Evidence map›Paper›PMID 30116743›Full record

ArticleJournal of diabetes research2018

Predicting Type 2 Diabetes Mellitus Occurrence Using Three-Dimensional Anthropometric Body Surface Scanning Measurements: A Prospective Cohort Study.

Ming-Kuo Ting, Pei-Ju Liao, I-Wen Wu, Shuo-Wei Chen, Ning-I Yang, Tzu-Yu Lin, Kuang-Hung Hsu

Open access · goldAbstract read
In one paragraph

Article in Journal of diabetes research, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
1.1field-weighted citation impact, top 23% of its field
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

13 citing papers in PubMed, 19 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. 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

7 authors at 3 institutions in 1 country.

Ming-Kuo TingDivision of Endocrinology and Metabolism, Chang Gung Memorial Hospital, Keelung, Taiwan.
Pei-Ju LiaoDepartment of Health Care Administration, Oriental Institute of Technology, New Taipei City, Taiwan.
I-Wen WuDivision of Nephrology, Chang Gung Memorial Hospital, Keelung, Taiwan.ORCID 0000-0001-8535-3582
Shuo-Wei ChenDivision of Gastroenterology and Hepatology, Chang Gung Memorial Hospital, Keelung, Taiwan.
Ning-I YangDivision of Cardiology, Chang Gung Memorial Hospital, Keelung, Taiwan.
Tzu-Yu LinHealthy Aging Research Center, Chang Gung University, Taoyuan, Taiwan.
Kuang-Hung HsuHealthy Aging Research Center, Chang Gung University, Taoyuan, Taiwan.ORCID 0000-0003-2642-7689
Keelung Chang Gung Memorial Hospital · TWChang Gung University · TWAsia Eastern University of Science and Technology · TW

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAn accurate and comprehensive anthropometric measure for predicting type 2 diabetes mellitus (T2DM) has not yet been depicted.

methodsA total of 8450 nondiabetic participants were recruited during 2000-2010 in Taiwan. The cohort was followed up to the end of 2013, over an average of 8.87 years. At recruitment, participants completed a questionnaire related to basic demographics, lifestyle variables, personal disease history, and family disease history. 3D body surface scanning was used to obtain 35 anatomical measurements. A Cox proportional hazard model was used to conduct multivariable analyses.

resultsA total of 2068 T2DM cases at an incidence rate of 27.59 × 10

conclusionsThis study suggests that as well as using traditional waist and TC measurements, NC can be used as an indicator to provide an early prediction of developing T2DM, while providing clues for future mechanistic investigations of T2DM.

Indexed as

AnthropometryBody Mass IndexAdolescentAdultAgedAged, 80 and overDiabetes Mellitus, Type 2FemaleFollow-Up StudiesHumansMaleMiddle AgedObesityProportional Hazards ModelsProspective StudiesRisk Factors

Identifiers

PMID30116743
PMCPMC6079414
OpenAlexW2829959232

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.