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Obesity is caused by a prolonged positive energy balance1,2. Whether reduced energy expenditure stemming from reduced activity levels contributes is debated3,4. Here we show that in both sexes, total energy expenditure (TEE) adjusted for body composition and age declined since the late 1980s, while adjusted activity energy expenditure increased over time. We use the International Atomic Energy Agency Doubly Labelled Water database on energy expenditure of adults in the United States and Europe (n = 4,799) to explore patterns in total (TEE: n = 4,799), basal (BEE: n = 1,432) and physical activity energy expenditure (n = 1,432) over time. In males, adjusted BEE decreased significantly, but in females this did not reach significance. A larger dataset of basal metabolic rate (equivalent to BEE) measurements of 9,912 adults across 163 studies spanning 100 years replicates the decline in BEE in both sexes. We conclude that increasing obesity in the United States/Europe has probably not been fuelled by reduced physical activity leading to lowered TEE. We identify here a decline in adjusted BEE as a previously unrecognized factor.

Background: Previous data have demonstrated that Tour de France riders maintain total daily energy expenditure (TDEE) between 3.5 and 5.5 times the basal metabolic rate (×BMR). In contrast, TDEE for healthy male septuagenarians has been reported to average 1.3 to 2.0 ×BMR. Purpose: Measure the TDEE and water efflux during ultraendurance work in an older population during the cross-continent cycling Race Across America. Methods: A 4-man septuagenarian team (70 [1.6] y, 72.0 [5.1] kg) received an oral dose of doubly labeled water prior to completing the Race Across America (4817 km, 51,816 m of climbing) for TDEE calculation. Nude body weight measures were coupled with collected urine samples. Results: The race was completed in approximately 6.5 days (official time: 6 d, 13 h, and 13 min) with an average speed of 30.6 (0.7) km·h−1 (age-group course record). Body weight remained unchanged (prerace: 70.4 [5.8] kg, postrace: 70.0 [5.3] kg). TDEE was calculated over 3 race segments. TDEE varied between individual riders and segments throughout the continuous event (24.7 [4.2] MJ·24 h−1, 5900 [1015] kcals·24 h−1, 3.4 [0.5] ×BMR). Water efflux averaged 10.2 (0.8) L·24 h−1 resulting in a total turnover of 45.3 (3.9) L amounting to 1.5 (0.2) times initial total body water during the race. Conclusions: Highly active septuagenarians maintain body weight prerace to postrace, suggesting near energy balance when TDEE approaches 4 ×BMR. These values exceed twice those of previously observed healthy but less active septuagenarian men and are comparable to professional riders during portions of the Tour de France. Advanced age and high metabolic output are not mutually exclusive.

To date, nutritional epidemiology has relied heavily on relatively weak methods including simple observational designs and substandard measurements. Despite low internal validity and other sources of bias, claims of causality are made commonly in this literature. Nutritional epidemiology investigations can be improved through greater scientific rigor and adherence to scientific reporting commensurate with research methods used. Some commentators advocate jettisoning nutritional epidemiology entirely, perhaps believing improvements are impossible. Still others support only normative refinements. But neither abolition nor minor tweaks are appropriate. Nutritional epidemiology, in its present state, offers utility, yet also needs marked, reformational renovation. Changing the status quo will require ongoing, unflinching scrutiny of research questions, practices, and reporting—and a willingness to admit that “good enough” is no longer good enough. As such, a workshop entitled “Toward more rigorous and informative nutritional epidemiology: the rational space between dismissal and defense of the status quo” was held from July 15 to August 14, 2020. This virtual symposium focused on: (1) Stronger Designs, (2) Stronger Measurement, (3) Stronger Analyses, and (4) Stronger Execution and Reporting. Participants from several leading academic institutions explored existing, evolving, and new better practices, tools, and techniques to collaboratively advance specific recommendations for strengthening nutritional epidemiology.

Total daily energy expenditure (“total expenditure”, MJ/d) reflects daily energy needs and is a critical variable in human health and physiology, yet it is unclear how daily expenditure changes over the life course. Here, we analyze a large, globally diverse database of total expenditure measured by the doubly labeled water method for males and females aged 8 days to 95 yr. We show that total expenditure is strongly related to fat free mass in a power-law manner and identify four distinct metabolic life stages. Fat free mass-adjusted daily expenditure accelerates rapidly in neonates (0-1yr) to ~46% above adult values at ~1 yr, declines slowly throughout childhood and adolescence (1-20 yr) to adult levels at ~20 yr, remains stable in adulthood (20-60 yr) even during pregnancy, and declines in older adults (60+ yr). These changes in total expenditure shed new light on human development and aging and should help shape nutrition and health strategies across the lifespan.

BACKGROUND Objective dietary biomarkers are urgently needed for a wider range of foods and nutrients. The breath carbon isotope ratio (CIR; measured as δ13C values) has potential as a noninvasive measure of short-term added sugar (AS) intake but has not been evaluated in a controlled-feeding study. OBJECTIVE The aim was to evaluate the effect of short-term AS intake on breath CIR in a dose-response, randomized, crossover feeding study. METHODS Six men and 6 women, aged 25 to 60 y, were randomly assigned to a balanced sequence of 5 dietary treatments. Three treatments delivered low (0 g/d), medium (75 g/d), or high (150 g/d) amounts of AS over the course of a single day's breakfast and lunch and 2 switched high and low intake amounts between breakfast and lunch. Experimental meals delivered 60% of daily energy and added-sugar targets. There was a washout period of 1-2 wk between treatments. Breath was collected at 2-h intervals from 08:00 (fasting) to 16:00 h. Breath CIR was measured using cavity ring-down spectroscopy, and the effects of dietary treatments and baseline were evaluated using multivariate linear regression. RESULTS Breath CIR showed a significant response to increasing AS intake at all sampling time points (all P < 0.0001), with a dose-response of 0.030 (95% CI: 0.024, 0.037) ‰/g. Fasting breath CIR (baseline) influenced postfeeding breath CIR at all sampling time points (P < 0.0001); however, effect sizes were largest in the morning. For afternoon-collected samples (14:00 and 16:00), the effect of recent AS intake (lunch) was 4-fold greater than the effect of previous added-sugar intake (breakfast). CONCLUSIONS These findings support the potential of the breath CIR as a biomarker of short-term AS intake in healthy US adults. More work is needed to evaluate other potential dietary effects and whether multiple breath collections could capture daily AS intake.

