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A Mathematical Model for Predicting Obesity Transmission With Both Genetic and Nongenetic Heredity
OBJECTIVE: Obesity is transmissible across generations through both genetic and nongenetic routes, but distinguishing between these factors is challenging. We aimed to quantitatively study the contribution of these genetic and nongenetic effects to assess their influence on obesity prevalence. METHO...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5916034/ https://www.ncbi.nlm.nih.gov/pubmed/29575611 http://dx.doi.org/10.1002/oby.22135 |
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author | Ejima, Keisuke Thomas, Diana Allison, David B. |
author_facet | Ejima, Keisuke Thomas, Diana Allison, David B. |
author_sort | Ejima, Keisuke |
collection | PubMed |
description | OBJECTIVE: Obesity is transmissible across generations through both genetic and nongenetic routes, but distinguishing between these factors is challenging. We aimed to quantitatively study the contribution of these genetic and nongenetic effects to assess their influence on obesity prevalence. METHODS: We proposed a mathematical model that incorporated both genetic and nongenetic effects of obesity. Model parameters were estimated by using observational data. Model simulations were used to assess the sensitivity of model parameters. To strengthen our approach, we also performed the parameter estimation and simulation using data from the UK. RESULTS: Individuals homozygous for a ‘hypothetical obesogenic gene’ are suggested to be more susceptible to both social contagious risk and spontaneous weight gain risk. The model predicted that obesity prevalence reaches 41.03% (39.28, 44.31) and 26.77% (25.62, 28.06) at 2030 in the US and UK, respectively. The social contagious risk factor had a greater overall impact on the distribution of the population with obesity than did spontaneous weight gain risk or mother-to-child obesity transmission risk. CONCLUSIONS: Although the proposed “first approximation” model captured the complex interactions between the genetic and nongenetic effects on obesity, this framework remains incomplete. Future work should incorporate other key features driving the obesity epidemic. |
format | Online Article Text |
id | pubmed-5916034 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
record_format | MEDLINE/PubMed |
spelling | pubmed-59160342018-09-25 A Mathematical Model for Predicting Obesity Transmission With Both Genetic and Nongenetic Heredity Ejima, Keisuke Thomas, Diana Allison, David B. Obesity (Silver Spring) Article OBJECTIVE: Obesity is transmissible across generations through both genetic and nongenetic routes, but distinguishing between these factors is challenging. We aimed to quantitatively study the contribution of these genetic and nongenetic effects to assess their influence on obesity prevalence. METHODS: We proposed a mathematical model that incorporated both genetic and nongenetic effects of obesity. Model parameters were estimated by using observational data. Model simulations were used to assess the sensitivity of model parameters. To strengthen our approach, we also performed the parameter estimation and simulation using data from the UK. RESULTS: Individuals homozygous for a ‘hypothetical obesogenic gene’ are suggested to be more susceptible to both social contagious risk and spontaneous weight gain risk. The model predicted that obesity prevalence reaches 41.03% (39.28, 44.31) and 26.77% (25.62, 28.06) at 2030 in the US and UK, respectively. The social contagious risk factor had a greater overall impact on the distribution of the population with obesity than did spontaneous weight gain risk or mother-to-child obesity transmission risk. CONCLUSIONS: Although the proposed “first approximation” model captured the complex interactions between the genetic and nongenetic effects on obesity, this framework remains incomplete. Future work should incorporate other key features driving the obesity epidemic. 2018-03-25 2018-05 /pmc/articles/PMC5916034/ /pubmed/29575611 http://dx.doi.org/10.1002/oby.22135 Text en http://www.nature.com/authors/editorial_policies/license.html#terms Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use:http://www.nature.com/authors/editorial_policies/license.html#terms |
spellingShingle | Article Ejima, Keisuke Thomas, Diana Allison, David B. A Mathematical Model for Predicting Obesity Transmission With Both Genetic and Nongenetic Heredity |
title | A Mathematical Model for Predicting Obesity Transmission With Both Genetic and Nongenetic Heredity |
title_full | A Mathematical Model for Predicting Obesity Transmission With Both Genetic and Nongenetic Heredity |
title_fullStr | A Mathematical Model for Predicting Obesity Transmission With Both Genetic and Nongenetic Heredity |
title_full_unstemmed | A Mathematical Model for Predicting Obesity Transmission With Both Genetic and Nongenetic Heredity |
title_short | A Mathematical Model for Predicting Obesity Transmission With Both Genetic and Nongenetic Heredity |
title_sort | mathematical model for predicting obesity transmission with both genetic and nongenetic heredity |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5916034/ https://www.ncbi.nlm.nih.gov/pubmed/29575611 http://dx.doi.org/10.1002/oby.22135 |
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