Estimating the global burden of infant mortality attributable to ambient particulate pollution: Analysis using a nonlinear exposure-response function that combines multinational linear effect estimates

利用结合多国线性效应估计的非线性暴露-反应函数分析环境颗粒物污染造成的全球婴儿死亡负担

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Abstract

Fine particulate matter (PM(2.5)) is a major contributor to infant mortality. However, the attributable global burden remains unclear due to the absence of a nonlinear exposure-response function that links all-cause infant mortality to various PM(2.5) concentrations. In this study, we systematically reviewed the literature on PM(2.5) exposure and under-five child mortality, then conducted multicenter epidemiological analyses using Demographic and Health Survey (DHS) data with fixed-effects logit regression. We integrated literature-derived estimates with local PM(2.5)-mortality associations across multiple regions. Using meta-regression, we quantified per unit exposure effects to develop a nonlinear exposure-response function, subsequently extrapolated to 189 countries (1998-2019) to estimate the global infant mortality burden attributable to PM(2.5) exposure. The results showed that prenatal exposure was more strongly associated with increased infant mortality in both linear and nonlinear analyses. The local effect of prenatal exposure was higher at the low-concentration end (<20 μg/m(3)) than at the high-concentration end (>20 μg/m(3)). The attributable deaths declined from 2.22 to 1.44 million, yet the attributable fraction rose from 32.6% to 39.3%, indicating persistent PM(2.5) risks despite child health improvements. These findings suggest that, although the improved child health partially mitigated the adverse effects of worsening air quality between 1998 and 2019, prenatal PM(2.5) exposure remained a significant risk factor.

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