Abstract

The WHO considers non-communicable diseases (NCDs), such as obesity, a major risk factor for becoming seriously ill with 2019 novel coronavirus (COVID-19) (1). A study by the UK Intensive Care National Audit and Research Centre indicates that two thirds of people who developed serious or fatal COVID-19-related complications were overweight or obese (2). The report includes data from all COVID-19 admissions in intensive care units in the UK until midnight, March 19, 2020. The study shows that almost 72 % of those in critical care units are either overweight or with obesity suggesting the impact of obesity in seriously ill COVID-19 patients.

Abstract

undefined: The world is in the grip of the COVID-19 pandemic. Public health measures that can reduce the risk of infection and death in addition to quarantines are desperately needed. This article reviews the roles of vitamin D in reducing the risk of respiratory tract infections, knowledge about the epidemiology of influenza and COVID-19, and how vitamin D supplementation might be a useful measure to reduce risk. Through several mechanisms, vitamin D can reduce risk of infections. Those mechanisms include inducing cathelicidins and defensins that can lower viral replication rates and reducing concentrations of pro-inflammatory cytokines that produce the inflammation that injures the lining of the lungs, leading to pneumonia, as well as increasing concentrations of anti-inflammatory cytokines. Several observational studies and clinical trials reported that vitamin D supplementation reduced the risk of influenza, whereas others did not. Evidence supporting the role of vitamin D in reducing risk of COVID-19 includes that the outbreak occurred in winter, a time when 25-hydroxyvitamin D (25(OH)D) concentrations are lowest; that the number of cases in the Southern Hemisphere near the end of summer are low; that vitamin D deficiency has been found to contribute to acute respiratory distress syndrome; and that case-fatality rates increase with age and with chronic disease comorbidity, both of which are associated with lower 25(OH)D concentration. To reduce the risk of infection, it is recommended that people at risk of influenza and/or COVID-19 consider taking 10,000 IU/d of vitamin D for a few weeks to rapidly raise 25(OH)D concentrations, followed by 5000 IU/d. The goal should be to raise 25(OH)D concentrations above 40-60 ng/mL (100-150 nmol/L). For treatment of people who become infected with COVID-19, higher vitamin D doses might be useful. Randomized controlled trials and large population studies should be conducted to evaluate these recommendations.

Abstract

Type 2 diabetes (T2D) is a major comorbidity of COVID-19. However, the impact of blood glucose (BG) control on the degree of required medical interventions and on mortality in patients with COVID-19 and T2D remains uncertain. Thus, we performed a retrospective, multi-centered study of 7,337 cases of COVID-19 in Hubei Province, China, among which 952 had pre-existing T2D. We found that subjects with T2D required more medical interventions and had a significantly higher mortality (7.8% versus 2.7%; adjusted hazard ratio [HR], 1.49) and multiple organ injury than the non-diabetic individuals. Further, we found that well-controlled BG (glycemic variability within 3.9 to 10.0 mmol/L) was associated with markedly lower mortality compared to individuals with poorly controlled BG (upper limit of glycemic variability exceeding 10.0 mmol/L) (adjusted HR, 0.14) during hospitalization. These findings provide clinical evidence correlating improved glycemic control with better outcomes in patients with COVID-19 and pre-existing T2D.

Abstract

BACKGROUND Many clinical trials have been conducted to verify the effects of interventions for prevention of type 2 diabetes (T2D) using different treatments and outcomes. The aim of this study was to compare the effectiveness of lifestyle modifications (LM) with other treatments in persons at high risk of T2D by a network meta-analysis (NMA). METHODS Searches were performed of PUBMED up to January 2018 to identify randomized controlled trials. The odds ratio (OR) with onset of T2D at 1 year in the intervention group (LM, dietary, exercise, or medication) versus a control group (standard treatments or placebo) were the effect sizes. Frequentist and Bayesian NMAs were conducted. RESULTS Forty-seven interventions and 12 treatments (20,113 participants) were used for the analyses. The OR in the LM was approximately 0.46 (95% CI: 0.33 to 0.61) times lower compared to the standard intervention by the Bayesian approach. The effects of LM compared to other treatments by indirect comparisons were not significant. CONCLUSIONS This meta-analysis further strengthened the evidence that LM reduces the onset of T2D compared to standard and placebo interventions and appears to be at least as effective as nine other treatments in preventing T2D.

