The case for large scale fungible cohorts

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Recruitment to UK Biobank has begun. The planned recruitment to a cohort of 500 000 men and women aged 40–69 over 5 years remains an ambitious target, but one which demonstrates the scale of study that is required to investigate many emerging research questions. The essential feature of a cohort study, following change over time in exposure and health status at the individual level, is a natural method through which to obtain a complete model of disease causation and public health.1 The value of large scale cohort studies is their ability to address many aetiologic questions definitively, particularly those involving gene/environment interactions. Large numbers also mean that many research questions can be answered in socially and politically acceptable time frames. However, due to inevitably low response rates, their public health utility is limited. Unrepresentativeness leads to biased estimates of incidence rates and biased estimates of the population impact of risk factors. Furthermore, since Doll and Hill established the first aetiological cohort,2 the design has had little public health development. The high cost of large cohort studies remains an important obstacle to investment in new cohorts. The understandable preference of research funding agencies is to add value to existing cohorts through data sharing. Although data sharing is a helpful way of reducing the influence of study specific bias, many emerging research questions are unlikely to be satisfactorily answered through data collected for other purposes. An alternative economy is to use register-based cohorts. Although enabling very large studies,3 this method is limited to hypotheses involving routinely collected data, and many conditions, such as dementia, will be under diagnosed.4 As the need for longitudinal data increases rather than diminishes, …