[La mise en abyme d'un projet intergénérationnel de recherche: Un comité intergénérationnel comme processus et sujet de recherche].

Les projets de nature intergénérationnelle sont aujourd'hui hautement valorisés par les décideurs publics et les responsables académiques. La pandémie de COVID-19 a fait ressurgir l'importance des relations entre les générations et des projets intergénérationnels ancrés dans la communauté. Cet article présente les résultats d'une étude visant à faire travailler ensemble des personnes aînées et des jeunes adultes au sein d'un projet intergénérationnel ancré dans la communauté. La particularité dans cette étude c'est qu'elle utilise une démarche méthodologique co-constructive, c'est-à-dire qu'elle jumelle des chercheurs et des chercheures académiques de différents horizons et des personnes aînées citoyennes tout au long du processus de recherche. Les résultats portent particulièrement sur les attentes des personnes participantes au projet intergénérationnel, la description du déroulement du projet (sur une période de dix mois) et les perceptions des relations intergénérationnelles au cours du projet. Nous terminons l'article par une discussion autour des constats centraux de notre étude et de notre expérience dans le cadre d'une recherche co-constructive.

Increased odds of having the metabolic syndrome with greater fat-free mass: counterintuitive results from the National Health and Nutrition Examination Survey database.

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.

Exercising for Insulin Sensitivity - Is There a Mechanistic Relationship With Quantitative Changes in Skeletal Muscle Mass?

Skeletal muscle (SM) tissue has been repetitively shown to play a major role in whole-body glucose homeostasis and overall metabolic health. Hence, SM hypertrophy through resistance training (RT) has been suggested to be favorable to glucose homeostasis in different populations, from young healthy to type 2 diabetic (T2D) individuals. While RT has been shown to contribute to improved metabolic health, including insulin sensitivity surrogates, in multiple studies, a universal understanding of a mechanistic explanation is currently lacking. Furthermore, exercised-improved glucose homeostasis and quantitative changes of SM mass have been hypothesized to be concurrent but not necessarily causally associated. With a straightforward focus on exercise interventions, this narrative review aims to highlight the current level of evidence of the impact of SM hypertrophy on glucose homeostasis, as well various mechanisms that are likely to explain those effects. These mechanistic insights could provide a strengthened rationale for future research assessing alternative RT strategies to the current classical modalities, such as low-load, high repetition RT or high-volume circuit-style RT, in metabolically impaired populations.

Obesity among postmenopausal women: what is the best anthropometric index to assess adiposity and success of weight-loss intervention?

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 ±â€Š5.3 y; BF%: 43.4 ±â€Š5.3) 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.

Physical activity energy expenditure and fat-free mass: relationship with metabolic syndrome in overweight or obese postmenopausal women.

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 (<10%). Cross-sectional data of 126 participants were divided into quartiles based on PAEE (Quartile (Q)1 = lowest PAEE) while fat-free mass (FFM) and fat mass were measured by dual-energy X-ray absorptiometry. MetS prevalence was significantly different between Q1 and Q4 (37.9% vs 13.3%, p = 0.03). After controlling for potential confounders, MetS severity was negatively associated with PAEE (B = -0.057, p < 0.01) and positively with FFM (B = 0.038, p < 0.001). Moderation analyses indicated that a greater FFM exacerbated the association between PAEE and MetS severity in Q1 and Q2 (PAEE × FFM; B = -0.004; p = 0.1). Our results suggest that displaying a low FRS and lower PAEE increase MetS prevalence and severity. In addition, greater FFM interacts with lower PAEE to worsens MetS severity, while higher PAEE lessened this effect. 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 counterintuitive perspective for the role of fat-free mass in metabolic health.

Fat-free mass (FFM) has long been recognized to play a role in metabolic homeostasis. Over the years, it has become widely accepted by the scientific and general community alike that having a greater FFM can be protective for metabolic health. Hence, in the context of an aging population concurrently facing sarcopenia and an elevated incidence of metabolic diseases, substantial efforts are being made to study and develop interventions aiming to maintain or increase FFM. However, accumulating evidence now suggests that a large FFM may be deleterious to metabolic health, at least in some populations. The objective of this article is thus to raise awareness surrounding these results and to explore possible explanations and mechanisms underlying this counterintuitive association.

Differential clusters of modifiable risk factors for impaired fasting glucose versus impaired glucose tolerance in adults 50 years of age and older.

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.

Low-Volume High-Intensity Interval Training (HIIT) versus Moderate-Intensity Continuous Training on Body Composition, Cardiometabolic Profile and Physical Capacity in Older Women.

