Uric acid best predicts metabolically unhealthy obesity with increased cardiovascular risk in youth and adults

Objective:

The obesity prevalence is growing worldwide and largely responsible for cardiovascular disease, the most common cause of death in the western world. The rationale of this study was to distinguish metabolically healthy from unhealthy overweight/obese young and adult patients as compared to healthy normal weight age matched controls by an extensive anthropometric, laboratory, and sonographic vascular assessment.

Design and Methods:

Three hundred fifty five young [8 to < 18 years, 299 overweight/obese(ow/ob), 56 normal weight (nw)] and 354 adult [>18‐60 years, 175 (ow/ob), 179 nw)] participants of the STYJOBS/EDECTA (STYrian Juvenile Obesity Study/Early DEteCTion of Atherosclerosis) cohort were analyzed. STYJOBS/EDECTA (NCT00482924) is a crossectional study to investigate metabolic/cardiovascular risk profiles in normal and ow/ob people free of disease except metabolic syndrome (MetS).

Results:

From 299 young ow/ob subjects (8‐< 18 years), 108 (36%), and from 175 adult ow/ob subjects (>18‐60 years), 79 (45%) had positive criteria for MetS. In both age groups, prevalence of MetS was greater among males. Overweight/obese subjects were divided into “healthy” (no MetS criterion except anthropometry fulfilled) and “unhealthy” (MetS positive). Although percentage body fat did not differ between “healthy” and “unhealthy” ow/ob, nuchal and visceral fat were significantly greater in the “unhealthy” group which had also significantly higher values of carotid intima media thickness (IMT). With MetS as the dependent variable, two logistic regressions including juveniles < 18 years or adults >18 years were performed. The potential predictor variables selected with the exception of age and gender by t test comparisons included IMT, ultrasensitive c‐reactive protein (US‐CRP), IL‐6, malondialdehyde (MDA), oxidized LDL, leptin, adiponectin, uric acid (UA), aldosterone, cortisol, transaminases, fibrinogen. In both groups, uric acid and in adults only, leptin and adiponectin, turned out as the best predictor.

Conclusion:

Serum levels of UA are a significant predictor of unhealthy obesity in juveniles and adults.     

Serum amyloid A is found on ApoB‐containing lipoproteins in obese humans with diabetes

Objective:

In murine models of obesity/diabetes, there is an increase in plasma serum amyloid A (SAA) levels along with redistribution of SAA from high‐density lipoprotein (HDL) to apolipoprotein B (apoB)‐containing lipoprotein particles, namely, low‐density lipoprotein and very low‐density lipoprotein. The goal of this study was to determine if obesity is associated with similar SAA lipoprotein redistribution in humans.

Design and Methods:

Three groups of obese individuals were recruited from a weight loss clinic: healthy obese (n = 14), metabolic syndrome (MetS) obese (n = 8), and obese with type 2 diabetes (n = 6). Plasma was separated into lipoprotein fractions by fast protein liquid chromatography, and SAA was measured in lipid fractions using enzyme‐linked immunosorbent assay and Western blotting.

Results:

Only the obese diabetic group had SAA detectable in apoB‐containing lipoproteins, and SAA reverted back to HDL with active weight loss.

Conclusions:

In human subjects, SAA is found in apoB‐containing lipoprotein particles only in obese subjects with type 2 diabetes, but not in healthy obese or obese subjects with MetS.     

Insulin Resistance is the Best Predictor of the Metabolic Syndrome in Subjects With a First‐Degree Relative With Type 2 Diabetes

