A cross‐sectional study of osteocalcin and body fat measures among obese adolescents

Osteocalcin (OCN), a marker of osteoblast activity, has been implicated in the regulation of energy metabolism by the skeleton and thus may affect body fat measures.

Objective:

To examine the relationships of OCN to body fat measures and whether they vary according to markers of energy and vitamin D metabolism.

Design and Methods:

Data were obtained from 58 obese adolescents aged 13‐17.9 years (38 females, 8 black or African‐American). Total fat mass (FM) [dual X‐ray absorptiometry (DXA)] and visceral adipose tissue (VAT) [computerized axial tomography (CT)] were calculated. Blood tests included leptin, OCN, 25‐hydroxyvitamin D [25(OH)D], parathyroid hormone (PTH), thyroid function tests, and triglycerides. Markers of glucose metabolism were obtained from fasting and OGTT samples.

Results and Conclusions:

Adolescents with 25(OH)D <20 ng mL^?1 were considered deficient (n = 17/58); none had high PTH (PTH ≥ 65 pg mL^?1). OCN was associated with lower VAT (?84.27 ± 33.89 mm²) and BMI (?0.10 ± 0.05 kg m^?2), not FM (P = 0.597) in a core model including age, sex, race, geographic latitude, summer, height z‐score, and tanner stage. Adding 25(OH)D deficiency and PTH attenuated the inverse association of OCN to VAT. There was a significant interaction of OCN and 25(OH)D deficiency on FM (0.37 ± 0.18 kg, P = 0.041) and BMI (0.28 ± 0.10 kg m^?2, P = 0.007) in this adjusted model, which was further explained by leptin. Adding A1C to the core model modified the relationship of OCN to VAT (?93.08 ± 35.05 mm², P = 0.011), which was further explained by HOMA‐IR. In summary, these findings provide initial evidence for a relationship between OCN and body fat measures that is dependent on energy metabolism and vitamin D status among obese adolescents.

     

Measurements of total and regional body composition in preschool children: A comparison of MRI,DXA, and anthropometric data

Objective:

There are clear sex differences in the distribution of visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) in adults, with males having more VAT and less SAT than females. This study assessed whether these differences between the sexes were already present in preschool children. It also evaluated which measures of body composition were most appropriate for assessing abdominal obesity in this age group.

Design and Methods:

One‐hundred and five children (57 boys and 48 girls) participated in the study. Body composition was measured using dual‐energy X‐ray absorptiometry (DXA). Weight, height, and waist circumference (WC) were also recorded. Magnetic resonance imaging (MRI) of the entire abdomen using sixteen 10‐mm‐thick T₁‐weighted slices was performed in a subgroup of 48 children (30 boys and 18 girls); SAT and VAT volumes were measured using semiautomated segmentation.

Results:

Boys had significantly more VAT than girls (0.17 versus 0.10 l, P < 0.001). Results showed that VAT correlated significantly with all measurements of anthropometry (P < 0.01) after adjusting for SAT and for total fat mass measured with DXA. The mean limits of agreement between DXA and MRI regarding truncal FM were calculated to be ?11.4 (range ?17.8 to ?3.6), using a Bland–Altman plot.

Conclusion:

Sex differences in adipose tissue distribution are apparent at an early age. MRI is the best method with which to study abdominal fat distribution in young children.

     

Adipose tissue‐specific modulation of galectin expression in lean and obese mice: Evidence for regulatory function

Objective:

Galectins (Gal) exert many activities, including regulation of inflammation and adipogenesis. We evaluated modulation of Gal‐1, ‐3, ‐9 and ‐12 in visceral (VAT) and subcutaneous (SAT) adipose tissue in mice.

Design and Methods:

We used two mouse models of obesity, high‐fat diet induced obesity (DIO) and ob/ob mice. We also evaluated the response of Gal‐1 KO mice to DIO.

