Zhongguo quanke yixue (Jan 2024)
Study on the Factors Affecting the Number of Chronic Diseases among Elderly Comorbidity Patients in Guangdong Province Based on the Model of Ecological Health
Abstract
Background The number of elderly comorbidity patients in our country is continuously increasing. With the accumulation of chronic diseases, older adults experience varying degrees of health loss. Currently, there is a lack of research analyzing the multi-level factors influencing the number of chronic conditions in elderly comorbidity patients. Objective To explore the factors influencing the number of chronic conditions in elderly patients from different levels combining with the etiology and characteristics of chronic diseases based on the health ecology model, so as to provide evidence for the management and prevention of chronic diseases in community-dwelling elderly comorbidity patients in our country. Methods In February 2023, a multi-stage stratified cluster random sampling method was used to select community-dwelling elderly (≥60 years old) comorbidity patients in Guangdong province as the survey subjects. A face-to-face interview was conducted using the "Survey Questionnaire on the Status and Influencing Factors of Elderly Patients with Multiple Chronic Conditions", which was based on the health ecology model and included five levels of individual trait, behavioral characteristic, interpersonal relationship, living and working conditions, and policy environment. The number of chronic conditions in elderly comorbidity patients was considered as the dependent variable, and an unordered multivariate Logistic regression analysis was conducted by incorporating independent variables according to the five levels. Results A total of 1 000 questionnaires were distributed, and 987 valid questionnaires were collected, with a recovery rate of 98.7%. Among the 987 elderly comorbidity patients, 346 (35.1%) had two concurrent chronic diseases, 456 (46.2%) had three concurrent chronic diseases, and 185 (18.7%) had more than three concurrent chronic diseases. The results of unordered multivariate logistic regression analysis showed that, compared to elderly patients with two concurrent chronic diseases, disease duration less than 6 years and 6-10 years, local urban household were risk factors for elderly patients with three concurrent chronic diseases (P<0.05), with OR (95%CI) values of 2.100 (1.284-3.435), 1.948 (1.201-3.158), and 4.103 (1.496-11.250), respectively. Having at least 6 hours of sleep daily, self-rating good health status, taking 1-3 types of medication daily, regularly participating in social activities, level of junior high school or below and high school/secondary school, and having urban employee medical insurance/rural resident medical insurance were protective factors for elderly patients with three concurrent chronic diseases (P<0.05), with OR (95%CI) values of 0.528 (0.322-0.867), 0.570 (0.325-0.998), 0.385 (0.261-0.569), 0.348 (0.208-0.582), 0.412 (0.175-0.972), 0.486 (0.298-0.790), and 0.392 (0.242-0.634), respectively. Being male, exercising less than 3 times a week were risk factors for elderly patients with more than three concurrent chronic diseases (P<0.05), with OR (95%CI) values of 2.563 (1.634-4.021), 2.990 (1.429-6.256), respectively. Having at least 6 hours of sleep daily, self-rating good and fair health status, taking 1-3 types of medication daily, having an annual average income below ≤30 000 and >30 000-50 000 yuan, and having urban employee medical insurance/rural resident medical insurance were protective factors for elderly patients with more than three concurrent chronic diseases (P<0.05), with OR (95%CI) values of 0.300 (0.159-0.565), 0.247 (0.125-0.487), 0.448 (0.240-0.837), 0.288 (0.178-0.467), 0.318 (0.155-0.654), 0.489 (0.293-0.816), and 0.416 (0.229-0.755), respectively. Conclusion The proportion of elderly comorbidity patients having 2-3 types of chronic diseases is relatively high in Guangdong province, accounting for over 80%. The factors influencing the number of chronic conditions in elderly comorbidity patients are complex, including gender, duration of disease, physical activity, sleep quality, self-rated health status, medication adherence, household registration type, supervision by children or family members in medication adherence or exercise, income level, educational level, and type of medical insurance. Moreover, there are significant differences in the risk factors across different comorbidity counts. Therefore, corresponding intervention measures should be implemented at different levels to reduce the number of chronic conditions in elderly comorbidity patients and improve their overall health level.
Keywords