BACKGROUND: Multiple methods of correcting nutrient intake for misreported energy intake have been proposed but have not been extensively compared. The availability of the Women's Health Initiative (WHI) data set, which includes several objective recovery biomarkers, offers an opportunity to compare these corrections with respect to protein intake. OBJECTIVE: We compared 5 energy-correction methods for self-reported dietary protein against urinary nitrogen–derived protein intake. METHODS: As part of the WHI Nutritional Biomarkers Study (NBS) 544 participants (50- to 80-y-old women) completed a FFQ and biomarker assessments using doubly labeled water (DLW) for total energy expenditure (TEE) and 24-h urinary nitrogen. Correction methods evaluated were as follows: 1) DLW-TEE; 2) the Institute of Medicine's (IOM's) estimated energy requirement (EER) TEE prediction equation based on sex, height, weight, and age; 3) published NBS total energy TEE prediction (WHI-NBS-TEE) using age, BMI, race, and income; 4) reported protein versus reported energy linear regression–based residual method; and 5) a Goldberg cutoff to exclude subjects reporting energy intakes

Background/Objectives: The winter holiday season in the US, which spans mid-November to mid-January, contributes to over half of annual body weight gain. Although self-reported data has linked this weight change to both increased energy intake and reduced physical activity, objective techniques have never been used and thus the actual cause of holiday weight gain is controversial. Here, we aimed to determine changes in components of energy balance leading to the holiday weight gain. Methods: Body weight change was compared between the pre-holiday (mid-September to mid-November) and the holiday period (mid-November to early January). Total energy expenditure (TEE) was measured using doubly labeled water during holiday time (early to mid-December). Subjective (ratings) and physiological (appetite-regulating hormones) measures of appetite, eating-away-from-home frequency, and incentive salience of food pictures were also evaluated. Results: In 23 obese adults (87% female), body weight change during the holidays (0.41 ± 0.42 kg) was significantly higher (P=0.02) than the body weight change during the pre-holiday period (−0.86 kg ± 0.42 kg). The TEE was unchanged during the two periods, suggesting no role of energy expenditure on weight gain. However, participants reported lower satisfaction after a meal pre-load which was significantly correlated with increased body weight during the holiday period. An increase in number of episodes of eating at sit-down restaurants was also reported during that period. Overall, these changing behaviors were supported by a non-significant increase in energy intake (+80 kcal/day, P=0.07) observed during the study holiday period. Conclusion: We conclude that a decrease in energy expenditure does not result in the weight increase, but that an increase in food intake is the more likely cause. Our data imply that compromised internal satiety mechanisms in presence of external food cues and diet related behavioral variables during the holidays may influence this weight gain.

Few biomarker-based validation studies have examined error in online self-report dietary assessment instruments, and food records (FRs) have been considered less than food frequency questionnaires (FFQs) and 24-hour recalls (24HRs). We investigated measurement error in online and paper-based FFQs, online 24HRs, and paper-based FRs in 3 samples drawn primarily from 3 cohorts, comprising 1,393 women and 1,455 men aged 45–86 years. Data collection occurred from January 2011 to October 2013. Attenuation factors and correlation coefficients between reported and true usual intake for energy, protein, sodium, potassium, and respective densities were estimated using recovery biomarkers. Across studies, average attenuation factors for energy were 0.07, 0.07, and 0.19 for a single FFQ, 24HR, and FR, respectively. Correlation coefficients for energy were 0.24, 0.23, and 0.40, respectively. Excluding energy, the average attenuation factors across nutrients and studies were 0.22 for a single FFQ, 0.22 for a single 24HR, and 0.51 for a single FR. Corresponding correlation coefficients were 0.31, 0.34, and 0.53, respectively. For densities (nutrient expressed relative to energy), the average attenuation factors across studies were 0.37, 0.17, and 0.50, respectively. The findings support prior research suggesting different instruments have unique strengths that should be leveraged in epidemiologic research.

Short sleep duration has been recognized as a risk factor for obesity. Whether extending sleep duration may mitigate this risk remains unknown.To determine the effects of a sleep extension intervention on objectively assessed energy intake, energy expenditure, and body weight in real-life settings among adults with overweight who habitually curtailed their sleep duration.This single-center, randomized clinical trial was conducted from November 1, 2014, to October 30, 2020. Participants were adults aged 21 to 40 years with a body mass index (calculated as weight in kilograms divided by height in meters squared) between 25.0 and 29.9 and had habitual sleep duration of less than 6.5 hours per night. Data were analyzed according to the intention-to-treat principle.After a 2-week habitual sleep period at baseline, participants were randomized to either an individualized sleep hygiene counseling session that was intended to extend their bedtime to 8.5 hours (sleep extension group) or to continue their habitual sleep (control group). All participants were instructed to continue daily routine activities at home without any prescribed diet or physical activity.The primary outcome was change in energy intake from baseline, which was objectively assessed as the sum of total energy expenditure and change in body energy stores. Total energy expenditure was measured by the doubly labeled water method. Change in body energy stores was computed using regression of daily home weights and body composition changes from dual-energy x-ray absorptiometry. Sleep duration was monitored by actigraphy. Changes from baseline were compared between the 2 groups using intention-to-treat analysis.Data from 80 randomized participants (mean [SD] age, 29.8 [5.1] years; 41 men [51.3%]) were analyzed. Sleep duration was increased by approximately 1.2 hours per night (95% CI, 1.0 to 1.4 hours; P .001) in the sleep extension group vs the control group. The sleep extension group had a significant decrease in energy intake compared with the control group (-270 kcal/d; 95% CI, -393 to -147 kcal/d; P .001). The change in sleep duration was inversely correlated with the change in energy intake (r = -0.41; 95% CI, -0.59 to -0.20; P .001). No significant treatment effect in total energy expenditure was found, resulting in weight reduction in the sleep extension group vs the control group.This trial found that sleep extension reduced energy intake and resulted in a negative energy balance in real-life settings among adults with overweight who habitually curtailed their sleep duration. Improving and maintaining healthy sleep duration over longer periods could be part of obesity prevention and weight loss programs.ClinicalTrials.gov Identifier: NCT02253368.