Results:

Both age and diet modulated expression of galectins, with DIO mice having higher serum Gal‐1 and Gal‐3 versus lean mice after 13‐17 weeks of high‐fat diet. In DIO mice there was a progressive increase in expression of Gal‐1 and Gal‐9 in SAT, whereas Gal‐3 increased in both VAT and SAT. Expression of Gal‐12 declined over time in VAT of DIO mice, similar to adiponectin. Obesity lead to increased production of Gal‐1 in adipocytes, whereas the increased Gal‐3 and Gal‐9 of obesity mostly derived from the stromovascular fraction. Expression of Gal‐12 was restricted to adipocytes. There was increased production of Gal‐3 and Gal‐9, but not Gal‐1, in CD11c^? and CD11c⁺ macrophages from VAT of DIO versus lean mice. Expression of Gal‐1, ‐3 and ‐12 in VAT and SAT of ob/ob mice followed a trend comparable to DIO mice. Rosiglitazone reduced serum Gal‐1, but not Gal‐3 and modulated expression of Gal‐3 in VAT and Gal‐9 and Gal‐12 in SAT of DIO mice. High‐fat feeding lead to increased adiposity in Gal‐1 KO versus WT mice, with loss of correlation between leptin and adiposity and no alterations in glucose and insulin levels.

Conclusions:

Obesity leads to differential modulation of Gal‐1, 3, 9 and 12 in VAT and SAT, with Gal‐1 acting as a modulator of adiposity.

     

Moderate‐To‐vigorous physical activity is associated with decreases in body mass index from ages 9 to 15 years

Objective:

The purpose of this study is to determine whether time spent in objectively measured physical activity is associated with change in body mass index (BMI) from ages 9 to 15.

Design and Methods:

The participants were enrolled in the National Institute of Child Health and Human Development Study of Early Child Care and Youth Development (n = 938). At ages 9, 11, 12, and 15 the time spent in moderate‐to‐vigorous physical activity (MVPA) was objectively measured, and BMI was calculated (kg/m²). Longitudinal quantile regression was used to analyze the data. The 10th, 25th, 50th, 75th, and 90th BMI percentiles were modeled as the dependent variables with age and MVPA (h/day) modeled as predictors. Adjustment was also made for gender, race, sleep, healthy eating score, maternal education, and sedentary behavior.

Results:

A negative association between MVPA and change in BMI was observed at the 90th BMI percentile (?3.57, 95% CI ?5.15 to ?1.99 kg/m² per hour of MVPA). The negative association between time spent in MVPA and change in BMI was progressively weaker toward the 10th BMI percentile (?0.27, 95% CI ?0.62 to 0.07 kg/m² per hour of MVPA). The associations remained similar after adjusting for the covariates, and when the analyses were stratified by gender.

Conclusion:

Time spent in MVPA was negatively associated with change in BMI from age 9 to 15. The association was strongest at the upper tail of the BMI distribution, and increasing time spent in MVPA could help reduce the prevalence of childhood obesity.

     

High‐normal tsh values in obesity: Is it insulin resistance or adipose tissue's guilt?

Objective:

Clinical evidences reported subclinical alterations of thyroid function in obesity, although the relationship between thyroid status and obesity remains unclear. We cross‐sectionally investigated the influence of metabolic features on hypothalamic–pituitary–thyroid axis in obesity.

Design and Methods:

We enrolled 60 euthyroid subjects with no history of type 2 diabetes mellitus and assessed the relationship of thyroid function with insulin resistance, measured using euglycemic clamp, and abdominal fat volume, quantified by computed tomography scan (CT scan). Thyroid stimulating hormone (TSH) correlated with BMI (r = 0.46; P = 0.02), both visceral (r = 0.58; P = 0.02) and subcutaneous adipose tissue volumes (r = 0.43; P = 0.03) and insulin resistance (inverse relationship with insulin sensitivity–glucose uptake: r = ?0.40; P = 0.04).

