Obesity considerations during the COVID-19 outbreak.

The worldwide population is facing a double burden of epidemic, the COVID-19 and obesity. This is even more alarming as obesity increases the COVID-19 severity. However, the relationship between obesity and COVID-19 severity is more complex than a simple association with BMI. In particular, obesity has been associated with low death rates in patients with acute respiratory distress syndrome, a fatal comorbidity to COVID-19, possibly due to the obesity paradox. Also, visceral adiposity could be a major risk factor for COVID-19 severity, due to its immune activation component, release of angiotensin-converting enzyme 2 and involvement in the cytokine storm, hypercoagulability and embolism. A poor antioxidant nutritional status also weakens the immune system, increasing inflammation and infection risk. Moreover, the COVID-19 lockdown might impact lifestyle patterns, mental health and weight bias, worsening the obesity then COIVD-19 situation. On the other hand, health care expenses and productivity loss are expected to increase during the concomitant epidemics. The co-occurrence of obesity and COVID-19 is a major challenge at both public health and economic levels that should urgently be taken into consideration. The identification of COVID-19 weight related risk factors and the development of appropriate weight management programs are needed to tackle the concomitant epidemics.

Cardiometabolic risk: leg fat is protective during childhood.

BACKGROUND: Childhood obesity is associated with early cardiometabolic risk (CMR), increased risk of adulthood obesity, and worse health outcomes. Leg fat mass (LFM) is protective beyond total fat mass (TFM) in adults. However, the limited evidence in children remains controversial. OBJECTIVE: We investigated the relationship between LFM and CMR factors in youth. SUBJECTS: A total of 203 overweight/obese children, 7-17-yr-old, followed in the Pediatric Clinic, Luxembourg. METHODS: TFM and LFM by dual energy x-ray absorptiometry and a detailed set of CMR markers were analyzed. RESULTS: After TFM, age, sex, body mass index (BMI) Z-score, sexual maturity status, and physical activity adjustments, negative significant partial correlations were shown between LFM and homeostasis model assessment of insulin resistance (HOMA) (variance explained: 6.05% by LFM*; 7.18% by TFM**), fasting insulin (variance explained: 5.71% by LFM*; 6.97% by TFM**), triglycerides (variance explained: 3.96% by LFM*; 2.76% by TFM*), systolic blood pressure (variance explained: 2.68% by LFM*; 4.33% by TFM*), C-reactive protein (variance explained: 2.31% by LFM*; 4.28% by TFM*), and resistin (variance explained: 2.16% by LFM*; 3.57% by TFM*). Significant positive partial correlations were observed between LFM and high-density lipoprotein (HDL) cholesterol (variance explained: 4.16% by LFM*) and adiponectin (variance explained: 3.09% by LFM*) (*p-value < 0.05 and **p-value < 0.001). In order to adjust for multiple testing, Benjamini-Hochberg method was applied and the adjusted significance level was determined for each analysis. LFM remained significant in the aforementioned models predicting HOMA, fasting insulin, triglycerides, and HDL cholesterol (Benjamini and Hochberg corrected p-value < 0.01). CONCLUSIONS: LFM is protective against CMR in children, at least in terms of insulin resistance and adverse blood lipid profiles.

Adding anthropometric measures of regional adiposity to BMI improves prediction of cardiometabolic, inflammatory and adipokines profiles in youths: a cross-sectional study.