In mammals, trait variation is often reported to be greater among males than females. However, to date, mainly only morphological traits have been studied. Energy expenditure represents the metabolic costs of multiple physical, physiological, and behavioral traits. Energy expenditure could exhibit particularly high greater male variation through a cumulative effect if those traits mostly exhibit greater male variation, or a lack of greater male variation if many of them do not. Sex differences in energy expenditure variation have been little explored. We analyzed a large database on energy expenditure in adult humans (1494 males and 3108 females) to investigate whether humans have evolved sex differences in the degree of interindividual variation in energy expenditure. We found that, even when statistically comparing males and females of the same age, height, and body composition, there is much more variation in total, activity, and basal energy expenditure among males. However, with aging, variation in total energy expenditure decreases, and because this happens more rapidly in males, the magnitude of greater male variation, though still large, is attenuated in older age groups. Considerably greater male variation in both total and activity energy expenditure could be explained by greater male variation in levels of daily activity. The considerably greater male variation in basal energy expenditure is remarkable and may be explained, at least in part, by greater male variation in the size of energy-demanding organs. If energy expenditure is a trait that is of indirect interest to females when choosing a sexual partner, this would suggest that energy expenditure is under sexual selection. However, we present a novel energetics model demonstrating that it is also possible that females have been under stabilizing selection pressure for an intermediate basal energy expenditure to maximize energy available for reproduction. (C) 2022 The Author(s). Published by Elsevier Ltd.

PURPOSE 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 yrs.) 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 non-linear methods (restricted cubic splines). Percent weight change (>3%) over a six-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 in the bottom decile to 2693 (SD = 480) kcal/d 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 in the bottom decile to 2372 (SD = 560) kcal/d in the top decile. CONCLUSION Energy balance status appears 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 appears 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.

Background: The doubly labelled water (DLW) method is an isotope-based technique that quantifies total energy expenditure (TEE) over periods of 1–3 weeks from the differential elimination of stable isotopes of oxygen and hydrogen. The method was invented in the 1950s, but limited ability to measure low isotope enrichments combined with the high cost of isotopes meant it only became feasible to use in humans in the 1980s. It is still relatively expensive to use, and alone small samples are unable to tackle some of the important questions surrounding energy balance such as how have expenditures changed over time and how do expenditures differ with age, between sexes and in different environments? Summary: By combining information across studies, answers to such questions may be possible. The International Atomic Energy Agency (IAEA) DLW database was established to pool DLW data across multiple studies. It was initiated by the main labs currently using the method and is hosted by the IAEA. At present, the database contains 6,621 measures of TEE by DLW from individuals in 23 countries, along with various additional data on the study participants. Key Messages: The IAEA DLW database is a key resource enabling future studies of energy demands.

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.

Publisher Copyright: © 2021 The Authors Understanding the impacts of activity on energy balance is crucial. Increasing levels of activity may bring diminishing returns in energy expenditure because of compensatory responses in non-activity energy expenditures.1–3 This suggestion has profound implications for both the evolution of metabolism and human health. It implies that a long-term increase in activity does not directly translate into an increase in total energy expenditure (TEE) because other components of TEE may decrease in response—energy compensation. We used the largest dataset compiled on adult TEE and basal energy expenditure (BEE) (n = 1,754) of people living normal lives to find that energy compensation by a typical human averages 28% due to reduced BEE; this suggests that only 72% of the extra calories we burn from additional activity translates into extra calories burned that day. Moreover, the degree of energy compensation varied considerably between people of different body compositions. This association between compensation and adiposity could be due to among-individual differences in compensation: people who compensate more may be more likely to accumulate body fat. Alternatively, the process might occur within individuals: as we get fatter, our body might compensate more strongly for the calories burned during activity, making losing fat progressively more difficult. Determining the causality of the relationship between energy compensation and adiposity will be key to improving public health strategies regarding obesity.

PURPOSE: To identify the accuracy of Body Mass Index (BMI) to categorize body weight in a sample of children with spina bifida and Down syndrome as compared to typically developing peers. METHODS: A secondary analysis of 32 children with spina bifida, Down syndrome or no chronic illness. A calculated BMI was plotted on the Centers for Disease Control and Prevention age- and sex-specific BMI growth charts to determine each child’s weight status. Percentage of body fat, obtained by labeled water, was plotted on two different body fat percentile reference curves, one derived from a whole body measure (DXA) of body fat and one by skin-fold measure. Differences in weight categories between calculated BMI and body fat percentile curves were reported. RESULTS: The calculated BMI for children with a disability had significant misclassifications as a screening tool for body fat when compared to children without a disability. Misclassifications were increased with the body fat percentile reference curve derived from skin-fold measures and for children who primarily used a wheelchair. CONCLUSION: The current recommendation to use BMI to categorize weight status is not useful for many children with disabilities. Further research to identify an alternative pragmatic strategy is necessary.