OBJECTIVES: To compare the effect of low-volume HIIT to moderate-intensity aerobic 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, VO2peak) were assessed before and after the intervention. Feasibility was evaluated with completion rate (training compliance; dropout rate) and affective response (Feeling scale; pre- and post-exercise). RESULTS: Total cholesterol, non-HDL-C levels and the Framingham risk score decreased in both groups (all p≤0.03). Although VO2peak remained unchanged, the 6MWT distance increased (p<0.0001), irrespective of the group. Completion rate and affective responses were not different between groups (all p≥0.38). CONCLUSION: A short-term HIIT program is feasible and provides as much benefits as MICT in older women.

Prevalence of the metabolic syndrome between 1999 and 2014 in the United States adult population and the impact of the 2007-2008 recession: an NHANES study.

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.

Profiling obesity phenotypes and trajectories in older adults of the Quebec NuAge cohort on nutrition and successful aging: A cluster analysis.

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.

Fat-free mass and glucose homeostasis: is greater fat-free mass an independent predictor of insulin resistance?

BACKGROUND: 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. OBJECTIVES: (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. METHODS: 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). RESULTS: aFFMI was an independent predictor of IR in younger (men: ß = 0.21; women: ß = 0.31; all p ≤ 0.001) and older (men: ß = 0.11; women: ß = 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. CONCLUSION: 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.

Should Waist Circumference Cutoffs in the Context of Cardiometabolic Risk Factor Assessment be Specific to Sex, Age, and BMI?

OBJECTIVE: 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. METHODS: 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. RESULTS: When age and BMI categories were considered in the identification of optimal WC thresholds, sensitivity to correctly identify at-risk individuals significantly improved. CONCLUSIONS: 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 one-year resistance training program following weight loss has no significant impact on body composition and energy expenditure in postmenopausal women living with overweight and obesity.

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% ±â€¯5.8; 5.05 kg ±â€¯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.

Body composition, cardiometabolic risk factors, physical activity, and inflammatory markers in premenopausal women after a 10-year follow-up: a MONET study.

OBJECTIVE: 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. METHODS: 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 ±â€Š1.7 years; body mass index: 23.2 ±â€Š2.2 kg/m) 6.0 ±â€Š0.3 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. RESULTS: 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. CONCLUSION: 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.

Effects of a 6-month caloric restriction induced-weight loss program in obese postmenopausal women with and without the metabolic syndrome: a MONET study.

OBJECTIVE: 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). METHODS: Secondary analyses were performed on 73 inactive obese postmenopausal women (age 57.7 ±â€Š4.8 years; body mass index 32.4 ±â€Š4.6 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. RESULTS: 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. CONCLUSIONS: 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.

Energy Density is Not a Consistent Correlate of Adiposity in Women During the Menopausal Transition.

PURPOSE: 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. METHODS: 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. RESULTS: 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. CONCLUSION: These results suggest that ED is a modest but inconsistent determinant of adiposity in healthy women at the time of the menopause transition.

Inflammation and Fat Mass as Determinants of Changes in Physical Capacity and Mobility in Older Adults Displaying A Large Variability in Body Composition: The NuAge Study.

Background/Study context: Determining whether C-reactive protein (CRP), blood lipids, total and trunk fat mass (FM), and waist circumference (WC) are associated with changes in physical capacity over 3 years (Δ) in elderly. METHODS: One hundred twenty-two men and women 68-83 years of age participated in a 3-year follow-up study. Physical capacity was measured using five objective tests: (1) Timed Up and Go (TUG), (2) chair stand (CS), (3) normal walking speed (NWS), (4) fast walking speed (FWS), and (5) one-leg stand (LS), along with physical performance score (PPS) at baseline (T1) and 3 years later (T4). Total and trunk FM, WC, blood lipids, and CRP measured at baseline, were considered as potential predictors. RESULTS: At baseline, CRP and total FM were significantly correlated with all physical capacity tests, whereas trunk FM was correlated with CS and LS, and blood lipids only with FSW. No significant correlation was observed for WC. Total and trunk FM measured at baseline were correlated with ΔTUG and ΔPPS, whereas trunk FM and WC measured at baseline were correlated with ΔNWS. CRP and blood lipids, measured at baseline, were not associated with any changes over 3 years. At the end, WC measured at baseline was the strongest independent predictor for all physical capacity measures at baseline (T1), and ΔPPS measured over 3 years could be predicted by baseline WC. CONCLUSION: FM distribution seems more useful to determine physical capacity than inflammation. Interestingly, over a short follow-up of 3 years, WC significantly predicted changes in a composite score of physical activity. More studies are needed to elucidate factors that may influence physical capacity decline over time.

Influence of cardiorespiratory fitness and physical activity levels on cardiometabolic risk factors during menopause transition: A MONET study.

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 < 30.0 mlO2 kg(- 1) min(- 1) (P < 0.05). However, only fasting triglycerides was lower in women with physical activity levels ≥ 770.0 Kcal/day (P < 0.05). Between fitness and physical activity levels, fitness was associated with more favorable values of cardiometabolic risk factors in women followed for 5 years during the menopause transition.