Current issues in the identification and treatment of metabolically healthy but obese individuals.

A unique subset of obese individuals who appear to be protected from the development of metabolic disturbances has been identified in the medical literature and is termed metabolically healthy but obese (MHO). Part of the issue is that there are no clear accepted criteria on the definition of MHO and the biological mechanisms to explain this phenotype are still unknown which render findings and/or conclusions difficult to interpret and making the application of this concept difficult in clinical practice. With the current definitions, the true prevalence of the MHO phenotype in the general population varies widely from approximately 3-57% of obese adults. In several prospective studies, the MHO individual has been associated with a similar risk of developing type 2 diabetes, cardiovascular disease and mortality when compared to healthy normal weight subjects; however, there is evidence to refute this concept. Furthermore, the current evidence cannot confirm that MHO subjects are permanently protected from the risk of developing metabolic disturbances associated with obesity. Currently, no standard practice guidelines for the treatment of MHO can be proposed, however, a regular surveillance of the waist circumference and cardio-metabolic risk factors such as elevated triglycerides, glycaemia, HOMA, C-reactive protein and low HDL, as well as the prevention of any further weight gain seem to represent the most prudent and sound attitude in the management of MHO subjects.

Relationship between different protein intake recommendations with muscle mass and muscle strength.

OBJECTIVE: The purpose of the present study was to examine the relationship between two different levels of protein intake (0.8 vs.1.2 g/kg body weight/day) with muscle mass and muscle strength. METHOD: Seventy-two postmenopausal women were recruited. Body composition (bioelectrical impedance analysis), muscle strength (dynamometer), energy metabolism (indirect calorimetry) and dietary intake (dietary journal) were measured. We divided the women into two groups. Women with a protein intake of ≥ 1.2 g/kg body weight/day were placed in the Protein ≥ 1.2 group (n = 35), whereas women with a protein intake of 0.8-1.19 g/kg body weight/day were categorized in the Protein 0.8-1.19 group (n = 32). RESULTS: No significant difference was observed between groups for age, height, skeletal muscle mass, resting energy expenditure, total energy expenditure, carbohydrate and lipid intake. Significant differences between groups were observed for body mass index (p < 0.001), fat mass (p < 0.001) and muscle strength (hand grip and knee extensors) (p < 0.001). More specifically, the Protein ≥ 1.2 group presented a higher muscle strength as well as a lower body mass index and fat mass compared to the Protein 0.8-1.19 group. In addition, the group with a protein intake of ≥ 1.2 g/kg body weight/day presented significantly higher energy intake (p = 0.002), and essential (p < 0.001) and non-essential (p < 0.001) amino acid intake. Interestingly, when muscle strength was adjusted for essential or non-essential amino acids, differences in muscle strength persisted. CONCLUSION: The present study indicates higher levels of muscle strength in postmenopausal women with a protein intake of ≥ 1.2 g/kg body weight/day compared to 0.8-1.19 g/kg body weight/day despite no differences in muscle mass.

Comparison between several muscle strength and cardiorespiratory fitness indices with body composition and energy expenditure in obese postmenopausal women.

The purpose of this study was to compare the relationship of several muscle strength and cardiorespiratory fitness indices with body composition and energy expenditure in obese postmenopausal women. This was a cross-sectional study involving 72 obese postmenopausal women (age: 60.0±4.8 years; body mass index: 34.1±3.5 kg/m²). Muscle strength was determined by hand dynamometer and cardiorespiratory fitness was measured by indirect calorimetry. Muscle strength and cardiorespiratory fitness were expressed in absolute (kg and L/min, respectively) and in relative values (kg/body weight (BW) and kg/lean body mass (LBM) for muscle strength and ml/min/kg BW and ml/min kg LBM for cardiorespiratory fitness). Body composition was measured using dual energy x-ray absorptiometry. Anthropometric (waist and thigh circumference), physical activity energy expenditure and daily number of steps (SenseWear armband) as well as blood pressure were also assessed. Correlations of muscle strength and cardiorespiratory fitness indices with body composition and energy expenditure showed several similarities, however, several variations were also observed. Furthermore, our results showed that age and waist circumference were the primary independent predictors for the muscle strength indices, explaining 22-37% of the variance and % body fat and age were the primary predictors for the cardiorespiratory fitness indices, explaining 18-40% of the variance. In conclusion, the present study indicates that the different methods of expressing muscle strength and cardiorespiratory fitness may display several variations and similarities with body composition and energy expenditure associations. Therefore, interpretations of relationships between muscle strength and cardiorespiratory indices with body composition and energy expenditure factors should take in account the method used to express them.

