Resting energy expenditure in elite athletes: development of new predictive equations based on anthropometric variables and bioelectrical impedance analysis derived phase angle.

BACKGROUND: An accurate estimation of athletes' energy needs is crucial in diet planning to improve sport performance and to maintain an appropriate body composition. This study aimed to develop and validate in elite athletes new equations for estimating resting energy expenditure (REE) based on anthropometric parameters as well as bioimpedance analysis (BIA)-derived raw variables and to validate the accuracy of selected predictive equations. METHODS: Adult elite athletes aged 18-40 yrs were studied. Anthropometry, indirect calorimetry and BIA were performed in all subjects. The new predictive equations were generated using different regression models. The accuracy of the new equations was assessed at the group level (bias) and at the individual level (precision accuracy), and then compared with the one of five equations used in the general population or three athletes-specific formulas. RESULTS: One-hundred and twenty-six male athletes (age 26.9 ± 9.1 yrs; weight 71.3 ± 10.9 kg; BMI 22.8 ± 2.7 kg/m2) from different sport specialties were randomly assigned to the calibration (n = 75) or validation group (n = 51). REE was directly correlated with individual characteristics, except for age, and raw BIA variables. Most of the equations from the literature were reasonably accurate at the population level (bias within ±5%). The new equations showed a mean bias -0.3% (Eq. A based on anthropometric parameters) and -0.6% (Eq. B based on BIA-derived raw variables). Precision accuracy (individual predicted-measured differences within ±5%) was ~75% in six out of eight of the selected equations and even higher for Eq. A (82.4%) and Eq. B (92.2%). CONCLUSION: In elite athletes, BIA-derived phase angle is a significant predictor of REE. The new equations have a very good prediction accuracy at both group and individual levels. The use of phase angle as predictor of REE requires further research with respect to different sport specialties, training programs and training level.

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.

Prediction of resting energy expenditure in healthy older adults: A systematic review.

BACKGROUND & AIMS: Estimates of energy requirements, based on measured or predicted resting energy expenditure (REE), are needed to avoid undernutrition or overnutrition (and their clinical consequences) in elderly subjects. The aims of this systematic review were to evaluate the prediction accuracy of REE in healthy elderly subjects and to ascertain which equation is more reliable at group level and/or individual level. METHODS: Studies assessing prediction of REE in general elderly population were systematically searched using PubMed, EMBASE, Web of Science and CINAHL until March 2020. Prediction accuracy of REE was assessed at both group (bias) and individual (precision) level for each equation. RESULTS: Fourteen studies met the inclusion criteria of this systematic review. Bias was reported in 8 papers and calculated in another 5 from absolute values. There was a prevalent tendency towards an overestimation of REE across the studies. The least bias was observed for the Mifflin (-0.3%) and Harris-Benedict (+2.6%) equations, with values above 5% for the FAO/WHO/UNU, Fredrix and Muller equations. Precision widely varied between studies for the same equation. The higher precision was observed using the Harris-Benedict equation (~70%), while the Henry and Mifflin equations provided estimates within 10% of measured values in 65% and 61% of elderly individuals, respectively. CONCLUSIONS: None of the prediction equations considered provides accurate and precise REE estimates in healthy older adults. However, the best prediction is given by the Mifflin equation at group level and by the Harris-Benedict equation at individual level. Further studies with strong quality design are needed to evaluate the variability and accuracy of REE in the elderly general population.

Acute assessment of subjective appetite and implicated hormones after a hypnosis-induced hallucinated meal: a randomized cross-over pilot trial.

