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      The Bidirectional Association Between Depression and Severe Hypoglycemic and Hyperglycemic Events in Type 1 Diabetes

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          Abstract

          OBJECTIVE

          Severe hyperglycemia and hypoglycemia (“severe dysglycemia”) are serious complications of type 1 diabetes (T1D). Depression has been associated with severe dysglycemia in type 2 diabetes but has not been thoroughly examined specifically in T1D. We evaluated bidirectional associations between depression and severe dysglycemia among older people with T1D.

          RESEARCH DESIGN AND METHODS

          We abstracted depression and severe dysglycemia requiring emergency room visit or hospitalization from medical health records in 3,742 patients with T1D during the study period (1996–2015). Cox proportional hazards models estimated the associations between depression and severe dysglycemia in both directions, adjusting for demographics, micro- and macrovascular complications, and HbA 1c.

          RESULTS

          During the study period, 41% had depression and 376 (11%) and 641 (20%) had hyperglycemia and hypoglycemia, respectively. Depression was strongly associated with a 2.5-fold increased risk of severe hyperglycemic events (hazard ratio [HR] 2.47 [95% CI 2.00, 3.05]) and 89% increased risk of severe hypoglycemic events (HR 1.89 [95% CI 1.61, 2.22]). The association was strongest within the first 6 months (HR hyperglycemia 7.14 [95% CI 5.29, 9.63]; HR hypoglycemia 5.58 [95% CI 4.46, 6.99]) to 1 year (HR hyperglycemia 5.16 [95% CI 3.88, 6.88]; HR hypoglycemia 4.05 [95% CI 3.26, 5.04]) after depression diagnosis. In models specifying severe dysglycemia as the exposure, hyperglycemic and hypoglycemic events were associated with 143% (HR 2.43 [95% CI 2.03, 2.91]) and 74% (HR 1.75 [95% CI 1.49, 2.05]) increased risk of depression, respectively.

          CONCLUSIONS

          Depression and severe dysglycemia are associated bidirectionally among patients with T1D. Depression greatly increases the risk of severe hypoglycemic and hyperglycemic events, particularly in the first 6 months to 1 year after diagnosis, and depression risk increases after severe dysglycemia episodes.

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          Most cited references 44

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          Defining and reporting hypoglycemia in diabetes: a report from the American Diabetes Association Workgroup on Hypoglycemia.

            (2005)
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            Overcoming the absence of socioeconomic data in medical records: validation and application of a census-based methodology.

             John Krieger (1992)
            Most US medical records lack socioeconomic data, hindering studies of social gradients in health and ascertainment of whether study samples are representative of the general population. This study assessed the validity of a census-based approach in addressing these problems. Socioeconomic data from 1980 census tracts and block groups were matched to the 1985 membership records of a large prepaid health plan (n = 1.9 million), with the link provided by each individual's residential address. Among a subset of 14,420 Black and White members, comparisons were made of the association of individual, census tract, and census block-group socioeconomic measures with hypertension, height, smoking, and reproductive history. Census-level and individual-level socioeconomic measures were similarly associated with the selected health outcomes. Census data permitted assessing response bias due to missing individual-level socioeconomic data and also contextual effects involving the interaction of individual- and neighborhood-level socioeconomic traits. On the basis of block-group characteristics, health plan members generally were representative of the total population; persons in impoverished neighborhoods, however, were underrepresented. This census-based methodology offers a valid and useful approach to overcoming the absence of socioeconomic data in most US medical records.
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              Depression and poor glycemic control: a meta-analytic review of the literature.

              Depression is common among patients with diabetes, but its relationship to glycemic control has not been systematically reviewed. Our objective was to determine whether depression is associated with poor glycemic control. Medline and PsycINFO databases and published reference lists were used to identify studies that measured the association of depression with glycemic control. Meta-analytic procedures were used to convert the findings to a common metric, calculate effect sizes (ESs), and statistically analyze the collective data. A total of 24 studies satisfied the inclusion and exclusion criteria for the meta-analysis. Depression was significantly associated with hyperglycemia (Z = 5.4, P < 0.0001). The standardized ES was in the small-to-moderate range (0.17) and was consistent, as the 95% CI was narrow (0.13-0.21). The ES was similar in studies of either type 1 or type 2 diabetes (ES 0.19 vs. 0.16) and larger when standardized interviews and diagnostic criteria rather than self-report questionnaires were used to assess depression (ES 0.28 vs. 0.15). Depression is associated with hyperglycemia in patients with type 1 or type 2 diabetes. Additional studies are needed to establish the directional nature of this relationship and to determine the effects of depression treatment on glycemic control and the long-term course of diabetes.
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                Author and article information

                Journal
                Diabetes Care
                Diabetes Care
                diacare
                dcare
                Diabetes Care
                Diabetes Care
                American Diabetes Association
                0149-5992
                1935-5548
                March 2018
                18 December 2017
                : 41
                : 3
                : 446-452
                Affiliations
                1Division of Research, Kaiser Permanente, Oakland, CA
                2Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA
                3Icahn School of Medicine at Mount Sinai, New York, NY
                4The Joseph Sagol Neuroscience Center, Sheba Medical Center, Ramat Gan, Israel
                Author notes
                Corresponding author: Paola Gilsanz, paola.gilsanz@ 123456kp.org .
                Article
                1566
                10.2337/dc17-1566
                5829958
                29255060
                © 2017 by the American Diabetes Association.

                Readers may use this article as long as the work is properly cited, the use is educational and not for profit, and the work is not altered. More information is available at http://www.diabetesjournals.org/content/license.

                Counts
                Figures: 0, Tables: 3, Equations: 0, References: 43, Pages: 7
                Product
                Funding
                Funded by: National Institute on Aging, DOI http://dx.doi.org/10.13039/100000049;
                Award ID: R01 AG047500
                Funded by: National Institute on Aging, DOI http://dx.doi.org/10.13039/100000049;
                Award ID: T32 AG049663
                Funded by: National Institute of Diabetes and Digestive and Kidney Diseases, DOI http://dx.doi.org/10.13039/100000062;
                Award ID: R01 DK103721
                Award ID: R01 DK081796
                Funded by: National Institute of Diabetes and Digestive and Kidney Diseases, DOI http://dx.doi.org/10.13039/100000062;
                Award ID: P30 DK092924
                Categories
                0407
                Epidemiology/Health Services Research

                Endocrinology & Diabetes

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