Evidence map›Paper›PMID 29378513›Full record

ArticleBMC cardiovascular disorders2018

New anthropometric indices or old ones: which perform better in estimating cardiovascular risks in Chinese adults.

Fei Wang, Yintao Chen, Ye Chang, Guozhe Sun, Yingxian Sun

Abstract readComparative Study
In one paragraph

Article in BMC cardiovascular disorders, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 52 papers.

0numbers the graph read from it
0cells of the map it votes in
52citing 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

52 citing papers in PubMed.

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  17. Role of waist circumferenceZhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences · 2024
    Review
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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

5 authors.

Fei WangDepartment of Cardiology, Jinhua Municipal Central Hospital, 351 Mingyue Street, Wucheng District, Jinhua, 321000, People's Republic of China.
Yintao ChenDepartment of Cardiology, the First Affiliated Hospital of China Medical University, 155 Nanjing North Street, Heping District, Shenyang, 110001, People's Republic of China.
Ye ChangDepartment of Cardiology, the First Affiliated Hospital of China Medical University, 155 Nanjing North Street, Heping District, Shenyang, 110001, People's Republic of China.
Guozhe SunDepartment of Cardiology, the First Affiliated Hospital of China Medical University, 155 Nanjing North Street, Heping District, Shenyang, 110001, People's Republic of China.
Yingxian SunDepartment of Cardiology, the First Affiliated Hospital of China Medical University, 155 Nanjing North Street, Heping District, Shenyang, 110001, People's Republic of China. sunyingxiancmu@126.com.ORCID 0000-0003-2694-3392

Funding

the National Science and Technology Support Program of China 2012BAJ18B02
6 · The paper itself

Abstract

backgroundVarious anthropometric indices can be used to estimate obesity, and it is important to determine which one is the best in predicting the risk of coronary heart disease (CHD) and to define the optimal cut-off point for the best index.

methodsThis cross-sectional study investigated a consecutive sample of 11,247 adults, who had lived in rural areas of China and were older than 35 years of age. Eight obesity indices, including the body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHR), waist-to-height ratio (WHtR), abdominal volume index (AVI), body adiposity index (BAI), body roundness index (BRI) and a body shape index (ABSI) were investigated. The risk of CHD was evaluated by the 10-year coronary event risk (Framingham risk score). Receiver operating characteristic (ROC) curve analyses were used to evaluate the predictive ability of the obesity indices for CHD risk.

resultsOf the whole population, 3636 (32.32%) participants had a risk score higher than 10%. Those who suffered medium or high CHD risk were more likely to have higher mean anthropometric indices, except for BMI in males. In the multivariate-adjusted logistic regression, all these anthropometric measurements were statistically associated with CHD risk in males. After adjusting for all the possible confounders, these anthropometric measurements, except for ABSI, remained as independent indicators of CHD risk in females. According to the ROC analyses, ABSI provided the largest area under the curve (AUC) value in males, and BMI showed the lowest AUC value, with AUC varying from 0.52 to 0.60. WHtR and BRI provided the largest AUC value in female, and similarly, BMI showed the lowest AUC value, with AUC varying from 0.59 to 0.70. The optimal cut-off values were as follows: WHtR (females: 0.54), BRI (females: 4.21), and ABSI (males: 0.078).

conclusionsABSI was the best anthropometric index for estimating CHD risk in males, and WHtR and BRI were the best indicators in females. Males should maintain an ABSI of less than 0.078, and females should maintain a WHtR of less than 0.54 or a BRI of less than 4.21.

Indexed as

AdultAnthropometryArea Under CurveChinaChi-Square DistributionCoronary DiseaseCross-Sectional StudiesFemaleHumansLogistic ModelsMaleMiddle AgedMultivariate AnalysisObesityPredictive Value of TestsReproducibility of ResultsABSIAnthropometric parametersBRICHD riskWHtR

Identifiers

PMID29378513
PMCPMC5789564

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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.