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 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.     

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.     

Overweight and Obese Pet Owners: Respondent and Pet Characteristics in the Rural Midwestern United States

The obesity epidemic has impacted both people and pets in the rural Midwestern United States (MWUS). Tailoring health advice to the socio-demographic characteristics and dietary patterns of owners and their pets can help promote adherence to health behavior changes for owners and foster health improvements for both owners and pets. The authors completed this cross-sectional study in the rural MWUS with the objective of describing health-related characteristics of non-over-weight/obese versus overweight/obese [NOO vs. OO] cat and dog owners and their pets. The primary aim was to detect differences that could inform health recommendations. For both cat and dog owners, dietary and lifestyle profiles differed between those who were non-overweight/obese and those who were overweight/obese. NOO dog owners trended toward fewer health problems, took fewer medications (p < 0.02), took more supplements (p < 0.03), and ate less fast food (p < 0.03) and more fish (p < 0.001) than OO owners. Dogs owned by NOO owners had more owner-initiated activity (M ± SD: 44.6 ± 63.0 vs. 27.2 ± 26.4 min/d) and were on more supplements (p < 0.003). NOO cat owners were younger (p < 0.03), had fewer health problems (p < 0.04), took fewer medications (p < 0.04), engaged in more exercise (p < 0.02), and ate less fast food (p < 0.03) than OO cat owners. The only significant difference between cats of NOO vs. OO owners was their predominant gender: 57% vs. 74% female (p < 0.01). These findings have implications for marketing, education, and health care for both owners and pets. Further investigation of the relationship between pet ownership and health is warranted.     

Longitudinal associations between BMI,waist circumference,and cardiometabolic risk in US youth: Monitoring implications

Objective:

This study examined whether change in body mass index (BMI) or waist circumference (WC) is associated with change in cardiometabolic risk factors and differences between cardiovascular disease specific and diabetes specific risk factors among adolescents. We also sought to examine any differences by gender or baseline body mass status.

Design:

The article is a longitudinal analysis of pre‐ and post‐data collected in the HEALTHY trial. Participants were 4,603 ethnically diverse adolescents who provided complete data at 6th and 8th grade assessments.

Methods:

The main outcome measures were percent change in the following cardiometabolic risk factors: fasting triglycerides, systolic and diastolic blood pressure, high density lipoprotein cholesterol, and glucose as well as a clustered metabolic risk score. Main exposures were change in BMI or WC z‐score. Models were run stratified by gender; secondary models were additionally stratified by baseline BMI group (normal, overweight, or obese).

Results:

Analysis showed that when cardiometabolic risk factors were treated as continuous variables, there was strong evidence (P < 0.001) that change in BMI z‐score was associated with change in the majority of the cardiovascular risk factors, except fasting glucose and the combined risk factor score for both boys and girls. There was some evidence that change in WC z‐score was associated with some cardiovascular risk factors, but change in WC z‐score was consistently associated with changes in fasting glucose.

Conclusions:

In conclusion, routine monitoring of BMI should be continued by health professionals, but additional information on disease risk may be provided by assessing WC.     

Cardiometabolic risks during anabolic hormone supplementation in older men

Objective:

To determine the cardiometabolic risks of testosterone and growth hormone (GH) replacement therapy to youthful levels during aging.

Design and Methods:

A double‐masked, partially placebo controlled study in 112 men 65‐90 years‐old was conducted. Transdermal testosterone (5 g vs. 10 g/day) using a Leydig Cell Clamp and subcutaneous recombinant GH (rhGH) (0 vs. 3 vs. 5 μg/kg/day) were administered for 16‐weeks. Measurements included testosterone and IGF‐1 levels, body composition by DEXA, and cardiometabolic risk factors (upper body fat, blood pressure, insulin sensitivity, fasting triglycerides, HDL‐cholesterol, and serum adiponectin) at baseline and after 16 weeks of treatment.

Results:

Some cardiometabolic factors improved (total and trunk fat, triglycerides, HDL‐cholesterol) and others worsened (systolic blood pressure, insulin sensitivity index [QUICKI], adiponectin). Cardiometabolic risk composite scores (CRCSs) improved (?0.69 ± 1.55, P < 0.001). In multivariate analyses, QUICKI, triglycerides, and HDL‐cholesterol contributed 33%, 16%, and 14% of the variance in CRCS, respectively. Pathway analyses indicated that changes in fat and lean mass were related to individual cardiometabolic variables and CRCS in a complex manner. Changes in BMI, reflecting composite effects of changes in fat and lean mass, were more robustly associated with cardiometabolic risks than changes in fat mass or LBM individually.

