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Background It is well established that body composition influences metabolic health, but emerging data are conflicting with the largely purported idea that a large fat‐free mass (FFM) has a protective effect on health. A potential explanation for these discrepancies is the way FFM is represented. The first objective is to determine the association between the metabolic syndrome (MetS) and FFM when the latter was represented in three different ways: 1—absolute FFM; 2—relative to squared height (FFMi); and 3—relative to body weight (FFM%). The second objective is to assess the impact of FFM on the relative risk of having the MetS after taking fat mass, physical activity, and sociodemographic variables into account. Methods A total of 5274 individuals from the National Health and Nutrition Examination Survey database were studied. Age‐specific and sex‐specific quartiles of the three representations of FFM were defined, and the prevalence of MetS was determined in each of them. Quartiles of FFMi (kg/m2) were used to calculate the odds ratios of having the MetS independently of FM, physical activity levels, and sociodemographic variables. Results The prevalence of MetS decreased with increasing quartiles of whole‐body FFM% (Q1: 40%; Q4: 10%) but grew with increasing quartiles of absolute FFM (Q1: 13%; Q4: 40%) and FFMi (Q1: 10%; Q4: 44%). Similar results were observed for appendicular and truncal FFM. The odds ratios of having the MetS, independently of fat mass, physical activity, and sociodemographic variables, were significantly greater in the fourth quartile of FFMi when compared with the first quartiles of each specific subgroup [Q4 vs. Q1: younger men: 4.16 (1.99–8.68); younger women: 5.74 (2.46–13.39); older men: 1.98 (1.22–3.22); older women: 2.88 (1.69–4.90); all P ≤ 0.01]. Conclusions These results support the notion that the representation of FFM significantly influences its association with MetS and that a larger FFM, whether absolute or relative to height, is associated with alterations in cardiometabolic health.

Objectives: To compare the effect of low-volume high-intensity interval training (HIIT) with moderate-intensity continuous training (MICT) on fat mass, cardiometabolic profile, and physical capacity, and confirm its feasibility in older women. Methods: Inactive older women (60–75 years) were randomly assigned to 8 weeks of either HIIT (75 min/week; n = 9) or MICT (150 min/week; n = 9). Body composition, fasting metabolic profile, cardiovascular risk (Framingham score), and physical capacity (senior fitness test, peak oxygen uptake) were assessed before and after the intervention. Feasibility was evaluated with completion rate (training compliance; dropout rate) and affective response (Feeling Scale; pre- and postexercise). Results: Total cholesterol level, non-high-density lipoprotein cholesterol level, and the Framingham risk score decreased in both groups (ps ≤ .03). Although peak oxygen uptake remained unchanged, the 6-min walk test distance increased (p ps ≥ .38). Conclusion: A short-term HIIT program is feasible and provides as much benefits as MICT in older women.

To document changes in prevalence of the metabolic syndrome (MetS) in the United States adult population between 1999 and 2014 and to explore how variations in the dietary intakes explain changes in MetS prevalence and its components over time. A total of 38 541 individuals (aged 20–85 years; National Health and Nutrition Examination Survey 1999–2014) were studied. Outcome variables were MetS, waist circumference (WC), plasma high-density lipoprotein cholesterol (HDL-c), triglycerides, fasting glucose (FG) levels, resting systolic and diastolic blood pressure, dietary intakes (total daily energy, carbohydrates, proteins, fats, sodium, and alcohol intakes), the poverty income ratio (PIR) and sociodemographic data (age, sex, ethnicity). Overall, the prevalence of the MetS significantly increased between 1999 and 2014 (27.9% to 31.5%). High plasma FG levels and high WC increased between 1999 and 2014, while the prevalence of the other components of MetS decreased or remained stable. Interestingly, a significant peak in MetS prevalence was observed in 2007–2008 compared with 1999–2006 (34.4% vs 27.6%), accompanied by a concomitant increase in WC and plasma FG levels, as well as a decrease in plasma HDL-c. Finally, significant decreases were observed for the PIR, total daily energy intake, sodium, and all macronutrient intakes in 2007–2008 compared with 1999–2006 (all P < 0.01). Results showed that the MetS prevalence significantly increased between 1999 and 2014 in the United States adult population, with a peak in 2007–2008. Interestingly, the 2007–2008 peak in MetS prevalence was accompanied by decreases in the PIR, total daily energy, and macronutrients intakes, suggesting potential impact of the 2007–2008 recession.

Objective: To compare the acute and chronic effects of low-volume high-intensity interval training (HIIT) to moderate-intensity continuous training (MICT) on glycemic control, body composition and continuous glucose monitoring (CGM) in older women with type 2 diabetes (T2D). Methods: Thirty older women (68 ± 5 years) with T2D were randomized in two groups—HIIT (75 min/week) or MICT (150 min/week). Glucose homeostasis (A1c, glucose, insulin, HOMA-IR2) and body composition (iDXA) were measured before and after the 12-week exercise intervention. During the first and last week of training (24-h before and 48-h after exercise), the following CGM-derived data were measured: 24-h and peak glucose levels, glucose variability and time spent in hypoglycemia as well as severe and mild hyperglycemia. Results: While lean body mass increased (p = 0.035), total and trunk fat mass decreased (p ≤ 0.007), without any difference between groups (p ≥ 0.81). Fasting glucose levels (p = 0.001) and A1c (p = 0.014) significantly improved in MICT only, with a significant difference between groups for fasting glucose (p = 0.02). Neither HIIT nor MICT impacted CGM-derived data at week 1 (p ≥ 0.25). However, 24-h and peak glucose levels, as well as time spent in mild hyperglycemia, decreased in HIIT at week 12 (p ≤ 0.03). Conclusion: These results suggest that 12 weeks of low-volume HIIT is enough to provide similar benefit to MICT for body composition and improve the acute effect of exercise when measured with CGM.

Background and aims To compare the effect of a low-volume walking high-intensity interval training (HIIT) to moderate-intensity continuous training (MICT) on risk of cardiovascular diseases and physical capacity in older women with type 2 diabetes (T2D). Methods Thirty inactive older women with T2D were randomized into either HIIT (75 min/week) or MICT (150 min/week). Cardiovascular risk profile (lipid profile; waist circumference and fat mass; resting, post-exercise and ambulatory blood pressure [BP]; VO2 peak; UKPDS score; ABC's) and physical capacity were assessed before and after a 12-week intervention. Results While resting systolic and diastolic BP (all p ≤ 0.01) were reduced, ambulatory BP (p ≥ 0.49) and lipid profile (p ≥ 0.40) remained unchanged after the intervention. Although VO2 peak increased to a similar extent in both groups (p = 0.015), the distance covered during the 6MWT (p = 0.01) and grip strength (p = 0.02) increased to a greater extend in HIIT. The UKPDS risk score decreased in both groups after the intervention (p = 0.03) and 31% of the participants reached the ABC's compared to 24% at baseline. Conclusion Low-volume walking HIIT is an efficient exercise intervention for older women with T2D as it improved some CVD risk factors and physical capacity. Nevertheless, neither low-volume HIIT nor MICT is sufficient to affect ambulatory blood pressure in T2D patients.

