Impact of follow-up time and analytical approaches to account for reverse causality on the association between physical activity and health outcomes in UK Biobank
journal contributionposted on 18.06.2021, 09:42 by Tessa Strain, Katrien Wijndaele, Stephen J Sharp, Paddy C Dempsey, Nick Wareham, Søren Brage
Abstract Background The advent of very large cohort studies (n > 500 000) has given rise to prospective analyses of health outcomes being undertaken after short (<4 years) follow-up periods. However, these studies are potentially at risk of reverse causality bias. We investigated differences in the associations between self-reported physical activity and all-cause and cardiovascular disease (CVD) mortality, and incident CVD, using different follow-up time cut-offs and methods to account for reverse causality bias. Methods Data were from n = 452 933 UK Biobank participants, aged 38–73 years at baseline. Median available follow-up time was 7 years (for all-cause and CVD mortality) and 6.1 years (for incident CVD). We additionally analysed associations at 1-, 2- and 4-year cut-offs after baseline. We fit up to four models: (1) adjusting for prevalent CVD and cancer, (2) excluding prevalent disease, (3) and (4) Model 2 excluding incident cases in the first 12 and 24 months, respectively. Results The strength of associations decreased as follow-up time cut-off increased. For all-cause mortality, Model 1 hazard ratios were 0.73 (0.69–0.78) after 1 year and 0.86 (0.84–0.87) after 7 years. Associations were weaker with increasing control for possible reverse causality. After 7-years follow-up, the hazard ratios were 0.86 (0.84–0.87) and 0.88 (0.86–0.90) for Models 1 and 4, respectively. Associations with CVD outcomes followed similar trends. Conclusions As analyses with longer follow-up times and increased control for reverse causality showed weaker associations, there are implications for the decision about when to analyse a cohort study with ongoing data collection, the interpretation of study results and their contribution to meta-analyses.
This work was supported by the Medical Research Council [grant numbers MC_UU_12015/1 and MC_UU_12015/3] (T.S., K.W., S.J.S., P.C.D., N.W., S.B.) and a National Health and Medical Research Council of Australia research fellowship [No. 1142685] (P.C.D.)