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To provide a new perspective for exploring the influencing factors of depression symptoms in individuals aged 45 and older in China, helping reveal the complex relationships among potential influencing factors.
Using data from the China Health and Retirement Longitudinal Study (CHARLS) 2018, independent variables were determined based on the five dimensions of the health ecological model. A total of 8 485 individuals aged 45 and older were included. The LASSO algorithm was employed for variable selection, and the Apriorism algorithm from association rules was utilized to mine the causal association rules of depression symptoms among the elderly in China from multiple dimensions.
The detection rate of depression symptoms among middle-aged and elderly individuals in China was 38.42%. The variables selected by LASSO regression included gender from the personal traits layer, self-rated health, life satisfaction, disability, number of chronic diseases, visual impairment, hearing impairment, and nighttime sleep duration from the behavioral traits layer, as well as household registration type and education level from the living and working conditions layer. The Apriorism algorithm identified 21 strong association rules, with the highest support of 20.71%, maximum confidence of 68.40%, and the highest lift of 1.78. Key association factors for depression symptoms among the elderly included living in rural areas, having two or more chronic diseases, nighttime sleep duration of less than 6 hours, being female, having a disability, poor self-rated health, and being relatively satisfied with life, with primary school education. Compared to those with excessive nighttime sleep duration, individuals with insufficient nighttime sleep duration exhibited a higher risk of depression symptoms. The factor of rural residence was highly correlated with nighttime sleep duration of less than 6 hours and having two or more chronic diseases.
This study suggests considering depression issues from three dimensions: personal traits, behavioral traits, and living and working conditions, emphasizing the need to pay special attention to rural populations and patients with comorbid chronic diseases during depression symptom screening.
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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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