Evidence map›Paper›PMID 40042774›Full record

ArticleEuropean geriatric medicine2025

Predictors of mood disturbance in older adults: a longitudinal cohort study.

Feng-Yi Wang, Ling-Jie Fan, Lin-Nan Huo, Yang Lin, Ren-Gang Zhang, Yong-Hong Yang, Quan Wei

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Article in European geriatric medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

7 authors.

Feng-Yi Wang *Department of Rehabilitation Medicine, West China Hospital Sichuan University, Chengdu, Sichuan Province, China.
Ling-Jie Fan *College of Computer Science, Sichuan University, Chengdu, Sichuan Province, China.
Lin-Nan HuoDepartment of Rehabilitation Medicine, West China Hospital Sichuan University, Chengdu, Sichuan Province, China.
Yang LinDepartment of Rehabilitation Medicine, West China Hospital Sichuan University, Chengdu, Sichuan Province, China.
Ren-Gang ZhangDepartment of Rehabilitation Medicine, West China Hospital Sichuan University, Chengdu, Sichuan Province, China.
Yong-Hong YangDepartment of Rehabilitation Medicine, West China Hospital Sichuan University, Chengdu, Sichuan Province, China. nicole@scu.edu.cn.ORCID http://orcid.org/0000-0003-3547-4858
Quan WeiDepartment of Rehabilitation Medicine, West China Hospital Sichuan University, Chengdu, Sichuan Province, China. weiquan@scu.edu.cn.

Funding

National Key R&D Program of China 2023YFC3603800National Key R&D Program of China 2023YFC3603801
6 · The paper itself

Abstract

purposeGiven the significant mental health challenges faced by the aging population, this study aimed to identify key predictors of mood disturbances among older adults, focusing on socioeconomic, health, and cognitive factors.

methodsThis post-hoc analysis utilized publicly available data from the National Health and Aging Trends Study (NHATS), a nationally representative longitudinal cohort study conducted in the United States. The analysis included 2,820 adults aged 65 years and above who were followed for three years (age average range 75-79 years, 54.7% female).

resultsDuring the follow-up period, 21.8% of participants developed new-onset mood disturbances. High-income status is associated with decreased risk (OR 0.71, 95% CI 0.52-0.96), while being Black showed a risk effect compared to White participants (OR 1.38, 95% CI 1.06-1.29). With not good health status (OR 1.58, 95% CI 1.04-2.41), without presence of diabetes (OR 0.74, 95% CI 0.58-0.95), and poor memory status (OR 2.14, 95% CI 1.10-4.15) were significant predictors. Without fear of falling (OR 0.77, 95% CI 0.61-0.97) and increased physical performance (OR 0.94, 95% CI 0.91-0.98) also decreased risk. Income-stratified analysis revealed that low-income groups were particularly affected by cognitive function, middle-income by health status, and high-income by physical activity levels.

conclusionSocioeconomic status, race, health conditions, and cognitive function are significant predictors of mood disturbances in older adults. These findings suggest the importance of developing targeted interventions based on income levels and addressing modifiable risk factors.

Indexed as

AgingMood DisordersAgedAged, 80 and overCognitionFemaleHealth StatusHumansLongitudinal StudiesMaleRisk FactorsSocioeconomic FactorsUnited StatesAnxietyDepressionMood disturbance

Identifiers

PMID40042774

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