Effect of body fat and gender on body temperature distribution

It is well known that body composition can influence peripheral heat loss and skin temperature. That the distribution of body fat is affected by gender is well known; however, there is little information on how body composition and gender influences the measure of skin temperature. This study evaluated skin temperature distribution according to body fat percentage (BF%) and gender. A sample of 94 apparently healthy volunteers (47 women and 47 men) was assessed with Dual-Energy X-Ray Absorptiometry (DXA) and infrared thermography (mean, maximum and minimum temperatures – T_Mean, T_Max and T_Min). The sample was divided into groups, according to health risk classification, based on BF%, as proposed by the American College of Sports Medicine: Average (n = 58), Elevated (n = 16) or High (n = 20). Women had lower T_Mean in most regions of interest (ROI). In both genders, group High had lower temperature values than Average and Elevated in the trunk, upper and lower limbs. In men, palms and posterior hands had a tendency (p < 0.05) for increased temperature along with increased BF%. T_Mean, T_Max and T_Min of trunk, upper and lower limbs were negatively correlated with BF% and the fat percentage of each segment (upper limbs, lower limbs and trunk). The highest correlations found in women were between posterior trunk and BF% (rho = −0.564, p < 0.001) and, in men, between anterior trunk and BF% (rho = −0.760, p < 0.001). Overall, this study found that women have lower skin temperature than men, which was related with higher BF%. Facial temperature seems not to be influenced by body fat. With the future collection of data on the relationship between BF% and skin temperature while taking into account factors such as body morphology, gender, and ethnicity, we conclude that measurement of BF may be reliably estimated with the use of thermal imaging technology.     

Body fat, abdominal fat, and body fat distribution is related to left atrial diameter in young children

In adults, the size of the left atria (LA) has important prognostic information. In obese adults, adolescents and children enlargement of LA have been observed. This has not been investigated on a population-based level in young children. We therefore assessed if total body fat mass (TBF), abdominal fat, and body fat distribution were related to LA diameter. Cross-sectional study of 244 children (boys = 137 and girls n = 107) aged 8-11 years, recruited from an urban population-based cohort. Dual-energy X-ray absorptiometry (DXA) measured total lean body mass, TBF, and abdominal fat mass (AFM). Body fat was also calculated as a percentage of body mass (BF%). Body fat distribution (AFM/TBF) was calculated. Echocardiography was performed with two-dimensional guided M-mode. LA diameter was measured and left ventricular mass (LVM) was calculated. Systolic blood pressure and diastolic blood pressure were measured and maturity assessed according to Tanner. There were significant (P < 0.05) univariate correlations for all children between TBF (r = 0.40), BF% (r = 0.32), AFM (r = 0.41), and AFM/TBF (r = 0.41) vs. LA diameter. Multiple regression analyses with the inclusion of possible confounders such as lean body mass, blood pressure, gender, age, and Tanner stage revealed that TBF, AFM, and AFM/TBF were all independently related to LA diameter. Differences in the different body fat measurements explained 6-9% of the variance in LA size. These results demonstrated that both total body fat, AFM, and body fat distribution are already at a young age negatively and independently associated to LA diameter.     

Television viewing and obesity in 300 women: evaluation of the pathways of energy intake and physical activity

We assessed the roles of energy intake and physical activity in the relationships among television (TV) viewing, body composition, and obesity using high-quality measurement methods. Adult women (n = 300) reported TV viewing behavior, which was categorized into infrequent (≤ 1 h/day), moderate (2 h/day), and frequent (≥ 3 h/day) viewing. Body fat percentage (BF%) was assessed using plethysmography (Bod Pod) and BMI was calculated from height and body weight. Energy intake and physical activity, including time spent in sedentary, moderate, and vigorous physical activity (PA), were objectively measured using 7-day weighed food records and 7-day accelerometry, respectively. The mean BF% of frequent TV viewers (34.6 ± 6.9%) was significantly greater (F = 3.9, P = 0.0218) than those of moderate (31.5 ± 6.7%) and infrequent viewers (30.8 ± 7.0%); however, BMI did not differ across the TV viewing groups (F = 0.8, P = 0.4172). Controlling statistically for differences in age, education, time in sedentary activity, time in moderate activity, and energy intake, considered individually, had no influence on the relationships between TV viewing and BF%, nor TV and BMI. Moreover, the relationship between TV and BF% remained significant after adjusting for differences in BMI (F = 3.6, P = 0.0276). However, adjusting for total PA reduced the relationship between TV and BF% to nonsignificance (F = 2.5, P = 0.0810), as did time spent in vigorous PA (F = 2.2, P = 0.1307). These data suggest a strong relationship between TV viewing and BF%. This association appears to be due, in part, to differences in total PA, particularly vigorous PA, but not time spent in sedentary activity, moderate activity, or energy intake.     

