Abstract

Objective To investigate prevalence and risk factors of peripheral artery disease (PAD), metabolic syndrome (MS) and peripheral artery disease complicated with metabolic syndrome among Kazakh adults lived in Xinjiang Yili prefecture. Methods Four-stage cluster sampling method was used to select adults aged 35 years and over for the study from six cities and prefectures of Xinjiang. All the participants were interviewed with questionnaire to collect their demographic characteristics. Physical checksup and blood biochemical measurements were performed for all of them, as well as blood pressure was measured in their lower legs and arms to calculate ankle brachial pressure index ( ABPI), a ratio of the blood pressure in the lower legs to that in the arms. Only data of Kazakh adults in Yili prefecture were analyzed in this paper, including prevalence and risk factors for PAD and MS, as well as their relationship.The patients with PAD were divided into two groups, one complicated with MS and the other without it Logistic regression analysis was used to identify potential risk factors for PAD and MS and their combination.Results A total of 1365 adult Kazakh people were surveyed. Prevalence of MS was 23.7 percent, 30.4 percent for men and 19.0 percent for women, respectively, and that of PAD was 9. 4 percent, 7.0 percent for men and 11.0 percent for women, respectively. Mean age in patients of PAD complicated with MS was older than that in those without MS (t=-5.348, P<0.01). Risk of PAD complicated with MS in Kazakh people associated with gender ( men), age, systolic pressure, diastolic pressure and blood glucose level.(P<0.05). Conclusions Both prevalence of PAD and MS are significantly higher among Kazakh people in Yili prefecture of Xinjiang, and increase with age. Prevalence of PAD is significantly higher in those with MS than that in those without MS. Risk factors of PAD complicated with MS include gender(men), age,systolic pressure, diastolic pressure and blood glucose level. Key words: Peripheral vascular disease; Metabolic syndrome X; Data collection

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