Contribution of modifiable risk factors for hypertension and type-2 diabetes in Peruvian resource-limited settings. Issue 1 (6th August 2015)

• Record Type: Journal Article
• Authors: Bernabé-Ortiz, Antonio; Carrillo-Larco, Rodrigo M; Gilman, Robert H; Checkley, William; Smeeth, Liam; Miranda, J Jaime
• Other Names: author non-byline.; Casas Juan P author non-byline.; Davey Smith George author non-byline.; Ebrahim Shah author non-byline.; García Héctor H author non-byline.; Huicho Luis author non-byline.; Málaga Germán author non-byline.; Montori Víctor M author non-byline.; Diette Gregory B author non-byline.; Huicho Luis author non-byline.; León-Velarde Fabiola author non-byline.; Rivera María author non-byline.; Wise Robert A author non-byline.; Sacksteder Katherine author non-byline.
• Is Part Of: Journal of epidemiology and community health. Volume 70:Issue 1(2016)
• Page Start: 49
• Page End: 55
• Publication Date: 2015-08-06
• Subjects: DIABETES -- Epidemiology of chronic non communicable diseases -- HYPERTENSION; Public health -- Periodicals; Epidemiology -- Periodicals; 614.4
• DOI: 10.1136/jech-2015-205988
• Languages: English
• ISSNs: 0143-005X

Abstract

Abstract : Background: It is important to understand the local burden of non-communicable diseases including within-country heterogeneity. The aim of this study was to characterise hypertension and type-2 diabetes profiles across different Peruvian geographical settings emphasising the assessment of modifiable risk factors. Methods: Analysis of the CRONICAS Cohort Study baseline assessment was conducted. Cardiometabolic outcomes were blood pressure categories (hypertension, prehypertension, normal) and glucose metabolism disorder status (diabetes, prediabetes, normal). Exposures were study setting and six modifiable factors (smoking, alcohol drinking, leisure time and transport-related physical activity levels, TV watching, fruit/vegetables intake and obesity). Poisson regression models were used to report prevalence ratios (PR). Population attributable risks (PAR) were also estimated. Results: Data from 3238 participants, 48.3% male, mean age 45.3 years, were analysed. Age-standardised (WHO population) prevalence of prehypertension and hypertension was 24% and 16%, whereas for prediabetes and type-2 diabetes it was 18% and 6%, respectively. Outcomes varied according to study setting (p<0.001). In multivariable model, hypertension was higher among daily smokers (PR 1.76), heavy alcohol drinkers (PR 1.61) and the obese (PR 2.06); whereas only obesity (PR 2.26) increased the prevalence of diabetes. PAR showed that obesity was an important determinant for hypertension (15.7%) and type-2 diabetes (23.9%). Conclusions: There is an evident heterogeneity in the prevalence of and risk factors for hypertension and diabetes within Peru. Prehypertension and prediabetes are highly prevalent across settings. Our results emphasise the need of understanding the epidemiology of cardiometabolic conditions to appropriately implement interventions to tackle the burden of non-communicable diseases.