ABSTRACT
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.
Subject(s)
Biomarkers , Energy Intake , Energy Metabolism , Postmenopause , Humans , Female , Biomarkers/blood , Middle Aged , Aged , Prospective Studies , Cohort Studies , Mortality , United States/epidemiology , Follow-Up StudiesABSTRACT
Bedrest shifts fasting and postprandial fuel selection towards carbohydrate use over lipids, potentially affecting astronauts' performance and health. We investigated whether this change occurs in astronauts after at least 3 months onboard the International Space Station (ISS). We further explored the associations with diet, physical activity (PA), and body composition. Before and during spaceflight, respiratory quotient (RQ), carbohydrate, and fat oxidation were measured by indirect calorimetry before and following a standardized meal in 11 males (age = 45.7 [SD 7.7] years, BMI = 24.3 [2.1] kg m-²). Postprandial substrate use was determined by 0-to-260 min postprandial incremental area under the curve (iAUC) of nutrient oxidation and the difference between maximal postprandial and fasting RQ (ΔRQ). Food quotient (FQ) was calculated from diet logs. Fat (FM) and fat-free mass (FFM) were measured by hydrometry and PA by accelerometry and diary logs. Spaceflight increased fasting RQ (P = 0.01) and carbohydrate oxidation (P = 0.04) and decreased fasting lipid oxidation (P < 0.01). An increase in FQ (P < 0.001) indicated dietary modifications onboard the ISS. Spaceflight-induced RQ changes adjusted for ground RQ correlated with inflight FQ (P < 0.01). In postprandial conditions, nutrient oxidation and ΔRQ were unaffected on average. Lipid oxidation changes negatively correlated with FFM changes and inflight aerobic exercise and positively with FM changes. The opposite was observed for carbohydrate oxidation. ΔRQ changes were negatively and positively related to FM and FFM changes, respectively. In conclusion, fasting substrate oxidation shift observed during spaceflight may primarily result from dietary modifications. Between-astronaut variability in postprandial substrate oxidation depends on body composition changes and inflight PA.
ABSTRACT
We aim to understand the effects of hydration changes on athletes' neuromuscular performance, on body water compartments, fat-free mass hydration and hydration biomarkers and to test the effects of the intervention on the response of acute dehydration in the hydration indexes. The H2OAthletes study (clinicaltrials.gov ID: NCT05380089) is a randomised controlled trial in thirty-eight national/international athletes of both sexes with low total water intake (WI) (i.e. < 35·0 ml/kg/d). In the intervention, participants will be randomly assigned to the control (CG, n 19) or experimental group (EG, n 19). During the 4-day intervention, WI will be maintained in the CG and increased in the EG (i.e. > 45·0 ml/kg/d). Exercise-induced dehydration protocols with thermal stress will be performed before and after the intervention. Neuromuscular performance (knee extension/flexion with electromyography and handgrip), hydration indexes (serum, urine and saliva osmolality), body water compartments and water flux (dilution techniques, body composition (four-compartment model) and biochemical parameters (vasopressin and Na) will be evaluated. This trial will provide novel evidence about the effects of hydration changes on neuromuscular function and hydration status in athletes with low WI, providing useful information for athletes and sports-related professionals aiming to improve athletic performance.
