Non-alcoholic fatty liver disease (NAFLD) is an emerging chronic liver disease that may lead to liver cirrhosis and hepatocellular carcinoma. We aimed to determine the association between the prevalence of metabolic syndrome (MetS) and NAFLD severity using semi-quantitative ultrasonography (US). A total of 614 participants were recruited from the community. NAFLD was evaluated according to the ultrasonographic Fatty Liver Indicator (US-FLI), which is a semi-quantitative liver ultrasound score. Insulin resistance was estimated with the homeostasis model assessment index for insulin resistance (HOMA-IR). NAFLD and MetS were found in 53.7 and 17.3% of the participants, respectively. Linear relationships were found between the severity of NAFLD and waist circumference, fasting glucose, HOMA-IR, triglycerides, HDL-C and blood pressure. After adjusting for confounding factors, i.e., body mass index and HOMA-IR, the odds ratios for MetS were 3.64 (95% confidence interval (CI): 1.5–8.83) for those with mild NAFLD and 9.4 (95% CI: 3.54–24.98) for those with moderate-to-severe NAFLD compared to those without NAFLD. The combination of the HOMA-IR and US-FLI scores better differentiated MetS than the HOMA-IR alone. In addition to obesity, the severity of NAFLD and the HOMA-IR both play important roles in MetS. Whether NAFLD is a component of MetS warrants further research.

Sarcopenia, highly linked with fall, frailty, and disease burden, is an emerging problem in aging society. Higher protein intake has been suggested to maintain nitrogen balance. Our objective was to investigate whether pre-sarcopenia status was associated with lower protein intake. A total of 327 community-dwelling elderly people were recruited for a cross-sectional study. We adopted the multivariate nutrient density model to identify associations between low muscle mass and dietary protein intake. The general linear regression models were applied to estimate skeletal muscle mass index across the quartiles of total protein and vegetable protein density. Participants with diets in the lowest quartile of total protein density (<13.2%) were at a higher risk for low muscle mass (odds ratio (OR) 3.03, 95% confidence interval (CI) 1.37–6.72) than those with diets in the highest quartile (≥17.2%). Similarly, participants with diets in the lowest quartile of vegetable protein density (<5.8%) were at a higher risk for low muscle mass (OR 2.34, 95% CI 1.14–4.83) than those with diets in the highest quartile (≥9.4%). Furthermore, the estimated skeletal muscle mass index increased significantly across the quartiles of total protein density (p = 0.023) and vegetable protein density (p = 0.025). Increasing daily intakes of total protein and vegetable protein densities appears to confer protection against pre-sarcopenia status.

Global burden of COVID-19 has not been well studied, disability-adjusted life years(DALYs) and value of statistical life(VSL) metrics were therefore proposed to quantify its impacts on health and economic loss globally. The life expectancy, cases, and death numbers of COVID-19 until 30th April 2021 were retrieved from open data to derive the epidemiological profiles and DALYs (including years of life lost (YLL) and years loss due to disability (YLD)) by four periods. The VSL estimates were estimated by using hedonic wage method(HWM) and contingent valuation method(CVM). The estimate of willingness to pay using CVM was based on the meta-regression mixed model. Machine learning method was used for classification. Globally, DALYs (in thousands) due to COVID-19 was tallied as 31,930 from Period I to IV. YLL dominated over YLD. The estimates of VSL were US$591 billion and US$5,135 billion based on HWM and CVM, respectively. The estimate of VSL increased from US$579 billion in Period I to US$2160 billion in Period IV using CVM. The higher the human development index(HDI), the higher the value of DALYs and VSL. However, there exits the disparity even at the same level of HDI. Machine learning analysis categorized eight patterns of global burden of COVID-19 with a large variation from US$0.001 billion to US$691.4 billion. Global burden of COVID-19 pandemic resulted in substantial health and value of life loss particularly in developed economies. Classifications of such health and economic loss is informative to early preparation of adequate resource to reduce impacts.