Evidence map›Paper›PMID 28407795›Full record

ArticleBMC public health2017

The association between self-rated health and different anthropometric and body composition measures in the Chinese population.

Kun Tang, Yingxi Zhao, Chunyan Li

Open access · goldAbstract read
In one paragraph

Article in BMC public health, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
4.1field-weighted citation impact, top 6% 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

11 citing papers in PubMed, 16 citations in OpenAlex.

  1. Obesity and self-rated health in middle-aged Danes.International journal of obesity (2005) · 2026
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  10. The Relationship between Lifestyle Factors and Body Compositionin Young Adults.International journal of environmental research and public health · 2017
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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

3 authors at 1 institution in 1 country.

Kun TangDepartment of Global Health, Peking University, Beijing, China. tangkun@hsc.pku.edu.cn.
Yingxi ZhaoInstitute for Medical Humanities, Peking University, Beijing, China.
Chunyan LiSchool of Public Health, Peking University, Beijing, China.
Peking University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTo analyze the strength of association between self-rated health and six anthropometric and body composition measures to explore the best indicator.

methodsAnalyses were based on the cross-sectional data from the China Kadoorie Biobank Study and approximately 300,000 adults were analyzed. Logistics regression was used to analyze the association between self-rated health (good or poor) and anthropometric and body composition measures (height, weight, body mass index (BMI), waist circumference (WC), hip circumference (HC) and body fat percentage, waist-to-hip ratio and waist-to-height ratio). Stratified analyses were undertaken to understand the effect modification of socioeconomic status on the association.

resultOdds ratio of self-rated better health had an inverted U-shape association with weight, BMI, WC and body fat, with weight levels increasing until around 73.8 and 65.7 kg for male and female, BMI around 26.8 kg/m

conclusionsBeing underweight and overweight are both risk factors for poor self-rated health in males and females, and weight is the best indicator of self-rated health compared with other measures.

Indexed as

Body CompositionDiagnostic Self EvaluationAdultAgedAnthropometryBody WeightChinaCross-Sectional StudiesFemaleHumansMaleMiddle AgedOverweightReproducibility of ResultsRisk FactorsSocioeconomic FactorsBMIChineseObesitySelf-rated HealthWaist Circumference

Identifiers

PMID28407795
PMCPMC5390392
OpenAlexW2605652152

What OpenQuestion holds

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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.