In recent years, researchers have sought to integrate genetic and other biomarker data with epidemiological data by obtaining biospecimens from participants in large-scale cohort studies. However, participation rates in biobank studies vary considerably [1–8] and are generally lower than for non-biomarker oriented research [2]. The limited evidence available suggests that older individuals, ethnic minorities, and those without a family history of illness are less likely to donate to biobanks than other potential participants [3, 5, 6]. Despite its implications for prevalence estimates and other aspects of biobank metholodogy, how participation relates to broader demographic, health and lifestyle factors is not known. This study investigates the relation of demographic, lifestyle and other personal characteristics, to participation in a biobank among members of an existing cohort study.

Information from the 45 and Up Study baseline questionnaire was used as the source of data to compare the characteristics of participants and non-participants in the Link-Up biobank and included: age; sex; education; country of origin (born in Australia/not born in Australia); whether a participant was caring for a sick or disabled family member or friend; self-report of assistance required with day-to-day tasks due to illness or disability; smoking status; body mass index; and physical limitations. Physical limitations were measured using the MOS-PF, which asks participants whether they are limited in their ability to perform vigorous and moderate physical activities and tasks such as: lifting shopping; climbing stairs; walking; bending, kneeling or stooping; and bathing or dressing [12]. This score was categorised into 4 groups: 100 (no physical limitations reported), 90–99, 60–89, and 0–59. Body mass index was calculated as the reported weight in kilograms divided by the reported height in metres, squared, and was classified according to World Health Organization criteria into underweight (<18.5kgm^-2), normal weight (18.5-24.9kgm^-2), overweight (25.0-29.9kgm^-2) and obese (≥30.0kgm^-2) [13].

Among individuals already taking part in a cohort study, people who participated in an biobank, through donating a blood sample and having physical measurements taken, were, on average, significantly younger, wealthier, more educated, less disabled and more likely to be born in Australia, compared to cohort members who did not participate. Those in part-time work were more likely to participate, and smokers and those with caregiving responsibilities were less likely to participate than other cohort members. No significant variation in response rate was observed according to sex, distance from collection site, time since joining the baseline 45 and Up Study and body mass index.

Research has previously been undertaken to investigate whether individuals would be willing to participate in biobanking, using hypothetical scenarios [14–17]. Past studies indicate that individuals may be reluctant to donate because of lack of personal relevance, concerns that their sample will be misused, and general distrust of biobanks or researchers [1, 18]. However, data comparing the characteristics of individuals who actually do or do not participate in biobanks are limited. Consistent with results from this study, previous studies have found that ethnic minorities and older people are less likely than others to donate biospecimens for research [19–21]. We were unable to identify any studies that evaluated directly the influence of health and lifestyle characteristics on biobank participation; the factors we identified are similar to those that influence participation in research in general (e.g. “the healthy cohort effect”) [22–24]. Overall, our findings suggest that individuals less engaged in health-seeking behaviours (e.g. smokers) were less likely to participate, as well as those potentially affected by access difficulties or time limitations, such as those with disabilities or carer responsibilities, or the elderly.

Participation rates and factors influencing participation in biobanks vary from study to study, and according to context [1–4, 8]. Even with the immense resources of the UK Biobank, a response rate of <10% was achieved. It has been suggested that those donating to biobanks should be representative of the general public [3]. Although this is generally seen as important for reliable estimates of point prevalence, experience to date indicates that this is unlikely to be practical on a large scale. Furthermore, participants do not need to be representative of the general population to make internal comparisons of relative risk within the cohort (i.e. to quantify associations between exposures and outcomes), which is generally the central purpose of large scale, long term biobanks. Such estimates of relative risk remain valid, even when the cohort is from a relatively select group [10, 25]. Examples of highly selected, yet valid, internal comparisons include estimates of the relative risks of lung cancer for smokers versus non smokers, among British Doctors [26], and consistent estimates of breast cancer risk in users versus non users of the oral contraceptive pill, in a variety of cohort studies [27]. For this study, this means that although the absolute response rates to the invitation may not necessarily be generalisable to other studies, internal comparisons, including characteristics of responders versus non-responders, are likely to be both valid and generalisable [10, 25]. More importantly, the implication for biobanks generally are that response rates and the characteristics of responders and non-responders may influence the generalisability of prevalence estimates from biobanks, but are less likely to be a problem for internal comparisons.

Another important consideration for long term biobanks is the need to include sufficient numbers of participants from specific population groups of interest to allow appropriately powered analyses. Our results indicate that certain groups are less likely to participate and strategies to enhance participation in these groups may be necessary to ensure appropriate heterogeneity in the biobank population. Such strategies could include targeted community-based recruitment of the elderly and migrant groups and home-based recruitment methods.

People participating in research studies involving biobanking differ from those who do not take part in a number of ways, and are generally in better health. In keeping with cohort studies in general, this means that caution should be exercised in generalising from estimates of absolute prevalence from biobank studies, however for many internal comparisons, estimates are likely to remain valid.