Objectives First, to establish the respective ability of body mass index (BMI), waist circumference (WC), and relative fat mass index (RFM), to estimate body fat (BF%) measured by DXA (DXA-BF%) and correctly identify postmenopausal women living with obesity (BF% > 35). Second, to identify the best indicator of successful weight-loss intervention in postmenopausal women living with obesity. Methods A total of 277 women (age: 59.8 ± 5.3 y; BF%: 43.4 ± 5.3) from five weight-loss studies with complete data for anthropometric measurements [BMI = weight/height (kg/m2); WC (cm)] and BF% were pooled together. Statistical performance indicators were determined to assess ability of RFM [64-(20 × height/waist circumference) + (12 × sex)], BMI and WC to estimate BF% before and after weight-loss intervention and to correctly identify postmenopausal women living with obesity. Results Compared with RFM (r = 0.51; r2 = 0.27; RMSE = 4.4%; Lin's CCC = 0.46) and WC (r = 0.49; r2 = 0.25; RMSE = 4.8%; Lin's CCC = 0.41), BMI (r = 0.73; r2 = 0.52; RMSE = 3.7%; Lin's CCC = 0.71) was the best anthropometric index to estimate DXA-BF% and correctly identify postmenopausal women living with obesity (sensitivity + specificity: BMI = 193; RFM = 152; WC = 158), with lower misclassification error, before weight-loss intervention. After weight-loss, the change in BMI was strongly correlated with change in DXA-BF%, indicating that the BMI is the best indicator of success weight-loss intervention. Conclusion In the absence of more objective measures of adiposity, BMI is a suitable proxy measure for BF% in postmenopausal women, for whom a lifestyle intervention is relevant. Furthermore, BMI can be used as an indicator to assess success of weight-loss intervention in this subpopulation.

Menopause transition is associated with detrimental changes in physical activity, body composition, and metabolic profile. Although physical activity energy expenditure (PAEE) is inversely associated with metabolic syndrome (MetS) in individuals at higher risk of cardiovascular disease, the association is unknown in low-risk individuals. The aim of the study was to investigate the association between PAEE and MetS (prevalence and severity) in inactive overweight or obese postmenopausal women with a low Framingham Risk Score ( Novelty: Inactive individuals displaying higher daily PAEE also have a lower MetS prevalence. Greater FFM is associated with a worse MetS severity where a higher PAEE mitigated this deleterious effect in our cohort.

A sex-specific standard waist circumference (WC) is widely used to determine cardiometabolic risk across ages even though aging impacts the link between fat distribution and cardiometabolic risk. The objective was to propose WC thresholds that better predict metabolic abnormalities according to sex, age, and body mass index (BMI) categories.First, receiver operating characteristic analyses were performed to identify optimal age (20-49, 50-64, and 65-80 years) and BMI (normal weight, overweight, obese I, and obese II+) specific WC thresholds to correctly identify at-risk individuals, that is, presenting ≥2 cardiometabolic risk factors of metabolic syndrome (n = 23,482; NHANES 2007-2014). Second, cross-validation analyses (n = 18,686; NHANES 1999-2006) were used to validate these WC optimal thresholds. Univariate logistic regression models with WC as an independent predictor were performed to quantify odds of being at-risk for each age and BMI subgroups.When age and BMI categories were considered in the identification of optimal WC thresholds, sensitivity to correctly identify at-risk individuals significantly improved.Our results indicate that the use of WC thresholds that are specific to age and BMI subcategories significantly increases the capacity to accurately identify at-risk individuals. They would thus be highly appropriate for clinicians in the context of efficient cardiometabolic risk assessment and intervention recommendations.

A greater fat-free mass (FFM) is purported to be associated with protective effects on insulin resistance (IR). However, recent studies suggested negative associations between FFM and IR. (1) To explore the direction of the association between FFM and IR in a large heterogeneous sample after controlling for confounding factors. (2) To determine cut off values of FFM associated with an increased risk of IR. Outcome variables were measured in 7044 individuals (48.6% women, 20–79 years; NHANES, 1999–2006): body composition [fat mass (FM), FFM and appendicular FFM (aFFM); DXA], FFM index [FFMI: FFM/height (kg/m2)], appendicular FFMI [aFFM/height (kg/m2)] and insulin resistance (HOMA-IR). Multivariate regression analyses were performed to determine the independent predictors of HOMA-IR in younger (20–49 years) and older (50–79 years) men and women. ROC analyses were used to determine FFM cut-offs to identify a higher risk of insulin resistance (HOMA-IR > 75th percentile). aFFMI was an independent predictor of IR in younger (men: β = 0.21; women: β = 0.31; all p ≤ 0.001) and older (men: β = 0.11; women: β = 0.37; all p ≤ 0.001) individuals. Thresholds for aFFMI at which the risk of IR was significantly increased were 8.96 and 8.39 kg/m2 in younger and older men, and 7.22 and 6.64 kg/m2 in younger and older women, respectively. Independently of age, a greater aFFMI was an independent predictor of IR. These results suggest revisiting how we envision the link between FFM and IR and explore potential mechanisms.

Menopausal transition and postmenopause are usually associated with changes in body composition and a decrease in physical activity energy expenditure (PAEE). This study investigated body composition, cardiometabolic risk factors, PAEE, and inflammatory markers in premenopausal women after a 10-year follow-up.In all, 102 premenopausal women participated in the 5-year observational longitudinal Montreal Ottawa New Emerging Team (MONET) study. This present substudy included 48 participants (age: 60.0 ± 1.7 years; body mass index: 23.2 ± 2.2 kg/m) 6.0 ± 0.3 years after completion of the initial MONET study. Measures included body composition, waist circumference (WC), fasting glucose and insulin levels, insulin sensitivity (QUICKI model), plasma lipid levels, PAEE, and inflammatory markers.Compared with baseline measures of the MONET study, analyses revealed no significant increase in body weight, although there were significant increases in WC, fat mass (FM), % FM, total cholesterol, low-density lipoprotein cholesterol and high-density lipoprotein cholesterol, haptoglobin, apolipoprotein B, ferritin, adiponectin, and soluble cluster of differentiation 14 (all P 0.001) after the 10-year follow-up. However, significant decreases were observed for fat-free mass, PAEE, fasting glucose levels, interleukin-8 levels, and soluble tumor necrosis factor receptors 1 and 2 (sTNFR-1 and sTNFR-2) levels (all P 0.05). To determine the effect of postmenopausal years, data were restructured based on final menstrual period (FMP), and one-way analyses of variance were performed.Waist circumference, % FM, total cholesterol, high-density lipoprotein cholesterol, apolipoprotein B, ferritin, adiponectin, and soluble cluster of differentiation 14 were higher in early and late postmenopausal periods in these women. sTNFR-1 and sTNFR-2 levels were higher at the FMP and early postmenopausal years as compared with the late postmenopausal periods. Finally, interleukin-8 levels were lower in years after FMP.The number of years elapsed since the FMP can affect body composition, cardiometabolic risk factors, and inflammatory markers in healthy premenopausal women going through menopausal transition and postmenopausal periods.

