Takeaway food consumption and cardio-metabolic risk factors in young adults

Background/objectives: Takeaway food consumption is positively associated with adiposity. Little is known about the associations with other cardio-metabolic risk factors. This study aimed to determine whether takeaway food consumption is associated with fasting glucose, insulin, lipids, homeostasis model assessment (HOMA) and blood pressure.

Subjects/methods: A national sample of 1896, 26–36 year olds completed a questionnaire on socio-demographics, takeaway food consumption, physical activity and sedentary behaviour. Waist circumference and blood pressure were measured, and a fasting blood sample was taken. For this analysis, takeaway food consumption was dichotomised to once a week or less and twice a week or more. Linear regression was used to calculate differences in the adjusted mean values for fasting lipids, glucose, insulin, HOMA and blood pressure. Models were adjusted for age, employment status, leisure time physical activity and TV viewing.

Results: Compared with women who ate takeaway once a week or less, women who ate takeaway twice a week or more had significantly higher adjusted mean fasting glucose (4.82 vs 4.88 mmol/l, respectively; P=0.045), higher HOMA scores (1.27 vs 1.40, respectively, P=0.034) and tended to have a higher mean fasting insulin (5.95 vs 6.45 mU/l, respectively, P=0.054). Similar associations were observed for men for fasting insulin and HOMA score, but the differences were not statistically significant. For both women and men adjustment for waist circumference attenuated the associations.

Conclusion: Consuming takeaway food at least twice a week was associated with cardio-metabolic risk factors in women but less so in men. The effect of takeaway food consumption was attenuated when adjusted for obesity.

Growth curves for cardio-metabolic risk factors in children and adolescents

OBJECTIVE: This study developed percentile curves for anthropometric (waist circumference) and cardiovascular (lipid profile) risk factors for US children and adolescents. STUDY DESIGN: A representative sample of US children and adolescents from the National Health and Nutrition Examination Survey from 1988 to 1994 (NHANES III) and the current national series (NHANES 1999-2006) were combined. Percentile curves were constructed, nationally weighted, and smoothed using the Lambda, Mu, and Sigma method. The percentile curves included age- and sex-specific percentile values that correspond with and transition into the adult abnormal cut-off values for each of these anthropometric and cardiovascular components. To increase the sample size, a second series of percentile curves was also created from the combination of the 2 NHANES databases, along with cross-sectional data from the Bogalusa Heart Study, the Muscatine Study, the Fels Longitudinal Study and the Princeton Lipid Research Clinics Study. RESULTS: These analyses resulted in a series of growth curves for waist circumference, total cholesterol, LDL cholesterol, triglycerides, and HDL cholesterol from a combination of pediatric data sets. The cut-off for abnormal waist circumference in adult males (102 cm) was equivalent to the 94(th) percentile line in 18-year-olds, and the cut-off in adult females (88 cm) was equivalent to the 84(th) percentile line in 18-year-olds. Triglycerides were found to have a bimodal pattern among females, with an initial peak at age 11 and a second at age 20; the curve for males increased steadily with age. The HDL curve for females was relatively flat, but the male curve declined starting at age 9 years. Similar curves for total and LDL cholesterol were constructed for both males and females. When data from the additional child studies were added to the national data, there was little difference in their patterns or rates of change from year to year. CONCLUSIONS: These curves represent waist and lipid percentiles for US children and adolescents, with identification of values that transition to adult abnormalities. They could be used conditionally for both epidemiological and possibly clinical applications, although they need to be validated against longitudinal data.

Threshold values of sagittal abdominal diameter for the detection of cardio-metabolic risk factors in Northeastern Mexico: a cross-sectional study

Background: The use of sagittal abdominal diameter (SAD) has been proposed for screening cardio-metabolic risk factors; however, its accuracy can be influenced by the choice of thresholds values. Aim: To determine the SAD threshold values for cardio-metabolic risk factors in Mexican adults; to assess whether parallel and serial SAD testing can improve waist circumference (WC) sensitivity and specificity; and to analyze the effect of considering SAD along with WC and body mass index (BMI) in detecting cardio-metabolic risk. Methods: This cross-sectional study was conducted during 2012-2014 in Northeast Mexico (n = 269). Data on anthropometric, clinical, and biochemical measurements were collected. Sex-adjusted receiver-operating characteristic curves (ROC) were obtained using hypertension, dysglycemia, dyslipidemia and insulin resistance as individual outcomes and metabolic syndrome as a composite outcome. Age-adjusted odds ratios and 95% confidence intervals (CI) were estimated using logistic regression. Results: The threshold value for SAD with acceptable combination of sensitivity and specificity was 24.6 cm in men and 22.5 cm in women. Parallel SAD testing improved WC sensitivity and serial testing improved WC specificity. The co-occurrence of high WC/high SAD increased the risk for insulin resistance by 2.4-fold (95% CI: 1.1-5.3), high BMI/high SAD by 4.3-fold (95% CI: 1.7-11.9) and SAD alone by 2.2-fold (95% CI: 1.2.-4.2). Conclusions: The use of SAD together with traditional obesity indices such as WC and BMI has advantages over using either of these indices alone. SAD may be a powerful screening tool for interventions for high-risk individuals.

