Pre-Statistical Considerations for Harmonization of Cognitive Instruments: Harmonization of ARIC, CARDIA, CHS, FHS, MESA, and NOMAS

Emily M. Briceño, Alden L. Gross, Bruno J. Giordani, Jennifer J. Manly, Rebecca F. Gottesman, Mitchell S.V. Elkind, Stephen Sidney, Stephanie Hingtgen, Ralph L. Sacco, Clinton B. Wright, Annette Fitzpatrick, Alison E. Fohner, Thomas H. Mosley, Kristine Yaffe, Deborah A. Levine

Research output: Contribution to journalArticlepeer-review

Abstract

Background: Meta-analyses of individuals' cognitive data are increasing to investigate the biomedical, lifestyle, and sociocultural factors that influence cognitive decline and dementia risk. Pre-statistical harmonization of cognitive instruments is a critical methodological step for accurate cognitive data harmonization, yet specific approaches for this process are unclear. Objective: To describe pre-statistical harmonization of cognitive instruments for an individual-level meta-analysis in the blood pressure and cognition (BP COG) study. Methods: We identified cognitive instruments from six cohorts (the Atherosclerosis Risk in Communities Study, Cardiovascular Health Study, Coronary Artery Risk Development in Young Adults study, Framingham Offspring Study, Multi-Ethnic Study of Atherosclerosis, and Northern Manhattan Study) and conducted an extensive review of each item's administration and scoring procedures, and score distributions. Results: We included 153 cognitive instrument items from 34 instruments across the six cohorts. Of these items, 42%were common across ≥2 cohorts. 86%of common items showed differences across cohorts. We found administration, scoring, and coding differences for seemingly equivalent items. These differences corresponded to variability across cohorts in score distributions and ranges. We performed data augmentation to adjust for differences. Conclusion: Cross-cohort administration, scoring, and procedural differences for cognitive instruments are frequent and need to be assessed to address potential impact on meta-analyses and cognitive data interpretation. Detecting and accounting for these differences is critical for accurate attributions of cognitive health across cohort studies.

Original languageEnglish (US)
Pages (from-to)1803-1813
Number of pages11
JournalJournal of Alzheimer's Disease
Volume83
Issue number4
DOIs
StatePublished - 2021
Externally publishedYes

Keywords

  • Cognition
  • dementia
  • epidemiology
  • methods

ASJC Scopus subject areas

  • Neuroscience(all)
  • Clinical Psychology
  • Geriatrics and Gerontology
  • Psychiatry and Mental health

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