Maternal ambient air pollution exposure with spatial-temporal variations and preterm birth risk assessment during 2013–2017 in Zhejiang Province, China

Overview of statistical methods for estimating the relative risk of delayed respiratory effect related to ambient air pollution exposure

Przeglad Epidemiologiczny ◽

10.32394/pe.74.61 ◽

2020 ◽

pp. 695-706

Keyword(s):

Risk Assessment ◽

Air Pollution ◽

Relative Risk ◽

Health Effect ◽

Poisson Model ◽

Ambient Air ◽

Ambient Air Pollution ◽

Distributed Lag ◽

Air Pollution Exposure ◽

Pollution Exposure

INTRODUCTION. The occurrence of smog episodes and their significant impact on human health have forced research focused on risk assessment. Over the years, methods of exposure measuring have been improved, as well as statistical models necessary to the biological response estimation including the risk of incidence or death. AIM. The aim of presented study is to review and evaluate possibilities of statistical methods of delayed respiratory health effects risk assessment related to ambient air pollution exposure. MATERIAL AND METHODS. The review of published data was carried using the PubMed platform from 1994 to the 2020 year. Over 80 references were include in the analysis identifying general characteristics, construction of models estimating the relative risk of respiratory incidents with delayed health effect, and modelling tools available in statistical packages R, SAS, and Statistica. RESULTS. Among various methods of health risk assessment, the Almon model, the Poisson model, and the Distributed Lag Non-Linear Models (DLNM) were most common used. Initially, the Poisson model was used, close to 60% of the cited works apply this method. The interest in the nonlinear modelling implementation has increased (34% of cited papers) in recent years. Mostly researchers used R or SAS statistical software. Usually, was calculated the relative risk of health effect related to short-term exposure (up to a week). About 75% of available papers concern measurements of relative risk in response to the concentration of pollution increase by unit=10 μg/m3. Other describe the risk associated with the exposure increasing by the interquartile range (IQR). CONCLUSIONS. Distributed Lag Non-linear Model DLNM is classified as the statistical tool recommended by researchers due to its flexibility in defining, simplicity in interpretation, and increasingly frequent applications to environmental epidemiology.

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Exposure-Lag-Response Association between Prenatal Ambient Air Pollution Exposure and Preterm Birth in Guangzhou, China

ISEE Conference Abstracts ◽

10.1289/isesisee.2018.o03.02.10 ◽

2018 ◽

Vol 2018 (1) ◽

Author(s):

Qiong Wang ◽

Tarik Benmarhnia ◽

Changchang Li ◽

Luke Knibbs ◽

Huanhuan Zhang ◽

...

Keyword(s):

Air Pollution ◽

Preterm Birth ◽

Ambient Air ◽

Ambient Air Pollution ◽

Air Pollution Exposure ◽

Pollution Exposure

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The Association between Preterm Birth and Ambient Air Pollution Exposure in Shiyan, China, 2015–2017

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18084326 ◽

2021 ◽

Vol 18 (8) ◽

pp. 4326

Author(s):

Qihao Chen ◽

Zhan Ren ◽

Yujie Liu ◽

Yunfei Qiu ◽

Haomin Yang ◽

...

Keyword(s):

Air Pollution ◽

Preterm Birth ◽

Pregnancy Outcomes ◽

Air Pollutants ◽

Ambient Air ◽

Ambient Air Pollution ◽

Air Pollution Exposure ◽

Exposure Windows ◽

Pollution Exposure ◽

Gestational Duration

Shortening of the gestational duration has been found associated with ambient air pollution exposure. However, the critical exposure windows of ambient air pollution for gestational duration remain inconsistent, and the association between ambient air pollution and early term births (ETB, 37 to 38 weeks) has rarely been studied relative to preterm births (PTB, 28–37 weeks). A time-series study was conducted in Shiyan, a medium-sized city in China. Birth information was collected from the Shiyan Maternity and Child Health Hospital, and 13,111 pregnant women who gave birth between 2015 and 2017 were included. Data of the concentrations of air pollutants, including PM10, PM2.5, NO2, and SO2 and meteorological data, were collected in the corresponding gestational period. The Cox regression analysis was performed to estimate the relationship between ambient air pollution exposure and the risk of preterm birth after controlling the confounders, including maternal age, education, Gravidity, parity, fetal gender, and delivery mode. Very preterm birth (VPTB, 28–32 weeks) as a subtype of PTB was also incorporated in this study. The risk of VPTB and ETB was positively associated with maternal ambient air pollution exposure, and the correlation of gaseous pollutants was stronger than particulate matter. With respect to exposure windows, the critical trimester of air pollutants for different adverse pregnancy outcomes was different. The exposure windows of PM10, PM2.5, and SO2 for ETB were found in the third trimester, with HRs (hazard ratios) of 1.06 (95%CI: 1.04, 1.09), 1.07 (95%CI: 1.04, 1.11), and 1.28 (95%CI: 1.20, 1.35), respectively. However, for NO2, the second and third trimesters exhibited similar results, the HRs reaching 1.10 (95%CI: 1.03, 6.17) and 1.09 (95%CI: 1.03,1.15), respectively. This study extends and strengthen the evidence for a significant correlation between the ambient air pollution exposure during pregnancy and the risk of not only PTB but, also, ETB. Moreover, our findings suggest that the exposure windows during pregnancy vary with different air pollutants and pregnancy outcomes.

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