Clustering of cardiovascular risk factors and carotid intima-media thickness: The USE-IMT study

The relation of a single risk factor with atherosclerosis is established. Clinically we know of risk factor clustering within individuals. Yet, studies into the magnitude of the relation of risk factor clusters with atherosclerosis are limited. Here, we assessed that relation. Individual participant...

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Veröffentlicht in:PloS one 2017-03, Vol.12 (3), p.e0173393-e0173393
Hauptverfasser: Wang, Xin, Dalmeijer, Geertje W, den Ruijter, Hester M, Anderson, Todd J, Britton, Annie R, Dekker, Jacqueline, Engström, Gunnar, Evans, Greg W, de Graaf, Jacqueline, Grobbee, Diederick E, Hedblad, Bo, Holewijn, Suzanne, Ikeda, Ai, Kauhanen, Jussi, Kitagawa, Kazuo, Kitamura, Akihiko, Kurl, Sudhir, Lonn, Eva M, Lorenz, Matthias W, Mathiesen, Ellisiv B, Nijpels, Giel, Okazaki, Shuhei, Polak, Joseph F, Price, Jacqueline F, Rembold, Christopher M, Rosvall, Maria, Rundek, Tatjana, Salonen, Jukka T, Sitzer, Matthias, Stehouwer, Coen D A, Tuomainen, Tomi-Pekka, Peters, Sanne A E, Bots, Michiel L
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container_end_page e0173393
container_issue 3
container_start_page e0173393
container_title PloS one
container_volume 12
creator Wang, Xin
Dalmeijer, Geertje W
den Ruijter, Hester M
Anderson, Todd J
Britton, Annie R
Dekker, Jacqueline
Engström, Gunnar
Evans, Greg W
de Graaf, Jacqueline
Grobbee, Diederick E
Hedblad, Bo
Holewijn, Suzanne
Ikeda, Ai
Kauhanen, Jussi
Kitagawa, Kazuo
Kitamura, Akihiko
Kurl, Sudhir
Lonn, Eva M
Lorenz, Matthias W
Mathiesen, Ellisiv B
Nijpels, Giel
Okazaki, Shuhei
Polak, Joseph F
Price, Jacqueline F
Rembold, Christopher M
Rosvall, Maria
Rundek, Tatjana
Salonen, Jukka T
Sitzer, Matthias
Stehouwer, Coen D A
Tuomainen, Tomi-Pekka
Peters, Sanne A E
Bots, Michiel L
description The relation of a single risk factor with atherosclerosis is established. Clinically we know of risk factor clustering within individuals. Yet, studies into the magnitude of the relation of risk factor clusters with atherosclerosis are limited. Here, we assessed that relation. Individual participant data from 14 cohorts, involving 59,025 individuals were used in this cross-sectional analysis. We made 15 clusters of four risk factors (current smoking, overweight, elevated blood pressure, elevated total cholesterol). Multilevel age and sex adjusted linear regression models were applied to estimate mean differences in common carotid intima-media thickness (CIMT) between clusters using those without any of the four risk factors as reference group. Compared to the reference, those with 1, 2, 3 or 4 risk factors had a significantly higher common CIMT: mean difference of 0.026 mm, 0.052 mm, 0.074 mm and 0.114 mm, respectively. These findings were the same in men and in women, and across ethnic groups. Within each risk factor cluster (1, 2, 3 risk factors), groups with elevated blood pressure had the largest CIMT and those with elevated cholesterol the lowest CIMT, a pattern similar for men and women. Clusters of risk factors relate to increased common CIMT in a graded manner, similar in men, women and across race-ethnic groups. Some clusters seemed more atherogenic than others. Our findings support the notion that cardiovascular prevention should focus on sets of risk factors rather than individual levels alone, but may prioritize within clusters.