RATIONALE This study determines if saliva collection procedures for the doubly labeled water (DLW) method, used for measuring total energy expenditure (TEE), are comparable to urine and plasma collection. Both the cavity ring-down spectroscopy (CRDS) and isotope ratio mass spectrometry (IRMS) analyses techniques are compared. METHODS Saliva specimens were collected from participants for the DLW method. The specimens were collected under different conditions: after consumption of tap water, after chewing gum, and during exposure to conditions of high and low relative humidity. The isotopes in saliva were compared with simultaneous plasma and urine collection. TEE calculated from saliva and analyzed using CRDS was compared to that of plasma analyzed using IRMS. RESULTS The within-individual variances were not significantly different between the saliva specimens (0.4‰) and plasma (0.3‰). After the oral dose of DLW, the saliva specimens displayed a shorter equilibration time to urine. When participants consumed 500 mL of tap water, the enrichment of saliva specimens reached a new plateau value faster than urine. Saliva collection exposed to high ambient humidity conditions was slightly less enriched as compared to low-humidity conditions while urine enrichment was unaffected. In contrast, whereas the within-individual effects of gum chewing during saliva collection on 18 O were unaffected, the abundance of 2 H in saliva was slightly lower after chewing the gum. The within-individual difference between TEE calculated from saliva and that calculated from plasma analyzed using IRMS did not differ from zero, and the standard deviation was not different from that predicted by a propagation of error analysis based on analytical error alone. CONCLUSIONS Our findings support using saliva specimens for the DLW method. The analysis of plasma and urine, however, requires reducing the memory effect resulting from contaminants. Also, it should be performed in a manner that minimizes exposure to air where specimens may be exposed to evaporation or contamination from water vapor during sampling.

Background The Goldberg cutoffs are used to decrease bias in self-reported estimates of energy intake (EISR). Whether the cutoffs reduce and eliminate bias when used in regressions of health outcomes has not been assessed. Objective We examined whether applying the Goldberg cutoffs to data used in nutrition studies could reliably reduce or eliminate bias. Methods We used data from the Comprehensive Assessment of Long-Term Effects of Reducing Intake of Energy (CALERIE), the Interactive Diet and Activity Tracking in American Association of Retired Persons (IDATA) study, and the National Diet and Nutrition Survey (NDNS). Each data set included EISR, energy intake estimated from doubly labeled water (EIDLW) as a reference method, and health outcomes including baseline anthropometric, biomarker, and behavioral measures and fitness test results. We conducted 3 linear regression analyses using EISR, a plausible EISR based on the Goldberg cutoffs (EIG), and EIDLW as an explanatory variable for each analysis. Regression coefficients were denoted ${\hat{\beta }_{\rm SR}}$, ${\hat{\beta }_{\rm G}}$, and ${\hat{\beta }_{\rm DLW}}$, respectively. Using the jackknife method, bias from ${\hat{\beta }_{\rm SR}}$ compared with ${\hat{\beta }_{\rm DLW}}$ and remaining bias from ${\hat{\beta }_{\rm G}}$ compared with ${\hat{\beta }_{\rm DLW}}$ were estimated. Analyses were repeated using Pearson correlation coefficients. Results The analyses from CALERIE, IDATA, and NDNS included 218, 349, and 317 individuals, respectively. Using EIG significantly decreased the bias only for a subset of those variables with significant bias: weight (56.1%; 95% CI: 28.5%, 83.7%) and waist circumference (WC) (59.8%; 95% CI: 33.2%, 86.5%) with CALERIE, weight (20.8%; 95% CI: -6.4%, 48.1%) and WC (17.3%; 95% CI: -20.8%, 55.4%) with IDATA, and WC (-9.5%; 95% CI: -72.2%, 53.1%) with NDNS. Furthermore, bias significantly remained even after excluding implausible data for various outcomes. Results obtained with Pearson correlation coefficient analyses were qualitatively consistent. Conclusions Some associations between EIG and outcomes remained biased compared with associations between EIDLW and outcomes. Use of the Goldberg cutoffs was not a reliable method for eliminating bias.

Medical nutrition therapy for long-chain fatty acid oxidation disorders (LC-FAODs) currently emphasizes fasting avoidance, restricted dietary long-chain fatty acid intake, supplementation with medium chain triglycerides, and increased carbohydrate intake. We hypothesize that increasing dietary protein intake relative to carbohydrate intake would preserve metabolic control yet induce physical benefits including reduced hepatic lipogenesis. Therefore, we compared two dietary approaches with similar fat intake but different carbohydrate to protein ratios in participants diagnosed with LC-FAODs. Thirteen participants were enrolled and randomized into either a high-protein (PRO) or a high-carbohydrate (CHO) diet for 4 months. Baseline and 4-month assessments included body composition, ectopic lipid deposition, and resting energy expenditure. End of study assessments also included total energy expenditure, metabolic responses to oral feedings, and whole-body fatty acid oxidation capacity. At the end of the dietary intervention, both groups had similar energy expenditure, fat and glucose oxidation rates, and glucolipid responses to mixed meal and oral glucose loads. Neither dietary group experienced worsening symptoms related to their LC-FAOD. Compared to the CHO group, the PRO group exhibited increased blood levels of short-chain acylcarnitines, reduced intrahepatic lipid content, and maintained lean body mass while the CHO group lost lean mass. In patients with LC-FAODs, increasing protein intake maintained metabolic control, reduced liver fat without risk of metabolic decompensation, and helped preserve lean body mass. We propose that a modest increase in dietary protein along with fasting avoidance and fat restriction may improve body composition and energy expenditure in patients with LC-FAODs.

