{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,8]],"date-time":"2026-04-08T00:55:10Z","timestamp":1775609710482,"version":"3.50.1"},"reference-count":71,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2025,6,8]],"date-time":"2025-06-08T00:00:00Z","timestamp":1749340800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Nutrients"],"abstract":"<jats:p>Background\/Objectives: Overnutrition, leading to overweight and obesity, is a growing concern among the elderly, contributing to non-communicable diseases. This study examines socio-demographic, dietary, and lifestyle factors associated with overnutrition in Hungarian adults aged 65 and older. Methods: A cross-sectional analysis was conducted using 2019 European Health Interview Survey data, including 1628 elderly participants. Body mass index (BMI \u2265 25 kg\/m2) defined overnutrition. Socio-demographic (gender, income, urbanization, partner status), dietary (fruit, vegetable, water, sweetener, salt intake), and lifestyle (alcohol, smoking, physical activity) factors were analyzed. Chi-square tests and multivariate logistic regression identified associations, with odds ratios (ORs) and 95% confidence intervals (CIs) calculated. Results: Overnutrition prevalence was 72.7%, higher in males (77.8%) than females (69.1%). Urbanization, income, and partner status showed associations. Significant predictors included lower water intake (OR = 0.47, 95% CI: 0.33\u20130.65 for 1\u20131.5 L), artificial sweetener use (OR = 1.54, 95% CI: 1.13\u20132.11), moderate\/high salt intake (OR = 1.45, 95% CI: 1.06\u20131.99), former\/never smoking (OR = 2.56, 95% CI: 1.73\u20133.77), and heavy alcohol use (OR = 4.00, 95% CI: 1.33\u201312.50). Conclusions: Artificial sweetener use, high salt intake, smoking history, and heavy alcohol consumption are key modifiable predictors of overnutrition, informing targeted interventions for elderly Hungarians.<\/jats:p>","DOI":"10.3390\/nu17121954","type":"journal-article","created":{"date-parts":[[2025,6,9]],"date-time":"2025-06-09T04:23:02Z","timestamp":1749442982000},"page":"1954","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Overnutrition in the Elderly Population: Socio-Demographic and Behavioral Risk Factors in Hungary"],"prefix":"10.3390","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-7022-5932","authenticated-orcid":false,"given":"Battamir","family":"Ulambayar","sequence":"first","affiliation":[{"name":"Department of Health Informatics, Faculty of Health Sciences, University of Debrecen, 4032 Debrecen, Hungary"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0006-0593-0188","authenticated-orcid":false,"given":"Amr Sayed","family":"Ghanem","sequence":"additional","affiliation":[{"name":"Department of Health Informatics, Faculty of Health Sciences, University of Debrecen, 4032 Debrecen, Hungary"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0554-7350","authenticated-orcid":false,"given":"Attila Csaba","family":"Nagy","sequence":"additional","affiliation":[{"name":"Department of Health Informatics, Faculty of Health Sciences, University of Debrecen, 4032 Debrecen, Hungary"},{"name":"Coordinating Centre for Epidemiology, University of Debrecen Clinical Centre, 4032 Debrecen, Hungary"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2025,6,8]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1159\/000322827","article-title":"Overnutrition and the Cardiorenal Syndrome: Use of a Rodent Model to Examine Mechanisms","volume":"1","author":"Pulakat","year":"2011","journal-title":"Cardiorenal Med."},{"key":"ref_2","unstructured":"(2025, May 13). 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