Dietary quality is associated with diabetes and cardio-metabolic risk factors1–3

In this study, our aim was to investigate the associations between diet quality and newly diagnosed diabetes, prediabetes, and cardio-metabolic risk factors. The analysis was based on 7441 participants of the Australian Diabetes, Obesity and Lifestyle study, a cross-sectional study of adults aged 25 y involving a 75-g oral glucose tolerance test. Diet quality was assessed via a dietary guideline index and FFQ data. Associations between diet quality and diabetes, prediabetes (impaired fasting glycemia, impaired glucose tolerance), and cardiovascular risk factors were investigated using linear and logistic regression adjusted for age, education, smoking, physical activity, sedentary behavior, and BMI. Higher diet quality was significantly associated with lower systolic and diastolic blood pressure among men, lower fasting plasma glucose among men and women, and lower systolic blood pressure, fasting plasma insulin, and 2-h plasma glucose and greater insulin sensitivity among women. Diet quality was inversely associated with abdominal obesity [odds ratio (OR) for top quartile: 0.68, 0.48–0.96], hypertension (OR: 0.50, 0.31–0.81), and type 2 diabetes (OR: 0.38, 0.18–0.80) among men. Lack of compliance with established dietary guidelines was associated with type 2 diabetes and cardio-metabolic risk factors. Further work is required to determine whether this dietary index has predictive validity for health in longitudinal studies.

A novel inflammatory biomarker, GlycA, associates with disease activity in rheumatoid arthritis and cardio-metabolic risk in BMI-matched controls

BACKGROUND: RA and CVD both have inflammation as part of the underlying biology. Our objective was to explore the relationships of GlycA, a measure of glycosylated acute phase proteins, with inflammation and cardiometabolic risk in RA, and explore whether these relationships were similar to those for persons without RA. METHODS: Plasma GlycA was determined for 50 individuals with mild-moderate RA disease activity and 39 controls matched for age, gender, and body mass index (BMI). Regression analyses were performed to assess relationships between GlycA and important markers of traditional inflammation and cardio-metabolic health: inflammatory cytokines, disease activity, measures of adiposity and insulin resistance. RESULTS: On average, RA activity was low (DAS-28 = 3.0 ± 1.4). Traditional inflammatory markers, ESR, hsCRP, IL-1β, IL-6, IL-18 and TNF-α were greater in RA versus controls (P < 0.05 for all). GlycA concentrations were significantly elevated in RA versus controls (P = 0.036). In RA, greater GlycA associated with disease activity (DAS-28; RDAS-28 = 0.5) and inflammation (RESR = 0.7, RhsCRP = 0.7, RIL-6 = 0.3: P < 0.05 for all); in BMI-matched controls, these inflammatory associations were absent or weaker (hsCRP), but GlycA was related to IL-18 (RhsCRP = 0.3, RIL-18 = 0.4: P < 0.05). In RA, greater GlycA associated with more total abdominal adiposity and less muscle density (Rabdominal-adiposity = 0.3, Rmuscle-density = -0.3, P < 0.05 for both). In BMI-matched controls, GlycA associated with more cardio-metabolic markers: BMI, waist circumference, adiposity measures and insulin resistance (R = 0.3-0.6, P < 0.05 for all). CONCLUSIONS: GlycA provides an integrated measure of inflammation with contributions from traditional inflammatory markers and cardio-metabolic sources, dominated by inflammatory markers in persons with RA and cardio-metabolic factors in those without.