To compare the effects of a caloric restriction (CR) on body composition, lipid profile, and glucose homeostasis in obese postmenopausal women with and without metabolic syndrome (MetS).Secondary analyses were performed on 73 inactive obese postmenopausal women (age 57.7 ± 4.8 years; body mass index 32.4 ± 4.6 kg/m) who participated in the 6-month CR arm of a study of the Montreal-Ottawa New Emerging Team. The harmonized MetS definition was used to categorize participants with MetS (n = 20, 27.39%) and without MetS (n = 53, 72.61%). Variables of interest were: body composition (dual-energy X-ray absorptiometry), body fat distribution (computed tomography scan), glucose homeostasis at fasting state and during a euglycemic/hyperinsulinemic clamp, fasting lipids, and resting blood pressure.By design, the MetS group had a worse cardiometabolic profile, whereas both groups were comparable for age. Fifty-five participants out of 73 displayed no change in MetS status after the intervention. Twelve participants out of 20 (or 60.0%) in the MetS group had no more MetS after weight loss (P = NS), whereas 6 participants out of 53 (or 11.3%) in the other group developed the MetS after the intervention (P = NS). Overall, indices of body composition and body fat distribution improved significantly and similarly in both groups (P between 0.03 and 0.0001). Furthermore, with the exception of triglyceride levels and triglycerides/high-density lipoprotein cholesterol ratio, which decrease significantly more in the MetS group (P ≤ 0.05), no difference was observed between groups for the other variables of the cardiometabolic profile.Despite no overall significant effects on MetS, heteregeneous results were obtained in response to weight loss in the present study, with some improving the MetS, whereas other displaying deteriorations. Further studies are needed to identify factors and phenotypes associated with positive and negative cardiometabolic responses to CR intervention.

The association between the energy density (ED) of foods and adiposity has been reported previously. However, whether the contribution of ED to adiposity remains significant when controlled for energy intake (EI) and physical activity energy expenditure (PAEE) remains to be clearly established. We aimed to investigate the independent contribution of ED to variations in body composition in women during the menopausal transition.Sixty-seven women from the MONET cohort study were analyzed. Seven-day food records were used to assess EI and ED. Body composition (body fat mass (FM) and trunk-fat mass (TFM)) was measured with dual-energy X-ray absorptiometry; PAEE was assessed with accelerometers. This secondary analysis of data included measurements obtained at years 1 and 5 of the study.Mean ED was correlated with FM (r = 0.22; P = 0.04) and TFM (r = 0.22; P = 0.04) at year 1, but not at year 5. The multiple regression analysis showed that EI and ED contributed to 14% of the variance in FM and TFM at year 1.These results suggest that ED is a modest but inconsistent determinant of adiposity in healthy women at the time of the menopause transition.

Background: Body mass index (BMI) is often criticised since it doesn’t consider sex, age and ethnicity, which may affect the height scaling exponent of the equation.Aims: First, to identify...

Background: The aim of this study was to identify modifiable risk factors associated with isolated impaired fasting glucose (IFG), isolate impaired glucose tolerance (IGT), or combined IFG-IGT in men and women aged 50 years and older. Methods: Cross-sectional analyses were performed in 703 men and women aged between 50 and 80 years old from NHANES (2007–2008). Outcome variables: IFG and IGT (ADA 2003), estimated body composition, cardiometabolic profile, and socio-demographic, dietary, and lifestyle factors. Results: First, 235 had normal glucose tolerance (men = 38.3%, women = 61.7%), 243 had IFG (men = 61.7%, women = 38.3%), 67 had IGT (men = 40.3%, women = 59.7%) and 158 had both conditions (men = 57.0%, women = 43.0%). The only common determinant of both IFG and IGT was triglyceride levels. High total fat mass index (FMI) and high total fat-free mass index (FFMI) were independently associated with IFG; while high C-reactive protein (CRP) levels were independently associated with IGT. Finally, combined IFG-IGT was associated with inadequate fiber intake, high FMI, FFMI, and CRP levels. Conclusions: Middle-age and older individuals presented different modifiable risk factors depending on whether they had IFG or IGT. IFG was associated with deteriorated body composition and lipids, whereas IGT was associated with deteriorated lipids and inflammatory factors. IFG-IGT, on the other hand, was associated with a larger number of risk factors, including worsen body composition, cardiometabolic and dietary factors. To prevent the transition to type 2 diabetes, specific clinical interventions targeting these risk factors should be considered.

To determine the influence of cardiorespiratory fitness (hereafter “fitness”) and physical activity levels on cardiometabolic risk factors in premenopausal women going through the menopause transition. An ancillary study including 66 premenopausal women who participated to a 5-year observational, longitudinal study (2004 to 2009 in Ottawa) on the effects of menopause transition on body composition and cardiometabolic risk factors. Women underwent a graded exercise test on treadmill to measure peak oxygen uptake (VO2 peak) at year 1 and 5 and physical activity levels were measured using accelerometers. Cardiometabolic risk factors included: waist circumference, fasting plasma lipids, glucose and insulin levels, HOMA-IR score, c-reactive protein, apolipoprotein B (apoB) and resting systolic and diastolic blood pressure. Change in fitness was not associated with changes in cardiometabolic risk factors. The changes in total physical activity levels on the other hand showed a significant negative association with apoB levels. Three-way linear mixed model repeated measures, showed lower values of waist circumference, fasting triglycerides, insulin levels, HOMA-IR score, apoB and diastolic blood pressure in women with a fitness ≥ 30.0 mlO2 kg− 1 min− 1 compared to women with a fitness, Highlights • Fitness and physical activity levels are independent predictors of CVD. • Change in total physical activity levels was negatively association with apoB. • Fitness was associated with more favorable values of cardiometabolic risk factors.

Objectives 1) To document quality of life (QOL) changes in type 2 diabetes (T2D) and at-risk individuals who took part in the DiabetAction program and 2) to determine if changes in the QOL were associated with program attendance. Methods QOL (SF-36 questionnaire), physical activity (PA) level, body weight, skinfold thickness, aerobic capacity and handgrip strength were measured before and after the 10-week intervention in 15 T2D and 14 at-risk individuals. Results Physical and mental components of QOL and 6 out of 8 domains of QOL were significantly improved in T2D and at-risk individuals after the intervention. Four significant correlations were identified: physical functioning domain with skinfolds (r = – 0.56) and aerobic capacity (r = 0.49), social functioning domain with handgrip strength (r = 0.43) and the physical health summary measure with body weight (r = – 0.45). Conclusion QOL was significantly improved after the DiabetAction program. Also, PA intervention appears to impact QOL to a larger extent when participants experience changes in body composition and fitness.

