A time series analysis of ambient air pollution and low birth weight in Xuzhou, China

Hao, Jingwen; Peng, Lei; Cheng, Peng; Li, Sha; Zhang, Chao; Fu, Weinan; Dou, Lianjie; Yang, Fan; Hao, Jiahu

doi:10.1080/09603123.2020.1867828

Cited by 6 publications

(2 citation statements)

References 39 publications

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“…Over the past decade, numerous studies have been published on air pollutant exposure and low birth weight in China ( 12 , 26 , 27 ). The study by Yuan et al ( 28 ) reported critical windows of gestational exposure to PM 2.5 were identified as 31st−34th gestational weeks for reduced birth weight, and 38th−42nd weeks for LBW, respectively.…”

Section: Discussionmentioning

confidence: 99%

Associations between maternal exposure to ambient air pollution and very low birth weight: A birth cohort study in Chongqing, China

Zhou

Ming²,

Yang³

et al. 2023

Front. Public Health

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IntroductionThere have been many researches done on the association between maternal exposure to ambient air pollution and adverse pregnancy outcomes, but few studies related to very low birth weight (VLBW). This study thus explores the association between maternal exposure to ambient air pollutants and the risk of VLBW, and estimates the sensitive exposure time window.MethodsA retrospective cohort study analyzed in Chongqing, China, during 2015–2020. The Generalized Additive Model were applied to estimate exposures for each participant during each trimester and the entire pregnancy period.ResultsFor each 10 μg/m3 increase in PM2.5 during pregnancy, the relative risk of VLBW increased on the first trimester, with RR = 1.100 (95% CI: 1.012, 1.195) in the single-pollutant model. Similarly, for each 10 μg/m3 increase in PM10, there was a 12.9% (RR = 1.129, 95% CI: 1.055, 1.209) increase for VLBW on the first trimester in the single-pollutant model, and an 11.5% (RR = 1.115, 95% CI: 1.024, 1.213) increase in the multi-pollutant model, respectively. The first and second trimester exposures of NO2 were found to have statistically significant RR values for VLBW. The RR values on the first trimester were 1.131 (95% CI: 1.037, 1.233) and 1.112 (95% CI: 1.015, 1.218) in the single-pollutant model and multi-pollutant model, respectively; The RR values on the second trimester were 1.129 (95% CI: 1.027, 1.241) and 1.146 (95% CI: 1.038, 1.265) in the single-pollutant model and multi-pollutant model, respectively. The RR of O3 exposure for VLBW on the entire trimester was 1.076 (95% CI: 1.010–1.146), and on the second trimester was 1.078 (95% CI: 1:016, 1.144) in the single-pollutant model.ConclusionThis study indicates that maternal exposure to high levels of PM2.5, PM10, NO2, and O3 during pregnancy may increase the risk of very low birth weight, especially for exposure on the first and second trimester. Reducing the risk of early maternal exposure to ambient air pollution is thus necessary for pregnant women.

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Section: Discussionmentioning

confidence: 99%

Associations between maternal exposure to ambient air pollution and very low birth weight: A birth cohort study in Chongqing, China

Zhou

Ming²,

Yang³

et al. 2023

Front. Public Health

View full text Add to dashboard Cite

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“…Research on the determinant factors that influence LBW has shown that the upper arm circumference of pregnant women and gestational age are risk factors for LBW [16], [25], [26]. Besides, the study also reveals that the stress conditions of pregnant women [12], sanitation [18], [22], [27], information and education during pregnancy [28], wealth and family income [29], [30], smoke and air pollution [31], [32] are proven to affect the cause of LBW .…”

Section: A the Determinant Factors Of Low-birth-weight Infantsmentioning

confidence: 99%

The Spatial and Flexible Model for Low-Birth-Weight Prediction

Nugroho¹,

Sulistyono²,

Iriany³

et al. 2022

Int. J. Adv. Sci. Eng. Inf. Technol.

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The case of Low Birth Weight (LBW) in Indonesia is still high. Based on data from the Central Agency on Statistics (BPS), the case of LBW in East Java is still high, with about 20,836 people in 2016 and 14,882 people in 2017. Many factors trigger LBW, especially women's condition and nutritional intake during pregnancy. This study aims to establish a location-based LBW prediction model using a spatial and flexible model. This research was conducted using a Geographically Weighted Regression (GWR) model in East Java and a flexible model with a genetic programming approach. Endogenous variables (Y) portrayed LBW cases in East Java and exogenous variables were the Percentage of Early Marriage (X1), Human Development Index (X2), Number of Midwives (X3), K1 Visit (X4), K4 Visit (X5), Consumption of Fe 30 (X6), and Consumption of Fe 90 (X7). Based on the analysis results using the GWR model, global equation models, and local models 38 models were obtained with R 2 = 82.06%. Meanwhile, based on the results of the analysis with a flexible model with a deep learning approach, the model was obtained with R 2 = 84.8%. From this study, it can be concluded that the GWR model and the flexible model have the same level of accuracy. However, the flexible model can show the nonlinear effect of the variables X1 and X3.

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Associations between congenital heart disease and air pollutants at different gestational weeks: a time-series analysis

Zhang

Yang

Liu

et al. 2022

Environ Geochem Health

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A time series analysis of ambient air pollution and low birth weight in Xuzhou, China

Cited by 6 publications

References 39 publications

Associations between maternal exposure to ambient air pollution and very low birth weight: A birth cohort study in Chongqing, China

Associations between maternal exposure to ambient air pollution and very low birth weight: A birth cohort study in Chongqing, China

The Spatial and Flexible Model for Low-Birth-Weight Prediction

Associations between congenital heart disease and air pollutants at different gestational weeks: a time-series analysis

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