Short-term regional meal fat storage in nonobese humans is not a predictor of long-term regional fat gain

Although body fat distribution strongly predicts metabolic health outcomes related to excess weight, little is known about the factors an individual might exhibit that predict a particular fat distribution pattern. We utilized the meal fatty acid tracer-adipose biopsy technique to assess upper and lower body subcutaneous (UBSQ and LBSQ, respectively) meal fat storage in lean volunteers who then were overfed to gain weight. Meal fatty acid storage in UBSQ and LBSQ adipose tissue, as well as daytime substrate oxidation (indirect calorimetry), was measured in 28 nonobese volunteers [n = 15 men, body mass index = 22.1 ± 2.5 (SD)] before and after an ～8-wk period of supervised overfeeding (weight gain = 4.6 ± 2.2 kg, fat gain = 3.8 ± 1.7 kg). Meal fat storage (mg/g adipose tissue lipid) in UBSQ (visit 1: 0.78 ± 0.34 and 1.04 ± 0.71 for women and men, respectively, P = 0.22; visit 2: 0.71 ± 0.24 and 0.90 ± 0.37 for women and men, respectively, P = 0.08) and LBSQ (visit 1: 0.60 ± 0.23 and 0.48 ± 0.29 for women and men, respectively, P = 0.25; visit 2: 0.62 ± 0.24 and 0.65 ± 0.23 for women and men, respectively, P = 0.67) adipose tissue did not differ between men and women at either visit. Fractional meal fatty acid storage in UBSQ (0.31 ± 0.15) or LBSQ (0.19 ± 0.13) adipose tissue at visit 1 did not predict the percent change in regional body fat in response to overfeeding. These data indicate that meal fat uptake trafficking in the short term (24 h) is not predictive of body fat distribution patterns. In general, UBSQ adipose tissue appears to be a favored depot for meal fat deposition in both sexes, and redistribution of meal fatty acids likely takes place at later time periods.     

Relative hypoadiponectinemia, insulin resistance, and increased visceral fat in euthyroid prepubertal girls with low-normal serum free thyroxine

A lower activity of the thyroid axis within the clinical reference range is related to a dysmetabolic phenotype in adult populations. We posited that such an association is already present as early as in prepubertal childhood. Serum thyroid stimulating hormone (TSH) and free T4, body fat (bioelectric impedance), insulin resistance (homeostasis model assessment of insulin resistance (HOMA(IR))), total and high molecular weight (HMW)-adiponectin and serum lipids were assessed in 234 euthyroid prepubertal children (113 boys and 121 girls) attending primary care clinics. Visceral fat (abdominal ultrasound) was measured in a subset of these subjects (n = 147; 74 boys and 73 girls). Explants of visceral adipose tissue from an additional six prepubertal children (three boys and three girls) were used to study the regulation of total and HMW-adiponectin by thyroid hormone. Serum free T4 was in girls independently associated with HMW-adiponectin, HOMA(IR) and visceral fat, so that circulating HMW-adiponectin decreased by 30% (β = 0.305 P < 0.005, R(2) = 0.13) and HOMA(IR) and visceral fat increased, respectively, by 90% (β = -0.255 P < 0.01, R(2) = 0.05) and 30% (β = -0.369, P < 0.005, R(2) = 0.12) from the highest to the lowest tertile of serum free T4. Nonsignificant differences in these parameters were found in boys. Treatment of visceral fat explants with thyroid hormone increased total and HMW-adiponectin by 70% and 53%, respectively, above control values (P < 0.01). In conclusion, a dysmetabolic phenotype, consisting of relative hypoadiponectinemia, insulin resistance and increased visceral fat, is associated with low-normal serum free thyroxine in euthyroid prepubertal girls. These associations may be partly explained by a positive regulation of HMW-adiponectin secretion by thyroid hormone.     

