Nurse, Nutritional Support Team & Department of Nursing, Seoul National University Hospital, Seoul, Republic of Korea.
Professor, College of Nursing Science, Kyung Hee University, 26, Kyungheedae-ro, Dongdaemun-gu, Seoul 02447, Republic of Korea.
Int J Nurs Stud. 2021 Mar;115:103850. doi: 10.1016/j.ijnurstu.2020.103850. Epub 2020 Dec 6.
Frailty is highly prevalent in older adults. Malnutrition is a common problem in older adults and is related to frailty.
The aim was to investigate a structural frailty model, to verify the factors which affect the frailty of older adults, and to evaluate the moderating effects of nutritional status on frailty through multi-group analysis.
Secondary analysis as a descriptive survey.
Data were prospectively collected from 1,374 older adults (age ≥ 70) from the Korean Frailty and Aging Cohort Study in 2017.
Frailty was measured by the FRAIL scale [robust (score 0), pre-frailty (score 1-2), frailty (score 3-5)], and nutritional status was evaluated by the Mini Nutritional Assessment (MNA) [well-nourished (score ≥ 24), risk of malnutrition (score 17-23.5), malnourished (score < 17)]. Other domains were evaluated with the hand grip strength test, Short Physical Performance Battery (SPPB), short form of the Geriatric Depression Scale (GDS), Mini-Mental State Examination (MMSE), and ENRICHD Social Support Instrument (ESSI). The frailty model was developed by confirming the relationship among the influencing factors of frailty. To evaluate the different frailty pathways according to nutritional status in multi-group analysis, participants were divided into two subgroups according to the mean MNA score. Subgroups were classified into a well-nourished group (n = 851) for scores equal to or higher than the average score, and a malnourished group (n = 523) for scores lower than the average score. The path analysis was performed using the AMOS 23.0 program.
The frailty model's fit indices were adequate. In the model, the most influential factor for frailty was depression, followed by SPPB, age, polypharmacy, cognitive function, and female sex. In the multi-group analysis according to nutritional status, the malnourished group significantly increased in frailty as SPPB scores decreased. In addition, SPPB scores and cognitive function significantly decreased with increasing age in the malnourished group when compared to the well-nourished group.
Depression, SPPB, age, polypharmacy, cognitive function, and female sex were found to be important factors that affect frailty. Malnourished older adults are more likely to suffer from physical impairment, lower cognitive function, and frailty. Vigorous efforts are needed to improve nutritional status in older adults, which ultimately might improve functional outcomes and frailty.
衰弱在老年人中非常普遍。营养不良是老年人常见的问题,与衰弱有关。
本研究旨在通过结构衰弱模型,验证影响老年人衰弱的因素,并通过多组分析评估营养状况对衰弱的调节作用。
二次分析作为描述性调查。
2017 年,从韩国衰弱和衰老队列研究中前瞻性收集了 1374 名年龄≥70 岁的老年人(Frailty Scale [健壮(评分 0)、衰弱前期(评分 1-2)、衰弱(评分 3-5)])。
采用 Mini Nutritional Assessment(MNA)[营养良好(评分≥24)、营养不良风险(评分 17-23.5)、营养不良(评分<17)]评估营养状况。其他领域采用握力测试、Short Physical Performance Battery(SPPB)、简易精神状态检查(MMSE)和老年抑郁量表(GDS)评估。通过确认衰弱影响因素之间的关系来建立衰弱模型。为了在多组分析中根据营养状况评估不同的衰弱途径,根据平均 MNA 评分将参与者分为两组。将亚组分为营养良好组(n=851),评分等于或高于平均评分,以及营养不良组(n=523),评分低于平均评分。使用 AMOS 23.0 程序进行路径分析。
衰弱模型的拟合指标良好。在该模型中,对衰弱影响最大的因素是抑郁,其次是 SPPB、年龄、多药治疗、认知功能和女性。根据营养状况的多组分析,随着 SPPB 评分的降低,营养不良组的衰弱程度显著增加。此外,与营养良好组相比,营养不良组的 SPPB 评分和认知功能随着年龄的增长而显著下降。
抑郁、SPPB、年龄、多药治疗、认知功能和女性是影响衰弱的重要因素。营养不良的老年人更容易出现身体功能障碍、认知功能下降和衰弱。需要大力改善老年人的营养状况,这最终可能改善功能结局和衰弱。