Congruent Validity of Resting Energy Expenditure Predictive Equations in Young Adults

Validity of predictive equations for total energy expenditure against doubly labeled water

Variations in physical activity energy expenditure can make accurate prediction of total energy expenditure (TEE) challenging. The purpose of the present study was to determine the accuracy of available equations to predict TEE in individuals varying in physical activity (PA) levels. TEE was measured by DLW in 56 adults varying in PA levels which were monitored by accelerometry. Ten different models were used to predict TEE and their accuracy and precision were evaluated, considering the effect of sex and PA. The models generally underestimated the TEE in this population. An equation published by Plucker was the most accurate in predicting the TEE in our entire sample. The Pontzer and Vinken models were the most accurate for those with lower PA levels. Despite the levels of accuracy of some equations, there were sizable errors (low precision) at an individual level. Future studies are needed to develop and validate these equations.

Impact of Equation Choice on Resting Metabolic Rate Ratio in High-Level Men and Women Athletes

OBJECTIVE

To examine the impact of the RMR ratio cutoff point selected on the categorization of prevalence/absence of low energy availability among predictive equations in high-level athletes (n = 241 [99 women]; 52% competed at the World Championship and Olympic Games), and whether this categorization is influenced by sex and the predictive equation used.

METHODS

We assessed RMR using indirect calorimetry, predicted the RMR using the equations proposed by Harris-Benedict, FAO/WHO/UNU, de Lorenzo, ten Haaf and Wejis, Wong, Jagim, Cunningham, and Freire, and computed the RMR ratio for each equation.

RESULTS

We observed that the cumulative percentage of RMR ratio values increased at a faster rate using Jagim, ten Haaf and Wejis, and Cunningham equations compared to the other equations. At the 0.90 value (the most used cutoff point in literature), the Jagim equation categorized ≥ 50% of the athletes into "low energy availability". No Sex × Equation × Sport interaction effect was observed (F = 0.10, p = 1.0). There was a significant main effect to Sex (F = 11.7, p < 0.001, ES = 0.05), Sport (F = 16.4, p < 0.001, ES = 0.01), and Equation (F = 64.1, p < 0.001, ES = 0.19). Wong and FAO/WHO/UNU equations yielded the largest errors (assessed vs. predicted RMR) in men and women, respectively.

CONCLUSION

The selected RMR ratio cutoff point influences the prevalence/absence of low energy availability characterization in high-level athletes and suggests that certain equations could bias its assessment.

Multiple factor assessment for determining resting metabolic rate in young adults

Existing formulas cannot fully explain the variation of resting metabolic rate (RMR). This study aims to examine potential influencing factors beyond anthropometric measurements and develop more accurate equations using accessible parameters. 324 healthy adults (230 females; 18-32 years old) participated in the study. Height, fat-free mass (FFM), fat mass (FM) and RMR were measured. Menstrual cycle, stress levels, living habits, and frequency of consuming caffeinated foods were collected. Measured RMR were compared with predictive values of the new equations and previous 11 equations. Mean RMR for men and women was 1825.2 ± 248.8 and 1345.1 ± 178.7 kcal/day, respectively. RMR adjusted for FFM0.66FM0.066 was positively correlated with BMI. The multiple regression model showed that RMR can be predicted in this population with model 1 (with FFM, FM, age, sex and daily sun exposure duration) or model 2 (with weight and height replacing FFM and FM). The accuracy was 75.31% in the population for predictive model 1 and 70.68% for predictive model 2. The new equations had overall improved performance when compared with existing equations. The predictive formula that consider daily sun exposure duration improve RMR prediction in young adults. Additional investigation is required among individuals in the middle-aged and elderly demographic.

Validation of predictive equations to estimate resting metabolic rate of females and males across different activity levels

OBJECTIVES

Using equations to predict resting metabolic rate (RMR) has yielded different degrees of validity, particularly when sex and different physical activity levels were considered. Therefore, the purpose of the present study was to determine the validity of several different predictive equations to estimate RMR in female and male adults with varying physical activity levels.