Results:

After performing multivariate regression, visceral adipose tissue volume was found to be the most powerful predictor of TSH (β = 3.05; P = 0.01), whereas glucose uptake, high‐density lipoprotein (HDL) cholesterol, low‐density lipoprotein (LDL) cholesterol, subcutaneous adipose tissue volume, and triglycerides were not. To further confirm the hypothesis that high‐normal TSH values could be dependent on adipose tissue, and not on insulin resistance, we restricted our analyses to moderately obese subjects' BMI ranging 30‐35 kg/m². This subgroup was then divided as insulin resistant and insulin sensitive according to the glucose uptake (≤ or >5 mg·kg^?1·min^?1, respectively). We did not find any statistical difference in TSH (insulin resistant: 1.62 ± 0.65 µU/ml vs. insulin sensitive: 1.46 ± 0.48; P = not significant) and BMI (insulin resistant: 32.2 ± 1.6 kg/m² vs. insulin sensitive: 32.4 ± 1.4; P = not significant), thus confirming absence of correlation between thyroid function and insulin sensitivity per se.

Conclusion:

Our study suggests that the increase in visceral adipose tissue is the best predictor of TSH concentration in obesity, independently from the eventual concurrent presence of insulin resistance.

     

Prediction of measured weight from self‐reported weight was not improved after stratification by body mass index

Objective:

Self‐reported weight may underestimate measured weight. Researchers have tried to reduce the error using statistical models to predict weight from self‐reported weight. We investigate whether deriving equations within separate BMI categories improves the prediction of weight compared with an equation derived regardless of an individual's BMI.

Design and Methods:

The analysis included self‐reported and measured data from 20,536 individuals participating in the EPIC‐Norfolk study. In a derivation set (n = 15,381) two approaches were used to predict weight from self‐reported weight: (1) using a linear regression model with measured weight as outcome and self‐reported weight and age as predictors, and (2) using the same model fit separately within 3 strata defined by BMI (< 25, 25‐30, ≥30 kg m^?2). The performance of these approaches was assessed in a validation set (n = 5,155). Measured weight was compared to self‐reported weight and predicted weight.

Results:

Self‐reported weight underestimated measured weight (P < 0.0001): mean difference ?1.2 ± 3.1 kg (men), ?1.3 ± 2.5 kg (women). Underestimation was greater in obese participants (P < 0.0001). Predicted weight using approach 1 was not significantly different from measured weight (P < 0.05). However, in individuals with BMI < 25 kg m^?2, weight was overestimated in men (0.90 ± 3.87 kg) and women (0.57 ± 2.06 kg), but underestimated in overweight (?0.29 ± 3.58, ?0.20 ± 2.62 kg) and obese (?1.46 ± 5.05 kg, ?0.73 ± 3.54 kg) men and women.

Conclusions:

Using separate prediction equations in strata of BMI did not further improve prediction of weight. In conclusion, predicted weight was closer to measured weight compared with self‐reported weight, but using equations derived in strata of BMI did not further improve the prediction and are not recommended for prediction of weight.

     

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.

     

Greater screen time is associated with adolescent obesity: A longitudinal study of the BMI distribution from Ages 14 to 18

Objective:

Previous research has examined the association between screen time and average changes in adolescent body mass index (BMI). Until now, no study has evaluated the longitudinal relationship between screen time and changes in the BMI distribution across mid to late adolescence.

Design and Methods:

Participants (n = 1,336) were adolescents who were followed from age 14 to age 18 and surveyed every 6 months. Time spent watching television/videos and playing video games was self‐reported (<1 h day^?1, 1 h day^?1, 2 h day^?1, 3 h day^?1, 4 h day^?1, or 5+ h day^?1). BMI (kg m^?2) was calculated from self‐reported height and weight. Longitudinal quantile regression was used to model the 10th, 25th, 50th, 75th, and 90th BMI percentiles as dependent variables. Study wave and screen time were the main predictors, and adjustment was made for gender, race, maternal education, hours of sleep, and physical activity.

Results:

Increases at all the BMI percentiles over time were observed, with the greatest increase observed at the 90th BMI percentile. Screen time was positively associated with changes in BMI at the 50th (0.17, 95% CI: 0.06, 0.27), 75th (0.31, 95% CI: 0.10, 0.52), and 90th BMI percentiles (0.56, 95% CI: 0.27, 0.82). No associations were observed between screen time and changes at the 10th and 25th BMI percentiles.

Conclusions:

Positive associations between screen time and changes in the BMI at the upper tail of the BMI distribution were observed. Therefore, lowering screen time, especially among overweight and obese adolescents, could contribute to reducing the prevalence of adolescent obesity.