OBJECTIVE The aim of this study was to examine if overweight postmenopausal women who do not experience fat mass loss after a 1-year aerobic exercise (AE) and resistance training (RT) program can still improve physical fitness. METHODS Thirty-one overweight women (body mass index 28-40 kg/m or waist circumference ≥88 cm) participated in three weekly supervised AE and RT sessions for 1 year. All women were categorized according to their fat mass changes after the intervention: 14 women were considered as responders (fat mass loss ≥5% of initial fat mass) and 17 as nonresponders (fat mass loss

Adequate protein intake and resistance training are effective strategies to maintain muscle mass, but the effect of their combination on metabolic profile during weight loss remains to be determined in older adults. The main objective of this study was to determine the effect of a 16-week high-protein caloric restriction combined with resistance training on chronic disease risk factors in obese older individuals with metabolic impairments. A total of 26 overweight adults aged between 60 and 75 years (BMI 32.4 ± 3.9 kg/m2) with at least 2 factors of the metabolic syndrome participated in this study and were randomized into two groups: 1) high-protein caloric restriction (HP; n= 12) and 2) high-protein caloric restriction combined with dynamic-resistance training (HP+RT; n=14). Caloric intake was reduced by 500 kcal/d in all participants and protein intake equated 25-30% of total calories (~1.4 g/kg/d). Exercise training consisted of 3 session/week of resistance training on pulley machines. Outcome measures included total and trunk fat mass (FM), total and appendicular lean body mass (LBM), fasting glucose level, lipid profile and blood pressure. Our results showed that total and trunk FM (all p

Obesity in older adults results from several interacting factors. Consequently, interventions have shown mitigated effects. We determined (a) the different subgroups of older adults with obesity based on clusters of associated comorbidities and (b) the trajectory of these clusters to assess their stability over 3 years and factors contributing to transitions. Obese men (n = 193; body mass index [BMI] = 33.15 ± 2.69 kg/m2 ) and women (n = 220; BMI = 33.71 ± 3.71 kg/m2 ) aged between 68 and 82 years were studied. Outcome variables were body composition, strength, physical capacity (PC), nutrition, psychological and physical health and social participation. Cluster analyses, stratified by sex, were used to identify obesity profiles at baseline and follow-up. Three profiles were identified, based on general health (GH), psychological health (PH) and PC: Cluster 1: healthy obese (GH+, PH+, PC+); Cluster 2: obese with low PC (GH+/-, PH+/-, PC-); Cluster 3: unhealthy obese (GH-, PH-, PC-). After 3 years, 61.2% and 70.2% of men and women remained in their initial cluster, compared to 20.4% and 13.7% who transitioned towards a worse health cluster and 18.3% and 16.0% who transitioned towards a more favourable cluster, partly explained by changes in physical health for men and physical health and PH for women. The results of this study show that targeting physical function in men and physical health and PH functions in women could prevent further health decline in older adults with obesity. Further studies are needed to investigate the role of these clusters in the prediction of cardiometabolic complications and mortality.

Objective: To investigate if an exaggerated peak exercise systolic blood pressure (peak ESBP) is associated with alteration of cardiometabolic risk factors and predict future resting hypertension in middle aged women. Methods: Data analysis was performed in 95 healthy normotensive premeno-pausal women at baseline and 84 after 5-year follow-up (age, 49.9 ± 1.9 years; BMI, 23.3 ± 2.2 kg/m2; resting BP, 117/73 ± 11.8/7.6 mmHg). Blood pressure was measured at rest and during a progressive exercise test on treadmill. Women were divided into two groups according to their peak ESBP

It is unknown whether leptin and peptide YY (PYY) influence changes in resting energy expenditure (REE), independently of fat mass (FM) and fat-free mass (FFM) in addition to changes in other energy expenditure (EE) components during weight loss.The objective of the study was to examine the relationships between leptin, PYY, and body composition with different EE components before and after weight loss and whether changes in leptin and PYY were associated with differences in predicted vs measured REE after the intervention.This was a randomized controlled design.The study was conducted in a laboratory.Participants were ninety-three overweight/obese postmenopausal women (aged 58.1 ± 4.8 y; body mass index 32.1 ± 4.3 kg/m(2)).Interventions included a 6-month caloric restriction diet alone or caloric restriction diet+resistance training.Body composition (dual energy x-ray absorptiometry), REE (indirect calorimetry), total EE (TEE; doubly labeled water), and fasting leptin and total PYY before and after weight loss were measured.Both interventions yielded significant decreases in weight, FFM, REE, and leptin, whereas a significant time × group interaction was noted for FM (greater decrease in FM in the diet+resistance training group) (P.05 for all outcomes). No significant differences in TEE, physical activity EE, and PYY were noted between baseline and after the intervention. Age, FFM, leptin, and PYY were the best predictors of baseline REE (R(2) = 0.77; P = .0001), whereas age, FFM, and FM were associated with REE after the intervention (R(2) = 0.88; P = .0001). The same predictors, except for leptin, were significantly related to TEE at baseline (R(2) = 0.70; P = .0001) and after the intervention (R(2) = 0.29; P = .0001), whereas only PYY was a significant predictor of physical activity EE at baseline and after the intervention. Changes in FM and leptin accounted for 27% of the variance in ΔREE (P = .0001). Greater predicted vs measured REE was noted after the intervention (P = .02). However, Δ leptin and ΔPYY were not significant predictors of the differences between postintervention measurement and predicted REE.Δ Leptin and ΔFM were strong contributors to changes in REE. However, Δ leptin and ΔPYY were not significant predictors of the differences between predicted and measured REE after the intervention.

This study aims to investigate individual characteristics that explain interindividual variations in glucose disposal in response to a 6-month weight loss program in obese postmenopausal women.The cohort was divided into tertiles based on changes in glucose disposal after weight loss. Only women in the upper tertile (positive responders: Δ glucose disposal ≥ 0.92 mg/kg/min; n = 19) and lower tertile (negative responders: Δ glucose disposal ≤ -0.23 mg/kg/min; n = 19) were considered for analyses. Outcome measures included body weight, lean body mass (LBM), LBM index (= LBM / height [m]), fat mass (FM), FM index (= FM / height [m]), visceral fat, subcutaneous abdominal fat, high-sensitivity C-reactive protein (hsCRP) levels, interleukin-6, lipid profile, physical activity levels, fasting blood glucose and insulin levels, glucose disposal by hyperinsulinemic-euglycemic clamp technique, and resting blood pressure.At baseline, positive responders had higher triglycerides and hsCRP levels and lower glucose disposal (0.01P0.05) than negative responders. Except for visceral fat, the entire cohort showed significant decreases in all measures of body composition (P0.005) after weight loss, with greater decreases in body weight, body mass index, and FM index in positive responders (P0.005). Finally, data revealed that only positive responders showed decreases in LBM, LBM index, and hsCRP levels after weight loss (P between 0.01 and 0.001).An important interindividual variability in changes in glucose disposal after weight loss is observed. Interestingly, participants who display improvements in glucose disposal also show significant decreases in LBM, LBM index, and hsCRP after weight loss.

