METHODS: We developed a quantitative tool - the Toolkit for Evaluating Alcohol policy Stringency and Enforcement (TEASE-16) - to assess the level of stringency and enforcement of 16 alcohol control policies. TEASE-16 was applied to policy data from nine study areas in the western Pacific: Australia, China excluding Hong Kong Special Administrative Region (SAR), Hong Kong SAR, Japan, Malaysia, New Zealand, the Philippines, Singapore and Viet Nam. Correlation and regression analyses were then used to examine the relationship between alcohol policy scores and income-adjusted levels of alcohol consumption per capita.
FINDINGS: Vast differences exist in how alcohol control policies are implemented in the western Pacific. Out of a possible 100 points, the nine study areas achieved TEASE-16 scores that ranged from 24.1 points for the Philippines to 67.5 points for Australia. Study areas with high policy scores - indicating relatively strong alcohol policy frameworks - had lower alcohol consumption per capita. Sensitivity analyses indicated scores and rankings for each study area remained relatively stable across different weighting schemes, indicating that TEASE-16 was robust.
CONCLUSION: TEASE-16 could be used by international and national regulatory bodies and policy-makers to guide the design, implementation, evaluation and refinement of effective policies to reduce alcohol consumption and related problems.
Methods: We searched seven databases up to July 2020 for randomized controlled trials investigating the effectiveness of telemedicine in the delivery of diabetes care in low- and middle-income countries. We extracted data on the study characteristics, primary end-points and effect sizes of outcomes. Using random effects analyses, we ran a series of meta-analyses for both biochemical outcomes and related patient properties.
Findings: We included 31 interventions in our meta-analysis. We observed significant standardized mean differences of -0.38 for glycated haemoglobin (95% confidence interval, CI: -0.52 to -0.23; I2 = 86.70%), -0.20 for fasting blood sugar (95% CI: -0.32 to -0.08; I2 = 64.28%), 0.81 for adherence to treatment (95% CI: 0.19 to 1.42; I2 = 93.75%), 0.55 for diabetes knowledge (95% CI: -0.10 to 1.20; I2 = 92.65%) and 1.68 for self-efficacy (95% CI: 1.06 to 2.30; I2 = 97.15%). We observed no significant treatment effects for other outcomes, with standardized mean differences of -0.04 for body mass index (95% CI: -0.13 to 0.05; I2 = 35.94%), -0.06 for total cholesterol (95% CI: -0.16 to 0.04; I2 = 59.93%) and -0.02 for triglycerides (95% CI: -0.12 to 0.09; I2 = 0%). Interventions via telephone and short message service yielded the highest treatment effects compared with services based on telemetry and smartphone applications.
Conclusion: Although we determined that telemedicine is effective in improving several diabetes-related outcomes, the certainty of evidence was very low due to substantial heterogeneity and risk of bias.