     

Sleep apnea modifies the long‐term impact of surgically induced weight loss on cardiac function and inflammation

Objective:

Obesity is frequently associated with obstructive sleep apnea (OSA). Both conditions are proinflammatory and proposed to deteriorate cardiac function. We used a nested cohort study design to evaluate the long‐term impact of bariatric surgery on OSA and how weight loss and OSA relate to inflammation and cardiac performance.

Design and Methods:

At 10‐year follow‐up in the Swedish Obese Subjects (SOS) study, we identified 19 obese subjects (BMI 31.2 ± 5.3 kg m^?2), who following bariatric surgery at SOS‐baseline had displayed sustained weight losses (surgery group), and 20 obese controls (BMI 42.0 ± 6.2 kg m^?2), who during the same time‐period had maintained stable weight (control group). All study participants underwent overnight polysomnography examination, echocardiography and analysis of inflammatory markers.

Results:

The surgery group displayed a lower apnea hypopnea index (AHI) (19.9 ± 21.5 vs. 37.8 ± 27.7 n/h, P = 0.013), lower inflammatory activity (hsCRP 2.3 ± 3.0 vs. 7.2 ± 5.0 mg L^?1, P < 0.001), reduced left ventricular mass (165 ± 22 vs. 207 ± 22 g, P < 0.001) and superior left ventricular diastolic function (E/A ratio 1.24 ± 1.10 vs. 1.05 ± 0.20, P = 0.006) as compared with weight stable obese controls. In multiple regression analyses including all subjects (n = 39) and controlling for BMI, the AHI remained independently associated with hsCRP (β = 0.09, P < 0.001), TNF‐α (β = 0.03, P = 0.031), IL‐6 (β = 0.01, P = 0.007), IL 10 (β = ?0.06; P = 0.018), left ventricular mass (β = 0.64, P < 0.001), left atrial area (β = 0.08, P = 0.002), pulmonary artery pressure (β = 0.08, P = 0.011) and E/E_a ratio (β = 0.04, P = 0.021).

Conclusions:

Patients with sustained weight loss after bariatric surgery display less severe sleep apnea, reduced inflammatory activity, and enhanced cardiac function. Persisting sleep apnea appears to limit the beneficial effect of weight loss on inflammation and cardiac performance.

     

Sympathetic support of energy expenditure and sympathetic nervous system activity after gastric bypass surgery

Objective:

This study was designed to determine how gastric bypass affects the sympathetically‐mediated component of resting energy expenditure (REE) and muscle sympathetic nerve activity (MSNA).

Design and Methods:

We measured REE before and after beta‐blockade in seventeen female subjects approximately three years post‐gastric bypass surgery and in nineteen female obese individuals for comparison. We also measured MSNA in a subset of these subjects.

Results:

The gastric bypass subjects had no change in REE after systemic beta‐blockade, reflecting a lack of sympathetic support of REE, in contrast to obese subjects where REE was reduced by beta‐blockade by approximately 5% (P < 0.05). The gastric bypass subjects, while still overweight (BMI = 29.3 vs 38.0 kg·m^?2 for obese subjects, P < 0.05), also had significantly lower MSNA compared to obese subjects (10.9 ± 2.3 vs. 21.9 ± 4.1 bursts·min^?1, P < 0.05). The reasons for low MSNA and a lack of sympathetically mediated support of REE after gastric bypass are likely multifactorial and may be related to changes in insulin sensitivity, body composition, and leptin, among other factors.

Conclusions:

These findings may have important consequences for the maintenance of weight loss after gastric bypass. Longitudinal studies are needed to further explore the changes in sympathetic support of REE and if changes in MSNA or tissue responsiveness are related to the sympathetic support of REE.

     

Anthropometric markers of obesity and mortality in white and African American adults: The pennington center longitudinal study

Objective:

The purpose of this study was to determine the association between anthropometric measures of obesity and all‐cause mortality in white and African American men and women.

