Obesity among Asian American people in the United States: A review.

Standard measures of obesity, i.e., body weight and BMI, suggest that Asian American people have a lower obesity prevalence than other racial groups in the United States. However, Asian American people face a unique challenge in their pattern of adiposity with central obesity, which raises the risk for multiple comorbidities, such as type 2 diabetes, metabolic syndrome, and cardiovascular disease, at a lower BMI compared with other populations. Several organizations recommend lower BMI cutoffs for obesity in Asian people (BMI ≥25.0 or ≥27.5 kg/m2 ) instead of the standard ≥30.0 kg/m2 threshold. The risks of obesity and related comorbidities in this population are further influenced by diet, physical activity, perceptions of health, and access to information and therapies. Asian-specific parameters for assessing obesity should become a standard part of clinical practice. Asian American people should equally be offered subgroup-specific tailored interventions owing to heterogeneity of this population. Access to medications and surgery should be improved, in part by updating US indications for therapies to reflect race-specific obesity thresholds and through inclusion of Asian American people of all subtypes with lower BMI values in clinical trials.

Baseline motives for eating palatable food: racial differences and preliminary utility in predicting weight loss.

PURPOSE: Behavioral predictors of weight-loss program (WLP) outcomes are needed and important because they can be modified. Eating calorie-dense palatable foods (PFs) outside of hunger contributes to obesity. This study assessed if habitual motives to consume PFs could predict weight-loss outcomes. METHODS: N = 171 Black and N = 141 White adults in a reduced-calorie program completed the Palatable Eating Motives Scale (PEMS). Body weight and body mass index (BMI) lost after 3 and 6 months were analyzed controlling for initial BMI and demographics. Greater PEMS motive scores meant more frequent habitual intake of PFs for that motive. RESULTS: Whites vs. Blacks had higher scores on most of the PEMS motives: Social, Coping, and Reward Enhancement. In Whites at 3 months, greater Reward Enhancement scores and initial BMI predicted more BMI loss (p < 0.05). At 6 months, greater Reward Enhancement and lower Conformity scores predicted more weight (p < 0.05) and BMI loss (Conformity: p < 0.05; Reward Enhancement: p = 0.05). PEMS motives did not predict outcomes for Blacks. CONCLUSION: The results provide preliminary evidence for the PEMS to predict WLP outcomes. White patients who eat PFs primarily for their rewarding properties and less to conform should fare better in Lifestyle programs while group or family-based interventions may be more efficacious when conformity is the main motive. Lower motive scores among Blacks suggest that eating PFs outside of hunger may go unrecognized or underreported and warrants further investigation. The findings highlight the motive-based heterogeneity of obesity and how it may be used to predict outcomes and customize interventions to improve WLP outcomes. LEVEL OF EVIDENCE: Level IV, multiple time series.

A complications-based clinical staging of obesity to guide treatment modality and intensity.

PURPOSE OF REVIEW: The current medical model for obesity management is BMI-centric because BMI is the predominant measure used to gauge disease severity, as well as indications for various treatment modalities. Recent advancements in therapy and understanding of the relationship between BMI and obesity-related complications call for a re-examination of this approach. RECENT FINDINGS: Advancements in treatment, including the recent approval of two new weight loss medications in the USA, have enabled development of new medical models for management of obesity. On the basis of accumulating data demonstrating the benefits of weight loss regarding multiple obesity-related complications (e.g., diabetes prevention, type 2 diabetes mellitus, cardiovascular disease risk, nonalcoholic steatohepatitis, sleep apnea), a complications-centric model is proposed that employs weight loss as a tool to treat and prevent obesity comorbidities. This model assures that the aggressiveness of therapy is commensurate with disease severity, and that therapy is directed at those obese patients who will benefit most from weight loss therapy. The treatment algorithm is comprehensive in addressing complications and quantitative when possible in the staging of risk or disease severity. SUMMARY: A complications-centric approach to obesity management identifies patients who will benefit most from weight loss, and optimizes patient outcomes, benefit/risk ratio, and the cost-effectiveness of interventions.

Eosinopenia: Is it a good marker of sepsis in comparison to procalcitonin and C-reactive protein levels for patients admitted to a critical care unit in an urban hospital?

INTRODUCTION: The role of eosinopenia as a marker of sepsis has recently been evaluated. The aim of our study was to test the value of eosinopenia as a diagnostic marker of sepsis in comparison to procalcitonin and C-reactive protein levels. METHODS: A prospective study of critically ill adult patients admitted to the medical intensive care unit at an urban hospital. Procalcitonin, C-reactive protein (CRP) levels and eosinophil counts were measured on admission. Patients were classified as non-infected or infected by the medical residents, fellows, and attendings. RESULTS: A total of 68 patients were enrolled into the study. At a cut-off value of 70 mg/L, the CRP level yielded a sensitivity of 94%, a specificity of 84%, a positive predicted value (PPV) of 83% and a negative predicted value (NPV) of 94%. At a cutoff value of 1.5 µg/L, the sensitivity of the procalcitonin test was 84%, specificity of 92%, PPV 90%, and NPV of 87%. The eosinophil cell count (cutoff of 50 cells/mm(3)) produced a sensitivity of 81%, specificity of 65%, a PPV of 66%, and a NPV of 80%. The comparison of the eosinophil cell count (<50 cells/mm(3)) and procalcitonin levels among the non-infected and infected groups showed a significant statistical difference (Fisher exact test, P = .0239). There was no statistical difference observed when comparisons were made between CRP levels and eosinophil count (Fisher exact test, P = .12). There was also a lack of significant statistical difference when CRP levels were compared to procalcitonin levels (Fisher exact test, P = .49). CONCLUSION: Eosinopenia is a very sensitive yet not specific serological marker of sepsis in the intensive care unit and can be utilized to guide physicians in the diagnosis of sepsis.