Predicting resting energy expenditure in young adults

Evaluating predictive equations for energy requirements throughout breast cancer trajectory: A comparative study

BACKGROUND & AIMS

Accurately estimating resting energy requirements is crucial for optimizing energy intake, particularly in the context of patients with varying energy needs, such as individuals with cancer. We sought to evaluate the agreement between resting energy expenditure (REE) predicted by 40 equations and that measured by reference methods in women undergoing active breast cancer treatment stage (I-IV) and post-completion (i.e., survivors).

METHODS

Data from 4 studies were combined. REE values estimated from 40 predictive equations identified by a systematic search were compared with REE assessed by indirect calorimetry (IC) using a metabolic cart (MC-REE N = 46) or a whole-room indirect calorimeter (WRIC-REE N = 44). Agreement between methods was evaluated using Bland-Altman and Lin's concordance coefficient correlation (Lin's CCC).

RESULTS

Ninety participants (24 % survivors, 61.1% had early-stage breast cancer I or II, mean age: 56.8 ± 11 years; body mass index: 28.7 ± 6.4 kg/m2) were included in this analysis. Mean MC-REE and WRIC-REE values were 1389 ± 199 kcal/day and 1506 ± 247 kcal/day, respectively. Limits of agreement were wide for all equations compared to both MC and WRIC (∼300 kcal for both methods), including the most commonly used ones, such as Harris-Benedict and Mifflin ST. Jeor equations; none had a bias within ±10% of measured REE, and all had low agreement per Lin's CCC analysis (<0.90). The Korth equation exhibited the best performance against WRIC and the Lvingston-Kohlstadt equation against MC. Similar patterns of bias were observed between survivors and patients and between patients with stages I-III versus IV cancer.

CONCLUSION

Most equations failed to accurately predict REE at the group level, and none were effective at the individual level. This inaccuracy has significant implications for women with or surviving breast cancer, who may experience weight gain, maintenance, or loss due to inaccurate energy needs estimations. Therefore, our research underscores the need for further efforts to improve REE estimation.

Single-nuclei RNA Profiling Reveals Disruption of Adipokine and Inflammatory Signaling in Adipose Tissue of Burn Patients

OBJECTIVE

We conducted a large-scale investigation of the systemic and adipose tissue-specific alterations in a clinical population of burn patients to identify factors that may influence hypermetabolism.

BACKGROUND

Previous research has identified chronic disturbances in adipose tissue inflammation, lipolysis, and browning, which may drive the perpetuation of hypermetabolism following the severe adrenergic stress of a burn injury. Given that adipose tissue is thought to be a central node in the regulation of systemic metabolism, we believe that systematically delineating the pathologic role of adipose tissue postburn, will lead to the identification of novel interventions to mitigate morbidity and mortality from severe burns.

METHODS

This was a single-institution cohort study, which obtained plasma and subcutaneous adipose tissue samples from severely burn adult patients over various time points during acute hospitalization. Whole-body clinical, metabolic, and inflammatory mediators were assessed in plasma, while genetic analyses through RT-qPCR and single-nuclei RNA sequencing were conducted in adipose tissue.

RESULTS

Systemic inflammation and adrenergic stress increase IL-6 signaling, lipolysis, browning, and adipokine dysfunction in the adipose tissue of adult burn patients, which may further propagate the long-term hypermetabolic response. Moreover, using single-nuclei RNA sequencing, we provide the first comprehensive characterization of alterations in the adipose tissue microenvironment occurring at acute and chronic stages postburn.

CONCLUSION

We provide novel insight toward the effect of burns on adipokine release, inflammatory signaling pathways, and adipose heterogeneity over the trajectory of acute and chronic stages.

New predictive equations to estimate resting energy expenditure of non-dialysis dependent chronic kidney disease patients

BACKGROUND

Determination of resting energy expenditure (REE) is an important step for the nutritional and medical care of patients with chronic kidney disease (CKD). Methods such as indirect calorimetry or traditional predictive equations are costly or inaccurate to estimate REE of CKD patients. We aimed to develop and validate predictive equations to estimate the REE of non-dialysis dependent-CKD patients.

METHODS

A database comprising REE measured by indirect calorimetry (mREE) of 170 non-dialysis dependent-CKD patients was used to develop (n = 119) and validate (n = 51) a new REE-predictive equation. Fat free mass (FFM) was assessed by anthropometry and by bioelectrical impedance (BIA).

