Exploring the impact of environmental exposure changes on metabolic biomarkers: A 6-month GPS-GIS study among women with overweight or obesity

被引：1

作者：

Letellier, Noemie ^{[1
,7
]}

Yang, Jiue-An ^{[2
]}

Alismail, Sarah ^{[2
]}

Nukavarapu, Nivedita ^{[2
]}

Hartman, Sheri J. ^{[3
]}

Rock, Cheryl L. ^{[4
]}

Sears, Dorothy D. ^{[5
]}

Jankowska, Marta M. ^{[2
]}

Benmarhnia, Tarik ^{[1
,6
]}

机构：

[1] Univ Calif San Diego, Scripps Inst Oceanog, San Diego, CA USA

[2] City Hope Natl Med Ctr, Beckman Res Inst, Populat Sci, 1500 E Duarte Rd, Duarte, CA 91010 USA

[3] Univ Calif San Diego, Herbert Wertheim Sch Publ Hlth & Human Longev Sci, San Diego, CA USA

[4] Univ Calif San Diego, Sch Med, Dept Family Med, La Jolla, CA USA

[5] Arizona State Univ, Coll Hlth Solut, Phoenix, AZ USA

[6] Univ Rennes, Irset, Inserm, EHESP,UMR S 1085, Rennes, France

[7] 8885 Biol Grade, La Jolla, CA 92037 USA

来源：

ENVIRONMENTAL RESEARCH | 2024年 / 243卷

关键词：

Neighborhood environment; Built environment; Pollution; Activity space; Chronic disease; Dynamic movement; BREAST-CANCER; INSULIN-RESISTANCE; WEIGHT-LOSS;

D O I：

10.1016/j.envres.2023.117881

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

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 similar to 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 (beta -0.010, 95%CI -0.025, 0.005; beta -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 (beta -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.

引用

页数：7