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

• Published in: Environmental research 2023-01, Vol.217, p.114866-114866, Article 114866
• Main Authors: Wang, Miyuan, Wen, Chen, Qi, Haiqin, Xu, Ke, Wei, Mengna, Xia, Wenqi, Lv, Lan, Duan, Zhengrong, Zhang, Jianduan
• Format: Article
• Language: English
• Subjects: Air Pollutants - analysis; Air pollution; Air Pollution - analysis; Child; China - epidemiology; Cross-Sectional Studies; Excessive gestational weight gain; Female; Gestational Weight Gain; Humans; Mediating effect; Nitrogen Dioxide - analysis; Particulate Matter - analysis; Pregnancy; Prospective Studies; Residential greenness; Weight Gain
• ISSN: 0013-9351; 1096-0953
• DOI: 10.1016/j.envres.2022.114866

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 o