METHODS AND ANALYSIS: The IPEN Adolescent observational, cross-sectional, multicountry study involves recruiting adolescent participants (ages 11-19 years) and one parent/guardian from neighbourhoods selected to ensure wide variations in walkability and socioeconomic status using common protocols and measures. Fifteen geographically, economically and culturally diverse countries, from six continents, participated: Australia, Bangladesh, Belgium, Brazil, Czech Republic, Denmark, Hong Kong SAR, India, Israel, Malaysia, New Zealand, Nigeria, Portugal, Spain and USA. Countries provided survey and accelerometer data (15 countries), GIS data (11), global positioning system data (10), and pedestrian environment audit data (8). A sample of n=6950 (52.6% female; mean age=14.5, SD=1.7) adolescents provided survey data, n=4852 had 4 or more 8+ hours valid days of accelerometer data, and n=5473 had GIS measures. Physical activity and sedentary behaviour were measured by waist-worn ActiGraph accelerometers and self-reports, and body mass index was used to categorise weight status.
ETHICS AND DISSEMINATION: Ethical approval was received from each study site's Institutional Review Board for their in-country studies. Informed assent by adolescents and consent by parents was obtained for all participants. No personally identifiable information was transferred to the IPEN coordinating centre for pooled datasets. Results will be communicated through standard scientific channels and findings used to advance the science of environmental correlates of physical activity, sedentary behaviour and weight status, with the ultimate goal to stimulate and guide actions to create more activity-supportive environments internationally.
METHODS: The current study estimated the annual spending and lifetime spending of smokers in the target Asia-Pacific countries (Hong Kong, Malaysia, Thailand, South Korea, Singapore, and Australia) on purchasing cigarettes, as well as predicted the revenue that could be generated if smokers spent the money on investment instead of buying cigarettes. Smokers' spending on cigarettes and the potential revenue generated from investment were estimated based on the selling prices of cigarettes, Standards & Poor's 500 Index, and life expectancies of smokers. Data were extracted from reports released by the World Health Organization or government authorities.
RESULTS: The annual expenses (in US$) on purchasing one pack of cigarettes, in decreasing order, were: Australia ($5628.30), Singapore ($3777.75), Hong Kong ($2799.55), Malaysia ($1529.35), South Korea ($1467.30), and Thailand ($657.00). The lifetime spending on purchasing one pack of cigarettes each day were: Australia ($308993.67), Singapore ($207398.48), Hong Kong ($151735.61 for male and $166853.18 for female), South Korea ($80261.31), Malaysia ($72338.26), and Thailand ($31207.50).
CONCLUSIONS: The cost burden of smoking is high from a smoker's perspective. Smokers should recognize the high economic burden and quit smoking to enjoy better health and wealth.
METHODS: In this prospective observational study, we measured BCAAs in fasting serum samples collected at inception from 2139 T2D patients free of cardiovascular-renal diseases. The study outcome was the first hospitalization for HF.
RESULTS: During 29 103 person-years of follow-up, 115 primary events occurred (age: 54.8 ± 11.2 years, 48.2% men, median [interquartile range] diabetes duration: 5 years [1-10]). Patients with incident HF had 5.6% higher serum BCAAs than those without HF (median 639.3 [561.3-756.3] vs 605.2 [524.8-708.7] μmol/L; P = .01). Serum BCAAs had a positive linear association with incident HF (per-SD increase in logarithmically transformed BCAAs: hazard ratio [HR] 1.22 [95% CI 1.07-1.39]), adjusting for age, sex, and diabetes duration. The HR remained significant after sequential adjustment of risk factors including incident coronary heart disease (1.24, 1.09-1.41); blood pressure, low-density lipoprotein cholesterol, and baseline use of related medications (1.31, 1.14-1.50); HbA1c , waist circumference, triglyceride, and baseline use of related medications (1.28, 1.11-1.48); albuminuria and estimated glomerular filtration rate (1.28, 1.11-1.48). The competing risk of death analyses showed similar results.
CONCLUSIONS: Circulating levels of BCAAs are independently associated with incident HF in patients with T2D. Prospective cohort analysis and randomized trials are needed to evaluate the long-term safety and efficacy of using different interventions to optimize BCAAs levels in these patients.