Objective: The dynapenic (DYN)-obese phenotype is associated with an impaired metabolic profile. However, there is a lack of evidences regarding the effect of lifestyle interventions on the metabolic profile of individual with dynapenic phenotype. The objective was to investigate the impact of caloric restriction (CR) with or without resistance training (RT) on body composition, metabolic profile and muscle strength in DYN and non-dynapenic (NDYN) overweight and obese menopausal women. Design: 109 obese menopausal women (age 57.9 ± 9.0 yrs; BMI 32.1 ± 4.6 kg/m2) were randomized to a 6-month CR intervention with or without a RT program. Participants were categorized as DYN or NDYN based on the lowest tertile of relative muscle strength in our cohort (< 4.86 kg/BMI). Measurements: Body composition was measured by DXA, body fat distribution by CT scan, glucose homeostasis at fasting state and during an euglycemic-hyperinsulinemic clamp, fasting lipids, resting blood pressure, fasting inflammation markers and maximal muscle strength. Results: No difference was observed between groups at baseline for body composition and the metabolic profile. Overall, a treatment effect was observed for all variables of body composition and some variables of the metabolic profile (fasting insulin, glucose disposal, triglyceride levels, triglycerides/HDL-Chol ratio and resting diastolic blood pressure) (P between 0.05 and 0.001). No Group X Treatment interaction was observed for variables of body composition and the metabolic profile. However, an interaction was observed for muscle strength; which significantly improved more in the CR+RT NDYN group (all P ≤ 0.05). Conclusions: In the present study, dynapenia was not associated with a worse metabolic profile at baseline in overweight and obese menopausal women. DYN and NDYN menopausal women showed similar cardiometabolic benefit from CR or CR+RT interventions. However, our results showed that the addition of RT to CR was more effective in improving maximal strength in DYN and NDYN obese menopausal women.

Resistance training (RT) has been shown to decrease fat mass (FM), and increase fat-free mass (FFM), which can be a useful for weight loss maintenance. Objective To examine the effects of a 1-year RT intervention on weight loss maintenance following a 6-month dietary weight loss intervention. Design Following a 6-month dietary weight loss intervention (−6% ± 5.8; 5.05 kg ± 4.45), 70 postmenopausal women living with overweight or obesity were randomized to a control group ( n = 34) or a RT group ( n = 36) (3×/week first 6 months, 2×/week last 6 months, 70–80% of 1-repetition maximum). Body composition (DXA), abdominal visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) (CT scan), resting energy expenditure (EE) (indirect calorimetry), physical activity EE and total daily EE were measured (doubly-labelled water). Results A total of 54 participants completed the study (control group n = 29; RT group n = 25) and compliance to the RT program was on average 64%. Significant regains were noted for body weight 0.98 (3.71) kg vs. 1.33 (3.94) kg and FM regain 1.32 (2.69) kg vs. 0.81 (3.26) kg in control and RT groups after the 1-year weight maintenance phase. No group differences were noted. Resting EE and total daily EE did not change after the weight maintenance phase, and no differences were observed between groups. Both groups had significantly greater than predicted decrease in resting EE after the 6-month dietary intervention and at the end of the 1-year weight-loss maintenance phase. Conclusions Our results suggest that a 1-year RT intervention following a 6-month dietary weight loss intervention does not improve weight loss maintenance, body composition or EE in post-menopausal women living with overweight or obesity.

It is unknown whether the satiety quotient (SQ) differs across the menopausal transition, and whether changes in SQ are related to changes in anthropometric/body composition variables. The objective of this study was to evaluate the changes in SQ and its association with energy intake and changes in anthropometric/body composition variables across the menopausal transition.At baseline, 102 premenopausal women (aged 49.9 ± 1.9 years, body mass index 23.3 ± 2.2 kg/m(2)) took part in a 5-year observational, longitudinal study. Body composition (DXA), appetite (visual analog scales), energy and macronutrient intakes (ad libitum lunch and 7-day food diary) were assessed annually. The SQ (mm/100 kcal) was calculated at 60 and 180 min post-breakfast consumption.Overall, the SQ increased at years 3 and 4 (p = 0.01-0.0001), despite no significant differences between menopausal status groups. Lower fullness, prospective food consumption and mean SQ values predicted overall increases in lunch energy and macronutrient intakes (p = 0.04-0.01), whereas only prospective food consumption and fullness SQ predicted energy intake and carbohydrate intake, respectively, when assessed with food diaries (p = 0.01). Delta SQs were negatively correlated with changes in waist circumference (p = 0.03-0.02), whereas delta SQs were positively (p = 0.04) and negatively (p = 0.02) associated with delta fat mass between years 1 and 5, and years 4 and 5, respectively.These results suggest that variations in SQ across the menopausal transition are related to energy and macronutrient intakes and coincide with changes in body composition and waist circumference.

Aim The purpose of this study was to determine an optimal cut-off point of skeletal muscle mass, using appendicular lean body mass (LBM) index, that identifies at risk individuals with deteriorated insulin sensitivity, using an established quantitative insulin sensitivity index ( QUICKI ) cut-off. Methods We performed a cross-sectional analysis in 231 lean and obese (BMI: 18.7–51.0kg/m 2 ) menopausal women. Fasting plasma glucose and insulin were obtained to calculate QUICKI as an index of insulin sensitivity. Skeletal muscle mass was measured as appendicular LBM by DXA and expressed as appendicular LBM index [appendicular LBM (kg)/height (m 2 )]. Cut-offs were determined using receiver operating characteristic (ROC) curve analyses. Results The best cut-off value for skeletal muscle mass index to identify menopausal women with reduced insulin sensitivity was 7.025kg/m 2 which had a sensitivity of 69.5% and specificity of 58.2%. Conclusion Our results suggest that sedentary postmenopausal women with an appendicular skeletal muscle mass index above 7.025kg/m 2 may be at greater risk of insulin resistance. Prospective studies are needed to validate our result.

Objective The purpose of this study was to investigate changes in dietary intake and appetite across the menopausal transition. Methods This was a 5-year observational, longitudinal study on the menopausal transition. The study included 94 premenopausal women at baseline (age: 49.9 ± 1.9 yrs; BMI: 23.3 ± 2.3 kg/m2). Body composition (DXA), appetite (visual analogue scale), eating frequency, energy intake (EI) and macronutrient composition (7-day food diary and buffet-type meal) were measured annually. Results Repeated-measures analyses revealed that total EI and carbohydrate intake from food diary decreased significantly over time in women who became postmenopausal by year 5 (P > 0.05) compared to women in the menopausal transition. In women who became postmenopausal by year 5, fat and protein intakes decreased across the menopausal transition (0.05 > P < 0.01). Although a decrease in % fat intake was observed during the menopausal transition (P < 0.05), this variable was significantly increased in the postmenopausal years (P < 0.05). Spontaneous EI and protein intake also declined over time and were higher in the years preceding menopause onset (P < 0.05). Desire to eat, hunger and prospective food consumption increased during the menopausal transition and remained at this higher level in the postmenopausal years (0.05 > P< 0.001). Fasting fullness decreased across the menopausal transition (P < 0.05). Conclusion These results suggest that menopausal transition is accompanied with a decrease in food intake and an increase in appetite.