Body adiposity and type 2 diabetes: increased risk with a high body fat percentage even having a normal BMI

Obesity is the major risk factor for the development of prediabetes and type 2 diabetes. BMI is widely used as a surrogate measure of obesity, but underestimates the prevalence of obesity, defined as an excess of body fat. We assessed the presence of impaired glucose tolerance or impaired fasting glucose (both considered together as prediabetes) or type 2 diabetes in relation to the criteria used for the diagnosis of obesity using BMI as compared to body fat percentage (BF%). We performed a cross-sectional study including 4,828 (587 lean, 1,320 overweight, and 2,921 obese classified according to BMI) white subjects (66% females), aged 18-80 years. BMI, BF% determined by air-displacement plethysmography (ADP) and conventional blood markers of glucose metabolism and lipid profile were measured. We found a higher than expected number of subjects with prediabetes or type 2 diabetes in the obese category according to BF% when the sample was globally analyzed (P < 0.0001) and in the lean BMI-classified subjects (P < 0.0001), but not in the overweight or obese-classified individuals. Importantly, BF% was significantly higher in lean (by BMI) women with prediabetes or type 2 diabetes as compared to those with normoglycemia (NG) (35.5 ± 7.0 vs. 30.3 ± 7.7%, P < 0.0001), whereas no differences were observed for BMI. Similarly, increased BF% was found in lean BMI-classified men with prediabetes or type 2 diabetes (25.2 ± 9.0 vs. 19.9 ± 8.0%, P = 0.008), exhibiting no differences in BMI or waist circumference. In conclusion, assessing BF% may help to diagnose disturbed glucose tolerance beyond information provided by BMI and waist circumference in particular in male subjects with BMI <25 kg/m(2) and over the age of 40.     

The effect of abdominal exercise on abdominal fat

The purpose of this study was to investigate the effect of abdominal exercises on abdominal fat. Twenty-four healthy, sedentary participants (14 men and 10 women), between 18 and 40 years, were randomly assigned to 1 of the following 2 groups: control group (CG) or abdominal exercise group (AG). Anthropometrics, body composition, and abdominal muscular endurance were tested before and after training. The AG performed 7 abdominal exercises, for 2 sets of 10 repetitions, on 5 d·wk(-1) for 6 weeks. The CG received no intervention, and all participants maintained an isocaloric diet throughout the study. Significance was set at p = 0.05 for all tests. There was no significant effect of abdominal exercises on body weight, body fat percentage, android fat percentage, android fat, abdominal circumference, abdominal skinfold and suprailiac skinfold measurements. The AG performed significantly greater amount of curl-up repetitions (47 ± 13) compared to the CG (32 ± 9) on the posttest. Six weeks of abdominal exercise training alone was not sufficient to reduce abdominal subcutaneous fat and other measures of body composition. Nevertheless, abdominal exercise training significantly improved muscular endurance to a greater extent than the CG.     

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.     

Impaired insulin sensitivity and elevated ectopic fat in healthy obese vs. nonobese prepubertal children

