Using a birth cohort to study brain health and preclinical dementia: recruitment and participation rates in Insight 46

• Main Authors: Sarah-Naomi James, Christopher A. Lane, Thomas D. Parker, Kirsty Lu, Jessica D. Collins, Heidi Murray-Smith, Michelle Byford, Andrew Wong, Ashvini Keshavan, Sarah Buchanan, Sarah E. Keuss, Diana Kuh, Nick C. Fox, Jonathan M. Schott, Marcus Richards
• Format: Article
• Language: English
• Published: BMC 2018-12-01
• Series: BMC Research Notes
• Subjects: Participation; Birth cohort; Longitudinal study; Neuroimaging; Sub-study; Older adults
• Online Access: http://link.springer.com/article/10.1186/s13104-018-3995-0

Abstract Objective Identifying and recruiting people with early pre-symptomatic Alzheimer’s disease to neuroimaging research studies is increasingly important. The extent to which results of these studies can be generalised depends on the recruitment and representativeness of the participants involved. We now report the recruitment and participation patterns from a neuroscience sub-study of the MRC National Survey of Health and Development, “Insight 46”. This study aimed to recruit 500 participants for extensive clinical and neuropsychological testing, and neuroimaging. We investigate how sociodemographic factors, health conditions and health-related behaviours predict participation at different levels of recruitment. Results We met our target recruitment (n = 502). Higher educational attainment and non-manual socio-economic position (SEP) were consistent predictors of recruitment. Health-related variables were also predictive at every level of recruitment; in particular higher cognition, not smoking and better self-rating health. Sex and APOE-e4 status were not predictors of participation at any level. Whilst recruitment targets were met, individuals with lower SEP, lower cognition, and more health problems are under-represented in Insight 46. Understanding the factors that influence recruitment are important when interpreting results; for Insight 46 it is likely that health-related outcomes and life course risks will under-estimate those seen in the general population.