Abstract

BACKGROUND Dietary fiber has been recommended for glucose control, and typically low intakes are observed in the general population. The role of fiber in glycemic control in reported literature is inconsistent and few reports are available in populations with type 1 diabetes (T1D). METHODS Using data from the Coronary Artery Calcification in Type 1 Diabetes (CACTI) study [n = 1257; T1D: n = 568; non-diabetic controls: n = 689] collected between March 2000 and April 2002, we examined cross-sectional (baseline) and longitudinal (six-year follow-up in 2006-2008) associations of dietary fiber and HbA1c. Participants completed a validated food frequency questionnaire, and a physical examination and fasting biochemical analyses (12 h fast) at baseline visit and at the year 6 visit. We used a linear regression model stratified by diabetes status, and adjusted for age, sex and total calories, and diabetes duration in the T1D group. We also examined correlations of dietary fiber with HbA1c. RESULTS Baseline dietary fiber intake and serum HbA1c in the T1D group were 16 g [median (IQ): 11-22 g) and 7.9 ± 1.3% mean (SD), respectively, and in the non-diabetic controls were 15 g [median (IQ): 11-21 g) and 5.4 ± 0.4%, respectively. Pearson partial correlation coefficients revealed a significant but weak inverse association of total dietary fiber with HbA1c when adjusted for age, sex, diabetes status and total calories (r = - 0.07, p = 0.01). In the adjusted linear regression model at baseline, total dietary fiber revealed a significant inverse association with HbA1c in the T1D group [β ± SE = - 0.32 ± 0.15, p = 0.034], as well as in the non-diabetic controls [- 0.10 ± 0.04, p = 0.009]. However, these results were attenuated after adjustment for dietary carbohydrates, fats and proteins, or for cholesterol and triglycerides. No such significance was observed at the year 6 follow-up, and with the HbA1c changes over 6 years. CONCLUSION Thus, at observed levels of intake, total dietary fiber reveals modest inverse associations with poor glycemic control. Future studies must further investigate the role of overall dietary quality adjusting for fiber-rich foods in T1D management.

Abstract

The incidence of skipping breakfast in pediatric subjects is rising, and a relationship with overweight (OW) and obesity (OB) has been shown. Associations with cardiovascular outcomes and skipping breakfast in adults have been reported. The purpose of this systematic review was to summarize the association of skipping breakfast with body weight and metabolic outcomes in the pediatric population. We searched relevant databases (2008⁻2018) and identified 56 articles, of which 39 were suitable to be included, basing on inclusion criteria (observational; defined breakfast skipping; weight and/or metabolic outcomes). Overall, 286,804 children and adolescents living in 33 countries were included. The definitions of OW/OB, skipping breakfast, and the nutrient assessment were highly heterogeneous. Confounding factors were reported infrequently. The prevalence of skipping breakfast ranged 10⁻30%, with an increasing trend in adolescents, mainly in girls. Skipping breakfast was associated with OW/OB in the 94.7% of the subjects. The lack of association was shown mainly in infants. Moreover, 16,130 subjects were investigated for cardiometabolic outcomes. Skipping breakfast was associated with a worse lipid profile, blood pressure levels, insulin-resistance, and metabolic syndrome. Five studies reported a lower quality dietary intake in breakfast skippers. This review supports skipping breakfast as an easy marker of the risk of OW/OB and metabolic diseases, whether or not it is directly involved in causality. We encourage intervention studies using standardized and generalizable indicators. Data on confounders, time of fasting, chronotypes, and nutrition quality are needed to establish the best practice for using it as a tool for assessing obesity risk.

Abstract

undefined: Few studies have investigated the association between selenium and metabolic syndrome. This study aimed to explore the associations between the serum selenium level and metabolic syndrome as well as examining each metabolic factor. In this case-control study, the participants were 1165 adults aged ≥40 (65.8 ± 10.0) years. Serum selenium was measured by inductively coupled plasma-mass spectrometry. The associations between serum selenium and metabolic syndrome were examined by multivariate logistic regression analyses. The least square means were computed by general linear models to compare the serum selenium levels in relation to the number of metabolic factors. The mean serum selenium concentration was 96.34 ± 25.90 μg/L, and it was positively correlated with waist circumference, systolic blood pressure, triglycerides, fasting glucose, and homeostatic model assessment insulin resistance (HOMA-IR) in women, but it was only correlated with fasting glucose and HOMA-IR in men. After adjustment, the odds ratios (ORs) of having metabolic syndrome increased with the selenium quartile groups ( for trend: <0.05), especially in women. The study demonstrated that the serum selenium levels were positively associated with metabolic syndrome following a non-linear dose⁻response trend. Selenium concentration was positively associated with insulin resistance in men and women, but it was associated with adiposity and lipid metabolism in women. The mechanism behind this warrants further confirmation.

