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Prevalence of Depression among Rural Residents with Diabetes Mellitus: A Cross-Sectional Study from Northeast China

Recent economic development in China has resulted in large increases in psychogenic and metabolic diseases. However, few studies have focused on the mental status of rural residents with diabetes. We aimed to investigate the prevalence of depressive symptoms among patients with diabetes to establish...

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Autores principales: Yu, Shasha, Yang, Hongmei, Guo, Xiaofan, Zheng, Liqiang, Sun, Yingxian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4923999/
https://www.ncbi.nlm.nih.gov/pubmed/27240394
http://dx.doi.org/10.3390/ijerph13060542
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author Yu, Shasha
Yang, Hongmei
Guo, Xiaofan
Zheng, Liqiang
Sun, Yingxian
author_facet Yu, Shasha
Yang, Hongmei
Guo, Xiaofan
Zheng, Liqiang
Sun, Yingxian
author_sort Yu, Shasha
collection PubMed
description Recent economic development in China has resulted in large increases in psychogenic and metabolic diseases. However, few studies have focused on the mental status of rural residents with diabetes. We aimed to investigate the prevalence of depressive symptoms among patients with diabetes to establish the association between depressive symptoms and socio-demographic and clinical factors. We conducted a cross-sectional analysis of 1187 patients with diabetes aged ≥35 years from rural Northeast China. Metabolic and anthropometric indicators were measured according to standard methods. Depressive symptoms were defined using the Patient Health Questionnaire-9 (PHQ-9). Five hundred and twenty-six residents (44.3%) of the total sample were male and 931 (78.4%) were <65 years old. One hundred and eight residents (8.76%) score ≥10 on the PHQ-9 scale. A statistically significant relationship was found between depressive symptoms and female gender, older age (≥65 years), high school or above education level, moderate physical activity, high family income, multiple additional illnesses, current alcohol consumption, and 7–8 h/d sleep duration. Multivariate analysis showed that female gender [odds ratio (OR) = 1.984, p = 0.028], high family income (OR = 0.483 for 5000–20,000 CNY/year, p = 0.011; OR = 0.356 for >2000 CNY/year, p = 0.003), 7–8 h/d sleep duration (OR = 0.453, p = 0.020), and having multiple additional illness (OR = 3.080, p < 0.001) were significantly associated with depressive symptoms. Prevalence of depressive symptoms in our study was high. Female gender and multiple illnesses were risk factors for depression, while long sleep duration and high family income seem to protect against depression among rural residents with diabetes in China.
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spelling pubmed-49239992016-07-05 Prevalence of Depression among Rural Residents with Diabetes Mellitus: A Cross-Sectional Study from Northeast China Yu, Shasha Yang, Hongmei Guo, Xiaofan Zheng, Liqiang Sun, Yingxian Int J Environ Res Public Health Article Recent economic development in China has resulted in large increases in psychogenic and metabolic diseases. However, few studies have focused on the mental status of rural residents with diabetes. We aimed to investigate the prevalence of depressive symptoms among patients with diabetes to establish the association between depressive symptoms and socio-demographic and clinical factors. We conducted a cross-sectional analysis of 1187 patients with diabetes aged ≥35 years from rural Northeast China. Metabolic and anthropometric indicators were measured according to standard methods. Depressive symptoms were defined using the Patient Health Questionnaire-9 (PHQ-9). Five hundred and twenty-six residents (44.3%) of the total sample were male and 931 (78.4%) were <65 years old. One hundred and eight residents (8.76%) score ≥10 on the PHQ-9 scale. A statistically significant relationship was found between depressive symptoms and female gender, older age (≥65 years), high school or above education level, moderate physical activity, high family income, multiple additional illnesses, current alcohol consumption, and 7–8 h/d sleep duration. Multivariate analysis showed that female gender [odds ratio (OR) = 1.984, p = 0.028], high family income (OR = 0.483 for 5000–20,000 CNY/year, p = 0.011; OR = 0.356 for >2000 CNY/year, p = 0.003), 7–8 h/d sleep duration (OR = 0.453, p = 0.020), and having multiple additional illness (OR = 3.080, p < 0.001) were significantly associated with depressive symptoms. Prevalence of depressive symptoms in our study was high. Female gender and multiple illnesses were risk factors for depression, while long sleep duration and high family income seem to protect against depression among rural residents with diabetes in China. MDPI 2016-05-28 2016-06 /pmc/articles/PMC4923999/ /pubmed/27240394 http://dx.doi.org/10.3390/ijerph13060542 Text en © 2016 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC-BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Yu, Shasha
Yang, Hongmei
Guo, Xiaofan
Zheng, Liqiang
Sun, Yingxian
Prevalence of Depression among Rural Residents with Diabetes Mellitus: A Cross-Sectional Study from Northeast China
title Prevalence of Depression among Rural Residents with Diabetes Mellitus: A Cross-Sectional Study from Northeast China
title_full Prevalence of Depression among Rural Residents with Diabetes Mellitus: A Cross-Sectional Study from Northeast China
title_fullStr Prevalence of Depression among Rural Residents with Diabetes Mellitus: A Cross-Sectional Study from Northeast China
title_full_unstemmed Prevalence of Depression among Rural Residents with Diabetes Mellitus: A Cross-Sectional Study from Northeast China
title_short Prevalence of Depression among Rural Residents with Diabetes Mellitus: A Cross-Sectional Study from Northeast China
title_sort prevalence of depression among rural residents with diabetes mellitus: a cross-sectional study from northeast china
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4923999/
https://www.ncbi.nlm.nih.gov/pubmed/27240394
http://dx.doi.org/10.3390/ijerph13060542
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