Attrition and bias in the MRC cognitive function and ageing study: an epidemiological investigation

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Abstract
Any hypothesis in longitudinal studies may be affected by attrition and poor response rates. The MRC Cognitive Function and Ageing study (MRC CFAS) is a population based longitudinal study in five centres with identical methodology in England and Wales each recruiting approximately 2,500 individuals. This paper aims to identify potential biases in the two-year follow-up interviews. Initial non-response: Those not in the baseline interviews were compared in terms of mortality to those who were in the baseline interviews at the time of the second wave interviews (1993-1996). Longitudinal attrition: Logistic regression analysis was used to examine baseline differences between individuals who took part in the two-year longitudinal wave compared with those who did not. Initial non-response: Individuals who moved away after sampling but before baseline interview were 1.8 times more likely to die by two years (95% Confidence interval(CI) 1.3-2.4) compared to respondents, after adjusting for age. The refusers had a slightly higher, but similar mortality pattern to responders (Odds ratio 1.2, 95%CI 1.1-1.4). Longitudinal attrition: Predictors for drop out due to death were being older, male, having impaired activities of daily living, poor self-perceived health, poor cognitive ability and smoking. Similarly individuals who refused were more likely to have poor cognitive ability, but had less years of full-time education and were more often living in their own home though less likely to be living alone. There was a higher refusal rate in the rural centres. Individuals who moved away or were uncontactable were more likely to be single, smokers, demented or depressed and were less likely to have moved if in warden-controlled accommodation at baseline. Longitudinal estimation of factors mentioned above could be biased, particularly cognitive ability and estimates of movements from own home to residential homes. However, these differences could also affect other investigations, particularly the estimates of incidence and longitudinal effects of health and psychiatric diseases, where the factors shown here to be associated with attrition are risk factors for the diseases. All longitudinal studies should investigate attrition and this may help with aspects of design and with the analysis of specific hypotheses.