Objectives To develop a model to predict future socioeconomic inequalities in body mass index (BMI) and obesity.
Design Microsimulation modelling using BMI data from adult participants of Australian Health Surveys, and published data on the relative risk of mortality in relation to BMI and socioeconomic position (SEP), based on education.
Participants 74 329 adults, aged 20 and over from Australian Health Surveys, 1995–2015.
Primary and secondary outcome measures The primary outcomes were BMI trajectories and obesity prevalence by SEP for four birth cohorts, born 10 years apart, centred on 1940, 1950, 1960 and 1970.
Results Simulations projected persistent or widening socioeconomic inequality in BMI and obesity over the adult life course, for all birth cohorts. Recent birth cohorts were predicted to have greater socioeconomic inequality by middle age, compared with earlier cohorts. For example, among men, there was no inequality in obesity prevalence at age 60 for the 1940 birth cohort (low SEP 25% (95% CI 17% to 34%); high SEP 26% (95% CI 19% to 34%)), yet for the 1970 birth cohort, obesity prevalence was projected to be 51% (95% CI 43% to 58%) and 41% (95% CI 36% to 46%) for the low and high SEP groups, respectively. Notably, for more recent birth cohorts, the model predicted the greatest socioeconomic inequality in severe obesity (BMI >35 kg/m2) at age 60.
Conclusions Lower SEP groups and more recent birth cohorts are at higher risk of obesity and severe obesity, and its consequences in middle age. Prevention efforts should focus on these vulnerable population groups in order to avoid future disparities in health outcomes. The model provides a framework for further research to investigate which interventions will be most effective in narrowing the gap in socioeconomic disparities in obesity in adulthood.
- socioeconomic inequalities
- BMI trajectory
This is an open access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited, appropriate credit is given, any changes made indicated, and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/.
Statistics from Altmetric.com
Contributors The author’s responsibilities were as follows: AH conceived the study. Model conceptualisation: AH and TL. Software: TL and AH. Analysed the data: AH, TL and EJT. Performed experiments: TL and EJT. Visualisation: AH, EJT and AK. Writing first draft: AH and AK. All authors revised the manuscript for important intellectual content. AH, EJT and TL had full access to the data and take responsibility for the integrity of the data analysis. AH is the guarantor. All authors have given final approval of the version to be published.
Funding EJT receives funding support from the National Health and Medical Research Council Centre of Research Excellence in Early Prevention of Obesity in Childhood (APP1101675). AK is supported by the Kassulke Scholarship for PhD study. TL is supported by a National Health and Medical Research Council Early Career Fellowship and a Heart Foundation Postdoctoral Fellowship (APP 1141392).
Competing interests None declared.
Provenance and peer review Not commissioned; externally peer reviewed.
Data sharing statement The model code is available on request. Data on which analyses are based are available from the Australian Bureau of Statistics.
Patient consent for publication Not required.
If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.