Methods: Fifteen countries of SA and SEA categorized as HE and LE, represented by the representatives of the national nephrology societies, participated in this questionnaire and interview-based assessment of the impact of economic status on renal care.
Results: Average incidence and prevalence of end-stage kidney disease (ESKD) per million population (pmp) are 1.8 times and 3.3 times higher in HE. Hemodialysis is the main renal replacement therapy (RRT) (HE-68%, LE-63%). Funding of dialysis in HE is mainly by state (65%) or insurance bodies (30%); out of pocket expenses (OOPE) are high in LE (41%). Highest cost for hemodialysis is in Brunei and Singapore, and lowest in Myanmar and Nepal. Median number of dialysis machines/1000 ESKD population is 110 in HE and 53 in LE. Average number of machines/dialysis units in HE is 2.7 times higher than LE. The HE countries have 9 times more dialysis centers pmp (median HE-17, LE-02) and 16 times more nephrologist density (median HE-14.8 ppm, LE-0.94 ppm). Dialysis sessions >2/week is frequently followed in HE (84%) and <2/week in LE (64%). "On-demand" hemodialysis (<2 sessions/week) is prevalent in LE. Hemodialysis dropout rates at one year are lower in HE (12.3%; LE 53.4%), death being the major cause (HE-93.6%; LE-43.8%); renal transplants constitute 4% (Brunei) to 39% (Hong Kong) of the RRT in HE. ESKD burden is expected to increase >10% in all the HE countries except Taiwan, 10%-20% in the majority of LE countries.
Conclusion: Economic disparity in SA and SEA is reflected by poor dialysis infrastructure and penetration, inadequate manpower, higher OOPE, higher dialysis dropout rates, and lesser renal transplantations in LE countries. Utility of RRT can be improved by state funding and better insurance coverage.
METHODS: GARFIELD-VTE is a global, prospective, non-interventional study of real-world treatment practices. In this study, we compared baseline characteristics, treatment patterns, and 12-month outcomes in Asia and ROW.
RESULTS: Of the 10,684 enrolled patients, 1822 (17.1%) were Asian (China n = 420, Hong Kong n = 98, Japan n = 148, Malaysia n = 244, South Korea n = 343, Taiwan n = 232, Thailand n = 337). Compared with ROW patients, those from Asia were more often female (57.4% vs. 48.0%), non-smokers (74.0% vs. 58.9%) and had a lower BMI (24.8 kg/m2 vs. 29.1 kg/m2). Asian patients were more likely to be managed in the hospital (86.9% vs. 70.4%) and to have active cancer (19.8% vs. 8.1%) or a history of cancer (19.1% vs. 12.0%). Asian patients received no anticoagulation more frequently than ROW patients (6.5% vs. 2.1%). Over 12-months follow-up, the rate of all-cause mortality (per 100 person-years [95% confidence interval]) was higher in Asians (15.2 [13.4-17.3] vs. 5.9 [5.4-6.5]). Adjusted hazard ratios indicated a higher risk of all-cause mortality in Asian patients than the ROW (1.32 [1.08-1.62]). The frequencies of major bleeding and recurrent VTE were similar.
CONCLUSION: Asian patients have different risk profiles, treatment patterns and a higher risk of mortality compared with the ROW.
MATERIALS AND METHODS: A total of 2306 subjects were selected from the patient archives of a large dental hospital and the chronological age for each subject was recorded. This age was assigned to each specific stage of dental development for each tooth to create a RDS. To validate this RDS, a further 484 subjects were randomly chosen from the patient archives and their dental age was assessed based on the scores from the RDS. Dental age was estimated using meta-analysis command corresponding to random effects statistical model. Chronological age (CA) and Dental Age (DA) were compared using the paired t-test.
RESULTS: The overall difference between the chronological and dental age (CA-DA) was 0.05 years (2.6 weeks) for males and 0.03 years (1.6 weeks) for females. The paired t-test indicated that there was no statistically significant difference between the chronological and dental age (p > 0.05).
CONCLUSION: The validated southern Chinese reference dataset based on dental maturation accurately estimated the chronological age.