Cardiorespiratory fitness is negatively associated with metabolic risk factors independently of the adherence to a healthy dietary pattern

Background and aim: Cardiorespiratory fitness (CRF) and diet have been involved as significant factors towards the prevention of cardio-metabolic diseases. This study aimed to assess the impact of the combined associations of CRF and adherence to the Southern European Atlantic Diet (SEADiet) on the clustering of metabolic risk factors in adolescents. Methods and Results: A cross-sectional school-based study was conducted on 468 adolescents aged 15-18, from the Azorean Islands, Portugal. We measured fasting glucose, insulin, total cholesterol (TC), HDL-cholesterol, triglycerides, systolic blood pressure, waits circumference and height. HOMA, TC/HDL-C ratio and waist-to-height ratio were calculated. For each of these variables, a Z-score was computed by age and sex. A metabolic risk score (MRS) was constructed by summing the Z scores of all individual risk factors. High risk was considered when the individual had 1SD of this score. CRF was measured with the 20 m-Shuttle-Run- Test. Adherence to SEADiet was assessed with a semi-quantitative food frequency questionnaire. Logistic regression showed that, after adjusting for potential confounders, unfit adolescents with low adherence to SEADiet had the highest odds of having MRS (OR Z 9.4; 95%CI:2.6e33.3) followed by the unfit ones with high adherence to the SEADiet (OR Z 6.6; 95% CI: 1.9e22.5) when compared to those who were fit and had higher adherence to SEADiet.

Is waist-to-height ratio a useful indicator of cardio-metabolic risk in 6-10-year-old children?

Background: Childhood obesity is a public health problem worldwide. Visceral obesity, particularly associated with cardio-metabolic risk, has been assessed by body mass index (BMI) and waist circumference, but both methods use sex-and age-specific percentile tables and are influenced by sexual maturity. Waist-to-height ratio (WHtR) is easier to obtain, does not involve tables and can be used to diagnose visceral obesity, even in normal-weight individuals. This study aims to compare the WHtR to the 2007 World Health Organization (WHO) reference for BMI in screening for the presence of cardio-metabolic and inflammatory risk factors in 6–10-year-old children. Methods: A cross-sectional study was undertaken with 175 subjects selected from the Reference Center for the Treatment of Children and Adolescents in Campos, Rio de Janeiro, Brazil. The subjects were classified according to the 2007 WHO standard as normal-weight (BMI z score > −1 and < 1) or overweight/obese (BMI z score ≥ 1). Systolic blood pressure (SBP), diastolic blood pressure (DBP), fasting glycemia, low-density lipoprotein (LDL), high-density lipoprotein (HDL), triglyceride (TG), Homeostatic Model Assessment – Insulin Resistance (HOMA-IR), leukocyte count and ultrasensitive C-reactive protein (CRP) were also analyzed. Results: There were significant correlations between WHtR and BMI z score (r = 0.88, p < 0.0001), SBP (r = 0.51, p < 0.0001), DBP (r = 0.49, p < 0.0001), LDL (r = 0.25, p < 0.0008, HDL (r = −0.28, p < 0.0002), TG (r = 0.26, p < 0.0006), HOMA-IR (r = 0.83, p < 0.0001) and CRP (r = 0.51, p < 0.0001). WHtR and BMI areas under the curve were similar for all the cardio-metabolic parameters. A WHtR cut-off value of > 0.47 was sensitive for screening insulin resistance and any one of the cardio-metabolic parameters. Conclusions: The WHtR was as sensitive as the 2007 WHO BMI in screening for metabolic risk factors in 6-10-year-old children. The public health message “keep your waist to less than half your height” can be effective in reducing cardio-metabolic risk because most of these risk factors are already present at a cut point of WHtR ≥ 0.5. However, as this is the first study to correlate the WHtR with inflammatory markers, we recommend further exploration of the use of WHtR in this age group and other population-based samples.

Increased cardio-metabolic risk is associated with increased TV viewing time

Purpose: Television viewing time, independent of leisure-time physical activity, has cross-sectional relationships with the metabolic syndrome and its individual components. We examined whether baseline and five-year changes in self-reported television viewing time are associated with changes in continuous biomarkers of cardio-metabolic risk (waist circumference, triglycerides, high density lipoprotein cholesterol, systolic and diastolic blood pressure, fasting plasma glucose; and a clustered cardio-metabolic risk score) in Australian adults. Methods: AusDiab is a prospective, population-based cohort study with biological, behavioral, and demographic measures collected in 1999–2000 and 2004–2005. Non-institutionalized adults aged ≥ 25 years were measured at baseline (11,247; 55% of those completing an initial household interview); 6,400 took part in the five-year follow-up biomedical examination, and 3,846 met the inclusion criteria for this analysis. Multiple linear regression analysis was used and unstandardized B coefficients (95% CI) are provided. Results: Baseline television viewing time (10 hours/week unit) was not significantly associated with change in any of the biomarkers of cardio-metabolic risk. Increases in television viewing time over five years (10 hours/week unit) were associated with increases in: waist circumference (cm) (men: 0.43 (0.08, 0.78), P = 0.02; women: 0.68 (0.30, 1.05), P <0.001), diastolic blood pressure (mmHg) (women: 0.47 (0.02, 0.92), P = 0.04), and the clustered cardio-metabolic risk score (women: 0.03 (0.01, 0.05), P = 0.007). These associations were independent of baseline television viewing time and baseline and change in physical activity and other potential confounders. Conclusion: These findings indicate that an increase in television viewing time is associated with adverse cardio-metabolic biomarker changes. Further prospective studies using objective measures of several sedentary behaviors are required to confirm causality of the associations found.

