Evidence map›Paper›PMID 31375086›Full record

ArticleBMC public health2019

Association between anthropometric indicators of obesity and cardiovascular risk factors among adults in Shanghai, China.

Yue Zhang, Yi'an Gu, Na Wang, Qi Zhao, Nawi Ng, Ruiping Wang, Xiaoyan Zhou, Yonggen Jiang, Weibing Wang, Genming Zhao

Open access · goldAbstract read
In one paragraph

Article in BMC public health, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed
6.9field-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

26 citing papers in PubMed, 50 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Development of Data Mining Algorithms for Identifying the Best Anthropometric Predictors for Cardiovascular Disease: MASHAD Cohort Study.High blood pressure & cardiovascular prevention : the official journal of the Italian Society of Hypertension · 2023
    Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article
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

10 authors at 4 institutions in 4 countries.

Yue ZhangDepartment of Epidemiology, School of Public Health, Key Laboratory of Public Health Safety of Ministry of Education, Fudan University, 138 Yi Xue Yuan Road, Shanghai, 200032, China.
Yi'an GuDepartment of Epidemiology, Columbia University, New York, USA.
Na WangDepartment of Epidemiology, School of Public Health, Key Laboratory of Public Health Safety of Ministry of Education, Fudan University, 138 Yi Xue Yuan Road, Shanghai, 200032, China.
Qi ZhaoDepartment of Epidemiology, School of Public Health, Key Laboratory of Public Health Safety of Ministry of Education, Fudan University, 138 Yi Xue Yuan Road, Shanghai, 200032, China.
Nawi NgDepartment of Public Health and Clinical Medicine, Unit for Demography and Aging Research at Umeå University, Umeå, Sweden.
Ruiping WangSongjiang Disease Prevention and Control Center, Shanghai, 201600, China.
Xiaoyan ZhouDepartment of Epidemiology, School of Public Health, Key Laboratory of Public Health Safety of Ministry of Education, Fudan University, 138 Yi Xue Yuan Road, Shanghai, 200032, China.
Yonggen JiangSongjiang Disease Prevention and Control Center, Shanghai, 201600, China.
Weibing WangDepartment of Epidemiology, School of Public Health, Key Laboratory of Public Health Safety of Ministry of Education, Fudan University, 138 Yi Xue Yuan Road, Shanghai, 200032, China.
Genming ZhaoDepartment of Epidemiology, School of Public Health, Key Laboratory of Public Health Safety of Ministry of Education, Fudan University, 138 Yi Xue Yuan Road, Shanghai, 200032, China. gmzhao@shmu.edu.cn.ORCID http://orcid.org/0000-0002-9625-478X
Fudan University · CNSongjiang District Central Hospital · CNColumbia University · USUmeå University · SE

Funding

National Key R & D Program of China 2017 YFC 0907001
6 · The paper itself

Abstract

backgroundTo determine the optimal cut-off values and evaluate the associations of body mass index (BMI), waist circumference (WC) and waist-height ratio (WHtR) with cardiovascular disease (CVD) risk factors.

methodsA large-scale cross-sectional survey was conducted among 35,256 adults aged 20-74 years in Shanghai between June 2016 and December 2017. Receiver operating characteristic (ROC) analyses were conducted to assess the optimal cut-off anthropometric indices of CVD risk factors including hypertension, diabetes, dyslipidemia and hyperuricemia. Multivariate Logistic regression models were preformed to evaluate the odds ratio of CVD risk factors.

resultsThe area under the curve (AUC) of WHtR was significantly greater than that of BMI or WC in the prediction of hypertension and diabetes, and AUCs were higher in women than men. The optimal cut-off values of WHtR were approximately 0.51 in both sexes, while the cut-off values of BMI and WC were higher for men compared with women. The optimal cutoff values of BMI and WC varied greatly across different age groups, but the difference in WHtR was relatively slight. Among women, the optimal threshold of anthropometric indices appeared to increase with age for hypertension and diabetes. The odds ratio between anthropometric indices and CVD risk factors were attenuated with age. WHtR had the greatest odds ratio for CVD risk factors among adults under 60 years old except for women with hypertension, while among 60-74 years, BMI yielded the greatest odds ratio in terms of all CVD outcomes except for women with diabetes.

conclusionsWHtR had the best performance for discriminating hypertension and diabetes and potentially be served as a standard screening tool in public health. The associations between three anthropometric indices and CVD risk factors differed by sex and decreased with age. These findings indicated a need to develop age- and gender-specific difference and make effective strategies for primary prevention of CVDs.

Indexed as

Body Mass IndexWaist CircumferenceWaist-Height RatioAdultAgedCardiovascular DiseasesChinaCross-Sectional StudiesFemaleHumansMaleMiddle AgedObesityReference ValuesRisk FactorsYoung AdultAnthropometric indicesCardiovascular diseasesObesityRisk factors

Identifiers

PMID31375086
PMCPMC6679475
OpenAlexW2964475002

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.