Objectives Factors that influence weight gain during the menopausal transition are not fully understood. The purpose of this study was to investigate changes in energy expenditure (EE) across the menopausal transition. Methods One hundred and two premenopausal women (age: 49.9 ± 1.9 yrs; BMI: 23.3 ± 2.2 kg/m2) were followed for 5 years. Body composition (DXA), physical activity EE (accelerometer), resting EE and thermic effect of food (indirect calorimetry) were measured annually. Results Total EE decreased significantly over time in postmenopausal women (P < 0.05), which was mostly due to a decrease in physical activity EE (P < 0.05). Although average resting EE remained stable over time in postmenopausal women, a significant increase, over the 5-year period, was noted in women who were in the menopausal transition by year 5 (P < 0.05). Finally, the time spent in moderate physical activity decreased and the time spent in sedentary physical activity increased during the menopausal transition (P < 0.05). Conclusion These results suggest that menopausal transition is accompanied with a decline in EE mainly characterized by a decrease in physical activity EE and a shift to a more sedentary lifestyle.

Conflicting results have been reported concerning the prevalence of cardiometabolic risk factors in women experiencing vasomotor symptoms (VMS).To compare cardiometabolic risk factors between women with and without VMS during the menopause transition and to determine the influence of physical activity on the prevalence of VMS.Yearly assessment of women transitioning through menopause included self-reported VMS (hot flushes and night sweats), body composition and fat distribution, fasting glucose, insulin and lipids, and physical activity levels.Eighty-five of the 102 premenopausal women at baseline were included (age: 49.9 ± 2.0 years; body mass index: 23.2 ± 2.2 kg/m(2)). According to linear mixed model analyses, no statistically significant differences were observed for fat mass, lean body mass, body fat distribution indices and cardiometabolic risk factors, when comparing symptomatic vs. asymptomatic women. Neither physical activity levels nor intensity were associated with the prevalence of VMS.Our results suggest that women transitioning through menopause who reported VMS did not show greater deteriorations in body composition, body fat distribution and cardiometabolic risk factors. Furthermore, physical activity levels were not associated with lower prevalence of vasomotor symptoms in the present cohort.

The objective of this study was to compare changes in body composition and the metabolic profile between women taking an intermittent diet (ID) and women taking a continuous diet (CD).Twenty-five obese postmenopausal women were randomized to an ID (n = 13) or a CD (n = 12). In the ID, 5-week energy restriction periods were followed by 5-week weight stabilization periods. In the CD, 15 weeks of energy restriction was followed by 5 weeks of weight stabilization. Outcome measures before, during, and after weight loss, as well as after a 1-year follow-up, were body weight and composition, waist circumference, resting metabolic rate, and fasting lipid and glucose levels.Body weight, waist circumference, percentage fat mass, and fat mass decreased significantly and similarly in both groups (P0.0001). Both groups showed similar overall decreases in plasma total cholesterol and triglycerides (all P0.05). Low-density lipoprotein cholesterol improved significantly in the CD group only, whereas fasting glucose decreased significantly in the ID group only. High-density lipoprotein cholesterol and resting metabolic rate remained stable in both groups. Fasting plasma triglyceride and glucose levels were the only metabolic variables to further improve after the fifth week of the protocol. At the 1-year follow-up, both interventions were associated with successful and similar weight loss maintenance and improvements in fasting plasma glucose levels.The ID resulted in similar short- and long-term changes in body composition and metabolic profile compared with a CD. Most improvements occurred during the first 5 weeks of treatment in both interventions.

Objective: Cardiovascular disease is the first cause of mortality in women in North America. The risk of car-diovascular disease increases sharply after middle age in women, especially after menopause. The aim was toinvestigate changes in body composition and cardiometabolic profile throughout the menopausal transition.Methods: This was a 5-year observational, longitudinal study on the menopausal transition. The study included102 premenopausal women at baseline (age, 49.9 T1.9 y; body mass index, 23.3 T2.2 kg/m 2 ). Outcome measuresinclude menopause status, body composition by dual-energy x-ray absorptiometry (total fat mass [FM], trunk FM,and total fat-free mass), waist circumference, visceral and abdominal subcutaneous fat, fasting glucose and insulinlevels, homeostasis model assessment of insulin resistance, plasma lipid levels (triglycerides, total cholesterol, andhigh- and low-density lipoprotein cholesterol), and resting blood pressure.Results: Repeated-measure analyses revealed significant increases for FM, percentage FM, trunk FM, visceralfat, plasma fasting glucose, and high-density lipoprotein cholesterol (0.05 9P G0.01) and a significant decrease forplasma glucose levels after follow-up. Those who were in perimenopause or postmenopause by year 3 of the studyshowed a significant increase in visceral fat (P G0.01) compared with baseline. Despite some significant changes inthe metabolic profile among the menopause statuses, the women did not show any cardiometabolic deterioration bythe end of the study.Conclusions: Our results suggest that changes in body composition and fat distribution can occur in nonobesewomen as they go through the menopausal transition. However, these changes were not accompanied by car-diometabolic deteriorations in the present study.Key Words: Menopause YBody composition YCardiometabolic risk factors YVisceral fat.

Metabolic is a heterogeneous concept that includes five elements, each of which has individual thresholds that might be different when considered as a criterion in the metabolic syndrome. Therefore, some individuals might present different levels of metabolic syndrome. This study aims to identify two different severities of patients with metabolic syndrome-moderate versus severe-and the respective association of these severities with lifestyle habits and physical capacity.The sample included 2,281 adults aged between 19 and 85 years from the National Health and Nutrition Examination Survey (NHANES) study. Subjects were subcategorized into three groups: No metabolic syndrome, moderate metabolic syndrome, or severe metabolic syndrome. Physical activity and dietary habits were assessed by questionnaires. Cardiorespiratory fitness (CRF) was measured in adults aged50 years, whereas physical capacity was measured in adults ≥50 years of age.Thirty-eight percent of subjects had metabolic syndrome. From those, 15.3% had severe metabolic syndrome. No difference was observed among groups for energy intake. Subjects aged50 years having severe metabolic syndrome had a lower CRF compared with moderate metabolic syndrome, whereas subjects ≥50 years reported less vigorous exercise (P≤0.05). Finally, subjects aged ≥50 years old having severe metabolic syndrome reported more physical incapacity compared to the other groups.This study confirms that metabolic syndrome is a heterogeneous condition that may be subclassified. Severe metabolic syndrome is associated with lower physical capacity and CRF compared to moderate metabolic syndrome. Studies are needed to determine if metabolic syndrome categorization can be useful for clinical practice.

