Fine particulate matter constituents and infant mortality in Africa: A multicountry study
Bibliographic record
Abstract
Few studies have investigated the association between exposure to fine particulate matter (PM2.5) and infant mortality in developing countries, especially for the health effects of specific PM2.5 constituents. We aimed to examine the association of long-term exposure to specific PM2.5 constituents with infant mortality in 15 African countries from 2005 to 2015. Based on the Demographic and Health Surveys (DHS) dataset, we included birth history records from 15 countries in Africa and conducted a multicountry cross-sectional study to examine the associations between specific PM2.5 constituents and infant mortality. We estimated annual residential exposure using satellite-derived PM2.5 for mass and a chemical transport model (GEOS-Chem) for its six constituents, including organic matter (OM), black carbon (BC), sulfate (SO42−), nitrate (NO3−), ammonium (NH4+), and soil dust (DUST). Multivariable logistic regression analysis was employed by fitting single-constituent models, the constituent-PM2.5 models, and the constituent-residual models. We also conducted stratified analyses by potential effect modifiers and examined the specific associations for each country. We found positive and significant associations between PM2.5 total mass and most of its constituents with infant mortality. In the single-constituent model, for an IQR increase in pollutant concentrations, the odds ratio (OR) of infant mortality was 1.03 (95 %CI; 1.01, 1.06) for PM2.5 total mass, and was 1.04 (95 %CI: 1.02, 1.06), 1.04 (95 %CI: 1.02, 1.05), 1.02 (95 %CI: 1.00, 1.03), 1.04 (1.01, 1.06) for BC, OM, SO42−, and DUST, respectively. The associations of BC, OM, and SO42− remained significant in the other two models. We observed larger estimates in subgroups with older maternal age, living in urban areas, using unclean cooking energy, and with access to piped water. The associations varied among countries, and by different constituents. The carbonaceous fractions and sulfate play a major important role among PM2.5 constituents on infant mortality. Our findings have certain policy implications for implementing effective measures for targeted reduction in specific sources (fossil fuel combustion and biomass burning) of PM2.5 constituents against the risk of infant mortality.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.013 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; both teacher heads agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".