Biomarker-assessed total energy intake and its cohort study association with all-cause mortality in postmenopausal females

BACKGROUND

The association of total energy intake (EI) with all-cause mortality is uncertain as are the dependencies of this association on age and weight change history.

OBJECTIVES

To identify an EI biomarker suitable for use in epidemiologic association studies and to study EI associations with total mortality in a Women's Health Initiative (WHI) cohort of postmenopausal United States females (1993-present).

METHODS

EI biomarkers were developed based on doubly labeled water (DLW) total energy expenditure (TEE) and weight variation during the 2-wk DLW protocol period using the energy balance method in an embedded feeding study (n = 153). This along with 2 earlier WHI nutrition biomarker studies having TEE assessments (n = 1131 total), with 14.6 y (median) follow-up, constituted a prospective cohort for the study of EI and all-cause mortality.

RESULTS

An empirical biomarker for log(EI) was developed that had a correlation of 0.73 with log(feeding study-consumed EI). The overall association between EI and mortality was nonsignificant. The association, however, depended on age (P = 0.009), with lower EI associated with lower mortality at younger ages, and also on preceding weight change history (P = 0.03). Among participants with stable or increasing weight, mortality hazard ratios (95% confidence intervals [CIs]) for a 12% lower EI were 0.66 (95% CI: 0.51, 0.87) at age 60, 0.84 (95% CI: 0.72, 0.98) at age 70, and 1.06 (95% CI: 0.87, 1.29) at age 80. Corresponding values for participants having preceding weight loss were 0.83 (95% CI: 0.61, 1.12) at age 60, 1.05 (95% CI: 0.87, 1.26) at age 70, and 1.33 (95% CI: 1.08, 1.63) at age 80. A previously considered EI biomarker, using a theoretical model for variation in body fat and fat-free mass components over time, gave similar results following rescaling.

CONCLUSIONS

Lower EI is associated with lower all-cause mortality among younger postmenopausal females with stable or increasing weight and with higher mortality among older females with weight loss. This study was registered with clinicaltrials.gov as NCT00000611.

Development and validation of age-specific predictive equations for total energy expenditure and physical activity levels for older adults

BACKGROUND

Predicting energy requirements for older adults is compromised by the underpinning data being extrapolated from younger adults.

OBJECTIVES

To generate and validate new total energy expenditure (TEE) predictive equations specifically for older adults using readily available measures (age, weight, height) and to generate and test new physical activity level (PAL) values derived from 1) reference method of indirect calorimetry and 2) predictive equations in adults aged ≥65 y.

METHODS

TEE derived from "gold standard" methods from n = 1657 (n = 1019 females, age range 65-90 y), was used to generate PAL values. PAL ranged 1.28-2.05 for males and 1.26-2.06 for females. Physical activity (PA) coefficients were also estimated and categorized (inactive to very active) from population means. Nonlinear regression was used to develop prediction equations for estimating TEE. Double cross-validation in a randomized, sex-stratified, age-matched 50:50 split, and leave one out cross-validation were performed. Comparisons were made with existing equations.

RESULTS

Equations predicting TEE using the Institute of Medicine method are as follows: For males, TEE = -5680.17 - 17.50 × age (years) + PA coefficient × (6.96 × weight [kilograms] + 44.21 × height [centimeters]) + 1.13 × resting metabolic rate (RMR) (kilojoule/day). For females, TEE = -5290.72 - 8.38 × age (years) + PA coefficient × (9.77 × weight [kilograms] + 41.51 × height [centimeters]) + 1.05 × RMR (kilojoule/day), where PA coefficient values range from 1 (inactive) to 1.51 (highly active) in males and 1 to 1.44 in females respectively. Predictive performance for TEE from anthropometric variables and population mean PA was moderate with limits of agreement approximately ±30%. This improved to ±20% if PA was adjusted for activity category (inactive, low active, active, and very active). Where RMR was included as a predictor variable, the performance improved further to ±10% with a median absolute prediction error of approximately 4%.

CONCLUSIONS

These new TEE prediction equations require only simple anthropometric data and are accurate and reproducible at a group level while performing better than existing equations. Substantial individual variability in PAL in older adults is the major source of variation when applied at an individual level.

Assessment of Cardiorespiratory and Metabolic Contributions in an Extreme Intensity CrossFit® Benchmark Workout

Our purpose was to characterize the oxygen uptake kinetics (VO2), energy systems contributions and total energy expenditure during a CrossFit® benchmark workout performed in the extreme intensity domain. Fourteen highly trained male CrossFitters, aged 28.3 ± 5.4 years, with height 177.8 ± 9.4 cm, body mass 87.9 ± 10.5 kg and 5.6 ± 1.8 years of training experience, performed the Isabel workout at maximal exertion. Cardiorespiratory variables were measured at baseline, during exercise and the recovery period, with blood lactate and glucose concentrations, including the ratings of perceived exertion, measured pre- and post-workout. The Isabel workout was 117 ± 10 s in duration and the VO2 peak was 47.2 ± 4.7 mL·kg-1·min-1, the primary component amplitude was 42.0 ± 6.0 mL·kg-1·min-1, the time delay was 4.3 ± 2.2 s and the time constant was 14.2 ± 6.0 s. The accumulated VO2 (0.6 ± 0.1 vs. 4.8 ± 1.0 L·min-1) value post-workout increased substantially when compared to baseline. Oxidative phosphorylation (40%), glycolytic (45%) and phosphagen (15%) pathways contributed to the 245 ± 25 kJ total energy expenditure. Despite the short ~2 min duration of the Isabel workout, the oxygen-dependent and oxygen-independent metabolism energy contributions to the total metabolic energy release were similar. The CrossFit® Isabel requires maximal effort and the pattern of physiological demands identifies this as a highly intensive and effective workout for developing fitness and conditioning for sports.

Longitudinal characteristics of physical frailty and its components in men and women post hip fracture

BACKGROUND

Frailty is an important geriatric syndrome predicting adverse health outcomes in older adults. However, the longitudinal characteristics of frailty components in post-hip fracture patients are less understood. Adopting the Fried frailty definition, we examined the longitudinal trends and sex trajectory differences in frailty and its components over 1 year post-fracture.

METHODS

Three hundred and twenty-seven hip fracture patients (162 men and 165 women with mean age 80.1 and 81.5) from Baltimore Hip Studies 7th cohort with measurements at 22 days after admission, and months 2, 6, and 12 post-fracture were analyzed. Frailty components included: grip strength, gait speed, weight, total energy expenditure, and exhaustion. Longitudinal analysis used mixed effect models.

RESULTS

At baseline, men were sicker with worse cognitive status, and had higher weight and grip strength, but lower total energy expenditure than women (p < 0.001). The prevalence of frailty was 31.5%, 30.2%, and 28.2% at months 2, 6, and 12 respectively, showing no longitudinal trends or sex differences. However, its components showed substantial recovery trends over the post-fracture year after confounding adjustments, including increasing gait speed, reducing risk of exhaustion, and stabilized weight loss and energy expenditure over time. Particularly, while men's grip strength tended to remain stable over first year post surgery within patients, women's grip strength reduced significantly over time within patients. On average over time within patients, women were more active with higher energy expenditures but lower grip strength and weight than men.

CONCLUSION

Significant recovery trends and sex differences were observed in frailty components during first year post-fracture. Overall frailty status did not show those trends over months 2-12 since a summary measure might obscure changes in components. Therefore, frailty components provided important multi-dimensional information on the complex recovery process of patients, indicating targets for intervention beyond the global binary measure of frailty.

