Evidence map›Paper›PMID 26888218›Full record

ArticleBMC cardiovascular disorders2016

Multivariable analysis of total cholesterol levels in male Swiss Armed Forces conscripts 2006-2012 (N = 174,872).

Marcel Bruggisser, Dieter Burki, Martin Haeusler, Frank J Rühli, Kaspar Staub

Open access · goldAbstract read
In one paragraph

Article in BMC cardiovascular disorders, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
4.3field-weighted citation impact, top 7% 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

6 citing papers in PubMed, 8 citations in OpenAlex.

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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

5 authors at 2 institutions in 1 country.

Marcel BruggisserSwiss Armed Forces, Medical Service, Worblentalstrasse 36, Ittigen, CH-3063, Switzerland.
Dieter BurkiViollier AG, Hagmattstrasse 14, Allschwil, CH-4123, Switzerland.
Martin HaeuslerInstitute of Evolutionary Medicine, University of Zürich, Winterthurerstrasse 190, CH-8057, Zürich, Switzerland.
Frank J RühliInstitute of Evolutionary Medicine, University of Zürich, Winterthurerstrasse 190, CH-8057, Zürich, Switzerland.
Kaspar StaubInstitute of Evolutionary Medicine, University of Zürich, Winterthurerstrasse 190, CH-8057, Zürich, Switzerland. kaspar.staub@iem.uzh.ch.
University of Zurich · CHGivaudan (Switzerland) · CH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCholesterol is an important contributor to morbidity and mortality risks due to its association with obesity, cardiovascular disease, and cancer. A system of mandatory military conscription is a useful tool for disease-risk monitoring in a given male population. Swiss military conscription data are representative for more than 90% of a given male birth cohort (with Swiss citizenship). The medical examination also includes voluntary laboratory testing, for which approximately 65% of the young men present at conscription give consent.

methodsHere we present the temporal and subgroup analyses of total serum cholesterol levels (TCL) among Swiss conscripts from 2006 to 2012 (N = 174,872; mean age = 19.75 years). The voluntary blood samples were tested by a central laboratory (Viollier AG) with identical measurement standards and strict quality control. To test differences in TCL by socioeconomic occupational status, sports test performance, Body Mass Index (BMI), age, and place of residence of the conscripts we used a multivariable regression model with TCL as dependent variable.

resultsMean TCL decreased significantly, by 0.125 mmol/l (95% CI 0.108-0.142, p < 0.001) from 4.225 mmol/l (95% CI 4.210-4.240) in 2006 to 4.100 mmol/l (95% CI 4.091-4.109) in 2012. Similarly, the prevalence of conscripts with an elevated TCL ≥ 5.17 mmol/l decreased from ≥ 10.2% prior to 2011 to 6.9% in 2011 and 8.2% in 2012. Multivariate regression showed an association between elevated TCL and lower socioeconomic occupational status, lower sports test performance, higher BMI, higher age, and area of residence. There was no longer a significant increase in mean TCL among the three grades of obesity (BMI ≥ 30.0 kg/m2) as defined by the WHO. Within the BMI categories of normal weight and overweight, TCL was stratified by sports performance (better sports performance = lower TCL).

conclusionDecreasing TCL in 2011 and 2012 fits the known pattern of conscripted persons' stabilizing BMI and sports test performance of the conscripts in recent years. However, small temporal drifts within the laboratory analyses cannot be ruled out as confounding factors. In conclusion, identifying subgroups with unfavorable lipid profiles will contribute to the continuing success of intensified public health programs.

Indexed as

Physical FitnessSocial ClassAdolescentAge FactorsBody Mass IndexCholesterolExercise TestHumansHypercholesterolemiaLinear ModelsMaleMilitary PersonnelMultivariate AnalysisObesityOverweightPopulation GrowthCholesterol

Identifiers

PMID26888218
PMCPMC4756510
OpenAlexW2277950322

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.