Metabolically healthy obesity: different prevalences using different criteria

Obesity: Can inflammatory status define metabolic health?

A recent study shows that inflammation could be the underlying factor that determines the differences in metabolic profiles between subgroups of obesity. An improved understanding and characterization of these subgroups should help to develop innovative approaches to treat obesity.

Differences in body composition between metabolically healthy obese and metabolically abnormal obese adults

Potential differences in body composition between metabolically healthy obese (MHO) and metabolically abnormal obese (OA) adults were explored with 395 obese adults from the Pennington Center Longitudinal Study (18-68 years). Adults were classified as OA (≥2 risk factors: blood pressure ≥130/85 mmHg; triglycerides ≥150 mg dl(-1); high-density lipoprotein cholesterol: men <40, women <50 mg dl(-1); fasting glucose ≥100 mg dl(-1); waist circumference: ≥102 cm men, women ≥88 cm) or MHO (<2 risk factors). Whole-body bone mineral density and content, percent body fat, fat mass, lean mass and trunk adipose tissue mass were measured with dual-energy X-ray absorptiometry. Visceral (VAT), subcutaneous (SAT) and total abdominal adipose tissue (TAT) were measured with computed tomography. Gender-specific general linear regression models were used to determine differences in body composition between MHO and OA controlling for age, race, smoking status and menopause status. In men, MHO had lower fat mass (kg and %), trunk adipose tissue, VAT, SAT, TAT and lean mass compared with OA. MHO women had lower fat mass (kg), lean mass, trunk adipose tissue, VAT and TAT when compared with OA women. In conclusion, OA and MHO cardiometabolic profiles are characterized by differences in body composition consistent between genders.

A metabolically healthy obese phenotype in hispanic participants in the IRAS family study

OBJECTIVE

Some obese individuals appear to be protected from developing type 2 diabetes mellitus and cardiovascular disease (CVD). This has led to characterizing body size phenotypes based on cardiometabolic risk factors specifically as obese or overweight, and as metabolically healthy (MH) or metabolically abnormal (MA) based upon blood pressure, lipids, glucose homeostasis, and inflammatory parameters. The aim of this study was to measure the prevalence of and describe fat distribution across these phenotypes in a minority population.

DESIGN AND METHODS

Hispanic participants (N = 1054) in the IRAS Family Study were categorized into different body size phenotypes. Computed tomography (CT) abdominal scans were evaluated for measures of nonalcoholic fatty liver disease (NAFLD) and abdominal fat distribution. Statistical models adjusting for familial relationships were estimated.

RESULTS

Seventy percent (70%) of the Hispanic cohort was overweight (32%) or obese (38%). Forty-one percent (n = 138) of overweight participants and 19% (n = 74) of obese participants met criteria for MH. Adjusted analyses showed the MH phenotype was associated with lower visceral adipose tissue (VAT) and higher liver density (indicating lower fat content) in obese participants (p = 0.0005 and p = 0.0002, respectively), and lower VAT but not liver density in overweight participants (p = 0.008 and p = 0.162, respectively) compared to their MA counterparts. Odds of NAFLD were reduced in MH obese (OR = 0.34, p = 0.0007) compared to MA obese. VAT did not differ between MH obese or overweight and normal weight groups.

CONCLUSIONS

These findings suggest that lower levels of visceral and liver fat, despite overall increased total body fat, may be a defining feature of MH obesity in Hispanic Americans.

Defining metabolically healthy obesity: role of dietary and lifestyle factors

BACKGROUND

There is a current lack of consensus on defining metabolically healthy obesity (MHO). Limited data on dietary and lifestyle factors and MHO exist. The aim of this study is to compare the prevalence, dietary factors and lifestyle behaviours of metabolically healthy and unhealthy obese and non-obese subjects according to different metabolic health criteria.

METHOD

Cross-sectional sample of 1,008 men and 1,039 women aged 45-74 years participated in the study. Participants were classified as obese (BMI ≥ 30 kg/m(2)) and non-obese (BMI < 30 kg/m(2)). Metabolic health status was defined using five existing MH definitions based on a range of cardiometabolic abnormalities. Dietary composition and quality, food pyramid servings, physical activity, alcohol and smoking behaviours were examined.

RESULTS

The prevalence of MHO varied considerably between definitions (2.2% to 11.9%), was higher among females and generally increased with age. Agreement between MHO classifications was poor. Among the obese, prevalence of MH was 6.8% to 36.6%. Among the non-obese, prevalence of metabolically unhealthy subjects was 21.8% to 87%. Calorie intake, dietary macronutrient composition, physical activity, alcohol and smoking behaviours were similar between the metabolically healthy and unhealthy regardless of BMI. Greater compliance with food pyramid recommendations and higher dietary quality were positively associated with metabolic health in obese (OR 1.45-1.53 unadjusted model) and non-obese subjects (OR 1.37-1.39 unadjusted model), respectively. Physical activity was associated with MHO defined by insulin resistance (OR 1.87, 95% CI 1.19-2.92, p = 0.006).

CONCLUSION

A standard MHO definition is required. Moderate and high levels of physical activity and compliance with food pyramid recommendations increase the likelihood of MHO. Stratification of obese individuals based on their metabolic health phenotype may be important in ascertaining the appropriate therapeutic or intervention strategy.

