Classification of health needs: a cluster analysis of older adults in urban areas

Abstract

BackgroundIn this study, a cross-sectional survey was used to understand and analyze the health status and health needs of the elderly in the community. The cluster analysis method was used to explore the relationship between health needs items and investigate the commonness among health demand items, to provide a reference for the development of health management of the elderly with chronic diseases.MethodsWe used convenience sampling to recruit the participants (aged 60 and above) from four urban community centers in Jinzhou City, Liaoning Province, China, in this study. This study uses the Medical Outcomes Study(MOS)36-Item Short-Form Health Survey. The self-designed questionnaire includes sociodemographic characteristics, chronic diseases, physical examination conditions, illness in the past two weeks, and a health needs questionnaire. SPSS 18.0 was used for data entry and analysis. Data analysis methods included descriptive statistical analysis, t-test, one-way analysis, cluster analysis, and linear multiple regression analysis.ResultsThe rate of health needs among the elderly in the community for various health services is 1.3–69.7%, of which the top three are: regular physical examination (69.7%), day Care Center (67.7%), the establishment of a Medical Alert Systems (66.1%). The health needs of the elderly in the community are divided into three categories: basic needs (24 items), health education (13 items), and first aid (2 items). The regression analysis found that the influencing factors of health status were age, revenue and expenditure, medical expenses, health education, basic needs, and first aid.ConclusionsThe community should strengthen the management of chronic diseases of the elderly and the publicity and education of related knowledge, and provide complementary health care services according to the health needs of the elderly, improve the health of the elderly, and improve the quality of life of the elderly.