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

Article type: Research Article

Authors: Briceño, Emily M.^{a; b; c; *} | Gross, Alden L.^d | Giordani, Bruno J.^{e; f} | Manly, Jennifer J.^{g; h} | Gottesman, Rebecca F.ⁱ | Elkind, Mitchell S.V.^{g; j} | Sidney, Stephen^k | Hingtgen, Stephanie^l | Sacco, Ralph L.^m | Wright, Clinton B.ⁿ | Fitzpatrick, Annette^o | Fohner, Alison E.^o | Mosley, Thomas H.^p | Yaffe, Kristine^q | Levine, Deborah A.^{b; c; l; r}

Affiliations: [a] Department of Physical Medicine and Rehabilitation, University of Michigan Medical School, Ann Arbor, MI, USA | [b] Cognitive Health Services Research Program, University of Michigan Medical School, Ann Arbor, MI, USA | [c] Institute for Healthcare Policy and Innovation, University of Michigan, Ann Arbor, MI, USA | [d] Department of Epidemiology, Johns Hopkins Bloomberg School Public Health, Baltimore, MD, USA | [e] Departments of Psychiatry, Neurology, Psychology, and School of Nursing; University of Michigan, Ann Arbor, MI, USA | [f] Mary A. Rackham Institute, University of Michigan, Ann Arbor, MI, USA | [g] Department of Neurology, Vagelos College of Physicians and Surgeons, Columbia University, New York, NY, USA | [h] Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, Columbia University, New York, NY, USA | [i] National Institute of Neurological Disorders and Stroke Intramural Research Program, Bethesda, MD, USA | [j] Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, USA | [k] Kaiser Permanente Northern California Division of Research, Oakland, CA, USA | [l] Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA | [m] Department of Neurology, University of Miami, Miami, FL, USA | [n] Division of Clinical Research, National Institute of Neurological Disorders and Stroke (NINDS), Bethesda, MD, USA | [o] Department of Epidemiology, University of Washington, Seattle, WA, USA | [p] Department of Medicine-Geriatrics, University of Mississippi Medical Center, Jackson, MI, USA | [q] Departments of Psychiatry, Neurology and Epidemiology, University of California, San Francisco, San Francisco, CA, USA | [r] Department of Neurology and Stroke Program, University of Michigan, Ann Arbor, MI, USA

Correspondence: [*] Correspondence to: Emily M. Briceño, PhD, University of Michigan Medical School, Department of Physical Medicine and Rehabilitation, Rehabilitation Psychology and Neuropsychology, 325 East Eisenhower Parkway, Ann Arbor, MI 48108, USA. Tel.: +1 734 763 6496; E-mail: emilande@med.umich.edu.

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.

Keywords: Cognition, dementia, epidemiology, methods

DOI: 10.3233/JAD-210459

Journal: Journal of Alzheimer's Disease, vol. 83, no. 4, pp. 1803-1813, 2021