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ORIGINAL RESEARCH article
Front. Public Health
Sec. Aging and Public Health
Volume 13 - 2025 | doi: 10.3389/fpubh.2025.1571509
This article is part of the Research TopicMeasurement Matters in Epidemiologic Studies of Health in Aging and Across the Life-courseView all 5 articles
Creation and verification of a predictive nomogram model for the incidence of social isolation among China's older population
Provisionally accepted- School of Nursing, Anhui Medical University, Hefei, China
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Objectives: To explore the risk factors associated with social isolation among the elderly in China, develop a nomogram model to forecast the risk, and evaluate its predictive accuracy.Methods: An investigation was conducted into the demographic, socioeconomic, health, and health behavior aspects of the elderly population. Using logistic regression and backward stepwise analysis, a nomogram model was constructed to predict the risk of social isolation by screening independent risk factors. Results: Social isolation was prevalent in 42.1% of Chinese older adults. Nomogram prediction models were created for the five screened variables, which included type of residence, health self-assessment, disability, depression, and sedentary hours.The nomogram model had an AUC of 0.734 (95%CI: 0.701-0.767) in the training cohort, and an AUC of 0.653 (95%CI: 0.580-0.725) in the validation cohort. The Hosmer-Lemeshow goodness-of-fit test revealed that there was a good fit (P>0.05). DCA results showed that clinical intervention had a high net benefit in the elderly when the threshold probability was 20%-85% for the training cohort and 30%-65% for the control cohort. Conclusions: Social isolation is a common issue for the elderly population in China. The prediction model using a nomogram for the elderly can efficiently detect and screen high-risk individuals for social isolation, forecasting its occurrence.The proposed nomogram may serve as a preliminary screening tool for social isolation risk but requires further optimization to improve accuracy.
Keywords: Social Isolation, elderly population, Nomogram model, Risk factors, Predictive accuracy
Received: 05 Feb 2025; Accepted: 09 Apr 2025.
Copyright: © 2025 you, Ding, Wei, Han and LIU. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Annuo LIU, School of Nursing, Anhui Medical University, Hefei, China
Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.