Age-related changes in resting energy expenditure in normal weight, overweight and obese men and women

Prediction of resting energy expenditure in Italian older adults with severe obesity

Background

In the last decade a large number of studies proposed and/or validated equations to estimate the Resting Energy Expenditure (REE) in adults and/or older adults, however, no equation currently available showed good accuracy for older adults with severe obesity. Thus, this study aimed to develop and validate new predictive equations for REE, based on data from the indirect calorimetry, in Italian older adults with severe obesity.

Methods

A retrospective study was as conducted with 764 Caucasian older adults with severe obesity (age range: 60-74 years and BMI ≥ 35 kg/m/²). Four models were used to test the accuracy of anthropometry and body composition variables in multivariable prediction of REE. All models were derived by stepwise multiple regression analysis using a calibration group of 382 subjects [295 females and 87 males] and the equations were cross-validated in the remaining 382 subjects [295 females and 87 males] as validation group. The new prediction equations and the other published equations were tested using the Bland-Altman method. Prediction accuracy was defined as the percentage of subjects whose REE was predicted within ± 10% of measured REE.

Results

All the equations analyzed predicted higher energy requirements for males than females, and most of them underestimated the energy requirement values of our sample. The highest accuracy values were observed in the new equations, with 62% in the anthropometric model and 63% in the body composition model.

Conclusion

Although the accuracy of our equations was slightly higher in comparison with the other taken into consideration, they cannot be considered completely satisfactory for predicting REE in Italians older adults with severe obesity. When predicting equations cannot guarantee precise or acceptable values of REE, the use of indirect calorimetry (if available) should be always recommended, especially in clinical practice.

Age But Not Menopausal Status Is Linked to Lower Resting Energy Expenditure

CONTEXT

It remains uncertain whether aging before late adulthood and menopause are associated with fat-free mass and fat mass-adjusted resting energy expenditure (REEadj).

OBJECTIVES

We investigated whether REEadj differs between middle-aged and younger women and between middle-aged women with different menopausal statuses. We repeated the age group comparison between middle-aged mothers and their daughters to partially control for genotype. We also explored whether serum estradiol and FSH concentrations explain REEadj in midlife.

METHODS

We divided 120 women, including 16 mother-daughter pairs, into age groups; group I (n = 26) consisted of participants aged 17 to 21, group II (n = 35) of those aged 22 to 38, and group III (n = 59) of those aged 41 to 58 years. The women in group III were further categorized as pre- or perimenopausal (n = 19), postmenopausal (n = 30), or postmenopausal hormone therapy users (n = 10). REE was assessed using indirect calorimetry, body composition using dual-energy X-ray absorptiometry, and hormones using immunoassays.

RESULTS

The REEadj of group I was 126 kcal/day [95% confidence interval (CI): 93-160] higher than that of group III, and the REEadj of group II was 88 kcal/day (95% CI: 49-127) higher. Furthermore, daughters had a 100 kcal/day (95% CI: 63-138 kcal/day) higher REEadj than their middle-aged mothers (all P < .001). In group III, REEadj was not lower in postmenopausal women and did not vary by sex hormone concentrations.

CONCLUSIONS

We demonstrated that REEadj declines with age in women before late adulthood, also when controlling partially for genetic background, and that menopause may not contribute to this decline.

Prediction of Individual Basal Rate Profiles From Patient Characteristics in Type 1 Diabetes on Insulin Pump Therapy

BACKGROUND

Basal rate profiles in patients with type 1 diabetes on insulin pump therapy are subject to enormous inter-individual heterogeneity. Tools to predict basal rates based on clinical characteristics may facilitate insulin pump therapy.

METHODS

Data from 339 consecutive in-patients with adult type 1 diabetes on insulin pump therapy were collected. Basal rate tests were performed over 24 hours. A mathematical algorithm to predict individual basal rate profiles was generated by relating the individual insulin demand to selected clinical characteristics in an exploratory cohort of 170 patients. The predicted insulin pump profiles were validated in a confirmatory cohort of 169 patients.