Subject(s)
Athletes , Body Water , Dehydration , Adult , Female , Humans , Male , Young Adult , Athletic Performance/physiology , Body Composition , Drinking/physiology , Electromyography , Exercise/physiology , Hand Strength/physiology , Organism Hydration Status , Water-Electrolyte Balance/physiology , Randomized Controlled Trials as TopicABSTRACT
BACKGROUND: Athletes vary in hydration status due to ongoing training regimes, diet demands, and extreme exertion. With water being one of the largest body composition compartments, its variation can cause misinterpretation of body composition assessments meant to monitor strength and training progress. In this study, we asked what accessible body composition approach could best quantify body composition in athletes with a variety of hydration levels. METHODS: The Da Kine Study recruited collegiate and intramural athletes to undergo a variety of body composition assessments including air-displacement plethysmography (ADP), deuterium-oxide dilution (D2O), dual-energy X-ray absorptiometry (DXA), underwater-weighing (UWW), 3D-optical (3DO) imaging, and bioelectrical impedance (BIA). Each of these methods generated 2- or 3-compartment body composition estimates of fat mass (FM) and fat-free mass (FFM) and was compared to equivalent measures of the criterion 6-compartment model (6CM) that accounts for variance in hydration. Body composition by each method was used to predict abdominal and thigh strength, assessed by isokinetic/isometric dynamometry. RESULTS: In total, 70 (35 female) athletes with a mean age of 21.8 ± 4.2 years were recruited. Percent hydration (Body Water6CM/FFM6CM) had substantial variation in both males (63-73 %) and females (58-78 %). ADP and DXA FM and FF M had moderate to substantial agreement with the 6C model (Lin's Concordance Coefficient [CCC] = 0.90-0.95) whereas the other measures had lesser agreement (CCC <0.90) with one exception of 3DO FFM in females (CCC = 0.91). All measures of FFM produced excellent precision with %CV < 1.0 %. However, FM measures in general had worse precision (% CV < 2.0 %). Increasing quartiles (significant p < 0.001 trend) of 6CM FFM resulted in increasing strength measures in males and females. Moreover, the stronger the agreement between the alternative methods to the 6CM, the more robust their correlation with strength, irrespective of hydration status. CONCLUSION: The criterion 6CM showed the best association to strength regardless of the hydration status of the athletes for both males and females. Simpler methods showed high precision for both FM and FFM and those with the strongest agreement to the 6CM had the highest strength associations. SUMMARY BOX: This study compared various body composition analysis methods in 70 athletes with varying states of hydration to the criterion 6-compartment model and assessed their relationship to muscle strength. The results showed that accurate and precise estimates of body composition can be determined in athletes, and a more accurate body composition measurement produces better strength estimates. The best laboratory-based techniques were air displacement plethysmography and dual-energy x-ray absorptiometry, while the commercial methods had moderate-poor agreement. Prioritizing accurate body composition assessment ensures better strength estimates in athletes.
Subject(s)
Body Composition , Body Water , Male , Humans , Female , Adolescent , Young Adult , Adult , Body Composition/physiology , Athletes , Absorptiometry, Photon/methods , Electric Impedance , Muscle Strength , Reproducibility of ResultsABSTRACT
BACKGROUND & AIMS: The multicompartment approach to body composition modeling provides a more precise quantification of body compartments in healthy and clinical populations. We sought to develop and validate a simplified and accessible multicompartment body composition model using 3-dimensional optical (3DO) imaging and bioelectrical impedance analysis (BIA). METHODS: Samples of adults and collegiate-aged student-athletes were recruited for model calibration. For the criterion multicompartment model (Wang-5C), participants received measures of scale weight, body volume (BV) via air displacement, total body water (TBW) via deuterium dilution, and bone mineral content (BMC) via dual energy x-ray absorptiometry. The candidate model (3DO-5C) used stepwise linear regression to derive surrogate measures of BV using 3DO, TBW using BIA, and BMC using demographics. Test-retest precision of the candidate model was assessed via root mean square error (RMSE). The 3DO-5C model was compared to criterion via mean difference, concordance correlation coefficient (CCC), and Bland-Altman analysis. This model was then validated using a separate dataset of 20 adults. RESULTS: 67 (31 female) participants were used to build the 3DO-5C model. Fat-free mass (FFM) estimates from Wang-5C (60.1 ± 13.4 kg) and 3DO-5C (60.3 ± 13.4 kg) showed no significant mean difference (-0.2 ± 2.0 kg; 95 % limits of agreement [LOA] -4.3 to +3.8) and the CCC was 0.99 with a similar effect in fat mass that reflected the difference in FFM measures. In the validation dataset, the 3DO-5C model showed no significant mean difference (0.0 ± 2.5 kg; 95 % LOA -3.6 to +3.7) for FFM with almost perfect equivalence (CCC = 0.99) compared to the criterion Wang-5C. Test-retest precision (RMSE = 0.73 kg FFM) supports the use of this model for more frequent testing in order to monitor body composition change over time. CONCLUSIONS: Body composition estimates provided by the 3DO-5C model are precise and accurate to criterion methods when correcting for field calibrations. The 3DO-5C approach offers a rapid, cost-effective, and accessible method of body composition assessment that can be used broadly to guide nutrition and exercise recommendations in athletic settings and clinical practice.
