PLoS ONE (Jan 2021)

Modelling future trajectories of obesity and body mass index in England.

  • Linda J Cobiac,
  • Peter Scarborough

DOI
https://doi.org/10.1371/journal.pone.0252072
Journal volume & issue
Vol. 16, no. 6
p. e0252072

Abstract

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BackgroundObesity is a leading risk for poor health outcomes in England. We examined best- and worst-case scenarios for the future trajectory of the obesity epidemic.MethodsTaking the last 27 years of Health Survey for England data, we determined both position and shape of the adult body mass index (BMI) distribution and projected these parameters 20 years forward in time. For the best-case scenario, we fitted linear models, allowing for a quadratic relationship between the outcome variable and time, to reflect a potential reversal in upwards trends. For the worst-case scenario, we fitted non-linear models that applied an exponential function to reflect a potential flattening of trends over time. Best-fitting models were identified using Monte Carlo cross-validation on 1991-2014 data, and predictions of population prevalence across five BMI categories were then validated using 2015-17 data.ResultsBoth linear and non-linear models showed a close fit to observed data (mean absolute error ConclusionsWhile obesity prediction depends on chosen modelling methods, even under optimistic assumptions it is likely that the majority of the English population will still be at increased risk of disease due to their weight until at least 2035, without greater allocation of resources to effective interventions.