BACKGROUND: Paediatric research analysing the relationship between the easy-to-use anthropometric measures for adiposity and cardiometabolic risk factors remains highly controversial in youth. Several studies suggest that only body mass index (BMI), a measure of relative weight, constitutes an accurate predictor, whereas others highlight the potential role of waist-to-hip ratio (WHR), waist circumference (Waist C), and waist-to-height ratio (WHtR). In this study, we examined the effectiveness of adding anthropometric measures of body fat distribution (Waist C Z Score, WHR Z Score and/or WHtR) to BMI Z Score to predict cardiometabolic risk factors in overweight and obese youth. We also examined the consistency of these associations with the "total fat mass + trunk/legs fat mass" and/or the "total fat mass + trunk fat mass" combinations, as assessed by dual energy X-ray absorptiometry (DXA), the gold standard measurement of body composition. METHODS: Anthropometric and DXA measurements of total and regional adiposity, as well as a comprehensive assessment of cardiometabolic, inflammatory and adipokines profiles were performed in 203 overweight and obese 7-17 year-old youths from the Paediatrics Clinic, Centre Hospitalier de Luxembourg. RESULTS: Adding only one anthropometric surrogate of regional fat to BMI Z Score improved the prediction of insulin resistance (WHR Z Score, R(2): 45.9%. Waist C Z Score, R(2): 45.5%), HDL-cholesterol (WHR Z Score, R(2): 9.6%. Waist C Z Score, R(2): 10.8%. WHtR, R(2): 6.5%), triglycerides (WHR Z Score, R(2): 11.7%. Waist C Z Score, R(2): 12.2%), adiponectin (WHR Z Score, R(2): 14.3%. Waist C Z Score, R(2): 17.7%), CRP (WHR Z Score, R(2): 18.2%. WHtR, R(2): 23.3%), systolic (WHtR, R(2): 22.4%), diastolic blood pressure (WHtR, R(2): 20%) and fibrinogen (WHtR, R(2): 21.8%). Moreover, WHR Z Score, Waist C Z Score and/or WHtR showed an independent significant contribution according to these models. These results were in line with the DXA findings. CONCLUSIONS: Adding anthropometric measures of regional adiposity to BMI Z Score improves the prediction of cardiometabolic, inflammatory and adipokines profiles in youth.

Geographical variation of overweight, obesity and related risk factors: Findings from the European Health Examination Survey in Luxembourg, 2013-2015.

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.

Screening for primary hyperparathyroidism before thyroid surgery: A prospective study.

BACKGROUND: Misdiagnosed primary hyperparathyroidism (PHPT) during thyroid surgery may lead to a difficult reoperation. Because PHPT is often asymptomatic, calcium measurements have been recommended before thyroid surgery, but no study has focused on the results of a prospective PHPT screening. METHODS: The prospective study of 748 patients consisted of 2-step screening of calcium measurement in all patients (normal range, 2.2 to 2.6 mmol/L, 8.8 to 10.4 mg/dL). If the calcium level was greater than 2.49 mmol/L (9.9 mg/dL), parathyroid hormone level (PTH; normal range, 11 to 65 pg/mL) and second calcium measurements were obtained. Positive screening was defined by 2 calcium levels greater than 2.49 mmol/L (9.9 mg/dL) and PTH level greater than 49 pg/mL. In patients with negative screening, we evaluated the number of parathyroid incidentalomas. In patients with positive screening, we rated parathyroid adenomas discovered as "easily accessible" or "requiring specific dissection." We assumed that the former could have been incidentally found by a surgeon unaware of calcium value. The cost estimation was based on French national health system databases. RESULTS: In the 9 patients with positive screening, 9 had parathyroid adenomas, 3 of them requiring specific dissection. In the 739 patients with negative screening, 12 had surgical incidentalomas and 2 had postoperative PHPT diagnosis. CONCLUSIONS: Our screening was not exhaustive, but it avoided a reoperation for missed PHPT in 3 patients. Population screening cost less than 3 reoperations. Other strategies, more exhaustive and/or cost-effective, should be investigated.

VAT=TAAT-SAAT: innovative anthropometric model to predict visceral adipose tissue without resort to CT-Scan or DXA.

OBJECTIVE: To investigate whether a combination of a selected but limited number of anthropometric measurements predicts visceral adipose tissue (VAT) better than other anthropometric measurements, without resort to medical imaging. HYPOTHESIS: Abdominal anthropometric measurements are total abdominal adipose tissue indicators and global measures of VAT and SAAT (subcutaneous abdominal adipose tissue). Therefore, subtracting the anthropometric measurement the more correlated possible with SAAT while being the least correlated possible with VAT, from the most correlated abdominal anthropometric measurement with VAT while being highly correlated with TAAT, may better predict VAT. DESIGN AND METHODS: BMI participants' range was from 16.3 to 52.9 kg m(-2) . Anthropometric and abdominal adipose tissues data by computed tomography (CT-Scan) were available in 253 patients (18-78 years) (CHU Nord, Marseille) and used to develop the anthropometric VAT prediction models. RESULTS: Subtraction of proximal thigh circumference from waist circumference, adjusted to age and/or BMI, predicts better VAT (Women: VAT = 2.15 × Waist C - 3.63 × Proximal Thigh C + 1.46 × Age + 6.22 × BMI - 92.713; R(2) = 0.836. Men: VAT = 6 × Waist C - 4.41 × proximal thigh C + 1.19 × Age - 213.65; R(2) = 0.803) than the best single anthropometric measurement or the association of two anthropometric measurements highly correlated with VAT. Both multivariate models showed no collinearity problem. Selected models demonstrate high sensitivity (97.7% in women, 100% in men). Similar predictive abilities were observed in the validation sample (Women: R(2) = 76%; Men: R(2) = 70%). Bland and Altman method showed no systematic estimation error of VAT. CONCLUSION: Validated in a large range of age and BMI, our results suggest the usefulness of the anthropometric selected models to predict VAT in Europides (South of France).