[Contemporary approaches to the assessment of energy intake and energy expenditure in athletes]

Assessment and interpreting of the energy expenditure (EE) in highly skilled athletes are important components of an effective training and performance prediction. Each component of EE (resting energy expenditure, thermic effect of food, and physical activity energy expenditure) is closely related to dietary patterns, the intensity and duration of physical activity, as well as a number of other factors that affect the functional state of athletes. Despite the importance of EE in the training process, coaches and athletes often do not take EE into account, which reduces the objectivity of assessing athletes' functional state. The purpose of this research was to summarize the recent information on the structure of EE and energy consumption in athletes. Material and methods. The search and analysis of publications was carried out using the PubMed, MEDLINE, Scopus, Web of Science, eLIBRARY databases, mainly for the last 10 years, using the search keywords: rest energy expenditure, thermic effect of food, physical activity energy expenditure, energy intake, total energy expenditure, athletes. Results. This overview includes information on the components of total energy expenditure, such as rest energy expenditure, thermic effect of food and physical activity energy expenditure, as well as generalized information on the factors affecting the variability of their values and methods for assessing one or another type of energy expenditure. International nutritional recommendations regarding the level of physical activity of athletes are systematized, as well as the advantages and disadvantages of methods for studying energy consumption and total energy expenditure are presented. Conclusion. Combined study of energy intake and energy expenditure will help athletes avoid the negative impact of energy deficiency on performance, and the correct construction of the training process with the maintenance of adequate energy consumption will have a positive impact on the performance and recovery processes after intensive physical exertion.

Prediction of the Physical Activity Level of Community-Dwelling Older Japanese Adults with a Triaxial Accelerometer Containing a Classification Algorithm for Ambulatory and Non-Ambulatory Activities

Accurate methods for the prediction of the total energy expenditure and physical activity level (PAL) in community-dwelling older adults have not been established. Therefore, we examined the validity of estimating the PAL using an activity monitor (Active style Pro HJA-350IT, [ASP]) and proposed correction formulae for such populations in Japan. Data for 69 Japanese community-dwelling adults aged 65 to 85 years were used. The total energy expenditure in free-living conditions was measured with the doubly labeled water method and the measured basal metabolic rate. The PAL was also estimated from metabolic equivalent (MET) values obtained with the activity monitor. Adjusted MET values were also calculated with the regression equation of Nagayoshi et al. (2019). The observed PAL was underestimated, but significantly correlated, with the PAL from the ASP. When adjusted using the Nagayoshi et al. regression equation, the PAL was overestimated. Therefore, we developed regression equations to estimate the actual PAL (Y) from the PAL obtained with the ASP for young adults (X) as follows: women: Y = 0.949 × X + 0.205, mean ± standard deviation of the prediction error = 0.00 ± 0.20; men: Y = 0.899 × X + 0.371, mean ± standard deviation of the prediction error = 0.00 ± 0.17.

Total energy expenditure of collision team sports players measured using doubly labeled water: a systematic review

PURPOSE

Total energy expenditure (TEE) is crucial for energy balance and recovery in athletes who participate in collision team sports with high training volumes. This study aimed to review the existing evidence on TEE measured using the doubly labeled water (DLW) technique in soccer, basketball, and rugby players. Furthermore, this systematic review summarized the training volume, match details during the measurement period, and body composition of the athletes.

METHODS

This systematic review used the PubMed, Science Direct, Web of Science, and Embase databases. Only articles presenting objectively measured data on the TEE of adolescent and adult collision team sports players were included, as measured using the DLW method. The measurement period, training, match information, and body composition data were also obtained. The search strategy identified 1497 articles, of which 13 met the selection criteria.

RESULTS

The 13 studies included four rugby players, six soccer players, and three basketball players; six of the 13 studies involved young players. The TEE measured using the DLW method was 3862.3-5783.9 kcal/day for rugby, 2859-3586 kcal/day for soccer, and 4006-4921 kcal/day for basketball players.

CONCLUSION

The TEE of collision sports players varies depending on the training or match load, body composition, and measurement period. Individual approaches to nutritional prescriptions for collision sports players should also account for different periods, anthropometric profiles, training, and game loads. This review provides evidence for developing nutritional guidelines to optimize the recovery and performance of collision team players.

Management of gestational weight gain in obese or overweight women based on resting energy expenditure: A pilot cohort study

Resting energy expenditure (REE) comprises 60% of total energy expenditure and variations may be associated with gestational weight gain (GWG). This study aims to explore the usability and feasibility of REE guided intervention for GWG in obese and overweight women. We conducted a prospective cohort study in LuHe Hospital of Capital Medical University in Beijing, China between May 1, 2017 and May 31, 2018. Obese/overweight women who had routine prenatal care visit at 10 to 13 weeks of gestation, were recruited after written informed consent was obtained. The intervention group (those women who were recruited between January 1 and May 31, 2018) used REE calculated daily total energy to manage GWG, while the control group (those women who were recruited between May 1 and December 31, 2017) used prepregnancy body mass index calculated daily total energy to manage GWG. GWG and daily total energy between the 2 groups were recorded from 10 to 13 weeks of gestation to delivery. A total of 68 eligible women (35 in intervention group and 33 in control group) were included in the final analysis. Daily total energy in the intervention group increased less than the control group, especially from 2nd trimester to 3rd trimester (1929.54 kcal/d vs. 2138.33 kcal/d). The variation of daily total energy from 1st trimester to 3rd trimester in the intervention group was lower than the control group (226.17 kcal/d vs 439.44 kcal/d). Overall GWG of the intervention group (13.45 kg) was significantly lower than the control group (18.20 kg). The percentage of excess-GWG in the intervention group (31.42%) was also significantly lower than the control (57.57%). Findings from our pilot study suggest that diet recommendation basting on REE may improve management of GWG in obese/overweight women.

Physical Activity and Total Daily Energy Expenditure in Older US Adults: Constrained versus Additive Models

PURPOSE

This study aimed to examine the shape of the relationship between physical activity (PA) and total energy expenditure (TEE) and to explore the role of energy balance status (negative, stable, positive) in influencing this association.

METHODS

Cross-sectional. Participants were 584 older adults (50-74 yr) participating in the Interactive Diet and Activity Tracking in AARP study. TEE was assessed by doubly labeled water and PA by accelerometer. The relationship between PA and TEE was assessed visually and using nonlinear methods (restricted cubic splines). Percent weight change (>3%) over a 6-month period was used as a proxy measurement of energy balance status.

RESULTS

TEE generally increased with increasing deciles of PA averaging 2354 (SD, 351) kcal·d-1 in the bottom decile to 2693 (SD, 480) kcal·d-1 in the top decile. Cubic spline models showed an approximate linear association between PA and TEE (linear relation, P < 0.0001; curvature, P = 0.920). Results were similar in subgroup analyses for individuals classified as stable or positive energy balance. For those in negative energy balance, TEE was generally flat with increasing deciles of PA averaging 2428 (SD, 285) kcal·d-1 in the bottom decile to 2372 (SD, 560) kcal·d-1 in the top decile.

CONCLUSIONS

Energy balance status seems to play an important role in the relationship between PA and TEE. When in a positive energy balance, the relationship between TEE and PA was consistent with an additive model; however, when energy balance was negative, TEE seems to be consistent with a constrained model. These findings support PA for weight gain prevention by increasing TEE; however, the effect of PA on TEE during periods of weight loss may be limited. An adequately powered, prospective study is warranted to confirm these exploratory findings.

Association between Water and Energy Requirements with Physical Activity and Fat-Free Mass in Preschool Children in Japan

Water and energy are essential for the human body. The doubly labeled water (DLW) method measures water turnover (WT) and total energy expenditure (TEE), which serves as a benchmark for the adequate intake (AI) of water and estimated energy requirements (EER). The objective of the current study was to examine the association of WT and TEE with physical activity and body composition in Japanese preschool children. We included 41 preschool children (22 girls, 19 boys) aged 3–6 in this study. WT, TEE, and fat-free mass (FFM) were obtained using DLW. Physical activity was measured using a triaxial accelerometer and categorized as light (LPA; 1.5–2.9 Metabolic equivalents, METs) and of moderate-to-vigorous intensity (MVPA; ≥3.0 METs). Exercise duration (Ex) was defined as ≥4.0 METs of physical activity. WT and TEE moderately positively correlated with Ex, but not with LPA. WT moderately positively correlated with BW and FFM while TEE strongly. We established predictive equations for WT and TEE using body weight (BW), FFM, step count, and Ex to guide the AI of water and EER in Japanese preschool children. We found that FFM and step count are the determinants of TEE, and that BW and Ex are the determinants of WT in preschool children.

