Bariatric surgery has been shown to impair bone health. This study aimed to investigate the fracture risk in patients after bariatric surgery versus propensity score-matched controls. The authors used the National Health Insurance Research Database of Taiwan and identified 2064 patients who underwent bariatric surgery during 2001 to 2009. These patients were matched to 5027 obese patients who did not receive bariatric surgery, using propensity score matching accounting for age, sex, Charlson Comorbidity Index, diabetes, hypertension, hyperlipidemia and the year morbid obesity was diagnosed. The authors followed the surgical and control cohorts to death, any diagnosis of fracture, or December 31, 2012, whichever occurred first. Cox proportional hazard regression models were used to calculate relative rates of fractures in the surgical group and control group. At the end of the 12-year study period, there were 183 fractures in the surgical group (mean follow-up 4.8 years) and 374 fractures in the matched control group (mean follow-up 4.9 years). Overall, there was a 1.21-fold [95% confidence interval (CI): 1.02–1.43] significantly increased risk of fracture in the surgical group compared with the control group. Stratified by surgical procedures, malabsorptive procedures showed a significantly higher fracture risk (1.47, 95% CI: 1.01–2.15). The Kaplan-Meier estimated fracture rates were 1.60% at 1 year, 2.37% at 2 years, 1.69% at 5 years, and 2.06% after 5 years for the surgical patients, compared with 1.51%, 1.65%, 1.53%, and 1.42%, respectively, for the matched controls. Adjusted analysis showed a trend towards an increased fracture risk, 1 to 2 years after bariatric surgery. (1.42, 95% CI: 0.99–2.05). Bariatric surgery was significantly associated with an increased risk of fractures, mainly with malabsorptive procedures, with a trend of an increased fracture risk 1 to 2 years after surgery. These results provide further evidence for the adverse effects of bariatric surgery on the risk of fractures.

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.

Objective Selenium is an essential micronutrient for human health. Although many observational and interventional studies have examined the associations between selenium and diabetes mellitus, the findings were inconclusive. This study aimed to investigate the relationship between serum selenium levels and prevalence of diabetes, and correlated the relationship to insulin resistance and central obesity. Research design and methods This was a hospital-based case–control study of 847 adults aged more than 40 years (diabetes: non-diabetes =1:2) in Northern Taiwan. Serum selenium was measured by an inductively coupled plasma-mass spectrometer. The association between serum selenium and diabetes was examined using multivariate logistic regression analyses. Results After adjusting for age, gender, current smoking, current drinking, and physical activity, the ORs (95% CI, p value) of having diabetes in the second (Q2), third (Q3), and fourth (Q4) selenium quartile groups were 1.24 (95% CI 0.78 to 1.98, p>0.05), 1.90 (95% CI 1.22 to 2.97, p<0.05), and 5.11 (95% CI 3.27 to 8.00, p<0.001), respectively, compared with the first (Q1) quartile group. Further adjustments for waist circumference and homeostatic model assessment-insulin resistance (HOMA-IR) largely removed the association of serum selenium levels with diabetes but not in the highest quartile (compared with Q1, Q3: 1.57, 95% CI 0.91 to 2.70, Q4: 3.79, 95% CI 2.17 to 6.32). Conclusions We found that serum selenium levels were positively associated with prevalence of diabetes. This is the first human study to link insulin resistance and central obesity to the association between selenium and diabetes. Furthermore, the association between selenium and diabetes was independent of insulin resistance and central obesity at high serum selenium levels. The mechanism behind warrants further confirmation.

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.