Although obesity is associated with insulin resistance and the metabolic syndrome (MetS), some obese individuals are metabolically healthy. Conversely, some lean individuals are insulin resistant (IR) and at increased cardiometabolic risk. To determine the relative importance of insulin sensitivity, BMI and waist circumference (WC) in predicting MetS, we studied these two extreme groups in a high‐risk population. One thousand seven hundred and sixty six subjects with a first‐degree relative with type 2 diabetes were stratified by BMI and homeostasis model assessment of insulin resistance (HOMA_IR) into groups. IR groups had higher triglycerides, fasting glucose, and more diabetes than their BMI‐group insulin sensitive (IS) counterparts. Within both IS and IR groups, obesity was associated with higher HOMA_IR and diastolic blood pressure (BP), but no difference in other metabolic variables. MetS (Adult Treatment Panel III (ATPIII)) prevalence was higher in IR groups (P < 0.001) and more subjects met each MetS criterion (P < 0.001). Within each BMI category, HOMA_IR independently predicted MetS (P < 0.001) whereas WC did not. Within IS and IR groups, age and WC, but not BMI, were independent determinants of MetS (P < 0.001). WC was a less meaningful predictor of MetS at higher values of HOMA_IR. HOMA_IR was a better predictor of MetS than WC or BMI (receiver operating characteristic (ROC) area under the curve 0.76 vs. 0.65 vs. 0.59, P < 0.001). In conclusion, insulin sensitivity rather than obesity is the major predictor of MetS and is better than WC at identifying obese individuals with a healthier metabolic profile. Further, as many lean individuals with a first‐degree relative with type 2 diabetes are IR and metabolically unhealthy, they may all benefit from metabolic testing.     

Obesity and body fat classification in the metabolic syndrome: Impact on cardiometabolic risk metabotype

Objective:

Obesity is a key factor in the development of the metabolic syndrome (MetS), which is associated with increased cardiometabolic risk. We investigated whether obesity classification by BMI and body fat percentage (BF%) influences cardiometabolic profile and dietary responsiveness in 486 MetS subjects (LIPGENE dietary intervention study).

Design and Methods:

Anthropometric measures, markers of inflammation and glucose metabolism, lipid profiles, adhesion molecules, and hemostatic factors were determined at baseline and after 12 weeks of four dietary interventions (high saturated fat (SFA), high monounsaturated fat (MUFA), and two low fat high complex carbohydrate (LFHCC) diets, one supplemented with long chain n‐3 polyunsaturated fatty acids (LC n‐3 PUFAs)).

Results:

About 39 and 87% of subjects classified as normal and overweight by BMI were obese according to their BF%. Individuals classified as obese by BMI (≥30 kg/m²) and BF% (≥25% (men) and ≥35% (women)) (OO, n = 284) had larger waist and hip measurements, higher BMI and were heavier (P < 0.001) than those classified as nonobese by BMI but obese by BF% (NOO, n = 92). OO individuals displayed a more proinflammatory (higher C reactive protein (CRP) and leptin), prothrombotic (higher plasminogen activator inhibitor‐1 (PAI‐1)), proatherogenic (higher leptin/adiponectin ratio) and more insulin resistant (higher HOMA‐IR) metabolic profile relative to the NOO group (P < 0.001). Interestingly, tumor necrosis factor‐α (TNF‐α) concentrations were lower post‐intervention in NOO individuals compared with OO subjects (P < 0.001).

Conclusions:

In conclusion, assessing BF% and BMI as part of a metabotype may help to identify individuals at greater cardiometabolic risk than BMI alone.     

Beta and alpha cell function in metabolically healthy but obese subjects: Relationship with entero‐insular axis

Objective:

Obesity is widely acknowledged as a critical risk factor for metabolic complications. Among obese subjects, there is a phenotype of metabolically healthy but obese (MHO) individuals that shows a favorable cardiometabolic risk profile. We aimed to evaluate the potential mechanisms underlying the metabolic profile of this subset, including alpha and beta cell function and entero‐insular axis.

Design and Methods:

One hundred twenty‐nine obese and 24 nonobese subjects were studied. Obese participants were defined as MHO or at‐risk obese, according to the homeostasis model of assessment‐insulin resistance (HOMA‐IR) index (MHO: lower tertile of HOMA‐IR, n = 43; at‐risk: upper tertile of HOMA‐IR index, n = 41). Insulin, glucagon, and incretin responses after a 120′ oral glucose tolerance test (75‐g OGTT) were investigated.