Body composition and its relationship to metabolic risk factors in Asian children

Obesity is a major public health problem in both developed and developing countries. The body mass index (BMI) is the most common index used to define obesity. The universal application of the same BMI classification across different ethnic groups is being challenged due to the inability of the index to differentiate fat mass (FM) and fat�]free mass (FFM) and the recognized ethnic differences in body composition. A better understanding of the body composition of Asian children from different backgrounds would help to better understand the obesity�]related health risks of people in this region. Moreover, the limitations of the BMI underscore the necessity to use where possible, more accurate measures of body fat assessment in research and clinical settings in addition to BMI, particularly in relation to the monitoring of prevention and treatment efforts. The aim of the first study was to determine the ethnic difference in the relationship between BMI and percent body fat (%BF) in pre�]pubertal Asian children from China, Lebanon, Malaysia, the Philippines, and Thailand. A total of 1039 children aged 8�]10 y were recruited using a non�]random purposive sampling approach aiming to encompass a wide BMI range from the five countries. Percent body fat (%BF) was determined using the deuterium dilution technique to quantify total body water (TBW) and subsequently derive proportions of FM and FFM. The study highlighted the sex and ethnic differences between BMI and %BF in Asian children from different countries. Girls had approximately 4.0% higher %BF compared with boys at a given BMI. Filipino boys tended to have a lower %BF than their Chinese, Lebanese, Malay and Thai counterparts at the same age and BMI level (corrected mean %BF was 25.7�}0.8%, 27.4�}0.4%, 27.1�}0.6%, 27.7�}0.5%, 28.1�}0.5% for Filipino, Chinese, Lebanese, Malay and Thai boys, respectively), although they differed significantly from Thai and Malay boys. Thai girls had approximately 2.0% higher %BF values than Chinese, Lebanese, Filipino and Malay counterparts (however no significant difference was seen among the four ethnic groups) at a given BMI (corrected mean %BF was 31.1�}0.5%, 28.6�}0.4%, 29.2�}0.6%, 29.5�}0.6%, 29.5�}0.5% for Thai, Chinese, Lebanese, Malay and Filipino girls, respectively). However, the ethnic difference in BMI�]%BF relationship varied by BMI. Compared with Caucasians, Asian children had a BMI 3�]6 units lower for a given %BF. More than one third of obese Asian children in the study were not identified using the WHO classification and more than half were not identified using the International Obesity Task Force (IOTF) classification. However, use of the Chinese classification increased the sensitivity by 19.7%, 18.1%, 2.3%, 2.3%, and 11.3% for Chinese, Lebanese, Malay, Filipino and Thai girls, respectively. A further aim of the first study was to determine the ethnic difference in body fat distribution in pre�]pubertal Asian children from China, Lebanon, Malaysia, and Thailand. The skin fold thicknesses, height, weight, waist circumference (WC) and total adiposity (as determined by deuterium dilution technique) of 922 children from the four countries was assessed. Chinese boys and girls had a similar trunk�]to�]extremity skin fold thickness ratio to Thai counterparts and both groups had higher ratios than the Malays and Lebanese at a given total FM. At a given BMI, both Chinese and Thai boys and girls had a higher WC than Malays and Lebanese (corrected mean WC was 68.1�}0.2 cm, 67.8�}0.3 cm, 65.8�}0.4 cm, 64.1�}0.3 cm for Chinese, Thai, Lebanese and Malay boys, respectively; 64.2�}0.2 cm, 65.0�}0.3 cm, 62.9�}0.4 cm, 60.6�}0.3 cm for Chinese, Thai, Lebanese and Malay girls, respectively). Chinese boys and girls had lower trunk fat adjusted subscapular/suprailiac skinfold ratio compared with Lebanese and Malay counterparts. The second study aimed to develop and cross�]validate bioelectrical impedance analysis (BIA) prediction equations of TBW and FFM for Asian pre�]pubertal children from China, Lebanon, Malaysia, the Philippines, and Thailand. Data on height, weight, age, gender, resistance and reactance measured by BIA were collected from 948 Asian children (492 boys and 456 girls) aged 8�]10 y from the five countries. The deuterium dilution technique was used as the criterion method for the estimation of TBW and FFM. The BIA equations were developed from the validation group (630 children randomly selected from the total sample) using stepwise multiple regression analysis and cross�]validated in a separate group (318 children) using the Bland�]Altman approach. Age, gender and ethnicity influenced the relationship between the resistance index (RI = height2/resistance), TBW and FFM. The BIA prediction equation for the estimation of TBW was: TBW (kg) = 0.231�~Height2 (cm)/resistance (ƒ¶) + 0.066�~Height (cm) + 0.188�~Weight (kg) + 0.128�~Age (yr) + 0.500�~Sex (male=1, female=0) . 