Exportation and Validation of Latent Constructs for Dementia Case Finding in a Mexican American Population-based Cohort

Donald R. Royall, Raymond F. Palmer, Kyriakos Markides

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

Background The latent variable "δ " has been validated as a dementia phenotype. δ can be extracted from Spearman's general intelligence factor "g" in any data set that contains measures of cognition and instrumental activities of daily living (IADL). We used δ composites ("d-scores") to estimate the prevalence of dementia in the Hispanic Established Population for Epidemiological Studies in the Elderly (H-EPESE). Method δ was constructed from Mini-Mental State Examination, a clock-drawing task (CLOX), and IADL. δ 's H-EPESE factor weights were validated in the well-characterized Texas Alzheimer's Research and Care Consortium (TARCC). Optimal thresholds for the discrimination between "Alzheimer's disease" (AD) versus normal controls (NCs) were determined by receiver operating characteristic curve. Those thresholds were used to estimate the prevalence of dementia in H-EPESE. Results Each δ homolog fits its source's data well. d-scores were strongly associated with Clinical Dementia Rating scale Sum of Boxes (r =.74-.85, all p <.001], and accurately distinguished AD cases from NCs, in both Mexican Americans (MAs) and non-Hispanic Whites (NHWs) [c = 0.94-0.96]. The TARCC MA threshold estimated the prevalence of dementia at 21.4% in H-EPESE. The NHW threshold estimated the prevalence of dementia at 21.0%. Conclusions It is possible to export δ composites from populations to well-characterized cohorts for validation.

Original languageEnglish (US)
Pages (from-to)947-955
Number of pages9
JournalJournals of Gerontology - Series B Psychological Sciences and Social Sciences
Volume72
Issue number6
DOIs
StatePublished - Nov 1 2017
Externally publishedYes

Fingerprint

dementia
Dementia
Hispanic Americans
Epidemiologic Studies
Population
Activities of Daily Living
Alzheimer Disease
Information Storage and Retrieval
Intelligence
Research
ROC Curve
Cognition
rating scale
Phenotype
Weights and Measures
cognition
intelligence
discrimination
recipient
examination

Keywords

  • Aging
  • Cognition
  • Dementia
  • Functional status
  • g

ASJC Scopus subject areas

  • Social Psychology
  • Clinical Psychology
  • Gerontology
  • Geriatrics and Gerontology

Cite this

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title = "Exportation and Validation of Latent Constructs for Dementia Case Finding in a Mexican American Population-based Cohort",
abstract = "Background The latent variable {"}δ {"} has been validated as a dementia phenotype. δ can be extracted from Spearman's general intelligence factor {"}g{"} in any data set that contains measures of cognition and instrumental activities of daily living (IADL). We used δ composites ({"}d-scores{"}) to estimate the prevalence of dementia in the Hispanic Established Population for Epidemiological Studies in the Elderly (H-EPESE). Method δ was constructed from Mini-Mental State Examination, a clock-drawing task (CLOX), and IADL. δ 's H-EPESE factor weights were validated in the well-characterized Texas Alzheimer's Research and Care Consortium (TARCC). Optimal thresholds for the discrimination between {"}Alzheimer's disease{"} (AD) versus normal controls (NCs) were determined by receiver operating characteristic curve. Those thresholds were used to estimate the prevalence of dementia in H-EPESE. Results Each δ homolog fits its source's data well. d-scores were strongly associated with Clinical Dementia Rating scale Sum of Boxes (r =.74-.85, all p <.001], and accurately distinguished AD cases from NCs, in both Mexican Americans (MAs) and non-Hispanic Whites (NHWs) [c = 0.94-0.96]. The TARCC MA threshold estimated the prevalence of dementia at 21.4{\%} in H-EPESE. The NHW threshold estimated the prevalence of dementia at 21.0{\%}. Conclusions It is possible to export δ composites from populations to well-characterized cohorts for validation.",
keywords = "Aging, Cognition, Dementia, Functional status, g",
author = "Royall, {Donald R.} and Palmer, {Raymond F.} and Kyriakos Markides",
year = "2017",
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T1 - Exportation and Validation of Latent Constructs for Dementia Case Finding in a Mexican American Population-based Cohort

AU - Royall, Donald R.

AU - Palmer, Raymond F.

AU - Markides, Kyriakos

PY - 2017/11/1

Y1 - 2017/11/1

N2 - Background The latent variable "δ " has been validated as a dementia phenotype. δ can be extracted from Spearman's general intelligence factor "g" in any data set that contains measures of cognition and instrumental activities of daily living (IADL). We used δ composites ("d-scores") to estimate the prevalence of dementia in the Hispanic Established Population for Epidemiological Studies in the Elderly (H-EPESE). Method δ was constructed from Mini-Mental State Examination, a clock-drawing task (CLOX), and IADL. δ 's H-EPESE factor weights were validated in the well-characterized Texas Alzheimer's Research and Care Consortium (TARCC). Optimal thresholds for the discrimination between "Alzheimer's disease" (AD) versus normal controls (NCs) were determined by receiver operating characteristic curve. Those thresholds were used to estimate the prevalence of dementia in H-EPESE. Results Each δ homolog fits its source's data well. d-scores were strongly associated with Clinical Dementia Rating scale Sum of Boxes (r =.74-.85, all p <.001], and accurately distinguished AD cases from NCs, in both Mexican Americans (MAs) and non-Hispanic Whites (NHWs) [c = 0.94-0.96]. The TARCC MA threshold estimated the prevalence of dementia at 21.4% in H-EPESE. The NHW threshold estimated the prevalence of dementia at 21.0%. Conclusions It is possible to export δ composites from populations to well-characterized cohorts for validation.

AB - Background The latent variable "δ " has been validated as a dementia phenotype. δ can be extracted from Spearman's general intelligence factor "g" in any data set that contains measures of cognition and instrumental activities of daily living (IADL). We used δ composites ("d-scores") to estimate the prevalence of dementia in the Hispanic Established Population for Epidemiological Studies in the Elderly (H-EPESE). Method δ was constructed from Mini-Mental State Examination, a clock-drawing task (CLOX), and IADL. δ 's H-EPESE factor weights were validated in the well-characterized Texas Alzheimer's Research and Care Consortium (TARCC). Optimal thresholds for the discrimination between "Alzheimer's disease" (AD) versus normal controls (NCs) were determined by receiver operating characteristic curve. Those thresholds were used to estimate the prevalence of dementia in H-EPESE. Results Each δ homolog fits its source's data well. d-scores were strongly associated with Clinical Dementia Rating scale Sum of Boxes (r =.74-.85, all p <.001], and accurately distinguished AD cases from NCs, in both Mexican Americans (MAs) and non-Hispanic Whites (NHWs) [c = 0.94-0.96]. The TARCC MA threshold estimated the prevalence of dementia at 21.4% in H-EPESE. The NHW threshold estimated the prevalence of dementia at 21.0%. Conclusions It is possible to export δ composites from populations to well-characterized cohorts for validation.

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