Design and Methods:

The sample included 14,343 adults 18‐89 years of age. Height, weight, and waist and hip circumferences were measured, and the BMI (kg m^?2), body adiposity index (BAI = ([hip circumference in centimeters]/[height in meters])^1.5 – 18), waist‐to‐height ratio (WHtR) and waist‐to‐hip ratio (WHR) were computed. Vital status of the participants was determined from linkage with the National Death Index through 2009. Cox regression was used to assess the association between anthropometry and all‐cause mortality, adjusting for age, sex, year of baseline examination, study code, smoking status, alcohol consumption and physical activity. Hazard ratios (HR) are expressed per standard deviation of each variable.

Results:

A total of 438 deaths occurred during 120,637 person‐years of follow‐up. All anthropometric markers demonstrated significant associations with all‐cause mortality in white subjects. In multivariable‐adjusted models, BMI (HR 1.34; 95% CI: 1.19‐1.50), waist circumference (1.41; 1.25‐1.60), BAI (1.34; 1.17‐1.53), WHtR (1.46; 1.28‐1.65), and WHR (1.40; 1.23‐1.61) all demonstrated significant relationships with mortality in white participants, but not in African Americans. In categorical analyses, there was a significant association between BMI status and mortality in whites but not African Americans. However, the risk associated with elevated waist circumference was similar in whites (1.49; 1.15‐1.94) and African Americans (1.60; 1.06‐2.40).

Conclusion:

In summary, this study has demonstrated race differences in the association between anthropometry and all‐cause mortality.

     

Racial/ethnic differences in the prevalence of gestational diabetes mellitus and maternal overweight and obesity,by Nativity,Florida, 2004‐2007

Objective:

We examined the risk of gestational diabetes mellitus (GDM) among foreign‐born and U.S.‐born mothers by race/ethnicity and BMI category.

Design and Method:

We used 2004‐2007 linked birth certificate and maternal hospital discharge data of live, singleton deliveries in Florida to compare GDM risk among foreign‐born and U.S.‐born mothers by race/ethnicity and BMI category. We examined maternal BMI and controlled for maternal age, parity, and height.

Results:

Overall, 22.4% of the women in our study were foreign born. The relative risk (RR) of GDM among women who were overweight or obese (BMI ≥ 25.0 kg m^?2) was higher than among women with normal BMI (18.5‐24.9 kg m^?2) regardless of nativity, ranging from 1.3 (95% confidence interval (CI) = 1.0, 1.9) to 3.8 (95% CI = 2.1, 7.2).Foreign‐born women also had a higher GDM risk than U.S.‐born women, with RR ranging from 1.1 (95% CI = 1.1, 1.2) to 2.1 (95% CI = 1.4, 3.1). This finding was independent of BMI, age, parity, and height for all racial/ethnicity groups.

Conclusions:

Although we found differences in age, parity, and height by nativity, these differences did not substantially reduce the increased risk of GDM among foreign‐born mothers. Health practitioners should be aware of and have a better understanding of how race/ethnicity and nativity can affect women with a high risk of GDM. Although BMI is a major risk factor for GDM, it does not appear to be associated with race/ethnicity or nativity.

     

The species–area relationship does not have an asymptote!

Aim

To attack a widespread myth.

Location

World‐wide.

Methods

Simple mathematical logical and empirical examples.

Results

As both species and area are finite and non‐negative, the species–area relationship is limited at both ends. The log species–log area relationship is normally effectively linear on scales from about 1 ha to 10⁷ km². There are no asymptotes. At the intercontinental scale it may get steeper; at small scales it may in different cases get steeper or shallower or maintain its slope.

Main conclusion

The species–area relationship does not have an asymptote.

     

Influence of calendar period on the association between BMI and coronary heart disease: A meta‐analysis of 31 cohorts

Objective:

The association between obesity and coronary heart disease (CHD) may have changed over time, for example due to improved pharmacological treatment of CHD risk factors. This meta‐analysis of 31 prospective cohort studies explores the influence of calendar period on CHD risk associated with body mass index (BMI).

Design and Methods:

The relative risks (RRs) of CHD for a five‐BMI‐unit increment and BMI categories were pooled by means of random effects models. Meta‐regression analysis was used to examine the influence of calendar period (>1985 v ≤1985) in univariate and multivariate analyses (including mean population age as a covariate).

