03003nas a2200505 4500000000100000008004100001100002200042700001700064700001300081700002200094700001900116700001800135700001800153700002200171700002100193700001500214700002400229700001500253700002100268700001300289700001900302700001900321700002100340700001600361700001300377700002000390700002200410700001700432700001900449700001700468700002100485700002400506700001800530700001900548700001800567700002000585700001900605700002500624700001700649245010100666300001300767490000700780520169600787022001402483 2017 d1 aGrobbee Diederick1 aBots Michiel1 aWang Xin1 aDalmeijer Geertje1 aRuijter Hester1 aAnderson Todd1 aBritton Annie1 aDekker Jacqueline1 aEngström Gunnar1 aEvans Greg1 ade Graaf Jacqueline1 aHedblad Bo1 aHolewijn Suzanne1 aIkeda Ai1 aKauhanen Jussi1 aKitagawa Kazuo1 aKitamura Akihiko1 aKurl Sudhir1 aLonn Eva1 aLorenz Matthias1 aMathiesen Ellisiv1 aNijpels Giel1 aOkazaki Shuhei1 aPolak Joseph1 aPrice Jacqueline1 aRembold Christopher1 aRosvall Maria1 aRundek Tatjana1 aSalonen Jukka1 aSitzer Matthias1 aStehouwer Coen1 aTuomainen Tomi-Pekka1 aPeters Sanne00aClustering of cardiovascular risk factors and carotid intima-media thickness: The USE-IMT study. ae01733930 v123 a

BACKGROUND: 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.

METHODS: 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.

RESULTS: 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.

CONCLUSION: 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.

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