METHOD

We measured the RMR of 50 adults (26 females and 24 males) evenly distributed through activity levels varying from sedentary to ultra-endurance. Body composition was measured by dual X-ray absorptiometry and physical activity was monitored by accelerometry. Ten equations to predict RMR were applied (using Body Mass [BM]: Harris & Benedict, 1919; Mifflin et al., 1990 [MifflinBM]; Pontzer et al., 2021 [PontzerBM]; Schofield, 1985; FAO/WHO/UNU, 2004; and using Fat-Free Mass (FFM): Cunningham, 1991; Johnstone et al., 2006; Mifflin et al., 1990 [MifflinFFM]; Nelson et al. 1992; Pontzer et al., 2021 [PontzerFFM]). The accuracy of these equations was analyzed, and the effect of sex and physical activity was evaluated using different accuracy metrics.

RESULTS

Equations using BM were less accurate for females, and their accuracy was influenced by physical activity and body composition. FFM equations were slightly less accurate for males but there was no obvious effect of physical activity or other sample parameters. PontzerFFM provides higher accuracy than other models independent of the magnitude of RMR, sex, activity levels, and sample characteristics.

CONCLUSION

Equations using FFM were more accurate than BM equations in our sample. Future studies are needed to test the accuracy of RMR prediction equations in diverse samples.

Accuracy of equations for estimating resting energy expenditure in children and adolescents living with phenylketonuria

BACKGROUND

Measuring resting energy expenditure (REE) in individuals living with phenylketonuria (PKU) using indirect calorimetry (IC) is unusual in healthcare facilities because it requires specific protocols and expensive equipment. Considering that determining REE is crucial for devising nutritional strategies for the management of PKU, the aim of this study was to identify the predictive equations that provide the best estimates of REE in children and adolescents living with PKU and to propose a predictive equation for determining REE in this population.

METHODS

An REE concordance study was conducted with children and adolescents living with PKU. Anthropometric and body composition assessments using bioimpedance and REE assessment using IC were performed. The results were compared to 29 predictive equations.

RESULTS

Fifty-four children and adolescents were evaluated. The REE obtained using IC differed from all estimated REE, except Henry's equation for male children (p = 0.058). Only this equation showed good agreement (0.900) with IC. Eight variables were associated with the REE obtained using IC with emphasis on fat-free mass (kg) (r = 0.786), weight (r = 0.775), height (r = 0.759) and blood phenylalanine (r = 0.503). With these variables, three REE equations were suggested, with R2  = 0.660, 0.635 and 0.618, respectively, and the third equation, which involves weight and height, showed adequate sample size for a statistical power of 0.942.

CONCLUSION

Most equations, not specific for individuals living with PKU, overestimate the REE of this population. We propose a predictive equation for assessing REE for children and adolescents living with PKU to be used in settings where IC is not available.

The effects of dietary and physical activity interventions on tinnitus symptoms: An RCT

OBJECTIVE

Subjective tinnitus is defined as the perception of irregular sound at different frequencies. Although the underlying cause of tinnitus is unclear, increased body weight is known to increase tinnitus symptoms. The present study aimed to determine the effects of dietary and physical activity interventions on tinnitus symptoms.

METHODS

Sixty-three obese subjects with tinnitus aged 20 to 65 years were divided into diet + physical activity (P.A.) (n = 15), diet (n = 16), P.A. (n = 15), and control (n = 17) groups. Dietary records, anthropometric measurements, Tinnitus Handicap Inventory (THI), Beck Depression Inventory (BDI), Short-Form Health Survey (SF-36), and Visual Analogue Scale (VAS) of all individuals were recorded and compared at the baseline and at study completion.

RESULTS

Body weight decreased in the diet + P.A. (-5.9 (3.5) kg), diet (-3.4 (0.9) kg), and P.A. (-2.0 (2.1) kg) groups compared to the baseline (p < 0.05). There was a more significant decrease in tinnitus frequency, tinnitus severity, and VAS scores in individuals with a weight loss of ≥ 5.0% than in those with < 5.0% (p < 0.05). A decrease of 1 kg/m² in BMI decreased the BDI score by 0.485 units and the THI score by 0.523 units. Step counts were increased in the diet + P.A. (3562.3±739.9) and P.A. (3797.1 ± 1801.1) groups compared to baseline (p < 0.01). Each increase of 1000 steps increased the SF-36 score by 1.592 units and decreased the THI score by 0.750 units (p < 0.05).

