Graduate Program in Gerontology, School of Medical Sciences, UNICAMP, Campinas, São Paulo, Brazil.
Graduate Program in Gerontology, School of Medical Sciences, UNICAMP, Campinas, São Paulo, Brazil.
J Am Med Dir Assoc. 2020 Sep;21(9):1309-1315.e4. doi: 10.1016/j.jamda.2020.02.005. Epub 2020 Mar 27.
Frailty is a multifactorial syndrome characterized by social, physical, and psychological stressors. Network analysis is a graphical statistical technique that can contribute to the understanding of this complex, multifactorial phenomenon. The aim of this study was to investigate the relationships between social, physical, and psychological factors and frailty in older persons.
A cross-sectional study.
A total of 2588 community-dwelling older persons from the FIBRA (Frailty in Brazilian Older Persons) 2008 to 2009 study.
Participants were assessed for sociodemographic variables, physical and mental health, and the frailty phenotype. Partial correlation network analysis with the Graphical Least Absolute Shrinkage and Selection Operator (glasso) estimator was performed to determine the relationships between social, physical, and psychological factors and frailty.
Mean participant age was 72.31 years, 7.0% were frail, and 50.6% were prefrail. In the network structure, frailty correlated most strongly with physical and psychological factors such as diabetes and depression and exhibited greater proximity to physical factors such as disability, urinary incontinence, and cardiovascular risk as measured by waist-to-hip ratio.
The analytical strategy used can provide information for specific subpopulations of interest and here confirmed that frailty is not uniformly determined but associated with different psychological and physical health factors, thereby allowing better understanding and management of this condition.
衰弱是一种多因素综合征，其特征是存在社会、身体和心理压力源。网络分析是一种图形统计技术，有助于理解这种复杂的多因素现象。本研究旨在探讨老年人社会、身体和心理因素与衰弱之间的关系。
横断面研究。
共纳入来自 2008 至 2009 年 FIBRA（巴西老年人衰弱）研究的 2588 名社区居住的老年人。
评估参与者的社会人口统计学变量、身体和心理健康状况以及衰弱表型。采用图形最小绝对收缩和选择算子（graphical least absolute shrinkage and selection operator，glasso）估计器进行部分相关网络分析，以确定社会、身体和心理因素与衰弱之间的关系。
参与者的平均年龄为 72.31 岁，7.0%为衰弱，50.6%为衰弱前期。在网络结构中，衰弱与身体和心理因素（如糖尿病和抑郁症）相关性最强，与残疾、尿失禁和心血管风险（通过腰臀比测量）等身体因素的接近度更高。
所使用的分析策略可以为特定的感兴趣的亚人群提供信息，这里证实衰弱不是由单一因素决定的，而是与不同的心理和身体健康因素相关，从而更好地理解和管理这种情况。
