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Journal Article
Research Support, Non-U.S. Gov't
Predictors of depression in Chinese community-dwelling people with type 2 diabetes.
Journal of Clinical Nursing 2009 May
AIMS: To examine levels of perceived social support and depression and to identify the related factors and predictors of depression among Chinese community-dwelling people with type 2 diabetes.
BACKGROUND: People with type 2 diabetes have a high risk for depression. Depression is a serious issue that leads to poor metabolic control and increased health care costs. However, little is known about the factors contributing to depression in Chinese people with type 2 diabetes.
DESIGN: A cross-sectional, descriptive correlation design was used.
METHODS: A convenient sample consisting of 148 people with type 2 diabetes participated. Personal information questionnaire was used to obtain socio-demographic characteristics; Zung Self-Rating Depression Scale and Multidimensional Scale of Perceived Social Support were used to measure depression and perceived social support, respectively. Spearman's correlation and Stepwise multiple regression analysis were used in data analysis.
RESULTS: The mean index score for depression was 46.53 and 39.2% of the subjects reported depression. The mean score for perceived social support was 5.24. Age, education level, marital status, monthly family income, living status, work status, regular exercise, duration of diabetes, diabetic complications, other chronic diseases and perceived social support were significantly correlated with depression. The best predictors of depression were perceived social support, duration of diabetes, regular exercise, work status and other chronic diseases.
CONCLUSIONS: Depression was common in people with type 2 diabetes. The people who had lower levels of perceived social support, longer diabetic duration, did not exercise regularly, were unemployed or retired and had other chronic diseases were more likely to report depression.
RELEVANCE TO CLINICAL PRACTICE: Nurses working in communities should assist people with type 2 diabetes in earlier detecting and treating their depression. Nurses should also design practical interventions to decrease depressive symptoms of those people through improving their diabetic conditions and perceived social support.
BACKGROUND: People with type 2 diabetes have a high risk for depression. Depression is a serious issue that leads to poor metabolic control and increased health care costs. However, little is known about the factors contributing to depression in Chinese people with type 2 diabetes.
DESIGN: A cross-sectional, descriptive correlation design was used.
METHODS: A convenient sample consisting of 148 people with type 2 diabetes participated. Personal information questionnaire was used to obtain socio-demographic characteristics; Zung Self-Rating Depression Scale and Multidimensional Scale of Perceived Social Support were used to measure depression and perceived social support, respectively. Spearman's correlation and Stepwise multiple regression analysis were used in data analysis.
RESULTS: The mean index score for depression was 46.53 and 39.2% of the subjects reported depression. The mean score for perceived social support was 5.24. Age, education level, marital status, monthly family income, living status, work status, regular exercise, duration of diabetes, diabetic complications, other chronic diseases and perceived social support were significantly correlated with depression. The best predictors of depression were perceived social support, duration of diabetes, regular exercise, work status and other chronic diseases.
CONCLUSIONS: Depression was common in people with type 2 diabetes. The people who had lower levels of perceived social support, longer diabetic duration, did not exercise regularly, were unemployed or retired and had other chronic diseases were more likely to report depression.
RELEVANCE TO CLINICAL PRACTICE: Nurses working in communities should assist people with type 2 diabetes in earlier detecting and treating their depression. Nurses should also design practical interventions to decrease depressive symptoms of those people through improving their diabetic conditions and perceived social support.
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