Evidence map›Paper›PMID 29575611›Full record

ArticleObesity (Silver Spring, Md.)2018

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

Keisuke Ejima, Diana M Thomas, David B Allison

Abstract read
In one paragraph

Article in Obesity (Silver Spring, Md.), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Keisuke EjimaDepartment of Epidemiology and Biostatistics, School of Public Health, Indiana University, Bloomington, Indiana, USA.ORCID 0000-0002-1185-3987
Diana M ThomasDepartment of Mathematical Sciences, United States Military Academy, West Point, New York, USA.ORCID 0000-0003-2641-9304
David B AllisonDepartment of Epidemiology and Biostatistics, School of Public Health, Indiana University, Bloomington, Indiana, USA.

Funding

Why is the prevalence of obesity so high in U.S. Southern States? Regional predictors of BMI and obesity treatment response.P30DK056336 · NIDDK · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI BARBARA A GOWER · 2000 to 2026
$31.9M
The Mathematical Sciences in Obesity ResearchR25DK099080 · NIDDK · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI DAVID B ALLISON, Andrew W Brown · 2013 to 2026
$1.2M
NIDDK NIH HHS P30 DK056336NIDDK NIH HHS R25 DK099080
6 · The paper itself

Abstract

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.

Indexed as

Models, TheoreticalChildFemaleHeredityHumansMaleObesity

Identifiers

PMID29575611
PMCPMC5916034

What Socratic holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.