Results:

During OGTT, MHO individuals showed in comparison with at‐risk subjects: lower fasting and afterloads plasma levels of glucose, insulin, and C‐peptide; higher disposition index; lower fasting (P = 0.004) and at 30′ (P = 0.01) plasma glucose‐dependent insulinotropic polypeptide (GIP) levels; lower area under the curve (AUC) (0‐30) for GIP (P = 0.008); higher glucagon‐like peptide‐1 (GLP‐1) plasma levels at 90′ (P = 0.02) and 120′ (P = 0.02); lower glucagon plasma levels at baseline (P = 0.04) and at 30′ (P = 0.03); and appropriate glucagon suppression after the oral glucose load.

Conclusions:

MHO subjects show, as well as normal‐weight individuals, a lower diabetogenic profile by virtue of higher disposition index and unaffected entero‐insular axis. At‐risk obese individuals present increased GIP levels that might play a role in determining increased glucagon secretion and inappropriate glucagon responses after glucose load, thus contributing to impaired glucose homeostasis.     

Body composition determinants of metabolic phenotypes of obesity in nonobese and obese postmenopausal women

Objective : Although obesity is typically associated with increased cardiovascular risk, a subset of obese individuals display a normal metabolic profile (“metabolically healthy obese,” MHO) and conversely, a subset of nonobese subjects present with obesity‐associated cardiometabolic abnormalities (“metabolically obese nonobese,” MONO). The aim of this cross‐sectional study was to identify the most important body composition determinants of metabolic phenotypes of obesity in nonobese and obese healthy postmenopausal women. Design and Methods : We studied a total of 150 postmenopausal women (age 54 ± 7 years, mean ± 1 SD). Based on a cardiometabolic risk score, nonobese (body mass index [BMI] ≤ 27) and obese women (BMI > 27) were classified into “metabolically healthy” and “unhealthy” phenotypes. Total and regional body composition was assessed with dual‐energy X‐ray absorptiometry (DXA). Results : In both obese and nonobese groups, the “unhealthy” phenotypes were characterized by frequent bodyweight fluctuations, higher biochemical markers of insulin resistance, hepatic steatosis and inflammation, and higher anthropometric and DXA‐derived indices of central adiposity, compared with “healthy” phenotypes. Indices of total adiposity, peripheral fat distribution and lean body mass were not significantly different between “healthy” and “unhealthy” phenotypes. Despite having increased fat mass, MHO women exhibited comparable cardiometabolic parameters with healthy nonobese, and better glucose and lipid levels than MONO. Two DXA‐derived indices, trunk‐to‐legs and abdominal‐to‐gluteofemoral fat ratio were the major independent determinants of the “unhealthy” phenotypes in our cohort. Conclusions : The “metabolically obese phenotype” is associated with bodyweight variability, multiple cardiometabolic abnormalities and an excess of central relative to peripheral fat in postmenopausal women. DXA‐derived centrality ratios can discriminate effectively between metabolic subtypes of obesity in menopause.     

The relationship of C‐reactive protein to obesity‐related depressive symptoms: A longitudinal study

Objective:

Obesity has been shown to produce a state of systematic low‐grade inflammation that may have detrimental neuropsychiatric effects.

Design and Methods:

Longitudinal associations between obesity, inflammation, and depressive symptoms amongst a cohort of older English adults over 4 years of follow‐up were examined. Participants were 3,891 obese and nonobese people drawn from the English longitudinal study of ageing (ELSA) [aged 64.9 (SD = 8.8) years, 44.6% men]. Depressive symptoms were assessed at baseline and after 4 years of follow‐up using the eight‐item center for epidemiological studies—depression scale (CES‐D).

Results:

Approximately 26.3% (N = 1,025) of the sample were categorized as obese at baseline. Obesity at baseline was associated with elevated levels of depressive symptoms at follow‐up (P < 0.001), in analyses that adjusted for depression levels at baseline and sociodemographic and background variables including the prevalence of permanent illness/disability, alcohol consumption, sedentary behavior, and smoking. In addition, C‐reactive protein (CRP) concentrations at baseline were independently associated with CES‐D depression scores at follow‐up (P = 0.008) in fully adjusted analyses. Subsequent mediation analyses revealed that CRP levels explained ～20% of the obesity‐related longitudinal change in depression scores.

Conclusion:

These data suggest that chronic inflammation may be a key determinant of depressive symptoms in obesity.     

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 ≥30kg/m²) and non-obese (BMI <30kg/m²). 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.     