Insulin sensitivity is impaired and ectopic fat (accretion of lipids outside of typical adipose tissue depots) increased in obese adults and adolescents. It is unknown how early in life this occurs; thus, it is important to evaluate young children to identify potential factors leading to the development of metabolic syndrome. We examined an ethnically diverse cohort of healthy, exclusively prepubertal children (N = 123; F = 57, M = 66; age 8.04 ± 0.77 years) to examine differences in insulin sensitivity and ectopic and visceral fat deposition between obese and nonobese youth. Obesity was categorized by age- and sex-adjusted BMI z-scores (nonobese = z-score <2 (N = 94) and obese = z-score ≥2 (N = 29)). Insulin sensitivity was assessed by both a frequently sampled intravenous glucose tolerance test (S(i)) and the homeostatic model assessment of insulin resistance (HOMA(IR)). Intramyocellular lipids (IMCLs) from soleus and intrahepatic lipids (IHLs) were assessed by magnetic resonance spectroscopy, visceral adipose tissue (VAT) by magnetic resonance imaging, and total body fat by dual-energy X-ray absorptiometry. We also examined serum lipids (total cholesterol, triglycerides, high-density lipoprotein cholesterol (HDL-C) and low-density lipoprotein cholesterol) and blood pressure (diastolic and systolic). Obese children exhibited significantly lower S(i) (5.9 ± 5.98 vs. 13.43 ± 8.18 (mμ/l)(-1)·min(-1), P = 0.01) and HDL-C and higher HOMA(IR) (1.68 ± 1.49 vs. 0.63 ± 0.47, P < 0.0001), IMCL (0.74 ± 0.39 vs. 0.44 ± 0.21% water peak, P < 0.0001), IHL (1.49 ± 1.13 vs. 0.54 ± 0.42% water peak, P < 0.0001), VAT (20.16 ± 8.01 vs. 10.62 ± 5.44 cm(2), P < 0.0001), total cholesterol, triglycerides, low-density lipoprotein cholesterol, and systolic blood pressure relative to nonobese children. These results confirm significantly increased ectopic fat and insulin resistance in healthy obese vs. nonobese children prior to puberty. Excessive adiposity during early development appears concomitant with precursors of type 2 diabetes and the metabolic syndrome.     

Insulin sensitivity and regional fat gain in response to overfeeding

Although insulin resistance and type 2 diabetes (T2DM) are associated with upper body fat distribution, it is unknown whether insulin resistance predisposes to upper body fat gain or whether upper body fat gain causes insulin resistance. Our objective was to determine whether insulin sensitivity predicts abdominal (subcutaneous and/or visceral) fat gain in normal weight adults. Twenty-eight (15 men) lean (BMI = 22.1 ± 2.5 kg/m(2)), healthy adults underwent ~8 weeks of overfeeding to gain ~4 kg fat. Body composition was assessed before and after overfeeding, using dual-energy X-ray absorptiometry (DXA) and abdominal computed tomography to measure total and regional (visceral, abdominal, and lower body subcutaneous) fat gain. We assessed insulin sensitivity with an intravenous glucose tolerance test (IVGTT) and the 24-h insulin area under the curve (AUC). We found a wide range of insulin sensitivity and a relatively narrow range of body fat distribution in this normal weight cohort. Participants gained 3.8 ± 1.7 kg of body fat (4.6 ± 2.2 kg body weight). The baseline 24-h AUC of insulin concentration was positively correlated with percent body fat (r = 0.43, P < 0.05). The contribution of leg fat gain to total fat gain ranged from 29 to 79%, whereas the contributions of abdominal subcutaneous fat and visceral fat gain to total fat gain ranged from 17 to 69% and -5 to 22%, respectively. Baseline insulin sensitivity, whether measured by an IVGTT (S(i)) or the 24-h AUC insulin, did not predict upper body subcutaneous or visceral fat gain in response to overfeeding. We conclude that reduced insulin sensitivity is not an obligate precursor to upper body fat gain.     

Lower extremity fat mass is associated with insulin resistance in overweight and obese individuals: the CARDIA study

Lower extremity fat mass (LEFM) has been shown to be favorably associated with glucose metabolism. However, it is not clear whether this relationship is similar across varying levels of obesity. We hypothesized that lower amounts of LEFM is associated with higher insulin resistance (IR) and this association may vary according to weight status. Participants with available measures were examined from the Coronary Artery Risk Development in Young Adults study (CARDIA), a multi-center longitudinal study of the etiology of atherosclerosis in black and white men and women aged 38-50 years old in 2005-2006 (n = 1,579). The homeostasis model assessment of IR (HOMA(IR)) was calculated to estimate IR, regional adiposity was measured using dual energy X-ray absorptiometry (DXA), and weight status was defined according to BMI categories. Obese and overweight participants exhibited higher IR, total fat mass (FM), trunk FM (TFM), and LEFM compared to normal weight participants. After controlling for age, height, race, study center, education, smoking, and cardiorespiratory fitness (CRF), greater LEFM was significantly associated with higher IR only in normal weight men and women. Further adjustment for TFM revealed that lower LEFM was significantly associated with higher IR in overweight and obese men and women and the positive association in normal weight individuals was attenuated. These results suggest that excess adiposity in the lower extremities may attenuate the metabolic risk observed at a given level of abdominal adiposity in overweight and obese individuals. Weight status presents additional complexity since the metabolic influence of adipose tissue may not be homogenous across anatomic regions or level of obesity.     

