Existing data sets to support studies of dementia or significant cognitive impairment and comorbid chronic conditions. Issue 6 (5th September 2014)

• Record Type: Journal Article
• Authors: Bell, Janice F.; Fitzpatrick, Annette L.; Copeland, Catherine; Chi, Gloria; Steinman, Lesley; Whitney, Robin L.; Atkins, David C.; Bryant, Lucinda L.; Grodstein, Francine; Larson, Eric; Logsdon, Rebecca; Snowden, Mark
• Is Part Of: Alzheimer's & dementia. Volume 11:Issue 6(2015)
• Page Start: 622
• Page End: 638
• Publication Date: 2014-09-05
• Subjects: Public health -- Databases -- Secondary Data analysis -- Dementia -- Cognitive impairment -- Multiple -- Chronic conditions; Alzheimer's disease -- Periodicals; Alzheimer Disease -- Periodicals; Dementia -- Periodicals; Démence; Maladie d'Alzheimer; Périodique électronique (Descripteur de forme); Ressource Internet (Descripteur de forme); 616.83
• DOI: 10.1016/j.jalz.2014.07.002
• Languages: English
• ISSNs: 1552-5260

Abstract

Abstract: Background: Dementia or other significant cognitive impairment (SCI) are often comorbid with other chronic diseases. To promote collaborative research on the intersection of these conditions, we compiled a systematic inventory of major data resources. Methods: Large data sets measuring dementia and/or cognition and chronic conditions in adults were included in the inventory. Key features of the resources were abstracted including region, participant sociodemographic characteristics, study design, sample size, accessibility, and available measures of dementia and/or cognition and comorbidities. Results: 117 study data sets were identified; 53% included clinical diagnoses of dementia along with valid and reliable measures of cognition. Most (79%) used longitudinal cohort designs and 41% had sample sizes greater than 5000. Approximately 47% were European‐based, 40% were US‐based, and 11% were based in other countries. Conclusions: Many high‐quality data sets exist to support collaborative studies of the effects of dementia or SCI on chronic conditions and to inform the development of evidence‐based disease management programs.