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养老院患者的肥胖问题:与常见护理问题的关联。

Obesity in Nursing Home Patients: Association with Common Care Problems.

机构信息

Institute of Nursing Science, Medical University of Graz, Neue Stiftingtalstraße 6/P06-WEST, 8010 Graz, Austria.

出版信息

Nutrients. 2023 Jul 18;15(14):3188. doi: 10.3390/nu15143188.

Abstract

(1) Background: There is not much research about obesity in nursing homes although knowledge will help us to develop customized treatment plans and prevention strategies, which may help to decrease the burden for all persons involved. The objective of conducting this study was to describe the prevalence of obesity and the association between obesity and care problems in nursing home patients. (2) Methods: This study is a secondary data analysis of data collected in an annually performed cross-sectional study called "Nursing Quality Measurement 2.0". A standardized and tested questionnaire was used to collect data. (3) Results: In total, 1236 nursing home patients took part, and 16.7% of them were obese. The multivariate logistic regression analysis results show that urinary incontinence is significantly associated with the presence of obesity (OR 2.111). The other care problems of pressure injuries, fecal and double incontinence, physical restraints, falls, and pain were not associated with obesity. (4) Conclusions: The results indicate that, in the nursing home setting, healthcare staff should pay special attention to the patients' nutritional status and help patients to maintain a healthy weight and prevent a loss of muscle mass and function. Conducting more studies with larger sample sizes is recommended, as this will allow for differentiation among different obesity classes.

摘要

(1) 背景:尽管了解肥胖症有助于我们制定针对养老院患者的个性化治疗计划和预防策略,从而可能有助于减轻相关各方的负担,但针对养老院肥胖症的研究并不多。本研究旨在描述肥胖症的流行情况,以及肥胖症与养老院患者护理问题之间的关联。(2) 方法:本研究是对“护理质量测量 2.0”年度横断面研究中收集数据的二次数据分析。采用标准化和经过测试的问卷收集数据。(3) 结果:共有 1236 名养老院患者参与,其中 16.7%的患者肥胖。多变量逻辑回归分析结果表明,尿失禁与肥胖显著相关(OR 2.111)。其他护理问题如压疮、大便失禁和双重失禁、身体约束、跌倒和疼痛与肥胖无关。(4) 结论:研究结果表明,在养老院环境中,医护人员应特别注意患者的营养状况,帮助患者保持健康的体重,预防肌肉质量和功能的丧失。建议进行更多的研究,扩大样本量,以区分不同的肥胖类别。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7b9f/10385003/a9fd9586d13e/nutrients-15-03188-g001.jpg

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