• Login
    Search 
    •   Home
    • Search
    •   Home
    • Search
    JavaScript is disabled for your browser. Some features of this site may not work without it.

    Browse

    All of eScholarship@UMassChanCommunitiesPublication DateAuthorsUMass Chan AffiliationsTitlesDocument TypesKeywords

    My Account

    LoginRegister

    Filter by Category

    Date Issued2015 (1)2013 (1)2011 (1)AuthorBalasubramanian, Raji (3)Ma, Yunsheng (3)Sepavich, Deidre M. (3)
    Zorn, Martha (3)
    Culver, Annie L. (2)View MoreUMass Chan AffiliationDepartment of Medicine, Division of Preventive and Behavioral Medicine (3)Document TypeJournal Article (3)KeywordWomen's Health (3)Antidepressive Agents (2)Community Health and Preventive Medicine (2)Depression (2)Diabetes Mellitus (2)View MoreJournalAmerican journal of public health (1)BMC endocrine disorders (1)Diabetes Care (1)

    Help

    AboutSubmission GuidelinesData Deposit PolicySearchingTerms of UseWebsite Migration FAQ

    Statistics

    Most Popular ItemsStatistics by CountryMost Popular Authors
     

    Search

    Show Advanced FiltersHide Advanced Filters

    Filters

    • Publications
    • Profiles

    Now showing items 1-3 of 3

    • List view
    • Grid view
    • Sort Options:
    • Relevance
    • Title Asc
    • Title Desc
    • Issue Date Asc
    • Issue Date Desc
    • Results Per Page:
    • 5
    • 10
    • 20
    • 40
    • 60
    • 80
    • 100

    • 3CSV
    • 3RefMan
    • 3EndNote
    • 3BibTex
    • Selective Export
    • Select All
    • Help
    Thumbnail

    Marginal structural models for the estimation of the risk of Diabetes Mellitus in the presence of elevated depressive symptoms and antidepressant medication use in the Women's Health Initiative observational and clinical trial cohorts

    Frisard, Christine; Gu, Xiangdong; Whitcomb, Brian; Ma, Yunsheng; Pekow, Penelope; Zorn, Martha; Sepavich, Deidre M.; Balasubramanian, Raji (2015-10-12)
    BACKGROUND: We evaluate the combined effect of the presence of elevated depressive symptoms and antidepressant medication use with respect to risk of type 2 diabetes among approximately 120,000 women enrolled in the Women's Health Initiative (WHI), and compare several different statistical models appropriate for causal inference in non-randomized settings. METHODS: Data were analyzed for 52,326 women in the Women's Health Initiative Clinical Trials (CT) Cohort and 68,169 women in the Observational Study (OS) Cohort after exclusions. We included follow-up to 2005, resulting in a median duration of 7.6 years of follow up after enrollment. Results from three multivariable Cox models were compared to those from marginal structural models that included time varying measures of antidepressant medication use, presence of elevated depressive symptoms and BMI, while adjusting for potential confounders including age, ethnicity, education, minutes of recreational physical activity per week, total energy intake, hormone therapy use, family history of diabetes and smoking status. RESULTS: Our results are consistent with previous studies examining the relationship of antidepressant medication use and risk of type 2 diabetes. All models showed a significant increase in diabetes risk for those taking antidepressants. The Cox Proportional Hazards models using baseline covariates showed the lowest increase in risk , with hazard ratios of 1.19 (95 % CI 1.06 - 1.35) and 1.14 (95 % CI 1.01 - 1.30) in the OS and CT, respectively. Hazard ratios from marginal structural models comparing antidepressant users to non-users were 1.35 (95 % CI 1.21 - 1.51) and 1.27 (95 % CI 1.13 - 1.43) in the WHI OS and CT, respectively - however, differences among estimates from traditional Cox models and marginal structural models were not statistically significant in both cohorts. One explanation suggests that time-dependent confounding was not a substantial factor in these data, however other explanations exist. Unadjusted Cox Proportional Hazards models showed that women with elevated depressive symptoms had a significant increase in diabetes risk that remained after adjustment for confounders. However, this association missed the threshold for statistical significance in propensity score adjusted and marginal structural models. CONCLUSIONS: Results from the multiple approaches provide further evidence of an increase in risk of type 2 diabetes for those on antidepressants.
    Thumbnail