0.316�~Ethnicity (Thai ethnicity=1, others=0) �] 4.574, and for the estimation of FFM: FFM (kg) = 0.299�~Height2 (cm)/resistance (ƒ¶) + 0.086�~Height (cm) + 0.245�~Weight (kg) + 0.260�~Age (yr) + 0.901�~Sex (male=1, female=0) �] 0.415�~Ethnicity (Thai ethnicity=1, others=0) �] 6.952. The R2 was 88.0% (root mean square error, RSME = 1.3 kg), 88.3% (RSME = 1.7 kg) for TBW and FFM equation, respectively. No significant difference between measured and predicted TBW and between measured and predicted FFM for the whole cross�]validation sample was found (bias = �]0.1�}1.4 kg, pure error = 1.4�}2.0 kg for TBW and bias = �]0.2�}1.9 kg, pure error = 1.8�}2.6 kg for FFM). However, the prediction equation for estimation of TBW/FFM tended to overestimate TBW/FFM at lower levels while underestimate at higher levels of TBW/FFM. Accuracy of the general equation for TBW and FFM compared favorably with both BMI�]specific and ethnic�]specific equations. There were significant differences between predicted TBW and FFM from external BIA equations derived from Caucasian populations and measured values in Asian children. There were three specific aims of the third study. The first was to explore the relationship between obesity and metabolic syndrome and abnormalities in Chinese children. A total of 608 boys and 800 girls aged 6�]12 y were recruited from four cities in China. Three definitions of pediatric metabolic syndrome and abnormalities were used, including the International Diabetes Federation (IDF) and National Cholesterol Education Program (NCEP) definition for adults modified by Cook et al. and de Ferranti et al. The prevalence of metabolic syndrome varied with different definitions, was highest using the de Ferranti definition (5.4%, 24.6% and 42.0%, respectively for normal�]weight, overweight and obese children), followed by the Cook definition (1.5%, 8.1%, and 25.1%, respectively), and the IDF definition (0.5%, 1.8% and 8.3%, respectively). Overweight and obese children had a higher risk of developing the metabolic syndrome compared to normal�]weight children (odds ratio varied with different definitions from 3.958 to 6.866 for overweight children, and 12.640�]26.007 for obese children). Overweight and obesity also increased the risk of developing metabolic abnormalities. Central obesity and high triglycerides (TG) were the most common while hyperglycemia was the least frequent in Chinese children regardless of different definitions. The second purpose was to determine the best obesity index for the prediction of cardiovascular (CV) risk factor clustering across a 2�]y follow�]up among BMI, %BF, WC and waist�]to�]height ratio (WHtR) in Chinese children. Height, weight, WC, %BF as determined by BIA, blood pressure, TG, high�]density lipoprotein cholesterol (HDL�]C), and fasting glucose were collected at baseline and 2 years later in 292 boys and 277 girls aged 8�]10 y. The results showed the percentage of children who remained overweight/obese defined on the basis of BMI, WC, WHtR and %BF was 89.7%, 93.5%, 84.5%, and 80.4%, respectively after 2 years. Obesity indices at baseline significantly correlated with TG, HDL�]C, and blood pressure at both baseline and 2 years later with a similar strength of correlations. BMI at baseline explained the greatest variance of later blood pressure. WC at baseline explained the greatest variance of later HDL�]C and glucose, while WHtR at baseline was the main predictor of later TG. Receiver�]operating characteristic (ROC) analysis explored the ability of the four indices to identify the later presence of CV risk. The overweight/obese children defined on the basis of BMI, WC, WHtR or %BF were more likely to develop CV risk 2 years later with relative risk (RR) scores of 3.670, 3.762, 2.767, and 2.804, respectively. The final purpose of the third study was to develop age�] and gender�]specific percentiles of WC and WHtR and cut�]off points of WC and WHtR for the prediction of CV risk in Chinese children. Smoothed percentile curves of WC and WHtR were produced in 2830 boys and 2699 girls aged 6�]12 y randomly selected from southern and northern China using the LMS method. The optimal age�] and gender�]specific thresholds of WC and WHtR for the prediction of cardiovascular risk factors clustering were derived in a sub�]sample (n=1845) by ROC analysis. Age�] and gender�]specific WC and WHtR percentiles were constructed. The WC thresholds were at the 90th and 84th percentiles for Chinese boys and girls, respectively, with sensitivity and specificity ranging from 67.2% to 83.3%. The WHtR thresholds were at the 91st and 94th percentiles for Chinese boys and girls, respectively, with sensitivity and specificity ranging from 78.6% to 88.9%. The cut�]offs of both WC and WHtR were age�] and gender�]dependent. In conclusion, the current thesis quantifies the ethnic differences in the BMI�]%BF relationship and body fat distribution between Asian children from different origins and confirms the necessity to consider ethnic differences in body composition when developing BMI and other obesity index criteria for obesity in Asian children. Moreover, ethnicity is also important in BIA prediction equations. In addition, WC and WHtR percentiles and thresholds for the prediction of CV risk in Chinese children differ from other populations. Although there was no advantage of WC or WHtR over BMI or %BF in the prediction of CV risk, obese children had a higher risk of developing the metabolic syndrome and abnormalities than normal�]weight children regardless of the obesity index used.

