The coronavirus-disease 2019 (COVID-19) was announced as a global pandemic by the World Health Organization. Challenges arise concerning how to optimally support the immune system in the general population, especially under self-confinement. An optimal immune response depends on an adequate diet and nutrition in order to keep infection at bay. For example, sufficient protein intake is crucial for optimal antibody production. Low micronutrient status, such as of vitamin A or zinc, has been associated with increased infection risk. Frequently, poor nutrient status is associated with inflammation and oxidative stress, which in turn can impact the immune system. Dietary constituents with especially high anti-inflammatory and antioxidant capacity include vitamin C, vitamin E, and phytochemicals such as carotenoids and polyphenols. Several of these can interact with transcription factors such as NF-kB and Nrf-2, related to anti-inflammatory and antioxidant effects, respectively. Vitamin D in particular may perturb viral cellular infection via interacting with cell entry receptors (angiotensin converting enzyme 2), ACE2. Dietary fiber, fermented by the gut microbiota into short-chain fatty acids, has also been shown to produce anti-inflammatory effects. In this review, we highlight the importance of an optimal status of relevant nutrients to effectively reduce inflammation and oxidative stress, thereby strengthening the immune system during the COVID-19 crisis.

Many chronic conditions such as cancer, chronic obstructive pulmonary disease, type-2 diabetes, obesity, peripheral/coronary artery disease and auto-immune diseases are associated with low-grade inflammation. Closely related to inflammation is oxidative stress (OS), which can be either causal or secondary to inflammation. While a low level of OS is physiological, chronically increased OS is deleterious. Therefore, valid biomarkers of these signalling pathways may enable detection and following progression of OS/inflammation as well as to evaluate treatment efficacy. Such biomarkers should be stable and obtainable through non-invasive methods and their determination should be affordable and easy. The most frequently used inflammatory markers include acute-phase proteins, essentially CRP, serum amyloid A, fibrinogen and procalcitonin, and cytokines, predominantly TNFα, interleukins 1β, 6, 8, 10 and 12 and their receptors and IFNγ. Some cytokines appear to be disease-specific. Conversely, OS—being ubiquitous—and its biomarkers appear less disease or tissue-specific. These include lipid peroxidation products, e.g., F2-isoprostanes and malondialdehyde, DNA breakdown products (e.g., 8-OH-dG), protein adducts (e.g., carbonylated proteins), or antioxidant status. More novel markers include also –omics related ones, as well as non-invasive, questionnaire-based measures, such as the dietary inflammatory-index (DII), but their link to biological responses may be variable. Nevertheless, many of these markers have been clearly related to a number of diseases. However, their use in clinical practice is often limited, due to lacking analytical or clinical validation, or technical challenges. In this review, we strive to highlight frequently employed and useful markers of inflammation-related OS, including novel promising markers.

A healthy gut microbiota (GM) is paramount for a healthy lifestyle. Alterations of the GM have been involved in the aetiology of several chronic diseases, including obesity and type 2 diabetes, as well as cardiovascular and neurodegenerative diseases. In pathological conditions, the diversity of the GM is commonly reduced or altered, often toward an increased Firmicutes/Bacteroidetes ratio. The colonic fermentation of dietary fiber has shown to stimulate the fraction of bacteria purported to have beneficial health effects, acting as prebiotics, and to increase the production of short chain fatty acids, e.g. propionate and butyrate, while also improving gut epithelium integrity such as tight junction functionality. However, a variety of phytochemicals, often associated with dietary fiber, have also been proposed to modulate the GM. Many phytochemicals possess antioxidant and anti-inflammatory properties that may positively affect the GM, including polyphenols, carotenoids, phytosterols/phytostanols, lignans, alkaloids, glucosinolates and terpenes. Some polyphenols may act as prebiotics, while carotenoids have been shown to alter immunoglobulin A expression, an important factor for bacteria colonization. Other phytochemicals may interact with the mucosa, another important factor for colonization, and prevent its degradation. Certain polyphenols have shown to influence bacterial communication, interacting with quorum sensing. Finally, phytochemicals can be metabolized in the gut into bioactive constituents, e.g. equol from daidzein and enterolactone from secoisolariciresinol, while bacteria can use glycosides for energy. In this review, we strive to highlight the potential interactions between prominent phytochemicals and health benefits related to the GM, emphasizing their potential as adjuvant strategies for GM-related diseases.