Pleiotropic effects of obesity-susceptibility loci on metabolic traits: a meta-analysis of up to 37,874 individuals

AIMS/HYPOTHESIS

Genetic pleiotropy may contribute to the clustering of obesity and metabolic conditions. We assessed whether genetic variants that are robustly associated with BMI and waist-to-hip ratio (WHR) also influence metabolic and cardiovascular traits, independently of obesity-related traits, in meta-analyses of up to 37,874 individuals from six European population-based studies.

METHODS

We examined associations of 32 BMI and 14 WHR loci, individually and combined in two genetic predisposition scores (GPSs), with glycaemic traits, blood lipids and BP, with and without adjusting for BMI and/or WHR.

RESULTS

We observed significant associations of BMI-increasing alleles at five BMI loci with lower levels of 2 h glucose (RBJ [also known as DNAJC27], QPTCL: effect sizes -0.068 and -0.107 SD, respectively), HDL-cholesterol (SLC39A8: -0.065 SD, MTCH2: -0.039 SD), and diastolic BP (SLC39A8: -0.069 SD), and higher and lower levels of LDL- and total cholesterol (QPTCL: 0.041 and 0.042 SDs, respectively, FLJ35779 [also known as POC5]: -0.042 and -0.041 SDs, respectively) (all p < 2.4 × 10(-4)), independent of BMI. The WHR-increasing alleles at two WHR loci were significantly associated with higher proinsulin (GRB14: 0.069 SD) and lower fasting glucose levels (CPEB4: -0.049 SD), independent of BMI and WHR. A higher GPS-BMI was associated with lower systolic BP (-0.005 SD), diastolic BP (-0.006 SD) and 2 h glucose (-0.013 SD), while a higher GPS-WHR was associated with lower HDL-cholesterol (-0.015 SD) and higher triacylglycerol levels (0.014 SD) (all p < 2.9 × 10(-3)), independent of BMI and/or WHR.

CONCLUSIONS/INTERPRETATION

These pleiotropic effects of obesity-susceptibility loci provide novel insights into mechanisms that link obesity with metabolic abnormalities.

Metabolic health is more closely associated with coronary artery calcification than obesity

BACKGROUND

Recent studies have suggested that metabolic health may contribute more to the atherosclerosis than obesity. The aim of this study is to compare coronary artery calcium scores (CACS) among patients with different metabolic health and obesity status.

METHODS

A health-screening program of 24,063 participants (mean age 41 years) was conducted, and CACS was assessed by multi-detector computerized tomography (MDCT). Being metabolically healthy was defined as having fewer than two of the following risk factors: high blood pressure, high fasting blood glucose, high triglyceride, low high-density lipoprotein cholesterol, highest decile of homeostasis model assessment-insulin resistance (HOMA-IR) index, and highest decile of high-sensitivity C-reactive protein (hs-CRP). Obesity status was defined as body mass index (BMI) higher than 25 kg/m(2). Analyses were performed in four groups divided according to metabolic health and obesity: metabolically healthy non-obese (MHNO), metabolically healthy obese (MHO), metabolically unhealthy non-obese (MUHNO), and metabolically unhealthy obese (MUHO).

RESULTS

Mean values of CACS in the four groups were significantly different, except those between MHNO and MHO and between MUHNO and MUHO. When multinomial logistic regression analysis was performed with five CACS categories as the dependent variables and after adjusting for age, sex, and smoking status, the MHO, MUHNO, and MUHO groups showed significantly increased odds ratio for increasing CACS categories compared with no calcification status (5.221 for CACS >400 in MUHO group with 95% CI 2.856∼5.032 with MHNO group as the reference). When other variables including the metabolic parameters were included in the same model, the risks were attenuated.

CONCLUSION

Metabolic health is more closely associated with subclinical atherosclerosis than obesity as assessed by CACS.

Associations between smoking, components of metabolic syndrome and lipoprotein particle size

BACKGROUND

The clustering of metabolic and cardiovascular risk factors is known as metabolic syndrome (MetS). The risk of having MetS is strongly associated with increased adiposity and can be further modified by smoking behavior. Apolipoproteins (apo) associated with low-density lipoprotein-cholesterol (LDL-C) and high-density lipoprotein-cholesterol (HDL-C) may be altered in MetS. This study aimed to examine the association between smoking and the following parameters: MetS and its components, levels of apolipoproteins and estimated lipoprotein particle size, separately for men and women, and in different body mass index (BMI) classes.

METHODS

We included 24,389 men and 35,078 women aged between 18 and 80 years who participated in the LifeLines Cohort Study between December 2006 and January 2012; 5,685 men and 6,989 women were current smokers. Participants were categorized into three different body mass index (BMI) classes (BMI <25; BMI 25 to 30; BMI ≥30 kg/m²). MetS was defined according to the National Cholesterol Education Program's Adult Treatment Panel III (NCEP:ATPIII) criteria. Blood pressure, anthropometric and lipid measurements were rigorously standardized, and the large sample size enabled a powerful estimate of quantitative changes. The association between smoking and the individual MetS components, and apoA1 and apoB, was tested with linear regression. Logistic regression was used to examine the effect of smoking and daily tobacco smoked on risk of having MetS. All models were age adjusted and stratified by sex and BMI class.

