lett.

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“…It also logs temperature, relative humidity, and filter-pressure drop. The ECM has been used for household energy studies (Fandiño-Del-Rio et al 2017), as has the earlier version of the instrument (the MicroPEM™) (Bruce et al 2018;Chartier et al 2017;Dutta et al 2017). ECM preparation before deployment includes component cleaning using ethanol and lint-free wipes and device calibration.…”

Section: Instrumentationmentioning

confidence: 99%

Air Pollutant Exposure and Stove Use Assessment Methods for the Household Air Pollution Intervention Network (HAPIN) Trial

Johnson

Steenland

Piedrahita

et al. 2020

Environ Health Perspect

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BACKGROUND: High quality personal exposure data is fundamental to understanding the health implications of household energy interventions, interpreting analyses across assigned study arms, and characterizing exposure-response relationships for household air pollution. This paper describes the exposure data collection for the Household Air Pollution Intervention Network (HAPIN), a multicountry randomized controlled trial of liquefied petroleum gas stoves and fuel among 3,200 households in India, Rwanda, Guatemala, and Peru. OBJECTIVES: The primary objectives of the exposure assessment are to estimate the exposure contrast achieved following a clean fuel intervention and to provide data for analyses of exposure-response relationships across a range of personal exposures. METHODS: Exposure measurements are being conducted over the 3-y time frame of the field study. We are measuring fine particulate matter [PM < 2:5 lm in aerodynamic diameter (PM 2:5)] with the Enhanced Children's MicroPEM™ (RTI International), carbon monoxide (CO) with the USB-EL-CO (Lascar Electronics), and black carbon with the OT21 transmissometer (Magee Scientific) in pregnant women, adult women, and children <1 year of age, primarily via multiple 24-h personal assessments (three, six, and three measurements, respectively) over the course of the 18month follow-up period using lightweight monitors. For children we are using an indirect measurement approach, combining data from area monitors and locator devices worn by the child. For a subsample (up to 10%) of the study population, we are doubling the frequency of measurements in order to estimate the accuracy of subject-specific typical exposure estimates. In addition, we are conducting ambient air monitoring to help characterize potential contributions of PM 2:5 exposure from background concentration. Stove use monitors (Geocene) are being used to assess compliance with the intervention, given that stove stacking (use of traditional stoves in addition to the intervention gas stove) may occur. CONCLUSIONS: The tools and approaches being used for HAPIN to estimate personal exposures build on previous efforts and take advantage of new technologies. In addition to providing key personal exposure data for this study, we hope the application and learnings from our exposure assessment will help inform future efforts to characterize exposure to household air pollution and for other contexts.

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“…For example, dust was noted as a trigger for allergic rhinitis (Adegbiji et al, 2018) and house dust/dust mite exposure was associated with asthma (Bardei et al, 2016;Flatin et al, 2018). Particulate matter was evaluated in 24 of the indoor air pollution research studies, most focusing on PM10 (Abou-Khadra, 2013;Ibhafidon et al, 2014;Makamure et al, 2016;Jafta et al, 2017;Nkhama et al, 2017;Nkosi et al, 2017;Mentz et al, 2018) and PM2.5 exposures (Oluwole et al, 2013;Chafe et al, 2014;Ibhafidon et al, 2014;Dutta et al, 2017;Lacey et al, 2017;Lin et al, 2017a;Malley et al, 2017;Nkhama et al, 2017;Wylie et al, 2017a;Wylie et al, 2017b;Mentz et al, 2018). Some studies also measured NO, NO2, SO2, CO, and O3 (Jafta et al, 2017;Wylie et al, 2017a).…”

Section: Exposures Measuredmentioning

confidence: 99%

Environmental Health Research in Africa: Important Progress and Promising Opportunities

Joubert

Mantooth²,

McAllister

2020

Front. Genet.

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The World Health Organization in 2016 estimated that over 20% of the global disease burden and deaths were attributed to modifiable environmental factors. However, data clearly characterizing the impact of environmental exposures and health endpoints in African populations is limited. To describe recent progress and identify important research gaps, we reviewed literature on environmental health research in African populations over the last decade, as well as research incorporating both genomic and environmental factors. We queried PubMed for peer-reviewed research articles, reviews, or books examining environmental exposures and health outcomes in human populations in Africa. Searches utilized medical subheading (MeSH) terms for environmental exposure categories listed in the March 2018 US National Report on Human Exposure to Environmental Chemicals, which includes chemicals with worldwide distributions. Our search strategy retrieved 540 relevant publications, with studies evaluating health impacts of ambient air pollution (n=105), indoor air pollution (n = 166), heavy metals (n = 130), pesticides (n = 95), dietary mold (n = 61), indoor mold (n = 9), per-and polyfluoroalkyl substances (PFASs, n = 0), electronic waste (n = 9), environmental phenols (n = 4), flame retardants (n = 8), and phthalates (n = 3), where publications could belong to more than one exposure category. Only 23 publications characterized both environmental and genomic risk factors. Cardiovascular and respiratory health endpoints impacted by air pollution were comparable to observations in other countries. Air pollution exposures unique to Africa and some other resource limited settings were dust and specific occupational exposures. Literature describing harmful health effects of metals, pesticides, and dietary mold represented a context unique to Africa. Studies of exposures to phthalates, PFASs, phenols, and flame retardants were very limited. These results underscore the need for further focus on current and emerging environmental and chemical health risks as well as better integration of genomic and environmental factors in African research studies. Environmental exposures with distinct routes of exposure, unique co-exposures and co-morbidities, combined with the extensive genomic diversity in Africa may lead to the identification of novel mechanisms underlying complex disease and promising potential for translation to global public health.

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Household air pollution and angiogenic factors in pregnant Nigerian women: A randomized controlled ethanol cookstove intervention

Cited by 14 publications

References 36 publications

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

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

Air Pollutant Exposure and Stove Use Assessment Methods for the Household Air Pollution Intervention Network (HAPIN) Trial

Environmental Health Research in Africa: Important Progress and Promising Opportunities

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