Results:

The age, sex, and smoking adjusted RR (95% confidence intervals) of CHD for a five‐BMI‐unit increment was 1.28(1.22:1.34). For underweight, overweight and obesity, the RRs (compared to normal weight) were 1.11(0.91:1.36), 1.31(1.22:1.41), and 1.78(1.55:2.04), respectively. The univariate analysis indicated 31% (95%CI: ?56:0) lower RR of CHD associated with a five‐BMI‐unit increment and a 51% (95%CI: ?78: ?14)) lower RR associated with obesity in studies starting after 1985 (n = 15 and 10, respectively) compared to studies starting in or before 1985 (n = 16 and 10). However, in the multivariate analysis, only mean population age was independently associated with the RRs for a five‐BMI‐unit increment and obesity (?29(95%CI: ?55: ?5)) and ?31(95%CI: ?66:3), respectively) per 10‐year increment in mean age).

Conclusion:

This study provides no consistent evidence for a difference in the association between BMI and CHD by calendar period. The mean population age seems to be the most important factor that modifies the association between the risk of CHD and BMI, in which the RR decreases with increasing age.

     

Nonalcoholic fatty liver disease in severely obese adolescent and adult patients

Objectives:

Nonalcoholic fatty liver disease (NAFLD) is increasingly an indication for liver transplantation in adults. While severe obesity (SO, BMI ≥40 kg m^?2) in adults is long standing, it is recent in duration in adolescents. With adolescent obesity on the rise, NAFLD is becoming the most frequent liver disease in adolescents. The hypothesis that SO adolescents and adults have different severity of NAFLD because of longer duration of obesity in SO adults was tested.

Design and Methods:

Preoperative clinical data, NAFLD activity and NASH (Nonalcoholic steatohepatitis) scores from intraoperative liver biopsies were extracted from a prospective database of consecutively operated SO adolescents and adults (n = 24 each). Fasting preoperative serum inflammatory mediators were evaluated by ELISA.

Results:

Other than age, baseline BMI, ethnicity and gender distribution, the incidence and extent of dyslipidemia, hypertension, and metabolic syndrome were comparable between groups. Histologic scores for steatosis and inflammation were similar. Adolescents have significantly higher NASH incidence, hepatocyte injury scores and fibrosis. This was associated with higher serum C‐reactive protein and sCD14 levels.

Conclusion:

For comparable BMI and metabolic profile, SO adolescents have more advanced liver damage, more severe systemic inflammation, suggesting differences in NAFLD etiologies and more aggressive disease progression in the young obese population.

     

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.

     

Cortisol,obesity, and the metabolic syndrome: A cross‐sectional study of obese subjects and review of the literature

Objective:

Circulating cortisol and psychosocial stress may contribute to the pathogenesis of obesity and metabolic syndrome (MS). To evaluate these relationships, a cross‐sectional study of 369 overweight and obese subjects and 60 healthy volunteers was performed and reviewed the previous literature.

Design and Methods:

Overweight and obese subjects had at least two other features of Cushing's syndrome. They underwent measurements representing cortisol dynamics (24 h urine cortisol excretion (UFC), bedtime salivary cortisol, 1 mg dexamethasone suppression test) and metabolic parameters (BMI, blood pressure (BP); fasting serum triglycerides, HDL, insulin, and glucose). Subjects also completed the Perceived Stress Scale (PSS). UFC, salivary cortisol, and weight from 60 healthy volunteers were analyzed.

Results:

No subject had Cushing's syndrome. UFC and dexamethasone responses were not associated with BMI or weight. However, salivary cortisol showed a trend to increase as BMI increased (P < 0.0001), and correlated with waist circumference (WC) in men (r_s = 0.28, P = 0.02) and systolic BP in women (r_s = 0.24, P = 0.0008). Post‐dexamethasone cortisol levels were weak to moderately correlated with fasting insulin (r_s = ?0.31, P = 0.01) and HOMA‐IR (r_s = ?0.31, P = 0.01) in men and systolic (r_s = 0.18, P = 0.02) and diastolic BP (r_s = 0.20, P = 0.009) in women. PSS results were higher in obese subjects than controls, but were not associated with cortisol or metabolic parameters. As expected, WC correlated with fasting insulin, HOMA‐IR, and systolic BP (adjusted for BMI and gender; P < 0.01). Literature showed inconsistent relationships between cortisol and metabolic parameters.