Epicardial adipose tissue extent: relationship with age, body fat distribution, and coronaropathy.

Epicardial fat is a relatively neglected component of the heart and could be an important risk factor of cardiac disease. The objective of our study was to assess the relationship between epicardial adipose tissue (EAT) extent, fat distribution, and coronaropathy in a group of adult victims of accidental or suspicious sudden death. In 56 cadavers, we performed 34 measurements of EAT from five computerized photographs of the heart (anterior and posterior faces, and three ventricle transversal slices) and analyzed their relationship with anthropometric markers of adiposity (BMI, waist and leg circumference, thickness of abdominal and thigh subcutaneous adipose tissue (SAT)), with the presence and staging of coronary artery disease (CAD), and with markers of myocardial hypertrophy. Simple linear regressions showed that EAT measurements are highly intercorrelated (r from 0.4 to 0.6, P < 0.001), and correlate with age, waist circumference, and heart weight, and to a lesser extent, with BMI, abdominal SAT thickness, and leg SAT thickness. Multiple regression showed that age, waist circumference, and heart weight significantly and independently correlate with EAT (P < 0.0001). No other anthropometric measurement was found independently correlated with EAT. The EAT/myocardium ratios correlated positively with age and waist circumference. Anterior and posterior areas of EAT were found significantly increased in patients with CAD and correlated positively with CAD staging (P = 0.0034, r = 0.38). Anterior EAT surface was found positively associated with CAD (P = 0.01), independently of age and other adiposity measurements. Prospective studies are needed to assess the risk of occurrence/progression of CAD that relate to EAT excess.

Insulin resistance induced by hydrocortisone is increased in patients with abdominal obesity.

Glucocorticoids hypersensitivity may be involved in the development of abdominal obesity and insulin resistance. Eight normal weight and eight obese women received on two occasions a 3-h intravenous infusion of saline or hydrocortisone (HC) (1.5 microg x kg(-1) x min(-1)). Plasma cortisol, insulin, and glucose levels were measured every 30 min from time(-30) (min) (time(-30)) to time(240). Free fatty acids, adiponectin, and plasminogen activator inhibitor-1 (PAI-1) levels were measured at time(-30), time(180), and time(240). At time(240), subjects underwent an insulin tolerance test to obtain an index of insulin sensitivity (K(ITT)). Mean(30-240) cortisol level was similar in control and obese women after saline (74 +/- 16 vs. 75 +/- 20 microg/l) and HC (235 +/- 17 vs. 245 +/- 47 microg/l). The effect of HC on mean(180-240) insulin, mean(180-240) insulin resistance obtained by homeostasis model assessment (HOMA-IR), and K(ITT) was significant in obese (11.4 +/- 2.0 vs. 8.2 +/- 1.3 mU/l, P < 0.05; 2.37 +/- 0.5 vs. 1.64 +/- 0.3, P < 0.05; 2.81 +/- 0.9 vs. 3.32 +/- 1.02%/min, P < 0.05) but not in control women (3.9 +/- 0.6 vs. 2.8 +/- 0.5 mU/l; 0.78 +/- 0.1 vs. 0.49 +/- 0.1; 4.36 +/- 1.1 vs. 4.37 +/- 1.2%/min). In the whole population, the quantity of visceral fat, estimated by computerized tomography scan, was correlated with the increment of plasma insulin and HOMA-IR during HC infusion [Delta mean(30-240) insulin (r = 0.61, P < 0.05), Delta mean(30-240) HOMA-IR (r = 0.66, P < 0.01)]. The increase of PAI-1 between time(180) and time(240) after HC was higher in obese women (+25%) than in controls (+12%) (P < 0.05), whereas no differential effect between groups was observed for free fatty acids or adiponectin. A moderate hypercortisolism, equivalent to that induced by a mild stress, has more pronounced consequences on insulin sensitivity in abdominally obese women than in controls. These deleterious effects are correlated with the amount of visceral fat.