Statistical Approaches for the Analysis of Combined Health-Related Factors in Association with Adult Cognitive Outcomes: A Scoping Review.

Sara E Dingle, Melissa S Bujtor, Catherine M Milte, Steven J Bowe, Robin M Daly, Susan J Torres

Journal: Journal of Alzheimer's disease : JAD 2023;92(4):1147-1171

PMID: 36872778

Abstract

BACKGROUND

Dementia prevention is a global health priority, and there is emerging evidence to support associations between individual modifiable health behaviors and cognitive function and dementia risk. However, a key property of these behaviors is they often co-occur or cluster, highlighting the importance of examining them in combination.

OBJECTIVE

To identify and characterize the statistical approaches used to aggregate multiple health-related behaviors/modifiable risk factors and assess associations with cognitive outcomes in adults.

METHODS

Eight electronic databases were searched to identify observational studies exploring the association between two or more aggregated health-related behaviors and cognitive outcomes in adults.

RESULTS

Sixty-two articles were included in this review. Fifty articles employed co-occurrence approaches alone to aggregate health behaviors/other modifiable risk factors, eight studies used solely clustering-based approaches, and four studies used a combination of both. Co-occurrence methods include additive index-based approaches and presenting specific health combinations, and whilst simple to construct and interpret, do not consider the underlying associations between co-occurring behaviors/risk factors. Clustering-based approaches do focus on underlying associations, and further work in this area may aid in identifying at-risk subgroups and understanding specific combinations of health-related behaviors/risk factors of particular importance in the scope of cognitive function and neurocognitive decline.

CONCLUSION

A co-occurrence approach to aggregating health-related behaviors/risk factors and exploring associations with adult cognitive outcomes has been the predominant statistical approach used to date, with a lack of research employing more advanced statistical methods to explore clustering-based approaches.

Address: Institute for Physical Activity and Nutrition Research, School of Exercise and Nutrition Sciences, Deakin University, Melbourne, VIC, Australia.; Department of Psychological Medicine, Stress, Psychiatry and Immunology Laboratory, Institute of Psychiatry, Psychology & Neuroscience, King's College, London, UK.; Biostatistics Unit, Faculty of Health, Deakin University, Melbourne, VIC, Australia.; Faculty of Health, Victoria University of Wellington, Wellington, New Zealand.
Bant logo

© Copyright 2026, Nutrition Evidence

NED wishes to thank the following organisations for their support:

We use cookies to improve your experience and analyze site traffic with Google Analytics. By continuing to use our site, you agree to our use of cookies. Learn more.