Abstract
This study used 23 factors (eight interval variables and 15 dummy variables) as proxies for health depreciation. We used 1248 older adults from the Center for Geriatrics and Gerontology of Taichung Veterans General Hospital (Taiwan) to examine the association among frailty, health depreciation, and mortality in older adults. This study found that a significant positive correlation existed between frailty and mortality in older adults. Further, we applied a recursive bivariate probit model to examine the association between health depreciation factors, frailty, and mortality. Our results showed that health depreciation factors, such as Charlson’s comorbidity index, diabetes and hyperlipidemia, significantly increased older adults’ frailty; in contrast, albumin and mini nutritional assessment significantly decreased older adults’ frailty. Through the frailty regression, we confirmed not only that health depreciation factors significantly influenced mortality, but also that creatinine, myocardial infarction, and malignant tumors could directly and significantly increase older adults’ mortality.
Highlights
At present, Taiwan is facing the problems of an aging population and a low birth rate
This study employs a database of the Center for Geriatrics and Gerontology at Taichung Veterans
The research results are as follows: (1) In the likelihood ratio test, when the correlation coefficients of the residual terms of the two regression equations are 0, the χ2 (1) is 13.983; the null hypothesis that the two regression equations are independent from each other is significantly rejected. This implies that regression parameters should be determined through recursive simultaneous estimation instead of individual estimation
Summary
Taiwan is facing the problems of an aging population and a low birth rate. The method was applied as follows: (1) we construct both a theoretical foundation and an empirical model and consider variables based upon the perspective of medical economics; (2) according to the five symptoms of FR defined by Fried et al [1], we categorize the participants’ symptoms, namely unintended weight loss, exhaustion, low activity, slowness, and low grip strength; those who had three or more symptoms were categorized in the FR group (N = 373), and those with 0–2 symptoms were categorized into the relatively healthy group (N = 875); (3) the correlation between FR and mortality and the difference test between three health-care types in terms of FR, MR, and HD are analyzed; and (4) we construct simultaneous recursive probit regression models to estimate the impact of various HD factors (e.g., hypertension, hyperlipidemia, hyperglycemia, tumors, pulmonary diseases, cerebrovascular diseases, blood creatinine, hemoglobin, and other chronic diseases) on the FR and MR in older adults. The remainder of this paper is organized as follows: Section 2 introduces the theoretical framework and empirical model; Section 3 analyzes the empirical results; and Section 4 delineates the research conclusions and suggestions
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