Background: Peer education has become a strategy for health promotion among high-risk groups for HIV infection worldwide. However, the extent to which peer education could have an impact on HIV prevention or the long-term effect of this impact is still unknown. This study thus quantifies the impact of peer education over time among high-risk HIV groups globally. Method: Following the PRISMA guidelines, a systematic review and meta-analysis was used to assess the effects and duration of peer education. A thorough literature search of PubMed, Web of Science, Embase and Cochrane Library was performed, and studies about peer education on high-risk HIV groups were reviewed. Pooled effects were calculated and the sources of heterogeneity were explored using meta-regression and subgroup analysis. Results: A total of 60 articles with 96,484 subjects were identified, and peer education was associated with 36% decreased rates of HIV infection among overall high risk groups (OR: 0.64; 95%CI: 0.47–0.87). Peer education can promote HIV testing (OR = 3.19; 95%CI:2.13,4.79) and condom use (OR = 2.66, 95% CI: 2.11–3.36) while reduce equipment sharing (OR = 0.50; 95%CI:0.33,0.75) and unprotected sex (OR = 0.82; 95%CI: 0.72–0.94). Time trend analysis revealed that peer education had a consistent effect on behavior change for over 24 months and the different follow-up times were a source of heterogeneity. Conclusion: Our study shows that peer education is an effective tool with long-term impact for behavior change among high-risk HIV groups worldwide. Low and middle-income countries are encouraged to conduct large-scale peer education.

Objective: In vitro and animal studies suggest that purified anthocyanins have favorable effects on metabolic profiles, but clinical trials have reported inconsistent findings. Furthermore, no study has been specifically conducted among individuals with prediabetes. The aim of this study was to investigate whether purified anthocyanins could improve cardiometabolic risk factors in Chinese adults with early untreated hyperglycemia. Research Design and Methods: This was a 12-week randomized, double-blind, placebo-controlled trial. A total of 160 participants aged 40–75 years with prediabetes or early untreated diabetes were randomly allocated to receive either purified anthocyanins (320 mg/day, n = 80) or placebo (n = 80) of identical appearance. A three-hour oral glucose tolerance test (OGTT) was performed, and cardiometabolic biomarkers (glycated hemoglobin A1c (HbA1c), fasting and postprandial glucose, insulin, C-peptide, and lipids) were measured at baseline and at the end of the trial. Results: A total of 138 subjects completed the protocol. Compared with placebo, purified anthocyanins moderately reduced HbA1c (−0.14%, 95% CI: −0.23~−0.04%; p = 0.005), low-density lipoprotein-c (LDL-c) (−0.2 mmol/L, 95% CI: −0.38~−0.01, p = 0.04), apolipoprotein A-1 (apo A1) (0.09 g/L, 95% CI: 0.02~0.17; p = 0.02), and apolipoprotein B (apo B) (−0.07 g/L, 95% CI: −0.13~−0.01; p = 0.01) according to intention-to-treat analysis. Subgroup analyses suggested that purified anthocyanins were more effective at improving glycemic control, insulin sensitivity, and lipids among patients with elevated metabolic markers. Conclusions: The 12-week randomized controlled trials (RCT) in Chinese adults with prediabetes or early untreated diabetes indicated that purified anthocyanins favorably affected glycemic control and lipid profile. Future studies of a longer duration that explore the dose-response relationship among patients with cardiometabolic disorders are needed to confirm our findings.

Objective: Adopting a healthy lifestyle, including regular physical activity, is widely believed to decrease cancer risk. This study aimed to quantitatively establish the dose‐response relationships between total physical activity and the risk of breast, colon, lung, gastric, and liver cancers. Methods: A systematic review and dose‐response analysis were conducted using PubMed and Embase from January 1, 1980 to March 20, 2023. Prospective cohort studies that examined the association between physical activity and the risks of any of the 5 outcomes were included. The search was confined to publications in the English language with a specific focus on human studies. Physical activity is standardized by using the data from US National Health and Nutrition Examination Surveys (NHANES) and the Global Burden of Disease 2019 database. Results: A total of 98 studies, involving a combined population of 16,418,361 individuals, were included in the analysis. Among the included studies, 57 focused on breast cancer, 17 on lung cancer, 23 on colon cancer, 5 on gastric cancer, and 7 on liver cancer. Overall, elevated levels of physical activity exhibited an inverse correlation with the risk of cancer. The dose‐response curve for lung cancer exhibited a non‐linear pattern, with the greatest benefit risk reduction observed at 13,200 MET‐minutes/week of physical activity, resulting in a 14.7% reduction in risk (relative risk 0.853, uncertainty interval 0.798 to 0.912) compared to the inactive population. In contrast, the dose‐response curves for colon, gastric, breast, and liver cancers showed linear associations, indicating that heightened levels of total physical activity were consistently associated with reduced cancer risks. However, the increase in physical activity yielded a smaller risk reduction for colon and gastric cancers compared to breast and liver cancers. Compared to individuals with insufficient activity (total activity level < 600 MET‐minutes/week), individuals with high levels of activity (≥ 8,000 MET‐minutes/week) experienced a 10.3% (0.897, 0.860 to 0.934) risk reduction for breast cancer; 5.9% (0.941, 0.884 to 1.001) for lung cancer; 7.1% (0.929, 0.909 to 0.949) for colon cancer; 5.1% (0.949, 0.908 to 0.992) for gastric cancer; 17.1% (0.829, 0.760 to 0.903) for liver cancer. Conclusions: This study demonstrated a significant inverse relationship between total physical activity and the risk of breast, gastric, liver, colon, and lung cancers.

Hepatitis B surface antigen (HBsAg) seroclearance during treatment is associated with a better prognosis among patients with chronic hepatitis B (CHB). Significant gaps remain in our understanding on how to predict HBsAg seroclearance accurately and efficiently based on obtainable clinical information. This study aimed to identify the optimal model to predict HBsAg seroclearance. We obtained the laboratory and demographic information for 2,235 patients with CHB from the South China Hepatitis Monitoring and Administration (SCHEMA) cohort. HBsAg seroclearance occurred in 106 patients in total. We developed models based on four algorithms, including the extreme gradient boosting (XGBoost), random forest (RF), decision tree (DCT), and logistic regression (LR). The optimal model was identified by the area under the receiver operating characteristic curve (AUC). The AUCs for XGBoost, RF, DCT, and LR models were 0.891, 0.829, 0.619, and 0.680, respectively, with XGBoost showing the best predictive performance. The variable importance plot of the XGBoost model indicated that the level of HBsAg was of high importance followed by age and the level of hepatitis B virus (HBV) DNA. Machine learning algorithms, especially XGBoost, have appropriate performance in predicting HBsAg seroclearance. The results showed the potential of machine learning algorithms for predicting HBsAg seroclearance utilizing obtainable clinical data.