Conclusions:

Testosterone and rhGH administration was associated with diverse changes in individual cardiometabolic risk factors, but in aggregate appeared not to worsen cardiometabolic risk in healthy older men after 4‐months. The long‐term effects of these and similar anabolic therapies on cardiovascular events should be investigated in populations with greater functional limitations along with important health disabilities including upper body obesity and other cardiometabolic risks.

     

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.     

Comparison of body adiposity index (BAI) and bmi with estimations of % body fat in clinically severe obese women

Objective:

Body adiposity index (BAI), a new surrogate measure of body fat (hip circumference/(height^1.5 – 18)), has been proposed as an alternative to body mass index (BMI). We compared BAI with BMI, and each of them with laboratory measures of body fat‐derived from bioimpedance analysis (BIA), air displacement plethysmography (ADP), and dual‐energy X‐ray absorptiometry (DXA) in clinically severe obese (CSO) participants.

Design and Methods:

Nineteen prebariatric surgery CSO, nondiabetic women were recruited (age = 32.6 ± 7.7 SD; BMI = 46.5 ± 9.0 kg/m²). Anthropometrics and body fat percentage (% fat) were determined from BIA, ADP, and DXA. Scatter plots with lines of equality and Bland–Altman plots were used to compare BAI and BMI with % fat derived from BIA, ADP, and DXA. BAI and BMI correlated highly with each other (r = 0.90, P < 0.001).

Results:

Both BAI and BMI correlated significantly with % fat from BIA and ADP. BAI, however, did not correlate significantly with % fat from DXA (r = 0.42, P = 0.08) whereas BMI did (r = 0.65, P = 0.003). BMI was also the single best predictor of % fat from both BIA (r² = 0.80, P < 0.001) and ADP (r² = 0.65, P < 0.001). The regression analysis showed that the standard error of the estimate (SEE), or residual error around the regression lines, was greater for BAI comparisons than for BMI comparisons with BIA, ADP, and DXA. Consistent with this, the Bland and Altman plots indicated wider 95% confidence intervals for BAI difference comparisons than for BMI difference comparisons for their respective means for BIA, ADP, and DXA.

Conclusions:

Thus, BAI does not appear to be an appropriate proxy for BMI in CSO women.     

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.     

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.     

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.     

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.     

Comparison of three bioelectrical impedance methods with DXA in overweight and obese men

Objective: To compare bioelectrical impedance analysis (BIA) of body composition using three different methods against DXA in overweight and obese men. Research Methods and Procedures: Forty‐three healthy overweight or obese men (ages 25 to 60 years; BMI, 28 to 43 kg/m²) underwent BIA assessment of body composition using the ImpediMed SFB7 (version 6; ImpediMed, Ltd., Eight Mile Plains, Queensland, Australia) in multifrequency mode (Imp‐MF) and DF50 single‐frequency mode (Imp‐SF) and the Tanita UltimateScale (Tanita Corp., Tokyo, Japan). Validity was assessed by comparison against DXA using linear regression and limits of agreement analysis. Results: All three BIA methods showed good relative agreement with DXA [Imp‐MF: fat mass (FM), r² = 0.81; fat‐free mass (FFM), r² = 0.81; percentage body fat (BF%), r² = 0.69; Imp‐SF: FM, r² = 0.65; FFM, r² = 0.76; BF%, r² = 0.40; Tanita: BF%, r² = 0.44; all p < 0.001]. Absolute agreement between DXA and Imp‐MF was poor, as indicated by a large bias and wide limits of agreement (bias, ±1.96 standard deviation; FM, ?6.6 ± 7.7 kg; FFM, 8.0 ± 7.1 kg; BF%, ?7.0 ± 6.6%). Imp‐SF and Tanita exhibited a smaller bias but wide limits of agreement (Imp‐SF: FM, ?1.1 ± 8.5 kg; FFM, 2.5 ± 7.9 kg; BF%, ?1.7 ± 7.3% Tanita: BF%, 1.2 ± 9.5%). Discussion: Compared with DXA, Imp‐MF produced large bias and wide limits of agreement, and its accuracy estimating body composition in overweight or obese men was poor. Imp‐SF and Tanita demonstrated little bias and may be useful for group comparisons, but their utility for assessment of body composition in individuals is limited.     

A natural fiber complex reduces body weight in the overweight and obese: A double‐blind,randomized, placebo‐controlled study

Objective:

A proprietary natural fiber complex (Litramine IQP G‐002AS) derived from Opuntia ficus‐indica, and standardized on lipophilic activity, was previously shown in preclinical and human studies to reduce dietary fat absorption through gastrointestinal (GI) fat binding. Here, we investigated the efficacy and safety of IQP G‐002AS in body weight reduction.