Age-Related Decline in Physical Activity Level in the Healthy Older Japanese Population

The Dietary Reference Intakes 2020 divided the older population into those aged 65-74 y and those over 75 y old. However, physical activity level in each age group was not specified. This study examined age-related differences in physical activity level among healthy Japanese older people, and the effect of lifestyles on these differences. In total, 70 people (22 men, 48 women) aged 65-85 y old participated in this study. Total energy expenditure was measured using the doubly labeled water method, and basal metabolic rate using expired gas concentration and volume. The Physical Activity Scale for the Elderly and a triaxial accelerometer were used to assess physical activities. Physical activity level was significantly higher among 65-74 y old (median 1.86) than those over 75 y old (1.76). However, the Physical Activity Scale for the Elderly did not show any significant differences between the age groups. The duration of physical activity with 3.0-5.9 metabolic equivalents was longer for both locomotive and household activities among 65-74 y old than those over 75 y old. Younger participants walked a median of 6,364 steps a day, compared with 4,419 steps for older people. The 65-74 y old participants involved in paid work or who habitually exercised, and those over 75 y old taking more than 40 min a day of moderate to vigorous physical activity, and walking more than the median level for their sex and age group had significantly higher physical activity levels.

Estimated Energy Requirements of Infants and Young Children up to 24 Months of Age

BACKGROUND

Establishing energy requirements in infants and young children is important in developing age-appropriate diet recommendations but most published guidelines for energy requirements have 1 or more limitations related to the data underlying the calculations.

OBJECTIVE

To develop a comprehensive set of daily energy requirements for infants and young children aged 0-24 mo meeting the ideals of worldwide applicability to all healthy children based on the use of the doubly labeled water (DLW) technique to measure total energy expenditure (TEE), the use of recent, international growth charts, and calculation of values across a wide range of body weight.

METHODS

Daily estimated energy requirements (EERs) were calculated in 1-mo increments from 0 to 24 mo for boys, girls, and combined, using as inputs the following: 1) TEE measured using the DLW technique, 2) energy deposition estimates from the Institute of Medicine, and 3) body weight values from the 25th to 75th percentiles from the 2006 WHO growth charts. EERs were combined for age groups 0 to <6, 6-8, 9-11, and 12-24 mo by averaging EERs from individual months. The EER calculations were supported by a systematic literature review and a meta-regression of existing studies.

RESULTS

Energy requirements naturally increase with age and are slightly higher in boys than in girls. The EERs derived in this study are similar to those in other recent international efforts.

CONCLUSIONS

This updated set of EERs for infants and young children expand and improve upon the methodology used to establish previous published guidelines. These estimates have multiple potential uses including planning age-appropriate menus for the complementary feeding period, the development of foods that are more precisely targeted to the needs of infants and children at particular ages, and establishing macronutrient requirements within specific age groups based on a percentage of energy, such as dietary fat.

Accuracy and Practical Considerations for Doubly Labeled Water Analysis in Nutrition Studies Using a Laser-Based Isotope Instrument (Off-Axis Integrated Cavity Output Spectroscopy)

BACKGROUND

Given the utility of the doubly labeled water (DLW) method for determination of energy expenditure, additional techniques for isotope analysis of the samples are welcome. Laser-based instruments are one such new analytical tool, but their accuracy and feasibility for DLW studies are grossly understudied.

OBJECTIVES

We assessed the accuracy of laser-based isotope ratio measurements as part of the DLW method for estimation of carbon dioxide production rate (rCO2) and total energy expenditure (TEE), in between-group comparison study designs.

METHODS

Urine samples from a previous study were analyzed with a laser-based instrument [off-axis integrated cavity output spectroscopy (OA-ICOS)]. In that study, participants consumed a high-, moderate-, or low-carbohydrate diet for 20 wk; urine samples were obtained in weeks 18-20 before and after a 2H- and 18O-enriched water dose. Isotope ratios (δ2H and δ18O), rCO2, and TEE calculated by standard methods were compared to results previously obtained with the standard technique of isotope ratio mass spectrometry (IRMS). Bias, SD, and bias ± 1.96SD bands between IRMS and OA-ICOS were computed.

RESULTS

The between OA-ICOS and IRMS rCO2 and TEE trends were equivalent (within 1.2% and 4.1%, respectively), in spite of the differences in measured δ18O values at high enrichment levels. The OA-ICOS δ18O values displayed an increasing offset from the IRMS results as the 18O enrichment increased (mean ± SD 4.6-5.7‰ ± 2‰ offset at the time point with highest 18O enrichment, ∼135‰), whereas the hydrogen isotope ratio (δ2H) differed only slightly between the methods (mean offset -4.9‰ for all time points). The between-diet differences in TEE from the previous study were recapitulated with a smaller subset of participants and time points.

CONCLUSIONS

OA-ICOS analysis is an accurate and feasible technique for the DLW method. Given the δ18O offset observed at high enrichment, validation of each OA-ICOS instrumental setup against established methods (e.g., IRMS) is recommended.

What Is the Impact of Energy Expenditure on Energy Intake?

Coupling energy intake (EI) to increases in energy expenditure (EE) may be adaptively, compensatorily, or maladaptively leading to weight gain. This narrative review examines if functioning of the homeostatic responses depends on the type of physiological perturbations in EE (e.g., due to exercise, sleep, temperature, or growth), or if it is influenced by protein intake, or the extent, duration, timing, and frequency of EE. As different measures to increase EE could convey discrepant neuronal or humoral signals that help to control food intake, the coupling of EI to EE could be tight or loose, which implies that some ways to increase EE may have advantages for body weight regulation. Exercise, physical activity, heat exposure, and a high protein intake favor weight loss, whereas an increase in EE due to cold exposure or sleep loss likely contributes to an overcompensation of EI, especially in vulnerable thrifty phenotypes, as well as under obesogenic environmental conditions, such as energy dense high fat—high carbohydrate diets. Irrespective of the type of EE, transient elevations in the metabolic rate seem to be general risk factors for weight gain, because a subsequent decrease in energy requirement is not compensated by an adequate adaptation of appetite and EI.

Reindeer herders from subarctic Finland exhibit high total energy expenditure and low energy intake during the autumn herd roundup

OBJECTIVE

High levels of total energy expenditure (TEE, kcal/day) have been documented among numerous human populations such as tropical climate horticulturalists and high-altitude agriculturalists. However, less work has been conducted among highly physically active cold climate populations.

METHODS

In October 2018, TEE was measured using the doubly labeled water (TEE_DLW , N = 10) and flex-heart rate methods (TEE_HR , N = 24) for 6-14 days among reindeer herders (20-62 years) in northern Finland during an especially physically demanding, but not seasonally representative, period of the year for herders-the annual reindeer herd roundup. Self-reported dietary intake was also collected during TEE measurement periods. TEE was then compared to that of hunter gatherer, farming, and market economies.

RESULTS

During the herd roundup, herders expended a mean of 4183 ± 949 kcal/day as measured by the DLW method, which was not significantly different from TEE_HR . Mean caloric intake was 1718 ± 709 kcal/day, and was significantly lower than TEE_DLW and TEE_HR (p < .001). Herder TEE_DLW was significantly higher than that of hunter gatherer (p = .0014) and market (p < .0014) economy populations; however, herder TEE_DLW was not different from that of farming populations (p = .91).

CONCLUSION

High TEE and low caloric intake among herders reflect the extreme demands placed on herders during the annual herd round up. Although TEE_DLW was similar between cold climate herders and hot climate farming populations, there are likely differences in how that TEE is comprised, reflecting the local ecologies of these populations.

Effect of Manual Data Cleaning on Nutrient Intakes Using the Automated Self-Administered 24-Hour Dietary Assessment Tool (ASA24)

BACKGROUND

Automated dietary assessment tools such as ASA24® are useful for collecting 24-hour recall data in large-scale studies. Modifications made during manual data cleaning may affect nutrient intakes.

OBJECTIVES

We evaluated the effects of modifications made during manual data cleaning on nutrient intakes of interest: energy, carbohydrate, total fat, protein, and fiber.

