In a paper recently published in Nature Aging, Carol Brayne (University of Cambridge) and DUPRI's Terrie Moffitt discuss the potential limitations of large-scale volunteer databanks (LSVD) in tackling ongoing global health challenges and inequalities. Large-scale volunteer databanks (LSVD) have emerged from the recognized value of cohorts, attracting substantial funding and promising great scientific value. A major focus is their size, with the implicit and sometimes explicit assumption that large size (thus power) creates generalizability. The authors contend that this is open to challenge. In the context of aging and age-related disease research, LSVD typically have limitations such as healthy volunteer, white ethnicity and high-education biases, and they omit early and late life stages critical for understanding aging. In short, these data sources are often not representative of the general population. Their outputs are heavily focused on biomedical pathways of single chronic diseases. LSVD outputs increasingly dominate the funding and the publication landscapes. The authors call for more transparent reporting in LSVD research, as well as a greater reflection on the value of LSVD in relation to resources consumed. They invite funders and researchers to examine whether LSVD do actually contribute knowledge needed for our acute global health challenges including inequalities.