Predictors of ectopic fat accumulation in liver and pancreas in obese men and women

The aim of the present study was to determine the relationship between body fat distribution, adipocytokines, inflammatory markers, fat intake and ectopic fat content of liver and pancreas in obese men and women. A total of 12 lean subjects (mean age 47.25 ± 14.88 years and mean BMI 22.85 ± 2), 38 obese subjects (18 men and 20 women) with mean age 49.1 ± 13.0 years and mean BMI 34.96 ± 4.21 kg/m2 were studied. Measurements: weight, height, BMI, waist circumference, as well as glucose, insulin, HOMA (homeostasis model assessment of insulin resistance), cholesterol, triglycerides, high-density lipoprotein cholesterol, high sensitivity C-reactive protein, daily energy intake, leptin, and adiponectin. Magnetic resonance was used to evaluate visceral, subcutaneous adipose tissue (SCAT) as well as liver and pancreas lipid content using in-phase and out-of-phase magnetic resonance imaging (MRI) sequence. Obese subjects had significantly higher weight, waist circumference, SCAT, deep SCAT, visceral adipose tissue (VAT), liver and pancreatic lipid content than lean subjects. Obese women had significantly lower VAT, liver and pancreas lipid content regardless of same BMI. In multiple regression analyses, the variance of liver lipid content explained by gender and VAT was 46%. When HOMA was added into a multiple regression, a small increase in the proportion of variance explained was observed. A 59.2% of the variance of pancreas lipid content was explained by gender and VAT. In conclusion, obese men show higher VAT and ectopic fat deposition in liver and pancreas than obese women despite same BMI. Independent of overall adiposity, insulin resistance, adiponectin and fat intake, VAT, measured with MRI, is the main predictor of ectopic fat deposition in both liver and pancreas.     

The role of body fat in female attractiveness

The purpose of the present study was to investigate the role of body fat percentage (BF%) on female attractiveness. To this end, a series of female body images were selected from a collection of dual-energy X-ray absorptiometry scans. Images were stratified by three levels (low, mid, and high) of waist-to-hip ratio (WHR) and seven levels (15%–50%) of BF%. These 21 images were presented in a random order and rated for attractiveness. Results indicate that WHR, BMI, and BF% are all significant predictors of female attractiveness when regressed separately (R²= 0.19, 0.70, and 0.76, respectively). When regressed simultaneously, all three variables accounted for 87% of the variance in image attractiveness, with only BF% and WHR being significant predictors. Further analysis revealed that body fat might disrupt the negative linear relationship between WHR and attractiveness. Men and women differed significantly in most categories of WHR and BF%, with men generally rating images as less attractive than women. These data indicate that BF% appears to be a strong cue for attractiveness and that the impact of WHR and BMI on attractiveness is dependent, in part, on BF%. The appearance of body fat may provide disruption in the visual cues of both shape and size of the female body, potentially impacting behavior.     

Determinants of insulin-resistant phenotypes in normal-weight and obese Black African women

Objective: Subsets of metabolically “healthy obese” and “at‐risk” normal‐weight individuals have been previously identified. The aim of this study was to explore the determinants of these phenotypes in black South African (SA) women. Methods and Procedures: From a total of 103 normal‐weight (BMI ≤ 25 kg/m²) and 122 obese (BMI ≥ 30 kg/m²) black SA women, body composition, fat distribution, blood pressure, fasting glucose levels, insulin resistance, and lipid profiles were measured. Questionnaires relating to family history, physical activity energy expenditure (PAEE), and socio‐demographic variables were administered. The subjects were classified as insulin sensitive or insulin resistant according to the homeostasis model assessment of insulin resistance (HOMA‐IR) (≥1.95 insulin resistant). Results: Our study showed that 22% of the normal‐weight women were insulin resistant and 38% of the obese women were insulin sensitive. Increased visceral adipose tissue (VAT) (P = 0.001) and decreased VAT/leg fat mass (P ≤ 0.001), independent of total body fatness, distinguished between the phenotypes. Moreover, the insulin‐sensitive women were of higher socioeconomic status, did more leisure and vigorous PAEE and were less likely to use injectable contraceptives. Using a regression model, body fat distribution, percent body fat, age, log leisure PAEE, and use of injected contraception accounted for 35% of the variance in HOMA‐IR in the normal‐weight women. In the obese women, 34% of the variance in HOMA‐IR was explained by the same variables, excluding PAEE. No differences in smoking status or family history of metabolic disease were found between the phenotypes. Discussion: Central fat distribution, total adiposity, socioeconomic status, leisure PAEE, and use of injectable contraceptives distinguished between insulin‐sensitive and insulin‐resistant black SA women.     