Background: Chronic inflammation has been associated with insulin resistance and related metabolic dysregulation, including type 2 diabetes mellitus (T2DM). Several non modifiable (i.e. genetic predisposition) and modifiable (i.e. sedentary lifestyle, energy-dense food) risk factors were suggested to explain the mechanisms involved in the development of inflammation, but are difficult to assess in clinical routine. The present study aimed to identify easy to asses clinical and biological risk factors associated with inflammation in patients with T2DM. Methods: One hundred nine patients (51 men, 58 women), 28–60 years old, from seven primary healthcare centers in Gaza City, Palestine, took part to the cross-sectional study (November 2013–May 2014). Study participants had T2DM with no history of inflammatory diseases, cardiovascular diseases, medication and/or any health condition that might affect the inflammatory markers, interleukin 6 (IL-6) and C-reactive protein (CRP). Inflammation was defined for IL-6 ≥ 2 pg/mL and CRP ≥ 6 mg/L. Multivariable logistic regressions were used to identify the relationship between inflammation and clinical and biological risk factors. Results: After adjustment for age and gender, inflammation seems to increase with increased body mass index (BMI) (OR: 1.427 [1.055–1.931]), increased fasting blood glucose (OR: 1.029 [1.007–1.052]) and decreased adiponectin values (OR: 0.571 [0.361–0.903]). There were also significant relationships between inflammation and BMI (OR: 1.432 [1.042–1.968]), fasting blood glucose (OR: 1.029 [1.006–1.052]) and adiponectin (OR: 0.569 [0.359–0.902]), after adjustment for smoking habits and physical activity. Conclusion: Managing obesity and associated complications (i.e. hyperglycemia, high adiponectin levels) might help decreasing inflammation in individuals with T2DM.

Background: Bioelectrical impedance analysis (BIA) is a widely used method to assess total body fat (TBF) depots characterising obesity. Automated BIA devices provide an inexpensive and easy assessment of TBF, making them widely available to the general public and healthcare providers without specific qualification to assess body composition. The equations included in the automated BIA devices have been developed in very few specific populations, which means that they are not suitable to assess TBF for everyone and need to be validated before use in other populations.The aimof the present work is to evaluate the accuracy of the automated BIA device Tanita® BC-532 in youth of White European ethnicity, compared with the dual-energy x-ray absorptiometry (DEXA), gold standard measurement of TBF.Methods: Total body fat percentage (TBF%) was measured with the BIA device Tanita® BC-532 and DEXA (Hologic® QDR4500W) in 197 youth of White European ethnicity (N = 104 girls), 7-17 years old, and visiting theDiabetes & Endocrinology Care Paediatrics Clinic, Centre Hospitalier de Luxembourg,for overweight or obesity management.Results: TBF% evaluated with BIA was significantly correlated with TBF% measured with DEXA in both boys (r_Pearson = 0.617) and girls (r_Pearson = 0.648) (p < 10^− 4). However, the residual mean between the assessment of TBF% by BIA and by DEXA [TBF_BIA(%)-TBF_DEXA(%)] is extremely high (mean ± standard deviation = 10.52% ± 5.22% in boys, respectively 9.96% ± 4.40% in girls). The maximal absolute residual value is also very high, about 24% in both genders.Conclusions: The automated BIA device Tanita® BC-532 appears to be not accurate to assess total body fat in youth with overweight or obesity. There is a need to calibrate the BIA device before its use in the populations where it was not previously validated.

The analyses of geographic variations in the prevalence of major chronic conditions, such as overweight and obesity, are an important public health tool to identify “hot spots” and inform allocation of funding for policy and health promotion campaigns, yet rarely performed. Here we aimed at exploring, for the first time in Luxembourg, potential geographic patterns in overweight/obesity prevalence in the country, adjusted for several demographic, socioeconomic, behavioural and health status characteristics. Data came from 720 men and 764 women, 25–64 years old, who participated in the European Health Examination Survey in Luxembourg (2013–2015). To investigate the geographical variation, geo-additive semi-parametric mixed model and Bayesian modelisations based on Markov Chain Monte Carlo techniques for inference were performed. Large disparities in the prevalence of overweight and obesity were found between municipalities, with the highest rates of obesity found in 3 municipalities located in the South-West of the country. Bayesian approach also underlined a nonlinear effect of age on overweight and obesity in both genders (significant in men) and highlighted the following risk factors: 1. country of birth for overweight in men born in a non-European country (Posterior Odds Ratio (POR): 3.24 [1.61–8.69]) and women born in Portugal (POR: 2.44 [1.25–4.43]), 2. low educational level (secondary or below) for overweight (POR: 1.66 (1.06–2.72)] and obesity (POR:2.09 [1.05–3.65]) in men, 3. single marital status for obesity in women (POR: 2.20 [1.24–3.91]), 4.fair (men: POR: 3.19 [1.58–6.79], women: POR: 2.24 [1.33–3.73]) to very bad health perception (men: POR: 15.01 [2.16–98.09]) for obesity, 5. sleeping more than 6 hours for obesity in unemployed men (POR: 3.66 [2.02–8.03]). Protective factors highlighted were: 1. single marital status against overweight (POR: [0.60 (0.38–0.96)]) and obesity (POR: 0.39 [0.16–0.84]) in men, 2. the fact to be widowed against overweight in women (POR: [0.30 (0.07–0.86)], as well as a non European country of birth (POR: 0.49 [0.19–0.98]), tertiary level of education (POR: 0.34 [0.18–0.64]), moderate alcohol consumption (POR: 0.54 [0.36–0.90]) and aerobic physical activity practice (POR: 0.44 [0.27–0.77]) against obesity in women. A double burden of environmental exposure due to historic mining and industrial activities and past economic vulnaribility in the South-West of the country may have participated to the higher prevalence of obesity found in this region. Other demographic, socioeconomic, behavioural and health status covariates could have been involved as well.