The use of hypnosis can generate hallucinatory phenomena, which ranged from vivid/auditory imagery to fully developed "hallucinations" in selected people. The aim of this pilot trial was investigating the acute effects of a hypnosis-induced hallucinated breakfast (HB) compared to those of a real breakfast (RB) on subjective appetite and appetite-regulating hormones in highly hypnotizable individuals. Eight healthy post-menopausal women were recruited to consume two meals: the HB and the RB in a randomized crossover design. Participants underwent appetite sensations measurements (before meal and each 30-min until 270-min) and blood sample collection (at 0, 20, 60, 90, 180-min). A 3-day food-record was filled after each meal. The adjusted repeated measures ANCOVA did not show any meal×time interactions on subjective appetite postprandially. As expected, significantly higher glucose (p < 0.001), insulin (p < 0.001), and lower free fatty acid (p < 0.001) concentrations were found after the RB, but not following HB. Furthermore, RB significantly increased postprandial levels of glucagon-like-peptide-1 and peptide-YY at 20, 60, 90 and 180-min, whereas acylated-ghrelin and leptin levels did not differ. Postprandial neuropeptide-Y and orexin-A values significantly increased at different time-points after RB, but not following HB, while α-melanocyte-stimulating hormone levels enhanced after HB only. Energy intakes were significantly lower after HB on the test-day only (HB = 1146.6 ± 343.8 vs RB = 1634.7 ± 274.2 kcal/d; p = 0.003). Appetite sensation might be modulated by fully developed meal "hallucination" induced by hypnosis, likely affecting brain-peptides implicated in the appetite regulation. However, further studies are needed to verify these results obtained in a highly selected group of individuals. NCT03934580.

New Predictive Equations for Estimating Resting Energy Expenditure in Adults With Crohn's Disease.

BACKGROUND: Increased resting energy expenditure (REE) has been hypothesized to be a potential cause of weight loss in individuals with Crohn's disease (CD). This study aimed to develop and validate new predictive equations for estimating REE in adults with CD. METHODS: Adults, ages 18-65 years, with CD were recruited. Anthropometry, indirect calorimetry, and bioimpedance analysis were performed in all patients. Disease activity was assessed by Crohn's Disease Activity Index. The new predictive equations were generated using different regression models. Prediction accuracy of the new equations was assessed and compared with the most commonly used equations. RESULTS: A total of 270 CD patients (159 males, 111 females) were included and randomly assigned to the calibration (n = 180) and validation groups (n = 90). REE was directly correlated with weight and bioimpedance index, whereas the relation with both age and disease activity was inverse. The new equations were suitable for estimating REE at population level (bias: -0.2 and -0.3, respectively). Individual accuracy was good in both models (≥80%, respectively), especially in females; and similar results were shown by some of the selected equations. But, when accuracy was set within ±5%, the new equations gave the highest prediction. CONCLUSION: The new, disease-specific, equations for predicting REE in individuals with CD give a good prediction accuracy as far as those proposed in the literature for the general population. However, the new ones performed better at the individual level. Further studies are needed to verify the reliability and usefulness of these new equations.

Assessment of bioelectrical phase angle as a predictor of nutritional status in patients with Crohn's disease: A cross sectional study.

BACKGROUND & AIMS: The assessment of body composition (BC) can be used to identify malnutrition in patients with Crohn's disease (CD). The aim of this study was to evaluate the nutritional status of CD patients by assessing BC, phase angle (PhA) and muscle strength. Differences in disease duration and medications were also considered. METHODS: Consecutive adult CD patients aged 18-65 years were enrolled in this cross-sectional study. Disease activity was clinically defined by the Crohn's Disease Activity Index (CDAI) in the active and quiescent phases. All participants underwent anthropometry, BC and handgrip-strength (HGS) measurements; additionally, blood samples were taken. Data from CD patients were also compared with age-, sex- and BMI-matched healthy people. RESULTS: A total of 140 CD patients with a mean age of 38.8 ± 13.9 years and a mean body weight of 64.9 ± 12 kg were recruited and compared to controls. The findings showed that all nutritional parameters, especially PhA and HGS, were lower in CD patients than in controls, and these parameters were substantially impaired as disease activity increased. Active CD patients had a lower body weight and fat mass than both the quiescent and control groups. PhA was negatively correlated with age (r = -0.362; p = 0.000) and CDAI (r = -0.135; p = 0.001) but was positively associated with fat free mass (FFM) (r = 0.443; p = 0.000) and HGS (r = 0.539; p = 0.000). Similarly, serum protein markers were lower in the active CD group than in the quiescent group (p < 0.05). Disease duration and medications did not significantly affect nutritional status. CONCLUSIONS: BIA-derived PhA is a valid indicator of nutritional status in CD patients, and its values decreased with increasing disease activity. Additionally, small alterations in BC, such as low FFM, and reduced HGS values can be considered markers of nutritional deficiency. Therefore, the assessment of BC should be recommended in clinical practice for screening and monitoring the nutritional status of CD patients.

