The Role of Morning Plasma Cortisol in Obesity: A Bi-directional Mendelian Randomization Study

Context Cortisol, an important hormone regulated by the hypothalamic-pituitary-adrenal (HPA) axis, is associated with obesity. However, it is unclear whether the relationship between cortisol and obesity is causal or could be explained by reverse causality. Objective This work aims to assess the role of morning plasma cortisol in clinical classes of obesity. Methods In this bi-directional two-sample Mendelian Randomization (MR) study, cortisol-associated genetic variants were obtained from the CORtisol NETwork consortium (n = 12,597). The primary outcomes were obesity class I (BMI ≥ 30 kg/m 2), class II (BMI ≥ 35 kg/m 2), and class III (BMI ≥ 40kg/m 2). Inverse variance weighting (IVW) method was used as the main analysis, with weighted median, MR-Egger, and MR-PRESSO as sensitivity analyses. Conversely, genetic variants predicting clinical classes of obesity were applied to the cortisol GWAS. Results Genetically predicted cortisol was associated with reduced risk of obesity class I (OR = 0.905; 95% CI, 0.865-0.946; p < 0.001). Evidence from bi-directional MR showed that obesity class II and class III were associated with lower cortisol levels ((class II-cortisol OR = 0.953; 95% CI, 0.923-0.983; p = 0.002); (class III-cortisol OR = 0.955; 95% CI, 0.942-0.967; p < 0.001)), indicating reverse causality between cortisol and obesity. Conclusions This study demonstrates that cortisol is negatively associated with obesity and vice versa. Together, these findings suggest that blunted morning plasma cortisol secretion may be responsible for severe obesity. Regulating morning plasma secretion might be a prevention measure for obese people.

Impact of body mass index on critically ill COVID-19 patients admitted in a tertiary care hospital : a retrospective observational study

Background: Increased body mass index (BMI) is a known risk factor for respiratory infection and is being recognized as a predisposing factor in the COVID‐19 pandemic caused by the severe acute respiratory syndrome coronavirus‐2. Aims and Objectives: This study aimed to assess the association between different body mass index categories with severe COVID-19 patients leading to death. Materials and Methods: This retrospective study of six months included the laboratory-confirmed COVID-19 patients admitted to an ICU of a tertiary care academic health care organization. The medical records were reviewed at least 14 days after admission. Results: 484 patients were included, and BMI data were available for 306 patients. 40.19% had a normal weight, 26.79% were overweight, 17.97% had BMI 30-34.9 Kg/m2 and 15.03% had BMI ≥ 35 Kg/m2. Overall, 58 patients (18.95%) died within 14 days of ICU admission, 50.98% were discharged alive or referred from the hospital within 14 days, and 30.06% remained hospitalized at 14 days. After controlling for all covariates, there was a significantly increased risk of mortality in the patients with obesity class I (RR 2.03, 95% CI 1.07-3.85, P = 0.030) and patients with obesity class II & III (RR 2.83, 95% CI 1.54–5.22, P <0.001) compared with those with normal BMI. Conclusions: Obesity was associated with an unfavorable outcome among patients with COVID-19. Patients with obesity should be more closely monitored when hospitalized for COVID-19 as there is increasing evidence of relation of severity of COVID-19 and obesity which appears to be a factor in the health risks.

Prevalence of Obesity and its primary comorbidities among patients attending the dietetics out-patient clinic in a tertiary health institution in southwestern Nigeria

