Jiaqi Zhang

Metabolic factors are major and controllable risk factors for cardiovascular diseases (CVD), and few studies have described this burden. We aim to assess it from 1990 to 2019 and predict the trends through 2034. Global Burden of Disease (GBD) provides data on sex, age, and socio-demographic index (SDI) levels. Numbers, age-standardized death rates (ASDR) and estimated annual percentage change (EAPC) were used. Future trends were estimated by NORDPRED model. The deaths cases of metabolic-related CVD increased from 8.61 million (95% UI: 7.91–9.29) to 13.71 million (95% UI: 12.24–14.94) globally. The ASDR continued to decline globally (EAPC = −1.36). The burden was heavier in male and middle-aged people and elderly people. CVD-related ASDR caused by high systolic blood pressure (SBP) had a downward trend globally (EAPC = −1.45), while trends of high body mass index (BMI) (EAPC = 1.29, 1.97, 0.92) and fasting plasma glucose (FPG) (EAPC = 0.95, 1.08, 0.46) were increasing in the middle, low-middle, and low SDI regions, respectively. Compared to 2015–2019, cumulative deaths will increase by 27.85% from 2030 to 2034, while ASDR will decrease 10.47%. The metabolic-related CVD burden remained high globally and deaths will continue to rise in the future. Men, middle-aged and elderly people were focus of concern. High SBP was globally well-managed over the past 30 years, but the CVD burden due to high BMI and FPG remained high. Exceptional initiatives are needed to regarding interventions targeting high BMI and FPG in middle and lower SDI regions.

Background: This observational cross-sectional study was designed to explore the effects of a low-carbohydrate diet (LCD) and a low-fat diet (LFD) on metabolic-dysfunction-associated fatty liver disease (MAFLD). Methods: This study involved 3961 adults. The associations between LCD/LFD scores and MAFLD were evaluated utilizing a multivariable logistic regression model. Additionally, a leave-one-out model was applied to assess the effect of isocaloric substitution of specific macronutrients. Results: Participants within the highest tertile of healthy LCD scores (0.63; 95% confidence interval [CI], 0.45–0.89) or with a healthy LFD score (0.64; 95%CI, 0.48–0.86) faced a lower MAFLD risk. Furthermore, compared with tertile 1, individuals with unhealthy LFD scores in terile 2 or tertile 3 had 49% (95%CI, 1.17–1.90) and 77% (95%CI, 1.19–2.63) higher risk levels for MAFLD, respectively. Conclusions: Healthy LCD and healthy LFD are protective against MAFLD, while unhealthy LFD can increase the risk of MAFLD. Both the quantity and quality of macronutrients might have significant influences on MAFLD.