Akt, AS160, metabolic risk factors and aerobic fitness in middle-aged women

Aims: This study investigated the association between the basal (rest) insulin-signaling proteins, Akt, and the Akt substrate AS160, metabolic risk factors, inflammatory markers and aerobic fitness, in middle-aged women with varying numbers of metabolic risk factors for type 2 diabetes. Methods: Sixteen women (n = 16) aged 51.3+/-5.1 (mean +/-SD) years provided muscle biopsies and blood samples at rest. In addition, anthropometric characteristics and aerobic power were assessed and the number of metabolic risk factors for each participant was determined (IDF criteria). Results: The mean number of metabolic risk factors was 1.6+/-1.2. Total Akt was negatively correlated with IL-1 beta (r = -0.45, p = 0.046), IL-6 (r = -0.44, p = 0.052) and TNF-alpha (r = -0.51, p = 0.025). Phosphorylated AS160 was positively correlated with HDL (r = 0.58, p = 0.024) and aerobic fitness (r = 0.51, p = 0.047). Furthermore, a multiple regression analysis revealed that both HDL (t = 2.5, p = 0.032) and VO(2peak) (t = 2.4, p = 0.037) were better predictors for phosphorylated AS160 than TNF-alpha or IL-6 (p>0.05). Conclusions: Elevated inflammatory markers and increased metabolic risk factors may inhibit insulin-signaling protein phosphorylation in middle-aged women, thereby increasing insulin resistance under basal conditions. Furthermore, higher HDL and fitness levels are associated with an increased AS160 phosphorylation, which may in turn reduce insulin resistance.

Inflammation, hepatic enzymes and resistance training in individuals with metabolic risk factors

AIMS: Increases in inflammatory markers, hepatic enzymes and physical inactivity are associated with the development of the metabolic syndrome (MetS). We examined whether inflammatory markers and hepatic enzymes are correlated with traditional risk factors for MetS and studied the effects of resistance training (RT) on these emerging risk factors in individuals with a high number of metabolic risk factors (HiMF, 2.9 +/- 0.8) and those with a low number of metabolic risk factors (LoMF, 0.5 +/- 0.5). METHODS: Twenty-eight men and 27 women aged 50.8 +/- 6.5 years (mean +/- sd) participated in the study. Participants were randomized to four groups, HiMF training (HiMFT), HiMF control (HiMFC), LoMF training (LoMFT) and LoMF control (LoMFC). Before and after 10 weeks of RT [3 days/week, seven exercises, three sets with intensity gradually increased from 40-50% of one repetition maximum (1RM) to 75-85% of 1RM], blood samples were obtained for the measurement of pro-inflammatory cytokines, C-reactive protein (CRP), gamma-glutamyltransferase (GGT) and alanine aminotransferase (ALT). RESULTS: At baseline, HiMF had higher interleukin-6 (33.9%), CRP (57.1%), GGT (45.2%) and ALT (40.6%) levels, compared with LoMF (all P < 0.05). CRP, GGT and ALT correlated with the number of risk factors (r = 0.48, 0.51 and 0.57, respectively, all P < 0.01) and with other anthropometric and clinical measures (r range from 0.26 to 0.60, P < 0.05). RT did not significantly alter inflammatory markers or hepatic enzymes (all P > 0.05). CONCLUSIONS: HiMF was associated with increased inflammatory markers and hepatic enzyme concentrations. RT did not reduce inflammatory markers and hepatic enzymes in individuals with HiMF.