doi_str_mv 10.1371/journal.pone.0173393
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Within each risk factor cluster (1, 2, 3 risk factors), groups with elevated blood pressure had the largest CIMT and those with elevated cholesterol the lowest CIMT, a pattern similar for men and women. Clusters of risk factors relate to increased common CIMT in a graded manner, similar in men, women and across race-ethnic groups. Some clusters seemed more atherogenic than others. 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Clinically we know of risk factor clustering within individuals. Yet, studies into the magnitude of the relation of risk factor clusters with atherosclerosis are limited. Here, we assessed that relation. Individual participant data from 14 cohorts, involving 59,025 individuals were used in this cross-sectional analysis. We made 15 clusters of four risk factors (current smoking, overweight, elevated blood pressure, elevated total cholesterol). Multilevel age and sex adjusted linear regression models were applied to estimate mean differences in common carotid intima-media thickness (CIMT) between clusters using those without any of the four risk factors as reference group. Compared to the reference, those with 1, 2, 3 or 4 risk factors had a significantly higher common CIMT: mean difference of 0.026 mm, 0.052 mm, 0.074 mm and 0.114 mm, respectively. These findings were the same in men and in women, and across ethnic groups. Within each risk factor cluster (1, 2, 3 risk factors), groups with elevated blood pressure had the largest CIMT and those with elevated cholesterol the lowest CIMT, a pattern similar for men and women. Clusters of risk factors relate to increased common CIMT in a graded manner, similar in men, women and across race-ethnic groups. Some clusters seemed more atherogenic than others. Our findings support the notion that cardiovascular prevention should focus on sets of risk factors rather than individual levels alone, but may prioritize within clusters.</description><subject>Age Factors</subject><subject>Aged</subject><subject>Analysis</subject><subject>Arteriosclerosis</subject><subject>artery</subject><subject>Atherosclerosis</subject><subject>Biology and Life Sciences</subject><subject>Blood</subject><subject>Blood pressure</subject><subject>Body weight</subject><subject>Cardiology</subject><subject>Cardiovascular disease</subject><subject>Cardiovascular diseases</subject><subject>Cardiovascular Diseases - diagnostic imaging</subject><subject>Cardiovascular Diseases - epidemiology</subject><subject>Cardiovascular tests</subject><subject>Carotid arteries</subject><subject>Carotid Intima-Media Thickness</subject><subject>Cholesterol</subject><subject>Cholesterol - blood</subject><subject>Clinical medical disciplines: 750</subject><subject>clinical-practice</subject><subject>Cluster Analysis</subject><subject>Clustering</subject><subject>Cohort Studies</subject><subject>Cross-Sectional Studies</subject><subject>Diabetes</subject><subject>disease</subject><subject>Epidemiology</subject><subject>Ethnic factors</subject><subject>events</subject><subject>Female</subject><subject>general-population</subject><subject>Health aspects</subject><subject>Health risk assessment</subject><subject>Health risks</subject><subject>Health Sciences</subject><subject>Humans</subject><subject>Hypertension</subject><subject>Hypertension - diagnostic imaging</subject><subject>Hypertension - epidemiology</subject><subject>Hälsovetenskap</subject><subject>Internal medicine</subject><subject>Klinisk medisinske fag: 750</subject><subject>Linear Models</subject><subject>Male</subject><subject>malmo diet</subject><subject>Medical disciplines: 700</subject><subject>Medicine</subject><subject>Medicine and Health Sciences</subject><subject>Medisinske Fag: 700</subject><subject>Men</subject><subject>Meta-Analysis as Topic</subject><subject>Metabolism</subject><subject>Middle Aged</subject><subject>Minority &amp; ethnic groups</subject><subject>Neurology</subject><subject>Nutrition</subject><subject>Overweight</subject><subject>Overweight - diagnostic imaging</subject><subject>Overweight - epidemiology</subject><subject>Physical Sciences</subject><subject>Population</subject><subject>prediction</subject><subject>Prevention</subject><subject>Primary care</subject><subject>progression</subject><subject>Public health</subject><subject>Regression analysis</subject><subject>Regression models</subject><subject>Risk analysis</subject><subject>Risk Factors</subject><subject>rotterdam</subject><subject>Sex Factors</subject><subject>Smoking</subject><subject>Smoking - epidemiology</subject><subject>Stroke</subject><subject>Studies</subject><subject>subclinical