Abstract

undefined: Previous studies indicate that eating behaviours and food cravings are associated with increased BMI and obesity. However, the interaction between these behaviours and other variables such as age, sex, BMI and genetics is complex. This study aimed to investigate the relationships between eating behaviours and food cravings, and to examine the influence of age, sex, body mass index (BMI) and fat mass and obesity-associated ( ) genotype on these relationships. A total of 475 participants (252 female, 223 male, BMI: 25.82 ± 6.14 kg/m², age: 30.65 ± 14.20 years) completed the revised 18-question version of the Three Factor Eating Questionnaire (TFEQ-R18) to assess cognitive restraint, uncontrolled eating and emotional eating, and the Food Cravings Inventory (FCI) to assess cravings for fatty food, sweet food, carbohydrates and fast food. DNA samples were genotyped for the rs9939609 polymorphism in the obesity-linked gene . Questionnaire data was analysed for associations between the TFEQ-R18 and FCI subscales for the whole study group, and the group divided by sex, genotype and age (≤25 years versus >25 years). Finally, mediation analysis was used to explore the relationships between BMI, cognitive restraint and food cravings. AA + AT genotype was associated with increased BMI, but not with differences in eating behavior scores or food craving scores; age was associated with increased BMI and decreases in food craving scores in which this effect was stronger in women compared to men. Increased cognitive restraint was associated with decreased food craving scores in the ≤25 years group. Mediation analysis demonstrated that in this group the association between BMI and reduced food cravings was mediated by cognitive restraint indicating that in this age group individuals use cognitive restraint to control their food cravings. The positive correlation between age and BMI confirms previous results but the findings of this study show that age, sex, genotype and BMI have an influence on the relationships between eating behaviours and food cravings and that these variables interact.

Abstract

undefined: Probiotic yogurt is suggested as a nutritional approach in type 2 diabetes (T2D) and obesity. We performed a systematic review and meta-analysis of randomized controlled trials (RCTs) evaluating the effects of probiotic yogurt on glycemic outcomes in T2D or obesity. The databases used to search for RCTs included Medline and Scopus. The RCTs were eligible if outcomes included selected glycemic markers. In nine eligible trials, 237 and 235 subjects were in treatment (probiotic yogurt) and control (mostly conventional yogurt) groups, respectively. There was no significant difference for pooled unstandardized mean difference (USMD) hemoglobin A1c (HbA1c) by probiotic yogurt compared with the control in T2D (USMD: -0.366; 95% CI: -0.755, 0.024, = 0.066) and obesity (USMD: 0.116, 95% CI: -0.007, 0.238, = 0.065). Similarly, there were no effects of probiotic yogurt on fasting blood glucose, fasting insulin, or insulin resistance (estimated by homeostatic model assessment of insulin resistance (HOMA-IR)) in either T2D or obesity. In conclusion, the present meta-analysis has not demonstrated the benefits of consuming probiotic compared with conventional yogurt for improving glucose control in patients with diabetes or obesity. Larger trials are needed to verify the benefits of probiotic and/or conventional yogurt or other probiotic fermented milk (e.g., kefir) on glycemic markers in patients with diabetes and obesity.

Abstract

undefined: The link between fibromyalgia syndrome (FMS) and obesity has not been thoroughly investigated. The purpose of this study was to examine the relationships among body mass index (BMI) and body composition parameters, including fat mass, fat mass percentage, and visceral fat, as well as FMS features, such as tender point count (TPC), pain, disease activity, fatigue, sleep quality, and anxiety, in a population of FMS women and healthy controls. A total of seventy-three women with FMS and seventy-three healthy controls, matched on weight, were included in this cross-sectional study. We used a body composition analyzer to measure fat mass, fat mass percentage, and visceral fat. Tender point count (TPC) was measured by algometry pressure. The disease severity was measured with the Fibromyalgia Impact Questionnaire (FIQ-R) and self-reported global pain was evaluated with the visual analog scale (VAS). To measure the quality of sleep, fatigue, and anxiety we used the Pittsburgh Sleep Quality Questionnaire (PSQI), the Spanish version of the multidimensional fatigue inventory (MFI), and the Beck Anxiety Inventory (BAI), respectively. Of the women in this study, 38.4% and 31.5% were overweight and obese, respectively. Significant differences in FIQ-R.1 (16.82 ± 6.86 vs. 20.66 ± 4.71, = 0.030), FIQ-R.3 (35.20 ± 89.02 vs. 40.33 ± 5.60, = 0.033), and FIQ-R total score (63.87 ± 19.12 vs. 75.94 ± 12.25, = 0.017) among normal-weight and overweight FMS were observed. Linear analysis regression revealed significant associations between FIQ-R.2 (β(95% CI)= 0.336, (0.027, 0.645), = 0.034), FIQ-R.3 (β(95% CI)= 0.235, (0.017, 0.453), = 0.035), and FIQ-R total score (β(95% CI)= 0.110, (0.010, 0.209), = 0.032) and BMI in FMS women after adjusting for age and menopause status. Associations between sleep latency and fat mass percentage in FMS women (β(95% CI)= 1.910, (0.078, 3.742), = 0.041) and sleep quality and visceral fat in healthy women (β(95% CI)= 2.614, (2.192, 3.036), = 0.008) adjusted for covariates were also reported. The higher BMI values are associated with poor FIQ-R scores and overweight and obese women with FMS have higher symptom severity. The promotion of an optimal BMI might contribute to ameliorate some of the FMS symptoms.