Evidence map›Paper›PMID 36686484›Full record

ArticleFrontiers in endocrinology2022

Assessing temporal differences of baseline body mass index, waist circumference, and waist-height ratio in predicting future diabetes.

Guotai Sheng, Jiajun Qiu, Maobin Kuang, Nan Peng, Guobo Xie, Yuanqin Chen, Shuhua Zhang, Yang Zou

Open access · goldAbstract read
In one paragraph

Article in Frontiers in endocrinology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
3.6field-weighted citation impact, top 6% 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

14 citing papers in PubMed, 18 citations in OpenAlex.

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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

8 authors at 3 institutions in 1 country.

Guotai ShengJiangxi Provincial Geriatric Hospital, Jiangxi Provincial People's Hospital, Medical College of Nanchang University, Nanchang, Jiangxi, China.
Jiajun QiuJiangxi Provincial Geriatric Hospital, Jiangxi Provincial People's Hospital, Medical College of Nanchang University, Nanchang, Jiangxi, China.
Maobin KuangJiangxi Provincial Geriatric Hospital, Jiangxi Provincial People's Hospital, Medical College of Nanchang University, Nanchang, Jiangxi, China.
Nan PengJiangxi Provincial Geriatric Hospital, Jiangxi Provincial People's Hospital, Medical College of Nanchang University, Nanchang, Jiangxi, China.
Guobo XieJiangxi Provincial Geriatric Hospital, Jiangxi Provincial People's Hospital, Medical College of Nanchang University, Nanchang, Jiangxi, China.
Yuanqin ChenJiangxi Provincial Geriatric Hospital, Jiangxi Provincial People's Hospital, Medical College of Nanchang University, Nanchang, Jiangxi, China.
Shuhua ZhangJiangxi Cardiovascular Research Institute, Jiangxi Provincial People's Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, Jiangxi, China.
Yang ZouJiangxi Cardiovascular Research Institute, Jiangxi Provincial People's Hospital, The First Affiliated Hospital of Nanchang Medical College, Nanchang, Jiangxi, China.
Nanchang University · CNFirst Affiliated Hospital of Jiangxi Medical College · CNJiangxi Provincial People's Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Obesity is the prominent modifiable risk factor known to influence the occurrence and progression of diabetes other than age, and the objective of this study was to evaluate and compare the predictive value of three simple baseline anthropometric indicators of obesity, body mass index (BMI), waist circumference (WC), and waist-height ratio (WHtR), for the occurrence of diabetes at different time points in the future. Methods: The study subjects were 12,823 individuals with normoglycemic at baseline who underwent health screening and had measurements of BMI, WC, and WHtR. The outcome of interest was new-onset diabetes during follow-up. Time-dependent receiver operator characteristics (ROC) curves of baseline BMI, WC, and WHtR for predicting the risk of diabetes in the next 2 to 12 years were constructed and their area under the ROC curves (AUCs) and corresponding optimal threshold values were calculated for each time point, which were used to compare the accuracy and stability of the above three indicators for predicting the occurrence of diabetes in different future periods. Results: During a median follow-up period of 7.02 years, with a maximum follow-up of 13 years, 320 new-onset diabetes were recorded. After adjusting for confounders and comparing standardized hazard ratios (HRs), WC was shown to be the best simple anthropometric indicator of obesity reflecting diabetes risk in all models, followed by WHtR. Time-dependent ROC analysis showed that WC had the highest AUC in predicting the occurrence of diabetes in the short term (2-5 years), and WHtR had the highest AUC in predicting the occurrence of diabetes in the medium to long term (6-12 years), while in any time point, both WC and WHtR had higher AUC than BMI in predicting future diabetes. In addition, we found relatively larger fluctuations in the thresholds of BMI and WC for predicting diabetes over time, while the thresholds of WHtR consistently remained between 0.47-0.50; comparatively speaking, WHtR may have greater application value in predicting future diabetes. Conclusions: Our analysis sustained that central obesity is a more important predictor of diabetes, and in clinical practice, we proposed measuring WHtR as a useful tool for predicting future diabetes.

Indexed as

Diabetes MellitusWaist-Height RatioBody Mass IndexHumansObesityROC CurveWaist CircumferenceBMIcentral obesitydiabetestime-dependent ROCwaist circumferencewaist-height ratio

Identifiers

PMID36686484
PMCPMC9852880
OpenAlexW4313595830

What Socratic holds

Textmetadata
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 Socratic graph.