Validation of a Latent Construct for Dementia in a Population-Wide Dataset from Singapore

Chao Xu Peh, Edimansyah Abdin, Janhavi A. Vaingankar, Swapna Verma, Boon Yiang Chua, Vathsala Sagayadevan, Esmond Seow, Yunjue Zhang, Shazana Shahwan, Li Ling Ng, Martin Prince, Siow Ann Chong, Mythily Subramaniam, Brandon Gavett (Editor)

Research output: Contribution to journalArticlepeer-review

10 Citations (Scopus)


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.
Original languageEnglish
Pages (from-to)823-833
Issue number2
Publication statusPublished - 19 Nov 2016


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