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Updated: Mar 12, 2026

Using Retinal Imaging to Study Dementia
Published on: November 6, 2017
Validation of a Latent Construct for Dementia in a Population-Wide Dataset from Singapore
Chao Xu Peh1, Edimansyah Abdin1, Janhavi A Vaingankar1
1Research Division, Institute of Mental Health, Singapore, Singapore.
Background:
The latent variable δ has been proposed as a proxy for dementia. Previous validation studies have been conducted using convenience samples. It is currently unknown how δ performs in population-wide data.
Objective:
To validate δ in Singapore using population-wide epidemiological study data on persons aged 60 and above.
Methods:
δ was constructed using items from the Community Screening Instrument for Dementia (CSI'D) and World Health Organization Disability Assessment Schedule (WHODAS II). Confirmatory factor analysis (CFA) was conducted to examine δ model fit. Convergent validity was examined with the Clinical Dementia Rating scale (CDR) and GMS-AGECAT dementia. Divergent validity was examined with GMS-AGECAT depression.
Results:
The δ model demonstrated fit to the data, χ2(df) = 249.71(55), p < 0.001, CFI = 0.990, TLI = 0.997, RMSEA = 0.037. Latent variable δ was significantly associated with CDR and GMS-AGECAT dementia (range: β= 0.32 to 0.63), and was not associated with GMS-AGECAT depression. Compared to unadjusted models, δ model fit was poor when adjusted for age, gender, ethnicity, and education.
Conclusion:
The study found some support for δ as a proxy for dementia in Singapore based on population data. Both convergent and divergent validity were established. In addition, the δ model structure appeared to be influenced by age, gender, ethnicity, and education covariates.
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