Healthy diet and physical activity are associated with a lower cardiometabolic risk (CMR). Little is known about whether they interact to improve CMR. The purpose of the present study was to determine the synergistic associations of diet quality and physical activity energy expenditure (PAEE) on CMR factors. The present study was ana posteriorianalysis of two cross-sectional studies on 124 inactive non-diabetic postmenopausal women with a BMI ≥ 27 kg/m2. The following factors were measured: diet quality (assessed by the Canadian Healthy Eating Index (C-HEI) from a 3 d food record); PAEE (doubly labelled water); body composition (dual-energy X-ray absorptiometry, computed tomography scan); lipoprotein profile (total, HDL- and LDL-cholesterol (HDL-C and LDL-C), non-HDL-C, total cholesterol:HDL-C, TAG, apoA1, apoB, apoA1:apoB and LDL-C:apoB); insulin sensitivity (homeostasis model assessment of insulin resistance and hyperinsulinaemic–euglycaemic clamp); inflammatory markers (high-sensitivity C-reactive protein (hs-CRP), haptoglobin, orosomucoid, IL-6 and leucocyte count). The association of the interaction PAEE × C-HEI and CMR factors was evaluated by hierarchical regressions. Fat mass-adjusted ANCOVA determined the interaction between PAEE and the C-HEI. In hierarchical regressions, the interaction PAEE × C-HEI was a correlate of more favourable values of HDL-C, apoB, apoA1:apoB and LDL-C:apoB ratios, and hs-CRP, while only PAEE was a negative correlate of haptoglobin. Compared with those in the low-PAEE/low-C-HEI group, women in the high-PAEE/high-C-HEI group had 10 % higher HDL-C, 13 % lower apoB, 11 % larger LDL particles and 28 % lower hs-CRP concentrations (P

The purpose of this study was to investigate the relationship between visceral adipose tissue (VAT), estimated with the Bertin index obtained from dual-energy X-ray absorptiometry (DXA), with cardiometabolic risk factors before and after a weight loss program and compare it with VAT measured with computed tomography (CT) scan. The study population for this analysis included 92 nondiabetic overweight and obese sedentary postmenopausal women (age: 58.1 ± 4.7 years, BMI: 31.8 ± 4.2 kg/m(2)) participating in a weight loss intervention that consisted of a caloric restricted diet with and without resistance training (RT). We measured (i) VAT using CT scan, (ii) body composition (using DXA) from which the Bertin index was calculated, (iii) cardiometabolic risk factors such as insulin sensitivity (using the hyperinsulinenic-euglycemic clamp technique), peak oxygen consumption, blood pressure, plasma lipids, C-reactive protein as well as fasting glucose and insulin. VAT levels for both methods significantly decreased after the weight loss intervention. Furthermore, no differences in VAT levels between both methods were observed before (88.0 ± 25.5 vs. 83.8 ± 22.0 cm(2)) and after (76.8 ± 27.8 vs. 73.6 ± 23.2 cm(2)) the weight loss intervention. In addition, the percent change in VAT levels after the weight loss intervention was similar between both methods (-13.0 ± 16.5 vs. -12.5 ± 12.6%). Moreover, similar relationships were observed between both measures of VAT with cardiometabolic risk factors before and after the weight loss intervention. Finally, results from the logistic regression analysis consistently showed that fat mass and lean body mass were independent predictors of pre- and post-VAT levels for both methods in our cohort. In conclusion, estimated visceral fat levels using the Bertin index may be able to trace variations of VAT after weight loss. This index also shows comparable relationships with cardiometabolic risk factors when compared to VAT measured using CT scan.

In postmenopause, ovarian decline along with sedentary lifestyle could contribute to the loss of lean body mass (LBM) and muscle strength. This study aimed to verify whether exercise and isoflavones could have additive effects on muscle quality, muscle mass index, relative strength and physical capacity in overweight sedentary postmenopausal women.We recruited 70 overweight-to-obese (body mass index 32.2±4.8 kg/m(2)) postmenopausal women (59±5 years old) to participate in a 6-month clinical study combining isoflavones (70 mg/day) and exercise (resistance and aerobic training) treatments. Subjects were divided into four groups: (1) placebo (n =15), (2) isoflavones (n =15), (3) exercise and placebo (n =20), and (4) exercise and isoflavone (n =20). Principal outcome variables included maximal muscle strength (1RM) at the leg press and the bench press, muscle mass index, muscle quality in the legs and relative strength.After 6 months of training, exercise produced 49% and 23% increases, respectively, in leg press and bench press 1RM (p ≤0.01). Leg relative strength and muscle quality increased by more than 50% (both p0.01), while muscle mass index increased by 7% (p0.05) in both exercise groups only.Exercise training can improve muscle tissue strength, function and quality in sedentary postmenopausal women. Isoflavones, irrespective of exercise, did not produce changes in these variables. From a clinical perspective, these results suggest that overweight women could reduce the risks of mobility impairments, even in the absence of weight loss, by following a sound exercise intervention that includes both resistance and aerobic training at a high intensity.

M Sénéchal1,2, H Arguin6, DR Bouchard4,5, AC Carpentier3, JL Ardilouze3, IJ Dionne1,2, M Brochu1,21Research Centre on Aging, Health and Social Services Centre, University Institute of Geriatrics of Sherbrooke, 2Faculty of Physical Education and Sports, University of Sherbrooke, 3Clinical Research Centre, Sherbrooke University Hospital Centre, Sherbrooke, QC; 4Faculty of Kinesiology and Recreation Management, University of Manitoba, Winnipeg, MB; 5Health, Leisure & Human Performance Research Institute, Winnipeg, MB; 6Division of Kinesiology, Department of Social and Preventive Medicine, Faculty of Medicine, Laval University, QC, CanadaObjective: To examine the association between weight gain since menopause and weight regain after a weight loss program.Methods: Participants were 19 obese women who participated in a 15-week weight loss program and a 12-month follow-up. Main outcomes were: body composition, resting metabolic rate, energy intake, energy expenditure, and weight regain at follow-up.Results: All body composition measures significantly decreased after intervention (all P ≤ 0.01) while all measures of fatness increased significantly after the 12-month follow-up (P ≤ 0.01). Body weight gain since menopause was associated with body weight regain (r = 0.65; P = 0.003) after follow-up even after adjustment for confounders.Conclusion: Weight gain since menopause is associated with body weight regain following the weight loss program. Therefore, weight gain since menopause should be considered as a factor influencing weight loss maintenance in older women.Keywords: obesity, body weight, weight regain, postmenopausal women, aging