BACKGROUND: To examine the feasibility and acceptability of a self-report activity diary completed by parents and older children to assess the child’s daily activity in children with and without special needs. METHODS: The study included 36 child/parent dyads stratified by child age and diagnosis. Parents (n=36) and children ≥13 years (n=12) were asked to report on the child’s daily activity using an activity diary. Feasibility was determined based on successfully returned diaries and acceptability via post-study interview. RESULTS: Activity diaries were submitted by 94% of the parents and 100% of the children, with 83% and 80%, respectively, successfully completed. Comments provided post-study regarding the diaries were primarily on the format and were generally negative. CONCLUSIONS: This activity diary was feasible to use, but not well accepted within our sample of children with and without special needs or their parents. Further research is needed to create valid physical activity assessment measures that are population specific for individuals with special needs.

Daily water intake (DWI) is essential for survival in humans; however, accurate assessment of DWI from drinks and beverages (Wdrinks) or food moisture (Wfoods) is difficult as it depends on self-reported intakes that are prone to inaccuracy. Here, we established an objective method to assess DWI components using doubly labeled water (DLW). Deuterium and H218O were orally administered, and the dilution space and elimination rate of 2H and 18O were measured. DWI was calculated from the deuterium turnover corrected for metabolic water production and insensible water absorption from humidity. Wfoods was estimated using dietary record (Wfoods-DR) or calculated from the total energy expenditure assessed by DLW (Wfoods-DLW). The current results underscore Wfoods-DR underestimation using self-reported dietary assessments, which underestimates food intake. This study proposes novel methods for calculating each DWI component using DLW.

Summary 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 (, Graphical Abstract, Highlights 5,756 doubly labeled water (DLW) measures highlight variation from calculation equation We derive here new equations for calculating CO2 production when using DLW These equations outperform previous equations in validation studies We recommend these equations should be adopted in future studies using DLW in humans, Speakman et al. use a large database of doubly labeled water measurements to show the choice of equation for the calculation of energy expenditure introduces significant variation into the final estimate. They then derive new equations that outperform previous equations in validation studies against chamber calorimetry.

Summary To sustain life, humans and other terrestrial animals must maintain a tight balance of water gain and water loss each day. 1 , 2 , 3 However, the evolution of human water balance physiology is poorly understood due to the absence of comparative measures from other hominoids. While humans drink daily to maintain water balance, rainforest-living great apes typically obtain adequate water from their food and can go days or weeks without drinking 4 , 5 , 6 . Here, we compare isotope-depletion measures of water turnover (L/d) in zoo- and rainforest-sanctuary-housed apes (chimpanzees, bonobos, gorillas, and orangutans) with 5 diverse human populations, including a hunter-gatherer community in a semi-arid savannah. Across the entire sample, water turnover was strongly related to total energy expenditure (TEE, kcal/d), physical activity, climate (ambient temperature and humidity), and fat free mass. In analyses controlling for those factors, water turnover was 30% to 50% lower in humans than in other apes despite humans’ greater sweating capacity. Water turnover in zoo and sanctuary apes was similar to estimated turnover in wild populations, as was the ratio of water intake to dietary energy intake (∼2.8 mL/kcal). However, zoo and sanctuary apes ingested a greater ratio of water to dry matter of food, which might contribute to digestive problems in captivity. Compared to apes, humans appear to target a lower ratio of water/energy intake (∼1.5 mL/kcal). Water stress due to changes in climate, diet, and behavior apparently led to previously unknown water conservation adaptations in hominin physiology.

Background: Diet is a modifiable behavior that influences an individual's health. Because of this, diet assessment is an important component of public health surveillance, evaluating response to community health interventions, and monitoring individual compliance to medical interventions. Diet assessments are usually performed using one of three basic methods: diet recall, diet diaries, or food frequency questionnaires. Although these three assessment instruments have displayed a strong agreement between themselves, when reported intake is compared with intake measured using quantitative nutrient biomarkers, investigators have identified systematic misreporting errors for all three of these self-reported dietary instruments. Aims: This work aims to summarize the state of knowledge regarding misreporting and why it impedes diet–health research and to introduce advances in the collection and the treatment of dietary data. Methods: This work reviews and summarizes published data on misreporting and the recent efforts to reduce such errors. Results: The evidence demonstrates a strong and consistent systematic underreporting of energy intake (EIn) across adults and children studies. Underreporting of EIn has been found to increase with body mass index (BMI), and the differences between macronutrient reports indicate that not all foods are underreported equally. Protein is least underreported, but which specific foods are commonly underreported are not known. Conclusions: Because energy underreporting varies as a function of BMI, self-reported EIn should not be used for the study of energy balance in the study of obesity. The between-individual variability in the underreporting of self-reported intake of energy and other nutrients attenuates diet–disease relationships. Recent efforts to correct for underreporting have reduced misreporting of diet outcomes, but improvements have been incremental in nature and more research is needed to validate and extend these efforts.

BACKGROUND: The carbon isotope ratio (CIR) is a proposed biomarker for added sugar (AS) intake in the United States; however, because the CIR is also associated with meat intake in most populations the need for specificity remains. The CIR of amino acids (AAs) has the potential to differentiate sugars from meat intakes, because essential AAs must derive from dietary protein whereas certain nonessential AAs can be synthesized from sugars. OBJECTIVES: We tested whether serum CIR-AAs in combination with participant characteristics could meet a prespecified biomarker criterion for AS intake in the Nutrition and Physical Activity Assessment Study Feeding Study (NPAAS-FS) of the Women's Health Initiative, a population in which the whole-serum CIR was not associated with AS intake. METHODS: Postmenopausal women (n = 145) from Seattle, WA, were provided with individualized diets that approximated their habitual food intakes for 2 wk. Dietary intakes from consumed foods were characterized over the feeding period using the Nutrition Data System for Research. The CIR of 7 AAs—Ala, Gly, Val, Leu, Ile, Pro, and Phe—were measured in fasting serum collected at the end of the 2-wk feeding period, using gas chromatography–combustion isotope ratio mass spectrometry. Biomarker models were evaluated using regression R(2) ≥ 0.36 as a major biomarker criterion, based on the benchmark R(2) values of well-established recovery biomarkers in the NPAAS-FS. RESULTS: AS intake was associated with CIR-Ala (ρ = 0.32; P

