Impact of interactions among metabolic syndrome components on the development of cardiovascular disease among Kazakhs in Xinjiang

Abstract

BackgroundFew prospective studies have explored the effect of interactions among metabolic syndrome (MS) components on the development of cardiovascular disease (CVD) in the Kazakh population in Xinjiang Province of China.MethodAs of December 2016, 2,644 participants who completed a baseline survey over a period of 5 years or more were included in the study. The multiplicative interactions among MS components were evaluated by incorporation of the product terms into a logistic regression model. The additive interactions among MS components were evaluated by calculating the additive interaction index. Logistic regression was used to construct a predictive model, and CVD risk level was divided according to the risk probability of the population that did not eventually have CVD.ResultsWhen we analyzed the independent risk of MS and its components on developing CVD, only blood pressure(BP) and waist circumference(WC) were associated with CVD. A linear association was found between the risk of CVD, BP/WC, and the number of other components (trend, P<0.001). The risk of developing CVD increased when BP and WC coexisted, or when combined BP/WC with MS (≥3 components except for BP and WC) was present; however, there were no significant interactions among MS components. After the CVD hazards were divided into four levels, it was showed that over 19.92% of the incidence probability was in the population under mediate-risk while over 35.24% of them was in the high-risk group, respectively.ConclusionsBP and WC were independent risk factors for CVD in the Kazakh population. The risk of CVD was greatly increased when BP and WC coexisted or when combined BP/WC with MS (≥3 components except for BP and WC) was present, but no significant interactions were found among MS components.

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“…The database construction and some statistical analyses have been previously described [ 12 ]. Cox proportional hazards regression model was used to evaluate the association of each component and the number of combinations of MS components on the development of CVD.…”

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