Obesity and the metabolic syndrome are significant determinants of functional capacity in women. In the past decade, the term "metabolically healthy obese" (MHO) emerged in the literature to identify a distinct category of obese individuals presenting less metabolic impairment than expected. However, MHO women might have similar risk than non-MHO women for nonmetabolic weight-related co-morbidities, including altered functional capacity.Eighty six obese women aged from 28 to 74 years old were studied. MHO was defined as a body mass index (BMI) ≥30.0 kg/m(2) with less than one metabolic syndrome criteria based on the Adult Treatment Panel III (ATP III) definition. Walking distance (m) and walking speed (m/sec), evaluated by the 6-min walk test, were used as indicators of functional capacity.Twenty one percent of the sample was considered MHO. Age, BMI, physical activity level, and diastolic blood pressure were not significantly different between MHO and non-MHO women. MHO women performed better on the 6-min walk test (519.8 m±68.2 vs. 448.4 m±67.1; P≤0.01) compared to non-MHO women. Moreover, in multiple regression analyses, MHO status and BMI were significantly associated with walking speed after adjustment for age, physical activity level, the total number of chronic conditions, and arthritis/osteoarthritis.Our results show that MHO women have a better functional capacity than non-MHO women, and therefore could be at lower risk for future disability. However, weight management remains important because BMI was also an independent predictor of functional capacity regardless of metabolic profile.

It is established that a high level of fat mass (FM) is related to mobility impairment in older adults. However, FM distribution has received very little attention. In this study, 904 well-functioning older adults aged between 68 and 82 years old were recruited to examine the association between waist circumference, trunk FM, leg FM, and mobility. The results show that waist circumference was the only measure of body fat distribution independently associated with mobility (p ≤ .001). Therefore, the use of objective measures of FM distribution may not be necessary to examine the impact of FM distribution on mobility.

Acute hyperinsulinemia reduces total and high molecular weight (HMW) adiponectin levels in humans. Whether an increase in insulin sensitivity (IS) is accompanied by a greater suppressive effect of hyperinsulinemia on adiponectin levels is unknown, however. To clarify the inhibitory role of insulin on adiponectin, total and HMW adiponectin levels were measured during acute hyperinsulinemia before and after an improvement in insulin sensitivity in response to weight loss. Forty-six overweight and obese postmenopausal women were randomized to either 6-month caloric restriction (CR) alone (n = 22), or CR with resistance training (CR+RT, n = 24). IS (hyperinsulinemic-euglycemic clamp) was assessed before and after weight loss. Total and HMW adiponectin levels were measured by ELISA at baseline, 90, 160, and 180 min of each clamp. Relative mean body weight loss was -8.0% ± 4.4% for both groups (CR: -7.7% ± 3.8%; CR+RT: -8.2% ± 5.0%). IS increased significantly, by 18.4% ± 25.3% (CR: 19.3% ± 29.7%; CR+RT: 17.7% ± 21.0%). Before each intervention, total and HMW adiponectin levels in both groups significantly decreased in response to hyperinsulinemia (total: -8.4% ± 19.4%; HMW: -3.2% ± 13.2%). Despite the improvement in IS seen after each intervention, a similar pattern of reduction to that before weight loss was observed in total and HMW adiponectin levels during hyperinsulinemia. These results establish that total and HMW adiponectin levels decline during a hyperinsulinemic-euglycemic clamp. Also, the insulin-sensitizing effect of weight loss via caloric restriction alone or with resistance training does not amplify the reduction in adiponectin levels observed during hyperinsulinemia in healthy postmenopausal women.

Background: Obesity in older adults results from several interacting factors. Consequently, interventions have shown mitigated effects. Objectives: We determined 1) the different subgroups of obese elderly based on clusters of associated comorbidities and 2) the trajectory of these clusters to assess their stability over 3 years and factors contributing to transitions. Methods: Obese men (n=193; BMI= 33.15 ± 2.69 kg/m2) and women (n=220; BMI= 33.71 ± 3.71 kg/m2) aged between 68 and 82 years were studied. Outcome variables were: body composition, strength, physical capacity, nutrition, psychological and physical health and social participation. Cluster analyses, stratified by sex, were used to identify obesity profiles at baseline and follow-up. Results: Three profiles were identified, based on general health (GH), psychological health (PH) and physical capacity (PC). Cluster 1: healthy obese (GH+, PH+, PC+); Custer 2: obese with low physical capacity (GH+/-, PH+/-, PC-); Cluster 3: unhealthy obese (GH-, PH-, PC-). After 3-years, 61% and 62% of men and women remained in their initial cluster, compared to 20.4% and 12.0% who transitioned toward a worse health Cluster and 18.3% and 14.2% who transitioned toward a more favorable cluster, partly explained by changes in physical health for men and physical and psychological health for women. Conclusion: The results of this study show that targeting physical capacity in men and physical and psychological health status in women could prevent further health decline in obese elderly. Further studies are needed to investigate the role of these clusters in the prediction of cardiometabolic complications and mortality.

The purpose of this study was to compare different methods to identify metabolically healthy but obese (MHO) individuals in a cohort of obese postmenopausal women. We examined the anthropometric and metabolic characteristics of 113 obese (age: 57.3 +/- 4.8 years; BMI: 34.2 +/- 2.7 kg/m(2)), sedentary postmenopausal women. The following methods were used to identify MHO subjects: the hyperinsulinemic-euglycemic clamp (MHO: upper quartile of glucose disposal rates); the Matsuda index (MHO: upper quartile of the Matsuda index); the homeostasis model assessment (HOMA) index (MHO: lower quartile of the HOMA index); having 0-1 cardiometabolic abnormalities (systolic/diastolic blood pressureor =130/85 mm Hg, triglycerides (TG)or =1.7 mmol/l, glucoseor =5.6 mmol/l, HOMA5.13, high-sensitive C-reactive protein (hsCRP)0.1 mg/l, high-density lipoprotein-cholesterol (HDL-C)1.3 mmol/l); and meeting four out of five metabolic factors (HOMAor =2.7, TGor =1.7 mmol/l, HDL-Cor =1.3 mmol/l, low-density lipoprotein-cholesterolor =2.6 mmol/l, hsCRPor =3.0 mg/l). Thereafter, we measured insulin sensitivity, body composition (dual-energy X-ray absorptiometry), body fat distribution (computed tomography scan), energy expenditure, plasma lipids, inflammation markers, resting blood pressure, and cardiorespiratory fitness. We found significant differences in body composition (i.e., peripheral fat mass, central lean body mass (LBM)) and metabolic risk factors (i.e., HDL-C, hsCRP) between MHO and at risk individuals using the different methods to identify both groups. In addition, significant differences between MHO subjects using the different methods to identify MHO individuals were observed such as age, TG/HDL, hsCRP, and fasting insulin. However, independently of the methods used, we noted some recurrent characteristics that identify MHO subjects such as TG, apolipoprotein B, and ferritin. In conclusion, the present study shows variations in body composition and metabolic profile based on the methods studied to define the MHO phenotype. Therefore, an expert consensus may be needed to standardize the identification of MHO individuals.