影響個人健康因素的相關研究:以中國家庭金融調查(CHFS)為例
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2023
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健康一直以來都是人生中重要的追尋目標,然而健康不單純只是由個人生理因素決定,人口背景因素、財務因素均會對健康產生影響。本研究透過2017年中國家庭金融調查(CHFS)的樣本資料進行次級資料分析,探討不同背景變項、財務變項、主觀幸福感對於戶主個人自評健康之間的關係及影響。利用Ordered Logistic Model分析方法得出不同的自變項與對影響力是否達統計上顯著以及其預測機率。研究結果發現:人口背景變項、財務變項、主觀幸福感對個人健康有顯著差異;而透過迴歸分析可知:除了「總消費」以外,其餘「年齡、性別、教育程度、婚姻關係、城鄉差距、總收入、總資產、總負債、主觀幸福感」共九項自變項均顯著的影響個人健康;而當個人健康狀況程度落於「一般」時,為本研究中各自變項最能有效預測的健康程度。
Health has always been an important pursuit in life; however, health is not solely determined by personal physiological factors, population background factors and financial factors also have an impact on health. This study used secondary data analysis of sample data from the 2017 China Household Finance Survey (CHFS) to explore the relationship and impact of different background variables, financial variables, and subjective well-being on the self-rated health of household heads. Ordered logistic model analysis was used to determine the statistical significance and predictive probability of different independent variables. The study found that population background variables, financial variables, and subjective well-being all have significant differences in personal health. The regression analysis revealed that, except for"total consumption," the other nine independent variables of "age, gender, education level, marital relationship, urban-rural gap, total income, total assets, total liabilities, and subjective well-being" all significantly affect personal health. When the level of personal health reaches "average," it is the most effectively predicted health level among the independent variables in this study.
Health has always been an important pursuit in life; however, health is not solely determined by personal physiological factors, population background factors and financial factors also have an impact on health. This study used secondary data analysis of sample data from the 2017 China Household Finance Survey (CHFS) to explore the relationship and impact of different background variables, financial variables, and subjective well-being on the self-rated health of household heads. Ordered logistic model analysis was used to determine the statistical significance and predictive probability of different independent variables. The study found that population background variables, financial variables, and subjective well-being all have significant differences in personal health. The regression analysis revealed that, except for"total consumption," the other nine independent variables of "age, gender, education level, marital relationship, urban-rural gap, total income, total assets, total liabilities, and subjective well-being" all significantly affect personal health. When the level of personal health reaches "average," it is the most effectively predicted health level among the independent variables in this study.
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主觀幸福感, 自評健康, 財務因素, 健康不平等, CHFS, Ordered Logistic Model, CHFS, financial factors, health inequality, self-rated health, subjective well-being, Ordered Logistic Model