RESULTS

Prevalence of MetS increased with higher BMI levels. A total of 64% of obese men and 42% of obese women had MetS. Current smoking was associated with a higher risk of MetS in both sexes and all BMI classes (odds ratio 1.7 to 2.4 for men, 1.8 to 2.3 for women, all P values <0.001). Current smokers had lower levels of HDL cholesterol and apoA1, higher levels of triglycerides and apoB, and higher waist circumference than non-smokers (all P <0.001). Smoking had no consistent association with blood pressure or fasting blood glucose. In all BMI classes, we found a dose-dependent association of daily tobacco consumption with MetS prevalence as well as with lower levels of HDL cholesterol, higher triglyceride levels and lower ratios of HDL cholesterol/apoA1 and, only in those with BMI <30, LDL cholesterol/apoB (all P <0.001).

CONCLUSIONS

Smoking is associated with an increased prevalence of MetS, independent of sex and BMI class. This increased risk is mainly related to lower HDL cholesterol, and higher triglycerides and waist circumference. In addition, smoking was associated with unfavorable changes in apoA1 and apoB, and in lipoprotein particle size. Please see related commentary: http://www.biomedcentral.com/1741-7015/11/196.

Metabolically healthy obesity: definitions, determinants and clinical implications

Obesity is associated with increased risk of developing metabolic syndrome (MetS), type 2 diabetes mellitus (T2DM) and cardiovascular disease (CVD) leading to higher all-cause mortality. However accumulating evidence suggests that not all obese subjects are at increased cardiometabolic risk and that the "metabolically healthy obese" (MHO) phenotype may exist in the absence of metabolic abnormalities. Despite the knowledge of the existence of obese metabolic phenotypes for some time now there is no standard set of criteria to define metabolic health, thus impacting on the accurate estimation of the prevalence of the MHO phenotype and making comparability between studies difficult. Furthermore prospective studies tracking the development of cardiometabolic disease and mortality in MHO have also produced conflicting results. Limited data regards the determinants of the MHO phenotype exist, particularly in relation to dietary and lifestyle behaviours. In light of the current obesity epidemic it is clear that current "one size fits all" approaches to tackle obesity are largely unsuccessful. Whether dietary, lifestyle and/or therapeutic interventions based on stratification of obese individuals according to their metabolic health phenotype are more effective remains to be seen, with limited and conflicting data available so far. This review will present the current state of the art including the epidemiology of MHO and its definitions, what factors may be important in determining metabolic health status and finally, some potential implications of the MHO phenotype in the context of obesity diagnosis, interventions and treatment.

Liver enzymes and vitamin D levels in metabolically healthy but obese individuals: Korean National Health and Nutrition Examination Survey

OBJECTIVE

Increased liver enzymes and decreased vitamin D levels are associated with insulin resistance and type 2 diabetes. We examined liver enzymes and vitamin D levels in metabolically healthy but obese (MHO) individuals and compared the values with those of other body size phenotypes in the Korean population.

MATERIALS/METHODS

A total of 16,190 people over the age of 18years were analyzed using data from the Fourth Korean National Health and Nutrition Examination Survey, which is a nationally representative survey. Body size phenotypes were classified into four groups by body mass index (BMI) and number of metabolic syndrome components.

RESULTS

The prevalence of MHO was 14.9% in the entire population and 47.7% in the obese population. In a correlation analysis adjusted for age, sex, and BMI, AST and ALT levels were positively correlated with insulin resistance and cardiometabolic risk factors of the metabolic syndrome, whereas vitamin D level was negatively correlated with these variables. MHO individuals had significantly lower concentrations of AST and ALT compared to metabolically abnormal obese (MAO) subjects, although vitamin D levels were not significantly different. Furthermore, a multiple logistic regression analysis revealed that MHO individuals had lower risk of liver enzyme abnormality compared to MAO after adjusting for potential confounding factors. However, the risk of vitamin D deficiency was not significantly different among groups with different body size phenotypes.

CONCLUSIONS

Although both liver enzymes and vitamin D levels are related to insulin resistance and metabolic syndrome, only liver enzymes were independently associated with MHO phenotype.

Transitional changes in energy intake, skeletal muscle content and nutritional behavior in college students during course-work based nutrition education

The purpose of this study was to investigate whether elective course work based nutrition education in university can change students' body composition and eating habits associated with obesity and its related health risk in first-year college students. A total of 38 students agreed and participated in the study. Participants received a series of lecture about obesity, weight management, and concepts of nutrition and food choices for 13 weeks. The students' BMI and body composition, including body fat and muscle contents, were measured. A 24-hour diet recall for two days was performed for food intake analysis, and the questionnaires for dietary behaviors were collected at the beginning and the end of the study. Paired t-test and χ²-test were used for statistical analysis. Data showed that most of the anthropometric parameters including body weight were not significantly changed at the end of the coursework. Interestingly, skeletal muscle contents in both obese (BMI ≥ 23) and lean (18.5 ≤ BMI ≤ 22.9) subjects were significantly increased. Total energy intake was decreased in total subjects after the study. Also, general nutrition behavior of the subjects including enough hydration and utilization of nutrition knowledge were significantly improved during the study period. The total number of responses to doing aerobic exercise was slightly increased after the study, but the average frequency of exercise in each individual was not changed. These results suggest that class-work based nutrition education on a regular basis could be a time and cost effective method for improving body composition and nutritional behavior in general college students.

