Evidence map›Paper›PMID 25479101›Full record

ArticlePloS one2014

Human growth and body weight dynamics: an integrative systems model.

Hazhir Rahmandad

Abstract read
In one paragraph

Article in PloS one, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

0numbers the graph read from it
0cells of the map it votes in
20citing 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

20 citing papers in PubMed.

  1. Review
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  17. Dynamics of Implementation and Maintenance of Organizational Health Interventions.International journal of environmental research and public health · 2017
    Article
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  20. Review
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

1 author.

Hazhir RahmandadIndustrial and Systems Engineering Department, Virginia Tech, Falls Church, Virginia, United States of America; Sloan School of Management, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States of America.

Funding

Dynamics of Obesity Intervention Adoption, Implementation and MaintenanceR21HL113680 · NHLBI · VIRGINIA POLYTECHNIC INST AND ST UNIV · PI RAHMANDAD, HAZHIR · 2012 to 2013
$419k
NHLBI NIH HHS 1R21HL113680-01NHLBI NIH HHS R21 HL113680NLM NIH HHS HHSN276201000004C
6 · The paper itself

Abstract

Quantifying human weight and height dynamics due to growth, aging, and energy balance can inform clinical practice and policy analysis. This paper presents the first mechanism-based model spanning full individual life and capturing changes in body weight, composition and height. Integrating previous empirical and modeling findings and validated against several additional empirical studies, the model replicates key trends in human growth including A) Changes in energy requirements from birth to old ages. B) Short and long-term dynamics of body weight and composition. C) Stunted growth with chronic malnutrition and potential for catch up growth. From obesity policy analysis to treating malnutrition and tracking growth trajectories, the model can address diverse policy questions. For example I find that even without further rise in obesity, the gap between healthy and actual Body Mass Indexes (BMIs) has embedded, for different population groups, a surplus of 14%-24% in energy intake which will be a source of significant inertia in obesity trends. In another analysis, energy deficit percentage needed to reduce BMI by one unit is found to be relatively constant across ages. Accompanying documented and freely available simulation model facilitates diverse applications customized to different sub-populations.

Indexed as

Body HeightBody WeightModels, BiologicalAdultAgingBirth WeightBody CompositionBody Mass IndexChild, PreschoolEnergy IntakeFemaleGrowth DisordersHumansInfant, NewbornMaleMalnutrition

Identifiers

PMID25479101
PMCPMC4257729

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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 OpenQuestion graph.