ECTI TRANSACTIONS ON COMPUTER INFORMATION TECHNOLOGYVolume 16, No. 02, Month JUNE, Year 2022, Pages 174 - 185
Uncovering the most and the least factors affecting elderly health using association mining
Abstract Download PDFThailand has entered the aging society since 2005 and is now stepping towards a complete aging society in 2021. The elderly’s health problems are difficult to avoid.The research aims to analyze the most influential and most minor powerful factors on the elderly’s health status. The association analysis approach is applied to discover the relationship between various factors that affect good health. 17,804 Thai elderly data from the National Statistical Office (NSO) of Thailand were employed. One hundred ninety-nine features were taken into the association rules mining modeling. FP-growth algorithm is chosen to find the most and the least factors affecting the health of the elderly. The interesting relationships among those factors are also disclosed. As a result, the feature that demonstrates good health is performing daily activities independently. Additionally, several features that are less likely to appear in healthy seniors are hard work, working at risk, living in an urban society, living with unfamiliar caregivers, having a few children, and lacking sufficient government medical care. The knowledge gained from the findings can be considered for preparing health care for the aging society.
Elderly, Health, Aging Society, Association Min- ing, Association Rules, Itemsets