Contribution of greenness, air pollution, and residential food environment to excess gestational weight gain: A cross-sectional study in Wuhan, China.
Prev Med
; 186: 108086, 2024 Jul 24.
Article
em En
| MEDLINE
| ID: mdl-39059478
ABSTRACT
OBJECTIVES:
Our goal was to explore how greenness, air pollution, and residential food environment were linked to excessive gestational weight gain (EGWG), and to estimate their combined effects on this condition.METHOD:
This cross-sectional analysis included 51,507 pregnant women from the Wuhan Maternal and Child Health Management Information System between 2016 and 2019. Generalized linear mixed regression models were employed to explore the relationships between greenness, air pollution, residential food environmental exposure, and EGWG; and the combined effects were further estimated by cluster analysis and principal components analysis.RESULT:
We only found a significant association between convenience store density within the 250 m buffer zone (OR = 1.03 and 95% CI 1.01,1.05) and EGWG. In terms of air pollution, sulfur dioxide(SO2), particulate matter with a diameter of 10 µm or less(PM10), and particulate matter with a diameter of 2.5 µm or less(PM2.5) were substantially correlated with a higher prevalence of EGWG and higher GWG, with (OR = 1.16 and 95% CI 1.12,1.21; OR = 1.12 and 95% CI 1.08,1.16; OR = 1.17 and 95% CI 1.14,1.21, respectively) per interquartile range(IQR) increase. Cluster analysis revealed the presence of three clusters representing urban exposures. In contrast to urban environment clusters characterized by favourable conditions, those exhibiting elevated air pollution levels, high-density residential food environment and low levels of greenness were found to have increased odds of EGWG (OR = 1.10, 95% CI 1.03, 1.19).CONCLUSION:
This study emphasizes that exposure to elevated air pollution, high-density residential neighbourhood food environments, and low levels of greenness is a neighbourhood obesogenic environment for pregnant women.
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Coleções:
01-internacional
Base de dados:
MEDLINE
Idioma:
En
Ano de publicação:
2024
Tipo de documento:
Article