Characterizing the profile of obese patients who are metabolically healthy.

The presence of obesity-related metabolic disturbances varies widely among obese individuals. Accordingly, a unique subset of obese individuals has been described in the medical literature, which seems to be protected or more resistant to the development of metabolic abnormalities associated with obesity. These individuals, now known as 'metabolically healthy but obese' (MHO), despite having excessive body fatness, display a favorable metabolic profile characterized by high levels of insulin sensitivity, no hypertension as well as a favorable lipid, inflammation, hormonal, liver enzyme and immune profile. However, recent studies have indicated that this healthier metabolic profile may not translate into a lower risk for mortality. Mechanisms that could explain the favorable metabolic profile of MHO individuals are poorly understood. However, preliminary evidence suggests that differences in visceral fat accumulation, birth weight, adipose cell size and gene expression-encoding markers of adipose cell differentiation may favor the development of the MHO phenotype. Despite the uncertainty regarding the exact degree of protection related to the MHO status, identification of underlying factors and mechanisms associated with this phenotype will eventually be invaluable in helping us understand factors that predispose, delay or protect obese individuals from metabolic disturbances. Collectively, a greater understanding of the MHO individual has important implications for therapeutic decision making, the characterization of subjects in research protocols and medical education.

Accuracy of the SenseWear Armband™ during ergocycling.

The present study aims to show the accuracy of a portable motion sensor, the SenseWear Armband, for the estimation of energy expenditure vs. energy expenditure measured by indirect calorimetry during ergocycling. 31 healthy adults (52% women; age: 26.7±6.3 years; Body Mass Index: 23.9±3.3 kg/m2) completed a 45-min ergocycling session at 50% of their VO2(peak). Despite a significant underestimation of 18.7±13.2 kcal during the first 10 min of the activity (T=5.06; p<0.001), we observed an overall good agreement between energy expenditure estimated by the SenseWear Armband during ergocycling and indirect calorimetry (260.3±80.1 vs. 287.8±97.1 kcal, respectively) (T=-2.148; p=0.04) and a significant intra-class correlation (r=0.81; p<0.001). The results of the present study indicate that the SenseWear Armband underestimated energy expenditure during a 45-min ergocycling session at a 50% VO2(peak) intensity, mainly during the first 10 min. Underestimation at the onset of the activity warrants further research.

Similar associations of total adiponectin and high molecular weight adiponectin with cardio-metabolic risk factors in a population of overweight and obese postmenopausal women: a MONET study.

The aim of the study was to examine the association between total adiponectin and high molecular weight (HMW) adiponectin levels with cardio-metabolic risk factors in a population of sedentary, overweight, and obese postmenopausal women. Cross-sectional study was carried out on 55 nondiabetic sedentary overweight and obese postmenopausal women aged between 50 and 70 years. Insulin sensitivity was assessed by euglycemic-hyperinsulinemic clamp technique. Body composition and visceral fat were measured using dual X-ray absorptiometry and computed tomography, respectively. Other cardio-metabolic risk factors included: plasma lipids, hsC-reactive protein, energy expenditure (doubly labeled water), peak oxygen consumption, muscle strength (using weight training equipment) as well as total and HMW adiponectin. Correlations of total and HMW adiponectin with various cardio-metabolic risk factors were comparable. In addition, regression analysis results showed similar independent predictors of total and HMW adiponectin. Finally, the receiver operator characteristic (ROC) curves for total and HMW adiponectin to predict insulin sensitivity showed no difference between the areas under curve (AUC) (AUC total adiponectin=0.80 [95% CI: 0.66-0.95] versus AUC HMW adiponectin=0.76 [95% CI: 0.60-0.91], p=0.36). The present study indicates that HMW adiponectin does not seem to provide additional information than total adiponectin in relation to cardio-metabolic risk factors in overweight/obese postmenopausal women.

