Associations between exposure to landscape fire smoke and child mortality in low-income and middle-income countries: a matched case-control study

Abstract

Background The prevalence of landscape fires has increased, particularly in low-income and middle-income countries (LMICs). We aimed to assess the impact of exposure to landscape fire smoke (LFS) on the health of children. MethodsWe conducted a sibling-matched case-control study and selected 552 155 children (aged <18 years) from Demographic and Health Surveys in 55 LMICs from 2000 to 2014. Each deceased child was matched with their sibling(s). The exposure indicators were fire-sourced PM 2•5 and dry-matter emissions. We associated these exposure indicators with child mortality using conditional regressions, and derived an exposure-response function using a non-linear model. Based on the association, we quantified the global burden of fire-attributable child deaths in LMICs from 2000 to 2014. Findings Each 1 µg/m³ increment of fire-sourced PM 2•5 was associated with a 2•31% (95% CI 1•50-3•13) increased risk of child mortality. The association was robust to different models. The exposure-response function was superlinear and suggested per-unit exposure to larger fires was more toxic. Based on our non-linear exposureresponse function, we estimated that between 2000 and 2014, the five countries with the largest number of child deaths associated with fire-sourced PM 2•5 were Nigeria (164 000 [126 000 to 209 000] annual deaths), Democratic Republic of the Congo (126 000 [95% CI 114 000 to 139 000] annual deaths), India (65 900 [−22 200 to 147 000] annual deaths), Uganda (30 200 [24 500 to 36 300] annual deaths), and Indonesia (28 900 [19 100 to 38 400]).Interpretation Exposure to landscape fire smoke contributes substantially to the global burden of child mortality.

Exposure to landscape fire smoke reduced birthweight in low- and middle-income countries: findings from a siblings-matched case-control study

“…The fire-sourced PM 2.5 concentrations were estimated using the GEOS-Chem . The detailed settings of the GEOS-Chem are provided in the previous publication ( Xue et al, 2021b ) and briefly summarized here. We used the 11-01 version of GEOS-Chem model ( https://geos-chem.seas.harvard.edu/ ).…”

“…To evaluate the association between fire-sourced PM 2.5 and birthweight, we applied a sibling-matched case–control study, similar to our previous work ( Xue et al, 2021b ; Xue et al, 2021c ; Xue et al, 2021c ; Xue et al, 2019 ). We defined the descendants of the same mother as a family group of matched siblings and compared birthweights within each group.…”

Insights into the new WHO &lt;italic&gt;Global Air Quality Guidelines&lt;/italic&gt;

“…其次, 有别于传统的队列 数据, 健康大数据在环境流行病学中的应用极大提高了空气 污染暴露反应关系的人群代表性. 这些数据包括基于医保数 据 [21] 或者临床/疾病登记数据 [28] 构建的"新型"队列研究、基 于人口普查数据开展的"全"人群研究等 [29,30] .…”

A scoping review on the health effects of smoke haze from vegetation and peatland fires in Southeast Asia: Issues with study approaches and interpretation

“…Among the 70 studies, 42, 11, and 15 were EPI, HBE and HRA studies, respectively; two were both EPI and HBE. Forty-nine studies were conducted in the maritime area (Indonesia [ 41 , 44 – 57 ], Malaysia [ 29 , 58 – 68 ], Singapore [ 69 – 82 ], Brunei [ 83 , 84 ], multiple countries in maritime area [ 40 , 85 – 89 ]), 17 in the mainland area (Thailand [ 32 , 90 – 104 ], multiple countries in mainland area [ 105 ]); and 4 in multiple countries in the entire Southeast Asia [ 19 , 106 – 108 ] ( Fig 2 ). The breakdown of studies by country is as follows: 41 EPI [ 32 , 44 – 46 , 49 – 58 , 61 – 67 , 69 , 70 , 75 – 84 , 90 , 97 – 103 ], three HBE [ 41 , 47 , 104 ], and 15 HRA [ 29 , 48 , 59 , 60 , 68 , 71 – 74 , 91 – 96 ] studies were conducted in a single country (Indonesia, Malaysia, Singapore, Brunei, and Thailand); whereas one EPI study [ 85 ], eight HBE […”