Evidence map›Paper›PMID 40811451›Full record

ArticlePloS one2025

Omnipresent intercorrelations of metabolic syndrome markers in the general population.

Marina Sanchez Rico, Emmanuel Wiernik, Sofiane Kab, Adeline Renuy, Nicolas Hoertel, Joël Ménard, Marcel Goldberg, Marie Zins, Pierre Meneton

Abstract read
In one paragraph

Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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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

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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

9 authors.

Marina Sanchez RicoAP-HP, DMU Psychiatrie et Addictologie, Hôpital Corentin-Celton, Issy-les-Moulineaux, France.
Emmanuel WiernikUniversité Paris Cité, Université Paris-Saclay, Université de Versailles Saint-Quentin-en-Yvelines, INSERM UMS_011, Villejuif, France.
Sofiane KabUniversité Paris Cité, Université Paris-Saclay, Université de Versailles Saint-Quentin-en-Yvelines, INSERM UMS_011, Villejuif, France.
Adeline RenuyUniversité Paris Cité, Université Paris-Saclay, Université de Versailles Saint-Quentin-en-Yvelines, INSERM UMS_011, Villejuif, France.
Nicolas HoertelAP-HP, DMU Psychiatrie et Addictologie, Hôpital Corentin-Celton, Issy-les-Moulineaux, France.
Joël MénardFaculté de Médecine, Université Paris Cité, Paris, France.
Marcel GoldbergUniversité Paris Cité, Université Paris-Saclay, Université de Versailles Saint-Quentin-en-Yvelines, INSERM UMS_011, Villejuif, France.ORCID https://orcid.org/0000-0002-6161-5880
Marie ZinsUniversité Paris Cité, Université Paris-Saclay, Université de Versailles Saint-Quentin-en-Yvelines, INSERM UMS_011, Villejuif, France.ORCID https://orcid.org/0000-0002-4540-4282
Pierre MenetonINSERM UMR_1142, Sorbonne Université, Université Paris 13, Paris, France.ORCID https://orcid.org/0000-0003-4611-1892

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundBesides the usual characterization of metabolic syndrome as a cluster of markers arbitrarily defined by thresholds, it is unclear to which extent these markers as continuous traits are correlated with each other in the general population. The present study aimed to explore these correlations across a wide array of biological, social and behavioral characteristics.

methodsThe cross-sectional analyses were performed in a large population-based French cohort (CONSTANCES) of 159,476 adults in whom blood glucose, low-density lipoproteins (LDL) and high-density lipoproteins (HDL), triglycerides, body mass index, waist and hip circumferences, systolic and diastolic blood pressures were measured at the time of recruitment between 2012 and 2021. Correlations between each pair of continuous marker distributions were assessed by calculating raw and partial correlation coefficients (r).

resultsThe same pattern of partial correlations is observed with little variation in all groups of sex, age, individual and parental histories of cardiovascular disease, diagnosis of metabolic syndrome, social position, work environment, lifetime unemployment exposure, smoking, non-moderate alcohol consumption, leisure-time physical inactivity and diet quality. This pattern is composed of strong and expected intercorrelations between systolic and diastolic blood pressures (r ranging from 0.62 to 0.74), between body mass index and waist (r from 0.50 to 0.63) and hip (r from 0.58 to 0.70) circumferences and between waist and hip circumferences (r from 0.07 to 0.19). It also includes intercorrelations of systolic blood pressure with waist (r from 0.10 to 0.21) and hip (r from -0.07 to -0.12) circumferences and with blood glucose (r from 0.09 to 0.15), those of triglycerides with blood glucose (r from 0.07 to 0.16), LDL (r from 0.24 to 0.33), HDL (r from -0.20 to -0.29) and waist circumference (r from 0.07 to 0.15), and finally those of waist and hip circumferences with blood glucose (r from 0.09 to 0.17 and from -0.08 to -0.13) and HDL (r from -0.12 to -0.24 and from 0.08 to 0.18).

conclusionsThese results show that metabolic syndrome markers are correlated with each other whatever the biological, social or behavioral characteristics of individuals. They suggest that it makes sense to systematically consider these markers all together rather than separately in terms of etiology, prevention and treatment of metabolic diseases and cardiovascular risk in the general population.

Indexed as

BiomarkersMetabolic SyndromeAdultAgedBlood GlucoseBlood PressureBody Mass IndexCross-Sectional StudiesFemaleFranceHumansLipoproteins, HDLLipoproteins, LDLMaleMiddle AgedTriglyceridesBiomarkersBlood GlucoseLipoproteins, HDLLipoproteins, LDLTriglycerides

Identifiers

PMID40811451
PMCPMC12352674

What Socratic holds

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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 Socratic graph.