RESULTS

The multiple regression analysis generated three equations: (1) REE (kcal/day) = 854 + 7.4*Weight + 179*Sex - 3.3*Age + 2.1 *eGFR + 26 (if DM) (R² = 0.424); (2) REE (kcal/day) = 678.3 + 14.07*FFM.ant + 54.8*Sex - 2*Age + 2.5*eGFR + 140.7* (if DM) (R² = 0.449); (3) REE (kcal/day) = 668 + 17.1*FFM.BIA - 2.7*Age - 92.7*Sex + 1.3*eGFR - 152.3 (if DM) (R² = 0.45). The estimated REE (eREE) was not different from the mREE (P = 0.181), a high ICC was found and the mean difference between mREE and eREE was not different from zero for the three equations in the validation group. eREE accuracy between 90 and 110% was observed in 55.3%, 62.5% and 61% of the patients for Eqs. (1), (2) and (3), respectively.

CONCLUSION

The equations showed acceptable accuracy for REE prediction making them a valuable tool to support practitioners to provide more reliable energy recommendations for this group of patients.

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.

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.

Predictive equations for estimating resting energy expenditure in women with overweight and obesity at three postpartum stages

The objective was to investigate which predictive equations provide the best estimates of resting energy expenditure (REE) in postpartum women with overweight and obesity. Lactating women with overweight or obesity underwent REE measurement by indirect calorimetry, and fat-free mass (FFM) was assessed by dual-energy X-ray absorptiometry at three postpartum stages. Predictive equations based on body weight and FFM were obtained from the literature. Performance of the predictive equations were analysed as the percentage of women whose REE was accurately predicted, defined as a predicted REE within ±10 % of measured REE. REE data were available for women at 10 weeks (n 71), 24 weeks (n 64) and 15 months (n 57) postpartum. Thirty-six predictive equations (twenty-five weight-based and eleven FFM-based) were validated. REE was accurately predicted in ≥80 % of women at all postpartum visits by six predictive equations (two weight-based and four FFM-based). The weight-based equation with the highest performance was that of Henry (weight, height, age 30-60 years) (Henry_WH30-60), with an overall mean of 83 % accurate predictions. The Henry_WH30-60 equation was highly suitable for predicting REE at all postpartum visits (irrespective of the women's actual age), and the performance was sustained across changes in weight and lactation status. No FFM-based equation was remarkably superior to Henry_WH30-60 for the total postpartum period.

Development of new predictive equations for basal metabolic rate in Iranian healthy adults: negligible effect of sex

Some studies have reported inaccuracy of predicting basal metabolic rate (BMR) by using common equations for Asian people. Thus, this study was undertaken to develop new predictive equations for the Iranian community and also to compare their accuracy with the commonly used formulas. Anthropometric measures and thyroid function were evaluated for 267 healthy subjects (18-60 y). Indirect calorimetry (InCal) was performed only for those participants with normal thyroid function tests (n = 252). Comparison of predicted RMR (both kcal/d and kcal.kg.wt^-1.d^-1) using current predictive formulas and measured RMR revealed that Harris-Benedict and FAO/WHO/UNU significantly over-estimated and Mifflin-St. Jeor significantly under-estimated RMR as compared to InCal measurements. In stepwise regression analysis for developing new equations, the highest r² (=0.89) was from a model comprising sex, height and weight. However, further analyses revealed that unlike the subjects under 30 y, the association between age and the measured RMR in subjects 30 y and plus was negative (r = -0.241, p = 0.001). As a result, two separate equations were developed for these two age groups. Over 80 percent of variations were covered by the new equations. In conclusion, there were statistical significant under- and over-estimation of RMR using common predictive equations in our subjects. Using the new equations, the accuracy of the calculated RMR increased remarkably.