FINDINGS

Basal rates (0.27 ± 0.01 IU.d^-1.kg^-1) showed circadian variations with peaks corresponding to the "dawn" and "dusk" phenomena. Age, gender, duration of pump treatment, body-mass-index, HbA_1c, and triacylglycerol concentrations largely predicted the individual basal insulin demand per day (IU/d; exploratory vs prospective cohorts: r² = 0.518, P < .0001). Model-predicted and actual basal insulin rates were not different (exploratory cohort: Δ 0.1 (95% CI -0.9; 1.0 U/d; P = .95; prospective cohort: Δ -0.5 (95% CI -1.5; 0.6 IU/d; P = .46). Similarly, precise predictions were possible for each hour of the day. Actual and predicted "dawn" index correlated significantly in the exploratory but not in the confirmatory cohort.

INTERPRETATION

Clinical characteristics predict 52% of the variation in individual basal rate profiles, including their diurnal fluctuations. The multivariate regression model can be used to initiate or optimize insulin pump treatment in patients with type 1 diabetes.

Comparison of total and activity energy expenditure estimates from physical activity questionnaires and doubly labelled water: a systematic review and meta-analysis

Physical activity questionnaires (PAQ) could be suitable tools in free-living people for measures of physical activity, total and activity energy expenditure (TEE and AEE). This meta-analysis was performed to determine valid PAQ for estimating TEE and AEE using doubly labelled water (DLW). We identified data from relevant studies by searching Google Scholar, PubMed and Scopus databases. This revealed thirty-eight studies that had validated PAQ with DLW and reported the mean differences between PAQ and DLW measures of TEE (TEEDLW - TEEPAQ) and AEE (AEEDLW - AEEPAQ). We assessed seventy-eight PAQ consisting of fifty-nine PAQ that assessed TEE and thirty-five PAQ that examined AEE. There was no significant difference between TEEPAQ and TEEDLW with a weighted mean difference of -243·3 and a range of -841·4 to 354·6 kJ/d, and a significant weighted mean difference of AEEDLW - AEE PAQ 414·6 and a range of 78·7-750·5. To determine whether any PAQ was a valid tool for estimating TEE and AEE, we carried out a subgroup analysis by type of PAQ. Only Active-Q, administered in two seasons, and 3-d PA diaries were correlated with TEE by DLW at the population level; however, these two PAQ did not demonstrate an acceptable limit of agreement at individual level. For AEE, no PAQ was correlated with DLW either at the population or at the individual levels. Active-Q and 3-d PA diaries were identified as the only valid PAQ for TEE estimation. Further well-designed studies are needed to verify this result and identify additional valid PAQ.

Association of Vitamin D status with Visceral Adiposity Index and Lipid Accumulation Product Index among a Group of Iranian People

There is a growing body of evidence linking vitamin D and its antiadipogenic activity with body composition. The aim of this study was to investigate the association between vitamin D levels, visceral adiposity index (VAI), and lipid accumulation product index among a group of Iranian people. This cross-sectional study was conducted with 270 Iranian adults. Body composition was measured via bio-impedance analysis. The 25-hydroxyvitamin D [25(OH)D] was also measured using the enzyme-linked immunosorbent assay method. The VAI and lipid accumulation product index were calculated. Multiple linear and logistic regression after controlling for confounder was used to report the results. Multiple linear regression showed that serum 25(OH)D levels were positively correlated with age (crude: β ± standard error [SE] = 0.23 ± 0.06, p ≤ 0.001; model I: β ± SE = 0.18 ± 0.05, p = 0.002) and percent body fat (crude: β ± SE = 0.10 ± 0.04, p = 0.02). Binary logistic regression analysis showed a higher chance of greater percent body fat and lipid accumulation product index in the crude model (odds ratio [OR], 2.05; 95% confidence interval [CI], 1.13–3.72 for percent body fat and OR, 2.07; 95% CI, 1.14–3.76 for lipid accumulation product index), which disappeared after adjusting for covariates. Adults with higher vitamin D levels had higher scores of percent body fat and lipid accumulation product index. More longitudinal studies are needed to confirm these results.

