NDLI: Analysis and prediction of older adult sports participation in South Korea using artificial neural networks and logistic regression models

Content Provider	Springer Nature : BioMed Central
Author	Byun, Hyun Jeon, Sangwan Yi, Eun Surk
Abstract	Background Korea’s aging population and the lack of older adult participation in sports are increasing medical expenses. Aims This study aimed to segment older adult sports participants based on their demographic characteristics and exercise practice behavior and applied artificial neural network and logistic regression models to these segments to best predict the effect of medical cost reduction. It presents strategies for older adult sports participation. Methods A sample comprising data on 1,770 older adults aged 50 years and above was drawn from the 2019 National Sports Survey. The data were analyzed through frequency analysis, hierarchical and K-means clustering, artificial neural network, logistic regression, cross-tabulation analyses, and one-way ANOVA using SPSS 23 and Modeler 14.2. Results The participants were divided into five clusters. The artificial neural network and logistic analysis models showed that the cluster comprising married women in their 60s who participated in active exercise had the highest possibility of reducing medical expenses. Discussion Targeting women in their 60s who actively participate in sports, the government should expand the supply of local gymnasiums, community centers, and sports programs. If local gymnasiums and community centers run sports programs and appoint appropriate sports instructors, the most effective medical cost reduction effect can be obtained. Conclusions This study contributes to the field by providing insights into the specific demographic segments to focus on for measures to reduce medical costs through sports participation.
Related Links	https://bmcgeriatr.biomedcentral.com/counter/pdf/10.1186/s12877-023-04375-2.pdf
Ending Page	12
Page Count	12
Starting Page	1
File Format	HTM / HTML
ISSN	14712318
DOI	10.1186/s12877-023-04375-2
Journal	BMC Geriatrics
Issue Number	1
Volume Number	23
Language	English
Publisher	BioMed Central
Publisher Date	2023-10-19
Access Restriction	Open
Subject Keyword	Geriatrics Gerontology Aging Rehabilitation Neural networks model Logistic regression model Older adult participants Medical costs Geriatrics/Gerontology
Content Type	Text
Resource Type	Article
Subject	Geriatrics and Gerontology
Journal Impact Factor	3.4/2023
5-Year Journal Impact Factor	4.1/2023

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