    Relations of Depressive Symptoms and Antidepressant Use to Body Mass Index and Selected Biomarkers for Diabetes and Cardiovascular Disease

    Ma, Yunsheng; Balasubramanian, Raji; Pagoto, Sherry L.; Schneider, Kristin L.; Hebert, James R.; Phillips, Lawrence S.; Goveas, Joseph S.; Culver, Annie L.; Olendzki, Barbara C.; Beck, James; et al. (2013-06-13)
    Objectives. We investigated whether depressive symptoms and antidepressant use are associated with biomarkers for glucose dysregulation and inflammation, body mass index (BMI), and waist circumference. Methods. Postmenopausal women were recruited into the Women's Health Initiative from 1993 to 1998, and data were collected at regular intervals through 2005. We used multiple linear regression models to examine whether depressive symptoms and antidepressant use are associated with BMI, waist circumference, and biomarkers. Results. Analysis of data from 71 809 women who completed all relevant baseline and year 3 assessments showed that both elevated depressive symptoms and antidepressant use were significantly associated with higher BMI and waist circumference. Among 1950 women, elevated depressive symptoms were significantly associated with increased insulin levels and measures of insulin resistance. Analyses of baseline data from 2242 women showed that both elevated depressive symptoms and antidepressant use were associated with higher C-reactive protein levels. Conclusions. Monitoring body habitus and other biomarkers among women with elevated depression symptoms or taking antidepressant medication may be prudent to prevent diabetes and cardiovascular disease. (Am J Public Health. Published online ahead of print June 13, 2013: e1-e10. doi:10.2105/AJPH.2013.301394).
    Thumbnail

    Elevated Depressive Symptoms, Antidepressant Use, and Diabetes in a Large Multiethnic National Sample of Postmenopausal Women

    Ma, Yunsheng; Balasubramanian, Raji; Pagoto, Sherry L.; Schneider, Kristin L.; Culver, Annie L.; Olendzki, Barbara C.; Tinker, Lesley; Liu, Simin; Safford, Monika M.; Sepavich, Deidre M.; et al. (2011-11-01)
    OBJECTIVE To examine elevated depressive symptoms and antidepressant use in relation to diabetes incidence in the Women’s Health Initiative. RESEARCH DESIGN AND METHODS A total of 161,808 postmenopausal women were followed for over an average of 7.6 years. Hazard ratios (HRs) estimating the effects of elevated depressive symptoms and antidepressant use on newly diagnosed incident diabetes were obtained using Cox proportional hazards models adjusted for known diabetes risk factors. RESULTS Multivariable-adjusted HRs indicated an increased risk of incident diabetes with elevated baseline depressive symptoms (HR 1.14 [95% CI 1.08–1.21]) and antidepressant use (1.20 [1.09–1.32]). These associations persisted in year 3 data, in which respective adjusted HRs were 1.23 (1.09–1.39) and 1.31 (1.14–1.50). CONCLUSIONS Postmenopausal women with elevated depressive symptoms and who use antidepressants have a greater risk of developing incident diabetes. In addition, longstanding elevated depressive symptoms and recent antidepressant medication use increase the risk of incident diabetes.
    DSpace software (copyright © 2002 - 2023)  DuraSpace
    Lamar Soutter Library, UMass Chan Medical School | 55 Lake Avenue North | Worcester, MA 01655 USA
    Quick Guide | escholarship@umassmed.edu
    Open Repository is a service operated by 
    Atmire NV
     

    Export search results

    The export option will allow you to export the current search results of the entered query to a file. Different formats are available for download. To export the items, click on the button corresponding with the preferred download format.

    By default, clicking on the export buttons will result in a download of the allowed maximum amount of items.

    To select a subset of the search results, click "Selective Export" button and make a selection of the items you want to export. The amount of items that can be exported at once is similarly restricted as the full export.

    After making a selection, click one of the export format buttons. The amount of items that will be exported is indicated in the bubble next to export format.