Doan, TinhLeach, LianaDoan, NhanStrazdins, Lyndall2025-05-232025-05-231070-5503WOS:001360972900001PubMed:39567469ORCID:/0000-0003-3686-2553/work/194842488ORCID:/0000-0002-2297-8187/work/194843732ORCID:/0000-0001-5158-6855/work/194845340http://www.scopus.com/inward/record.url?scp=85209755518&partnerID=8YFLogxKhttps://hdl.handle.net/1885/733751892Background: More than two-thirds of Australians are overweight. Existing research based on non-experimental data has primarily established associations, rather than causal inferences, between physical activity (PA) and body mass index (BMI). PA and BMI likely affect each other, a reciprocal interplay most studies overlook. We investigate the causal relationship between PA and BMI using a quasi-experimental approach to overcome reverse causality bias. Method: A maximum likelihood treatment effect model, a quasi-experimental method, was employed. Data was from an observational longitudinal dataset of 130,397 observations with 19,677 unique individuals aged 15–64 (52% are females) from the Household, Income, and Labour Dynamics in Australia survey 2006–2019. We first tested for the reverse relationships (whereby overweight limits PA) before estimating the effect of PA on BMI. Results: The first-stage modelling results showed that overweight and obese adults are less likely to engage in PA, as are those resource constrained (time or socioeconomically). In the second modelling stage, there was a clear and significant effect of PA on BMI. Being physically active more than three times a week led to a 2.55-point reduction in BMI (p < 0.001). For women, this effect was more pronounced, with a 2.92-point reduction (p < 0.001). Conclusion: This study leverages existing longitudinal data to provide causal estimates of PA on BMI—finding that PA reduces BMI, particularly for women. As many individuals face resource constraints, campaigns to promote behavioural change need to be nuanced and shift some of the responsibility for physically activity from individuals to policy and organizational reforms.We are grateful to and acknowledge the support of the following institutions: The Australian Research Council Discovery Grant DP190100975; the Household, Income and Labour Dynamics in Australia (HILDA) Survey which was initiated and is funded by the Australian Government Department of Social Services (DSS) and managed by the Melbourne Institute of Applied Economic and Social Research (Melbourne Institute). The findings and views reported in this paper, however, are those of the authors.15enPublisher Copyright: © International Society of Behavioral Medicine 2024.AustraliaBMICausal relationshipPhysical activityTreatment effect model2024-11-0810.1007/s12529-024-10336-985209755518