Affiliation:
1. Graduate School Shanghai University of Medicine & Health Sciences Shanghai China
2. Graduate School Shanghai University of Traditional Chinese Medicine Shanghai China
3. Department of integrated traditional Chinese and Western Medicine Shanghai University of Medicine and Health Sciences Affiliated Zhoupu Hospital Shanghai China
4. School of Nursing & Health Management Shanghai University of Medicine & Health Sciences Shanghai China
5. Department of medicine Kashgar Vocational and Technical College Kashgar China
6. School of Management Hainan Medical University Haikou China
7. School of Clinical Medicine Shanghai University of Medicine & Health Sciences Shanghai China
Abstract
AbstractAimTo compare the quality of life of patients with and without multimorbidity and investigate potential factors related to the quality of life in patients with multimorbidity.DesignA descriptive cross‐sectional study.MethodsThis study included 1778 residents with chronic diseases, including single disease (1255 people, average age: 60.78 ± 9.42) and multimorbidity (523 people, average age: 64.03 ± 8.91) groups, who were recruited from urban residents of Shanghai through a multistage, stratified, probability proportional to size sampling method. The quality of life was measured using the World Health Organization Quality of Life Questionnaire. The socio‐demographic data and psychological states were measured using a self‐made structured questionnaire, Self‐rating Anxiety Scale, and Self‐rating Depression Scale. Differences in demographic characteristics were estimated using Pearson's chi‐squared test, and independent t‐test or one‐way ANOVA followed by S‐N‐K test was used to compare the mean quality of life. Multiple linear regression analysis was conducted to identify risk factors for multimorbidity.ResultsThere were differences in age, education, income, and BMI between single‐disease and multimorbidity groups, but no differences in gender, marriage, and occupation. Multimorbidity had lower quality of life, reflected in all four domains. Multiple linear regression analyses showed that low level of education, low income, number of diseases, depression, and anxiety were negatively related to quality of life in all domains.
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