Comparison between several insulin sensitivity indices and metabolic risk factors in overweight and obese postmenopausal women: a MONET study.

BACKGROUND AND AIMS: The purpose of this study was to compare the relationship of several insulin sensitivity indices with cardiometabolic risk factors in overweight and obese postmenopausal women. METHODS AND RESULTS: This was a cross-sectional study involving 137 overweight and obese postmenopausal women (age: 57.7+/-4.8 yrs; body mass index: 32.4+/-4.6 kg/m(2); body fat: 38.6+/-9.2 kg). Insulin sensitivity was determined by the euglycaemic-hyperinsulinemic (EH) clamp technique as well as by oral glucose tolerance test (OGTT) derived indices (Stumvoll, Matsuda and SI(is)) and fasting surrogate indices (HOMA, QUICKI). Cardiometabolic risk factors included: body composition and visceral fat that were measured using dual energy X-ray absorptiometry and computed tomography, respectively. Peak oxygen consumption, lower body muscle strength (using weight training equipment), physical activity energy expenditure (doubly labeled water), plasma lipids and C-reactive protein were also measured. Correlations of insulin sensitivity indices with metabolic risk factors showed some similarities, however, a wide range of variations were also observed. Furthermore, our results showed that visceral fat was the primary predictor for surrogate and OGTT indices, explaining 15-28% of the variance and the triglycerides/HDL-C ratio was the primary predictor for the EH clamp indices, explaining 15-17% of the variance. CONCLUSION: The present study indicates that the different methods of measuring and/or expressing insulin sensitivity display variations for associations with cardiometabolic risk factors. Therefore, interpretations of relationships between insulin sensitivity indices and cardiometabolic risk factors should take into account the method used to estimate and express insulin sensitivity.

HOMA or QUICKI: is it useful to test the reproducibility of formulas?

AIM: HOMA and QUICKI are the most widely used indices for assessing insulin sensitivity. Both are based on fasting glucose and insulin measures, and mainly differ by the log transformation of these variables in QUICKI. However, HOMA is less reproducible than QUICKI, and log HOMA does not improve its reproducibility. The aim of this study was to investigate the various mathematical transformations of HOMA and to assess its reproducibility. METHOD: We used data from a clamp study involving 123 non-diabetic overweight and obese postmenopausal women. Fasting insulin and glucose were measured in two visits 15 and 30 days apart. This allowed us to calculate HOMA as (fasting glucose [mmol/L] x fasting insulin [microU/mL])/22.5 and QUICKI as 1/(log fasting glucose [mg/dL]+log fasting insulin [microU/mL]) twice for subjects who were weight-stable between visits. RESULTS: QUICKI had better reproducibility (CV=3.9%) than either HOMA (CV=26.7%) or log HOMA (CV=22.0%). However, log-transforming HOMA using log (glucose x insulin)/log (22.5) and log-transforming HOMA without transforming the constant denominator improved its CV to 6.5% and 5.7%, respectively. CONCLUSION: By modifying the mathematical expression of HOMA, we were able to achieve comparable CVs for QUICKI and HOMA. However, the CV should be used to assess the reproducibility of techniques to measure glucose and insulin, not of mathematical formulas. When evaluating indices for the assessment of insulin sensitivity, the key point is how well they correlate with the 'gold-standard' glucose clamp.

Relationship between the hyperinsulinemic-euglycaemic clamp and a new simple index assessing insulin sensitivity in overweight and obese postmenopausal women.