Validation of predictive equations for resting energy expenditure in treatment-seeking adults with overweight and obesity: Measured versus estimated

The quantification of resting energy expenditure (REE) in patients with obesity is an important measure. We aimed to evaluate the validity of predictive equations in estimating REE compared with indirect calorimetry (IC) in treatment-seeking Arab adults with overweight or obesity. Twenty-three predictive equations were compared with REE values measured by IC (Vmax Encore 229) in 89 adult participants with overweight or obesity (mean age = 40.62 ± 15.96 years and mean body mass index [BMI] = 35.02 ± 4.60 kg/m²) referred to the Department of Nutrition and Dietetics of Beirut Arab University (Lebanon). The accuracy of the predictive equations was evaluated on the basis of whether the percentage prediction was within 10% of the measured REE, and the mean difference between predicted and measured values (bias). The Bland-Altman method was used to assess the agreement between the predicted and measured values. The equations that demonstrated the closest agreement with IC were the De La Cruz equation in males (accurate predictions: 68.2%; bias: -19.52 kcal/day) and the Mifflin equation in females (accurate prediction: 61.2%; bias: -36.43 kcal/day). In conclusion, we suggest that these two equations produce the least biased estimations for REE in this population.

ENERGY EXPENDITURE IN 21-HYDROXYLASE CONGENITAL ADRENAL HYPERPLASIA PATIENTS AND COMPARISON WITH PREDICTIVE EQUATIONS

Objective: To characterize resting energy expenditure (REE) in patients with classic 21-hydroxylase congenital adrenal hyperplasia (21-OH CAH) using indirect calorimetry and compare it to the most commonly used REE predictive equations. Methods: This case-control study comprised 29 post-pubertal 21-OH CAH patients regularly followed at the University of Campinas. Elevated serum 17-hydroxyprogesterone and CYP21 gene molecular analysis confirmed the diagnosis. A healthy control group paired by age, gender, and body mass index was examined. Dual-energy X-ray absorptiometry (DEXA) measured body compositions. A bioimpedance analyzer determined fat-free mass, and indirect calorimetry using a metabolic cart measured REE. Results: Unlike our initial hypothesis, REE was similar between the groups (18.7 ± 3.1 kcal/kg/day in CAH vs. 20.3 ± 3.5 kcal/kg/day in controls; P = .728). No predictive equations reached the stipulated accuracy criteria, thus lacking validity in REE assessment in adults with the characteristics of the group studied. DEXA analysis revealed higher body fat and diminished nonbone lean mass in 21-OH CAH. Anthropometric and bioelectrical impedance parameters were not significantly different. Conclusion: Classic 21-OH CAH is generally followed in reference centers, which may facilitate indirect calorimetry use for REE measurement. Alternatively, considering our REE findings in adult 21-OH CAH patients, nutrition management based on 25 kcal/body weight/day (measured REE × activity factor 1.2 to 1.3) may be reasonable for current body weight maintenance in these patients. Abbreviations: 17-OHP = 17-hydroxyprogesterone; 21-OH CAH = classic 21-hydroxylase deficiency congenital adrenal hyperplasia; BMI = body mass index; REE = resting energy expenditure; VO2 = volume of oxygen; VCO₂ = volume of carbon dioxide.

Predicting Equations and Resting Energy Expenditure Changes in Overweight Adults

Introduction

The aim of the study is to show the differences between the measured and estimated values of resting energy expenditure and any changes occurring after the 6-month weight loss intervention program.

Methods

We included 33 healthy adults aged 25–49 years with an average body mass index 29.1±2.7 kg/m 2 for female and 29.8±2.8 kg/m² for male. The measured resting energy expenditure was obtained by indirect calorimeter MedGem® Microlife and estimated resting energy expenditure by the Harris–Benedict equation, the Mifflin–St Jeor equation, the Owen equation, the Wright equation, and by the Tanita body composition analyser. All measurements and calculations were carried out before and after the 6-month intervention. Results were compared using paired t-tests. P value less than 0.05 was considered statistically significant.

Results

A comparison of the measured resting energy expenditure of female subjects with the estimated resting energy expenditure using the Harris–Benedict equation, the Mifflin–St Jeor equation and the Wright equation showed a statistically significant difference. A comparison of the measured resting energy expenditure of male subjects with the estimated resting energy expenditure using the Harris–Benedict equation and the Wright equation showed a statistically significant difference. There was a significant difference in the measured resting energy expenditure and estimated resting energy expenditure using Tanita.

Conclusions

We concluded that the most comparable equation for our sample was the Owen’s equation. After losing weight, the measured resting energy expenditure has decreased, which must be taken into account in further diet therapy.

