Evidence map›Paper›PMID 34855783›Full record

ArticlePloS one2021

Longitudinal trajectories of blood lipid levels in an ageing population sample of Russian Western-Siberian urban population.

Jaroslav A Hubacek, Yuri Nikitin, Yulia Ragino, Ekaterina Stakhneva, Hynek Pikhart, Anne Peasey, Michael V Holmes, Denes Stefler, Andrey Ryabikov, Eugeny Verevkin and 2 more

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.4field-weighted citation impact, top 35% 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

1 citing paper in PubMed, 4 citations in OpenAlex.

  1. 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

12 authors at 4 institutions in 3 countries.

Jaroslav A HubacekExperimental Medicine Centre, Institute for Clinical and Experimental Medicine, Prague, Czech Republic.ORCID 0000-0001-6537-1353
Yuri NikitinResearch Institute of Internal and Preventive Medicine-Branch of Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences, Novosibirsk, Russia.
Yulia RaginoResearch Institute of Internal and Preventive Medicine-Branch of Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences, Novosibirsk, Russia.
Ekaterina StakhnevaResearch Institute of Internal and Preventive Medicine-Branch of Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences, Novosibirsk, Russia.
Hynek PikhartDepartment of Epidemiology and Public Health, University College London, London, United Kingdom.
Anne PeaseyDepartment of Epidemiology and Public Health, University College London, London, United Kingdom.
Michael V HolmesNuffield Department of Population Health, University of Oxford, Oxford, United Kingdom.
Denes SteflerDepartment of Epidemiology and Public Health, University College London, London, United Kingdom.
Andrey RyabikovResearch Institute of Internal and Preventive Medicine-Branch of Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences, Novosibirsk, Russia.
Eugeny VerevkinResearch Institute of Internal and Preventive Medicine-Branch of Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences, Novosibirsk, Russia.
Martin BobakDepartment of Epidemiology and Public Health, University College London, London, United Kingdom.
Sofia MalyutinaResearch Institute of Internal and Preventive Medicine-Branch of Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences, Novosibirsk, Russia.
Institute of Cytology and Genetics · RUUniversity College London · GBCharles University · CZUniversity of Oxford · GB

Funding

Health disparities and agingin societies in transitionR01AG023522 · NIA · UNIVERSITY COLLEGE LONDON · PI MARMOT, MICHAEL G · 2004 to 2008
$2.2M
British Heart Foundation FS/18/23/33512Department of HealthMedical Research CouncilNIA NIH HHS R01 AG023522Wellcome Trust WT064947Wellcome Trust WT081081
6 · The paper itself

Abstract

This study investigated 12-year blood lipid trajectories and whether these trajectories are modified by smoking and lipid lowering treatment in older Russians. To do so, we analysed data on 9,218 Russian West-Siberian Caucasians aged 45-69 years at baseline participating in the international HAPIEE cohort study. Mixed-effect multilevel models were used to estimate individual level lipid trajectories across the baseline and two follow-up examinations (16,445 separate measurements over 12 years). In all age groups, we observed a reduction in serum total cholesterol (TC), LDL-C and non-HDL-C over time even after adjusting for sex, statin treatment, hypertension, diabetes, social factors and mortality (P<0.01). In contrast, serum triglyceride (TG) values increased over time in younger age groups, reached a plateau and decreased in older age groups (> 60 years at baseline). In smokers, TC, LDL-C, non-HDL-C and TG decreased less markedly than in non-smokers, while HDL-C decreased more rapidly while the LDL-C/HDL-C ratio increased. In subjects treated with lipid-lowering drugs, TC, LDL-C and non-HDL-C decreased more markedly and HDL-C less markedly than in untreated subjects while TG and LDL-C/HDL-C remained stable or increased in treatment naïve subjects. We conclude, that in this ageing population we observed marked changes in blood lipids over a 12 year follow up, with decreasing trajectories of TC, LDL-C and non-HDL-C and mixed trajectories of TG. The findings suggest that monitoring of age-related trajectories in blood lipids may improve prediction of CVD risk beyond single measurements.

Indexed as

AgingLipidsAgedCholesterol, HDLCholesterol, LDLFemaleHumansLongitudinal StudiesMaleMiddle AgedRussiaSmokingTriglyceridesUrban PopulationCholesterol, HDLCholesterol, LDLLipidsTriglycerides

Identifiers

PMID34855783
PMCPMC8638938
OpenAlexW3215588283

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.