Evidence map›Paper›PMID 32138664›Full record

ArticleBMC cardiovascular disorders2020

Different adiposity indices and their associations with hypertension among Chinese population from Jiangxi province.

Lihua Hu, Guiping Hu, Xiao Huang, Wei Zhou, Chunjiao You, Juxiang Li, Ping Li, Yanqing Wu, Qinghua Wu, Zengwu Wang and 3 more

Open access · goldAbstract readComparative Study
In one paragraph

Article in BMC cardiovascular disorders, 2020. 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
3.0field-weighted citation impact, top 7% 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, 27 citations in OpenAlex.

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  14. Anthropometric, Bioelectric, and Visceral Fat Indices to Predict Hypertension in Rural Rohtak, Haryana.Indian journal of community medicine : official publication of Indian Association of Preventive & Social Medicine
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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

13 authors at 3 institutions in 1 country.

Lihua HuDepartment of Cardiovascular Medicine, the Second Affiliated Hospital of Nanchang University, No. 1 Minde Road, Nanchang of Jiangxi, 330006, China.
Guiping HuSchool of Medical Science and Engineering, Beihang University, Beijing, China.
Xiao HuangDepartment of Cardiovascular Medicine, the Second Affiliated Hospital of Nanchang University, No. 1 Minde Road, Nanchang of Jiangxi, 330006, China.
Wei ZhouCenter for Prevention and Treatment of Cardiovascular Diseases, the Second Affiliated Hospital of Nanchang University, Nanchang of Jiangxi, China.
Chunjiao YouDepartment of Cardiovascular Medicine, the Second Affiliated Hospital of Nanchang University, No. 1 Minde Road, Nanchang of Jiangxi, 330006, China.
Juxiang LiDepartment of Cardiovascular Medicine, the Second Affiliated Hospital of Nanchang University, No. 1 Minde Road, Nanchang of Jiangxi, 330006, China.
Ping LiDepartment of Cardiovascular Medicine, the Second Affiliated Hospital of Nanchang University, No. 1 Minde Road, Nanchang of Jiangxi, 330006, China.
Yanqing WuDepartment of Cardiovascular Medicine, the Second Affiliated Hospital of Nanchang University, No. 1 Minde Road, Nanchang of Jiangxi, 330006, China.
Qinghua WuDepartment of Cardiovascular Medicine, the Second Affiliated Hospital of Nanchang University, No. 1 Minde Road, Nanchang of Jiangxi, 330006, China.
Zengwu WangDivision of Prevention and Community Health, National Center for Cardiovascular Disease, Fuwai Hospital, Peking Union Medical College & Chinese Academy of Medical Sciences, Beijing, China.
Runlin GaoFuwai Hospital, Peking Union Medical College & Chinese Academy of Medical Sciences, Beijing, China.
Huihui BaoDepartment of Cardiovascular Medicine, the Second Affiliated Hospital of Nanchang University, No. 1 Minde Road, Nanchang of Jiangxi, 330006, China. huihui_bao77@126.com.
Xiaoshu ChengDepartment of Cardiovascular Medicine, the Second Affiliated Hospital of Nanchang University, No. 1 Minde Road, Nanchang of Jiangxi, 330006, China. xiaoshumenfan126@163.com.ORCID 0000-0001-7445-1988
Nanchang University · CNChinese Academy of Medical Sciences & Peking Union Medical College · CNBeihang University · CN

Funding

National Key R&D Program in the Twelfth Five-year Plan from the Chinese Ministry of Science and Technology 2011BAI11B01, 2014ZX09303305National Natural Science Foundation of China 81560051Science and Technology project of Health Planning Commission in Jiangxi Province 2016YNQN12034
6 · The paper itself

Abstract

backgroundTo date, the best adiposity index that predicts or associates strongly with hypertension remains controversial. Therefore, we aimed to compare the performance of different adiposity indices [BMI (body mass index), WC (waist circumference), WHtR (waist-to-height ratio), ABSI (a body shape index), VAI (visceral adipose index), BFP (body fat percentage)] as associates and potential predictors of risk of hypertension among Chinese population.

methodsA cross-sectional survey was conducted in Jiangxi province, China from 2013 to 2014. A total of 14,573 participants were included in the study. The physical measurements included body height, weight, WC, BFP and VAI. Multivariate logistic regression analysis was performed to assess the associations between different adiposity indices and the prevalence of hypertension. Receiver operating characteristic (ROC) analysis was also performed.

resultsAll adiposity indices were independently and positively associated with the prevalence of hypertension in a dose response fashion. The area under the curves (AUCs) for WHtR, BFP and VAI were significantly larger than those for other adiposity indices in both males and females (all P < 0.01). For males, no statistically significant difference was found in AUCs among WHtR and BFP (0.653 vs. 0.647, P = 0.4774). The AUC of WHtR was significantly higher than VAI (0.653 vs. 0.636, P < 0.01). For females, the AUCs demonstrated that WHtR was significantly more powerful than BFP and VAI (both P < 0.05) for predicting hypertension [WHtR, 0.689 (0.677-0.702); BFP, 0.677 (0.664-0.690); VAI, 0.668 (0.655-0.680)]. Whereas no significant differences were found in AUCs for hypertension among BFP and VAI in both sexes (all P > 0.1). The AUCs for hypertension associated with each adiposity index declined with age in both males and females. For subjects aged < 65 years, WHtR still had the largest AUC. However, for participants aged ≥65 years, BMI had the largest AUC.

conclusionThe findings indicated that WHtR was the best for predicting hypertension, followed by BFP and VAI, especially in younger population.

Indexed as

AdiposityBlood PressureWaist-Height RatioAdultAgedAsian PeopleBody Mass IndexChinaCross-Sectional StudiesFemaleHumansHypertensionIntra-Abdominal FatMaleMiddle AgedObesityBody fat percentageHypertensionReceiver operating characteristic curveVisceral adipose indexWaist-to-height ratio

Identifiers

PMID32138664
PMCPMC7059680
OpenAlexW3010768226

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Registered trials

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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.