Gastric bypass does not normalize obesity‐related changes in ghrelin profile and leads to higher acylated ghrelin fraction

Objective:

Gastric bypass (GBP) lowers food intake, body weight, and insulin resistance in severe obesity (SO). Ghrelin is a gastric orexigenic and adipogenic hormone contributing to modulate energy balance and insulin action. Total plasma ghrelin (T‐Ghr) level is low and inversely related to body weight and insulin resistance in moderately obese patients, but these observations may not extend to the orexigenic acylated form (A‐Ghr) whose plasma concentration increase in moderate obesity.

Design and Methods:

We investigated the impact of GBP on plasma T‐, A‐, and A/T‐Ghr in SO patients (n = 28, 20 women), with measurements at baseline and 1, 3, 6, and 12 months after surgery. Additional cross‐sectional comparison was performed between nonobese, moderately obese, and SO individuals before GBP and at the end of the follow‐up period.

Results:

Before GBP, SO had lowest T‐Ghr and highest A/T‐Ghr profile compared with both nonobese and moderately obese individuals. Lack of early (0‐3 months from GBP) T‐Ghr changes masked a sharp increase in A‐Ghr and A/T‐Ghr profile (P < 0.05) that remained elevated following later increments (6‐12 months) of both T‐ and A‐Ghr (P < 0.05). Levels of A‐Ghr and A/T‐Ghr at 12 months of follow‐up remained higher than in matched moderately obese individuals not treated with surgery (P < 0.05).

Conclusions:

The data show that following GBP, early T‐Ghr stability masks elevation of A/T‐Ghr, that is stabilized after later increments of both T‐ and A‐hormones. GBP does not normalize the obesity‐associated elevated A/T‐Ghr ratio, instead resulting in enhanced A‐Ghr excess. Excess A‐Ghr is unlikely to contribute to, and might limit, the common GBP‐induced declines of appetite, body weight, and insulin resistance.     

Movement Discordance between Healthy and Non-Healthy US Adults

Introduction

Physical activity is known to significantly impact cardiometabolic health. Accelerometer data, as a measure of physical activity, can be used to objectively identify a disparity in movement (movement discordance) between healthy and unhealthy adults. The purpose of this study was to examine the Movement Discordance between healthy and unhealthy adults in a large US population sample.

Methods

Demographic, health and accelerometer data from the National Health and Nutrition Examination Study (NHANES) 2003–2004 and 2005–2006 cohorts were used for this study. Participants were classified as either having a “normal” or “abnormal” value for each cardiometabolic health parameter examined, based on published criteria. Linear regression analyses were performed to determine significance of each abnormal health parameter (risk factor) in its unique effect on the accelerometer counts, controlling for age and gender. Average accelerometer counts per minute (cpm) by gender and age categories were estimated separately for the groups of normal and abnormal cardiometabolic risk.

Results

Average cpm for those with healthy levels of each individual cardiometabolic health parameter range from 296 cpm (for C reactive protein) to 337 cpm (for waist circumference), while average cpm for those with abnormal levels of each individual cardiometabolic health parameter range from 216 cpm (for insulin) to 291 cpm (for LDL-cholesterol). After controlling for age and gender, waist circumference, HbA1c, Insulin, Homocysteine, and HDL-Cholesterol were the cardiometabolic health parameters that showed significant, unique and independent effects on cpm. Overall, individuals who have abnormal values for all significant cardiometabolic health parameters (“unhealthy”) averaged 267 cpm (SE = 15 cpm), while the healthy sample of this study averaged 428 cpm (SE = 10 cpm). The difference in cpm between the unhealthy and healthy groups is similar between males and females. Further, for both males and females, the cpm gap between unhealthy and healthy is largest in the 30s (males: 183 cpm; females 144 cpm) and lessens as age increases, with the lowest gap seen in those 80+ years (males, 81 cpm; females, 85 cpm).

Conclusion

This Movement Discordance between healthy and unhealthy adults represents a gap in movement that needs to be closed to improve the health of individuals with, or at risk for cardiometabolic disease.     