Long-term trends in the body mass index and obesity risk in Estonia: an age-period-cohort approach

OBJECTIVES

To analyse the age, period and cohort effects on the mean body mass index (BMI) and obesity over the past two decades in Estonia.

METHODS

Study used data from nationally representative repeated cross-sectional surveys on 11,547 men and 16,298 women from 1996 to 2018. The independent effects of age, period and cohort on predicted mean BMI and probability of obesity (BMI ≥ 30 kg/m²) were modelled using hierarchical age-period-cohort analysis.

RESULTS

Curvilinear association between age and mean BMI was found for men, whereas the increase in mean BMI was almost linear for women. The predicted mean BMI for 40-year-old men had increased by 6% and probability of obesity by 1.8 times over 1996-2018; the period effects were slightly smaller for women. Men from the 1970s birth cohort had higher mean BMI compared to the average, whereas no significant cohort effects were found for obesity outcome.

CONCLUSIONS

Population-level BMI changes in Estonia during 1996-2018 were mostly driven by period rather than cohort-specific changes.

Reduction of Resting Energy Expenditure and Sarcopenic Obesity in Adults with Overweight and Obesity: A Brief Report

BACKGROUND AND AIM

The last decade has seen the emergence of a new condition, describing the coexistence of obesity and sarcopenia, termed Sarcopenic Obesity (SO). The aim of this study was to assess the potential association between SO and reduced Resting Energy Expenditure (REE).

METHODS

Body composition and REE were measured using a bioimpedance analyser (Tanita BC-418) and Indirect Calorimeter (Vmax Encore 229), respectively in 89 adults with overweight or obesity of both genders, referred to the Outpatient Clinic of the Department of Nutrition and Dietetics at Beirut Arab University (Lebanon). Participants were then categorized on the basis of having SO or not.

RESULTS

Thirty-nine of the 89 participants met the criteria for SO (43.8%), and these participants displayed a significantly lower REE per unit body weight than those in the group without SO (19.02 ± 2.26 vs. 20.87 ± 2.77; p = 0.001). Linear regression analysis showed that the presence of SO decreases REE by 1.557 kcal/day for each kg of body weight (β = -1.557; CI = -0.261 - (-0.503); p = 0.004), after adjusting for age and gender.

CONCLUSION

SO appears to be present in a high proportion of treatment-seeking adults with overweight or obesity of both genders, and it seems to be associated with a reduced REE, compared with those without SO. Future studies are needed to clarify whether this may influence clinical outcomes.

Evaluation of Factors Associated with Hypermetabolism and Hypometabolism in Critically Ill AKI Patients

Acute kidney injury (AKI) is a frequent and serious condition with high mortality. The presence of hypermetabolism may be a factor related to poorer prognosis. This study evaluated the resting energy expenditure (REE) of intensive care unit (ICU) patients with severe AKI using indirect calorimetry (IC) and identified factors associated with metabolism categories. Patients were evaluated through measurement of REE and estimation of basal energy expenditure (BEE) using the Harris⁻Benedict equation. Metabolism categories were as follows: hypermetabolism (REE/BEE > 1.3) and hypometabolism (REE/BEE < 0.9). The metabolism categories were compared using ANOVA and the chi-square test. Variables were analyzed by multiple logistic regression tests. Also, survivors and non-survivors were compared using Student&rsquo;s t-tests along with Cox regression tests. Kaplan⁻Meier survival curves were also performed. We evaluated 124 patients with a mean age of 61.08 &plusmn; 16.6 years. Sixty-four patients were hypermetabolic (62%) and 18 were hypometabolic (14%). Vasoactive drug (VAD) dose and younger age were independently associated with hypermetabolism. The survival analysis was not associated with metabolism categorization. In conclusion, patients with severe AKI are mostly hypermetabolic and hypermetabolic patients of a lower age receiving treatment with higher VAD doses. The only factors associated with death were protein intake and VAD dose.

Evaluating the predictive factors of resting energy expenditure and validating predictive equations for Chinese obese children

BACKGROUND

To study the predictive factors of resting energy expenditure (REE) and evaluate the accuracy of predicted equations with indirect calorimeter (IC) in Chinese school-age children, particularly for the obese population.

