ArticleFrontiers in global women's health2026
An integrated climate-structured personal and ambient air pollution monitoring framework embedded within a pregnancy and postpartum cohort in Sub-Saharan Africa.
Article in Frontiers in global women's health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: In sub-Saharan Africa, climatic variability intersects with structural inequities-biomass reliance, informal livelihoods, rapid urbanisation, and sparse regulatory monitoring-to generate highly heterogeneous air pollution exposures during pregnancy. Maternal exposure assessment in the region remains dominated by coarse ambient estimates, limiting understanding of how climate and microenvironment jointly shape actual personal exposure through their influence on pollutant generation, dispersion, and proximity to emission sources. Objective: To develop and implement an adaptable, climate-structured personal and ambient PM₂.₅ monitoring framework embedded within the PRECISE pregnancy cohort across The Gambia, Kenya, and Mozambique. Methods: A purposively sampled subset of 343 pregnant or postpartum women (The Gambia Results: The protocol generated 3,190 person-days of personal exposure data together with 328 unique days of continuous ambient data. Ambient datasets achieved high completeness in The Gambia and Kenya (>85% data capture); Mozambique ambient capture was lower due to site-level connectivity constraints. Ambient monitoring periods were included only when ≥75% of expected observations were available; periods not meeting this threshold were excluded from primary analyses. Inter-sensor agreement was robust (R Conclusion: This integrated monitoring framework extends the operational and methodological capacity for high-resolution exposure assessment through the generation of high-resolution, climate-structured exposure data within pregnancy cohorts in under-monitored African settings, advancing equitable exposure science and strengthening climate-informed maternal and newborn health research. Significance statement: This study establishes an adaptable, climate-structured exposure measurement architecture that reduces exposure misclassification and enables more precise exposure-response inference in maternal health research conducted in under-monitored environments.
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