Environmental mixtures and body mass index in two prospective US-based cohorts of female nurses,Journal of Hazardous Materials

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Environmental mixtures and body mass index in two prospective US-based cohorts of female nurses
Journal of Hazardous Materials ( IF 12.2 ) Pub Date : 2024-09-10 , DOI: 10.1016/j.jhazmat.2024.135794
Boya Zhang ₁ , Jaime E Hart ₁ , Francine Laden ₂ , Matthew Bozigar ₃ , Peter James ₄

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We estimated the joint effect of particulate matter ≤ 2.5 µm in diameter (PM2.5), nitrogen dioxide (NO2), seasonal temperature, noise, greenness, light at night, and neighborhood socioeconomic status (NSES) on body mass index (BMI) in a mixture context among 194,966 participants from the Nurses’ Health Study (NHS) and Nurses’ Health Study II (NHSII) over 30 years. BMI was calculated from self-reported weight and height. Single- and multi-exposure generalized estimating equations models were used to estimate the difference in BMI per interquartile range (IQR) increase of environmental factors, and quantile g-computation methods were used to estimate joint associations. In both cohorts, we consistently observed positive associations of BMI with PM2.5 and NO2 concentrations as well as negative associations with light at night and NSES regardless modeling approach. A positive association with noise was only observed in NHS. Negative associations with greenness and winter temperature were only observed in NHSII. Overall, the changes in BMI per quintile increase in all eight exposures were −0.11 (−0.13, −0.08) in NHS and −0.39 (−0.41, −0.37) in NHSII, which were largely driven by air pollution and nighttime noise (18–45 %) in the positive direction and NSES (>70 %) in the negative direction. Future intervention on environmental factors, especially reducing PM2.5, NO2 and noise or improving the NSES, might be helpful to lower BMI.

中文翻译：

两个前瞻性美国女护士队列的环境混合物和体重指数

我们估计了直径≤ 2.5 μm 颗粒物（PM2.5）、二氧化氮（NO2）、季节性温度、噪音、绿度、夜间光线和社区社会经济地位（NSES）对体重指数（BMI）的联合影响来自护士健康研究（NHS）和护士健康研究 II （NHSII）的 194,966 名参与者在 30 年内。BMI 是根据自我报告的体重和身高计算的。使用单次和多次暴露广义估计方程模型来估计环境因素每四分位距（IQR）增加的 BMI 差异，并使用分位数 g 计算方法估计联合关联。在这两个队列中，无论建模方法如何，我们都一致观察到 BMI 与 PM2.5 和 NO2 浓度的正相关以及与夜间光线和 NSES 的负相关。仅在 NHS 中观察到与噪声的正相关。仅在 NHSII 中观察到与绿色度和冬季温度的负相关。总体而言，在所有八次暴露中，每五分之一暴露的BMI变化在NHS中为-0.11 （-0.13， -0.08），在NHSII中为-0.39 （-0.41， -0.37），这主要是由空气污染和夜间噪音（18-45%）驱动的，而NSES（>70%）在负方向上。未来对环境因素的干预，特别是减少 PM2.5、NO2 和噪音或改善 NSES，可能有助于降低 BMI。

更新日期：2024-09-10

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