Objective: The study assessed the prevalence of obesity and its co-morbidities among patients attending the dietetics outpatient clinic of the hospital. Methods: The prevalence of obesity and its co-morbidities were assessed in this retrospective study from the available in the outpatient clinic of the Dietetics Department in University College Hospital Ibadan, Oyo State. Age, gender, occupation, religion, height, weight, diagnosed diseases were extracted from the record of individuals who presented at the clinic over 72 months. Data obtained was analyzed using the Statistical Package for Social Sciences (SPSS) version 20. Result: A total of 3248 patients’ records were assessed. Of these, 1174 (36.15%) patients met the criteria for obesity according to their recorded BMI; 614(52.3%) had obesity class I (BMI 30–34.9), 343(29.2%) had obesity class II (BMI 35–39.9) and 217(18.5%) had obesity class III (BMI ≥40). Obesity was significantly higher amongst females than males (p<0.05). The most prevalent single co-morbidity was diabetes 22.3%, while the most prevalent double co-morbidity was hypertension/diabetes 22.9%. Conclusion: The prevalence of obesity amongst patients was significant. Diabetes and hypertension were the most dominant co-morbidity. Interventions should be developed to combat the increasing prevalence of the diseases and these should involve educating the public and clinical management of the diseases upon identification.

Executive Functions of Adults with Binge-Eating Disorder: The Role of Weight Status and Psychopathology

Findings on executive functions (EFs) in binge-eating disorder (BED) are inconsistent and possibly biased by associated comorbidities. This study aimed to identify whether distinct levels of physical and mental comorbidity are related to EFs in BED. General and food-specific EFs in n = 77 adults with BED were compared to population-based norms and associations with weight status, depressive symptoms, and eating disorder psychopathology were analyzed. To detect within-sample patterns of EF performance, k-means clustering was applied. The results indicated that participants’ general EFs were within the average range with slight deficits in alertness. While depression and eating disorder psychopathology were unrelated to EFs, weight status was associated with food-specific attentional bias that was significantly higher in obesity class 2 than in overweight/obesity class 1 and obesity class 3. Four meaningful clusters with distinct strengths and impairments in general and food-specific EFs but without differences in clinical variables were identified. Altogether, adults with BED showed few specific deficits compared to normative data. Performance was unrelated to depression and eating disorder psychopathology, while weight status was associated with food-specific EFs only. The results highlight the need for longitudinal studies to evaluate the relevance of EFs in BED development and maintenance in neurologically healthy adults.

The Effect of Obesity Class on the Energetics and Mechanics of Walking

Higher mass-normalized net energy cost of walking (NetCw/kg) and mechanical pendular recovery are observed in obese compared to lean adults. This study aimed to investigate the effect of different classes of obesity on the energetics and mechanics of walking and to explore the relationships between body mass, NetCw/kg and gait mechanics by using principal component analysis (PCA). NetCw/kg and gait mechanics were computed in severely obese (SOG; n = 18, BMI = 40.1 ± 4.4 kg·m−2), moderately obese (MOG; n = 17, BMI = 32.2 ± 1.5 kg·m−2) and normal-weight (NWG; n = 13, BMI = 22.0 ± 1.5 kg·m−2) adults during five walking trials (0.56, 0.83, 1.11, 1.39, 1.67 m·s−1) on an instrumented treadmill. NetCw/kg was significantly higher in SOG compared to NWG (p = 0.019), with no significant difference between SOG and MOG (p = 0.14), nor between MOG and NWG (p = 0.27). Recovery was significantly higher in SOG than in NWG (p = 0.028), with no significant difference between SOG and MOG (p = 0.13), nor between MOG and NWG (p = 0.35). PCA models explained between 17.0% and 44.2% of the data variance. This study showed that: (1) obesity class influences the gait energetics and mechanics; (2) PCA was able to identify two components, showing that the obesity class is associated with lower walking efficiency and better pendulum-like characteristics.

