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.

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.

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.

Importance of tangible physical changes for quality of life improvements of type 2 diabetic and at-risk individuals involved in exercise intervention A quasi-experimental design.

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.

Synergistic associations of physical activity and diet quality on cardiometabolic risk factors in overweight and obese postmenopausal women.

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 an a posteriori analysis 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< 0·05). PAEE and the C-HEI have a synergistic association with the CMR profile. These results support the integration of both diet quality and physical activity in the management of CMR.

The TaqIA RFLP is associated with attenuated intervention-induced body weight loss and increased carbohydrate intake in post-menopausal obese women.

INTRODUCTION: Polymorphisms of the dopamine receptor D2 (DRD2) gene have been associated with obesity phenotypes. Our aim was to examine if the genotype of TaqIA Restriction Fragment Length Polymorphism (RFPL) was related to an attenuated weight loss response or to changes in energy expenditure (EE) and food preference before and after weight loss. methods: Obese post-menopausal women (age=57.1 ± 4.6 yr, weight=85.4 ± 15.4 kg and BMI=32.8 ± 4.5 kg/m(2)) were genotyped for TaqIA (n=127) by using PCR-RFLP analysis and categorized as possessing at least one copy of the A1 allele (A1(+)) or no copy (A1(-)). Women were randomized into two groups, caloric restriction (CR) and caloric restriction+resistance training (CRRT) and in this study were further classified as follows: A1(+)CR, A1(+)CRRT, A1-(-)CR and (-)A1(-)CRRT. Body composition, total daily EE, physical activity EE, Resting EE (REE), and energy intake were obtained at baseline and post-intervention using DXA, doubly-labeled water, indirect calorimetry, and 3-day dietary records, respectively. RESULTS: Overall, all of the anthropometric variables and REE significantly decreased post-intervention (p<0.001). Women in the CRRT group lost significantly more fat mass (FM) than the CR women (p<0.05). There were significant time by group by allele interactions for attenuated body weight (BW), BMI, and FM loss for A1(+) (vs. A1(-)) in CRRT (p<0.05) and for increased % carbohydrate intake (p<0.01). CONCLUSION: TaqIA genotype was associated with body weight loss post-intervention; more specifically, carriers of the A1 allele lost significantly less BW and FM than the A1(-) and had increased carbohydrate intake in the CRRT group.

[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.

Effects of rapid or slow weight loss on body composition and metabolic risk factors in obese postmenopausal women. A pilot study.

To compare the effect of rapid or slow weight loss (WL) on body composition and metabolic risk factors following a caloric restriction. Ten obese, postmenopausal women were matched for total body WL. Dependent variables were: body composition, lipid profile and blood pressure. Both groups decreased obesity measures (all P≤0.05) while lean body mass decreased in the rapid WL group (P≤0.05). Significant improvements in fasting triglyceride level and diastolic blood pressure were observed only in the slow WL group. A slower WL seems to be more beneficial to improve body composition as well as metabolic risk factors in postmenopausal women.

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.

Is fat mass distribution related to impaired mobility in older men and women? Nutrition as a determinant of successful aging: the Quebec longitudinal study.

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.

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.

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.

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.

Effects of the addition of a resistance training programme to a caloric restriction weight loss intervention on psychosocial factors in overweight and obese post-menopausal women: a Montreal Ottawa New Emerging Team study.

The aim of this study was to examine the effects of the addition of a resistance training programme to a caloric restriction weight loss intervention on psychosocial profile. The study sample consisted of 137 overweight and obese post-menopausal women. Participants were randomized to a caloric restriction group and caloric restriction + resistance training group. Psychosocial, anthropometric, and metabolic variables were measured before and after the 6-month weight loss intervention. Both groups presented similar weight loss and there were no significant differences between the caloric restriction group and caloric restriction + resistance training group for changes in psychosocial profile. Thereafter, all participants were classified into quintiles based on the amount of weight loss. In all quintiles, women markedly improved body esteem and self-esteem, and decreased hunger and perceived risk for diabetes mellitus (P < 0.05). However, significant increases in dietary restraint were observed in quintiles 2-5 (> or =2.4 % body weight loss), decreases in disinhibition in quintiles 3-5 (> or =4.9 %), increases in self-efficacy in quintiles 3-5 (> or =4.9 %), and increases in health perceptions in quintile 5 (> or =11.1%). The results of this study do not support the hypothesis that the addition of a resistance training programme to a caloric restriction weight loss intervention has additional benefits on psychosocial profile. Overall, the significant improvements in the psychosocial profile observed were mostly accounted for by the degree of weight loss.

Changes in objective and self-reported measures of physical capacity after an intervention in obese older women.

The aim of this study was to determine if objective and self-reported measures of physical capacity are two equivalent methods to detect changes following an intervention in obese older women. 36 obese women aged between 55 and 75 years participated in a 3-month study with the aim of improving physical capacity by caloric restriction and/or resistance training. Physical capacity was measured objectively with 10 different tests and self-reported with the SF-36 physical functioning score (SF-36 PF score). Then the performance-to-objective tests were computed using quartiles to provide a baseline global physical capacity score. The mean percentage of change of the 10 tests as well as the SF-36 PF score were also calculated after the study. Body composition was measured by dual-energy X-ray (DXA) absorptiometry. The baseline global physical capacity score and the SF-36 PF score were significantly correlated at baseline (r = 0.43; P < 0.01). Eight out of the 10 objective tests of physical capacity improved after the intervention, while no improvement was observed for the SF-36 PF score. On average, percentage of change in physical capacity was 4.1 +/- 5.9% for the SF-36 PF score and 11.1 +/- 2.9% for the objective measures. However, no significant correlation was observed between percentage of changes between the two approaches after the intervention (r = 0.32; P = 0.07). Based on these results, the method used to quantify physical capacity after an intervention may have major implications on the outcomes. The methods used should be carefully analyzed in regard to the objective of the study.

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.

Effect of physical exertion on the biological monitoring of exposure to various solvents following exposure by inhalation in human volunteers: III. Styrene.

This study evaluated the impact of different work load intensities on biological indicators of styrene exposure. Four adult Caucasian men, aged 20 to 44 years, were recruited. Groups of 2-4 volunteers were exposed to 20 ppm of styrene in an exposure chamber according to scenarios involving either aerobic, muscular, or both types of physical exercise for 3 or 7 hr. The target intensities for each 30-min exercise period-interspaced with 15 min at rest-were the following: REST, 38 watts AERO (time-weighted average intensity), 34 watts AERO/MUSC, 49 watts AERO/MUSC, and 54 watts AERO for 7 hr and 22 watts MUSC for 3 hr. End-exhaled air samples were collected at 15 time points during and after 7-hr exposures for the determination of styrene concentrations. Urine samples were collected before the start of exposure, after the first 3 hr of exposure, and at the end of exposure for the determination of mandelic acid (MA) and phenylglyoxilic acid (PGA) concentrations. Compared with exposure at rest, styrene in alveolar air increased by a factor up to 1.7, while the sum of urinary MA and PGA increased by a factor ranging from 1.2 to 3.5, depending on the exposure scenario. Concentrations of biological indicators of styrene fluctuated with physical exertion and were correlated with the magnitude of the physical activity and pulmonary ventilation. Despite the physical exertion effect, urinary concentrations of styrene metabolites after a single-day exposure remain below the current biological exposure index value recommended by ACGIH; therefore, no additional health risk is expected. However, results shows that work load intensities must be considered in the interpretation of biological monitoring data and in the evaluation of the health risk associated with styrene exposure.