Evidence map›Paper›PMID 25593147›Full record

ReviewAdvances in nutrition (Bethesda, Md.)2015

Applications of systems science in biomedical research regarding obesity and noncommunicable chronic diseases: opportunities, promise, and challenges.

Youfa Wang, Hong Xue, Shiyong Liu

Abstract readReview
In one paragraph

Review in Advances in nutrition (Bethesda, Md.), 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. Article
  5. Article
  6. Article
  7. Article
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.

Youfa WangDepartment of Epidemiology and Environmental Health, School of Public Health and Health Professions, University at Buffalo, State University of New York; Buffalo, NY; and youfawan@buffalo.edu.
Hong XueDepartment of Epidemiology and Environmental Health, School of Public Health and Health Professions, University at Buffalo, State University of New York; Buffalo, NY; and.
Shiyong LiuDepartment of Epidemiology and Environmental Health, School of Public Health and Health Professions, University at Buffalo, State University of New York; Buffalo, NY; and Research Institute of Economics and Management, Southwestern University of Finance and Economics, Chengdu, China.

Funding

MULTILEVEL SYSTEMS-ORIENTED CHILDHOOD OBESITY STUDY IN CHINAU54HD070725 · NICHD · JOHNS HOPKINS UNIVERSITY · PI GITTELSOHN, JOEL · 2011 to 2016
$15.9M
Causes and Interventions for Childhood Obesity:Innovative Systems AnalysisR01HD064685 · NICHD · STATE UNIVERSITY OF NEW YORK AT BUFFALO · PI WANG, YOUFA · 2010 to 2013
$1.2M
NICHD NIH HHS 1R01HD064685-01A1NICHD NIH HHS U54 HD070725
6 · The paper itself

Abstract

Interest in the application of systems science (SS) in biomedical research, particularly regarding obesity and noncommunicable chronic disease (NCD) research, has been growing rapidly over the past decade. SS is a broad term referring to a family of research approaches that include modeling. As an emerging approach being adopted in public health, SS focuses on the complex dynamic interaction between agents (e.g., people) and subsystems defined at different levels. SS provides a conceptual framework for interdisciplinary and transdisciplinary approaches that address complex problems. SS has unique advantages for studying obesity and NCD problems in comparison to the traditional analytic approaches. The application of SS in biomedical research dates back to the 1960s with the development of computing capacity and simulation software. In recent decades, SS has been applied to addressing the growing global obesity epidemic. There is growing appreciation and support for using SS in the public health field, with many promising opportunities. There are also many challenges and uncertainties, including methodologic, funding, and institutional barriers. Integrated efforts by stakeholders that address these challenges are critical for the successful application of SS in the future.

Indexed as

Chronic DiseaseModels, TheoreticalObesitySystems TheoryBiomedical ResearchHumansPublic HealthSciencechildinterventionmodelsnoncommunicable chronic diseasesobesitypolicysimulationsystems science

Identifiers

PMID25593147
PMCPMC4288284

What OpenQuestion holds

Textmetadata
Read underepoch 390

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.