Abstract：
BACKGROUND: Little is known about the impact of environmental exposure change on metabolic biomarkers associated with cancer risk. Furthermore, this limited epidemiological evidence on metabolic biomarkers focused on residential exposure, without considering the activity space which can be done by modelling dynamic exposures. In this longitudinal study, we aimed to investigate the impact of environmental exposures change on metabolic biomarkers using GPS-GIS based measurements.
METHODS: Among two weight loss interventions, the Reach for Health and the MENU studies, which included ∼460 women at risk of breast cancer or breast cancer survivors residing in Southern California, three metabolic biomarkers (insulin resistance, fasting glucose, and C-reactive protein) were assessed. Dynamic GPS-GIS based exposure to green spaces, recreation, walkability, NO2, and PM2.5 were calculated at baseline and 6 months follow-up using time-weighted spatial averaging. Generalized estimating equations models were used to examine the relationship between changes in environmental exposures and biomarker levels over time.
RESULTS: Overall, six-month environmental exposure change was not associated with metabolic biomarkers change. Stratified analyses by level of environmental exposures at baseline revealed that reduced NO2 and PM2.5 exposure was associated with reduced fasting glucose concentration among women living in a healthier environment at baseline (β -0.010, 95%CI -0.025, 0.005; β -0.019, 95%CI -0.034, -0.003, respectively). Women living in poor environmental conditions at baseline and exposed to greener environments had decreased C-reactive protein concentrations (β -1.001, 95%CI -1.888, -0.131).
CONCLUSIONS: The impact of environmental exposure changes on metabolic biomarkers over time may be modified by baseline exposure conditions.
METHODS: Among two weight loss interventions, the Reach for Health and the MENU studies, which included ∼460 women at risk of breast cancer or breast cancer survivors residing in Southern California, three metabolic biomarkers (insulin resistance, fasting glucose, and C-reactive protein) were assessed. Dynamic GPS-GIS based exposure to green spaces, recreation, walkability, NO2, and PM2.5 were calculated at baseline and 6 months follow-up using time-weighted spatial averaging. Generalized estimating equations models were used to examine the relationship between changes in environmental exposures and biomarker levels over time.
RESULTS: Overall, six-month environmental exposure change was not associated with metabolic biomarkers change. Stratified analyses by level of environmental exposures at baseline revealed that reduced NO2 and PM2.5 exposure was associated with reduced fasting glucose concentration among women living in a healthier environment at baseline (β -0.010, 95%CI -0.025, 0.005; β -0.019, 95%CI -0.034, -0.003, respectively). Women living in poor environmental conditions at baseline and exposed to greener environments had decreased C-reactive protein concentrations (β -1.001, 95%CI -1.888, -0.131).
CONCLUSIONS: The impact of environmental exposure changes on metabolic biomarkers over time may be modified by baseline exposure conditions.
摘要：
背景：关于环境暴露变化对与癌症风险相关的代谢生物标志物的影响知之甚少。此外，关于代谢生物标志物的有限流行病学证据集中在住宅暴露上，而不考虑可以通过对动态曝光进行建模来完成的活动空间。在这项纵向研究中，我们旨在使用基于GPS-GIS的测量,研究环境暴露变化对代谢生物标志物的影响.
方法：在两种减肥干预措施中，接触健康和菜单研究，其中包括460名有乳腺癌风险的女性或居住在南加州的乳腺癌幸存者，三种代谢生物标志物(胰岛素抵抗，空腹血糖,和C反应蛋白）进行评估。基于动态GPS-GIS的绿色空间暴露，娱乐,适行性,使用时间加权空间平均在基线和6个月随访时计算NO2和PM2.5。使用广义估计方程模型来检查环境暴露与生物标志物水平随时间的变化之间的关系。
结果：总体而言，6个月的环境暴露变化与代谢生物标志物变化无关.基线环境暴露水平分层分析显示，NO2和PM2.5暴露减少与基线生活在健康环境中的女性空腹血糖浓度降低相关（分别为β-0.010,95CI-0.025,0.005;β-0.019,95CI-0.034,-0.003）。基线时生活在恶劣环境条件下并暴露于绿色环境的女性C反应蛋白浓度降低（β-1.001,95CI-1.888,-0.131）。
结论：环境暴露随时间变化对代谢生物标志物的影响可能会被基线暴露条件所改变。
方法：在两种减肥干预措施中，接触健康和菜单研究，其中包括460名有乳腺癌风险的女性或居住在南加州的乳腺癌幸存者，三种代谢生物标志物(胰岛素抵抗，空腹血糖,和C反应蛋白）进行评估。基于动态GPS-GIS的绿色空间暴露，娱乐,适行性,使用时间加权空间平均在基线和6个月随访时计算NO2和PM2.5。使用广义估计方程模型来检查环境暴露与生物标志物水平随时间的变化之间的关系。
结果：总体而言，6个月的环境暴露变化与代谢生物标志物变化无关.基线环境暴露水平分层分析显示，NO2和PM2.5暴露减少与基线生活在健康环境中的女性空腹血糖浓度降低相关（分别为β-0.010,95CI-0.025,0.005;β-0.019,95CI-0.034,-0.003）。基线时生活在恶劣环境条件下并暴露于绿色环境的女性C反应蛋白浓度降低（β-1.001,95CI-1.888,-0.131）。
结论：环境暴露随时间变化对代谢生物标志物的影响可能会被基线暴露条件所改变。
