Evidence map›Paper›PMID 37865773›Full record

ArticleBMC cardiovascular disorders2023

Association of adiposity indices with cardiometabolic multimorbidity among 101,973 chinese adults: a cross-sectional study.

Xiaoru Qin, Chaolei Chen, Jiabin Wang, Anping Cai, Xiaoxuan Feng, Xiaofei Jiang, Yingqing Feng

Open access · goldAbstract read
In one paragraph

Article in BMC cardiovascular disorders, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed, 2 pooled it
7.3field-weighted citation impact, top 2% 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

24 citing papers in PubMed, 2 syntheses or guidelines pooled it, 34 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

7 authors at 3 institutions in 1 country.

Xiaoru QinDepartment of Cardiology, Zhuhai hospital affiliated with Jinan University (Zhuhai People's Hospital), Zhuhai, China.
Chaolei ChenDepartment of cardiology, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, China.
Jiabin WangGlobal Health Research Center, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China.
Anping CaiDepartment of cardiology, Guangdong Cardiovascular Institute, Guangdong Provincial People's Hospital, Guangdong Academy of Medical Sciences, Southern Medical University, Guangzhou, China.
Xiaoxuan FengGuangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China.
Xiaofei JiangDepartment of Cardiology, Zhuhai People's Hospital (Zhuhai hospital affiliated with Jinan University), Zhuhai, China.
Yingqing FengDepartment of Cardiology, Zhuhai hospital affiliated with Jinan University (Zhuhai People's Hospital), Zhuhai, China. fengyingqing@gdph.org.cn.
Southern Medical University · CNGuangdong Academy of Medical Sciences · CNZhuhai People's Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCardiometabolic multimorbidity (CMM) and obesity represent two major health problems. The relationship between adiposity indices and CMM, however, remains understudied. This study aimed to investigate the associations of body mass index (BMI), waist circumference (WC), waist-to-height ratio (WHtR), a body shape index (ABSI), body roundness index (BRI), and conicity index (CI) with CMM among Chinese adults.

methodsData of 101,973 participants were collected from a population-based screening project in Southern China. CMM was defined as having two or more of the following diseases: coronary heart disease, stroke, hypertension, and diabetes. The relationship between the six adiposity indices and CMM was investigated by multivariate logistic regression and restricted cubic splines. Receiver operator characteristic curve, C-statistic and net reclassification index were used to estimate the discriminative and incremental values of adiposity indices on CMM.

resultsLogistic regression models showed the six adiposity indices were all significantly associated with the odds of CMM with non-linear relationships. For per SD increment, WC (Odds ratio [OR]: 1.66; 95% confidence interval (CI): 1.62-1.70) and WHtR (OR, 1.61; 95% CI, 1.58-1.65) were more significantly associated with a higher prevalence of CMM than BMI (OR, 1.55; 95% CI, 1.52-1.58) (all P < 0.05). In addition, WC, WHtR, and BRI displayed significantly better performance in detecting CMM compared with BMI (all P < 0.05). Their respective area under the curve (AUC) values were 0.675 (95% CI: 0.670-0.680), 0.679 (95% CI: 0.675-0.684), and 0.679 (95% CI: 0.675-0.684), while BMI yielded an AUC of 0.637 (95% CI: 0.632-0.643). These findings hold true across all subgroups based on sex and age. When Adding WC, WHtR, or BRI to a base model, they all provided larger incremental values for the discrimination of CMM compared with BMI (all P < 0.05).

conclusionsAdiposity indices were closely associated with the odds of CMM, with WC and WHtR demonstrating stronger associations than BMI. WC, WHtR, and BRI were superior to BMI in discriminative ability for CMM. Avoidance of obesity (especially abdominal obesity) may be the preferred primary prevention strategy for CMM while controlling for other major CMM risk factors.

Indexed as

AdiposityHypertensionAdultBody Mass IndexCardiometabolic Risk FactorsChinaCross-Sectional StudiesEast Asian PeopleHumansMultimorbidityObesityRisk FactorsWaist CircumferenceWaist-Height RatioAdiposity indicesCardiometabolic multimorbidityObesity

Identifiers

PMID37865773
PMCPMC10590510
OpenAlexW4387843702

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.