AUTHOR=Zhang Min , Rong Jian , Liu Song , Zhang Beibei , Zhao Yaodong , Wang Haibo , Ding Hong TITLE=Factors related to self-rated health of older adults in rural China: A study based on decision tree and logistic regression model JOURNAL=Frontiers in Public Health VOLUME=10 YEAR=2022 URL=https://www.frontiersin.org/journals/public-health/articles/10.3389/fpubh.2022.952714 DOI=10.3389/fpubh.2022.952714 ISSN=2296-2565 ABSTRACT=Objective

This study aimed to explore the related factors of self-rated health (SRH) by using decision tree and logistic regression models among older adults in rural China.

Methods

Convenience sampling was employed with 1,223 enrolled respondents who met the inclusion criteria from 10 randomly selected villages in M County in China. The content of the questionnaire covered demographic characteristics, physical and mental health, sleep status, and risk of falling. The Pittsburgh Sleep Quality Index (PSQI) and the Morse Falls Risk Scale (MFS) were used to evaluate sleep status and risk of falling, respectively. The decision tree and logistic regression models were employed to analyze the related factors of SRH.

Results

Notably, 817 (68.7%) subjects had good SRH. The logistic regression model showed that living standard, alcohol consumption, sleep quality, labor, hospitalization, discomfort, the number of chronic diseases, and mental health were associated with SRH (P-value < 0.05), while the decision tree model showed that the number of chronic diseases, sleep quality, mental health, hospitalization, gender, and drinking were associated with SRH. The sensitivity and specificity of the logistic regression model were 67.7 and 75.5%, respectively, and the area under the ROC curve was 0.789 (0.763, 0.816); the sensitivity and specificity of the decision tree model were 71.5, and 61.4% respectively, and the area under the ROC curve was 0.733 (0.703, 0.763).

Conclusion

Decision tree and logistic regression models complement each other and can describe the factors related to the SRH of the elderly in rural China from different aspects. Our findings indicated that mental health, hospitalization, drinking, and sleep quality were the important associated factors.