Relationship between commonly defined metabolic health phenotypes and obesity with lung function in a working population: A cross-sectional study.

BACKGROUND: Four phenotypes relate metabolism and obesity: metabolically healthy (MHO) and unhealthy (MUO) people with obesity and metabolically healthy (MHNO) and unhealthy (MUNO) people without obesity. No studies have addressed the association between these categories and lung function in the working population. OBJECTIVES: The aim was to determine the relationship of phenotypes to lung ageing as measured by lung age and its relationship to lung dysfunction. METHODS: A descriptive cross-sectional study was conducted in a working population. The outcome variable was lung function assessed by lung age. The four phenotypes of obesity and metabolic health (MHNO, MHO, MUO and MUNO) were determined using NCEP-ATP III criteria. Lung dysfunctions were classified into restrictive, obstructive, and mixed patterns. RESULTS: The mean age of the participants was 43.7 years, ranging from 18 to 67 years. Of the 1860 workers, 51.3 % were women. The prevalences found were 71.4 %, 12 %, 10.6 % and 6 % for MHNO, MUO, MHO, and MUNO, respectively. MHO (ß = 0.66; p = 0.591) was not associated with increased lung ageing compared with MHNO, but MUO (ß = 7.1; p < 0.001) and MUNO (ß = 6.6; p < 0.001) were. Concerning pulmonary dysfunctions, MUNO (OR = 1.93; p < 0.001) and MUO (OR = 2.91; p < 0.001) were found to be related to the presence of a restrictive pattern, and MUNO (OR = 2.40; p = 0.028) to the mixed pattern. CONCLUSION: The results show that metabolic abnormalities, not obesity, are responsible for premature lung ageing and, therefore, lung function decline. In our study, having obesity without metabolic abnormality was not significantly associated with the presence of dysfunctional respiratory patterns.

Association between Metabolic Syndrome and Leukocytes: Systematic Review and Meta-Analysis.

Background: Metabolic syndrome (MetS) is a group of metabolic abnormalities characterised by central obesity, hypertension, dyslipidaemia, and dysregulation of blood glucose, which is associated with the risk of diabetes, cardiovascular disease, and overall mortality. White blood cell count is a selective marker of acute infection and inflammation, which could provide information on the metabolic status of subjects. This study aims to provide the best evidence on the association between MetS and white blood cell count by determining the effect size of this biomarker. Methods: A systematic review and meta-analysis of studies indexed in the PubMed and Scopus databases were performed. Methodological quality was assessed using the STROBE tool, overall risk of bias using RevMan (Cochrane Collaboration), and quality of evidence using Grade Pro. Results: We included 14 articles comparing leukocyte concentrations in 21,005 subjects with MetS and 66,339 controls. Subjects with MetS had a higher mean leukocyte count, 0.64 cells ×109/L; CI95% 0.55-0.72; p < 0.00001; I2 = 93%. Conclusions: An in-depth evaluation of the relationship of leukocytes in the pathophysiological process of MetS could lead to new insights into early diagnosis.

Diagnostic accuracy of anthropometric indices for metabolically healthy obesity in child and adolescent population.

BACKGROUND: A variable percentage of children and adolescents with obesity do not have cardiometabolic comorbidities. A phenotype called metabolically healthy obese (MHO) has emerged to describe this population subgroup. Early identification of this condition may prevent the progression to metabolically unhealthy obesity (MUO). MATERIAL AND METHODS: A cross-sectional descriptive study of 265 children and adolescents from Cordoba (Spain) conducted in 2018. The outcome variables were MHO, established based on three criteria: International Criterion, HOMA-IR, and a combination of the previous two. RESULTS: The prevalence of MHO ranged from 9.4% to 12.8% of the study population, between 41% and 55.7% of the sample with obesity. The highest agreement was reached between the HOMA-IR definitions and the combined criteria. The waist-to-height ratio (WHtR) was the indicator with the highest discriminant capacity for MHO in 2 of the three criteria, with its best cut-off point at 0.47 for both. CONCLUSION: The prevalence of MHO in children and adolescents differed according to the criteria used for diagnosis. The anthropometric variable with the most remarkable discriminating capacity for MHO was WHtR, with the same cut-off point in the three criteria analysed. IMPACT STATEMENT: This research work defines the existence of metabolically healthy obesity through anthropometric indicators in children and adolescents. Definitions that combine cardiometabolic criteria and insulin resistance are used to identify metabolically healthy obesity, as well as the prediction of this phenomenon through anthropometric variables. The present investigation helps to identify metabolically healthy obesity before metabolic abnormalities begin.

Diagnostic accuracy of the waist-to-height ratio and other anthropometric indices for metabolically healthy obesity in the working population.

Approximately one-third of overweight individuals, and half of those with obesity, do not have cardiometabolic disorders. For this reason, a phenotype called metabolically healthy obese (MHO) has emerged to describe this population group. The early detection of this situation could save costs associated with the development of comorbidities or pharmacological interventions. Therefore, the aim is to know the prevalence of MHO in the working population and propose variables for its detection. Cross-sectional descriptive study of 635 workers of the Cordoba City Council was carried out based on the results of the 2016 health surveillance. The outcome variables were the MHO, established based on the criteria of the IDF, NCEP-ATP III, and Aguilar-Salinas. In addition, the degree of agreement between the different MHO criteria was studied using Cohen's kappa (k), and the predictive capacity of the anthropometric variables was assessed with Receiver Operator Curves. The prevalence of MHO ranged from 6.6 to 9%. The highest agreement was reached between the IDF and NCEP-ATP III definitions (k = 0.811; 95% CI 0.724-0.898; p < 0.001). The waist-to-height ratio (WHtR) showed the highest discriminant capacity for MHO, with its best cut-off point at 0.55 for all criteria used. Sensitivity ranged from 84 to 93%. The prevalence of MHO in the working population differed according to the criteria used for diagnosis. The anthropometric variable with the highest discriminant capacity for MHO was WHtR, presenting the same cut-off point in the three criteria analyzed. Therefore, WHtR is the variable that best detects the presence of MHO.