CONCLUSION

Dietary and physical activity interventions, alone or in combination, alleviated tinnitus symptoms and increased quality of life in individuals with tinnitus. Due to its contribution to obesity prevention and positive effects on tinnitus, organizing dietary and physical activity programs for obese individuals with tinnitus would improve these individuals' quality of life.

Calculation of basal metabolic rate in patients with morbid obesity treated in spa conditions

BACKGROUND

The purpose of this study is to calculate the basal metabolic rate with the Mifflin equation based on the expected body mass for normal body mass index values in obese patients treated in spa conditions.

METHODS

Authors recruited patients with morbid obesity (body mass index>40 kg/m² ) and non-obese controls (body mass index<30 kg/m² ). Authors included 104 patients with morbid obesity (mean body mass index ±standard deviation, 46.9 ± 2.1) treated in spa conditions, and 90 non-obese controls (mean body mass index 28 ± 1.3).

RESULTS

The mean basal metabolic rate calculated based on actual body mass was 2088 ± 303 kcal in patients with morbid obesity, and it was 1424 ± 268 kcal in non-obese controls. Basal metabolic rate calculated based on expected body mass for normal body mass index decreased significantly in patients with morbid obesity (p<0.01), but not in non-obese controls. Accordingly, energy expenditure and planned caloric intake was significantly lower when basal metabolic rate was calculated based on expected body mass than actual body mass in patients with morbid obesity, but not in non-obese controls (p<0.01).

CONCLUSIONS

Expected body mass for normal body mass index, should be used to calculate basal metabolic rate in patients with morbid obesity. This article is protected by copyright. All rights reserved.

EVALUATION OF REST ENERGY EXPENDITURE IN PATIENTS WITH NON ALCOHOLIC FATTY LIVER DISEASE

BACKGROUND

Non-alcoholic fatty liver disease (NAFLD) is currently considered a global public health problem, with changes in lifestyle being the effective way to treat the disease. To date, there is no recommended standard of assessment to determine the resting energy expenditure (REE) of patients with NAFLD, so that dietary therapy can be properly guided.

OBJECTIVE

To evaluate the REE of patients with NAFLD through indirect calorimetry and compare with different predictive formulas of REE and with REE by electrical bioimpedance analysis (BIA). Assess body composition through BIA, with NAFLD staging and the presence of comorbidities.

METHODS

They were evaluated in patients with NAFLD over 18 years of age treated at the Gastroenterology outpatient clinic of a tertiary level hospital in southern Brazil. NAFLD staging was performed using liver biopsy or a non-invasive method. Weight, height and body mass index (BMI) were determined in all patients. The short version of the International Physical Activity Questionnaire was used to assess physical activity. Comorbidities as arterial hypertension, diabetes mellitus and dyslipidemia were evaluated. To estimate energy expenditure at rest, Harris-Benedict, Jeor Mifflin-St, World Health Organization and Schofield formulas were used. BIA was used to assess resting metabolic rate (RMR) and body mass, and to measure RMR, indirect calorimetry was also used. Associations between categorical variables were tested with Pearson's χ2 test and between groups with McNemar's test. The level of significance assumed was 5%. The degree of agreement between the REE measurement methods was assessed using the Blan-Altman test.

RESULTS

A total of 67 patients were evaluated, 70.5% male, with a mean age of 59 years and a mean BMI of 33.08 kg/m2 ±5.13. The average RMR per CI was 1,753 kcal ±614.58. When comparing the RMR estimate by different formulas with indirect calorimetry, only the Jeor Mifflin-St formula showed a statistically significant difference (P=0.0001), with a difference of +318.49 kcal. BIA and Harris Benedict's formula presented values closer to CI, 1,658 and 1,845 kcal respectively.

CONCLUSION

We suggest that the Jeor Mifflin-St formula should not be used to estimate the RMR in patients with NAFLD. In the absence of indirect calorimetry, some alternatives can be used safely in this population, such as BIA and the predictive formulas of Harris Benedict, Schofield and the World Health Organization.

Relationships between diet and basal fat oxidation and maximal fat oxidation during exercise in sedentary adults

BACKGROUND AND AIMS

To study the relationships between different dietary factors (i.e., energy, macronutrient and fatty acid intake, food group consumption, and dietary pattern) and basal fat oxidation (BFox) and maximal fat oxidation during exercise (MFO) in sedentary adults.

