Satellite and ground-level residential greenness and hair steroid hormones during pregnancy.

IF 4.2 Q2 ENVIRONMENTAL SCIENCES
Sohini Bhattacharya, Yaron Michael, Nadezhda Sokolova, Noam David, Maya Levhar, Anat Schonblum, Liat Arnon, Liat Salzer Sheelo, Michal Eisner, Eran Hadar, Israel Meizner, Arnon Wiznitzer, Aron Weller, Lee Koren, Keren Agay-Shay
{"title":"Satellite and ground-level residential greenness and hair steroid hormones during pregnancy.","authors":"Sohini Bhattacharya, Yaron Michael, Nadezhda Sokolova, Noam David, Maya Levhar, Anat Schonblum, Liat Arnon, Liat Salzer Sheelo, Michal Eisner, Eran Hadar, Israel Meizner, Arnon Wiznitzer, Aron Weller, Lee Koren, Keren Agay-Shay","doi":"10.1097/EE9.0000000000000492","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>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.</p><p><strong>Objective: </strong>This study aimed to evaluate associations between residential greenness and multiple hair steroid levels during pregnancy, using both satellite and ground-level greenness exposure.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusion: </strong>Living in greener areas during the second trimester of pregnancy is associated with lower chronic stress markers, especially hair cortisol and cortisone.</p>","PeriodicalId":11713,"journal":{"name":"Environmental Epidemiology","volume":"10 3","pages":"e492"},"PeriodicalIF":4.2000,"publicationDate":"2026-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13232905/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Environmental Epidemiology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1097/EE9.0000000000000492","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
引用次数: 0

Abstract

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.

卫星和地面住宅绿化和毛发类固醇激素在怀孕期间。
背景:使用卫星数据测量的住宅绿化与较低的皮质醇有关,但怀孕期间其他激素的证据有限。谷歌街景(GSV)图像提供行人视角,允许评估特定的绿化特征。目的:本研究旨在通过卫星和地面绿化暴露来评估孕期住宅绿化与多种毛发类固醇水平之间的关系。方法:采用液相色谱-质谱法对385例妊娠中期的毛发激素(皮质醇、可的松、黄体酮和脱氢表雄酮)进行定量分析。我们使用了孕早期的毛发皮质醇数据。基于地理编码的出生地址,采用基于卫星的归一化植被指数(NDVI)数据,在100米、300米和500米缓冲区采用横断面方法计算平均住宅绿化度。深度学习算法应用于176,196张GSV图像,以估计参与者住所100米缓冲区内的绿化,草,植物和树木的百分比。线性模型和广义估计方程被用来评估绿色分位数和毛发类固醇之间的关系。结果:在妊娠中期,在调整后的模型中,暴露于平均NDVI的最高分位数与最低分位数相比,与所有缓冲液中较低的平均z-皮质醇水平显著相关。500 m缓冲区内较高的平均NDVI与较低的平均z-可的松水平相关。对于GSV图像,较高的草百分比与较低的z-皮质醇和z-可的松水平相关。对头发皮质醇的重复测量也显示出类似的结果,在孕早期和孕中期,平均z-皮质醇水平较低。结论:孕中期生活在绿化地区的妇女慢性应激指标较低,尤其是毛发皮质醇和可的松。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Environmental Epidemiology
Environmental Epidemiology Medicine-Public Health, Environmental and Occupational Health
CiteScore
5.70
自引率
2.80%
发文量
71
审稿时长
25 weeks
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信
小红书