OBJECTIVE: The purpose of this study was to compare assessment of insulin sensitivity from hyperinsulinemic euglycaemic (HIEG) clamp with indexes derived from fasting and oral glucose tolerance test (OGTT). SUBJECTS AND METHODS: Cross-sectional study with 107 sedentary non-diabetic overweight and obese postmenopausal (BMI=32.4+/-0.4 kg/m(2)) women undergoing both HIEG clamp and OGTT. Pairs of data were analyzed using Pearson correlation and Bland-Altman graphs analysis. Comparison between correlations was made using the method reported by Zar. RESULTS: All the indexes derived from either the OGTT or surrogate indexes were highly correlated with all the clamp-derived formulas (P<0.0001). However, HOMA and QUICKI were generally less correlated than OGTT-derived indexes. Analogically to QUICKI, we calculated a new formula derived from the OGTT measurements of glucose and insulin named simple index assessing insulin sensitivity (SI(is)OGTT)=1/[log(sum glucose t(0-30-90-120)) (mmol/l)+log(sum insulin t(0-30-90-120)) (microUI/ml)]. By using this formula, we found high significant correlations (r's=0.61-0.65; P<0.0001) with the clamp results. Moreover, the correlations of SI(is)OGTT with the clamp data were higher than for other previously published indexes. CONCLUSION: In that large group of non-diabetic overweight and obese postmenopausal women insulin sensitivity index derived from OGTT provided more accurate information than fasting based formula. We propose a new simple index for the assessment of insulin sensitivity from the OGTT data (SI(is)OGTT). The advantage of this new formula over all previously published OGTT-derived indexes of insulin sensitivity is that it is 1) easy to calculate 2) better correlated than other indexes of insulin sensitivity and 3) not affected by the way clamp results are expressed. Further studies are needed to validate SI(is)OGTT index in other populations.

Can HbA1c be Used to Screen for Glucose Abnormalities Among Adults with Severe Mental Illness?

Aim: Prediabetes and type 2 diabetes are highly prevalent among individuals with serious mental illness and increased by antipsychotic medication. Although widely recommended, many obstacles prevent these patients from obtaining a proper screening for dysglycemia. Currently, glycated hemoglobin (HbA1c), fasting glucose, and 2-hour glucose levels from the oral glucose tolerance test are used for screening prediabetes and type 2 diabetes. The objective of this study was to investigate if HbA1c could be used as the only screening test among individuals with serious mental illness. Methods: Cross sectional study comparing the sensitivity of HbA1c, fasting glucose, and 2-h oral glucose tolerance test to detect dysglycemias in serious mental illness participants referred for metabolic complications. Results: A total of 84 participants (43 female; aged: 38.5±12.8 years; BMI: 35.0±6.8 kg/m²) was included. Regarding prediabetes, 44, 44 and 76% were identified by HbA1c, fasting glucose, and 2 h- oral glucose tolerance test respectively and for type 2 diabetes, 60, 53 and 66% were identified by HbA1c, fasting glucose and 2 h-oral glucose tolerance test. The overlap between the 3 markers was low (8% of participants for prediabetes and 26% for Type 2 diabetes). Sensitivity of HbA1c were moderate (range 40-62.5%), while its specificity was excellent (92-93%). Conclusion: The present study indicates a low agreement between HbA1c, fasting glucose and 2-h oral glucose tolerance test. It appears that these markers do not identify the same participants. Thus, HbA1c may not be used alone to detect all glucose abnormalities among individuals with serious mental illness.

Lifestyle behaviours and components of energy balance as independent predictors of ghrelin and adiponectin in young non-obese women.