Design and Methods:

One hundred twenty‐five overweight and obese adults participated in the study. Subjects were advised on physical activity, and received nutritional counseling, including hypocaloric diet plans (30% energy from fat and 500 kcal deficit/day). After a 2‐week placebo run‐in phase, subjects were randomized to receive either 3 g/day of IQP G‐002AS (IQ) or a placebo. The primary endpoint was change in body weight from baseline; secondary endpoints included additional obesity measures and safety parameters.

Results:

One hundred twenty‐three subjects completed the 12‐week treatment phase (intention‐to‐treat (ITT) population: 30 male and 93 female; mean BMI: 29.6 ± 2.8 kg/m² and age: 45.4 ± 11.3 years). The mean body weight change from baseline was 3.8 ± 1.8 kg in IQ vs. 1.4 ± 2.6 kg in placebo (P < 0.001). More IQ subjects lost at least 5% of their initial body weight compared to placebo (P = 0.027). Compared with placebo, IQ also showed significantly greater reduction in BMI, body fat composition, and waist circumference. IQ was well tolerated with no adverse reactions reported.

Conclusions:

These results suggest that the natural fiber complex Litramine IQP G‐002AS is effective in promoting weight loss.     

Nicotinamide nucleotide transhydrogenase mRNA expression is related to human obesity

Objective:

A spontaneous deletion in the nicotinamide nucleotide transhydrogenase (Nnt) gene eliminating exons 7‐11 in C57BL/6J (B6J) mice is associated with reduced glucose‐stimulated insulin secretion in vitro, impaired glucose tolerance, higher epigonadal fat mass, and altered susceptibility to diet induced obesity of male B6J mice was proposed. A potential implication for NNT in human adipose tissue distribution has not been investigated so far.

Design and Methods:

Therefore, NNT mRNA expression in paired human samples of visceral (vis) and subcutaneous (sc) adipose tissue from 221 subjects with a wide range of body mass index (BMI), insulin sensitivity, and glucose tolerance was analyzed.

Results:

NNT mRNA expression is significantly higher in visceral fat of obese patients and correlates with body weight, BMI, % body fat, visceral and sc fat area, waist and hip circumference, and fasting plasma insulin (FPI). Multivariate linear regression analysis revealed visceral NNT expression as age and gender independent predictor of BMI, waist circumference, visceral fat area, and % body fat, but not FPI and 2 h OGTT glucose.

Conclusion:

In conclusion, a functional relevance of NNT in the development of human obesity and visceral fat distribution was suggested here.     

Lifestyle Behaviors in Metabolically Healthy and Unhealthy Overweight and Obese Women: A Preliminary Study

Background

Few studies have examined dietary data or objective measures of physical activity (PA) and sedentary behavior among metabolically healthy overweight/obese (MHO) and metabolically unhealthy overweight/obese (MUO). Thus, the purpose is to determine whether PA, sedentary behavior and/or diet differ between MHO and MUO in a sample of young women.

Methods

Forty-six overweight/obese (BMI ≥25 kg/m²) African American and Caucasian women 19–35 years were classified by cardiometabolic risk factors, including elevated blood pressure, triglyceride, glucose and C-reactive protein, low high density lipoprotein, and insulin resistance (MUO ≥2; MHO, <2). Time (mins/day) in light, moderate, vigorous PA, and sedentary behavior were estimated using an accelerometer (≥3 days; ≥8 hrs wear time). Questionnaires were used to quantify sitting time, TV/computer use and usual daily activity. The Block Food Frequency Questionnaire assessed dietary food intake. Differences between MHO and MUO for lifestyle behaviors were tested with linear regression (continuous data) or logistic regression (categorical data) after adjusting for age, race, BMI, smoking and accelerometer wear and/or total kilocalories, as appropriate.

Results

Women were 26.7±4.7 years, with a mean BMI of 31.1±3.7 kg/m², and 61% were African American. Compared to MUO (n = 9), MHO (n = 37; 80%) spent less mins/day in sedentary behavior (difference: -58.1±25.5, p = 0.02), more mins/day in light PA (difference: 38.2±16.1, p = 0.02), and had higher daily METs (difference: 0.21±0.09, p = 0.03). MHO had higher fiber intakes (g/day of total fiber, soluble fiber, fruit/vegetable fiber, bean fiber) and daily servings of vegetables; but lower daily dairy servings, saturated fat, monounsaturated fat and trans fats (g/day) compared to MUO.

Conclusion

Compared to MUO, MHO young women demonstrate healthier lifestyle habits with less sedentary behavior, more time in light PA, and healthier dietary quality for fat type and fiber. Future studies are needed to replicate findings with larger samples that include men and women of diverse race/ethnic groups.     