METHOD AND RESULTS

A total of 212 (n = 130 women; 32.4 ± 15.1 years) sedentary healthy adults took part in the present study. Information on the different dietary factors examined was gathered through a food frequency questionnaire and three nonconsecutive 24 h recalls. Energy and macronutrient intakes and food consumption were then estimated and dietary patterns calculated. BFox and MFO were measured by indirect calorimetry following standard procedures. Our study shows that dietary fiber intake was positively associated with BFox after taking into consideration the age, sex, and energy intake. A significant positive association between nut consumption and BFox was observed, which became nonsignificant after taking into consideration the age and energy intake. Fat intake and the dietary quality index (DQI), and the DQI for the Mediterranean diet were positively associated with MFO, which was attenuated after taking sex, age, and energy intake into consideration.

CONCLUSION

A higher dietary fiber intake and fat intake are associated with higher BFox and MFO, respectively, in sedentary adults.

CLINICAL TRIALS

ClinicalTrials.gov, ID: NCT02365129 (https://clinicaltrials.gov/ct2/show/study/NCT02365129) & ID: NCT03334357 (https://clinicaltrials.gov/ct2/show/NCT03334357).

Weight change adjusted equations for assessing resting metabolic rate in overweight and obese adults

BACKGROUND

Although over one hundred equations have been developed to predict the energy expenditure of individuals, none are sensitive to weight change in assessment of resting metabolic rate (RMR) before and after weight loss.

OBJECTIVE

To formulate adjusted equations for overweight and obese individuals and to compare their accuracy with existing prediction RMR equations before and after weight loss.

SUBJECTS/MATERIALS

This is historical prospective study. Participants included 39 overweight and obese men and women before and after losing 10-20% from baseline weight on a diet and physical activity regimen for at least three months. Pre and post weight loss measured RMR results were compared to estimated RMR using several existing prediction equations: Harris and Benedict, Ravussin and Bogardus, and Mifflin et al. To improve the accuracy of these prediction equations, we suggest new equations adjusted for weight loss, based on measured RMR and evaluated their accuracy.

RESULTS

Pre and post weight loss data indicated: significant fat reduction in both genders; reduction in free-fat mass only in men, and a significant decrease in measured RMR only in women. Our suggested equations were the most accurate and closest to measured RMR in both genders, in comparison to the Harris and Benedict, Ravussin and Bogardus, and Mifflin et al equation results. Estimated RMR using the latter equations was significantly lower than measured RMR in both genders at pre and post weight loss (P < 0.01).

CONCLUSIONS

This study highlights the need for adjusting RMR equations before and after weight loss in overweight and obese individuals. Further research is needed to validate our suggested equations.

Resting Energy Expenditure of Master Athletes: Accuracy of Predictive Equations and Primary Determinants

Resting energy expenditure (REE) is determined mainly by fat-free mass (FFM). FFM depends also on daily physical activity. REE normally decreases with increased age due to decreases in FFM and physical activity. Measuring REE is essential for estimating total energy expenditure. As such, there are a number of different equations in use to predict REE. In recent years, an increasing number of older adults continue to participate in competitive sports creating the surge of master athletes. It is currently unclear if these equations developed primarily for the general population are also valid for highly active, older master athletes. Therefore, we tested the validity of six commonly-used equations for predicting REE in master athletes. In conjunction with the World Masters Athletic Championship in Malaga, Spain, we measured REE in 113 master athletes by indirect calorimetry. The most commonly used equations to predict REE [Harris & Benedict (H&B), World Health Organization (WHO), Müller (MÜL), Müller-FFM (MÜL-FFM), Cunningham (CUN), and De Lorenzo (LOR)] were tested for their accuracies. The influences of age, sex, height, body weight, FFM, training hours per week, phase angle, ambient temperature, and athletic specialization on REE were determined. All estimated REEs for the general population differed significantly from the measured ones (H&B, WHO, MÜL, MÜL-FFM, CUN, all p < 0.005). The equation put forward by De Lorenzo provided the most accurate prediction of REE for master athletes, closely followed by FFM-based Cunningham’s equation. The accuracy of the remaining commonly-used prediction equations to estimate REE in master athletes are less accurate. Body weight (p < 0.001), FFM (p < 0.001), FM (p = 0.007), sex (p = 0.045) and interestingly temperature (p = 0.004) are the significant predictors of REE. We conclude that REE in master athletes is primarily determined by body composition and ambient temperature. Our study provides a first estimate of energy requirements for master athletes in order to cover adequately athletes’ energy and nutrient requirements to maintain their health status and physical performance.