Meta‐analysis of the association between body mass index and health‐related quality of life among adults,assessed by the SF‐36

Objective:

Obesity is associated with impaired overall health‐related quality of life but individual studies suggest the relationship may differ for mental and physical quality of life. A systematic review using Medline, Embase, PsycINFO and ISI Web of Knowledge, and random effects meta‐analysis was undertaken.

Design and Methods:

Studies were included in the meta‐analysis if they were conducted on adults (defined as age >16 years), reported an overall physical and mental component score of the SF‐36, and, or both. Heterogeneity was assessed using I² statistics and publication and small study biases using funnel plots and Egger's test. Between‐study heterogeneity was explored using meta‐regression.

Results:

Eight eligible studies provided 42 estimates of effect size, based on 43,086 study participants. Adults with higher than normal body mass index had significantly reduced physical quality of life with a clear dose‐response relationship across all categories. Among class III obese adults, the score was reduced by 9.72 points (95% Confidence Interval 7.24, 12.20, P < 0.001). Mental quality of life was also significantly reduced among class III obese (?1.75, 95% confidence interval ?3.33, ?0.16, P = 0.031), but was not significantly different among obese (class I and class II) individuals, and was significantly increased among overweight adults (0.42, 95% confidence interval 0.17, 0.67, P = 0.001), compared to normal weight individuals. Heterogeneity was high in some categories, but there was no significant publication or small study bias.

Conclusions:

Different patterns were observed for physical and mental HRQoL, but both were impaired in obese individuals. This meta‐analysis provides further evidence on the impact of obesity on both aspects of health‐related quality of life.

     

Metabolic Abnormalities Are Common among South American Hispanics Subjects with Normal Weight or Excess Body Weight: The CRONICAS Cohort Study

Objective

We aimed to characterize metabolic status by body mass index (BMI) status.

Methods

The CRONICAS longitudinal study was performed in an age-and-sex stratified random sample of participants aged 35 years or older in four Peruvian settings: Lima (Peru’s capital, costal urban, highly urbanized), urban and rural Puno (both high-altitude), and Tumbes (costal semirural). Data from the baseline study, conducted in 2010, was used. Individuals were classified by BMI as normal weight (18.5–24.9 kg/m²), overweight (25.0–29.9 kg/m²), and obese (≥30 kg/m²), and as metabolically healthy (0–1 metabolic abnormality) or metabolically unhealthy (≥2 abnormalities). Abnormalities included individual components of the metabolic syndrome, high-sensitivity C-reactive protein, and insulin resistance.

Results

A total of 3088 (age 55.6±12.6 years, 51.3% females) had all measurements. Of these, 890 (28.8%), 1361 (44.1%) and 837 (27.1%) were normal weight, overweight and obese, respectively. Overall, 19.0% of normal weight in contrast to 54.9% of overweight and 77.7% of obese individuals had ≥3 risk factors (p<0.001). Among normal weight individuals, 43.1% were metabolically unhealthy, and age ≥65 years, female, and highest socioeconomic groups were more likely to have this pattern. In contrast, only 16.4% of overweight and 3.9% of obese individuals were metabolically healthy and, compared to Lima, the rural and urban sites in Puno were more likely to have a metabolically healthier profile.

Conclusions

Most Peruvians with overweight and obesity have additional risk factors for cardiovascular disease, as well as a majority of those with a healthy weight. Prevention programs aimed at individuals with a normal BMI, and those who are overweight and obese, are urgently needed, such as screening for elevated fasting cholesterol and glucose.     

PROP taster status interacts with the built environment to influence children's food acceptance and body weight status

Objectives:

Eating behaviors and obesity are complex phenotypes influenced by genes and the environment, but few studies have investigated the interaction of these two variables. The purpose of this study was to use a gene‐environment interaction model to test for differences in children's food acceptance and body weights.

Design and Methods:

Inherited ability to taste 6‐n‐propylthiouracil (PROP) was assessed as a marker of oral taste responsiveness. Food environment was classified as “healthy” or “unhealthy” based on proximity to outlets that sell fruits/vegetables and fast foods using Geographic Information Systems (GIS). The cohort consisted of 120 children, ages 4‐6 years, recruited from New York City over 2005‐2010. Home address and other demographic variables were reported by parents and PROP status, food acceptance, and anthropometrics were assessed in the laboratory. Based on a screening test, children were classified as PROP tasters or non‐tasters. Hierarchical linear models analysis of variance was performed to examine differences in food acceptance and body mass index (BMI) z‐scores as a function of PROP status, the food environment (“healthy” vs. “unhealthy”), and their interaction.

