A Mathematical Model for Predicting Obesity Transmission with Both Genetic and Nongenetic Heredity

作者：Ejima Keisuke^*; Thomas Diana M; Allison David B

来源：Obesity, 2018, 26(5): 927-933.

DOI：10.1002/oby.22135

ObjectiveObesity is transmissible across generations through both genetic and nongenetic routes, but distinguishing between these factors is challenging. This study aimed to quantitatively examine the contribution of these genetic and nongenetic effects to assess their influence on obesity prevalence.
MethodsA mathematical model was proposed that incorporated both the 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 the study's approach, parameter estimation and simulation using data from the United Kingdom were also performed.
ResultsIndividuals homozygous for a hypothetical obesogenic gene were suggested to be more susceptible to both socially contagious risk and spontaneous weight gain risk. The model predicted that obesity prevalence would reach 41.03% (39.28, 44.31) and 26.77% (25.62, 28.06) at 2030 in the United States and United Kingdom, respectively. The socially 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.
ConclusionsAlthough 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.

• 出版日期2018-5