Shi Chen1, Shirui Wang2, Tiantian Li3, Huijuan Zhu1, Siyu Liang2, Ke Xu4, Yuelun Zhang5, Xianxian Yuan1, Yingying Yang1, Hui Pan1, Xiaoming Shi3. 1. Department of Endocrinology, Key Laboratory of Endocrinology of National Health Commission, Peking Union Medical College Hospital (PUMCH), Chinese Academy of Medical Sciences & Peking Union Medical College (CAMS & PUMC), Beijing, China. 2. Eight-year Program of Clinical Medicine, PUMCH, CAMS & PUMC, Beijing, China. 3. National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China. 4. Department of Endocrinology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, China. 5. Central Research Laboratory, PUMCH, CAMS & PUMC, Beijing, China.
Abstract
BACKGROUND: Macrosomia is associated with both neonatal complications and adult diseases (obesity, diabetes mellitus, etc.). Previous studies have reported maternal exposure to PM2.5 might influence metabolism and fetal development and cause adverse pregnancy outcomes. Studies conducted in areas with low PM2.5 concentration have found relationship between gestational PM2.5 exposure and birth weight. However, the impact of air pollution on macrosomia has not been studied, especially in highly polluted areas. OBJECTIVE: To evaluate the association between fine particulate matter (PM2.5) exposure during pregnancy and the risk of macrosomia. METHODS: Data from preconception health examination and prenatal and postnatal records were collected from 1 January 2010 to 31 December 2012 in the National Free Preconception Health Examination Project. Monthly mean of PM2.5 concentration during pregnancy was estimated from satellite data using an ensemble machine learning model. A newborn with birth weight above 4000 g was defined as macrosomia. Logistic regression models were used to examine the association between maternal exposure to PM2.5 and the risk of macrosomia, after adjusting for maternal age, pre-pregnancy body mass index, parity, neonatal sex, duration of gestation, seasonality, educational level, smoking and drinking habits, past history of diabetes mellitus and hypertension, and family history of diabetes mellitus. Restricted cubic spline models were used to evaluate the dose-response relationship between the risk of macrosomia and PM2.5 concentration. RESULTS: Of 177 841 singleton nonlow birth weight newborns included, 14 598 (8.2%) had macrosomia. The mean PM2.5 concentrations were 70.7, 71.5, and 80.9 μg/m3 in the first, second, and third trimesters. In full-adjusted logistic regression models, significant associations were found between increased risk of macrosomia and every 10 μg/m3 increase of PM2.5 concentration over the first (odds ratio [OR]: 1.045; 95% CI, 1.037-1.052), second (OR: 1.035; 95% CI, 1.028-1.043), and third (OR: 1.033; 95% CI, 1.026-1.039) trimesters. There was a nonlinear does-response association between PM2.5 concentration and the risk of macrosomia. CONCLUSIONS: Maternal exposure to PM2.5 during pregnancy was associated with an increased risk of macrosomia in China.
BACKGROUND:Macrosomia is associated with both neonatal complications and adult diseases (obesity, diabetes mellitus, etc.). Previous studies have reported maternal exposure to PM2.5 might influence metabolism and fetal development and cause adverse pregnancy outcomes. Studies conducted in areas with low PM2.5 concentration have found relationship between gestational PM2.5 exposure and birth weight. However, the impact of air pollution on macrosomia has not been studied, especially in highly polluted areas. OBJECTIVE: To evaluate the association between fine particulate matter (PM2.5) exposure during pregnancy and the risk of macrosomia. METHODS: Data from preconception health examination and prenatal and postnatal records were collected from 1 January 2010 to 31 December 2012 in the National Free Preconception Health Examination Project. Monthly mean of PM2.5 concentration during pregnancy was estimated from satellite data using an ensemble machine learning model. A newborn with birth weight above 4000 g was defined as macrosomia. Logistic regression models were used to examine the association between maternal exposure to PM2.5 and the risk of macrosomia, after adjusting for maternal age, pre-pregnancy body mass index, parity, neonatal sex, duration of gestation, seasonality, educational level, smoking and drinking habits, past history of diabetes mellitus and hypertension, and family history of diabetes mellitus. Restricted cubic spline models were used to evaluate the dose-response relationship between the risk of macrosomia and PM2.5 concentration. RESULTS: Of 177 841 singleton nonlow birth weight newborns included, 14 598 (8.2%) had macrosomia. The mean PM2.5 concentrations were 70.7, 71.5, and 80.9 μg/m3 in the first, second, and third trimesters. In full-adjusted logistic regression models, significant associations were found between increased risk of macrosomia and every 10 μg/m3 increase of PM2.5 concentration over the first (odds ratio [OR]: 1.045; 95% CI, 1.037-1.052), second (OR: 1.035; 95% CI, 1.028-1.043), and third (OR: 1.033; 95% CI, 1.026-1.039) trimesters. There was a nonlinear does-response association between PM2.5 concentration and the risk of macrosomia. CONCLUSIONS: Maternal exposure to PM2.5 during pregnancy was associated with an increased risk of macrosomia in China.
Authors: Maya A Deyssenroth; Maria José Rosa; Melissa N Eliot; Karl T Kelsey; Itai Kloog; Joel D Schwartz; Gregory A Wellenius; Shouneng Peng; Ke Hao; Carmen J Marsit; Jia Chen Journal: Environ Res Date: 2021-05-18 Impact factor: 8.431
Authors: Kristina W Whitworth; Alison Rector; Jennifer Ish; Suneet P J Chauhan; Jesús Ibarluzea; Mònica Guxens; Michael D Swartz; Elaine Symanski; Carmen Iñiguez Journal: Epidemiology Date: 2022-05-01 Impact factor: 4.860