METHODS

Differences in mean intake before and after data cleaning modifications for all recalls and average intakes per subject were analyzed by paired t-tests. The Chi-squared test was used to determine whether unsupervised recalls had more open-ended text responses that required modification than supervised recalls. We characterized food types of text response modifications. Correlations between predictive energy requirements, measured total energy expenditure (TEE), and mean energy intake from raw and modified data were examined.

RESULTS

After excluding 11 recalls with invalidating technical errors, 1499 valid recalls completed by 393 subjects were included in this analysis. We found significant differences before and after modifications for energy, carbohydrate, total fat, and protein intakes for all recalls (P < 0.05). Limiting to modified recalls, there were significant differences for all nutrients of interest, including fiber (P < 0.02). There was not a significantly greater proportion of text responses requiring modification for home compared with supervised recalls (P = 0.271). Predicted energy requirements correlated highly with TEE. There was no significant difference in correlation of mean energy intake with TEE for modified compared with raw data. Mean intake for individual subjects was significantly different for energy, protein, and fat intakes following cleaning modifications (P < 0.001).

CONCLUSIONS

Manual modifications can change mean nutrient intakes for an entire cohort and individuals. However, modifications did not significantly affect the correlation of energy intake with predictive requirements and measured expenditure. Investigators can consider their research question and nutrients of interest when deciding to make cleaning modifications.

A standard calculation methodology for human doubly labeled water studies

The doubly labeled water (DLW) method measures total energy expenditure (TEE) in free-living subjects. Several equations are used to convert isotopic data into TEE. Using the International Atomic Energy Agency (IAEA) DLW database (5,756 measurements of adults and children), we show considerable variability is introduced by different equations. The estimated rCO₂ is sensitive to the dilution space ratio (DSR) of the two isotopes. Based on performance in validation studies, we propose a new equation based on a new estimate of the mean DSR. The DSR is lower at low body masses (<10 kg). Using data for 1,021 babies and infants, we show that the DSR varies non-linearly with body mass between 0 and 10 kg. Using this relationship to predict DSR from weight provides an equation for rCO₂ over this size range that agrees well with indirect calorimetry (average difference 0.64%; SD = 12.2%). We propose adoption of these equations in future studies.

Association of Lower-Extremity Muscle Performance and Physical Activity Level and Intensity in Middle-Aged and Older Adults: A Doubly Labeled Water and Accelerometer Study

OBJECTIVES

The purpose of this study was to examine if there is a relationship between lower-extremity muscle performance (LEMP) and physical activity, especially the physical activity level (PAL) value, in community-dwelling middle-aged and older adults.

DESIGN

Cross-sectional study.

SETTING

Community-based.

PARTICIPANTS

Participants were 54 community-dwelling and independent middle-aged and older individuals (aged 54-89 years).

MEASUREMENTS

Physical activity level was calculated from the total energy expenditure of each participant obtained using the doubly labeled water method (PALDLW) and estimated basal metabolic rate. Daily step count and intensity of physical activity was monitored with a triaxial accelerometer, and LEMP was assessed using the five-repetition sit-to-stand test (STS-5) and vertical jumping (VJ).

RESULTS

The results of STS-5 nearly negatively correlated with those of PALDLW when analysing the middle-aged and older man and woman, separately. VJ positively correlated with PALDLW when analysing the middle-aged and older men and woman, separately. The relationship between LEMP (e.g. STS-5 and VJ) and PAL were maintained, regardless of sex and body composition. PALDLW was significantly positively correlated with LPA, MVPA, and steps, and significantly negatively correlated with sedentary time. The relationship PALDLW and steps was described as following equation: PALDLW = 0.0000392 × steps +1.531.

CONCLUSIONS

These findings suggest that PALDLW is a key contributor to increasing LEMP among middle-aged and older adults. Maintaining high PALDLW may be beneficial to independent living, and participation in recreational and social activities in middle-aged and older adults.

Energy Gap between Doubly Labeled Water-Based Energy Expenditure and Calculated Energy Intake from Recipes and Plate Waste, and Subsequent Weight Changes in Elderly Residents in Japanese Long-Term Care Facilities: CLEVER Study

Unintentional weight loss is a major frailty component; thus, assessing energy imbalance is essential for institutionalized elderly residents. This study examined prediction errors of the observed energy intake (OEI) against the actual energy intake obtained from the doubly labeled water (DLW) method and clarified the relationship between the energy gap obtained by subtracting total energy expenditure (TEE) from OEI and subsequent weight changes in elderly residents in long-term care facilities. Overall, 46 participants were recruited in Japan. TEE was measured using the DLW method, and OEI was calculated from recipes and plate waste simultaneously over a 14–15-day period at baseline. The total energy intake (TEI_DLW) was determined on the basis of DLW and weight changes during the DLW period. The weight was longitudinally tracked monthly for 12 months in the 28 residents who still lived at the facilities. OEI was higher than TEI_DLW by a mean of 232 kcal/day (15.3%) among 46 residents at baseline. The longitudinal data of 28 residents showed that the energy gap tended to be correlated with the slope of weight change (ρ = 0.337, p = 0.080) and the median value was significantly lower in the weight loss group (152 kcal/day) than in the weight gain group (350 kcal/day) (p < 0.05). In conclusion, weight loss could occur at Japanese long-term care facilities even if the difference obtained by subtracting TEE from OEI was positive because OEI was overestimated by more than 200 kcal/day.

Optimal Estimate for Energy Requirements in Adult Patients With the m.3243A>G Mutation in Mitochondrial DNA

Aim

We aimed to identify the optimal method to estimate total energy expenditure (TEE) in mitochondrial disease (MD) patients.

Methods

Resting energy expenditure (REE) was measured in MD patients carrying the m3243A>G mutation using indirect calorimetry (IC) and compared with results of 21 predictive equations (PEs) for REE and with REE‐IC measurements in healthy controls. Physical activity level (PAL) was measured using accelerometery (SenseWear) and compared with a fixed average PAL (1.4) as well as patients’ self‐estimated activity levels. TEE was calculated as REE‐IC × PAL SenseWear and compared with usual care and energy recommendations for healthy adults.

Results

Thirty‐eight MD patients (age: 48 ± 13 years; body mass index 24 ± 4 kg/m²; male 20%) and 25 matched controls were included. The accuracy of most PEs was between 63% and 76%. The difference in REE‐IC in healthy controls (1532 ± 182 kcal) and MD patients (1430 ± 221) was borderline not significant (P = .052). Patients’ estimations PAL were 18%–34% accurate at the individual level. The fixed activity factor was 53% accurate. Patients overestimated their PAL. Usual care predicted TEE accurately in only 32% of patients.

Conclusion

TEE is lower in these MD patients than the recommendations for healthy adults because of their lower physical activity. In MD patients, 6 PEs for REE provide a reliable alternative for IC, with an accuracy of 71%–76%. As PAL is highly variable and not reliably estimated by patients, measurement of PAL using accelerometery is recommended in this population.

Total Energy Expenditure, Body Composition, Physical Activity, and Step Count in Japanese Preschool Children: A Study Based on Doubly Labeled Water

Adequate energy intake is essential for the healthy development of children, and the estimated energy requirement of children is determined by total daily energy expenditure (TDEE) and energy deposition for growth. A previous study in Japanese tweens indicated that TDEE could be estimated by fat-free mass (FFM) and step count. The aims of this study were to measure TDEE in Japanese preschool children and to confirm whether TDEE can be estimated by FFM and step count in preschool children. Twenty-one children aged 4-6 years old (11 girls and 10 boys; age, 5.1 (0.9) years; height, 107.2 (6.6) cm; weight, 17.5 (1.7) kg; BMI, 15.3 (1.3); mean (SD)) participated in this study. FFM and 7-day TDEE were obtained by doubly labeled water (DLW). Participants wore accelerometers during the DLW measurement period. No significant differences were observed in age-adjusted height, weight, BMI, FFM (13.0 (1.5) kg), or TDEE (1300 (174) kcal/day) between girls and boys. Girls had significantly higher percent fat and a lower daily step count than boys. Stepwise regression analysis revealed that FFM and step count were significant predictors of TDEE; TDEE (kcal/day) = 85.0 × FFM (kg) + 0.0135 × step count (steps/day). This accounted for 74% of TDEE variance. The current study confirmed that FFM and step count are major determinants of TDEE in Japanese preschool children as well as adolescents, although further research is needed to obtain precise equations.