AIM: Dysregulation of the normal levels of ghrelin, leptin and adiponectin in young non-obese subjects could promote food intake, diabetes and cardiovascular disease in later stages of life. Little information is available on how plasmatic concentrations of these hormones may be influenced by eating habits and/or components of energy balance in a young population, which if known, could facilitate their voluntary regulation. METHODS: In this cross-sectional study we examined the predictors of fasting plasma ghrelin, adiponectin and leptin in a population of well-characterized young non-obese women (N = 63). Energy intake was assessed by 24-hour dietary recall, resting metabolic rate (RMR) by indirect calorimetry, physical activity energy expenditure (PAEE) by tri-axial accelerometer, physical fitness by VO(2 peak), and eating behaviors by self administrated questionnaire. RESULTS: Lower RMR and higher HDL-cholesterol were independent predictors of higher plasma ghrelin explaining 17.6% of its variation even after correcting for BMI. Higher total or central fat mass was the only predictor of higher plasma leptin, and no other variable added any power to the prediction equation. Finally, higher energy intake and waist circumference and lower PAEE predicted lower plasma adiponectin in young non-obese women, explaining 43% of the variation in its concentrations even after correcting for total or central fat mass. CONCLUSION: Components of the energy balance (ie: energy intake and/or expenditure) influence adiponectin and ghrelin circulating levels. That is, higher energy intake and lower physical activity independently predict lower adiponectin concentrations, whereas lower resting metabolic rate independently predicts higher ghrelin levels in young non-obese women. Prospective studies are needed to examine whether circulating concentrations of ghrelin and adiponectin can be voluntarily regulated by lifestyle interventions.

Surrogate indexes vs. euglycaemic-hyperinsulinemic clamp as an indicator of insulin resistance and cardiovascular risk factors in overweight and obese postmenopausal women.

BACKGROUND: There is considerable interest in validating the most convenient method to estimate insulin sensitivity in clinical research protocols that could best indicate cardiovascular risk factors. To address this issue we examined the interrelationships of several cardiovascular risk factors with surrogate indexes such as fasting insulin, the homeostasis model assessment (HOMA), the quantitative insulin sensitivity check index (QUICKI) and the revised QUICKI vs the euglycaemic-hyperinsulinemic (EH) clamp in a non-diabetic overweight or obese postmenopausal female population. DESIGN: Cross-sectional study involving 88 obese postmenopausal women (age: 57.5+/-5.0 yrs; body mass index: 32.52+/-4.4 kg/m2; percent body fat: 46.35+/-4.9%). METHODS: Insulin sensitivity was determined by the EH clamp technique as well as by surrogate indexes such as fasting insulin, HOMA, log HOMA, QUICKI and revised QUICKI. Body composition and body fat distribution were measured using dual energy x-ray absorptiometry and computed tomography, respectively. RESULTS: Correlations between insulin resistance indexes (fasting insulin, revised QUICKI, QUICKI, log HOMA, HOMA) vs glucose disposal were similar (range of r's=0.40 to 0.49), suggesting that no index was superior to another with respect to its relationship with the EH clamp. Correlations between the insulin resistance indexes with plasma lipids were comparable among all indexes, however, systolic blood pressure, visceral fat and C-reactive protein were moderately superior with index vs the EH clamp. CONCLUSION: Surrogate measures of insulin resistance, in particular fasting insulin, are simple tools appropriate for epidemiological studies that can be used as substitutes for the EH clamp to estimate glucose disposal and cardiovascular risk factors in overweight and obese postmenopausal women.

Adverse effects of weight loss: Are persistent organic pollutants a potential culprit?

Health professionals commonly recommend weight loss to individuals with obesity. However, unexpected adverse health effects after a weight-loss program have been reported in several studies. The factors that could explain this phenomenon are currently poorly understood. However, one potential factor that has emerged is persistent organic pollutants (POPs). Due to their lipophilic nature, POPs are known to accumulate in the adipose tissue and their concentrations are found to be higher in obese individuals than lean subjects. There is evidence to suggest that weight loss induces a significant increase in POPs levels in the bloodstream. Furthermore, the increases in plasma POPs levels after weight loss are even greater with an intensive weight loss. Thus, a critical question that remains unresolved is whether POPs released from the adipose tissue to the bloodstream during intensive weight loss could increase the risk of cardiometabolic disturbances. In turn, the accumulation of POPs released in response to an intensive weight loss may impair energy metabolism and stimulate a subsequent weight regain. Thus, the purpose of this review is to provide insights about the role of POPs on cardiometabolic risk factors during weight loss and weight regain that could potentially explain, at least in part, the adverse effects observed in certain weight-loss studies. We will also discuss the potential synergistic or antagonistic POPs-dependent risks following weight-loss programs. Ultimately, this may lead in establishing new therapeutic boundaries to minimize potential health hazards related to weight loss.