Validity of optical device lipometer and bioelectric impedance analysis for body fat assessment in men and women

The aims of this study were to validate different subcutaneous adipose tissue layers (SAT-layers) measured by lipometer for body fat percentage (BF%) assessment with dual-energy X-ray absorptiometry (DXA) and to compare the validity of lipometer and bioelectrical impedance analysis (BIA). The subjects were 21 male (18-60 years) and 19 female (23-54 years) healthy Estonian volunteers. SAT-layers were measured by lipometer using 15 standardized SAT-layers. Sum of arms, legs and trunk SAT-layers were calculated and compared with arms, legs and trunk fat percentage measured by DXA. BF% was calculated by BIA using the equations of Lukaski et al. and Chumlea et al. for both genders and the equations of Segal et al. for males and Van Loan and Mayclin for females. BF% measured by DXA was significantly higher than calculated by Lukaski et al. and Chumlea et al. in both genders. The correlation was highest between the BF% measured by DXA and using Segal et al. equation in males (r = 0.94) and Van Loan and Mayclin equation in females (r = 0.84). High relationship was observed between BF% measured by DXA and sum of 15 SAT-layers (r = 0.88 in males and r = 0.91 in females). Stepwise multiple regression analysis indicated that two selected SAT-layers explained 85.9% and 86.7% (R2 x 100) of the total variance in BF% measured by DXA in males and females, respectively: [BF% = 1.308 neck + 0.638 hip + 6.971 (males; SEE = 2.59) and BF% = 1.152 hip + 1.797 calf + 12.347 (females; SEE = 3.46)]. In conclusion, lipometer and BIA give a similar mean estimation of BF% when compared with DXA. However, there is a wide range of variance for the upper and lower limits of agreement between the methods, and the methods are not interchangeable. Lipometer seems to be superior to BIA.     

Quantitative trait loci associated with body weight and abdominal fat traits on chicken chromosomes 3, 5 and 7

Body weight and abdominal fat traits in meat-type chickens are complex and economically important factors. Our objective was to identify quantitative trait loci (QTL) responsible for body weight and abdominal fat traits in broiler chickens. The Northeast Agricultural University Resource Population (NEAURP) is a cross between broiler sires and Baier layer dams. We measured body weight and abdominal fat traits in the F(2) population. A total of 362 F(2) individuals derived from four F(1) families and their parents and F(0) birds were genotyped using 29 fluorescent microsatellite markers located on chromosomes 3, 5 and 7. Linkage maps for the three chromosomes were constructed and interval mapping was performed to identify putative QTLs. Nine QTL for body weight were identified at the 5% genome-wide level, while 15 QTL were identified at the 5% chromosome-wide level. Phenotypic variance explained by these QTL varied from 2.95 to 6.03%. In particular, a QTL region spanning 31 cM, associated with body weight at 1 to 12 weeks of age and carcass weight at 12 weeks of age, was first identified on chromosome 5. Three QTLs for the abdominal fat traits were identified at the 5% chromosome-wide level. These QTLs explained 3.42 to 3.59% of the phenotypic variance. This information will help direct prospective fine mapping studies and can facilitate the identification of underlying genes and causal mutations for body weight and abdominal fat traits.     