Development of metabolic syndrome components in adults with a healthy obese phenotype: a 3-year follow-up

OBJECTIVE

There is a lack of data on the progression from a healthy obese phenotype toward an unhealthy obese phenotype and the development of metabolic syndrome (MetS). Our aim was to assess the development of MetS 3 years after screening in centrally obese individuals with a healthy obese phenotype and to evaluate the usefulness of repeated screening.

DESIGN AND METHODS

Eighty-eight individuals (mean age 47 years, 88% female) with central obesity as their only MetS component (ATP III criteria) at baseline screening were re-evaluated for MetS status after 3 years.

RESULTS

At follow-up, the cardiometabolic risk profile in centrally obese individuals with a healthy phenotype showed a tendency toward deterioration. Thirty-two percent developed at least one additional MetS component, 7% had developed MetS. Nobody had developed type 2 diabetes. An increased triglyceride level (n = 16) and an increased blood pressure (n = 18) were the components most often present at follow-up. The people developing additional MetS components had a lower education level compared with the group that preserved the healthy centrally obese phenotype (80 vs. 71% lower educated, P = 0.35). They also had slightly worse baseline levels of the risk factors.

CONCLUSION

The number of centrally obese individuals developing an unhealthy phenotype in this relatively short follow-up period emphasizes the need for a regular surveillance of cardiometabolic parameters in centrally obese individuals. However, it is questionable whether a repeated screening for type 2 diabetes every 3 years, as recommended by the American Diabetes Association, in this category of patients is appropriate.

The outliers become a stampede as immunometabolism reaches a tipping point

Obesity and Type 2 diabetes mellitus (T2D) are characterized by pro-inflammatory alterations in the immune system including shifts in leukocyte subset differentiation and in cytokine/chemokine balance. The chronic, low-grade inflammation resulting largely from changes in T-cell, B-cell, and myeloid compartments promotes and/or exacerbates insulin resistance (IR) that, together with pancreatic islet failure, defines T2D. Animal model studies show that interruption of immune cell-mediated inflammation by any one of several methods almost invariably results in the prevention or delay of obesity and/or IR. However, anti-inflammatory therapies have had a modest impact on established T2D in clinical trials. These seemingly contradictory results indicate that a more comprehensive understanding of human IR/T2D-associated immune cell function is needed to leverage animal studies into clinical treatments. Important outstanding analyses include identifying potential immunological checkpoints in disease etiology, detailing immune cell/adipose tissue cross-talk, and defining strengths/weaknesses of model organism studies to determine whether we can harness the promising new field of immunometabolism to curb the global obesity and T2D epidemics.

Comparison of Metabolic Characteristics of Metabolically Healthy but Obese (MHO) Middle-Aged Men According to Different Criteria

Background

To compare the prevalence and metabolic characteristics of metabolically healthy but obese (MHO) individuals according to different criteria.

Methods

We examined 186 MHO middle-aged men (age, 37.2 years; body mass index [BMI], 27.2 kg/m²). The following methods were used to determine MHO: the National Cholesterol Education Program (NCEP) Adult Treatment Panel III criteria, 0-2 cardiometabolic abnormalities; the Wildman criteria, 0-1 cardiometabolic abnormalities; the Karelis criteria, 0-1 cardiometabolic abnormalities; the homeostasis model assessment [HOMA] criteria (lowest quartile of HOMA). After dividing the overall subjects into two age groups, we compared the prevalence and clinical characteristics between MHO and at-risk groups according to four different criteria.

Results

The prevalence of MHO using the NCEP, Wildman, Kaleris, and HOMA criteria were 70.4%, 59.7%, 28.5%, and 24.2%, respectively. The agreement between the groups according to the NCEP and Wildman criteria was substantial (kappa = 0.8, P < 0.001). Among individuals 35 years or younger, and regardless of method, the MHO subjects had significantly lower weight, waist circumference, BMI, body fat percentage, insulin, HOMA, alanine aminotransferase, triglyceride (TG), and TG/high density lipoprotein cholesterol (HDL-C) ratio than the at-risk subjects (P < 0.05); However, among individuals older than 35 years old, and regardless of method, the MHO subjects had different insulin, HOMA, HDL-C, and TG/HDL-C levels than the at-risk subjects (P < 0.05).

Conclusion

The differences in metabolic profile between MHO and at-risk groups varied according to age. MHO prevalence varies considerably according to the criteria employed. Expert consensus is needed in order to define a standardized protocol for determining MHO.

Physical activity and screen time in metabolically healthy obese phenotypes in adolescents and adults

INTRODUCTION

The purpose of this study was to examine levels of physical activity (PA) and screen time (ST) in metabolically healthy obese (MHO) and metabolically unhealthy obese (MUO) adolescents and adults.

