Zhang Taotao, Li Shang, Zhu Zhichen, Sha Kexin, Liu Yuwen
College of Nursing, Bengbu Medical University, Bengbu, Anhui, China.
College of Health Management, Bengbu Medical University, Bengbu, Anhui, China.
Front Public Health. 2025 Aug 18;13:1624599. doi: 10.3389/fpubh.2025.1624599. eCollection 2025.
The mechanisms linking depression and cognitive decline in older adults in the context of global aging are unclear, and functional status may modulate the relationship. This study aimed to reveal the heterogeneity of cognitive functioning in older adults under different physical functional states through latent profile analysis (LPA) and to explore the patterns associated with depressive symptoms.
Based on the China Health and Retirement Longitudinal Study (CHARLS) 2020 data, 4,158 older adults ≥60 years old were included, and the subtypes of cognitive functions (immediate memory, delayed memory, calculative ability, orientation, and visual construction) were classified by LPA. The associations between different cognitive categories and depressive symptoms were analyzed by stepwise logistic regression. The samples were stratified according to the physical functioning status into "functional intactness "and "functional impairment."
In the functional intactness group, LPA identified three cognitive profiles, and the risk of depression was significantly higher in the low cognitive function with severe calculative impairment group (19.1%) (OR = 1.52, 95% CI: 1.21-1.91); in the functional impairment group, LPA identified four cognitive profiles, and the risk of depression in the low cognitive function with severe calculative impairment group (21.3%) was 3.37 times higher than that in the high cognitive function group (95% CI: 2.40-4.74), and the low cognitive function with impaired calculative ability group was independently associated with depression risk (OR = 2.65, 95% CI: 1.77-3.94). The strength of the association between low cognition and depression was significantly higher in the functionally impaired population than in the functionally intact population (B-value: 1.25 vs. 0.42, both < 0.001).
Cognitive function heterogeneity significantly affects depression risk through functional status stratification, impaired functioning exacerbates the predictive role of low cognitive functioning for depression, and calculative impairment may be an early marker of executive function impairment. The findings provide a basis for the precise identification of people at high risk of depression and the development of stratified intervention strategies.
在全球老龄化背景下，老年人抑郁与认知衰退之间的关联机制尚不清楚，功能状态可能会调节这种关系。本研究旨在通过潜在剖面分析（LPA）揭示不同身体功能状态下老年人认知功能的异质性，并探索与抑郁症状相关的模式。
基于中国健康与养老追踪调查（CHARLS）2020年的数据，纳入4158名60岁及以上的老年人，通过LPA对认知功能亚型（即时记忆、延迟记忆、计算能力、定向和视觉构建）进行分类。通过逐步逻辑回归分析不同认知类别与抑郁症状之间的关联。根据身体功能状态将样本分为“功能完好”和“功能受损”两组。
在功能完好组中，LPA识别出三种认知剖面，计算能力严重受损的低认知功能组抑郁风险显著更高（19.1%）（OR = 1.52，95%CI：1.21 - 1.91）；在功能受损组中，LPA识别出四种认知剖面，计算能力严重受损的低认知功能组（21.3%）抑郁风险比高认知功能组高3.37倍（95%CI：2.40 - 4.74），计算能力受损的低认知功能组与抑郁风险独立相关（OR = 2.65，95%CI：1.77 - 3.94）。功能受损人群中低认知与抑郁之间的关联强度显著高于功能完好人群（B值：1.25对0.42，均<0.001）。
认知功能异质性通过功能状态分层显著影响抑郁风险，功能受损会加剧低认知功能对抑郁的预测作用，计算能力受损可能是执行功能受损的早期标志。这些发现为精准识别抑郁高危人群及制定分层干预策略提供了依据。