METHODS

Recruited children were from the department of child healthcare in Nanjing children's hospital during July 2014-September 2015. Anthropometric parameters and body composition were measured by bioelectrical impedance. Measured REE was assessed by IC. Predicted REE was estimated using ten published equations.

RESULTS

248 children aged 7-13 years were recruited, including 148 obese [body mass index standard deviation score (BMISDS) = 2.48 ± 0.91] and 100 non-obese (BMISDS = - 0.96 ± 1.08). The unit mass of REE (REE/kg) in obese group (29.06 ± 5.74) was lower than that in non-obese group (37.51 ± 6.56). The stepwise regression showed that age, BMISDS and fat-free mass (FFM) had a major impact on REE/kg as the regression equation: Y = 54.41 - 1.36 × X₁ - 2.25 × X₂ - 0.16 × X₃ (Y REE/kg, X₁ age, X₂ BMISDS, X₃ FFM; R = 0.633, R² = 0.401, P < 0.01). The accuracy of predicted REE in obese subjects was 62.16% by the new predictive equations.

CONCLUSIONS

The REE/kg in obese children was lower and closely correlated with age, BMISDS and FFM. It is necessary to validate the new predictive equation in a larger sample to estimate energy requirements, particularly for children with obesity.

Development and validation of new predictive equation for resting energy expenditure in adults with overweight and obesity

BACKGROUND & AIMS

Accurate predictive equations of resting energy expenditure (REE) are crucial in devising nutritional strategies to manage overweight/obesity, especially in countries where these are highly prevalent. REE is the most common measurement used to estimate energy requirements in the nutritional context; the most accurate method of measuring REE is indirect calorimetry (IC). However, this method is costly and often rarely feasible in many clinical settings. The objective of the present study was to develop and validate a new equation for predicting REE in adults with overweight and obesity.

METHODS

This was a cross-sectional study including 410 men and women with overweight and obesity (20-60 y). Participants were randomly assigned; the development group included 200 subjects and the validation group 210 subjects. The new predictive equation was derived using stepwise multiple linear regression analysis. The accuracy of the new equation was compared to several existing predictive equations (PEs). The accuracy rate was calculated as the percentage of subjects whose REE-PE was within ±10% of the REE-IC. REE was measured by IC and anthropometric measurements.

RESULTS

One predictive equation was developed (NEQ) in which weight was the strongest predictor of REE. Compared with others predicted equations already using, the new designed equation showed the less mean bias (Kj/day): NEQ: 25.7, Valencia:129, WHO/FAO/United Nations University: 270, Mifflin-St Jeor: 308, Owen: -808, Carrasco: -1097, Korth: -36.4, Johnstone: -375, Livingstone: -315, De Lorenzo: -28.3, Lazzer: -123, Muller: -145, Huang: -399 and Bernstein: -1335.

CONCLUSIONS

The present equation had the highest predictive accuracy in subjects with overweight or obesity compared with the previous equations derived from different populations. Thus, these new equation can be used to assist the nutritional management of these subjects.

Postprandial Increase in Energy Expenditure Correlates with Body Weight Reduction in Patients with Type 2 Diabetes Receiving Diet Therapy

AIM

The clinical significance of energy expenditure (EE) in the treatment of type 2 diabetes has not been fully elucidated. Here we analyzed the relationships between EE and clinical measurements in patients with type 2 diabetes receiving diet therapy.

METHODS

A total of 100 patients (34 women and 66 men) with type 2 diabetes admitted to our hospital for glycemic control were enrolled. The participants received an energy-restricted diet during their hospitalization (median, 15 days). EE was measured in the fasted (FEE) and postprandial (PPEE) states using indirect calorimetry. The postprandial increment of EE (ΔEE) was calculated from the FEE and PPEE (ΔEE=PPEE-FEE).

RESULTS

FEE, PPEE, and ΔEE were 0.997±0.203, 1.104±0.213, and 0.107±0.134 kcal/min, respectively. Body weight decreased from 68.7±16.6 to 66.8±16.0 kg (p＜0.0001) during hospitalization. FEE and PPEE showed positive correlations with height, body weight, body mass index, and abdominal circumference at admission, but ΔEE was not correlated with these anthropometric measurements. On the other hand, ΔEE was inversely correlated with the body weight change. The association between ΔEE and the body weight change was independent of age, sex, and HbA1c.