The influence of family history of hypertension on disease prevalence and associated metabolic risk factors among Sri Lankan adults

Background Hypertension is a major contributor to the global non-communicable disease burden. Family history is an important non-modifiable risk factor for hypertension. The present study aims to describe the influence of family history (FH) on hypertension prevalence and associated metabolic risk factors in a large cohort of South Asian adults, from a nationally representative sample from Sri Lanka. Methods A cross-sectional survey among 5,000 Sri Lankan adults, evaluating FH at the levels of parents, grandparents, siblings and children. A binary logistic regression analysis was performed in all patients with ‘presence of hypertension’ as dichotomous dependent variable and using family history in parents, grandparents, siblings and children as binary independent variables. The adjusted odds ratio controlling for confounders (age, gender, body mass index, diabetes, hyperlipidemia and physical activity) are presented below. Results In all adults the prevalence of hypertension was significantly higher in patients with a FH (29.3 %, n = 572/1951) than those without (24.4 %, n = 616/2530) (p < 0.001). Presence of a FH significantly increased the risk of hypertension (OR:1.29; 95 % CI:1.13-1.47), obesity (OR:1.36; 95 % CI: 1.27–1.45), central obesity (OR:1.30; 95 % CI 1.22–1.40) and metabolic syndrome (OR:1.19; 95 % CI: 1.08–1.30). In all adults presence of family history in parents (OR:1.28; 95 % CI: 1.12–1.48), grandparents (OR:1.34; 95 % CI: 1.20–1.50) and siblings (OR:1.27; 95 % CI: 1.21–1.33) all were associated with significantly increased risk of developing hypertension. Conclusions Our results show that the prevalence of hypertension was significantly higher in those with a FH of hypertension. FH of hypertension was also associated with the prevalence of obesity, central obesity and metabolic syndrome. Individuals with a FH of hypertension form an easily identifiable group who may benefit from targeted interventions.

Dietary and exercise interventions to improve quality of life, metabolic risk factors and androgen deficiency symptoms in men with prostate cancer undergoing androgen deprivation therapy

Introduction Lifestyle interventions might be useful in the management of adverse effects of androgen deprivation therapy (ADT) in men with prostate cancer. Objectives To examine the effects of dietary and exercise interventions on quality of life (QoL), metabolic risk factors and androgen deficiency symptoms in men with prostate cancer undergoing ADT. Methods CINAHL, Cochrane library, Medline and PsychINFO were searched to identify randomised controlled trials published from January, 2004 to October, 2014. Data extraction and methodological quality assessment was independently conducted by two reviewers. Meta-analysis was conducted using RevMan® 5.3.5. Results Of 2183 articles retrieved, 11 studies met the inclusion criteria and had low risk of bias.Nine studies evaluated exercise (resistance and/or aerobic and/or counselling) and three evaluated dietary supplementation. Median sample size =79 (33–121) and median intervention duration was 12 weeks (12–24). Exercise improved QoL measures (SMD 0.26, 95%CI −0.01 to 0.53) but not body composition, metabolic risk or vasomotor symptoms. Qualitative analysis indicated soy (or isoflavone) supplementation did not improve vasomotor symptoms; however, may improve QoL. Conclusions Few studies have evaluated the efficacy of lifestyle interventions in the management of adverse effects of ADT. We found inconclusive results for exercise in improving QoL and negative results for other outcomes. For soy-based products, we found negative results for modifying vasomotor symptoms and inconclusive results for improving QoL. Future work should investigate the best mode of exercise for improving QoL and other interventions such as dietary counselling should be investigated for their potential to modify these outcomes.

