Full
Outline
With the acceleration of population aging in China, the problem of depressive symptoms in the elderly is prominent, and there is health inequity between urban and rural elderly.
To investigate the influencing factors of depressive symptoms among Chinese elderly population and their urban-rural differences, so as to provide references for preventing depressive symptoms in the elderly.
Relevant data of 4 449 elderly individuals aged ≥ 60 years were collected from the 2022 China Family Panel Studies (CFPS). The chi-square test was used to compare the differences in the detection rate of depressive symptoms between urban and rural areas. Binary logistic regression was adopted to screen for the main influencing factors, and the random forest model was applied to rank these factors by their importance.
The detection rate of depressive symptoms among Chinese elderly was 25.20%, with rural elderly showing a higher rate (30.58%) than urban elderly (19.80%) (χ2=68.542, P<0.05).
of the regression analysis indicated that gender, chronic disease, self-rated health, napping, nighttime sleep time, interpersonal relationships, education level, retirement status, regional distribution, and income level are common influencing factors of depressive symptoms among the urban and rural elderly populations. The random forest model showed that, for the urban elderly population, the factors ranked in descending order of influence on depressive symptoms are good self-rated health (OR=0.396, 95% CI: 0.312-0.503), secondary school (OR=0.639, 95% CI: 0.473-0.862), and being retired (OR=0.726, 95% CI: 0.541-0.975). For the rural elderly population, the factors are good self-rated health (OR=0.472, 95% CI: 0.383-0.581), having chronic diseases (OR=1.918, 95% CI: 1.552-2.370), and nighttime sleep time <7h (OR=1.697, 95% CI: 1.365-2.110).
The higher detection rate of depressive symptoms among rural elderly warrants special attention to self-rated health, with particular focus on education level and retirement status for urban elderly, and chronic disease and nighttime sleep time for rural elderly, so as to formulate differentiated intervention strategies.
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| 科 Family | 属数 Number of genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) | 属 Genus | 种数 Number of species | 占总种数比例 Percentage of total species (%) |
|---|---|---|---|---|---|---|
| 鹅膏菌科Amanitaceae | 2 | 11 | 5.26 | 鹅膏菌属 Amanita | 10 | 4.78 |
| 小菇科 Mycenaceae | 2 | 12 | 5.74 | 丝盖伞属 Inocybe | 5 | 2.39 |
| 多孔菌科 Polyporaceae | 8 | 14 | 6.70 | 蜡蘑属 Laccaria | 5 | 2.39 |
| 红菇科 Russulaceae | 3 | 23 | 11.00 | 小皮伞属 Marasmius | 6 | 2.87 |
| 小菇属 Mycena | 11 | 5.26 | ||||
| 光柄菇属 Pluteus | 5 | 2.39 | ||||
| 红菇属 Russula | 17 | 8.13 | ||||
| 栓菌属 Trametes | 5 | 2.39 |
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