Background: Residential greenness, measured using satellite data, is associated with lower cortisol, but evidence for other hormones during pregnancy is limited. Google Street View (GSV) images provide pedestrian perspectives, allowing assessment of specific greenness features. Objective: This study aimed to evaluate associations between residential greenness and multiple hair steroid levels during pregnancy, using both satellite and ground-level greenness exposure. Methods: Hair steroids (cortisol, cortisone, progesterone, and dehydroepiandrosterone) during the second trimester were quantified using liquid chromatography-mass spectrometry in 385 pregnant individuals. We used first-trimester hair cortisol data. Based on geocoded birth addresses, mean residential greenness was calculated using satellite-based Normalized Difference Vegetation Index (NDVI) data at 100-, 300-, and 500-m buffers in a cross-sectional approach. Deep learning algorithms were applied to 176,196 GSV images to estimate % total greenness, grass, plants, and trees within a 100-m buffer of participants’ residences. Linear models and Generalized Estimating Equations were used to evaluate associations between greenness tertiles and hair steroids. Results: During the second trimester, in adjusted models, exposure to the highest compared with the lowest tertile of mean NDVI was associated with significantly lower mean z-cortisol levels within all buffers. Higher mean NDVI within the 500-m buffer was associated with significantly lower mean z-cortisone levels. For GSV images, higher % grass was associated with lower z-cortisol and z-cortisone levels. Using repeated measures of hair cortisol demonstrated similar results, with lower mean z-cortisol levels across the first and second trimesters. Conclusion: Living in greener areas during the second trimester of pregnancy is associated with lower chronic stress markers, especially hair cortisol and cortisone.
Bhattacharya et al. (2026) studied this question.