Evidence map›Paper›PMID 30508913›Full record

SynthesisMedicine2018

Associations of anthropometric adiposity indexes with hypertension risk: A systematic review and meta-analysis including PURE-China.

Guijuan Deng, Lu Yin, Weida Liu, Xiaoyun Liu, Quanyong Xiang, Zhenzhen Qian, Juntao Ma, Hui Chen, Yang Wang, Bo Hu and 3 more

Open access · goldAbstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in Medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
33citing papers in PubMed, 3 pooled it
6.4field-weighted citation impact, top 3% 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

33 citing papers in PubMed, 3 syntheses or guidelines pooled it, 56 citations in OpenAlex.

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  8. Association between anthropometric indices and 5-year hypertension incidence in the general Japanese population.Hypertension research : official journal of the Japanese Society of Hypertension · 2024
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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 5 institutions in 4 countries.

Guijuan DengState Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases.
Lu YinState Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases.
Weida LiuState Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases.
Xiaoyun LiuState Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases.
Quanyong XiangJiangsu Province Center for Disease Control & Prevention.
Zhenzhen QianJiangxinzhou Community Health Service Center, Nanjing.
Juntao MaAcademy of Military Sciences, People's Liberation Army of China, Beijing, China.
Hui ChenState Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases.
Yang WangState Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases.
Bo HuState Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases.
Wei LiState Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases.
Yu JiangSchool of Public Health, Peking Union Medical College & Chinese Academy of Medical Sciences, Beijing.
China Investigator team
Fu Wai Hospital · CNState Key Laboratory of Cardiovascular DiseaseCommunity Health Center · USJiangsu Provincial Center for Disease Control and Prevention · CNPeking Union Medical College Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND AND

objectiveThe association between hypertension and obesity has been confirmed, while no agreement has been reached about which anthropometric adiposity index is the best. This meta-analysis aimed to perform a systematic review and meta-analysis on the associations of hypertension risk with body mass index (BMI), waist circumstance (WC), waist-to-hip ratio (WHR), and waist-to-height ratio (WHtR), and a prospective urban and rural epidemiology study from China (PURE-China) was added into this meta-analysis as an individual study.

methodsSystematic literature searching was conducted to identify relevant articles published up to September 2018 in CNKI, WANFANG Data, Web of Science, SinoMed, PubMed, MEDLINE, EMBASE, Cochrane Library and cross-referencing. Literature reporting the association of hypertension risk with BMI, WC, WHR, and WHtR were defined as eligible. PURE-China data were analyzed and included as 1 eligible study into meta-analyses. Summary odds ratio (OR) and area under receiver operating characteristic curve (AUC) were pooled using meta-analysis methods. Heterogeneity and publication bias were evaluated. Subgroups based on gender, country and study design were conducted as well.

resultsThirty-eight original articles including PURE-China were included into meta-analyses, involving 309,585 subjects. WHtR had the strongest association with hypertension risk (OR, 1.68; 95% confidence interval, [CI]:1.29-2.19) and prediction ability (AUC, 70.9%; 95% CI: 67.8%-74.2%), which were also confirmed in subgroup analyses based on gender and country. However, BMI was found to have the highest prediction ability in adjusted models of PURE-China and followed WC, both of which were superior to WHtR (73.7% and 73.4% vs 73.2%).

conclusionsOur overall meta-analysis further confirmed WHtR as a good indicator at discriminating those individuals at increased risk of hypertension, and in some cases, it is better than BMI, WC, and WHR.

Indexed as

AdiposityHumansHypertensionRisk

Identifiers

PMID30508913
PMCPMC6283208
OpenAlexW2922663380

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.