Using measured resting metabolic rate to derive calorie prescriptions in a behavioral weight loss program

Objective

Within behavioral weight loss (BWL) programs, using measured resting metabolic rate (RMR) is a more accurate—yet costlier—alternative to the standard method of assigning calorie prescriptions using baseline weight. This investigation aimed to assess differences between calorie goals prescribed using each method including demographic predictors and associations with weight loss.

Methods

This is an ancillary study to a trial comparing approaches to motivational enhancement in a 6‐months BWL program designed for emerging adults age 18–25 (N = 308). RMR was measured at baseline and used to derive calorie prescriptions; standard calorie goals were retrospectively assigned for the purpose of these analyses.

Results

Standard calorie prescriptions were significantly higher than those derived from RMR. Sex and race were significant predictors of calorie prescription discrepancies: using the standard method, women and Black participants were assigned higher calorie goals than their RMR would indicate. Calorie goal discrepancy did not predict 6‐months weight change.

Conclusions

Differences in calorie prescriptions between approaches were significant; however, it remains to be determined whether measuring RMR is worth the cost, time, and participant burden. It may be the case that this consideration has greater impact for certain subgroups—namely, women and Black participants.

Accuracy of the Resting Energy Expenditure Estimation Equations for Healthy Women

Background: There exist several prediction equations for the estimation of resting energy expenditure (REE). However, none of these equations have been validated in the Chilean female population yet. The aims of this study are (1) to determine the accuracy of existing equations for prediction of REE and (2) to develop new equations in a sample of healthy Chilean women. Methods: A cross-sectional descriptive study was carried out on 620 Chilean women. The sample showed an age range between 18 and 73 years, a body mass index average of 28.5 ± 5.2 kg/m², and a prevalence of overweight and obesity of 41% and 33.2%, respectively. REE was measured by indirect calorimetry (REE_IC), which was used as the gold standard to determine the accuracy of twelve available REE prediction equations and to calculate alternative formulas for estimation of REE. Paired t-tests and Bland–Altman plots were used to know the accuracy of the estimation equations with REE_IC. At the same time, multiple linear regressions were performed to propose possible alternative equations. The analyses were carried out by age groups and according to nutritional status. Results: All the equations showed a tendency to overestimate REE, regardless of age or nutritional status. Overall, the Ireton-Jones equation achieved the highest mean percentage difference from REE_IC at 67.1 ± 31%. The alternative new equations, containing variables of body composition, reached a higher percentage of classification within ±10% of REE_IC. Conclusions: The available equations do not adequately estimate REE in this sample of Chilean women. Although they must be validated, the new formulas proposed show better adaptation to this Chilean sample.

New predictive equations for estimating resting energy expenditure in subjects with normal weight and overweight

OBJECTIVE

The aim of this study was to develop and validate new predictive equations for estimating resting energy expenditure (REE) in subjects with normal weight and overweight, considering anthropometric parameters as well as raw variables from bioimpedance analysis (BIA).

METHODS

Adult participants with normal weight and overweight were recruited and randomly split into calibration and validation groups. Indirect calorimetry (IC) and BIA were performed in all subjects. New predictive equations were developed using the following models: model 1 with age, weight, stature, and body mass index (BMI) as predictors; and model 2: model 1 + raw BIA variables (bioimpedance index and phase angle). The accuracy of the new equations at both the group (bias) and individual (within ±10%) levels was tested in the validation group. Three published predictive equations were also compared, with the REE values measured by IC.

RESULTS

A total of 2483 adults were included for developing and validating the new equations. All selected formulas, including the new ones, showed a bias of <5% in estimating REE at the group level. Accuracy at the individual level was slightly higher for the new equations, especially for the equation based on raw BIA variables (men = 70.3%; women = 72.3%).