Background Millions of infants are fed breast milk substitutes, and the type of infant formula can impact weight gain patterns. Objective We conducted a randomized controlled trial to determine the direct impact of 2 types of infant formula (cow milk formula, CMF; extensively protein hydrolyzed formula, EHF) on growth and energy balance. Design A racially diverse group of formula-fed infants (n = 113) were randomly assigned to either CMF or EHF from the age of 0.75 to 12.5 mo. At each monthly visit, anthropometric measures were obtained to determine growth z scores and weight gain velocity, and to categorize early weight gain patterns as rapid or nonrapid. Also, diet records were collected to determine energy from formula and other sources. Comprehensive assessments of energy balance (intake, expenditure, loss) were made at 0.75, 3.5, and 12.5 mo. Results Beginning 3 wk after randomization, CMF infants had significantly higher weight, but not length, z scores than did EHF infants, and this persisted after solid foods complemented the formula diet. On average, weight gain velocity from 0.75 to 4.5 mo was within the range of typically growing infants for both groups, yet velocity was 3.9 g/d greater for CMF infants (P = 0.002), who were more likely to be classified as an early rapid weight gainer, than EHF infants (46% compared with 18%; P = 0.007). Early differences in energy intake and fecal loss, yielding greater energy available for deposition among CMF infants, contributed to the differential weight gain patterns. There were no significant differences between the formula treatment groups in total energy expenditure or sleeping energy expenditure. Conclusions Among healthy infants, the type of formula impacted on early rapid weight gain patterns owing to energy intake and loss mechanisms. Research is needed to identify the macronutrients and other compositional constituents in EHF and breast milk that promote satiation and healthy weight gain during sensitive periods of development. This trial was registered at clinicaltrials.gov as: NCT01700205.

Background The 4-component (4C) model is a criterion method for human body composition that separates the body into fat, water, mineral, and protein, but requires 4 measurements with significant cost and time requirements that preclude wide clinical use. A simplified model integrating only 2 measurements—dual-energy X-ray absorptiometry (DXA) and bioelectrical impedance analysis (BIA)—and 10 min of patient time has been proposed. Objective We aimed to validate a rapid, simplified 4C DXA + BIA body composition model in a clinical population. Design This was a cross-sectional observational study of 31 healthy adults. Participants underwent whole-body DXA, segmental BIA, air displacement plethysmography (ADP), and total body water (TBW) measurement by deuterium (D2O) dilution. 4C composition was calculated through the use of the Lohman model [DXA mineral mass, D2O TBW, ADP body volume (BV), scale weight] and the simplified model (DXA mineral mass and BV, BIA TBW, scale weight). Accuracy of percentage of fat (%Fat) and protein measurements was assessed via linear regression. Test-retest precision was calculated with the use of duplicate DXA and BIA measurements. Results Of 31 participants, 23 were included in the analysis. TBWBIA showed good test-retest precision (%CV = 5.2 raw; 1.1 after outlier removal) and high accuracy to TBWD2O [TBWD2O = 0.956*TBWBIA, R2= 0.92, root mean squared error (RMSE) = 2.2 kg]. %Fat estimates from DXA, ADP, D2O, and BIA all showed high correlation with the Lohman model. However, only the 4C simplified model provides high accuracy for both %Fat (R2 = 0.96, RMSE = 2.33) and protein mass (R2= 0.76, RMSE = 1.8 kg). %Fat precision from 4C DXA + BIA was comparable with DXA (root mean square-SD = 0.8 and 0.6 percentage units, respectively). Conclusions This work validates a simplified 4C method that measures fat, water, mineral, and protein in a 10-min clinic visit. This model has broad clinical application to monitor many conditions including over/dehydration, malnutrition, obesity, sarcopenia, and cachexia.

BACKGROUND Summer weight gain in children has been reported; however, this is usually based on two time points. Our objective was to investigate monthly variation in weight status. METHODS Cross-sectional, de-identified health records including height, weight and demographics, collected between 2007 and 2012 from South Central Wisconsin in 70 531 children age 5-16 years were analysed. The monthly averages in body mass index (BMI) z-score were analysed cross-sectionally followed by a paired analysis for a subset with one visit each during school and summer months. RESULTS BMI z-scores during the summer months (June-August) were lower than values during the school year (September-May). Of note, there was a rapid decrease in BMI z-scores from May to June, with June BMI z-score values being 0.065 units less (95% CI 0.046-0.085) than those in May, little change from June to August and a rapid increase between the August and September BMI z-scores. CONCLUSION The monthly pattern does not fully agree with previous two-point school-based studies. Results raise concern that the use of two time point measures of BMIs (early fall and late spring) is suboptimal for evaluation of circannual variation. We suggest that future evaluation of the effect of school-based or summer interventions utilizes additional measures in those periods so that a seasonal analysis can be performed.