Results and Conclusion:

Results showed an interaction between taster status and the food environment on BMI z‐score and food acceptance. Non‐taster children living in healthy food environments had greater acceptance of vegetables than taster children living in healthy food environments (P ≤ 0.005). Moreover, non‐tasters from unhealthy food environments had higher BMI z‐scores than all other groups (P ≤ 0.005). Incorporating genetic markers of taste into studies that assess the built environment may improve the ability of these measures to predict risk for obesity and eating behaviors. Obesity (2012)     

The Prevalence of Metabolically Healthy Obese Subjects Defined by BMI and Dual‐Energy X‐Ray Absorptiometry

Nearly one‐third of obese (OB) people are reported to be metabolically healthy based on BMI criteria. It is unknown whether this holds true when more accurate adiposity measurements are applied such as dual‐energy X‐ray absorptiometry (DXA). We compared differences in the prevalence of cardiometabolic abnormalities among adiposity groups classified using BMI vs. DXA criteria. A total of 1,907 adult volunteers from Newfoundland and Labrador participated. BMI and body fat percentage (%BF; measured using DXA) were measured following a 12‐h fasting period. Subjects were categorized as normal weight (NW), overweight (OW), or OB based on BMI and %BF criteria. Cardiometabolic abnormalities considered included elevated triglyceride, glucose, and high‐sensitivity C‐reactive protein (hsCRP) levels, decreased high‐density lipoprotein (HDL) cholesterol levels, insulin resistance, and hypertension. Subjects were classified as metabolically healthy (0 or 1 cardiometabolic abnormality) or abnormal (≥2 cardiometabolic abnormalities). We found low agreement in the prevalence of cardiometabolic abnormalities between BMI and %BF classifications (κ = 0.373, P < 0.001). Among NW and OW subjects, the prevalence of metabolically healthy individuals was similar between BMI and %BF (77.6 vs. 75.7% and 58.8 vs. 62.5%, respectively) however, there was a pronounced difference among OB subjects (34.0 vs. 47.7%, P < 0.05). Similar trends were evident using three additional definitions to characterize metabolically healthy individuals. Our findings indicate that approximately one‐half of OB people are metabolically healthy when classified using %BF criteria which is significantly higher than previously reported using BMI. Caution should therefore be taken when making inferences about the metabolic health of an OB population depending on the method used to measure adiposity.     

The inverse relation of HDL anti‐oxidative functionality with serum amyloid a is lost in metabolic syndrome subjects

Objective:

Anti‐oxidative properties of high density lipoproteins (HDL) are relevant for atheroprotection. HDL carry serum amyloid A (SAA), which may impair HDL functionality. We questioned whether HDL anti‐oxidative capacity is determined by SAA.

Design and Methods:

Relationships of HDL anti‐oxidative capacity (% inhibition of low density lipoprotein oxidation in vitro) with SAA were determined in 54 non‐diabetic subjects without metabolic syndrome (MetS) and 68 subjects with MetS (including 51 subjects with Type 2 diabetes mellitus).

Results:

SAA levels were higher in MetS subjects, coinciding higher high sensitive C‐reactive protein (hs‐CRP) and lower HDL cholesterol and apolipoprotein (apo) A‐I levels (P<0.001 for all). HDL anti‐oxidative capacity was not different between subjects with and without MetS (P=0.76), but the HDL anti‐oxidation index (HDL anti‐oxidative capacity multiplied by individual HDL cholesterol concentrations), as a measure of global anti‐oxidative functionality of HDL, was lower in Mets subjects (P<0.001). HDL anti‐oxidative capacity was correlated inversely with SAA levels in subjects without MetS (r=‐0.286, P=0.036). Notably, this relationship was independent of HDL cholesterol or apoA‐I (P<0.05 for both). In contrast, no relation of HDL anti‐oxidative capacity with SAA was observed in MetS subjects (r=0.032, P=0.80). The relationship of SAA with HDL anti‐oxidative capacity was different in subjects with MetS compared to subjects without MetS (P=0.039 for the interaction between the presence of MetS and SAA on HDL anti‐oxidative capacity) taking age and diabetes status into account.