Total energy expenditure measured using doubly labeled water compared with estimated energy requirements in older adults (≥65 y): analysis of primary data

BACKGROUND

Contemporary energy expenditure data are crucial to inform and guide nutrition policy in older adults to optimize nutrition and health.

OBJECTIVE

The aim was to determine the optimal method of estimating total energy expenditure (TEE) in adults (aged ≥65 y) through 1) establishing which published predictive equations have the closest agreement between measured resting metabolic rate (RMR) and predicted RMR and 2) utilizing the RMR equations with the best agreement to predict TEE against the reference method of doubly labeled water (DLW).

METHODS

A database consisting of international participant-level TEE data from DLW studies was developed to enable comparison with energy requirements estimated by 17 commonly used predictive equations. This database included 31 studies comprising 988 participant-level RMR data and 1488 participant-level TEE data. Mean physical activity level (PAL) was determined for men (PAL = 1.69, n = 320) and women (PAL = 1.66, n = 668). Bland-Altman plots assessed agreement of measured RMR and TEE with predicted RMR and TEE in adults aged ≥65 y, and subgroups of 65-79 y and ≥80 y. Linear regression assessed proportional bias.

RESULTS

The Ikeda, Livingston, and Mifflin equations most closely agreed with measured RMR and TEE in all adults aged ≥65 y and in the 65-79 y and ≥80 y subgroups. In adults aged ≥65 y, the Ikeda and Livingston equations overestimated TEE by a mean ± SD of 175 ± 1362 kJ/d and 86 ± 1344 kJ/d, respectively. The Mifflin equation underestimated TEE by a mean ± SD of 24 ± 1401 kJ/d. Proportional bias was present as energy expenditure increased.

CONCLUSIONS

The Ikeda, Livingston, or Mifflin equations are recommended for estimating energy requirements of older adults. Future research should focus on developing predictive equations to meet the requirements of the older population with consideration given to body composition and functional measures.

Estimation of Energy Intake by a Food Frequency Questionnaire: Calibration and Validation with the Doubly Labeled Water Method in Japanese Older People

Accurate assessments of a target population’s energy intake (EI) are essential to prevent poor nutritional status. However, self-reported dietary records (DRs) or food frequency questionnaires (FFQs) are not always accurate, thereby requiring validation and calibration studies. This study aimed to validate the EI estimated by a FFQ using the doubly labeled water (DLW) method. Participants were 109 Japanese older adults (50 women and 59 men) aged 65–88 years. The EI was obtained by a DR and 47-item FFQ over 1 year. The total energy expenditure (TEE) was measured by DLW for ~2 weeks. EI was significantly lower than TEE (p < 0.01); ratios of EI assessed by DR and FFQ against TEE were 0.91 ± 0.17 and 0.82 ± 0.22, respectively. TEE was significantly and moderately correlated with the EI estimated by the DR (r = 0.45, p < 0.01) and FFQ (r = 0.37, p < 0.01). Furthermore, the EI correlation coefficients estimated by DR and the FFQ in this study were not significantly different (p = 0.46). The EI/TEE ratio was significantly and negatively correlated with the body mass index (BMI). In conclusion, EI estimated with a DR or FFQ modestly correlated with TEE, and calibrating EI with a developed equation in this study can attenuate the underestimation of EI.

Validity of One-Day Physical Activity Recall for Estimating Total Energy Expenditure in Elderly Residents at Long-Term Care Facilities: CLinical EValuation of Energy Requirements Study (CLEVER Study)

Malnutrition is a severe problem among elderly residents living in long-term care facilities. A simple and accurate estimation for total daily energy expenditure (TEE) is required in order to provide them with an adequate amount of food. The purpose of this study was to validate a physical activity assessment tool for estimating TEE among elderly residents. The data of 58 subjects aged 69-99 y were analyzed in this study. The one-day physical activity recall was filled out by facility staff for a typical day. TEE was measured by the doubly labeled water (DLW) method (TEE_DLW), and predicted by one-day physical activity recall using the basal metabolic rate (pTEE_BMR) and body weight (pTEE_BW). The TEE_DLW, pTEE_BMR and pTEE_BW were 1,129±196 kcal/d, 1,186±251 kcal/d and 1,326±236 kcal/d, respectively. In a regression model, body weight, movement means and sex explained 39.0% of the variance in the difference between pTEE_BMR and TEE_DLW (p<0.05). Percentage of fat mass, body weight, and Barthel Index except mobility explained 47.3% of the variance in the difference between pTEE_BW and TEE_DLW (p<0.05). The current results suggested that pTEE_BW is not recommended to estimate TEE because the error depends on body size, and pTEE_BMR was significantly correlated with TEE_DLW but also included systematic errors in elderly residents. In order to improve the accuracy of the present assessment to estimate TEE, it is necessary to establish a new equation of basal metabolic rate for elderly residents and consider sex and movement means to estimate TEE.

The use of whole body calorimetry to compare measured versus predicted energy expenditure in postpartum women

BACKGROUND

Accurate assessment of energy expenditure may support weight-management recommendations. Measuring energy expenditure for each postpartum woman is unfeasible; therefore, accurate predictive equations are needed.

OBJECTIVES

This study compared measured with predicted resting energy expenditure (REE) and total energy expenditure (TEE) in postpartum women.

METHODS

This was a longitudinal observational study. REE was measured at 3 mo postpartum (n = 52) and 9 mo postpartum (n = 49), whereas TEE was measured once at 9 mo postpartum (n = 43) by whole body calorimetry (WBC). Measured REE (REEWBC) was compared with 17 predictive equations; measured TEE plus breast milk energy output (ERWBC) was compared with the estimated energy requirements/Dietary Reference Intakes equation (EERDRI). Fat and fat-free mass were measured by dual-energy X-ray absorptiometry. Group-level agreement was assessed by the Pearson correlation, paired t test, and Bland-Altman (bias) analyses. Individual-level accuracy was assessed with the use of Bland-Altman limits of agreement, and by the percentage of women with predicted energy expenditure within 10% of measured values ("accuracy").

RESULTS

The cohort was primarily Caucasian (90%). At a group level, the best equation predicting REEWBC was the DRI at 3 mo postpartum (-7 kcal, -0.1%; absolute and percentage bias, respectively), and the Harris-Benedict at 9 mo postpartum (-17 kcal, -0.5%). At an individual level, the Food and Agriculture Organization/World Health Organization/United Nations University (FAO/WHO/UNU) height and weight equation was the most accurate at 3 mo postpartum (100% accuracy) and 9 mo postpartum (98% accuracy), with the smallest limits of agreement. Equations including body composition variables were not more accurate. Compared with ERWBC, EERDRI bias was -36 kcal, with inaccurate predictions in 33% of women.

CONCLUSIONS

Many REE predictive equations were accurate for group assessment, with the FAO/WHO/UNU height and weight equation having the highest accuracy for individuals. EERDRI performed well at a group level, but inaccurately for 33% of women. A greater understanding of the physiology driving energy expenditure in the postpartum period is needed to better predict TEE and ultimately guide effective weight-management recommendations.

Energy Requirement Assessment and Water Turnover in Japanese College Wrestlers Using the Doubly Labeled Water Method

Estimated energy requirements (EERs) are important for sports based on body weight classifications to aid in weight management. The basis for establishing EERs varies and includes self-reported energy intake (EI), predicted energy expenditure, and measured daily energy expenditure. Currently, however, no studies have been performed with male wrestlers using the highly accurate and precise doubly labeled water (DLW) method to estimate energy and fluid requirement. The primary aim of this study was to compare total energy expenditure (TEE), self-reported EI, and the difference in collegiate wrestlers during a normal training period using the DLW method. The secondary aims were to measure the water turnover and the physical activity level (PAL) of the athletes, and to examine the accuracy of two currently used equations to predict EER. Ten healthy males (age, 20.4±0.5 y) belonging to the East-Japan college league participated in this study. TEE was measured using the DLW method, and EI was assessed with self-reported dietary records for ~1 wk. There was a significant difference between TEE (17.9±2.5 MJ•d^-1 [4,283±590 kcal•d^-1]) and self-reported EI (14.4±3.3 MJ•d^-1 [3,446±799 kcal•d^-1]), a difference of 19%. The water turnover was 4.61±0.73 L•d^-1. The measured PAL (2.6±0.3) was higher than two predicted values during the training season and thus the two EER prediction equations produced underestimated values relative to DLW. We found that previous EERs were underestimating requirements in collegiate wrestlers and that those estimates should be revised.