Conclusion:

Taken together, these data do not support a strong relationship between systemic cortisol or stress and obesity or MS.

     

Central adiposity and other anthropometric factors in relation to risk of macrosomia in an african american population

Objective:

Previous studies have consistently identified maternal obesity and gestational weight gain (GWG) as risk factors for macrosomia, but little is known about the effects of central adiposity and body fat distribution. Using self‐reported data from the Black Women's Health Study (BWHS), a large follow‐up study of US black women, we examined the risk of macrosomia in relation to prepregnancy waist circumference, prepregnancy waist‐to‐hip ratio (WHR), prepregnancy BMI, and GWG.

Design and Methods:

During 1995–2003, BWHS participants ages 21–44 years delivered 6,687 full‐term singleton births (gestational age >37 weeks). We compared mothers of 691 infants weighing ≥4,000 g with mothers of 5,996 infants weighing <4,000 g. Generalized estimating equation models (GEE) that accounted for more than one birth per mother were used to estimate multivariable odds ratios (OR) and 95% confidence intervals (CI).

Results:

Independent of prepregnancy BMI, prepregnancy waist circumference was positively associated with risk of macrosomia (OR = 1.58, 95% CI: 1.07–2.32, for ≥35.0 vs. <27.0 inches (≥88.9 vs. <68.6 cm); P trend = 0.04). As expected, prepregnancy BMI was also positively associated with macrosomia (OR = 1.74, 95% CI: 1.25–2.41 for BMI ≥35.0 vs. 18.5–24.9 kg m^?2). GWG above the amount recommended by the 2009 Institute of Medicine report was associated with an increased risk of macrosomia and the association was present in each category of prepregnancy BMI (18.5–24.9, 25.0–29.9, and ≥30.0 kg m^?2; P trend <0.001).

Conclusions:

Our data suggest that overall obesity, high GWG, and high waist circumference are independent risk factors for macrosomia among US black women.

     

Circulating regulatory T cells are reduced in obesity and may identify subjects at increased metabolic and cardiovascular risk

Objective:

Reduced numbers of regulatory T (T_reg) cells have been observed in visceral adipose tissue of obese mice and humans. However, it is unknown whether human obesity affects circulating Treg cells and whether their number is associated with markers of systemic inflammation or glucose intolerance.

Design and Methods:

Peripheral blood mononuclear cells were isolated from venous blood of obese (BMI ≥ 27 kg/m²; n = 30) and nonobese (BMI ≥ 27 kg/m²; n = 13) individuals and analyzed using flow cytometry for the expression of CD4, CD25, and Foxp3.

Results:

Reduced circulating T_reg‐cell numbers were detected in obese compared with nonobese study participants (P = 0.038). Circulating CD4⁺CD25⁺CD127^?Foxp3 T_reg cells inversely correlated with body weight (P = 0.009), BMI (P = 0.004) and plasma leptin levels (P = 0.004) and were reduced in subjects with hsCRP ≥ 3.0 mg/L (P = 0.034) or HbA1c ≥ 5.5% (P < 0.005). Receiver operating characteristic curve analysis revealed a cutoff of circulating Treg cells < 1.06% to be predictive for hsCRP levels ≥ 3.0 mg/L, and logistic regression showed that the risk of having hsCRP levels ≥ 3.0 mg/L was increased 9.6‐fold (P = 0.008), if T_reg cells were below this threshold. The T_reg cutoff for HbA1c levels ≥ 5.5% was 0.73%, and this cutoff also predicted an increased risk of having elevated levels of both hsCRP and HbA1c, if only obese subjects were examined.

Conclusion:

Our findings thus reveal an association between circulating T_reg cells and measures of adiposity, inflammation, and glucose intolerance. Although further prospective studies are needed, we present data suggesting that the determination of T_reg cells might be useful to identify obese subjects at increased risk of developing cardiovascular and/or metabolic complications.