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The association of depression and diabetes across methods, measures, and study contexts
BACKGROUND: Empirical research has revealed a positive relationship between type 2 diabetes mellitus and depression, but questions remain regarding timing of depression measurement, types of instruments used to measure depression, and whether “depression” is defined as clinical depression or depress...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5755050/ https://www.ncbi.nlm.nih.gov/pubmed/29318033 http://dx.doi.org/10.1186/s40842-017-0052-1 |
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author | Hunter, Jaimie C. DeVellis, Brenda M. Jordan, Joanne M. Sue Kirkman, M. Linnan, Laura A. Rini, Christine Fisher, Edwin B. |
author_facet | Hunter, Jaimie C. DeVellis, Brenda M. Jordan, Joanne M. Sue Kirkman, M. Linnan, Laura A. Rini, Christine Fisher, Edwin B. |
author_sort | Hunter, Jaimie C. |
collection | PubMed |
description | BACKGROUND: Empirical research has revealed a positive relationship between type 2 diabetes mellitus and depression, but questions remain regarding timing of depression measurement, types of instruments used to measure depression, and whether “depression” is defined as clinical depression or depressive symptoms. The present study sought to establish the robustness of the depression-diabetes relationship across depression definition, severity of depressive symptoms, recent depression, and lifetime depression in a nationally representative dataset and a large rural dataset. METHODS: The present examination, conducted between 2014 and 2015, used two large secondary datasets: the National Health and Nutrition Examination Survey (NHANES) from 2007 to 2008 (n = 3072) and the Arthritis, Coping, and Emotion Study (ACES) from 2002 to 2006 (n = 2300). Depressive symptoms in NHANES were measured using the Patient Health Questionnaire 9-item survey (PHQ-9). ACES used the Center for Epidemiologic Studies—Depression Scale (CES-D) to measure depressive symptoms and the Composite International Diagnostic Interview (CIDI) to measure diagnosable depression. Diabetes was modelled as the dichotomous outcome variable (presence vs. absence of diabetes). Logistic regression was used for all analyses, most of which were cross-sectional. Analyses controlled for age, ethnicity, sex, education, and body mass index, and NHANES analyses used sample weights to account for the complex survey design. Additional analyses using NHANES data focused on the addition of health behavior variables and inflammation to the model. RESULTS: NHANES. Every one-point increase in depressive symptoms was associated with a 5% increase in odds of having diabetes [OR: 1.05 (CI: 1.03, 1.07)]. These findings persisted after controlling for health behaviors and inflammation. ACES. For every one-point increase in depressive symptom score, odds of having diabetes increased by 2% [OR: 1.02 (CI: 1.01, 1.03)]. Recent (past 12 months) depression [OR: 1.49, (CI: 1.03, 2.13)] and lifetime depression [OR: 1.40 (CI: 1.09, 1.81)] were also significantly associated with having diabetes. CONCLUSIONS: This study provides evidence for the robustness of the relationship between depression or depressive symptoms and diabetes and demonstrates that depression occurring over the lifetime can be associated with diabetes just as robustly as that which occurs more proximal to the time of study measurement. |
format | Online Article Text |
id | pubmed-5755050 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-57550502018-01-09 The association of depression and diabetes across methods, measures, and study contexts Hunter, Jaimie C. DeVellis, Brenda M. Jordan, Joanne M. Sue Kirkman, M. Linnan, Laura A. Rini, Christine Fisher, Edwin B. Clin Diabetes Endocrinol Research Article BACKGROUND: Empirical research has revealed a positive relationship between type 2 diabetes mellitus and depression, but questions remain regarding timing of depression measurement, types of instruments used to measure depression, and whether “depression” is defined as clinical depression or depressive symptoms. The present study sought to establish the robustness of the depression-diabetes relationship across depression definition, severity of depressive symptoms, recent depression, and lifetime depression in a nationally representative dataset and a large rural dataset. METHODS: The present examination, conducted between 2014 and 2015, used two large secondary datasets: the National Health and Nutrition Examination Survey (NHANES) from 2007 to 2008 (n = 3072) and the Arthritis, Coping, and Emotion Study (ACES) from 2002 to 2006 (n = 2300). Depressive symptoms in NHANES were measured using the Patient Health Questionnaire 9-item survey (PHQ-9). ACES used the Center for Epidemiologic Studies—Depression Scale (CES-D) to measure depressive symptoms and the Composite International Diagnostic Interview (CIDI) to measure diagnosable depression. Diabetes was modelled as the dichotomous outcome variable (presence vs. absence of diabetes). Logistic regression was used for all analyses, most of which were cross-sectional. Analyses controlled for age, ethnicity, sex, education, and body mass index, and NHANES analyses used sample weights to account for the complex survey design. Additional analyses using NHANES data focused on the addition of health behavior variables and inflammation to the model. RESULTS: NHANES. Every one-point increase in depressive symptoms was associated with a 5% increase in odds of having diabetes [OR: 1.05 (CI: 1.03, 1.07)]. These findings persisted after controlling for health behaviors and inflammation. ACES. For every one-point increase in depressive symptom score, odds of having diabetes increased by 2% [OR: 1.02 (CI: 1.01, 1.03)]. Recent (past 12 months) depression [OR: 1.49, (CI: 1.03, 2.13)] and lifetime depression [OR: 1.40 (CI: 1.09, 1.81)] were also significantly associated with having diabetes. CONCLUSIONS: This study provides evidence for the robustness of the relationship between depression or depressive symptoms and diabetes and demonstrates that depression occurring over the lifetime can be associated with diabetes just as robustly as that which occurs more proximal to the time of study measurement. BioMed Central 2018-01-04 /pmc/articles/PMC5755050/ /pubmed/29318033 http://dx.doi.org/10.1186/s40842-017-0052-1 Text en © The Author(s). 2018 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Article Hunter, Jaimie C. DeVellis, Brenda M. Jordan, Joanne M. Sue Kirkman, M. Linnan, Laura A. Rini, Christine Fisher, Edwin B. The association of depression and diabetes across methods, measures, and study contexts |
title | The association of depression and diabetes across methods, measures, and study contexts |
title_full | The association of depression and diabetes across methods, measures, and study contexts |
title_fullStr | The association of depression and diabetes across methods, measures, and study contexts |
title_full_unstemmed | The association of depression and diabetes across methods, measures, and study contexts |
title_short | The association of depression and diabetes across methods, measures, and study contexts |
title_sort | association of depression and diabetes across methods, measures, and study contexts |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5755050/ https://www.ncbi.nlm.nih.gov/pubmed/29318033 http://dx.doi.org/10.1186/s40842-017-0052-1 |
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