Serum uric acid and metabolic risk factors in three ethnic groups: Asian Indians and Creoles in Mauritius and Chinese in Qingdao, China

In humans with a loss of uricase the final oxidation product of purine catabolism is uric acid (UA). The prevalence of hyperuricemia has been increasing around the world accompanied by a rapid increase in obesity and diabetes. Since hyperuricemia was first described as being associated with hyperglycemia and hypertension by Kylin in 1923, there has been a growing interest in the association between elevated UA and other metabolic abnormalities of hyperglycemia, abdominal obesity, dyslipidemia, and hypertension. The direction of causality between hyperuricemia and metabolic disorders, however, is unceartain. The association of UA with metabolic abnormalities still needs to be delineated in population samples. Our overall aims were to study the prevalence of hyperuricemia and the metabolic factors clustering with hyperuricemia, to explore the dynamical changes in blood UA levels with the deterioration in glucose metabolism and to estimate the predictive capability of UA in the development of diabetes. Four population-based surveys for diabetes and other non-communicable diseases were conducted in 1987, 1992, and 1998 in Mauritius, and in 2001-2002 in Qingdao, China. The Qingdao study comprised 1 288 Chinese men and 2 344 women between 20-74, and the Mauritius study consisted of 3 784 Mauritian Indian and Mauritian Creole men and 4 442 women between 25-74. In Mauritius, re-exams were made in 1992 and/or 1998 for 1 941 men (1 409 Indians and 532 Creoles) and 2 318 non pregnant women (1 645 Indians and 673 Creoles), free of diabetes, cardiovascular diseases, and gout at baseline examinations in 1987 or 1992, using the same study protocol. The questionnaire was designed to collect demographic details, physical examinations and standard 75g oral glucose tolerance tests were performed in all cohorts. Fasting blood UA and lipid profiles were also determined. The age-standardized prevalence in Chinese living in Qingdao was 25.3% for hyperuricemia (defined as fasting serum UA > 420 μmol/l in men and > 360 μmol/l in women) and 0.36% for gout in adults between 20-74. Hyperuricemia was more prevalent in men than in women. One standard deviation increase in UA concentration was associated with the clustering of metabolic risk factors for both men and women in three ethnic groups. Waist circumference, body mass index, and serum triglycerides appeared to be independently associated with hyperuricemia in both sexes and in all ethnic groups except in Chinese women, in whom triglycerides, high-density lipoprotein cholesterol, and total cholesterol were associated with hyperuricemia. Serum UA increased with increasing fasting plasma glucose levels up to a value of 7.0 mmol/l, but significantly decreased thereafter in mainland Chinese. An inverse relationship occurred between 2-h plasma glucose and serum UA when 2-h plasma glucose higher than 8.0 mmol/l. In the prospective study in Mauritius, 337 (17.4%) men and 379 (16.4%) women developed diabetes during the follow-up. Elevated UA levels at baseline increased 1.14-fold in risk of incident diabetes in Indian men and 1.37-fold in Creole men, but no significant risk was observed in women. In conclusion, the prevalence of hyperuricemia was high in Chinese in Qingdao, blood UA was associated with the clustering of metabolic risk factors in Mauritian Indian, Mauritian Creole, and Chinese living in Qingdao, and a high baseline UA level independently predicted the development of diabetes in Mauritian men. The clinical use of UA as a marker of hyperglycemia and other metabolic disorders needs to be further studied. Keywords: Uric acid, Hyperuricemia, Risk factors, Type 2 Diabetes, Incidence, Mauritius, Chinese

GWAS of butyrylcholinesterase activity identifies four novel loci, independent effects within BCHE and secondary associations with metabolic risk factors

Serum butyrylcholinesterase (BCHE) activity is associated with obesity, blood pressure and biomarkers of cardiovascular and diabetes risk. We have conducted a genome-wide association scan to discover genetic variants affecting BCHE activity, and to clarify whether the associations between BCHE activity and cardiometabolic risk factors are caused by variation in BCHE or whether BCHE variation is secondary to the metabolic abnormalities. We measured serum BCHE in adolescents and adults from three cohorts of Australian twin and family studies. The genotypes from approximately 2.4 million single-nucleotide polymorphisms (SNPs) were available in 8791 participants with BCHE measurements. We detected significant associations with BCHE activity at three independent groups of SNPs at the BCHE locus (P = 5.8 x 10(-262), 7.8 x 10(-47), 2.9 x 10(-12)) and at four other loci: RNPEP (P = 9.4 x 10(-16)), RAPH1-ABI2 (P = 4.1 x 10(-18)), UGT1A1 (P = 4.0 x 10(-8)) and an intergenic region on chromosome 8 (P = 1.4 x 10(-8)). These loci affecting BCHE activity were not associated with metabolic risk factors. On the other hand, SNPs in genes previously associated with metabolic risk had effects on BCHE activity more often than can be explained by chance. In particular, SNPs within FTO and GCKR were associated with BCHE activity, but their effects were partly mediated by body mass index and triglycerides, respectively. We conclude that variation in BCHE activity is due to multiple variants across the spectrum from uncommon/large effect to common/small effect, and partly results from (rather than causes) metabolic abnormalities.