The effects of Ramadan fasting on activity and energy expenditure

Background

Fasting during the month of Ramadan entails abstinence from eating and drinking between dawn and sunset and a major shift in meal times and patterns with associated changes in several hormones and circadian rhythms; whether there are accompanying changes in energy metabolism is unclear.

Objective

We have investigated the impact of Ramadan fasting on resting metabolic rate (RMR), activity, and total energy expenditure (TEE).

Design

Healthy nonobese volunteers (n = 29; 16 women) fasting during Ramadan were recruited. RMR was measured with the use of indirect calorimetry. In subgroups of participants, activity (n = 11; 5 women) and TEE (n = 10; 5 women) in free-living conditions were measured with the use of accelerometers and the doubly labeled water technique, respectively. Body composition was measured with the use of bioelectrical impedance. Measurements were repeated after a wash-out period of between 1 and 2 mo after Ramadan. Nonparametric tests were used for comparative statistics.

Results

Ramadan fasting did not result in any change in RMR (mean ± SD: 1365.7 ± 230.2 compared with 1362.9 ± 273.6 kcal/d for Ramadan and post-Ramadan respectively, P = 0.713, n = 29). However, controlling for the effects of age, sex, and body weight, RMR was higher in the first week of Ramadan than in subsequent weeks. During Ramadan, the total number of steps walked were significantly lower (n = 11, P = 0.001), while overall sleeping time was reduced and different sleeping patterns were seen. TEE did not differ significantly between Ramadan and post-Ramadan (mean ± SD: 2224.1 ± 433.7 compared with 2121.0 ± 718.5 kcal/d for Ramadan and post-Ramadan, P = 0.7695, n = 10).

Conclusions

Ramadan fasting is associated with reduced activity and sleeping time, but no significant change in RMR or TEE. Reported weight changes with Ramadan in other studies are more likely to be due to differences in food intake. This trial is registered at clinicaltrials.gov as NCT02696421.

Short time effect of a single session of intense whole-body electromyostimulation on energy expenditure. A contribution to fat reduction?

To determine the underlying mechanisms after 1 session of (intense) whole-body electromyostimulation (WB-EMS) on total energy expenditure (TEE) and resting metabolic rate (RMR), 16 subjects followed a standardized protocol of indirect calorimetry for up to 72 h in 12-h intervals. The single session significantly increased RMR by approximately 25% ± 10% (p < 0.001) and TEE by approximately 9.5% ± 1%, a net effect of ∼460 ± 50 kcal (WB-EMS vs. control group).

Low Energy Turnover of Physically Inactive Participants as a Determinant of Insufficient Mineral and Vitamin Intake in NHANES

Micronutrient requirements do not scale linearly with physical activity-related energy expenditure (AEE). Inactive persons may have insufficient micronutrient intake because of low energy intake (EI). We extracted data from NHANES 2003-2006 on 4015 adults (53 ± 18 years (mean ± SD), 29 ± 6 kg/m², 48% women) with valid physical activity (accelerometry) and food intake (2 × 24 h-dietary recall) measures. Total energy expenditure (TEE) was estimated by summing the basal metabolic rate (BMR, Harris-Benedict), AEE, and 10% of TEE for the thermic effect of food, to calculate the physical activity levels (PAL = TEE/BMR). Energy intake (EI) was scaled to match TEE assuming energy balance. Adjusted food intake was then analyzed for energy and micronutrient content and compared to estimated average requirements. The NHANES population was physically insufficiently active. There were 2440 inactive (PAL < 1.4), 1469 lightly to moderately active (PAL1.4 < 1.7), 94 sufficiently active (PAL1.7 < 2.0), and 12 very active participants (PAL ≥ 2.0). The inactive vs. active had significantly lower intake for all micronutrients apart from vitamin A, B12, C, K, and copper (p < 0.05). The inactive participants had insufficient intake for 6/19 micronutrients, while the active participants had insufficient intake for 5/19 (p < 0.05) micronutrients. Multiple linear regression indicated a lower risk for insufficient micronutrient intake for participants with higher PAL and BMI (p < 0.001). Symmetrical up-scaling of PAL and EI to recommended physical activity levels reduced the frequency of micronutrient insufficiencies. It follows that prevalence of insufficient micronutrient intake from food in NHANES might be partly determined by low energy turnover from insufficient PAL.

Energy Requirement Assessment in Japanese Table Tennis Players Using the Doubly Labeled Water Method

Total daily energy expenditure (TEE) and physical activity level (PAL) are important for adequate nutritional management in athletes. The PAL of table tennis has been estimated to about 2.0: it is categorized as a moderateactivity sport (4.0 metabolic equivalents [METs]) in the Compendium of Physical Activities. However, modern table tennis makes high physiological demands. The aims of the current study were to examine (1) TEE and PAL of competitive table tennis players and (2) the physiological demands of various types of table tennis practice. In Experiment 1, we measured TEE and PAL in 10 Japanese college competitive table tennis players (aged 19.9 ± 1.1 years) using the doubly labeled water (DLW) method during training and with an exercise training log and self-reported energy intake. TEE was 15.5 ± 1.9 MJ·day^-1 (3695 ± 449 kcal·day^-1); PAL was 2.53 ± 0.25; and the average training duration was 181 ± 38 min·day^-1. In Experiment 2, we measured METs of five different practices in seven college competition players (20.6 ± 1.2 years). Three practices without footwork were 4.5-5.2 METs, and two practices with footwork were 9.5-11.5 METs. Table tennis practices averaged 7.1 ± 3.2 METS demonstrating similarities with other vigorous racket sports. In conclusion the current Compendium of Physical Activities underestimates the physiological demands of table tennis practice for competition; the estimated energy requirement should be based on DLW method data.

Total Energy Expenditure in Obese Kuwaiti Primary School Children Assessed by the Doubly-Labeled Water Technique

The aim of this pilot study was to assess body composition and total energy expenditure (TEE) in 35 obese 7–9 years old Kuwaiti children (18 girls and 17 boys). Total body water (TBW) and TEE were assessed by doubly-labeled water technique. TBW was derived from the intercept of the elimination rate of deuterium and TEE from the difference in elimination rates of ¹⁸O and deuterium. TBW was used to estimate fat-free mass (FFM), using hydration factors for different ages and gender. Fat mass (FM) was calculated as the difference between body weight and FFM. Body weight was not statistically different but TBW was significantly higher (p = 0.018) in boys (44.9% ± 3.3%) than girls (42.4% ± 3.0%), while girls had significantly higher estimated FM (45.2 ± 3.9 weight % versus 41.6% ± 4.3%; p = 0.014). TEE was significantly higher in boys (2395 ± 349 kcal/day) compared with girls (1978 ± 169 kcal/day); p = 0.001. Estimated physical activity level (PAL) was significantly higher in boys; 1.61 ± 0.167 versus 1.51 ± 0.870; p = 0.034. Our results provide the first dataset of TEE in 7–9 years old obese Kuwaiti children and highlight important gender differences to be considered during the development of school based interventions targeted to combat childhood obesity.

Human energy expenditure, allocation, and interactions in natural temperate, hot, and cold environments

OBJECTIVE

The aim of this research is to analyze how energy is allocated differently in temperate, hot, and cold environments among National Outdoor Leadership School students.

METHOD

Basal metabolic rate, physical activity, thermoregulation, and the thermic effect of food were estimated to determine the total energy expenditure and energy allocation differences among a group of healthy, highly active adults (N = 59) participating in National Outdoor Leadership School courses in the western United States. Two of these courses took place in both hot and temperate climates (N = 22) and the other two in both temperate and cold climates (N = 28). Data from a pilot study (N = 6) in a temperate climate were also included. Each climate regime lasted for one month.

