Health risk assessment of rural older population

BACKGROUND: With the accelerated development of aging, the health problems of rural elderly are becoming increasingly severe. OBJECTIVE: The study aims to understand the mental health issues of the rural older population. METHODS: The risk factor analysis and the disease risk assessment are utilized to analyze the impacts of depression on older adults. First, the prevalence of depression in China’s rural older population is counted and analyzed. Next, both single and multi-factor analyses are employed to analyze the degree of depression among rural older adults quantitatively, and the existing risk factors are determined. The multiple risk factors and multi-source logistic regression algorithm establish the risk assessment model of depression in the rural older population. Finally, the risk factors of depression in older adults are calculated by analyzing and processing the above statistical data. A risk assessment model of depression is built, whose sensitivity and specificity are tested. RESULTS: Single-factor analysis and multi-factor analysis reveal 20 vital influencing factors of depression in older adults, such as cognitive ability, emotional state, and memory. The sensitivity and specificity of the risk assessment model based on multi-factor logistic regression are 87.3%80.2%, respectively, capable of effectively assessing and screening the potential population of depression among older adults. CONCLUSIONS: This model provides a scientific basis for screening out and preventing older adults’ mental health issues with depression and improving older adults’ quality of life.