Energy expenditure during the group exercise course Bodypump in young healthy individuals.

AIM: The purpose of the present study was to examine the energy expenditure during the group resistance training exercise course Bodypump in young healthy individuals. METHODS: The study population consisted of 40 men and women (age: 31.7±5.8 years, body mass index [BMI]: 24±2.6 kg/m2) that performed three 60-min sessions of the group resistance training exercise course Bodypump. Free living energy expenditure during the course was measured using the portable SenseWear armband. Perceived energy expenditure, perception of effort, fatigue and pleasure were also measured after the course. RESULTS: Mean energy expenditure and intensity during the Bodypump course for all participants were 250.3±67.8 kcal or 4.2 kcal/min and 3.5±0.7 METS, respectively. Interestingly, perceived energy expenditure for all participants was significantly higher by ~67% compared to measured energy expenditure (394.1±116 vs. 250.3±67.8 kcal, respectively; P<0.05). Moreover, 85% of all individuals reported that the Bodypump course was highly enjoyable. CONCLUSION: Energy expenditure during a 60-min Bodypump course appears to be approximately 250 kcal and seems to be performed at a moderate intensity (3.5 METS) in young healthy men and women. These results could have an impact on the amount of physical activity an individual performs as well as the preparation of physical activity programs by kinesiologists.

Effect of cysteine-rich whey protein (immunocal®) supplementation in combination with resistance training on muscle strength and lean body mass in non-frail elderly subjects: a randomized, double-blind controlled study.

OBJECTIVES: The purpose of the present study was to examine the effect of a cysteine-rich whey protein (Immunocal®) supplementation in combination with resistance training on muscle strength and lean body mass (LBM) in elderly individuals. We hypothesized that the cysteine-rich whey protein (Immunocal®) group would experience a greater increase in muscle strength and lean body mass versus the control group (casein). DESIGN: Randomized double-blind controlled intervention study. SETTING: Institut de Recherches Cliniques de Montréal in Montreal, Canada. PARTICIPANTS: Ninety-nine non-frail elderly subjects were recruited. INTERVENTION: Participants were randomly assigned into two groups. The experimental group received a cysteine-rich whey protein isolate (Immunocal®) (20 g/day) and the control group received casein (20 g/day) during a 135-day period. In addition, both groups performed the same resistance training program (3 times per week). MEASUREMENTS: Body composition (DXA) and muscle strength (leg press) were measured. RESULTS: Of the 99 recruited participants, 84 completed the 135-day study period. Of these, 67 subjects (33 in the casein group and 34 in the Immunocal® group) complied and used at least 80 % of the study product and completed at least 80 % of their training sessions. Results in this selected group show an increase in all three muscle strength variables (absolute, normalized by BW and by LBM) by 31.0 %, 30.9 % and 30.0 %, respectively in the casein group as well as 39.3 %, 39.9 % and 43.3 %, respectively in the Immunocal® group after the intervention (p < 0.05). The increases in muscle strength favored Immunocal® versus casein by approximately 10 % when expressed in kg per kg BW and in kg per kg LBM (p < 0.05). No significant changes were found between pre-and-post intervention in both groups for total LBM. CONCLUSIONS: Our findings showed increases in muscle strength in both groups after resistance training, however, significant additional increases were observed in muscle strength with the addition of a cysteine-rich whey protein (Immunocal®) versus casein.

Can we identify metabolically healthy but obese individuals (MHO)?