Exercise prescription in patients with cirrhosis: Recommendations for clinical practice

Exercise in cirrhosis of the liver is an emerging topic in hepatology. Despite the known benefits of exercise in the general population, there are currently few studies addressing that issue in relation to cirrhosis and more evidence is still needed. Even though some studies have reported an acute, exercise-induced increase in the hepatic venous pressure gradient (HVPG), the opposite (a decrease in the HVPG) has been shown by recent data after an exercise program carried out for>14 weeks. In addition to that benefit, improvement has been described in the metabolic profile, quality of life, muscle mass, cardiopulmonary function, and nutritional status. Together, those features make exercise in cirrhosis a very attractive intervention. However, certain aspects must be taken into account before prescribing exercise in that population and they include cardiovascular risk, musculoskeletal disorders, and complications related to cirrhosis. After considering those factors, an individually tailored exercise program should be developed for each patient, according to the points stated above and the desired goal. Information about exercise-limiting factors, type of exercise prescribed, monitoring methods, and concomitant nutritional therapy is provided in the present review.

Congruent Validity of Resting Energy Expenditure Predictive Equations in Young Adults

Having valid and reliable resting energy expenditure (REE) estimations is crucial to establish reachable goals for dietary and exercise interventions. However, most of the REE predictive equations were developed some time ago and, as the body composition of the current population has changed, it is highly relevant to assess the validity of REE predictive equations in contemporary young adults. In addition, little is known about the role of sex and weight status on the validity of these predictive equations. Therefore, this study aimed to investigate the role of sex and weight status in congruent validity of REE predictive equations in young adults. A total of 132 young healthy adults (67.4% women, 18⁻26 years old) participated in the study. We measured REE by indirect calorimetry strictly following the standard procedures, and we compared it to 45 predictive equations. The most accurate equations were the following: (i) the Schofield and the "Food and Agriculture Organization of the United Nations/World Health Organization/United Nations" (FAO/WHO/UNU) equations in normal weight men; (ii) the Mifflin and FAO/WHO/UNU equations in normal weight women; (iii) the Livingston and Korth equations in overweight men; (iv) the Johnstone and Frankenfield equations in overweight women; (v) the Owen and Bernstein equations in obese men; and (vi) the Owen equation in obese women. In conclusion, the results of this study show that the best equation to estimate REE depends on sex and weight status in young healthy adults.

Accuracy and Validity of Resting Energy Expenditure Predictive Equations in Middle-Aged Adults

Indirect calorimetry (IC) is considered the reference method to determine the resting energy expenditure (REE), but its use in a clinical context is limited. Alternatively, there is a number of REE predictive equations to estimate the REE. However, it has been shown that the available REE predictive equations could either overestimate or underestimate the REE as measured by IC. Moreover, the role of the weight status in the accuracy and validity of the REE predictive equations requires further attention. Therefore, this study aimed to determine the accuracy and validity of REE predictive equations in normal-weight, overweight, and obese sedentary middle-aged adults. A total of 73 sedentary middle-aged adults (53% women, 40⁻65 years old) participated in the study. We measured REE by indirect calorimetry, strictly following the standard procedures, and we compared it with the values obtained from 33 predictive equations. The most accurate predictive equations in middle-aged sedentary adults were: (i) the equation of FAO/WHO/UNU in normal-weight individuals (50.0% of prediction accuracy), (ii) the equation of Livingston in overweight individuals (46.9% of prediction accuracy), and (iii) the equation of Owen in individuals with obesity (52.9% of prediction accuracy). Our study shows that the weight status plays an important role in the accuracy and validity of different REE predictive equations in middle-aged adults.

Dietary management and supplementation with branched-chain amino acids in cirrhosis of the liver

One of the most important characteristics of malnutrition is the loss of muscle mass and the severe depletion of the protein reserve, secondarily affecting energy metabolism. That impacts nutritional status and the progression of disease-related complications. Nutritional treatment is one of the main factors in the comprehensive management of those patients. Achieving adequate energy intake that provides the macronutrients and micronutrients necessary to prevent or correct malnutrition is attempted through dietary measures. ESPEN, the European Society for Clinical Nutrition and Metabolism, recommends a caloric intake of 30-40kcal/kg/day, in which carbohydrates provide 45-60% of the daily energy intake and proteins supply 1.0-1.5g/kg/day. The remaining portion of the total energy expenditure should be covered by lipids. The administration of branched-chain amino acids has been shown to be beneficial not only in counteracting malnutrition, but also as a coadjuvant treatment in specific complications, thus playing a favorable role in outcome and quality of life. Therefore, branched-chain amino acids should be considered part of nutritional treatment in patients with advanced stages of cirrhosis of the liver, particularly in the presence of complications.