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As global obesity rates continue to rise, it is important to understand the origin, role and range of human variation of body mass index (BMI) in assessing health and healthcare. A growing body of evidence suggests that BMI is a poor indicator of health across populations, and that there may be a metabolically healthy obese phenotype. Here, we review the reasons why BMI is an inadequate tool for assessing cardiometabolic health. We then suggest that cold climate adaptations may also render BMI an uninformative metric. Underlying evolutionary and environmental drivers may allow for heat conserving larger body sizes without necessarily increasing metabolic health risks. However, there may also be a potential mismatch between modern obesogenic environments and adaptations to cold climates, highlighting the need to further investigate the potential for metabolically healthy obese phenotypes among circumpolar and other populations as well as the broader meaning for metabolic health.
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(1) Background: The health implications associated with the metabolically healthy obese (MHO) phenotype, in particular related to symptoms of depression, are still not clear. the purpose of this study is to check whether depression and metabolic status are relevant by classifying them into four groups in accordance with the MHO diagnostic standard. Other impressions seen were the differences between sexes and the effects of the MHO on the occurrence of depression. (2) Methods: A sample of 3,586,492 adult individuals from the National Health Insurance Database of Korea was classified into four categories by their metabolic status and body mass index: (1) metabolically healthy non-obese (MHN); (2) metabolically healthy obese (MHO); (3) metabolically unhealthy non-obese (MUN); and (4) metabolically unhealthy obese (MUO). Participants were followed for six to eight years for new incidences of depression. The statistical significance of the general characteristics of the four groups, as well as the mean differences in metabolic syndrome risk factors, was assessed with the use of a one-way analysis of variance (ANOVA). (3) Results: The MHN ratio in women was higher than in men (men 39.3%, women 55.2%). In both men and women, depression incidence was the highest among MUO participants (odds ratio (OR) = 1.01 in men; OR = 1.09 in women). It was concluded as well that, among the risk factors of metabolic syndrome, waist circumference was the most related to depression. Among the four groups, the MUO phenotype was the most related to depression. Furthermore, in women participants, MHO is also related to a higher risk of depressive symptoms. These findings indicate that MHO is not a totally benign condition in relation to depression in women. (4) Conclusion: Therefore, reducing metabolic syndrome and obesity patients in Korea will likely reduce the incidence of depression.
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Depresión/epidemiología , Obesidad Metabólica Benigna/psicología , Adulto , Índice de Masa Corporal , Femenino , Humanos , Masculino , Síndrome Metabólico/epidemiología , Persona de Mediana Edad , Programas Nacionales de Salud , Obesidad Metabólica Benigna/epidemiología , República de Corea/epidemiología , Factores de Riesgo , Circunferencia de la CinturaRESUMEN
The concept of heterogeneity among obese individuals in their risk for developing metabolic dysfunction and associated complications has been recognized for decades. At the origin of the heterogeneity idea is the acknowledgement that individuals with central obesity are more prone to developing type 2 diabetes and cardiovascular disease than those with peripheral obesity. There have been attempts to categorize subjects according to their metabolic health and degree of obesity giving rise to different obese and non-obese phenotypes that include metabolically unhealthy normal-weight (MUHNW), metabolically healthy obese (MHO), and metabolically unhealthy obese (MUO). Individuals belonging to the MHO phenotype are obese according to their body mass index although exhibiting fewer or none metabolic anomalies such as type 2 diabetes, dyslipidemia, hypertension, and/or unfavorable inflammatory and fribinolytic profiles. However, some authors claim that MHO is only transient in nature. Additionally, the phenotype categorization is controversial as it lacks standardized definitions possibly blurring the distinction between obesity phenotypes and confounding the associations with health outcomes. To add to the discussion, the factors underlying the origin or protection from metabolic deterioration and cardiometabolic risk for these subclasses are being intensely investigated and several hypotheses have been put forward. In the present review, we compare the different definitions of obesity phenotypes and present several possible factors underlying them (adipose tissue distribution and cellularity, contaminant accumulation on the adipose tissue, dysbiosis and metabolic endotoxemia imposing on to the endocannabinoid tone and inflammasome, and nutrient intake and dietary patterns) having inflammatory activation at the center.
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BACKGROUND AND AIMS: We aimed to evaluate whether the metabolically healthy obese (MHO) phenotype was associated with hepatic steatosis (HS) or left ventricular hypertrophy (LVH) in young people with overweight (OW), obesity (OB) and morbid obesity (MOB) and whether the prevalence of these comorbidities was affected by OB severity. METHODS AND RESULTS: An abdominal ultrasound was performed in 1769 children and adolescents, mean age 10.6 years (range 5-18) with MHO phenotype, defined as the absence of traditional cardiometabolic risk factors, in order to identify HS. In a subsample of 177 youth the presence of LVH, defined by 95th percentile of LV mass/h2.7 for age and gender, was also analyzed. The prevalence of HS increased from 23.0% in OW to 27.8% in OB and 45.1% in MOB (P < 0.0001). The proportion of LVH increased from 36.8% in OW to 57.9% in OB and 54.5% in MOB (P < 0.05). As compared with OW, the odds ratio (95% CI) for HS was 2.18 (1.56-3.05), P < 0.0001) in OB and 6.20 (4.26-9.03), P < 0.0001) in MOB, independently of confounding factors. The odds ratio for LVH was 2.46 (1.20-5.06), P < 0.025) in OB and 2.79 (1.18-6.61), P < 0.025) in MOB, as compared with OW. CONCLUSION: In spite of the absence of traditional cardiometabolic risk factors, the prevalence of HS and LVH progressively increased across BMI categories. MHO phenotype does not represent a "benign" condition in youth.
