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The diabesity epidemic in the light of evolution: insights from the capacity–load model
The global nutrition transition, which embraces major changes in how food is produced, distributed and consumed, is associated with rapid increases in the prevalence of obesity, but the implications for diabetes differ between populations. A simple conceptual model treats diabetes risk as the functi...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Springer Berlin Heidelberg
2019
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6731192/ https://www.ncbi.nlm.nih.gov/pubmed/31451870 http://dx.doi.org/10.1007/s00125-019-4944-8 |
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author | Wells, Jonathan C. K. |
author_facet | Wells, Jonathan C. K. |
author_sort | Wells, Jonathan C. K. |
collection | PubMed |
description | The global nutrition transition, which embraces major changes in how food is produced, distributed and consumed, is associated with rapid increases in the prevalence of obesity, but the implications for diabetes differ between populations. A simple conceptual model treats diabetes risk as the function of two interacting traits: ‘metabolic capacity,’ which promotes glucose homeostasis, and ‘metabolic load’, which challenges glucose homoeostasis. Population variability in diabetes prevalence is consistent with this conceptual model, indicating that the effect of obesity varies by ethnicity. Evolutionary life history theory can help explain why variability in metabolic capacity and metabolic load emerges. At the species level (hominin evolution), across human populations and within individual life courses, phenotypic variability emerges under selective pressure to maximise reproductive fitness rather than metabolic health. Those exposed to adverse environments may express or develop several metabolic traits that are individually beneficial for reproductive fitness, but which cumulatively increase diabetes risk. Public health interventions can help promote metabolic capacity, but there are limits to the benefits that can emerge within a single generation. This means that efforts to curb metabolic load (obesity, unhealthy lifestyles) must remain at the forefront of diabetes prevention. Such efforts should go beyond individuals and target the broader food system and socioeconomic factors, in order to maximise their efficacy. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s00125-019-4944-8) contains a slideset of the figures for download, which is available to authorised users. |
format | Online Article Text |
id | pubmed-6731192 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-67311922019-09-20 The diabesity epidemic in the light of evolution: insights from the capacity–load model Wells, Jonathan C. K. Diabetologia Review The global nutrition transition, which embraces major changes in how food is produced, distributed and consumed, is associated with rapid increases in the prevalence of obesity, but the implications for diabetes differ between populations. A simple conceptual model treats diabetes risk as the function of two interacting traits: ‘metabolic capacity,’ which promotes glucose homeostasis, and ‘metabolic load’, which challenges glucose homoeostasis. Population variability in diabetes prevalence is consistent with this conceptual model, indicating that the effect of obesity varies by ethnicity. Evolutionary life history theory can help explain why variability in metabolic capacity and metabolic load emerges. At the species level (hominin evolution), across human populations and within individual life courses, phenotypic variability emerges under selective pressure to maximise reproductive fitness rather than metabolic health. Those exposed to adverse environments may express or develop several metabolic traits that are individually beneficial for reproductive fitness, but which cumulatively increase diabetes risk. Public health interventions can help promote metabolic capacity, but there are limits to the benefits that can emerge within a single generation. This means that efforts to curb metabolic load (obesity, unhealthy lifestyles) must remain at the forefront of diabetes prevention. Such efforts should go beyond individuals and target the broader food system and socioeconomic factors, in order to maximise their efficacy. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1007/s00125-019-4944-8) contains a slideset of the figures for download, which is available to authorised users. Springer Berlin Heidelberg 2019-08-27 2019 /pmc/articles/PMC6731192/ /pubmed/31451870 http://dx.doi.org/10.1007/s00125-019-4944-8 Text en © The Author(s) 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Review Wells, Jonathan C. K. The diabesity epidemic in the light of evolution: insights from the capacity–load model |
title | The diabesity epidemic in the light of evolution: insights from the capacity–load model |
title_full | The diabesity epidemic in the light of evolution: insights from the capacity–load model |
title_fullStr | The diabesity epidemic in the light of evolution: insights from the capacity–load model |
title_full_unstemmed | The diabesity epidemic in the light of evolution: insights from the capacity–load model |
title_short | The diabesity epidemic in the light of evolution: insights from the capacity–load model |
title_sort | diabesity epidemic in the light of evolution: insights from the capacity–load model |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6731192/ https://www.ncbi.nlm.nih.gov/pubmed/31451870 http://dx.doi.org/10.1007/s00125-019-4944-8 |
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