Are Raw BIA Variables Useful for Predicting Resting Energy Expenditure in Adults with Obesity?

This study aimed to develop and validate new predictive equations for resting energy expenditure (REE) in a large sample of subjects with obesity also considering raw variables from bioimpedance-analysis (BIA). A total of 2225 consecutive obese outpatients were recruited and randomly assigned to calibration (n = 1680) and validation (n = 545) groups. Subjects were also split into three subgroups according to their body mass index (BMI). The new predictive equations were generated using two models: Model 1 with age, weight, height, and BMI as predictors, and Model 2 in which raw BIA variables (bioimpedance-index and phase angle) were added. Our results showed that REE was directly correlated with all anthropometric and raw-BIA variables, while the correlation with age was inverse. All the new predictive equations were effective in estimating REE in both sexes and in the different BMI subgroups. Accuracy at the individual level was high for specific group-equation especially in subjects with BMI > 50 kg/m². Therefore, new equations based on raw-BIA variables were as accurate as those based on anthropometry. Equations developed for BMI categories did not substantially improve REE prediction, except for subjects with a BMI > 50 kg/m². Further studies are required to verify the application of those formulas and the role of raw-BIA variables for predicting REE.

Resting energy expenditure in adult patients with Crohn's disease.

BACKGROUND & AIMS: Crohn's disease (CD) is a chronic intestinal disorder of unknown etiology involving any section of the gastrointestinal tract often associated with protein-energy malnutrition (PEM). Increased resting energy expenditure (REE) unmatched by adequate dietary intake is amongst the pathogenetic mechanisms proposed for PEM. Aim of this study was to evaluate REE in CD patients receiving or not immuno-suppressive therapy as compared to controls. METHODS: 36 CD patients (22 M and 14 F, age range 18-55 years) clinically stable and without complications since at least 6 month were studied. REE was evaluated by indirect calorimetry and body composition by BIA. Full biochemistry was performed. Patients were divided into two groups: Group 1 (G1 = 12 patients) without and Group 2 (G2 = 24 patients) with immuno-suppressive therapy. RESULTS: The two groups were similar for age, height and BMI whereas significantly differed for weight (G1 vs G2: 56.9 ± 7.44 vs 62.3 ± 8.34 kg), fat free mass (FFM: 40.4 ± 5.73 vs 48.2 ± 7.06 kg), fat mass (FM: 17.0 ± 3.55 vs 13.9 ± 5.54 kg) and phase angle (PA: 5.6 ± 1.4 vs 6.5 ± 1.0°). Serum inflammation parameters were significantly higher in G1 than in G2: hs-PCR: 7.76 ± 14.2 vs 7.16 ± 13.4 mg/dl; alfa 2-protein: 11.7 ± 3.69 vs 9.74 ± 2.08 mg/dl; fibrinogen: 424 ± 174 vs 334 ± 118 mg/dl (p < 0.05). REE was higher in G2 vs G1: 1383 ± 267 vs 1582 ± 253kcal/die (p < 0.05) both in men: 1579 ± 314 vs 1640 ± 203 and women: 1267 ± 140 vs 1380 ± 132. Nevertheless, when corrected for FFM, REE resulted higher in G1 than G2 (34.8 ± 4.89 vs 33.0 ± 4.35 kcal/kg, p < 0.05) group, also higher compared to our, age and sex matched, control population (REE/FFM: 30.9 ± 4.5 kcal/kg). CONCLUSIONS: Our preliminary results show that REE when adjusted for FFM is increased in clinically stable CD patients and mildly reduced by immunosuppressive therapy possibly through a direct action on inflammation and on body composition characteristics.