CONCLUSIONS

Postprandial increase in energy expenditure may be a determinant of individual differences in weight reduction in patients with type 2 diabetes on diet therapy. As a simple surrogate for diet-induced thermogenesis, ΔEE may serve as a useful predictive marker for the efficacy of diet therapy.

Gender- and Age-Specific REE and REE/FFM Distributions in Healthy Chinese Adults

Basic data on the resting energy expenditure (REE) of healthy populations are currently rare, especially for developing countries. The aims of the present study were to describe gender- and age-specific REE distributions and to evaluate the relationships among glycolipid metabolism, eating behaviors, and REE in healthy Chinese adults. This cross-sectional survey included 540 subjects (343 women and 197 men, 20–79 years old). REE was measured by indirect calorimetry and expressed as kcal/day/kg total body weight. The data were presented as the means and percentiles for REE and the REE to fat-free mass (FFM) ratio; differences were described by gender and age. Partial correlation analysis was used to analyze the correlations between REE, tertiles of REE/FFM, and glycolipid metabolism and eating behaviors. In this study, we confirmed a decline in REE with age in women (p = 0.000) and men (p = 0.000), and we found that men have a higher REE (p = 0.000) and lower REE/FFM (p = 0.021) than women. Furthermore, we observed no associations among glycolipid metabolism, eating behaviors, and REE in healthy Chinese adults. In conclusion, the results presented here may be useful to clinicians and nutritionists for comparing healthy and ill subjects and identifying changes in REE that are related to aging, malnutrition, and chronic diseases.

Is Obesity Associated with Altered Energy Expenditure?

Historically, obese individuals were believed to have lower energy expenditure (EE) rates than nonobese individuals (normal and overweight), which, in the long term, would contribute to a positive energy balance and subsequent weight gain. The aim of this review was to critically appraise studies that compared measures of EE and its components, resting EE (REE), activity EE (AEE), and diet-induced thermogenesis (DIT), in obese and nonobese adults to elucidate whether obesity is associated with altered EE. Contrary to popular belief, research has shown that obese individuals have higher absolute REE and total EE. When body composition (namely the metabolically active component, fat-free mass) is taken into account, these differences between obese and nonobese individuals disappear, suggesting that EE in obese individuals is not altered. However, an important question is whether AEE is lower in obese individuals because of a decrease in overall physical activity or because of less energy expended while performing physical activity. AEE and DIT could be reduced in obese individuals, mostly because of unhealthy behavior (low physical activity, higher intake of fat). However, the current evidence does not support the hypothesis that obesity is sustained by lower daily EE or REE. Future studies, comparing EE between obese and nonobese and assessing potential physiologic abnormalities in obese individuals, should be able to better answer the question of whether these individuals have altered energy metabolism.

Increased Resting Energy Expenditure after Endovascular Coiling for Subarachnoid Hemorrhage

BACKGROUND

Appropriate nutritional care from the acute stage is essential for improved functional outcomes and reduced mortality in patients with subarachnoid hemorrhage (SAH). Although endovascular coiling is increasingly being used as an alternative to neurosurgical clipping and craniotomy for ruptured aneurysms, the resting energy expenditure (REE) of patients treated with this new technique has not been systemically evaluated.

METHODS

We measured REE values by indirect calorimetry in 12 SAH patients treated with endovascular coiling. We averaged the REE measurements obtained on days 1 and 7 after endovascular coiling, and then we statistically compared the mean REE values with those in 30 patients with acute cerebral infarction (ACI) by the Wilcoxon rank-sum test (P <.05). Next, we calculated the ratio of measured REE values to the values estimated using the Harris-Benedict equation to adjust for demographic differences in sex, weight, height, and age between the groups.

RESULTS

The ratios were significantly higher in SAH patients (median value, 1.12; interquartile range, 1.05-1.23) than in ACI patients (median value, 1.02; interquartile range, .97-1.09).