METHODS

NHANES data from obese adolescents (12-18 years, BMI z-score ≥ 95th percentile) and adults (19-85 years, BMI ≥ 30 kg/m(2)) were pooled from 2003-2005 cycles. Metabolic phenotypes were categorized as MHO (0 or 1 cardiometabolic risk factor; triglycerides, HDL-C, blood pressure, or glucose) or MUO (≥2 cardiometabolic risk factors). Logistic regression models estimated associations between phenotype and PA/ST adjusted for age, gender, BMI, race/ethnicity, menopausal status, and NHANES cycle.

RESULTS

Among adolescents, PA was not associated with MHO. In contrast, MHO adults 19-44 years were 85% more likely to engage in active transportation and 2.7 times more likely to be involved in light intensity usual daily activity versus sitting. For each minute per day, adults 45-85 years were 36% more likely to have the MHO phenotype with higher levels of moderate PA. ST was not associated with metabolic phenotypes in adolescents or adults.

CONCLUSION

The current study provides evidence that PA, but not ST, differs between MHO and MUO in adults, but not in adolescents. Future studies are needed to confirm results.

Prognostic implications for insulin-sensitive and insulin-resistant normal-weight and obese individuals from a population-based cohort

BACKGROUND

There are few prospective data on the prognosis of insulin-sensitive and insulin-resistant normal-weight (NW) or obese individuals.

OBJECTIVES

The estimated liver fat content, incidences of hyperglycemia and cardiovascular disease, and all-cause and cardiovascular mortality rates were investigated in a population-based cohort of 1658 individuals who were categorized according to BMI and insulin resistance as defined by HOMA-IR values ≥2.5 and the presence of metabolic syndrome.

DESIGN

This was a prospective cohort study with a 9-y follow-up. Anthropometric values, blood pressure, and blood metabolic variables were measured, and information on vital status was collected from demographic files at follow-up.

RESULTS

A total of 137 of 677 NW individuals (20%) were classified as insulin resistant and normal weight (IR-NW), and 72 of 330 obese individuals (22%) were classified as insulin sensitive and obese (IS-obese). Incidences of diabetes, impaired fasting glucose, and cardiovascular events were 0.4%, 6.3%, and 3.3%, respectively, in insulin-sensitive and normal-weight (IS-NW) individuals (reference category); 5.8%, 10.2%, and 6.6%, respectively, in IR-NW individuals; and 5.6%, 8.3%, and 8.3%, respectively, in IS-obese individuals. In a multiple logistic regression model, risks of incident hyperglycemia and cardiovascular events increased in both groups compared with in the reference category [HR (95% CI): 2.54 (1.42, 4.55) and 1.98 (0.86, 4.54) in IR-NW subjects; 2.16 (1.01, 4.63) and 2.76 (1.05, 7.28) in IS-obese subjects]. The estimated liver fat content significantly increased during follow-up only in the IR-NW group in the same model. Cardiovascular mortality was 2-3-fold higher in IR-NW and IS-obese than in IS-NW individuals in a Cox regression model.

CONCLUSIONS

Our data refute the existence of healthy obese phenotypes because IS-obese individuals showed increased cardiometabolic risk. The existence of unhealthy NW phenotypes is supported by their increased risk of incident hyperglycemia, fatty liver, cardiovascular events, and death.

Binge eating disorder in elderly individuals

OBJECTIVE

To preliminarily describe the clinical features of elderly individuals with binge eating disorder (BED).

METHOD

The psychological and general medical characteristics of 20 elderly individuals (65 years of age and older) who met DSM-IV-TR for BED were systematically evaluated.

RESULTS

Elderly individuals with BED reported an average (SD) of 4.5 (2.9) binge eating episodes per week. Weight and shape concerns were of significant importance for participants' schema for self-evaluation. Mood disorders were the most frequent co-occurring psychiatric disorders. Despite having a mean (SD) body mass index of 36.4 (10.6), most participants presented in good general medical health.

DISCUSSION

Regarding eating pathology, psychiatric comorbidity, and associated obesity, BED in this group of elderly individuals was similar to BED in younger adults. However, other than presenting with obesity, the participants reported good general medical health. BED might be a problem for a subset of physically healthy elderly individuals. Studies further examining psychiatric and medical presentation, including metabolic profile, of elderly individuals with BED may be warranted.

Relation of childhood obesity/cardiometabolic phenotypes to adult cardiometabolic profile: the Bogalusa Heart Study

Not all obese adults have cardiometabolic abnormalities. It is unknown whether this is true in children and, if true, whether children who have metabolically healthy overweight/obesity (MHO) will also have favorable cardiometabolic profiles in adulthood. These aspects were examined in 1,098 individuals who participated as both children (aged 5-17 years) and adults (aged 24-43 years) in the Bogalusa Heart Study between 1997 and 2002 in Bogalusa, Louisiana. MHO was defined as being in the top body mass index quartile, while low density lipoprotein cholesterol, triglycerides, mean arterial pressure, and glucose were in the bottom 3 quartiles, and high density lipoprotein cholesterol was in the top 3 quartiles. Forty-six children (4.2%) had MHO, and they were more likely to retain MHO status in adulthood compared with children in other categories (P < 0.0001). Despite markedly increased obesity in childhood and in adulthood, these same MHO children and adults showed a cardiometabolic profile generally comparable to that of nonoverweight/obese children (P > 0.05 in most cases). Moreover, there was no difference in carotid intima-media thickness in adulthood between MHO children and nonoverweight/obese children. Further, carotid intima-media thickness in adulthood was lower in MHO children than in metabolically abnormal, overweight/obese children (P = 0.003). In conclusion, the MHO phenotype starts in childhood and continues into adulthood.