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Hígado Graso/epidemiología , Hipertrofia Ventricular Izquierda/epidemiología , Obesidad Metabólica Benigna/epidemiología , Obesidad Infantil/epidemiología , Adolescente , Factores de Edad , Índice de Masa Corporal , Niño , Preescolar , Comorbilidad , Estudios Transversales , Hígado Graso/diagnóstico por imagen , Femenino , Humanos , Hipertrofia Ventricular Izquierda/diagnóstico por imagen , Italia/epidemiología , Masculino , Obesidad Metabólica Benigna/diagnóstico , Obesidad Mórbida/diagnóstico , Obesidad Mórbida/epidemiología , Obesidad Infantil/diagnóstico , Fenotipo , Prevalencia , Estudios Retrospectivos , Medición de Riesgo , Factores de Riesgo , Índice de Severidad de la EnfermedadRESUMEN
BACKGROUND: Metabolically healthy obesity seems to be a unique phenotype for the risk of cardiometabolic diseases. However, it is not known whether this phenotype is associated with the risk of proteinuria. METHODS: Study subjects were 9,185 non-diabetic Japanese male workers aged 40-55 years who had no proteinuria, an estimated glomerular filtration rate ≥60 mL/min/1.73 m2, no history of cancer, and no use of antihypertensive or lipid-lowering medications at baseline. Obesity was defined as body mass index ≥25.0 kg/m2. Metabolic health was defined as the presence of no Adult Treatment Panel III components of the metabolic syndrome criteria, excluding waist circumference, and metabolic unhealth was defined as the presence of one or more metabolic syndrome components, excluding waist circumference. "Consecutive proteinuria" was considered positive if proteinuria was detected twice consecutively as 1+ or higher on urine dipstick at annual examinations to exclude chance proteinuria as much as possible. RESULTS: During the 81,660 person-years follow-up period, we confirmed 390 cases of consecutive proteinuria. Compared with metabolically healthy non-obesity, metabolically healthy obesity was not associated with the risk of consecutive proteinuria (multiple-adjusted hazard ratio [HR] 0.86; 95% confidence interval [CI], 0.37-1.99), but metabolically unhealthy non-obesity with ≥2 metabolic syndrome components (HR 1.77; 95% CI, 1.30-2.42), metabolically unhealthy obesity with one component (HR 1.71; 95% CI, 1.12-2.61), and metabolically unhealthy obesity with ≥2 metabolic syndrome components (HR 2.77; 95% CI, 2.01-3.82) were associated with an increased risk of consecutive proteinuria. CONCLUSIONS: Metabolically healthy obesity did not increase the risk of consecutive proteinuria in Japanese middle-aged men.
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Obesidad Metabólica Benigna/epidemiología , Proteinuria/epidemiología , Adulto , Femenino , Estudios de Seguimiento , Humanos , Japón/epidemiología , Masculino , Persona de Mediana Edad , RiesgoRESUMEN
OBJECTIVE: The purpose of this study was to examine the relationship between usual sugar-sweetened beverage (SSB) consumption and prevalence of abnormal metabolic health across body mass index (BMI) categories. METHODS: The metabolic health of 6,842 non-diabetic adults was classified using cross-sectional data from the Framingham Heart Study Offspring (1998-2001) and Third Generation (2002-2005) cohorts. Adults were classified as normal weight, overweight or obese and, within these categories, metabolic health was defined based on five criteria-hypertension, elevated fasting glucose, elevated triglycerides, low HDL cholesterol, and insulin resistance. Individuals without metabolic abnormalities were considered metabolically healthy. Logistic regression was used to examine the associations between categories of SSB consumption and risk of metabolic health after stratification by BMI. RESULTS: Comparing the highest category of SSB consumers (median of 7 SSB per week) to the lowest category (non-consumers), odds ratios (95% confidence intervals) for metabolically abnormal phenotypes, compared to the metabolically normal, were 1.9 (1.1-3.4) among the obese, 2.0 (1.4-2.9) among the overweight, and 1.9 (1.4-2.6) among the normal weight individuals. CONCLUSIONS: In this cross-sectional analysis, it is observed that, irrespective of weight status, consumers of SSB were more likely to display metabolic abnormalities compared to non-consumers in a dose-dependent manner.