CONCLUSIONS

Compared to the equations in the literature, the new equations showed good accuracy at both the group and individual levels, with a slight improvement in individual accuracy for the formula including raw BIA variables. However, future research is required to verify the role of the raw BIA variables in predicting REE in subjects with normal weight and overweight.

Accuracy of resting metabolic rate prediction equations among healthy adults in Trinidad and Tobago

BACKGROUND

Over 50% of adults in Latin America and the Caribbean have a body mass index (BMI) ≥ 25 suggesting excess energy intakes relative to energy expenditure. Accurate estimation of resting metabolic rate (RMR), the largest component of total energy requirements, is crucial to strategies aimed at reducing the prevalence and incidence of overweight and obesity.

AIM

We evaluated the accuracies of established and locally developed RMR prediction equations (RMR_P) among adults.

METHODS

Four hundred adult volunteers ages 20 to 65 years had RMR measured (RMR_M) with a MedGem® indirect calorimeter according to recommended procedures. RMR_P were compared to RMR_M with values ± 10% of RMR_M deemed accurate. Anthropometry was measured using standard procedure. Linear regression with bootstrap analyses was used to develop local RMR_P equations based on anthropometric and demographic variables. The University of the West Indies Ethics Committee approved the study.

RESULTS

Males had higher mean absolute RMR (p < 0.001) but similar mean age-adjusted measured RMR per kg of body (20.9 vs. 21.5 kcals/day; p = 0.1) to females. The top performing established anthropometry-based RMR_P among participants by sex, physical activity (PA) level and BMI status subgroups were Mifflin-St Jeor, Owen, Korth, Harris-Benedict, and Livingston, while Johnstone, Cunningham, Müller (body composition (BC)), Katch and McArdle, Mifflin-St Jeor (BC) were the most accurate BC-based RMR_P. Locally developed RMR_P had accuracies comparable to their top-ranked established RMR_P counterparts.

CONCLUSIONS

Accuracies of established RMR_P depended on habitual PA level, BMI status, BC and sex. Furthermore, locally developed RMR_P provide useful alternatives to established RMR_P.

Resting Energy Expenditure during Breastfeeding: Body Composition Analysis vs. Predictive Equations Based on Anthropometric Parameters

Accurate estimation of energy expenditure in a breastfeeding woman is crucial for maintaining the proper nutritional status of the woman and healthy development of the infant. The current literature does not contain data regarding resting energy expenditure (REE) in breastfeeding women. Using mathematical equations is the most common method of REE assessment. However, due to changes in metabolism and body composition during pregnancy and lactation, the mathematical equations used among the general population may not apply. The aim of this study was to evaluate the resting energy expenditure of exclusively breastfeeding women by using body composition analysis–estimated REE (eREE) and to provide the most appropriate predictive equations–predicted REE (pREE) based on anthropometric parameters to estimate it. This was a pilot study with 40 exclusively breastfeeding women. Height and weight were measured and body composition analysis was performed. We predicted REE using fourteen self-selected equations, based on anthropometric parameters and/or age, and/or sex. The median eREE was 1515.0 ± 68.4 kcal (95% Cl, 1477–1582 kcal) and the pREE ranged from 1149.7 kcal (95% Cl, 1088.7–1215.0) by Bernstein et al., to 1576.8 kcal (95% Cl, 1479.9–1683.4), by Müller et al. Significant differences between eREE and all pREE were observed (p < 0.001, except Korth et al. equations). The Müller et al. equation was the most accurate with the smallest individual variation. All predictive equations showed low agreement, and in most cases, the results were underestimated. These findings indicate the need for further studies to propose more suitable methods to determine the energy requirements for breastfeeding women.

Association of Basal Metabolic Rate and Nutrients Oxidation with Cardiometabolic Risk Factors and Insulin Sensitivity in Sedentary Middle-Aged Adults