Risk factors associated with the metabolic syndrome in abdominal obesity

Obesity is associated with the metabolic syndrome. However, not all obese individuals have cardiovascular risk factors (CVRF). It is not clear how many abdominally obese individuals are free of CVRF and what distinguishes them from the group of obese individuals with CVRF. In this study, we aimed to assess the associated factors and prevalence of abdominal obesity without CVRF. In our cross-sectional analysis, we included n = 4244 subjects from the Study of Health in Pomerania (SHIP), a population-based study and n = 6671 subjects from the Diabetes Cardiovascular Risk-Evaluation: Targets and Essential Data for Commitment of Treatment (DETECT) study, a representative primary care study in Germany. We defined abdominal obesity by waist-to-height ratio (WHtR) of 0.5 or greater. We assessed how many subjects with abdominal obesity had CVRF based on the definition of the metabolic syndrome. We analysed which conditions were associated with the absence of CVRF in abdominal obesity. In SHIP and DETECT, 2652 (62.5%) and 5126 (76.8%) subjects had a WHtR ≥ 0.5. Among those with a WHtR ≥ 0.5, 9.0% and 13.8% were free of CVRF and 49.9% and 52.7% had at least two CVRF in SHIP and DETECT, respectively. In both studies, after backward elimination, age, male sex, body mass index and high liver enzymes and unemployment were consistently inversely associated with the absence of CVRF. Among abdominally obese subjects, the prevalence of metabolically healthy subjects is low. Conditions consistently associated with the absence of CVRF in abdominal obesity are younger age, female sex, low BMI, and normal liver enzymes, the latter likely reflecting the absence of steatohepatitis.

Association of LIPA gene polymorphisms with obesity-related metabolic complications among severely obese patients

The lipase A, lysosomal acid, cholesterol esterase enzyme (LIPA) is involved in the hydrolysis of triglycerides (TGs) and cholesteryl esters (CEs) delivered to lysosomes. LIPA deficiency in human causes two distinct phenotypes characterized by intracellular storage of CE and derangements in the control of cholesterol production, namely the Wolman disease (WD) and the CE storage disease (CESD). To test the potential association of LIPA gene polymorphisms with obesity-related metabolic complications, promoter, exons, and intronic flanking regions of the LIPA gene were first sequenced in 25 individuals. From the 14 common polymorphisms identified, 12 tagging single-nucleotide polymorphisms (tSNPs) were genotyped in a cohort of 1,751 obese individuals. After adjustments for the effect of age, sex, diabetes, and medication, the C allele of SNP rs1051338 was associated with lower blood pressure (BP; systolic (SBP) P = 0.004; diastolic (DBP) P = 0.006). Three of the tested SNPs were associated with modifications of the plasma lipid profile. The G/G genotype of rs2071509 was associated with higher high-density lipoprotein cholesterol (HDL-C) levels (P = 0.009) and minor allele of rs1131706 was also associated with higher HDL-C (P = 0.004) and an association between rs3802656 and total cholesterol (total-C)/HDL-C ratio was identified (P = 0.04). These results thus suggest that LIPA polymorphisms contribute to the interindividual variability observed in obesity-related metabolic complications.

Impact of metabolic comorbidity on the association between body mass index and health-related quality of life: a Scotland-wide cross-sectional study of 5,608 participants

Background

The prevalence of obesity is rising in Scotland and globally. Overall, obesity is associated with increased morbidity, mortality and reduced health-related quality of life. Studies suggest that "healthy obesity" (obesity without metabolic comorbidity) may not be associated with morbidity or mortality. Its impact on health-related quality of life is unknown.

Methods

We extracted data from the Scottish Health Survey on self-reported health-related quality of life, body mass index (BMI), demographic information and comorbidity. SF-12 responses were converted into an overall health utility score. Linear regression analyses were used to explore the association between BMI and health utility, stratified by the presence or absence of metabolic comorbidity (diabetes, hypertension, hypercholesterolemia or cardiovascular disease), and adjusted for potential confounders (age, sex and deprivation quintile).

Results

Of the 5,608 individuals, 3,744 (66.8%) were either overweight or obese and 921 (16.4%) had metabolic comorbidity. There was an inverted U-shaped relationship whereby health utility was highest among overweight individuals and fell with increasing BMI. There was a significant interaction with metabolic comorbidity (p = 0.007). Individuals with metabolic comorbidty had lower utility scores and a steeper decline in utility with increasing BMI (morbidly obese, adjusted coefficient: -0.064, 95% CI -0.115, -0.012, p = 0.015 for metabolic comorbidity versus -0.042, 95% CI -0.067, -0.018, p = 0.001 for no metabolic comorbidity).

Conclusions

The adverse impact of obesity on health-related quality of life is greater among individuals with metabolic comorbidity. However, increased BMI is associated with reduced health-related quality of life even in the absence of metabolic comorbidity, casting doubt on the notion of "healthy obesity".

