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

<h4>Background</h4>Obesity 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.<h4>Methods</h4>Taking the last 27 years of Health Survey for England data, we determined both positi...

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Autores principales:	Linda J Cobiac, Peter Scarborough
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/c97466a62eba49e8aa1f3fc31d3350b2
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spelling	oai:doaj.org-article:c97466a62eba49e8aa1f3fc31d3350b22021-12-02T20:05:21ZModelling future trajectories of obesity and body mass index in England.1932-620310.1371/journal.pone.0252072https://doaj.org/article/c97466a62eba49e8aa1f3fc31d3350b22021-01-01T00:00:00Zhttps://doi.org/10.1371/journal.pone.0252072https://doaj.org/toc/1932-6203<h4>Background</h4>Obesity 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.<h4>Methods</h4>Taking 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.<h4>Results</h4>Both linear and non-linear models showed a close fit to observed data (mean absolute error <2%). In the best-case scenario, the proportion of the population at increased risk (BMI≥25kg/m2) is predicted to fall from 66% in 2017 to 53% (95% confidence interval: 41% to 64%) in 2035. In the worst-case scenario, this proportion is likely to remain relatively stable overall- 64% (37% to 90%) in 2035 -but with an increasing proportion of the population at highest risk (BMI≥35kg/m2).<h4>Conclusions</h4>While 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.Linda J CobiacPeter ScarboroughPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 16, Iss 6, p e0252072 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Linda J Cobiac Peter Scarborough Modelling future trajectories of obesity and body mass index in England.
description	<h4>Background</h4>Obesity 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.<h4>Methods</h4>Taking 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.<h4>Results</h4>Both linear and non-linear models showed a close fit to observed data (mean absolute error <2%). In the best-case scenario, the proportion of the population at increased risk (BMI≥25kg/m2) is predicted to fall from 66% in 2017 to 53% (95% confidence interval: 41% to 64%) in 2035. In the worst-case scenario, this proportion is likely to remain relatively stable overall- 64% (37% to 90%) in 2035 -but with an increasing proportion of the population at highest risk (BMI≥35kg/m2).<h4>Conclusions</h4>While 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.
format	article
author	Linda J Cobiac Peter Scarborough
author_facet	Linda J Cobiac Peter Scarborough
author_sort	Linda J Cobiac
title	Modelling future trajectories of obesity and body mass index in England.
title_short	Modelling future trajectories of obesity and body mass index in England.
title_full	Modelling future trajectories of obesity and body mass index in England.
title_fullStr	Modelling future trajectories of obesity and body mass index in England.
title_full_unstemmed	Modelling future trajectories of obesity and body mass index in England.
title_sort	modelling future trajectories of obesity and body mass index in england.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/c97466a62eba49e8aa1f3fc31d3350b2
work_keys_str_mv	AT lindajcobiac modellingfuturetrajectoriesofobesityandbodymassindexinengland AT peterscarborough modellingfuturetrajectoriesofobesityandbodymassindexinengland
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Modelling future trajectories of obesity and body mass index in England.

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