School of Psychology, Ulster University, Cromore Road, Coleraine BT52 1SA, United Kingdom.
School of Psychology, Ulster University, Cromore Road, Coleraine BT52 1SA, United Kingdom.
J Affect Disord. 2022 Feb 1;298(Pt A):345-354. doi: 10.1016/j.jad.2021.10.114. Epub 2021 Oct 29.
This study investigated the role of a large range psychological, attitudinal and health related variables as predictors of depression trajectories amongst older adults over a 4-year time period.
Data from three consecutive waves of the TILDA survey of older community dwelling adults aged 50+ in Ireland were combined for analysis. Depression symptom scores were assessed using the Center for Epidemiological Studies- Depression scale (CES-D). Changes in depression scores over three time points were modelled as distinct trajectory classes using group-based trajectory modelling, whilst simultaneously controlling for demographic, attitudinal and health related predictors of these trajectory classes using multinomial regression.
Four distinct depression trajectories were identified as (1) a stable low symptom level group (79%), (2) a moderate but deteriorating symptoms group (7.6%), (3) a moderate but improving group (10.1%) and (4) a vulnerable group with consistently high symptoms (3.1%). Multinomial logistic regression indicated that limiting pain, mobility impairments, perceived stress and loneliness predicted membership of the moderate and higher depressive symptom classes. Retirement status and higher reported levels of worry were associated with a greater likelihood of membership of the moderate symptom classes only.
Use of the CES-D is open to bias due to subjective nature of respondent reporting.
Results concur with previous studies on the development of depression among older people and highlight the key health related and psychological variables that may inform interventions aimed at mitigating risks of developing depression among older adults.
本研究旨在探讨一系列广泛的心理、态度和健康相关变量在预测老年人抑郁轨迹中的作用,研究时间跨度为 4 年。
对来自爱尔兰连续三波 50 岁以上社区居住的老年人 TILDA 调查的数据进行了综合分析。使用流行病学研究中心抑郁量表(CES-D)评估抑郁症状评分。使用基于群组的轨迹建模,将抑郁评分在三个时间点的变化建模为不同的轨迹类别,同时使用多项逻辑回归控制这些轨迹类别的人口统计学、态度和健康相关预测因素。
确定了四个不同的抑郁轨迹类别,分别是:(1)稳定的低症状水平组(79%);(2)症状逐渐加重的中等程度组(7.6%);(3)症状逐渐改善的中等程度组(10.1%);(4)持续出现高症状的脆弱组(3.1%)。多项逻辑回归表明,限制疼痛、行动障碍、感知压力和孤独感预测了中等到更高的抑郁症状类别的成员身份。退休状态和更高的报告担忧水平与中等到更高的抑郁症状类别的成员身份更相关。
由于受访者报告的主观性,CES-D 的使用存在偏见。
结果与先前关于老年人抑郁发展的研究一致,并强调了可能为针对老年人抑郁风险的干预措施提供信息的关键健康相关和心理变量。