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Multivariate Logistic regression analysis of the compliance in elderly diabetes and countermeasures / 中国生化药物杂志
Chinese Journal of Biochemical Pharmaceutics ; (6): 189-191, 2016.
Artículo en Chino | WPRIM | ID: wpr-506302
ABSTRACT
Objective To analyze the causes of poor compliance of elderly patients with diabetes mellitus , and put forward corresponding countermeasures to control blood glucose level and delay the occurrence of complications .Methods A total of 113 elderly patients with type 2 diabetes mellitus aged 60 years and over were recruited in endocrinology department of our hospital.The self-made questionnaire was used to investigate the compliance and the factors that affected the compliance.Results There were 48 patients (42.48%) with good compliance and 65 patients (57.52%) with poor compliance.Univariate analysis showed that the level of education, monthly income, drug types, understanding of diabetes-related knowledge and whether the elderly living alone affected compliance ( P<0.05 ) .Multivariate Logistic regression analysis showed that patients with low education level, poor monthly income, medication types and living alone were the main factors that influence the compliance of elderly patients with diabetes mellitus (P<0.05).And the level of education, monthly income level and the compliance of diabetic medication was positively correlated, medication types and living alone and diabetes compliance were negatively correlated (P<0.05).Conclusion The low level of education, poor monthly income, medication types and living alone are the main factors that affect the compliance of elderly patients with diabetes.The social and family support can effectively improve the compliance of elder patients with diabetes.

Texto completo: Disponible Índice: WPRIM (Pacífico Occidental) Idioma: Chino Revista: Chinese Journal of Biochemical Pharmaceutics Año: 2016 Tipo del documento: Artículo

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Texto completo: Disponible Índice: WPRIM (Pacífico Occidental) Idioma: Chino Revista: Chinese Journal of Biochemical Pharmaceutics Año: 2016 Tipo del documento: Artículo