Association between Adherence to Nutritional Guidelines,the Metabolic Syndrome and Adiposity Markers in a French Adult General Population

Introduction

Few studies have focused on the association between diet quality scores and the Metabolic Syndrome (MetS), a multi-component condition predictive of cardiovascular diseases (CVD) and death. The present study aims at investigating, in a cross-sectional design, the association between adherence to the French dietary guidelines through an a priori score – the French Nutrition and Health Program-Guideline Score (PNNS-GS) – and cardiovascular risk factors (CVRF) including the MetS and adiposity markers.

Methods

7902 French adults participating in the NutriNet-Santé study (an on-going web-based cohort study) attended a clinical and biological examination between January 2011 and November 2012: a fasting blood sample was drawn, blood pressure and body composition (bio-impedance) were measured. Multivariate linear and logistic regression models were used to assess the association between PNNS-GS and CVRF or the MetS.

Results

An increase of PNNS-GS was significantly negatively associated with waist circumference (WC), systolic and diastolic blood pressure (SBP and DBP) and serum triglycerides concentrations. From bottom to top quartile of PNNS-GS, SBP decreased from 129.9 to 128.8 mm Hg, DBP from 76.7 to 75.9 mm Hg, serum triglycerides concentrations from 110.8 to 104.6 mg/dL and WC from 94.8 to 90.1 cm for men and 81.3 to 78.9 cm for women. All adiposity markers (waist and hip circumference, % body fat, % trunk fat, % leg fat) were markedly reduced across quartiles of PNNS-GS and linearly. Individuals with a better PNNS-GS (quartile 4 vs quartile 1) were less likely to have the MetS (OR=0.71, 95% CI: 0.56-0.89).

Conclusion

The negative association between a higher adherence to the French dietary guidelines and a number of CVRF, the MetS prevalence and regional adiposity supports the importance of promoting the PNNS dietary guidelines in the population for the prevention of cardiometabolic abnormalities and hence, cardiovascular diseases.     

Parental obesity moderates the relationship between childhood appetitive traits and weight

Objective:

In this study, the independent and combined associations between childhood appetitive traits and parental obesity on weight gain from 0 to 24 months and body mass index (BMI) z‐score at 24 months in a diverse community‐based sample of dual parent families (n = 213) were examined.

Design and Methods:

Participants were mothers who had recently completed a randomized trial of weight loss for overweight/obese postpartum women. As measures of childhood appetitive traits, mothers completed subscales of the Children's Eating Behavior Questionnaire, including Desire to Drink (DD), Enjoyment of Food (EF), and Satiety Responsiveness (SR), and a 24‐h dietary recall for their child. Heights and weights were measured for all children and mothers and self‐reported for mothers' partners. The relationship between children's appetitive traits and parental obesity on toddler weight gain and BMI z‐score were evaluated using multivariate linear regression models, controlling for a number of potential confounders.

Results:

Having two obese parents was related to greater weight gain from birth to 24 months independent of childhood appetitive traits, and although significant associations were found between appetitive traits (DD and SR) and child BMI z‐score at 24 months, these associations were observed only among children who had two obese parents. When both parents were obese, increasing DD and decreasing SR were associated with a higher BMI z‐score.

Conclusions:

The results highlight the importance of considering familial risk factors when examining the relationship between childhood appetitive traits on childhood obesity.     

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.     

Disability,Arthritis, and Body Weight among Adults 45 Years and Older

Objectives : To examine the association between body weight and disability among persons with and without self‐reported arthritis. Research Methods and Procedures : Data were analyzed for noninstitutionalized adults, 45 years or older, in states that participated in the Behavioral Risk Factor Surveillance System. Self‐reported BMI (kilograms per meter squared) was used to categorize participants into six BMI‐defined groups: underweight (<18.5), normal weight (18.5 to <25), overweight (25 to <30), obese, class 1 (30 to <35), obese, class 2 (35 to <40), and obese, class 3 (≥40). Results : Class 3 obesity (BMI ≥ 40) was significantly associated with disability among participants both with and without self‐reported arthritis. The adjusted odds ratio (AOR) for disability in participants with class 3 obesity was 2.75 [95% confidence interval (CI) = 2.22 to 3.40] among those with self‐reported arthritis and 1.77 (95% CI = 1.20 to 2.62) among those without self‐reported arthritis compared with those of normal weight (BMI 18.5 to <25). Persons with self‐reported arthritis who were obese, class 2 (BMI 35 to <40) and obese, class 1 (BMI 30 to <35) and women with self‐reported arthritis who were overweight (BMI 25 to <30) also had higher odds of disability compared with those of normal weight [AOR = 1.72 (95% CI = 1.47 to 2.00), AOR = 1.30 (95% CI = 1.17 to 1.44), and AOR = 1.18 (95% CI = 1.06 to 1.32), respectively]. Discussion : Our findings reveal that obesity is associated with disability. Preventing and controlling obesity may improve the quality of life for persons with and without self‐reported arthritis.