Supplementary file 1_Stronger associations of affectivity than social leisure activities w

Longitudinal survey data from 1,847 Chinese older adults (≥65 years) without dementia at baseline, tracked from 2008 to 2018. The dataset, authored by Yelin Gu and shared on figshare, was used to model trajectories of positive/negative affectivity and social leisure activities and their association with cognitive impairment risk. Analysis employed Group-Based Trajectory Models and binomial logistic regression.

Use Cases

• Modeling long-term cognitive risk based on affectivity trajectories described in the study
• Comparing the predictive strength of psychological factors versus social activities for cognitive decline
• Replicating trajectory subgroup analysis (e.g., 'High-rapid-increasing PNA' vs 'Low-stable-increasing PNA')
• Investigating interaction effects between affective states and social engagement on cognitive health

Strengths

• Longitudinal design with a 10-year follow-up period from 2008 to 2018
• Includes 1,847 older adult participants at baseline
• Results include specific statistical measures (e.g., OR=3.64, 95% CI: 2.92, 4.52; Δχ²(1) = 137.37, p < 0.001)

Limitations

• Column-level documentation is absent; field semantics must be inferred after download
• Row count for the underlying analysis dataset is unknown, which may limit suitability assessment
• Data is provided as a 172.0 KB DOCX file, which is a very small size and likely contains summary results rather than raw data

Provenance

Source

Chinese Longitudinal Healthy Longevity Survey (CLHLS)

Collection Method

Survey data analyzed using Group-Based Trajectory Models (GBTM) and binomial logistic regression.

Time Range

2008 to 2018

Freshness

Last updated 2026-05-19 05:38:17; freshness should be verified

Geography

China