Evidence map›Paper›PMID 28632766›Full record

ArticlePloS one2017

Associations between anthropometric parameters and lipid profiles in Chinese individuals with age ≥40 years and BMI <28kg/m2.

Zhi Yang, Xun Ding, Jiang Liu, Peng Duan, Lian Si, Binghua Wan, Ping Tu

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
2.0field-weighted citation impact, top 13% 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

13 citing papers in PubMed, 24 citations in OpenAlex.

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  12. Epidemiological study of metabolic syndrome in Brazilian soldiers.Archives of endocrinology and metabolism · 2019
    Observational
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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

7 authors at 1 institution in 1 country.

Zhi YangNanchang Key Laboratory of Diabetes, The Third Hospital of Nanchang, Jiangxi Province, China.ORCID http://orcid.org/0000-0002-7116-4243
Xun DingNanchang Key Laboratory of Diabetes, The Third Hospital of Nanchang, Jiangxi Province, China.
Jiang LiuNanchang Key Laboratory of Diabetes, The Third Hospital of Nanchang, Jiangxi Province, China.
Peng DuanNanchang Key Laboratory of Diabetes, The Third Hospital of Nanchang, Jiangxi Province, China.
Lian SiNanchang Key Laboratory of Diabetes, The Third Hospital of Nanchang, Jiangxi Province, China.
Binghua WanNanchang Key Laboratory of Diabetes, The Third Hospital of Nanchang, Jiangxi Province, China.
Ping TuNanchang Key Laboratory of Diabetes, The Third Hospital of Nanchang, Jiangxi Province, China.
Third Hospital of Nanchang · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundLipid abnormalities are associated with overweight and obesity. Some simple anthropometric measurements such as body mass index (BMI), waist circumference (WC), waist-to-hip ratio (WHpR), and waist-to-height ratio (WHtR), may link to increased risk of dyslipidemia. However, diverse results were found in different population studies. We focused on the associations between these measurements and dyslipidemia in non-obese (BMI <28kg/m2) population aged more than 40 years. METHODS AND

findingsCross-sectional study of 4185 non-obese adults aged more than 40 years was conducted in Nanchang, Jiangxi province, China. Questionnaire, anthropometric and laboratory tests were conducted. The National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III) criteria were used to define high total cholesterol (TC), high low-density lipoprotein cholesterol (LDL-C), low high-density lipoprotein cholesterol (HDL-C), hypertriglyceridemia and dyslipidemia. The overall prevalence of high TC, high LDL-C, low HDL-C, hypercholesterolemia, hypertriglyceridemia and dyslipidemia were 15.68%, 27.98%, 20.12%, 44.01%, 21.98% and 49.06% respectively. Multiple logistic regressions showed only BMI (per quartile increment) increased risks for prevalent high LDL-C, low HDL-C, hypercholesterolemia, hypertriglyceridemia, and dyslipidemia. Regardless of sex, age and prevalent metabolic syndrome, increasing BMI was persistently independent risk factor for having low HDL-C, hypercholesterolemia and dyslipidemia, however was not associated with high TC.

conclusionsIn non-obese Chinese population aged more than 40 years, increasing BMI may better identify the prevalent dyslipidemia than other anthropometric measurements. However, due to the different meanings, both BMI and WC should be measured and monitored for metabolic risk assessment.

Indexed as

Body Mass IndexWaist CircumferenceAdultAgedAged, 80 and overChinaCross-Sectional StudiesFemaleHumansLipidsMaleMetabolic SyndromeMiddle AgedPrevalenceRisk FactorsLipids

Identifiers

PMID28632766
PMCPMC5478121
OpenAlexW2671932359

What OpenQuestion holds

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LicenceCC BY
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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.