AGBDA. Artículos de Investigación

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Examinando AGBDA. Artículos de Investigación por Autor "Anand, Sonia S."

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  • Publicación
    Acceso abierto
    The association between ownership of common household devices and obesity and diabetes in high, middle and low income countries
    (2014-03-04) Lear, Scott A.; Teo, Koon; Gasevic, Danijela; Zhang, Xiaohe; Poirier, Paul P.; Rangarajan, Sumathy; Seron, Pamela; Kelishadi, Roya; Mohd Tamil, Azmi; Kruger, Annamarie; Iqbal, Romaina; Swidan, Hani; Gómez Arbeláez, Diego; Yusuf, Rita; Chifamba, Jephat; Kutty, V. Raman; Karsıdag, Kubilay; Kumar, Rajesh; Li, Wei; Szuba, Andrzej; Avezum, Alvaro; Diaz, Rafael; Anand, Sonia S.; Rosengren, Annika; Yusuf, Salim; The PURE (Prospective Urban Rural Epidemiology) Study investigators
    Background: Household devices (e.g., television, car, computer) are common in high income countries, and their use has been linked to obesity and type 2 diabetes mellitus. We hypothesized that device ownership is associated with obesity and diabetes and that these effects are explained through reduced physical activity, increased sitting time and increased energy intake. Methods: We performed a cross-sectional analysis using data from the Prospective Urban Rural Epidemiology study involving 153 996 adults from high, upper-middle, lower-middle and low income countries. We used multilevel regression models to account for clustering at the community and country levels. Results: Ownership of a household device increased from low to high income countries (4% to 83% for all 3 devices) and was associated with decreased physical activity and increased sitting, dietary energy intake, body mass index and waist circumference. There was an increased odds of obesity and diabetes with the ownership of any 1 household device compared to no device ownership (obesity: odds ratio [OR] 1.43, 95% confidence interval [CI] 1.32–1.55; diabetes: OR 1.38, 95% CI 1.28–1.50). Ownership of a second device increased the odds further but ownership of a third device did not. Subsequent adjustment for lifestyle factors modestly attenuated these associations. Of the 3 devices, ownership of a television had the strongest association with obesity (OR 1.39, 95% CI 1.29–1.49) and diabetes (OR 1.33, 95% CI 1.23–1.44). When stratified by country income level, the odds of obesity and diabetes when owning all 3 devices was greatest in low income countries (obesity: OR 3.15, 95% CI 2.33-4.25; diabetes: OR 1.97, 95% CI 1.53–2.53) and decreased through country income levels such that we did not detect an association in high income countries. Interpretation: The ownership of household devices increased the likelihood of obesity and diabetes, and this was mediated in part by effects on physical activity, sitting time and dietary energy intake. With increasing ownership of household devices in developing countries, societal interventions are needed to mitigate their effects on poor health.
  • Publicación
    Acceso abierto
    Cardiovascular risk and events in 17 low-, middle-, and high-income countries
    (2014-08-28) Yusuf, Salim; Rangarajan, Sumathy; Teo, Koon; Islam, Shofiqul; Li, Wei; Liu, Lisheng; Bo, Jian; Lou, Qinglin; Lu, Fanghong; Liu, Tianlu; Yu, Liu; Zhang, Shiying; Mony, Prem; Swaminathan, Sumathi; Mohan, Viswanathan; Gupta, Rajeev; Kumar, Rajesh; Vijayakumar, Krishnapillai; Lear, Scott A.; Anand, Sonia S.; Wielgosz, Andreas; Diaz, Rafael; Avezum, Alvaro; Lopez-Jaramillo, Patricio; Lanas, Fernando; Yusoff, Khalid; Ismail, Noorhassim; Iqbal, Romaina; Rahman, Omar; Rosengren, Annika; Yusufali, Afzalhussein; Kelishadi, Roya; Kruger, Annamarie; Puoane, Thandi; Szuba, Andrzej; Chifamba, Jephat; Oguz, Aytekin; McQueen, Matthew J.; McKee, Martin; Dagenais, Gilles; The PURE (Prospective Urban Rural Epidemiology) Study investigators
    BACKGROUND More than 80% of deaths from cardiovascular disease are estimated to occur in low-income and middle-income countries, but the reasons are unknown. METHODS We enrolled 156,424 persons from 628 urban and rural communities in 17 countries (3 high-income, 10 middle-income, and 4 low-income countries) and assessed their cardiovascular risk using the INTERHEART Risk Score, a validated score for quantifying risk-factor burden without the use of laboratory testing (with higher scores indicating greater risk-factor burden). Participants were followed for incident cardiovascular disease and death for a mean of 4.1 years. RESULTS The mean INTERHEART Risk Score was highest in high-income countries, intermediate in middle-income countries, and lowest in low-income countries (P<0.001). However, the rates of major cardiovascular events (death from cardiovascular causes, myocardial infarction, stroke, or heart failure) were lower in high-income countries than in middle- and low-income countries (3.99 events per 1000 person-years vs. 5.38 and 6.43 events per 1000 person-years, respectively; P<0.001). Case fatality rates were also lowest in high-income countries (6.5%, 15.9%, and 17.3% in high-, middle-, and low-income countries, respectively; P=0.01). Urban communities had a higher risk-factor burden than rural communities but lower rates of cardiovascular events (4.83 vs. 6.25 events per 1000 person-years, P<0.001) and case fatality rates (13.52% vs. 17.25%, P<0.001). The use of preventive medications and revascularization procedures was significantly more common in high-income countries than in middle- or low-income countries (P<0.001). CONCLUSIONS Although the risk-factor burden was lowest in low-income countries, the rates of major cardiovascular disease and death were substantially higher in low-income countries than in high-income countries. The high burden of risk factors in high-income countries may have been mitigated by better control of risk factors and more frequent use of proven pharmacologic therapies and revascularization. (Funded by the Population Health Research Institute and others.)