atherosclerosis</subject><subject>VDP</subject><issn>1932-6203</issn><issn>1932-6203</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>BENPR</sourceid><sourceid>3HK</sourceid><sourceid>DOA</sourceid><recordid>eNqNk11v0zAUhiMEYqPwDxBEQkJwkeKPfDhcIE3VgEpDk1jHrXXsOKm31C62M9i_x6XtaNAuplw4On7e4-P3-CTJS4ymmFb4w5UdnIF-urZGTRGuKK3po-QY15RkJUH08cH_UfLM-yuECsrK8mlyRBgllBF6nPBZP_ignDZdattUgmu0vQEvhx5c6rS_TluQwTqfgmk2-zboJtUm6BVkK9VoSMNSy2ujvP-YLpYqvbw4zebfFqkPQ3P7PHnSQu_Vi906SS4_ny5mX7Oz8y_z2clZJitWhawSgGtCEQPIBdQ5Q2VV5awSpZCtaEkjKKkAE1lIDFSSHOOaiUIRaKRijaKT5PU277q3nu-88Ryzqi4RoXkeifmWaCxc8bWL9btbbkHzvwHrOg4uaNkrLoQkpAZKRU1zVDIgJRJISlLiEtFo3iTJtrn8L7UexChbN6x5DHUD94qTIraliPynXXWDiJ5JZYKDfiQb7xi95J294QWN1efo3_VkbEnQhhvrgGOEaMUxwRWJxLvdEc7-HJQPfKW9VH0PRtlh4wRjNUNFyR6CIsQKjGhE3_yH3m_tjuoguqdNa-Ml5CYpP8lZmefRPxyp6T1U_Bq10jK-4lbH-EjwfiSITFC_QweD93x-8f3h7PmPMfv2gF0q6MPS234I2ho_BvO969Z7p9q7jmHEN0O4d4NvhpDvhjDKXh12-060nzr6B0jjKcI</recordid><startdate>20170321</startdate><enddate>20170321</enddate><creator>Wang, Xin</creator><creator>Dalmeijer, Geertje W</creator><creator>den Ruijter, Hester M</creator><creator>Anderson, Todd J</creator><creator>Britton, Annie R</creator><creator>Dekker, Jacqueline</creator><creator>Engström, Gunnar</creator><creator>Evans, Greg W</creator><creator>de Graaf, Jacqueline</creator><creator>Grobbee, Diederick E</creator><creator>Hedblad, Bo</creator><creator>Holewijn, Suzanne</creator><creator>Ikeda, Ai</creator><creator>Kauhanen, Jussi</creator><creator>Kitagawa, Kazuo</creator><creator>Kitamura, Akihiko</creator><creator>Kurl, Sudhir</creator><creator>Lonn, Eva M</creator><creator>Lorenz, Matthias W</creator><creator>Mathiesen, Ellisiv B</creator><creator>Nijpels, Giel</creator><creator>Okazaki, Shuhei</creator><creator>Polak, Joseph F</creator><creator>Price, Jacqueline F</creator><creator>Rembold, Christopher M</creator><creator>Rosvall, Maria</creator><creator>Rundek, Tatjana</creator><creator>Salonen, Jukka T</creator><creator>Sitzer, Matthias</creator><creator>Stehouwer, Coen D A</creator><creator>Tuomainen, Tomi-Pekka</creator><creator>Peters, Sanne A E</creator><creator>Bots, Michiel L</creator><general>Public Library of Science</general><general>Public Library of Science (PLoS)</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>IOV</scope><scope>ISR</scope><scope>3V.</scope><scope>7QG</scope><scope>7QL</scope><scope>7QO</scope><scope>7RV</scope><scope>7SN</scope><scope>7SS</scope><scope>7T5</scope><scope>7TG</scope><scope>7TM</scope><scope>7U9</scope><scope>7X2</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8C1</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABJCF</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>ATCPS</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BGLVJ</scope><scope>BHPHI</scope><scope>C1K</scope><scope>CCPQU</scope><scope>D1I</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>H94</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>KB.</scope><scope>KB0</scope><scope>KL.</scope><scope>L6V</scope><scope>LK8</scope><scope>M0K</scope><scope>M0S</scope><scope>M1P</scope><scope>M7N</scope><scope>M7P</scope><scope>M7S</scope><scope>NAPCQ</scope><scope>P5Z</scope><scope>P62</scope><scope>P64</scope><scope>PATMY</scope><scope>PDBOC</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PTHSS</scope><scope>PYCSY</scope><scope>RC3</scope><scope>7X8</scope><scope>3HK</scope><scope>5PM</scope><scope>ADTPV</scope><scope>AOWAS</scope><scope>F1U</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0002-9048-6635</orcidid></search><sort><creationdate>20170321</creationdate><title>Clustering of cardiovascular risk factors and carotid intima-media thickness: The USE-IMT study</title><author>Wang, Xin ; Dalmeijer, Geertje W ; den Ruijter, Hester M ; Anderson, Todd J ; Britton, Annie R ; Dekker, Jacqueline ; Engström, Gunnar ; Evans, Greg W ; de Graaf, Jacqueline ; Grobbee, Diederick E ; Hedblad, Bo ; Holewijn, Suzanne ; Ikeda, Ai ; Kauhanen, Jussi ; Kitagawa, Kazuo ; Kitamura, Akihiko ; Kurl, Sudhir ; Lonn, Eva M ; Lorenz, Matthias W ; Mathiesen, Ellisiv B ; Nijpels, Giel ; Okazaki, Shuhei ; Polak, Joseph F ; Price, Jacqueline F ; Rembold, Christopher M ; Rosvall, Maria ; Rundek, Tatjana ; Salonen, Jukka T ; Sitzer, Matthias ; Stehouwer, Coen D A ; Tuomainen, Tomi-Pekka ; Peters, Sanne A E ; Bots, Michiel L</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c787t-7ba192308aa4ba9480677487b6bcfbf2db327a12c5c1a3c241198b5e2adce8de3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2017</creationdate><topic>Age Factors</topic><topic>Aged</topic><topic>Analysis</topic><topic>Arteriosclerosis</topic><topic>artery</topic><topic>Atherosclerosis</topic><topic>Biology and Life Sciences</topic><topic>Blood</topic><topic>Blood pressure</topic><topic>Body