This cross-sectional study aimed to examine the association of basal metabolic rate (BMR) and basal fat and carbohydrate oxidation (BFox and BCHox, respectively) with cardiometabolic risk factors and insulin sensitivity in sedentary middle-aged adults. A total of 71 healthy sedentary adults (37 women) aged 40–65 years participated in the current study. Data were collected during the baseline assessments of the FIT-AGEING randomized controlled trial. BMR was measured via indirect calorimetry, and BFox and BCHox estimated by stoichiometric equations. Blood pressure, glucose, insulin, total cholesterol, high-density lipoprotein cholesterol, low-density lipoprotein cholesterol, and triglycerides plasma levels were selected as cardiometabolic risk factors and assessed following standard procedures. We observed positive associations of BMR with plasma insulin and the homeostatic model assessment of insulin resistance index (HOMA; all p < 0.05) which were attenuated or disappeared after controlling by sex, age, and/or lean mass. There were positive associations between BFox and the quantitative insulin sensitivity check index (QUICKI; p < 0.015), while negative associations were noted between BFox and plasma insulin and HOMA (p < 0.015). There was a significant negative association between BCHox with QUICKI (p < 0.01), whereas significant positive relationships were obtained when BCHox was associated with plasma insulin and HOMA (p < 0.01). These associations persisted in almost all cases when controlling by sex, age and/or lean mass. No further relationships were found when BMR, BFox, and BCHox were associated with other cardiometabolic risk factors. In conclusion, our study findings support that greater BFox and lower BCHox are related to improved insulin sensitivity, whereas BMR seems to be not associated with neither cardiometabolic risk nor insulin sensitivity in sedentary middle-aged adults. Further intervention studies are necessary to well-understand the physiological mechanism implied in this relationship.

Association between sleep quality and time with energy metabolism in sedentary adults

The aim of the present study was to investigate the relationship of sleep quality and time with basal metabolic rate (BMR) and fuel oxidation in basal conditions and during exercise in sedentary middle-aged adults. We also studied the mediation role of dietary intake and adherence to the traditional Mediterranean Diet in the relationship between sleep parameters and energy metabolism parameters.A secondary analysis of the FIT-AGEING study was undertaken. 70 middle-aged sedentary adults (40-65 years old) participated in the present study. Sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI) and wrist accelerometers (ActiSleep, Actigraph, Pensacola, Florida, USA) for 7 consecutive days. BMR was measured with indirect calorimetry and fuel oxidation was estimated through stoichiometric equations. Maximal fat oxidation was determined by a walking graded exercise test and dietary intake with 24 h recalls. Adherence to the traditional Mediterranean diet was assessed through the PREDIMED questionnaire. PSQI global score (poor sleep quality) was associated with lower basal fat oxidation (BFox), both expressed in g/min and as a percentage of BMR, independently of confounders. We did not find any association between other sleep and energy metabolism parameters. No mediating role of the dietary intake or PREDIMED global score was observed in the association of PSQI and BFox. In conclusion, our study showed that a subjective poor sleep quality was associated with lower BFox, which is not mediated by dietary intake in sedentary adults.

Metabolic rate in sedentary adults, following different exercise training interventions: The FIT-AGEING randomized controlled trial

BACKGROUND & AIMS

This study compares the influence of different exercise training programs on basal metabolic rate (BMR) and fat oxidation, in basal conditions (BFox) and during exercise (MFO), in sedentary, middle-aged adults.

METHODS

The study subjects of this 12 week-long, randomised controlled trial, were 71 middle-aged adults (age 53.5 ± 4.9 years; 52% women). Subjects were randomly assigned to one of the following groups: (1) no exercise, (2) concurrent training based on international physical activity recommendations (PAR group), (3) high intensity interval training (HIIT group), and (4) high intensity interval training plus whole-body electromyostimulation (HIIT + EMS group). Subject BMR, BFox and MFO were determined by indirect calorimetry before and after the intervention.

RESULTS

The HIIT + EMS subjects showed significant increases in BFox following the intervention compared with the control group (all P = 0.043); no such differences were seen in the PAR and HIIT compared with the control group (all P ≥ 0.1). A significant increase in post-intervention MFO was noted for the HIIT and HIIT + EMS group compared to the non-exercise control group (P < 0.05); no such difference was seen in the PAR group compared to the control group (all P ≥ 0.05).

CONCLUSIONS

Twelve weeks of high intensity interval training plus whole-body electromyostimulation may increase the BFox and MFO of middle-aged sedentary adults. These findings have important clinical implications; a well-designed high-intensity interval training program plus whole-body electromyostimulation might be followed to help combat the appearance of chronic metabolic diseases characterized by metabolic inflexibility in middle-aged sedentary adults, though it will be necessary to determine how long the effects last.