Deciphering the Irregular Risk of Stroke Increased by Obesity Classes: A Stratified Mendelian Randomization Study

BackgroundTo investigate the relationship between different classes of obesity and stroke, we conducted a stratified Mendelian randomization (MR) study.MethodsThe body mass index (BMI) data of 263,407 Europeans with three classes of obesity (obesity class I, 30 kg/m2 ≤ BMI &lt; 35 kg/m2; obesity class II, 35 kg/m2 ≤ BMI &lt; 40 kg/m2; obesity class III, 40 kg/m2 ≤ BMI) were extracted from the Genetic Investigation of ANthropometric Traits (GIANT) consortium. Summary-level data of stroke and its subtypes [ischemic stroke (IS) and intracerebral hemorrhage (ICH)] were obtained from the genome-wide association study (GWAS) meta-analysis, which was performed by the MEGASTROKE consortium. MR methods were used to identify the causal relationships.ResultsThe MR analysis revealed that both obesity class I [odds ratio (OR) = 1.08, 95% CI: 1.05–1.12, p = 1.0 × 10-5] and obesity class II (OR = 1.06, 95% CI: 1.03–1.09, p = 1 × 10-4) were significantly positively related to IS, while obesity class III was not (OR = 1.01, 95% CI: 0.96–1.06, p = 0.65). In contrast to IS, there was no class of obesity associated with ICH risk. Further examination of the relationship between obesity classification and IS subtypes revealed that certain degrees of obesity were related to large artery stroke (LAS) (OR = 1.14, 95% CI: 1.04–1.24, p = 2.8 × 10-3 for class I; OR = 1.08, 95% CI: 1.01–1.16, p = 0.002 for class II) and cardioembolic stroke (CES) (OR = 1.11, 95% CI: 1.02–1.20, p = 0.02 for class I; OR = 1.08, 95% CI: 1.02–1.15, p = 0.007 for class II).ConclusionsA higher risk of IS, but not ICH, could be linked to obesity classes I and II. A strong association between LAS and CES and obesity was observed among all IS subtypes in the obese population.

Underweight is a major risk factor for atrial fibrillation in Asian people with type 2 diabetes mellitus

Background Atrial fibrillation (AF) is prevalent in patients with type 2 diabetes mellitus (T2DM). Obesity commonly accompanies T2DM, and increases the risk of AF. However, the dose-relationship between body mass index (BMI) and AF risk has seldom been studied in patients with diabetes. Methods This cohort study utilized a database from National Taiwan University Hospital, a tertiary medical center in Taiwan. Between 2014 and 2019, 64,339 adult patients with T2DM were enrolled for analysis. BMI was measured and categorized as underweight (BMI < 18.5), normal (18.5 ≤ BMI < 24), overweight (24 ≤ BMI < 27), obesity class 1 (27 ≤ BMI < 30), obesity class 2 (30 ≤ BMI < 35), or obesity class 3 (BMI ≥ 35). Multivariate Cox regression and spline regression models were employed to estimate the relationship between BMI and the risk of AF in patients with T2DM. Results The incidence of AF was 1.97 per 1000 person-years (median follow-up, 70.7 months). In multivariate Cox regression, using normal BMI as the reference group, underweight (HR 1.52, 95% CI 1.25–1.87, p < 0.001) was associated with a significantly higher risk of AF, while overweight was associated with significantly reduced risk of AF (HR 0.82, 95% CI 0.73–0.89, p < 0.001). Kaplan–Meier analysis showed AF risk was highest in the underweight group, followed by obesity class 3, while the overweight group had the lowest incidence of AF (log-rank test, p < 0.001). The cubic restrictive spline model revealed a “J-shaped” or “L-shaped” relationship between BMI and AF risk. Conclusions Underweight status confers the highest AF risk in Asian patients with T2DM.

