Air–Noise Pollution Linkages: Testing Innovative Community-Based Adaptation and Mitigation Strategies in Kenya

<i>Introduction:</i> Our case study was conducted across healthcare facilities in Kilifi and Nairobi, where perinatal adolescents were screened for depression. <i>Objective:</i> The relationship of environmental monitoring in addressing mental health needs of vulnerable perinatal adolescent populations was explored. <i>Methods:</i> We installed outdoor air quality sensors at two facilities in Nairobi-Kangemi and Kariobangi North health centers-and two in Kilifi-Mtwapa and Vipingo health centers-and installed sensors in two households of two perinatal adolescents. Community health workers monitored air quality and noise levels data, collecting experiential data on stress and mood from perinatal adolescents. <i>Findings:</i> Air quality monitoring revealed site-specific variations in PM<sub>2.5</sub> concentrations. Kariobangi Health Center recorded the highest mean concentration of 29.45 µg/m³, exceeding the WHO 2021 annual guideline of 5 µg/m³ indicating substantially degraded air quality. Kangemi Health Center was next (21.27 µg/m³), followed by Mtwapa (15.34 µg/m³) and Vipingo (12.52 µg/m³). Noise monitoring revealed consistently elevated exposure in healthcare settings. At Kangemi Health Center, mean noise levels reached 52.2 dB (median: 53.5 dB), surpassing the WHO guideline for hospital settings (<35-40 dB). Household-level air quality monitoring highlighted significant operational challenges: sensor deployment constraints, difficulties in ensuring continuous temporal coverage, and substantial intra-day variability-underscoring the need for improved monitoring design and calibration strategies. <i>Conclusions:</i> We tested air and noise monitoring deployment as a lever for strengthening the health system and a strategy for improved patient care and mental well-being. We trained community health workers and youth leaders in a task-shifting model to collect environmental health data. Our approach sought to ease the deployment of environmental monitoring in a sustainable data collection process. However, both mitigation, targeting reduction in sources of pollution, and adaptation efforts focused on coping with the effects of air and noise pollution on vulnerable populations within primary care need concerted efforts.

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Publication Details

Journal
Annals of Global Health
Published
2025-10-28
DOI
https://doi.org/10.5334/aogh.4750
Primary Topic
Noise Effects and Management
Type
article
Field-Weighted Citation Impact
0.00

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article

Air–Noise Pollution Linkages: Testing Innovative Community-Based Adaptation and Mitigation Strategies in Kenya

Obadia Yator, Edith Apondi, Manasi Kumar, Osman Warfa et al.
Annals of Global Health
Noise Effects and Management
article

Air–Noise Pollution Linkages: Testing Innovative Community-Based Adaptation and Mitigation Strategies in Kenya

Obadia Yator, Edith Apondi, Manasi Kumar, Osman Warfa, Albert Tele, Darius Nyamai, Hassan Leli, Vincent Nyongesa, Philip Osano, Ayub Macharia, Beatrice Madeghe, Carol Ngunu, Ngongang Wandji Danube, Lucas Kalama, Josphat Asande
article en

Abstract

<i>Introduction:</i> Our case study was conducted across healthcare facilities in Kilifi and Nairobi, where perinatal adolescents were screened for depression. <i>Objective:</i> The relationship of environmental monitoring in addressing mental health needs of vulnerable perinatal adolescent populations was explored. <i>Methods:</i> We installed outdoor air quality sensors at two facilities in Nairobi-Kangemi and Kariobangi North health centers-and two in Kilifi-Mtwapa and Vipingo health centers-and installed sensors in two households of two perinatal adolescents. Community health workers monitored air quality and noise levels data, collecting experiential data on stress and mood from perinatal adolescents. <i>Findings:</i> Air quality monitoring revealed site-specific variations in PM<sub>2.5</sub> concentrations. Kariobangi Health Center recorded the highest mean concentration of 29.45 µg/m³, exceeding the WHO 2021 annual guideline of 5 µg/m³ indicating substantially degraded air quality. Kangemi Health Center was next (21.27 µg/m³), followed by Mtwapa (15.34 µg/m³) and Vipingo (12.52 µg/m³). Noise monitoring revealed consistently elevated exposure in healthcare settings. At Kangemi Health Center, mean noise levels reached 52.2 dB (median: 53.5 dB), surpassing the WHO guideline for hospital settings (<35-40 dB). Household-level air quality monitoring highlighted significant operational challenges: sensor deployment constraints, difficulties in ensuring continuous temporal coverage, and substantial intra-day variability-underscoring the need for improved monitoring design and calibration strategies. <i>Conclusions:</i> We tested air and noise monitoring deployment as a lever for strengthening the health system and a strategy for improved patient care and mental well-being. We trained community health workers and youth leaders in a task-shifting model to collect environmental health data. Our approach sought to ease the deployment of environmental monitoring in a sustainable data collection process. However, both mitigation, targeting reduction in sources of pollution, and adaptation efforts focused on coping with the effects of air and noise pollution on vulnerable populations within primary care need concerted efforts.

Annals of Global HealthVol. 91(1)
University of Nairobi (KE), Department of National Defence (CA), Kaneka (United States) (US), Information and Communication Technology Authority (KE), Karen Hospital (KE), Kenyatta National Hospital (KE), Directorate of Health (IS), Kenya School of Government (KE), Stockholm Environment Institute (KE), Ministry of Health (KE), Moving the GoalPosts (KE), National Defence College Kenya (KE), World Agroforestry Centre (KE), New York University (US), Vrije Universiteit Amsterdam (NL)
National Institutes of Health, Fogarty International Center
Openalex Percentile: Top 58%
Noise Effects and Management
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