OBJECTIVES: A unique subset of obese individuals termed, Metabolically Healthy but Obese (MHO), has been described in the literature. However, there is no agreed upon method to identify MHO individuals for research protocols or in clinical practice. Therefore, we examined a large cohort of obese older women to attempt to develop a first set of clinical markers that may identify MHO individuals. METHODS: We studied 154 obese postmenopausal women (age: 57.0 +/- 5.3 years and BMI: 34.3 +/- 5.5 kg/m2). Selection criteria for MHO individuals were partially based on the National Cholesterol Education Program's Adult Treatment Panel III report (ATP III) for lipid profiles (triglycerides: < or =1.7 mmol/l, total cholesterol: < or =5.2 mmol/l, HDL-cholesterol: > or =1.3 mmol/l and LDL-cholesterol: < or =2.6 mmol/l) and from the study of Brochu et al. (2001) for insulin sensitivity (HOMA<=1.95). When 4 out of 5 criteria are met, we suggest that a diagnosis of the MHO individual could be made. RESULTS: Based on the proposed criteria, 19 out of 154 (12.3%) postmenopausal women subjects were identified as MHO. By design, MHO individuals showed a favourable lipid profile and higher insulin sensitivity values. CONCLUSION: We suggest a potential new set of clinical markers to identify MHO individuals. Identifying MHO individuals could have important implications for therapeutic medical decision making, subject characterization in research protocols and in medical education.

Relationship between the Level of Education and Functional Capacity in Active Elderly Adults.

BACKGROUND: Both the level of education and functional capacity seems to be associated with the level of physical activity in the elderly. However, the relationship between the level of education and functional capacity in active elderly adults is poorly understood. OBJECTIVE: To examine the association between the level of education and the functional capacity profile of active elderly adults. DESIGN: Cross-sectional. PARTICIPANTS: One hundred and four elderly men and 198 postmenauposal women (mean age: 62.7 ± 7.6 years old) were recruited among registered members of the YMCAs of Montreal who practiced at least one hour of structured physical activity per week. Participants were then divided in two groups based on their level of education (the cut-off point was the high-school diploma). MEASUREMENTS: Body composition (DXA), muscle strength (knee extensors, handgrip), estimated maximal oxygen consumption (2-km walk test), perceived health (SF-36) and functional capacity (timed up and go, alternate step and one-leg stance tests) were measured. The level of education of the participants was assessed by questionnaire. RESULTS: Body composition was similar between groups. We observed that all functional capacity tests as well as the global functional capacity score were significantly higher in the most educated group compared to the least educated group (p<0.05). In addition, the most educated group had significantly higher levels of knee extensors strength, estimated maximal oxygen consumption and perception of physical functioning. CONCLUSIONS: A higher level of education was associated with a favourable functional capacity profile in our cohort of active elderly adults. However, the mechanism(s) which could mediate this association remain(s) unknown.

Good vs. poor self-rated diabetes control: differences in cardiovascular risk and self-care activities.

AIM: The aim of this study was to assess differences in cardiovascular risk and performance of self-care activities in people who rated their diabetes control as good or poor. METHODS: A sub-sample of 77 participants who took part in the Evaluation of Diabetes Treatment telephone interview were invited into a clinic to complete a series of laboratory examinations. Self-rated diabetes control was validated using the following laboratory markers: HbA1c, total cholesterol/HDL cholesterol ratio and LDL cholesterol. Differences in blood pressure and BMI were also assessed. Finally, all participants also completed the Summary of Self-Care activities questionnaire. RESULTS: Those people who rated their diabetes control as fair or poor had a significantly higher BMI, HbA1c levels, total cholesterol/HDL-cholesterol ratio and systolic blood pressure. When asked about self-care activities in the past week, those people who reported their diabetes control was fair/poor had spent significantly fewer days following a general diet and exercising. CONCLUSIONS: People with poor self-rated diabetes control have unfavourable cardiovascular risk and decreased performance of self-care activities.