1102. Evaluation of Vancomycin Accumulation in Patients with Obesity

Background Current vancomycin guidelines recommend using actual body weight for dosing. However, in patients with obesity, this may result in lower initial vancomycin concentrations that can accumulate with continued doses due to differences in volume of distribution. The objective of this study is to evaluate the incidence of vancomycin accumulation in patients with obesity and identify potential factors associated with accumulation. Methods This is a single-center, retrospective, observational study at a tertiary academic medical center. Adult patients with a BMI ≥ 30 kg/m2 and with ≥ 2 vancomycin serum trough concentrations within the same encounter in 2019 were screened. Patients were excluded if they were pregnant, had unstable renal function or severe renal impairment, received &lt; 3 doses before a concentration was drawn, or had inconsistent dosing prior to a concentration draw. Linear kinetics were used to correct for differences in timing of concentration or dose changes. The major endpoint was the incidence of vancomycin accumulation, defined as a 20% increase in trough concentration between the first and any subsequent trough concentrations within the first 10 days of therapy. Minor endpoints included the percentage of supratherapeutic concentrations and the incidence of acute kidney injury (AKI). Descriptive statistics were used to evaluate endpoints and multivariable logistic regression was used to evaluate factors associated with accumulation. Results We screened 543 patients, and 162 were included in our analysis. The median age was 56.5 years (interquartile range [IQR] 43 - 65.3), and 62.3% were male. The median weight was 112.7 kg (IQR 99.8 - 122.6) and the median BMI was 36.8 kg/m2 (IQR 33.1 - 41). The median total daily vancomycin dose at initiation was 28.7 mg/kg/day (IQR 25.4 - 31.2). Vancomycin accumulation occurred in 99 patients (61.1%) within the first 10 days of therapy and AKI occurred in 21 patients (14.9%). No factors studied, including age, gender, obesity class, initial dose, SCr, or frequency were associated with accumulation. Conclusion Most patients with obesity experienced vancomycin accumulation within the first 10 days of therapy. Providers should be cautious when assessing a vancomycin concentration early in the treatment course. Disclosures All Authors: No reported disclosures

329. Severe Obesity: A Critical Risk Factor for In-Hospital Complications and Mortality in the Hispanic Population

Background Obesity, Diabetes mellitus type 2, race and other characteristics has been associated with an increased risk of adverse outcomes in patients with COVID-19 disease. The prevalence of obesity in the United States in 2017-2018 was 42.4%. Webb County, Texas with a 95.6% Hispanic population shows an obesity prevalence of 35.8% in 2014. It is unclear whether obesity increases the risks of complications and mortality in Hispanic population from COVID-19 disease. Methods This is a retrospective cohort study of patients admitted to the hospital with the diagnosis of COVID-19 between March 2020 and August 2020. 950 patients were tested and admitted to the hospital with the diagnosis of COVID-19 pneumonia. Patients were categorized into classes of body habitus by BMI: underweight (&lt; 18.5), normal (18.5-24.9), overweight (25.0-29.9), obesity class 1 (30.0-34.9), obesity class 2 (35.0-39.9), and obesity class 3 ( &gt;40.0). Results 950 Hispanic patients were included (Male-52.8%, Female- 47.2%) in the study. In total, 19.05% of our patients died during the hospitalization with an increased risk of mortality in patients having obesity class 2 (RR 4.14, 95% CI = 2.2–7.7 p=&lt; 0.0001), and obesity class 3 (RR 6.0, 95% CI = 1.3–4.6 p=&lt; 0.0001) compared with those with normal BMI. Mortality was higher in obese patients who required invasive mechanical ventilation at 93.75% compared to obese patients who were non-ventilated at 4.29%. Patients with obesity class 2 and 3 had higher risks of in-hospital complications including AKI requiring renal replacement therapy, ARDS, and arrythmias most commonly atrial fibrillation/flutter at 26.7%, 18.42% and 13.5%. Characteristics of In-hospital complication complications due to COVID-19 disease Conclusion Patients admitted to the hospital with the diagnosis of COVID-19 disease with obesity classes 2 and 3 have a significantly increased risk of mortality as compared to normal and overweight patients. Severe obesity was also associated with increased hospital complications of AKI, ARDS, and Atrial Fibrillation. This further affirms that obesity is a pertinent risk factor to be considered in COVID-19 patients. Disclosures All Authors: No reported disclosures