Insulin sensitivity deteriorates after short-term lifestyle intervention in the insulin sensitive phenotype of obesity

OBJECTIVE

To investigate the effects of a 3-month lifestyle intervention on insulin sensitivity and its related cardiometabolic factors in obese patients.

METHODS

Anthropometry, body composition, oral glucose tolerance test, lipids, alanine aminotransferase, insulin sensitivity (insulinogenic index (ISI), homeostasis model assessment, β-cell performance (disposition index)) were evaluated in 263 obese women and 93 obese men before and after 3 months of hypocaloric low fat/high protein diet associated with physical activity 30 min/day.

RESULTS

Patients were divided into 3 groups according to the intervention-induced ISI changes: group 1 (decrease), group 2 (stability) and group 3 (increase). Insulin sensitivity and the disposition index were significantly higher before the intervention in group 1 than in group 3. BMI, waist circumference, and fat mass significantly decreased in groups 1 and 3 in both sexes. β-cell performance decreased in group 1 and increased in group 3. Metabolic variables improved in group 3, whereas glucose levels increased in women of group 1. The post-intervention insulin sensitivity was lower in group 1 than in group 3.

CONCLUSION

Lifestyle intervention induces changes in insulin sensitivity and metabolic factors that depend on the pre-intervention degree of insulin sensitivity. Weight loss leads to metabolic benefits in insulin-resistant, obese patients, whereas it may paradoxically worsen the metabolic conditions in the insulin-sensitive phenotype of obesity.

All-cause mortality risk of metabolically healthy obese individuals in NHANES III

Mortality risk across metabolic health-by-BMI categories in NHANES-III was examined. Metabolic health was defined as: (1) homeostasis model assessment-insulin resistance (HOMA-IR) <2.5; (2) ≤2 Adult Treatment Panel (ATP) III metabolic syndrome criteria; (3) combined definition using ≤1 of the following: HOMA-IR ≥1.95 (or diabetes medications), triglycerides ≥1.7 mmol/L, HDL-C <1.04 mmol/L (males) or <1.30 mmol/L (females), LDL-C ≥2.6 mmol/L, and total cholesterol ≥5.2 mmol/L (or cholesterol-lowering medications). Hazard ratios (HR) for all-cause mortality were estimated with Cox regression models. Nonpregnant women and men were included (n = 4373, mean ± SD, age 37.1 ± 10.9 years, BMI 27.3 ± 5.8 kg/m², 49.4% female). Only 40 of 1160 obese individuals were identified as MHO by all definitions. MHO groups had superior levels of clinical risk factors compared to unhealthy individuals but inferior levels compared to healthy lean groups. There was increased risk of all-cause mortality in metabolically unhealthy obese participants regardless of definition (HOMA-IR HR 2.07 (CI 1.3-3.4), P < 0.01; ATP-III HR 1.98 (CI 1.4-2.9), P < 0.001; combined definition HR 2.19 (CI 1.3-3.8), P < 0.01). MHO participants were not significantly different from healthy lean individuals by any definition. While MHO individuals are not at significantly increased risk of all-cause mortality, their clinical risk profile is worse than that of metabolically healthy lean individuals.

Resistance to type 2 diabetes mellitus: a matter of hormesis?

Type 2 diabetes mellitus is characterized by subclinical systemic inflammation and impaired regulation of blood glucose levels. Interestingly, impairment of glycemic control occurs despite substantial insulin secretion early in the course of this disease. Dysfunction of several organs (including pancreatic islets, liver, skeletal muscle, adipose tissue, gut, hypothalamus and the immune system) has been implicated in the pathogenesis of type 2 diabetes mellitus. However, diabetes-promoting lifestyle factors do not inevitably cause disease in all persons exposed. Hence, defense mechanisms must exist that can keep the detrimental influence of these risk factors at bay. Hormesis describes the phenomenon that exposure to a mild stressor confers resistance to subsequent, otherwise harmful, conditions of increased stress. This Review discusses the emerging concept that the effectiveness of an adaptive (hormetic) response to detrimental lifestyle factors determines the extent of protection from progression to type 2 diabetes mellitus. Further analysis of these protective hormetic responses at the molecular level should help to identify novel targets for preventive or therapeutic intervention in patients at risk of developing type 2 diabetes mellitus or those with overt disease.

Metabolically healthy and unhealthy obesity phenotypes in the general population: the FIN-D2D Survey

BACKGROUND

The aim of this work was to examine the prevalence of different metabolical phenotypes of obesity, and to analyze, by using different risk scores, how the metabolic syndrome (MetS) definition discriminates between unhealthy and healthy metabolic phenotypes in different obesity classes.

METHODS

The Finnish type 2 diabetes (FIN-D2D) survey, a part of the larger implementation study, was carried out in 2007. The present cross-sectional analysis comprises 2,849 individuals aged 45-74 years. The MetS was defined with the new Harmonization definition. Cardiovascular risk was estimated with the Framingham and SCORE risk scores. Diabetes risk was assessed with the FINDRISK score. Non-alcoholic fatty liver disease (NAFLD) was estimated with the NAFLD score. Participants with and without MetS were classified in different weight categories and analysis of regression models were used to test the linear trend between body mass index (BMI) and various characteristics in individuals with and without MetS; and interaction between BMI and MetS.