RESULTS

Total energy expenditure values were statistically equivalent in temperate and hot climates (p = .97). However, subjects experienced significantly higher total energy expenditures in cold climates (p < .0001), expending an additional ∼1550 kcal day^-1 . There is a significant interaction between physical activity and thermoregulation, such that physical activity reduces thermoregulatory costs in cold climates, but increases it in hot climates.

CONCLUSIONS

Dissection of the energy budget revealed that total energy expenditure is significantly higher in cold climates. This is due to a combination of high levels of physical activity and high thermoregulatory costs. High levels of physical activity may substantially lower the cost of thermoregulation in cold climates, and this interaction should be taken into account when estimating TEE.

Dilution space ratio of 2H and 18O of doubly labeled water method in humans

Variation of the dilution space ratio (Nd/No) between deuterium ((2)H) and oxygen-18 ((18)O) impacts the calculation of total energy expenditure (TEE) by doubly labeled water (DLW). Our aim was to examine the physiological and methodological sources of variation of Nd/No in humans. We analyzed data from 2,297 humans (0.25-89 yr old). This included the variables Nd/No, total body water, TEE, body mass index (BMI), and percent body fat (%fat). To differentiate between physiologic and methodologic sources of variation, the urine samples from 54 subjects were divided and blinded and analyzed separately, and repeated DLW dosing was performed in an additional 55 participants after 6 mo. Sex, BMI, and %fat did not significantly affect Nd/No, for which the interindividual SD was 0.017. The measurement error from the duplicate urine sample sets was 0.010, and intraindividual SD of Nd/No in repeats experiments was 0.013. An additional SD of 0.008 was contributed by calibration of the DLW dose water. The variation of measured Nd/No in humans was distributed within a small range and measurement error accounted for 68% of this variation. There was no evidence that Nd/No differed with respect to sex, BMI, and age between 1 and 80 yr, and thus use of a constant value is suggested to minimize the effect of stable isotope analysis error on calculation of TEE in the DLW studies in humans. Based on a review of 103 publications, the average dilution space ratio is 1.036 for individuals between 1 and 80 yr of age.

Evaluation of the ability of three physical activity monitors to predict weight change and estimate energy expenditure

Activity monitors such as the Actical accelerometer, the Sensewear armband, and the Intelligent Device for Energy Expenditure and Activity (IDEEA) are commonly validated against gold standards (e.g., doubly labeled water, or DLW) to determine whether they accurately measure total daily energy expenditure (TEE) or activity energy expenditure (AEE). However, little research has assessed whether these parameters or others (e.g., posture allocation) predict body weight change over time. The aims of this study were to (i) test whether estimated energy expenditure or posture allocation from the devices was associated with weight change during and following a low-calorie diet (LCD) and (ii) compare free-living TEE and AEE predictions from the devices against DLW before weight change. Eighty-seven participants from 2 clinical trials wore 2 of the 3 devices simultaneously for 1 week of a 2-week DLW period. Participants then completed an 8-week LCD and were weighed at the start and end of the LCD and 6 and 12 months after the LCD. More time spent walking at baseline, measured by the IDEEA, significantly predicted greater weight loss during the 8-week LCD. Measures of posture allocation demonstrated medium effect sizes in their relationships with weight change. Bland-Altman analyses indicated that the Sensewear and the IDEEA accurately estimated TEE, and the IDEEA accurately measured AEE. The results suggest that the ability of energy expenditure and posture allocation to predict weight change is limited, and the accuracy of TEE and AEE measurements varies across activity monitoring devices, with multi-sensor monitors demonstrating stronger validity.

A Mobile Phone Based Method to Assess Energy and Food Intake in Young Children: A Validation Study against the Doubly Labelled Water Method and 24 h Dietary Recalls

Mobile phones are becoming important instruments for assessing diet and energy intake. We developed the Tool for Energy Balance in Children (TECH), which uses a mobile phone to assess energy and food intake in pre-school children. The aims of this study were: (a) to compare energy intake (EI) using TECH with total energy expenditure (TEE) measured via doubly labelled water (DLW); and (b) to compare intakes of fruits, vegetables, fruit juice, sweetened beverages, candy, ice cream, and bakery products using TECH with intakes acquired by 24 h dietary recalls. Participants were 39 healthy, Swedish children (5.5 ± 0.5 years) within the ongoing Mobile-based Intervention Intended to Stop Obesity in Preschoolers (MINISTOP) obesity prevention trial. Energy and food intakes were assessed during four days using TECH and 24 h telephone dietary recalls. Mean EI (TECH) was not statistically different from TEE (DLW) (5820 ± 820 kJ/24 h and 6040 ± 680 kJ/24 h, respectively). No significant differences in the average food intakes using TECH and 24 h dietary recalls were found. All food intakes were correlated between TECH and the 24 h dietary recalls (ρ = 0.665-0.896, p < 0.001). In conclusion, TECH accurately estimated the average intakes of energy and selected foods and thus has the potential to be a useful tool for dietary studies in pre-school children, for example obesity prevention trials.

Assessment of energy requirements in patients with short bowel syndrome by using the doubly labeled water method

BACKGROUND

Short bowel syndrome (SBS) is a serious malabsorption disorder, and dietetic management of patients with SBS is extremely challenging. Once the degree of undernutrition has been assessed, successful dietary intervention is contingent on an accurate estimation and provision of energy needs.

OBJECTIVE

We quantified total energy expenditure (TEE) in patients with SBS by using the doubly labeled water (DLW) method to inform energy needs and nutritional therapy goals.

DESIGN

In this observational study, TEE was measured in 22 participants, 11 with SBS and 11 sex-, age-, and body mass index (BMI)-matched controls (non-SBS), for 14 d with the DLW method. Predicted energy requirements were determined by using the Escott-Stump equation and compared with TEE determined with DLW. Resting energy expenditure was measured by using indirect calorimetry, and an accelerometer was also used to determine physical activity level.

RESULTS

Participants were aged (mean ± SD) 53 ± 8 y. Measured TEE was significantly higher than predicted TEE for the SBS group (1875 ± 276 compared with 1517 ± 175 kcal/d, P = 0.001) and also for the non-SBS group (2393 ± 445 compared with 1532 ± 178 kcal/d, P < 0.01). Measured TEE was significantly lower in the SBS group than in the non-SBS group (P < 0.01); however, predicted TEE did not differ significantly between the groups (P = 0.84). No significant differences were seen between measured and predicted resting energy expenditure either within or between groups.

CONCLUSIONS

Measured TEE in patients with SBS was significantly higher than predicted by using standard equations but also lower than values for age-, BMI-, and sex-matched non-SBS controls. Currently used formulas in clinical practice appear to underestimate energy requirements of patients with SBS, and revision is needed to prevent underfeeding and improve long-term prognosis. This trial was registered at clinicaltrials.gov as NCT02113228.

Protein ingestion acutely inhibits insulin-stimulated muscle carnitine uptake in healthy young men

BACKGROUND

Increasing skeletal muscle carnitine content represents an appealing intervention in conditions of perturbed lipid metabolism such as obesity and type 2 diabetes but requires chronic L-carnitine feeding on a daily basis in a high-carbohydrate beverage.

OBJECTIVE

We investigated whether whey protein ingestion could reduce the carbohydrate load required to stimulate insulin-mediated muscle carnitine accretion.

DESIGN

Seven healthy men [mean ± SD age: 24 ± 5 y; body mass index (in kg/m(2)): 23 ± 3] ingested 80 g carbohydrate, 40 g carbohydrate + 40 g protein, or control (flavored water) beverages 60 min after the ingestion of 4.5 g L-carnitine tartrate (3 g L-carnitine; 0.1% (2)[H]3-L-carnitine). Serum insulin concentration, net forearm carnitine balance (NCB; arterialized-venous and venous plasma carnitine difference × brachial artery flow), and carnitine disappearance (Rd) and appearance (Ra) rates were determined at 20-min intervals for 180 min.