Toward an early marker of metabolic dysfunction: omentin-1 in prepubertal children

Omentin-1 is a recently recognized adipokine primarily originating in visceral adipose tissue. We posited that circulating omentin-1 could be an early marker of metabolic dysfunction. To this end, we examined the associations between circulating omentin-1, body fat (bioelectric impedance), an endocrine-metabolic profile (homeostasis model assessment for insulin resistance (HOMA(IR)), serum lipids, high-molecular-weight (HMW) adiponectin and blood pressure (BP)) and family history of obesity and diabetes in asymptomatic prepubertal children (n = 161; 77 boys and 84 girls; age 7 ± 1 year) with a normal distribution of height and weight. Increased circulating omentin-1 was associated with a poorer metabolic profile, with relatively higher HOMA(IR), fasting triacylglycerol, BP and familial prevalence of diabetes (all P < 0.005 to P < 0.0001), and relatively lower fraction of HMW adiponectin (P < 0.005), whereas no relationship was found with body weight or fat or with family history of obesity. All these associations were independent of age, gender and fat mass. In conclusion, circulating omentin-1 may become a marker of metabolic dysfunction integrating insulin sensitivity, markers of adipose-tissue metabolism and BP as early as in prepubertal childhood.     

Adiponectin is inversely associated with intramyocellular and intrahepatic lipids in obese premenopausal women

Adiponectin, an adipokine secreted by adipocytes, exerts beneficial effects on glucose and lipid metabolism and has been found to improve insulin resistance by decreasing triglyceride content in muscle and liver in obese mice. Adiponectin is found in several isoforms and the high-molecular weight (HMW) form has been linked most strongly to the insulin-sensitizing effects. Fat content in skeletal muscle (intramyocellular lipids, IMCL) and liver (intrahepatic lipids, IHL) can be quantified noninvasively using proton magnetic resonance spectroscopy ((1)H-MRS). The purpose of our study was to assess the relationship between HMW adiponectin and measures of glucose homeostasis, IMCL and IHL, and to determine predictors of adiponectin levels. We studied 66 premenopausal women (mean BMI 31.0 ± 6.6 kg/m(2)) who underwent (1)H-MRS of calf muscles and liver for IMCL and IHL, computed tomography (CT) of the abdomen for abdominal fat depots, dual-energy X-ray absorptiometry (DXA) for fat and lean mass assessments, HMW and total adiponectin, fasting lipid profile and an oral glucose tolerance test (homeostasis model assessment of insulin resistance (HOMA(IR)), glucose and insulin area under the curve). There were strong inverse associations between HMW adiponectin and measures of insulin resistance, IMCL and IHL, independent of visceral adipose tissue (VAT) and total body fat. IHL was the strongest predictor of adiponectin and adiponectin was a predictor of HOMA(IR). Our study showed that in premenopausal obese women HMW adiponectin is inversely associated with IMCL and IHL content. This suggests that adiponectin exerts positive effects on insulin sensitivity in obesity by decreasing intracellular triglyceride content in skeletal muscle and liver; it is also possible that our results reflect effects of insulin on adiponectin.     

Systemic blockade of TNF-α does not improve insulin resistance in humans

The purpose of this study was to determine whether long-term modulation of inflammatory activity by tumor necrosis factor (TNF)-α inhibitors has some influence on insulin resistance (IR). 16 active rheumatoid arthritis (RA) patients without CV risk factors treated with anti-TNF-α agents were included in this study. RA activity by disease activity score 28, IR by HOMA2-IR, body composition by impedance analysis, physical activity by accelerometry, abdominal fat distribution by magnetic resonance imaging, and serum level of key adipokines by ELISA were measured at baseline and during a 1-year follow-up period. Patient body mass index increased significantly (26.94 ± 3.88 vs. 28.06 ± 4.57 kg/m2, p=0.02) after 1 year of treatment. Body composition, in terms of fat and fat-free mass, remained unchanged except for a significant elevation in body cell mass (25.50 ± 4.60 vs. 26.60 ± 3.17 kg, p=0.02). Basal levels of IR in the RA patients included in this study were significantly higher than healthy controls (1.6 ± 0.8 vs. 1.11 ± 0.56, p=0.011) but did not change during the follow-up. Nor did basal concentrations of adiponectin, visfatin, leptin, ghrelin, resistin, and apelin in response to anti-TNF-α treatment; only retinol-binding protein 4, showed a significant increase (51.7 ± 32.7 vs. 64.9 ± 28.4 μg/ml, p=0.03) at the end of the study. IR, adiposity distribution, and serum levels of most adipokines are not significantly affected by long-term inhibition of TNF-α in RA patients. Our data suggest that although systemic blockade of TNF-α exerts an anticachectic effect in RA patients, it does not seem to play a major role in IR.