METHODS: This was a cross-sectional study of 22,210 adult men and women who underwent a comprehensive health screening examination between 2011 and 2013 (median age 40 years). Sugar-sweetened carbonated beverage consumption was assessed using a validated food frequency questionnaire, and CAC was measured by cardiac computed tomography. Multivariable-adjusted CAC score ratios and 95% CIs were estimated from robust Tobit regression models for the natural logarithm (CAC score +1).
RESULTS: The prevalence of detectable CAC (CAC score >0) was 11.7% (n = 2,604). After adjustment for age; sex; center; year of screening examination; education level; physical activity; smoking; alcohol intake; family history of cardiovascular disease; history of hypertension; history of hypercholesterolemia; and intake of total energy, fruits, vegetables, and red and processed meats, only the highest category of sugar-sweetened carbonated beverage consumption was associated with an increased CAC score compared with the lowest consumption category. The multivariable-adjusted CAC ratio comparing participants who consumed ≥5 sugar-sweetened carbonated beverages per week with nondrinkers was 1.70 (95% CI, 1.03-2.81). This association did not differ by clinical subgroup, including participants at low cardiovascular risk.
CONCLUSION: Our findings suggest that high levels of sugar-sweetened carbonated beverage consumption are associated with a higher prevalence and degree of CAC in asymptomatic adults without a history of cardiovascular disease, cancer, or diabetes.
METHODS: A cluster-randomized controlled trial was conducted with schools as clusters over a period of six-months with pre and post intervention evaluations. Participants were public secondary school students (14-19 years) from four schools in Brong Ahafo, Ghana. Students in the intervention group were trained by the researchers whereas those of the control group received no intervention. The intervention included health education and physical activity modules. Follow-up data using same questionnaire were collected within two weeks after the intervention was completed. Intention-to-treat analysis was performed after replacing missing values using the multiple imputation method. The generalized linear mixed model (GLMM) was used to assess the effects of the intervention study.
RESULTS: The GLMM analyses showed the intervention was effective in attaining 0.77(p<0.001), 0.72(p<0.001), 0.47(p<0.001), 0.56(p<0.001), and 0.39(p = 0.045) higher total physical activity, fruits, vegetables, seafood, and water scores respectively for the intervention group over the control group. The intervention was also significant in reducing -0.15(p<0.001),-0.23(p<0.001),-0.50(p<0.001),-0.32(p<0.001),-0.90(p<0.001),-0.87(p<0.001),-0.38(p<0.001), -0.63(p<0.001), -1.63(p<0.001), 0.61(p<0.001), and -1.53(p = 0.005) carbohydrates, fats and oils, fried eggs, fried chicken, carbonated drinks, sugar, sweet snacks, salted fish, weight, BMI, and diastolic BP. The odds of quitting alcohol use in the intervention group were 1.06 times more than the control group. There was no significant effect on reducing smoking and systolic BP.
CONCLUSION: There is an urgent need for the intervention program to be integrated into the existing curriculum structure of secondary school schools. Implementing the intervention will allow for longer and more consistent impact on the reduction of CVD risk factors among secondary school students.