4.8 Article

Urinary metal mixtures and longitudinal changes in glucose homeostasis: The Study of Women's Health Across the Nation (SWAN)

期刊

ENVIRONMENT INTERNATIONAL
卷 145, 期 -, 页码 -

出版社

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.envint.2020.106109

关键词

Metals; Mixtures; Insulin resistance; beta-cell dysfunction; Women

资金

  1. National Institutes of Health (NIH), DHHS, through the National Institute on Aging (NIA)
  2. National Institute of Nursing Research (NINR)
  3. NIH Office of Research on Women's Health (ORWH) [U01NR004061, U01AG012505, U01AG012535, U01AG012531, U01AG012539, U01AG012546, U01AG012553, U01AG012554, U01AG012495]
  4. National Institute of Environmental Health Sciences (NIEHS) [R01ES026578, R01-ES026964, P30-ES017885]
  5. Center for Disease Control and Prevention (CDC)/National Institute for Occupational Safety and Health (NIOSH) [T42-OH008455]
  6. National Center for Research Resources
  7. National Center for Advancing Translational Sciences, National Institutes of Health, through UCSF-CTSI [UL1 RR024131]
  8. [U01AG017719]

向作者/读者索取更多资源

Background: Epidemiologic studies on associations between metals and insulin resistance and beta-cell dysfunction have been cross-sectional and focused on individual metals. Objective: We assessed the association of exposure to metal mixtures, based on assessment of 15 urinary metals, with both baseline levels and longitudinal changes in homeostatic model assessments for insulin resistance (HOMA-IR) and beta-cell function (HOMA-beta). Methods: We examined 1262 women, aged 45-56 years at baseline (1999-2000), who were followed through 2015-2016, from the Study of Women's Health Across the Nation. Urinary concentrations of 15 metals (arsenic, barium, cadmium, cobalt, cesium, copper, mercury, manganese, molybdenum, nickel, lead, antimony, tin, thallium, and zinc) were determined at baseline. HOMA-IR and HOMA-beta were repeatedly measured over 16 years of follow-up. A two-stage modeling was used to account for correlations in dependent and independent variables: In stage-1, linear mixed effects models were used to estimate the participant-specific baseline HOMA levels from random intercepts and participant-specific rates of changes from random slopes. In stage-2, adaptive elastic-net (AENET) models were fit to identify components of metal mixtures associated with participant-specific baseline levels and rates of changes in HOMA-IR and HOMA-beta, respectively. An environmental risk score (ERS) was used to integrate metal mixture effects from AENET results. Results: In multivariable adjusted AENET models, urinary zinc was associated with higher HOMA-IR at baseline, whereas molybdenum was associated with lower HOMA-IR at baseline. The estimated changes in baseline HOMA-IR for one standard deviation increase in log-transformed urinary metal concentrations were 5.76% (3.05%, 8.55%) for zinc and 3.25% ( 5.45%, 1.00%) for molybdenum, respectively. Urinary zinc was also associated with lower HOMA-beta at baseline. Arsenic was associated with a slightly faster rate of decline in HOMA-beta in the AENET model evaluating associations between metals and rate of changes. Significant associations of ERS with both HOMA-IR and HOMA-beta at baseline were observed. ERS for the rate of changes was not calculated and examined in relation to rates of changes in HOMA-IR and HOMA-beta because only a single metal was selected by AENET. Conclusion: Exposure to metal mixtures may be exerting effects on insulin resistance and beta-cell dysfunction, which might be mechanisms by which metal exposures lead to elevated diabetes risks.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.8
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据