Conclusion:

Higher SAA levels may impair HDL anti‐oxidative functionality. The relationship of this physiologically relevant HDL functionality measure with circulating SAA levels is apparently disturbed in metabolic syndrome.     

Associations of leg fat accumulation with adiposity‐related biological factors and risk of metabolic syndrome

Objective:

To examine associations between regional fat mass (FM) distribution and cardiometabolic risk factors among ethnic minority groups, such as non‐Hispanic blacks and Hispanics.

Design and Methods:

The associations among 8,802 US residents who participated in the 1999‐2004 US National Health and Nutrition Examination Survey were examined. Body composition was measured using dual‐energy X‐ray absorptiometry. Leg fat indices included leg FM, leg FM percent (FM%), leg to whole body FM ratio (leg/whole), and leg to trunk FM ratio (leg/trunk). The correlation between leg fat indices and adiposity‐related risk factors, as well as the association of these indices with metabolic syndrome (MetS) was evaluated.

Results:

After adjusting for covariates including age, gender, and trunk FM or trunk FM%, higher leg FM and leg FM% were, in general, correlated favorably with adiposity‐related risk factors and associated with lower odds of MetS in all ethnicities, including non‐Hispanic whites and blacks and Hispanic groups. In addition, in all multivariate‐adjusted models, leg/whole and leg/trunk ratios were strongly associated with lower levels of most risk factors and decreased odds of MetS in these ethnicities (all odds ratios comparing extreme quintiles < 0.1).

Conclusions:

Results show that leg fat accumulation is inversely associated with adiposity‐related biological factors and risk of MetS in both whites and ethnic groups, suggesting that regional fat distribution plays an important role in the etiology of adiposity‐related diseases in these populations.     

Diet composition and activity level of at risk and metabolically healthy obese american adults

Objective:

Obesity often clusters with other major cardiovascular disease risk factors, yet a subset of the obese appears to be protected from these risks. Two obesity phenotypes are described, (i) “metabolically healthy” obese, broadly defined as body mass index (BMI) ≥ 30 kg/m² and favorable levels of blood pressure, lipids, and glucose; and (ii) “at risk” obese, BMI ≥ 30 with unfavorable levels of these risk factors. More than 30% of obese American adults are metabolically healthy. Diet and activity determinants of obesity phenotypes are unclear. We hypothesized that metabolically healthy obese have more favorable behavioral factors, including less adverse diet composition and higher activity levels than at risk obese in the multi‐ethnic group of 775 obese American adults ages 40‐59 years from the International Population Study on Macro/Micronutrients and Blood Pressure (INTERMAP) cohort.

Design and Methods:

In gender‐stratified analyses, mean values for diet composition and activity behavior variables, adjusted for age, race, and education, were compared between metabolically healthy and at risk obese.

Results:

Nearly one in five (149/775 or 19%) of obese American INTERMAP participants were classified as metabolically healthy obese. Diet composition and most activity behaviors were similar between obesity phenotypes, although metabolically healthy obese women reported higher sleep duration than at risk obese women.

Conclusions:

These results do not support hypotheses that diet composition and/or physical activity account for the absence of cardiometabolic abnormalities in metabolically healthy obese.     