RESULTS

A metabolically healthy but obese phenotype was observed in 9.2% of obese men and in 16.4% of obese women. The MetS-BMI interaction was significant for fasting glucose, 2-hour plasma glucose, fasting plasma insulin and insulin resistance (HOMA-IR)(p < 0.001 for all). The prevalence of total diabetes (detected prior to or during survey) was 37.0% in obese individuals with MetS and 4.3% in obese individuals without MetS (p < 0.001). MetS-BMI interaction was significant (p < 0.001) also for the Framingham 10 year CVD risk score, NAFLD score and estimated liver fat %, indicating greater effect of increasing BMI in participants with MetS compared to participants without MetS. The metabolically healthy but obese individuals had lower 2-hour postload glucose levels (p = 0.0030), lower NAFLD scores (p < 0.001) and lower CVD risk scores (Framingham, p < 0.001; SCORE, p = 0.002) than normal weight individuals with MetS.

CONCLUSIONS

Undetected Type 2 diabetes was more prevalent among those with MetS irrespective of the BMI class and increasing BMI had a significantly greater effect on estimates of liver fat and future CVD risk among those with MetS compared with participants without MetS. A healthy obese phenotype was associated with a better metabolic profile than observed in normal weight individuals with MetS.

The association between inflammatory biomarkers and metabolically healthy obesity depends of the definition used

BACKGROUND/OBJECTIVES

To assess the distribution of interleukin (IL)-1β, IL-6, tumour necrosis factor (TNF)-α and C-reactive protein (CRP) according to the different definitions of metabolically healthy obesity (MHO).

SUBJECTS/METHODS

A total of 881 obese (body mass index (BMI) > or =30 kg/m2) subjects derived from the population-based CoLaus Study participated in this study. MHO was defined using six sets of criteria including different combinations of waist, blood pressure, total high-density lipoprotein cholesterol or low-density lipoprotein -cholesterol, triglycerides, fasting glucose, homeostasis model, high-sensitivity CRP, and personal history of cardiovascular, respiratory or metabolic diseases. IL-1β, IL-6 and TNF-α were assessed by multiplexed flow cytometric assay. CRP was assessed by immunoassay.

RESULTS

On bivariate analysis some, but not all, definitions of MHO led to significantly lower levels of IL-6, TNF-α and CRP compared with non-MH obese subjects. Most of these differences became nonsignificant after multivariate analysis. An posteriori analysis showed a statistical power between 9 and 79%, depending on the inflammatory biomarker and MHO definition considered. Further increasing sample size to overweight+obese individuals (BMI > or =25 kg/m2, n=2917) showed metabolically healthy status to be significantly associated with lower levels of CRP, while no association was found for IL-1β. Significantly lower IL-6 and TNF-α levels were also found with some but not all MHO definitions, the differences in IL-6 becoming nonsignificant after adjusting for abdominal obesity or percent body fat.

CONCLUSIONS

MHO individuals present with decreased levels of CRP and, depending on MHO definition, also with decreased levels in IL-6 and TNF-α. Conversely, no association with IL-1β levels was found.

Prevalence and clinical profile of metabolic obesity and phenotypic obesity in Asian Indians

BACKGROUND

We estimated the prevalence of metabolically obese nonobese (MONO), metabolically obese obese (MOO), and metabolically healthy obese (MHO) individuals and correlated this with the prevalence of coronary artery disease (CAD) compared to metabolically healthy nonobese (MHNO) in urban South Indians.

METHOD

Study subjects (n = 2350) were recruited from the Chennai Urban Rural Epidemiology Study. Generalized obesity was defined as a body mass index (BMI) ≥25 kg/m(2), based on the World Health Organization Asia Pacific guidelines. Metabolic syndrome (MS) was diagnosed based on the South Asian Modified-National Cholesterol Education Programme criteria. Coronary artery disease was defined by known myocardial infarction or Q waves on resting electrocardiogram.

RESULTS

Metabolically obese nonobese was defined as nonobese subjects (BMI < 25 kg/m(2)) with MS, MOO as obesity (BMI ≥ 25 kg/m(2)) with MS, MHO as obese subjects (BMI ≥ 25 kg/m(2)) with no MS, and MHNO as no obesity or MS. Metabolically obese nonobese was identified in 355 (15.1%), MOO in 348 (14.8%), MHO in 312 (13.3%), and MHNO in 1335 (56.8%) subjects. The prevalence of CAD among the MONO, MOO, MHO, and MHNO was 5.5%, 4.2%, 1.4%, and 2.6%. However, when age standardization was done, there was no statistically significant increase in the risk of CAD among MONO [odds ratio (OR) = 1.300, 95% confidence interval (CI) 0.706-2.394, p = .339], MOO (OR = 1.651, 95% CI 0.852-3.199, p = .137), and MHO (OR = 0.524, 95% CI 0.250-2.130, p = .564) groups compared to MHNO, perhaps due to small numbers.

CONCLUSION

Metabolic obesity may have different clinical implications than phenotypic obesity.