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Long-Term PM 2.5 Exposure Is Associated with Symptoms of Acute Respiratory Infections among Children under Five Years of Age in Kenya, 2014

Author

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  • Peter S. Larson

    (Social Environment and Health Program, Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI 48104, USA
    Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48105, USA
    Current address: Institute for Social Research, 426 Thompson St., Ann Arbor, MI 48104, USA.
    These authors contributed equally to this work.)

  • Leon Espira

    (Center for Global Health Equity, University of Michigan, Ann Arbor, MI 48105, USA
    These authors contributed equally to this work.)

  • Bailey E. Glenn

    (Department of Biostatistics and Epidemiology, School of Public Health and Health Sciences, University of Massachusetts, Amherst, MA 01003, USA)

  • Miles C. Larson

    (Washtenaw Community College, Ann Arbor, MI 48105, USA)

  • Christopher S. Crowe

    (Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48105, USA)

  • Seoyeon Jang

    (Department of Environmental Health Sciences, School of Public Health, University of Michigan, Ann Arbor, MI 48105, USA)

  • Marie S. O’Neill

    (Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI 48105, USA
    Department of Environmental Health Sciences, School of Public Health, University of Michigan, Ann Arbor, MI 48105, USA)

Abstract

Introduction: Short-term exposures to air pollutants such as particulate matter (PM) have been associated with increased risk for symptoms of acute respiratory infections (ARIs). Less well understood is how long-term exposures to fine PM (PM 2.5 ) might increase risk of ARIs and their symptoms. This research uses georeferenced Demographic Health Survey (DHS) data from Kenya (2014) along with a remote sensing based raster of PM 2.5 concentrations to test associations between PM 2.5 exposure and ARI symptoms in children for up to 12 monthly lags. Methods: Predicted PM 2.5 concentrations were extracted from raster of monthly averages for latitude/longitude locations of survey clusters. These data and other environmental and demographic data were used in a logistic regression model of ARI symptoms within a distributed lag nonlinear modeling framework (DLNM) to test lag associations of PM 2.5 exposure with binary presence/absence of ARI symptoms in the previous two weeks. Results: Out of 7036 children under five for whom data were available, 46.8% reported ARI symptoms in the previous two weeks. Exposure to PM 2.5 within the same month and as an average for the previous 12 months was 18.31 and 22.1 µg/m 3 , respectively, far in excess of guidelines set by the World Health Organization. One-year average PM 2.5 exposure was higher for children who experienced ARI symptoms compared with children who did not (22.4 vs. 21.8 µg/m 3 , p < 0.0001.) Logistic regression models using the DLNM framework indicated that while PM exposure was not significantly associated with ARI symptoms for early lags, exposure to high concentrations of PM 2.5 (90th percentile) was associated with elevated odds for ARI symptoms along a gradient of lag exposure time even when controlling for age, sex, types of cooking fuels, and precipitation. Conclusions: Long-term exposure to high concentrations of PM 2.5 may increase risk for acute respiratory problems in small children. However, more work should be carried out to increase capacity to accurately measure air pollutants in emerging economies such as Kenya.

Suggested Citation

  • Peter S. Larson & Leon Espira & Bailey E. Glenn & Miles C. Larson & Christopher S. Crowe & Seoyeon Jang & Marie S. O’Neill, 2022. "Long-Term PM 2.5 Exposure Is Associated with Symptoms of Acute Respiratory Infections among Children under Five Years of Age in Kenya, 2014," IJERPH, MDPI, vol. 19(5), pages 1-20, February.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:5:p:2525-:d:755517
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    References listed on IDEAS

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    1. Aderiana Mutheu Mbandi & Jan R. Böhnke & Dietrich Schwela & Harry Vallack & Mike R. Ashmore & Lisa Emberson, 2019. "Estimating On-Road Vehicle Fuel Economy in Africa: A Case Study Based on an Urban Transport Survey in Nairobi, Kenya," Energies, MDPI, vol. 12(6), pages 1-28, March.
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