Health profiles and socioeconomic characteristics of nonagenarians residing in Mugello, a rural area in Tuscany (Italy)

Author:

Strozza CosmoORCID,Pasqualetti Patrizio,Egidi Viviana,Loreti Claudia,Vannetti Federica,Macchi Claudio,Bonaccorsi Guglielmo,Boni Roberta,Castagnoli Chiara,Cecchi Francesca,Cesari Francesca,Epifani Francesco,Frandi Roberta,Giusti Betti,Luisi Maria Luisa Eliana,Marcucci Rossella,Molino-Lova Raffaello,Paperini Anita,Razzolini Lorenzo,Sofi Francesco,Turcan Nona,Valecchi Debora,Padua Luca,

Abstract

Abstract Background Health, as defined by the WHO, is a multidimensional concept that includes different aspects. Interest in the health conditions of the oldest-old has increased as a consequence of the phenomenon of population aging. This study investigates whether (1) it is possible to identify health profiles among the oldest-old, taking into account physical, emotional and psychological information about health, and (2) there are demographic and socioeconomic differences among the health profiles. Methods Latent Class Analysis with covariates was applied to the Mugello Study data to identify health profiles among the 504 nonagenarians residing in the Mugello district (Tuscany, Italy) and to evaluate the association between socioeconomic characteristics and the health profiles resulting from the analysis. Results This study highlights four groups labeled according to the posterior probability of determining a certain health characteristic: “healthy”, “physically healthy with cognitive impairment”, “unhealthy”, and “severely unhealthy”. Some demographic and socioeconomic characteristics were found to be associated with the final groups: older nonagenarians are more likely to be in worse health conditions; men are in general healthier than women; more educated individuals are less likely to be in extremely poor health conditions, while the lowest-educated are more likely to be cognitively impaired; and office or intellectual workers are less likely to be in poor health conditions than are farmers. Conclusions Considering multiple dimensions of health to determine health profiles among the oldest-old could help to better evaluate their care needs according to their health status.

Publisher

Springer Science and Business Media LLC

Subject

Geriatrics and Gerontology

Reference58 articles.

1. World Health Organization. Global Health and aging. Geneva: U.S. National Institute of Aging; 2011.

2. Bambra C, Pope D, Swami V, Stanistreet D, Roskam A, Kunst A, et al. Gender, health inequalities and welfare state regimes: a cross-national study of 13 European countries. J Epidemiol Community Health. 2009;63:38–44. https://doi.org/10.1136/jech.2007.070292.

3. World Population Prospects - Population Division - United Nations n.d. https://esa.un.org/unpd/wpp/ (Accessed May 17, 2018).

4. Ministero dell’economia e delle finanze (RGS). Il monitoraggio della spesa sanitaria. Rapporto n° 6. Roma; 2019. http://www.rgs.mef.gov.it/_Documenti/VERSIONE-I/Attivit--i/Spesa-soci/Attivit-monitoraggio-RGS/2019/IMDSS-RS2019.pdf. Accessed 23 Mar 2020.

5. Skirbekk VF, Staudinger UM, Cohen JE. How to measure population aging? The answer is less than obvious: a review. Gerontology. 2018;1:1–9. https://doi.org/10.1159/000494025.

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3