BackgroundSeveral indirect calorimetry (IC) instruments are commercially available, but comparative validity and reliability data are lacking. Existing data are limited by inconsistencies in protocols, subject characteristics, or single-instrument validation comparisons. The aim of this study was to compare accuracy and reliability of metabolic carts using methanol combustion as the cross-laboratory criterion.MethodsEight 20-minute methanol burn trials were completed on 12 metabolic carts. Respiratory exchange ratio (RER) and percent O-2 and CO2 recovery were calculated.ResultsFor accuracy, 1 Omnical, Cosmed Quark CPET (Cosmed), and both Parvos (Parvo Medics trueOne 2400) measured all 3 variables within 2% of the true value; both DeltaTracs and the Vmax Encore System (Vmax) showed similar accuracy in measuring 1 or 2, but not all, variables. For reliability, 8 instruments were shown to be reliable, with the 2 Omnicals ranking best (coefficient of variation [CV] ConclusionsOmnical, Parvo, Cosmed, and DeltaTrac had greater accuracy and reliability. The small number of instruments tested and expected differences in gas calibration variability limits the generalizability of conclusions. Finally, humidity and temperature could be modified in the laboratory to optimize IC conditions.

Objective Little is known about long-term metabolic (energy expenditure) adaptation after bariatric surgery. Methods Resting metabolic rate under basal conditions (RMR), total daily energy expenditure (TDEE), and body composition were measured in 25 participants in the Longitudinal Assessment of Bariatric Surgery-2. Results Six months after surgery, BMI (±SD) decreased (47 ± 6 kg/m2 to 37 ± 5 kg/m2 ), body fat went from 48% ± 6% to 40% ± 6% fat, and fat-free mass went from 67 ± 9 kg to 60 ± 9 kg. In absolute terms, RMR and TDEE both decreased significantly (1,730 ± 278 kcal/d vs. 1,430 ± 200 kcal/d and 2,879 ± 544 kcal/d vs. 2,369 ± 304 kcal/d), and the achieved energy balance was -1,293 ± 355 kcal/d. Sixteen of these participants underwent repeated measures at ∼24 months; TDEE decreased 6 months postoperatively (2,957 ± 540 kcal/d to 2,423 ± 324 kcal/d; P = 0.0003), but at ∼24 months, TDEE (2,602 ± 471 kcal/d) was not significantly different compared with month 6. The average negative energy balance from baseline to month 24 was -379 ± 131 kcal/d. Conclusions RMR and TDEE fall precipitously in the first 6 months after bariatric surgery, but these adaptive changes were no longer significant after 2 years.

Background Controlled human feeding studies are necessary for robust nutritional biomarker development and validation. Previous feeding studies have typically evaluated single nutrients and tested relatively few diets. Objectives The objectives were 1) to simultaneously associate dietary intake with a range of potential nutritional biomarkers in postmenopausal women by using a controlled feeding study whereby each participant was provided a diet similar to her usual diet and 2) to evaluate serum concentrations of select nutrients as potential biomarkers with the use of established urinary recovery biomarkers of energy and protein as benchmarks for evaluation. Design Postmenopausal women from the Women's Health Initiative (n = 153) were provided with a 2-wk controlled diet in which each individual's menu approximated her habitual food intake as estimated from her 4-d food record and adjusted for estimated energy requirements. Serum biomarkers, including carotenoids, tocopherols, folate, vitamin B-12, and phospholipid fatty acids, were collected at the beginning and end of the feeding period. Doubly labeled water and urinary nitrogen biomarkers were used to derive estimates of energy and protein consumption, respectively. Results Linear regression of (ln-transformed) consumed nutrients on (ln-transformed) potential biomarkers and participant characteristics led to the following regression (R2) values for serum concentration biomarkers: folate, 0.49; vitamin B-12, 0.51; α-carotene, 0.53; β-carotene, 0.39; lutein + zeaxanthin, 0.46; lycopene, 0.32; and α-tocopherol, 0.47. R2 values for percentage of energy from polyunsaturated fatty acids and urinary recovery biomarkers of energy and protein intakes were 0.27, 0.53, and 0.43, respectively. Phospholipid saturated fatty acids and monounsaturated fatty acids and serum γ-tocopherol were weakly associated with intake (R2 Conclusions Serum concentration biomarkers of several vitamins and carotenoids performed similarly to established energy and protein urinary recovery biomarkers in representing nutrient intake variation in a feeding study, and thus are likely suitable for application in this population of postmenopausal women. Further work is needed to identify objective measures of categories of fatty acid intake. This trial was registered at clinicaltrials.gov as NCT00000611.

Background Recent studies suggest kids tend to gain the most weight in summer, but schools are chastised for supporting obesogenic environments. Conclusions on circannual weight gain are hampered by infrequent body mass index (BMI) measurements, and guidance is limited on the optimal timeframe for paediatric weight interventions. Objectives This study characterized circannual trends in BMI in Wisconsin children and adolescents and identified sociodemographic differences in excess weight gain. Methods An observational study was used to pool data from 2010 to 2015 to examine circannual BMI z-score trends for Marshfield Clinic patients age 3 to 17 years. Daily 0.20, 0.50, and 0.80 quantiles of BMI z-score were estimated, stratified by gender, race, and age. Results BMI z-scores increased July to September, followed by a decrease in October to December, and another increase to decrease cycle beginning in February. For adolescents, the summer increase in BMI was greater among those in the upper BMI z-score quantile relative to those in the lower quantile (+0.15 units vs +0.04 units). This pattern was opposite in children. Conclusions BMI increased most rapidly in late summer. This growth persisted through autumn in adolescents who were larger, suggesting weight management support may be beneficial for kids who are overweight at the start of the school year.