Are predictive equations a valid method of assessing the resting metabolic rate of overweight or obese former athletes?

Athletes retiring from their sports career, an understudied population, are susceptible to become overweight/obese because of decreased energy expenditure not followed by a reduction in energy intake. Therefore, their energy requirements, through resting metabolic rate (RMR), should be accurately addressed for weight management purposes. This study aimed to determine the validity of predictive equations (PEq) for RMR estimation using indirect calorimetry as the reference method in a sample of overweight/obese former athletes. The study uses cross-sectional data collected during baseline measurements of a lifestyle intervention (NCT03031951). The RMR of 56 overweight/obese (31.5 (4.0 kg/m²)) individuals (78.6% male, 37.5% obese, 95.8 (14.8 kg), 174.2 (8.7 cm)) was measured by indirect calorimetry and predicted using seven PEq: Harris-Benedict, Cunningham, Schofield, FAO/WHO/UNU, Owen, Mifflin-St. Jeor, and Katch-McArdle. Dual-energy X-ray absorptiometry was used to assess body composition. The PEq overestimated the RMR measured by the indirect calorimetry, 70-300 kcal/day (4.3-14.9%). The linear regression between the reference and each of the PEq did not differ from the identity line with estimated values explaining around 50% of the variability of the measured values. The agreement between the methods was weak for all the PEq showing wide limits of agreement. The Harris-Benedict equation was the only one in which the difference between the methods was not related to the magnitude of the measured RMR. Given the weak performance of the various RMR models in overweight/obese former athletes, an effective weight management intervention based on estimated resting energy requirements may be compromised.

Association of basal metabolic rate and fuel oxidation in basal conditions and during exercise, with plasma S-klotho: the FIT-AGEING study

S-klotho, the shed form of α-klotho, is thought to be an ageing suppressor with functions related to the physiology of energy metabolism. However, it remains unknown whether ageing biomarkers such as S-klotho and/or chronological ageing are associated in any way with basal metabolic rate (BMR) and fuel oxidation in basal conditions and during exercise. The present work investigates the association of BMR and fuel oxidation in basal conditions and during exercise, with plasma S-klotho in middle-aged, sedentary adults. BMR was measured by indirect calorimetry in 74 such subjects (53% women; age 53.7±5.1 years) following standard procedures, and their fuel oxidation estimated via stoichiometric equations. The maximal fat oxidation during exercise (MFO) and the intensity of exercise that elicits MFO (Fat_max) were determined using a walking graded exercise test. No relationship was seen between BMR and plasma S-klotho (P>0.1), although both basal fat oxidation and MFO showed positive associations with this protein (both P<0.001); these relationships persisted after controlling for age, sex and fat mass. However, no significant associations were seen between BMR, basal fat oxidation or MFO and chronological age (all P>0.1). The present findings suggest that basal fat oxidation and MFO are strongly associated with plasma S-klotho in middle-aged sedentary adults. These results support the idea that metabolic flexibility is a powerful predictor of biological ageing.

Ruiz J. Energy expenditure differences across lying, sitting, and standing positions in young healthy adults

The time spent in sedentary behaviour represents an important public health burden. To reduce sedentary time in the general population, the simplest, most effective, and most accessible method is to decrease lying and sitting time. We aimed to compare differences on energy expenditure (EE) across lying, sitting, and standing positions; and to analyse the associations between the change on EE of changing from one position to another and anthropometric and body composition parameters in young healthy adults. A total of 55 (69% women) young healthy adults aged 21.7 ± 2.2 participated in the study. We measured EE by indirect calorimetry across lying, sitting, and standing positions following the standard procedures. The EE was significantly higher in standing than in both lying and sitting positions (mean difference: 0.121±0.292 and 0.125±0.241 kcal/min, respectively; all P<0.001), and no differences were observed between lying and sitting positions (P = 1.000). There was a negative association between the EE differences in sitting vs. standing position and lean body mass (P = 0.048), yet no associations between EE differences with the rest of the anthropometric and body composition parameters were observed in each position pair studied (all P>0.321). Our findings support the fact that increasing the time spent standing could be a simple strategy to slightly increase EE. Therefore, our results have important clinical implications including a better monitoring, characterizing, and promoting countermeasures to sedentariness through low-level physical activities.