Assessing the association between prenatal ambient temperature and extreme low birth weight in South Asia
Year: 2025
Type: article
Study design: Observational Study
Abstract: BACKGROUND: Previous studies have suggested the negative effects of exposure to high temperature during pregnancy on multiple adverse birth outcomes. However, there is a lack of evidence regarding the exposure-response relationship and future risk projections for extreme low birth weight (ELBW) in South Asia. METHODS: A total of 393,530 pregnant women from Bangladesh, India, Nepal, and Pakistan were included in this analysis. Annual mean temperature throughout each woman's entire gestational period was estimated from the fifth generation of the European Re-Analysis Land Dataset (ERA5-land). We employed the multivariable mixed effect regression model, incorporating random effects for survey strata, to assess the relationship between temperature and ELBW. RESULTS: Stepwise regression models show robust and monotonically varying exposure-response relationships. In the fully adjusted model, for every 1 °C increase in temperature, the risk of ELBW may increase by 1.41 % (95 % CI: 0.99 %, 1.85 %), while birth weight may decrease by -2.26 g (95 % CI: 3.47, -1.04). We found that 2.25 % (95 % CI: 1.26 %, 3.25 %) of ELBW risk can be attributed to annual mean temperature in South Asia, with India having the highest attributed risk (AF = 3.01 %, 95 % CI: 2.48 %, 3.53 %), followed by Bangladesh (AF = 2.81 %, 95 % CI: 2.32 %, 3.29 %). Several environmental, maternal, and household factors may modify the relationship between ambient temperature and ELBW. The risk of ELBW related to temperature rise would increase in the future, especially under the unrestricted emission scenario (e.g. SSP585). CONCLUSIONS: In South Asia, greater risks and burdens of ELBW were observed with increasing prenatal ambient temperature. A deeper understanding of covariant factors and intervention measures were needed to address maternal and child health issues under climate change.
Authors: Siqi Ai, Dongjing Zhang, Jingyuan Cao, Jianyong Lu, Liecheng Hong, Haiyan He, Xiaotao Zhou
Language: English
Subfield: Health, Toxicology and Mutagenesis
Field: Environmental Science
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $3,800
Award: G2017989905
OpenAlex ID: W4410468445