Background Automated Self-Administered 24-Hour Dietary Assessment Tool (ASA24) is a self-administered web-based tool designed to collect detailed dietary data at low cost in observational studies. Objective The objectives of this study were to describe, overall and by demographic groups, the performance and feasibility of ASA24-2011 recalls and compare Healthy Eating Index-2015 (HEI-2015) total and component scores to 4-day food records (4DFRs) and food frequency questionnaires (FFQs). Design Over 12 months, participants completed up to 6 ASA24 recalls, 2 web-based FFQs, and 2 unweighed paper-and-pencil 4DFRs. Up to 3 attempts were made to obtain each ASA24 recall. Participants were administered doubly-labeled water to provide a measure of total energy expenditure and collected two 24-hour urine samples to assess concentrations of nitrogen, sodium, and potassium. Participants/setting From January through September 2012, 1,110 adult members of AARP, 50 to 74 years of age, were recruited from the Pittsburgh, PA, area to participate in the Interactive Diet and Activity Tracking in AARP (IDATA) study. After excluding 33 participants who had not completed any dietary assessments, 531 men and 546 women remained. Main outcome measures Response rates, nutrient intakes compared to recovery biomarkers across each ASA24 administration day, and HEI-2015 total and component scores were measured. Statistical analyses performed Means, medians, standard deviations, interquartile ranges, and HEI-2015 total and component scores computed using a multivariate measurement error model are presented. Results Ninety-one percent of men and 86% of women completed 3 ASA24 recalls. Approximately three-quarters completed 5 or more, higher than the completion rates for 2 4DFRs and 2 FFQs. Approximately, three-quarters of men and 70% of women completed ASA24 on the first attempt; 1 in 5 completed it on the second. Completion rates varied slightly by age and body mass index. Median time to complete ASA24-2011 (current version: ASA24-2020) declined with subsequent recalls from 55 to 41 minutes in men and from 58 to 42 minutes in women and was lowest in those younger than 60 years. Mean nutrient intakes were similar across recalls. For each recording day, energy intakes estimated by ASA24 were lower than energy expenditure. Reported intakes for protein, potassium, and sodium were closer to recovery biomarkers for women, but not for men. Geometric means of reported intakes of these nutrients did not systematically vary across ASA24 administrations, but differences between reported intakes and biomarkers differed by nutrient. Of 100 possible points, HEI-2015 total scores were nearly identical for 4DFRs and ASA24 recalls and higher for FFQs (men: 61, 60, and 68; women: 64, 64, and 72, respectively). Conclusions ASA24, a freely available dietary assessment tool for use in large-scale nutrition research, was found to be highly feasible. Similar to previously reported data for nutrient intakes, HEI-2015 total and component scores for ASA24 recalls were comparable to those for 4DFRs, but not FFQs. Trial registration ClinicalTrials.gov identifier: NCT03268577 ( http://www.clinicaltrials.gov ).

Made available in DSpace on 2019-10-06T16:37:46Z (GMT). No. of bitstreams: 0 Previous issue date: 2019-01-01 Objective: To investigate the influence of changes in energy balance and body composition on the rate of weight loss throughout 1 year of Roux-en-Y gastric bypass. Methods: Variables were collected pre-, 6, and 12 months (M) post-surgery from 18 women (BMI ≥ 40 and ≤ 50 kg m−2, 20 to 45 years). Total energy expenditure (TEEm), fat-free mass (FFM), and fat mass (FM) were measured by doubly labeled water. Self-reported energy intake (EIsr) was obtained from three non-consecutive food diaries. Metabolic adaptation was assessed via deviations from TEE predictive equation, and the calculated energy intake (EIc) via the sum of TEE and change in body stores. Results: BMI significantly decreased (mean ± SD) from 45 ± 2 kg m−2 to 32 ± 3 kg m−2 at 6 M, and to 30 ± 3 kg m−2 at 12 M after surgery. The TEEm reduced significantly at both time points when compared with pre-surgery (6 M: − 612 ± 317 kcal day−1; 12 M: − 447 ± 516 kcal day−1). At 6 M, a metabolic adaptation was observed and the energy balance was − 1151 ± 195 kcal day−1, while at 12 M it was − 332 ± 158 kcal day−1. Changes in the values of TEEm were associated with changes in body weight at 12 M post-surgery. A significant underreporting was observed for EIsr (1057 ± 385 kcal day−1) vs. EIc (2083 ± 309 kcal day−1) at 12 M post-operative. Conclusion: The higher rate of weight loss at 6 M post-surgery was a response to energy imbalance, which was caused by high restriction in energy intake even with the presence of metabolic adaptation at this time. The EIsr was not sufficiently accurate to assess the energy consumption of this population. Registration of Clinical Trials (Observational Study): Brazilian Clinical Trials Registry: RBR-8k5jsj. Universal Trial Number: U1111-1206-0858. School of Pharmaceutical Sciences Sao Paulo State University – UNESP, Rodovia Araraquara Jaú, Km 01, s/n. Bairro: Campos Ville Department of Neurology University of Wisconsin – Madison, 1685 Highland Avenue, Medical Foundation Centennial Building, 7th Floor Biotechnology Center University of Wisconsin – Madison, 425 Henry Mall Street Ribeirao Preto Medical School University of Sao Paulo – USP, Avenida Bandeirantes, 3900 - Bairro: Monte Alegre Stable Isotope Center Bioscience Institute Sao Paulo State University – UNESP, Rua Prof. Dr. Antônio Celso Wagner Zanin, 250 - Bairro: Distrito de Rubião Junior Education Department Institute of Biosciences Sao Paulo State University – UNESP, Rua Prof. Dr. Antônio Celso Wagner Zanin, 250 - Bairro: Distrito de Rubião Junior School of Pharmaceutical Sciences Sao Paulo State University – UNESP, Rodovia Araraquara Jaú, Km 01, s/n. Bairro: Campos Ville Stable Isotope Center Bioscience Institute Sao Paulo State University – UNESP, Rua Prof. Dr. Antônio Celso Wagner Zanin, 250 - Bairro: Distrito de Rubião Junior Education Department Institute of Biosciences Sao Paulo State University – UNESP, Rua Prof. Dr. Antônio Celso Wagner Zanin, 250 - Bairro: Distrito de Rubião Junior