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 cohort study was conducted in 77,425 men and women free of NAFLD and metabolic abnormalities at baseline, who were followed-up annually or biennially for an average of 4.5 years. Being metabolically healthy was defined as not having any metabolic syndrome component and having a homeostasis model assessment of insulin resistance <2.5. The presence of fatty liver was determined using ultrasound.
RESULTS: During 348,193.5 person-years of follow-up, 10,340 participants developed NAFLD (incidence rate, 29.7 per 1,000 person-years). The multivariable adjusted hazard ratios (95% confidence intervals) for incident NAFLD comparing overweight and obese with normal-weight participants were 2.15 (2.06-2.26) and 3.55 (3.37-3.74), respectively. In detailed dose-response analyses, increasing baseline BMI showed a strong and approximately linear relationship with the incidence of NAFLD, with no threshold at no risk. This association was present in both men and women, although it was stronger in women (P for interaction <0.001), and it was evident in all clinically relevant subgroups evaluated, including participants with low inflammation status.
CONCLUSIONS: In a large cohort of strictly defined metabolically healthy men and women, overweight and obesity were strongly and progressively associated with an increased incidence of NAFLD, suggesting that the obese phenotype per se, regardless of metabolic abnormalities, can increase the risk of NAFLD.
METHODS: This study is based on the collective and direct experiences of the founding members of the HTAsiaLink Network. Data were collected from presentations they made at various international forums and additional information was reviewed. Data analysis was done using the framework developed by San Martin-Rodriguez et al.Results and Conclusions:HTAsiaLink is a network of health technology assessment (HTA) agencies in Asia established in 2011 with the aim of strengthening individual and institutional HTA capacity, reducing duplication and optimizing resources, transfer and sharing of HTA-related lessons among members, and beyond. During its 6 years, the network has expanded, initiating several capacity building activities and joint-research projects, raising awareness of the importance of HTA within the region and beyond, and gaining global recognition while establishing relationships with other global networks. The study identifies the determinants of success of the collaboration. The systemic factors include the favorable outlook toward HTA as an approach for healthcare priority setting in countries with UHC mandates. On organizational factors, the number of newly established HTA agencies in the region with similar needs for capacity building and peer-to-peer support was catalytic for the network development. The interactional aspects include ownership, trust, and team spirit among network members. The network, however, faces challenges notably, financial sustainability and management of the expanded network.
METHODS: In the EQ-VT protocol, 196 pairs of EQ-5D-5L health states were valued by a general population sample using DCE method for all studies. DCE data were obtained from the study PI. To understand how the health preferences are different/similar with each other, the following analyses were done: (1) the statistical difference between the coefficients; (2) the relative importance of the five EQ-5D dimensions; (3) the relative importance of the response levels.
RESULTS: The number of statistically differed coefficients between two studies ranged from 2 to 16 (mean: 9.3), out of 20 main effects coefficients. For the relative importance, there is not a universal preference pattern that fits all studies, but with some common characteristics, e.g. mobility is considered the most important; the relative importance of levels are approximately 20% for level 2, 30% for level 3, 70% for level 4 for all studies.
DISCUSSION: Following a standardized study protocol, there are still considerable differences in the modeling and relative importance results in the EQ-5D-5L DCE data among 11 Asian studies. These findings advocate the use of local value set for calculating health state utility.