weight</topic><topic>Cardiology</topic><topic>Cardiovascular disease</topic><topic>Cardiovascular diseases</topic><topic>Cardiovascular Diseases - diagnostic imaging</topic><topic>Cardiovascular Diseases - epidemiology</topic><topic>Cardiovascular tests</topic><topic>Carotid arteries</topic><topic>Carotid Intima-Media Thickness</topic><topic>Cholesterol</topic><topic>Cholesterol - blood</topic><topic>Clinical medical disciplines: 750</topic><topic>clinical-practice</topic><topic>Cluster Analysis</topic><topic>Clustering</topic><topic>Cohort Studies</topic><topic>Cross-Sectional Studies</topic><topic>Diabetes</topic><topic>disease</topic><topic>Epidemiology</topic><topic>Ethnic factors</topic><topic>events</topic><topic>Female</topic><topic>general-population</topic><topic>Health aspects</topic><topic>Health risk assessment</topic><topic>Health risks</topic><topic>Health Sciences</topic><topic>Humans</topic><topic>Hypertension</topic><topic>Hypertension - diagnostic imaging</topic><topic>Hypertension - epidemiology</topic><topic>Hälsovetenskap</topic><topic>Internal medicine</topic><topic>Klinisk medisinske fag: 750</topic><topic>Linear Models</topic><topic>Male</topic><topic>malmo diet</topic><topic>Medical disciplines: 700</topic><topic>Medicine</topic><topic>Medicine and Health Sciences</topic><topic>Medisinske Fag: 700</topic><topic>Men</topic><topic>Meta-Analysis as Topic</topic><topic>Metabolism</topic><topic>Middle Aged</topic><topic>Minority &amp; 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Clinically we know of risk factor clustering within individuals. Yet, studies into the magnitude of the relation of risk factor clusters with atherosclerosis are limited. Here, we assessed that relation. Individual participant data from 14 cohorts, involving 59,025 individuals were used in this cross-sectional analysis. We made 15 clusters of four risk factors (current smoking, overweight, elevated blood pressure, elevated total cholesterol). Multilevel age and sex adjusted linear regression models were applied to estimate mean differences in common carotid intima-media thickness (CIMT) between clusters using those without any of the four risk factors as reference group. Compared to the reference, those with 1, 2, 3 or 4 risk factors had a significantly higher common CIMT: mean difference of 0.026 mm, 0.052 mm, 0.074 mm and 0.114 mm, respectively. These findings were the same in men and in women, and across ethnic groups. Within each risk factor cluster (1, 2, 3 risk factors), groups with elevated blood pressure had the largest CIMT and those with elevated cholesterol the lowest CIMT, a pattern similar for men and women. Clusters of risk factors relate to increased common CIMT in a graded manner, similar in men, women and across race-ethnic groups. Some clusters seemed more atherogenic than others. Our findings support the notion that cardiovascular prevention should focus on sets of risk factors rather than individual levels alone, but may prioritize within clusters.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>28323823</pmid><doi>10.1371/journal.pone.0173393</doi><tpages>e0173393</tpages><orcidid>https://orcid.org/0000-0002-9048-6635</orcidid><oa>free_for_read</oa></addata></record>
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subjects Age Factors
Aged
Analysis
Arteriosclerosis
artery
Atherosclerosis
Biology and Life Sciences
Blood
Blood pressure
Body weight
Cardiology
Cardiovascular disease
Cardiovascular diseases
Cardiovascular Diseases - diagnostic imaging
Cardiovascular Diseases - epidemiology
Cardiovascular tests
Carotid arteries
Carotid Intima-Media Thickness
Cholesterol
Cholesterol - blood
Clinical medical disciplines: 750
clinical-practice
Cluster Analysis
Clustering
Cohort Studies
Cross-Sectional Studies
Diabetes
disease
Epidemiology
Ethnic factors
events
Female
general-population
Health aspects
Health risk assessment
Health risks
Health Sciences
Humans
Hypertension
Hypertension - diagnostic imaging
Hypertension - epidemiology
Hälsovetenskap
Internal medicine
Klinisk medisinske fag: 750
Linear Models
Male
malmo diet
Medical disciplines: 700
Medicine
Medicine and Health Sciences
Medisinske Fag: 700
Men
Meta-Analysis as Topic
Metabolism
Middle Aged
Minority & ethnic groups
Neurology
Nutrition
Overweight
Overweight - diagnostic imaging
Overweight - epidemiology
Physical Sciences
Population
prediction
Prevention
Primary care
progression
Public health
Regression analysis
Regression models
Risk analysis
Risk Factors
rotterdam
Sex Factors
Smoking
Smoking - epidemiology
Stroke
Studies
subclinical atherosclerosis
VDP
title Clustering of cardiovascular risk factors and carotid intima-media thickness: The USE-IMT study
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