Residential greenness and air pollution concerning excessive gestational weight gain during pregnancy: A cross-sectional study in Wuhan, China

环境卫生 空气污染 环境科学 人口 污染物 医学 化学 有机化学
作者
Miyuan Wang,Wen Chen,Haiqin Qi,Ke Xu,Mengna Wei,Wenqi Xia,Lan Lv,Zhengrong Duan,Jianduan Zhang
出处
期刊:Environmental Research [Elsevier]
卷期号:217: 114866-114866 被引量:3
标识
DOI:10.1016/j.envres.2022.114866
摘要

Previous studies have indicated that exposure to residential greenness may benefit the health status of pregnant women, and air pollution may exert a mediating effect. Gestational weight gain (GWG) is an important indicator of pregnant women and fetuses' health and nutrition status. However, evidence concerning the impact of residential greenness on excessive gestational weight gain (EGWG) is scarce, and to what extent air pollution in urban settings mediates this relationship remains unclear.This study aims to explore the association of residential greenness with EGWG, consider the mediating effect of air pollution, and estimate the combined impact of residential greenness and air pollution exposures on EGWG.This population-based cross-sectional study involved 51,507 pregnant women with individual-level data on residential addresses in the Wuhan Maternal and Child Health Management Information System. Two spectral indexes, the normalized difference vegetation index (NDVI) and soil-adjusted vegetation index (SAVI), were used to proxy residential greenness. The air pollution data included six indicators (PM2.5, PM10, SO2, CO, NO2, O3) and used the Ordinary Kriging interpolation method to estimate overall pregnancy exposure to air pollutants. Generalized linear mixed regression models were utilized to explore the relationship between residential greenness and EGWG. Restricted cubic spline (RCS) models were developed to examine the dose-response relationships. Mediation analyses explored the potential mediating role of air pollution in the residential greenness-EGWG associations. Finally, the weighted-quantile-sum (WQS) regression model was used to investigate the association between residential greenness-air pollutants co-exposure and EGWG.Among all participants, 26,442 had EGWG. In the adjusted model, the negative association was found significant for NDVI100-m, NDVI200-m, and NDVI500-m with EGWG. For example, each IQR increase in NDVI100-m was associated with 2.8% (95% CI: 0.6-5.0) lower odds for EGWG. The result of WQS regression showed that, when considering the six air pollutants and NDVI-100m together, both positive and negative WQS indices were significantly associated with EGWG, PM10, PM2.5, with SO2 having significant weights in the positive effect direction and CO, O3, NO2, and NDVI100-m having a negative effect. Our results also suggested that SO2, NO2, PM10, PM2.5, and CO significantly mediated the association between NDVI-100m and EGWG, and our estimates were generally robust in the sensitivity analysis.Exposure to a higher level of residential greenness is associated with a reduced risk of EGWG, in which air pollution may exert a mediating effect. Pregnant women might benefit more in gaining healthy gestational weight when greenness levels increase from low to medium than from medium to high. Given the current cross-sectional study design, large-sale prospective cohort studies are needed to confirm our findings further.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
Mrsummer发布了新的文献求助10
刚刚
小郭发布了新的文献求助10
1秒前
拓跋箴发布了新的文献求助10
1秒前
2秒前
淡淡的航空完成签到,获得积分10
2秒前
sqz完成签到,获得积分10
2秒前
梦城完成签到,获得积分10
3秒前
852应助科研通管家采纳,获得10
3秒前
3秒前
慕青应助Nisaix采纳,获得10
3秒前
华仔应助科研通管家采纳,获得30
3秒前
3秒前
3秒前
CodeCraft应助科研通管家采纳,获得10
3秒前
思源应助科研通管家采纳,获得10
4秒前
wsyiming完成签到,获得积分10
4秒前
英姑应助科研通管家采纳,获得10
4秒前
香蕉觅云应助科研通管家采纳,获得10
4秒前
我是老大应助科研通管家采纳,获得10
4秒前
4秒前
4秒前
我喜欢高浩洋应助niu采纳,获得10
4秒前
5秒前
5秒前
7秒前
7秒前
脑洞疼应助快乐的远航采纳,获得10
7秒前
小冰完成签到,获得积分10
7秒前
科研通AI6.3应助张巨锋采纳,获得10
7秒前
万能图书馆应助飞鱼采纳,获得10
7秒前
情怀应助生动的翠容采纳,获得10
8秒前
所所应助林沫采纳,获得10
8秒前
8秒前
林木完成签到,获得积分10
8秒前
领导范儿应助hhh采纳,获得10
8秒前
传奇3应助Mrsummer采纳,获得10
10秒前
10秒前
CipherSage应助酒酿圆子采纳,获得10
10秒前
10秒前
秋子完成签到,获得积分10
12秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Handbook of pharmaceutical excipients, Ninth edition 5000
Aerospace Standards Index - 2026 ASIN2026 3000
Signals, Systems, and Signal Processing 610
Discrete-Time Signals and Systems 610
Research Methods for Business: A Skill Building Approach, 9th Edition 500
Social Work and Social Welfare: An Invitation(7th Edition) 410
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 纳米技术 有机化学 物理 生物化学 化学工程 计算机科学 复合材料 内科学 催化作用 光电子学 物理化学 电极 冶金 遗传学 细胞生物学
热门帖子
关注 科研通微信公众号,转发送积分 6053426
求助须知:如何正确求助?哪些是违规求助? 7872390
关于积分的说明 16278311
捐赠科研通 5198785
什么是DOI,文献DOI怎么找? 2781636
邀请新用户注册赠送积分活动 1764556
关于科研通互助平台的介绍 1646184