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Geospatial determinants of maternal and child exposure to fine particulate matter in Kintampo, Ghana: Levels within the household and community, by surrounding building density and near roadways

Journal of Exposure Science & Environmental Epidemiology (2023)Cite this article

Abstract

Background

Personal exposure to fine particulate matter (PM2.5) from household air pollution is well-documented in sub-Saharan Africa, but spatiotemporal patterns of exposure are poorly characterized.

Objective

We used paired GPS and personal PM2.5 data to evaluate changes in exposure across location-time environments (e.g., household and community, during cooking and non-cooking hours), building density and proximity to roadways.

Methods

Our study included 259 sessions of geolocated, gravimetrically-calibrated one-minute personal PM2.5 measurements from participants in the GRAPHS Child Lung Function Study. The household vicinity was defined using a 50-meter buffer around participants’ homes. Community boundaries were developed using a spatial clustering algorithm applied to an open-source dataset of building footprints in Africa. For each GPS location, we estimated building density (500 m buffer) and proximity to roadways (100 m buffer). We estimated changes in PM2.5 exposure by location (household, community), time of day (morning/evening cooking hours, night), building density, and proximity to roadways using linear mixed effect models.

Results

Relative to nighttime household exposure, PM2.5 exposure during evening cooking hours was 2.84 (95%CI = 2.70–2.98) and 1.80 (95%CI = 1.54–2.10) times higher in the household and community, respectively. Exposures were elevated in areas with the highest versus lowest quartile of building density (FactorQ1vsQ4 = 1.60, 95%CI = 1.42–1.80). The effect of building density was strongest during evening cooking hours, and influenced levels in both the household and community (31% and 65% relative increase from Q1 to Q4, respectively). Being proximal to a trunk, tertiary or track roadway increased exposure by a factor of 1.16 (95%CI = 1.07–1.25), 1.68 (95%CI = 1.45–1.95) and 1.27 (95%CI = 1.06–1.53), respectively.

Impact

  • Household air pollution from cooking with solid fuels in sub-Saharan Africa is a major environmental concern for maternal and child health. Our study advances previous knowledge by quantifying the impact of household cooking activities on air pollution levels in the community, and identifying two geographic features, building density and roadways, that contribute to maternal and child daily exposure. Household cooking contributes to higher air pollution levels in the community especially in areas with greater building density. Findings underscore the need for equitable clean household energy transitions that reach entire communities to reduce health risks from household and outdoor air pollution.

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Fig. 1: Example of a GPS trajectory throughout a session.
Fig. 2: Distribution of average participant PM2.5 exposures (µg/m3) for the fourth versus first quartile (Q4 vs. Q1) of surrounding building density (80%+ confidence) by time of day.
Fig. 3: Factor change in 30-minute average log-transformed PM2.5 exposure (µg/m3) and 95% confidence intervals for location-time environments modeled jointly with quartiles of surrounding building density.

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Data availability

The datasets generated during and/or analyzed during the current study are not publicly available because this analysis included geolocated information considered to be personally identifiable information (PII). However, the authors have created a GitHub repository demonstrating the development of community boundaries as well as estimating surrounding building density and nearby roadways using a simulated GPS trajectory [https://github.com/dmedgyesi/GeospatialGhana].

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Acknowledgements

The authors are grateful to the mothers and their children who participated in the study. The authors would also like to thank the community leaders in the study area for their support.

Funding

This work was supported by the National Institute of Environmental Health Sciences (NIEHS) Grants R01ES026991, P30ES009089, R01ES019547, R21HD094229, R01ES024489, R01ES034433, K23HL1353449, and T32ES007322.

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Authors and Affiliations

  1. Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY, USA

    Danielle N. Medgyesi, Jeremy Porter & Darby W. Jack

  2. Kintampo Health Research Centre, Research and Development Division, Ghana Health Service, Kintampo, North Municipality, Ghana

    Mohammed Nuhu Mujtaba, Sulemana Watara Abubakari, Seyram Kaali & Kwaku Poku Asante

  3. Lamont-Doherty Earth Observatory, Columbia University, Palisades, NY, USA

    Qiang Yang & Steven N. Chillrud

  4. Elsevier Global STM Journals, New York, NY, USA

    Qiang Yang

  5. Division of Pulmonary, Critical Care and Sleep Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA

    Alison G. Lee

  6. Department of Sociology, School of Humanities and Social Sciences, Brooklyn College, Brooklyn, NY, USA

    Jeremy Porter

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Contributions

KPA, DNM, DWJ and SNC conceived of the work. MNM, SK, DWJ and SNC led the exposure assessment work. QY processed the data used in this analysis. All authors contributed to the design of the study. JP provided spatial analysis advice. DNM completed the analysis and drafted the manuscript. All authors contributed to the interpretation of results and revision of the manuscript.

Corresponding author

Correspondence to Danielle N. Medgyesi.

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The authors declare no competing interests.

Ethical approval

The protocol for this study was approved by the Kintampo Health Research Center Institutional Ethics Committee, and the Institutional Review Board for Human Subjects Research at Columbia University Medical Center and Mount Sinai.

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Medgyesi, D.N., Mujtaba, M.N., Yang, Q. et al. Geospatial determinants of maternal and child exposure to fine particulate matter in Kintampo, Ghana: Levels within the household and community, by surrounding building density and near roadways. J Expo Sci Environ Epidemiol (2023). https://doi.org/10.1038/s41370-023-00606-1

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