Dietary Patterns and the Metabolic Syndrome in Obese and Non‐obese Framingham Women**

Objectives: To examine the relationship between habitual dietary patterns and the metabolic syndrome (MetS) in women and to identify foci for preventive nutrition interventions. Research Methods and Procedures: Dietary patterns, nutrient intake, cardiovascular disease (CVD), and MetS risk factors were characterized in 1615 Framingham Offspring‐Spouse Study (FOS) women. Dietary pattern subgroups were compared for MetS prevalence and CVD risk factor status using logistic regression and analysis of covariance. Analyses were performed overall in women and stratified on obesity status; multivariate models controlled for age, apolipoprotein E (APOE) genotypes, and CVD risk factors. Results: Food and nutrient profiles and overall nutritional risk of five non‐overlapping habitual dietary patterns of women were identified including Heart Healthier, Lighter Eating, Wine and Moderate Eating, Higher Fat, and Empty Calories. Rates of hypertension and low high‐density lipoprotein levels were high in non‐obese women, but individual MetS risk factor levels were substantially increased in obese women. Overall MetS risk varied by dietary pattern and obesity status, independently of APOE and CVD risk factors. Compared with obese or non‐obese women and women overall with other dietary patterns, MetS was highest in those with the Empty Calorie pattern (contrast p value: p < 0.05). Discussion: This research shows the independent relationship between habitual dietary patterns and MetS risk in FOS women and the influence of obesity status. High overall MetS risk and the varying prevalence of individual MetS risk factors in female subgroups emphasize the importance of preventive nutrition interventions and suggest potential benefits of targeted behavior change in both obese and non‐obese women by dietary pattern.     

Serum hemorphin‐7 levels are decreased in obesity

Objective:

Hemorphin peptides exhibit biological activities that interfere with the endorphin system, the inflammatory response, and blood‐pressure control. VV‐hemorphin‐7 and LVV‐hemorphin‐7 peptides exert a hypotensive effect, in particular, by inhibiting the renin–angiotensin system. Furthermore, levels of circulating hemorphin‐7 peptides have been found to be decreased in diseases such as type 1 and type 2 diabetes.

Design and Methods:

Because type 2 diabetes and obesity share common features, such as insulin resistance, microinflammation, high glomerular‐filtration rate (GFR), and cardiovascular risk, we evaluated serum VV‐hemorphin‐7 like immunoreactivity (VVH7‐i.r.) levels, using an enzyme‐linked immunosorbent assay method, on a group of 54 obese subjects without diabetes or hypertension, compared with a group of 33 healthy normal‐weight subjects.

Results:

Circulating VVH7‐i.r. levels were significantly decreased in the obese group compared with the control group (1.98 ± 0.19 vs. 4.86 ± 0.54 µmol/l, respectively, P < 0.01), and a significant negative correlation between VVH7‐i.r. and diastolic blood pressure (DBP) was found in obese patients (r = ?0.35, P = 0.011). There was no significant correlation between VVH7‐i.r. level and insulin resistance, metabolic syndrome, or GFR.

Conclusions:

The decreased serum hemorphin‐7 found in obese subjects, as in diabetes, may contribute to the development of hypertension and to the cardiovascular risk associated with these metabolic diseases.

     

A randomized,phase 3 trial of naltrexone SR/bupropion SR on weight and obesity‐related risk factors (COR‐II)

Objective:

To examine the effects of naltrexone/bupropion (NB) combination therapy on weight and weight‐related risk factors in overweight and obese participants.

Design and Methods:

CONTRAVE Obesity Research‐II (COR‐II) was a double‐blind, placebo‐controlled study of 1,496 obese (BMI 30‐45 kg/m²) or overweight (27‐45 kg/m² with dyslipidemia and/or hypertension) participants randomized 2:1 to combined naltrexone sustained‐release (SR) (32 mg/day) plus bupropion SR (360 mg/day) (NB32) or placebo for up to 56 weeks. The co‐primary endpoints were percent weight change and proportion achieving ≥5% weight loss at week 28.

Results:

Significantly (P < 0.001) greater weight loss was observed with NB32 versus placebo at week 28 (?6.5% vs. ?1.9%) and week 56 (?6.4% vs. ?1.2%). More NB32‐treated participants (P < 0.001) experienced ≥5% weight loss versus placebo at week 28 (55.6% vs. 17.5%) and week 56 (50.5% vs. 17.1%). NB32 produced greater improvements in various cardiometabolic risk markers, participant‐reported weight‐related quality of life, and control of eating. The most common adverse event with NB was nausea, which was generally mild to moderate and transient. NB was not associated with increased events of depression or suicidality versus placebo.

Conclusion:

NB represents a novel pharmacological approach to the treatment of obesity, and may become a valuable new therapeutic option.