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Updated: May 8, 2025

Assessment of Age-related Changes in Cognitive Functions Using EmoCogMeter, a Novel Tablet-computer Based Approach
Published on: February 14, 2014
Predictors of mood disturbance in older adults: a longitudinal cohort study
Feng-Yi Wang1,2,3, Ling-Jie Fan4,3, Lin-Nan Huo1,3
1Department of Rehabilitation Medicine, West China Hospital Sichuan University, Chengdu, Sichuan Province, China.
Purpose:
Given 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.
Methods:
This 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).
Results:
During 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.
Conclusion:
Socioeconomic 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.
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