Department of Sociology, Institute for Population Research, The Ohio State University, Columbus, Ohio, United States of America.
Department of Sociology, Institute for Social Research, University of Michigan, Ann Arbor, Michigan, United States of America.
PLoS One. 2023 Feb 8;18(2):e0281139. doi: 10.1371/journal.pone.0281139. eCollection 2023.
Despite the extensive study of predictors of cognitive decline in older age, a key uncertainty is how much these predictors explain both the intercept and age- and non-age-related change in cognitive functioning (CF). We examined the contribution of a broad range of life course determinants to CF trajectories. Data came from 7,068 participants in the 1996-2016 Health and Retirement Study. CF was measured as a summary score on a 27-point cognitive battery of items. We estimated multilevel growth curve models to examine the CF trajectories in individuals ages 54-85. We found that the variation in CF level at age 54 was three times as much as the variation in age slope. All the observed individual predictors explained 38% of the variation in CF at age 54. Personal education was the most important predictor (25%), followed by race, household wealth and income, parental education, occupation, and depression. The contributions of activity limitations, chronic diseases, health behaviors (obesity, smoking, vigorous activity), childhood conditions (childhood health, nutrition, financial situation), gender, marital status, and religion were rather small (<5%). Even though the age slope varied with many adulthood factors, they only explained 5.6% of the between-person variation in age slope. Moreover, age explained 23% of within-person variation in CF from age 54 to 85. The rest non-age-related within-person variation could not be explained by the observed time-varying factors. These findings suggest that future research is urgently needed to discover the main determinants of the slope of cognitive decline to slow down the progression of cognitive impairment and dementia.
尽管人们对老年人认知能力下降的预测因素进行了广泛的研究,但一个关键的不确定性是这些预测因素在多大程度上解释了认知功能(CF)的截距和与年龄相关及非年龄相关的变化。我们研究了广泛的人生历程决定因素对 CF 轨迹的贡献。数据来自于 1996 年至 2016 年健康与退休研究中的 7068 名参与者。CF 以 27 项认知项目组成的综合得分来衡量。我们估计了多层次增长曲线模型,以检查年龄在 54-85 岁的个体的 CF 轨迹。我们发现,CF 水平在 54 岁时的变化是年龄斜率变化的三倍。所有观察到的个体预测因素解释了 CF 在 54 岁时的 38%的变化。个人教育是最重要的预测因素(占 25%),其次是种族、家庭财富和收入、父母教育、职业和抑郁。活动受限、慢性疾病、健康行为(肥胖、吸烟、剧烈活动)、儿童时期状况(儿童健康、营养、经济状况)、性别、婚姻状况和宗教的贡献相当小(<5%)。尽管年龄斜率受许多成年因素的影响,但它们只解释了个体间年龄斜率差异的 5.6%。此外,年龄解释了 54 岁至 85 岁期间 CF 的个体内变化的 23%。其余与年龄无关的个体内变化无法用观察到的时变因素来解释。这些发现表明,迫切需要开展未来研究,以发现认知能力下降斜率的主要决定因素,从而减缓认知障碍和痴呆的进展。