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疾病和智力是中年后抑郁症状个体差异的较强预测因素。

Illness and intelligence are comparatively strong predictors of individual differences in depressive symptoms following middle age.

机构信息

a Swiss National Center of Competence in Research LIVES - Overcoming Vulnerability: Life Course Perspectives , Universities of Lausanne and of Geneva , Switzerland.

b Department of Experimental Psychology , University of Oxford , Oxford , UK.

出版信息

Aging Ment Health. 2019 Jan;23(1):122-131. doi: 10.1080/13607863.2017.1394440. Epub 2017 Oct 27.

DOI:10.1080/13607863.2017.1394440
PMID:29077479
Abstract

OBJECTIVE

We compared the importance of socio-demographic, lifestyle, health, and multiple cognitive measures for predicting individual differences in depressive symptoms in later adulthood.

METHOD

Data came from 6203 community-dwelling older adults (age 41-93 years at study entry) from the United Kingdom. Predictors (36 in total) were assessed up to four times across a period of approximately 12 years. Depressive symptoms were measured with the Geriatric Depression Scale. Statistical methods included multiple imputation (for missing data), random forest analysis (a machine learning approach), and multivariate regression.

RESULTS

On average, depressive symptoms increased gradually following middle age and appeared to accelerate in later life. Individual differences in depressive symptoms were most strongly associated with differences in combined symptoms of physical illness (positive relation) and fluid intelligence (negative relation). The strength of association between depressive symptoms and fluid intelligence was unaffected by differences in health status within a subsample of chronically depressed individuals.

CONCLUSION

Joint consideration of general health status and fluid intelligence may facilitate prediction of depressive symptoms severity during later life and may also serve to identify sub-populations of community-dwelling elders at risk for chronic depression.

摘要

目的

我们比较了社会人口统计学、生活方式、健康和多种认知测量对预测成年后期个体抑郁症状差异的重要性。

方法

数据来自英国的 6203 名居住在社区的老年人(研究开始时年龄在 41-93 岁之间)。预测因子(共 36 个)在大约 12 年的时间内进行了多达四次评估。抑郁症状使用老年抑郁量表进行测量。统计方法包括多重插补(用于缺失数据)、随机森林分析(一种机器学习方法)和多元回归。

结果

平均而言,抑郁症状在中年后逐渐增加,在晚年似乎加速。抑郁症状的个体差异与身体疾病(正相关)和流体智力(负相关)的综合症状差异最密切相关。在慢性抑郁个体的亚样本中,抑郁症状与流体智力之间的关联强度不受健康状况差异的影响。

结论

综合考虑一般健康状况和流体智力可以促进对晚年抑郁症状严重程度的预测,也可以帮助识别社区居住的老年人中存在慢性抑郁风险的亚人群。

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