RESULTS

Serum insulin and plasma flow areas under the curve (AUCs) were similarly elevated by carbohydrate [4.5 ± 0.8 U/L · min (P < 0.01) and 0.5 ± 0.6 L (P < 0.05), respectively] and carbohydrate+protein [3.8 ± 0.6 U/L · min (P < 0.01) and 0.4 ± 0.6 L (P = 0.05), respectively] consumption, respectively, compared with the control visit (0.04 ± 0.1 U/L · min and -0.5 ± 0.2 L). Plasma carnitine AUC was greater after carbohydrate+protein consumption (3.5 ± 0.5 mmol/L · min) than after control and carbohydrate visits [2.1 ± 0.2 mmol/L · min (P < 0.05) and 1.9 ± 0.3 mmol/L · min (P < 0.01), respectively]. NCB AUC with carbohydrate (4.1 ± 3.1 μmol) was greater than during control and carbohydrate-protein visits (-8.6 ± 3.0 and -14.6 ± 6.4 μmol, respectively; P < 0.05), as was Rd AUC after carbohydrate (35.7 ± 25.2 μmol) compared with control and carbohydrate consumption [19.7 ± 15.5 μmol (P = 0.07) and 14.8 ± 9.6 μmol (P < 0.05), respectively].

CONCLUSIONS

The insulin-mediated increase in forearm carnitine balance with carbohydrate consumption was acutely blunted by a carbohydrate+protein beverage, which suggests that carbohydrate+protein could inhibit chronic muscle carnitine accumulation.

A systematic review and meta-analysis of randomized controlled trials of the impact of sleep duration on adiposity and components of energy balance

Recent epidemiological and ecological trends in humans indicate a possible causal relationship between sleep duration and energy balance. We aimed to find experimental evidence that has tested this relationship between sleep duration and measures of body composition, food intake or biomarkers related to food intake. We conducted a systematic literature review using six databases throughout 7 August 2014. We sought reports of randomized controlled trials where sleep duration was manipulated and measured outcomes were body weight or other body composition metrics, food intake, and/or biomarkers related to eating. We found 18 unique studies meeting all criteria: eight studies with an outcome of body weight (4 - increased sleep, 4 - reduced sleep); four studies on food intake; four studies of sleep restriction on total energy expenditure and three of respiratory quotient; and four studies on leptin and/or ghrelin. Few controlled experimental studies have addressed the question of the effect of sleep on body weight/composition and eating. The available experimental literature suggests that sleep restriction increases food intake and total energy expenditure with inconsistent effects on integrated energy balance as operationalized by weight change. Future controlled trials that examine the impact of increased sleep on body weight/energy balance factors are warranted.

Energy gap in the aetiology of body weight gain and obesity: a challenging concept with a complex evaluation and pitfalls

The concept of energy gap(s) is useful for understanding the consequence of a small daily, weekly, or monthly positive energy balance and the inconspicuous shift in weight gain ultimately leading to overweight and obesity. Energy gap is a dynamic concept: an initial positive energy gap incurred via an increase in energy intake (or a decrease in physical activity) is not constant, may fade out with time if the initial conditions are maintained, and depends on the 'efficiency' with which the readjustment of the energy imbalance gap occurs with time. The metabolic response to an energy imbalance gap and the magnitude of the energy gap(s) can be estimated by at least two methods, i.e. i) assessment by longitudinal overfeeding studies, imposing (by design) an initial positive energy imbalance gap; ii) retrospective assessment based on epidemiological surveys, whereby the accumulated endogenous energy storage per unit of time is calculated from the change in body weight and body composition. In order to illustrate the difficulty of accurately assessing an energy gap we have used, as an illustrative example, a recent epidemiological study which tracked changes in total energy intake (estimated by gross food availability) and body weight over 3 decades in the US, combined with total energy expenditure prediction from body weight using doubly labelled water data. At the population level, the study attempted to assess the cause of the energy gap purported to be entirely due to increased food intake. Based on an estimate of change in energy intake judged to be more reliable (i.e. in the same study population) and together with calculations of simple energetic indices, our analysis suggests that conclusions about the fundamental causes of obesity development in a population (excess intake vs. low physical activity or both) is clouded by a high level of uncertainty.

Estimating the energy costs of intermittent exercise

To date, steady state models represent the only acceptable methodology for the estimation of exercise energy costs. Conversely, comparisons made between continuous and intermittent exercise generally reveal major physiological discrepancies, leading to speculation as to why steady state energy expenditure models should be applied to intermittent exercise. Under intermittent conditions, skeletal muscle invokes varying aerobic and anaerobic metabolic responses, each with the potential to make significant contributions to overall energy costs. We hypothesize that if the aerobic-only energetic profile of steady state exercise can be used to estimate the energetics of non-steady state and intermittent exercise, then the converse also must be true. In fact, reasonable estimates of energy costs to work volumes or work rates can be demonstrated under steady state, non-steady state and intermittent conditions; the problem with the latter two is metabolic variability. Using resistance training as a model, estimates of both aerobic and anaerobic energy cost components, as opposed to one or the other, have reduced the overall energetic variability that appears inherent to brief, intense, intermittent exercise models.

Validity of 24-h recalls in (pre-)school aged children: comparison of proxy-reported energy intakes with measured energy expenditure

BACKGROUND & AIMS

Little is known about the validity of repeated 24-h dietary recalls (24-HDR) as a measure of total energy intake (EI) in young children. This study aimed to evaluate the validity of proxy-reported EI by comparison with total energy expenditure (TEE) measured by the doubly labeled water (DLW) technique.

METHODS

The agreement between EI and TEE was investigated in 36 (47.2% boys) children aged 4-10 years from Belgium and Spain using subgroup analyses and Bland-Altman plots. Low-energy-reporters (LER), adequate-energy-reporters (AER) and high-energy-reporters (HER) were defined from the ratio of EI over TEE by application of age- and sex-specific cut-off values.

RESULTS

There was good agreement between means of EI (1500 kcal/day) and TEE (1523 kcal/day) at group level though in single children, i.e. at the individual level, large differences were observed. Almost perfect agreement between EI and TEE was observed in thin/normal weight children (EI: 1511 kcal/day; TEE: 1513 kcal/day). Even in overweight/obese children the mean difference between EI and TEE was only -86 kcal/day. Among the participants, 28 (78%) were classified as AER, five (14%) as HER and three (8%) as LER.

CONCLUSION

Two proxy-reported 24-HDRs were found to be a valid instrument to assess EI on group level but not on the individual level.

Approaches for quantifying energy intake and %calorie restriction during calorie restriction interventions in humans: the multicenter CALERIE study

Calorie restriction (CR) is a component of most weight loss interventions and a potential strategy to slow aging. Accurate determination of energy intake and %CR is critical when interpreting the results of CR interventions; this is most accurately achieved using the doubly labeled water method to quantify total energy expenditure (TEE). However, the costs and analytical requirements of this method preclude its repeated use in many clinical trials. Our aims were to determine 1) the optimal TEE assessment time points for quantifying average energy intake and %CR during long-term CR interventions and 2) the optimal approach for quantifying short-term changes in body energy stores to determine energy intake and %CR during 2-wk DLW periods. Adults randomized to a CR intervention in the multicenter CALERIE study underwent measurements of TEE by doubly labeled water and body composition at baseline and months 1, 3, and 6. Average %CR achieved during the intervention was 24.9 ± 8.7%, which was computed using an approach that included four TEE assessment time points (i.e., TEE(baseline, months 1, 3, and 6)) plus the 6-mo change in body composition. Approaches that included fewer TEE assessments yielded %CR values of 23.4 ± 9.0 (TEE(baseline,) months 3 and 6), 25.0 ± 8.7 (TEE(baseline,) months 1 and 6), and 20.9 ± 7.1% (TEE(baseline, month 6)); the latter approach differed significantly from approach 1 (P < 0.001). TEE declined 9.6 ± 9.9% within 2-4 wk of CR beginning and then stabilized. Regression of daily home weights provided the most reliable estimate of short-term change in energy stores. In summary, optimal quantification of energy intake and %CR during weight loss necessitates a TEE measurement within the first month of CR to capture the rapid reduction in TEE.