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Background  To determine the prevalence of depressive symptoms and to explore related factors of depressive symptoms in hemodialysis (HD) patients in northern China.    Methods  We used a cross-sectional research design to recruit 227 chronic kidney disease (CKD) patients who were undergoing HD treatment in northern China during December, 2012 to March, 2013. The Chinese edition of the Center for Epidemiologic Studies Depression (CES-D) was used to measure depressive symptoms. Information on quality of life (QOL), activities of daily living (ADL), social support status, coping style, self-efficacy, ego resiliency and demographic characteristics was all collected by face to face interview. Multivariate logistic regression analysis was used to explore related factors of depressive symptoms.    Results  The prevalence of depressive symptoms among HD patients was 29.1%. Patients with a lower mood have worse ADL and QOL than patients with better mood. Patients with a lower mood have got less social support than patients with better mood, including both family support and outside family support. For coping style, patients with a lower mood were more inclined to choose “acceptance-resignation” coping style than patients with better mood, while the result is opposite in “avoidance” coping style. And patients with a better mood have better self-efficacy and ego resiliency than patients with lower mood. Multivariate logistic regression analyses revealed that ADL (OR = 1.124,  p  = 0.002), family support (OR = 0.867,  p  = 0.021), “acceptance-resignation” coping style (OR = 1.228,  p  = 0.022), and ego resiliency (OR = 0.944,  p  = 0.021) were associated with low mood independently.    Conclusions  The prevalence of depressive symptoms is high in CKD patients on HD in northern China. activities of daily living, family support, “acceptance-resignation” coping style and ego resiliency were independently associated with depressive symptoms.

Prevalence and related factors of depressive symptoms in hemodialysis patients in northern China