CONCLUSIONS

Because endovascular coiling is less invasive than neurosurgical clipping, the observed increase in REE was attributed to metabolic changes after SAH. To provide optimal nutritional care to SAH patients from the acute stage, clinicians should be aware of this change in REE.

Age-related changes in basal substrate oxidation and visceral adiposity and their association with metabolic syndrome

PURPOSE

Ageing is directly associated with visceral fat (VAT) deposition and decline of metabolically active cellular mass, which may determine age-related shifts in substrate oxidation and increased cardiometabolic risk. We tested whether VAT and fasting respiratory quotient (RQ, an index of macronutrient oxidation) changed with age and if they were associated with increased risk of metabolic syndrome (MetSyn).

METHODS

A total of 2819 adult participants (age range: 18-81 years; men/women: 894/1925) were included; we collected history, anthropometric measures, biochemistry, smoking habits, and physical activity. The body mass index range was 18.5-60.2 kg/m(2). Gas exchanges (VO2 and VCO2) were measured by indirect calorimetry in fasting conditions, and RQ was calculated. Body composition was measured by bioelectrical impedance. Abdominal subcutaneous fat and VAT were measured by ultrasonography. MetSyn was diagnosed using harmonised international criteria. Multivariate linear and logistic regression models were utilised.

RESULTS

VAT increased with age in both men (r = 0.31, p < 0.001) and women (r = 0.37, p < 0.001). Basal RQ was not significantly associated with age (p = 0.49) and VAT (p = 0.20); in addition, basal RQ was not a significant predictor of MetSyn (OR 3.31, 0.57-19.08, p = 0.27). VAT was the primary predictor of MetSyn risk in a fully adjusted logistic model (OR 4.25, 3.01-5.99, p < 0.001).

CONCLUSIONS

Visceral adiposity remains one of the most important risk factors for cardiometabolic risk and is a significant predictor of MetSyn. Post-absorptive substrate oxidation does not appear to play a significant role in age-related changes in body composition and cardiometabolic risk, except for a correlation with triglyceride concentration.

Effect of vitamin D supplementation alone or with calcium on adiposity measures: a systematic review and meta-analysis of randomized controlled trials

CONTEXT

The independent or interactive effects of vitamin D and calcium on adiposity remain inconclusive.

OBJECTIVE

The objective of this systematic review and meta-analysis was to assess whether vitamin D and calcium supplements cause changes in adiposity.

DATA SOURCES

MEDLINE, Embase, and the Cochrane Central Register of Controlled Trials databases were searched for literature published from 1966 to March 2014.

STUDY SELECTION

A systematic search was conducted for randomized clinical trials with ≥ 50 participants aged ≥ 18 years at baseline who had received at least 12 weeks of treatment. Among the inclusion criteria were supplementation with vitamin D with or without calcium and measurement of adiposity (weight, body mass index [BMI], and/or fat mass).

DATA EXTRACTION

The primary endpoints assessed were changes in weight, BMI, or fat mass.

DATA SYNTHESIS

Of 953 trials identified, 26 randomized clinical trials (n = 12, vitamin D alone; n = 10, vitamin D plus calcium versus calcium control; n = 4, vitamin D plus calcium versus placebo) with a total of 42,430 participants (median duration, 12 months) met the inclusion criteria. When compared with placebo, vitamin D supplementation had no significant effect on BMI (weighted mean difference [WMD], -0.06 kg/m(2); 95% confidence interval [95%CI], -0.14 to 0.03), weight (WMD, -0.05 kg; 95%CI, -0.32 to 0.23), or fat mass (WMD, -0.43 kg; 95%CI, -1.69 to 0.84). Likewise, no significant reduction in BMI (WMD, 0.02 kg/m(2); 95%CI, -0.11 to 0.14), weight (WMD, 0.12 kg; 95%CI, -0.24 to 0.49), or fat mass (WMD, 0.12 kg; 95%CI, -0.22 to 0.45) was observed in participants who received vitamin D plus calcium compared with those who received calcium control.

CONCLUSIONS

Supplementation with vitamin D showed no effect on adiposity measures in adults.