Subject(s)
Body Composition , Bone Density , Adult , Humans , Female , Aged , Electric Impedance , Absorptiometry, Photon/methods , Optical Imaging , Reproducibility of ResultsABSTRACT
BACKGROUND: Although prior evidence indicates that water intake is important for health, the ability to accurately measure community-dwelling intake is limited. Only a few studies have evaluated self-reported water intake against an objective recovery biomarker. OBJECTIVES: The aim was to compare preformed water intakes (all sources including food) by multiple Automated Self-Administered 24-h recalls (ASA24s), food frequency questionnaires (FFQs), and 4-d food records (4DFRs) against a recovery biomarker, doubly labeled water (DLW), to assess measurement error. METHODS: Over 1 y, 1082 women and men (50%), aged 50 to 74 y, were asked to complete 6 ASA24s, 2 FFQs, 2 unweighted 4DFRs, and an administration of DLW (n = 686). Geometric means of water intake by self-report tools were compared with DLW. Attenuation factors and correlation coefficients between self-reported and the recovery biomarker (DLW) were estimated. RESULTS: Mean water intakes by DLW were 2777 mL/d (interquartile range, 2350 to 3331) in women and 3243 mL/d (interquartile range, 2720 to 3838) in men. Compared with DLW, water intake was underestimated by 18% to 31% on ASA24s and 43% to 44% on 4DFRs. Estimated geometric means from FFQs differed from DLW by -1% to +13%. For a single ASA24, FFQ, and 4DFR, attenuation factors were 0.28, 0.27, and 0.32 and correlation coefficients were 0.46, 0.48, and 0.49, respectively. Repeated use of 6 ASA24s, 2 FFQs, and 2 4DFRs improved attenuation factors to 0.43, 0.32, and 0.39 and correlation coefficients to 0.58, 0.53, and 0.54, respectively. CONCLUSIONS: FFQs may better estimate population means for usual water intake compared with ASA24 and 4DFR. Similar attenuation factors and correlation coefficients across all self-report tools indicate that researchers have 3 feasible options if the goal is understanding intake-disease relationships. The findings are useful for planning future nutrition studies that set policy priorities for populations and to understand the health impact of water. This trial was registered at clinicaltrials.gov as NCT03268577.
Subject(s)
Energy Intake , Water , Female , Humans , Male , Biomarkers , Diet Records , Drinking , Mental Recall , Reproducibility of Results , Surveys and QuestionnairesABSTRACT
Background: The consequences of obesity are ominous, yet healthcare professionals are not adequately preventing or treating obesity in youth with Down syndrome (DS). Total daily energy expenditure (TDEE) is the energy expended in 24â h through physical activity and life-sustaining physiologic processes. An individual's TDEE is essential for determining the daily caloric intake needed to maintain or change body weight. Successful prevention and treatment of obesity in youth with DS is severely compromised by the lack of data on TDEE and information on weight-related behaviors for this high-risk population. This manuscript describes the protocol for the federally funded study that is in process to determine daily energy expenditure in a large cohort of children with DS. Methods: This observational cross-sectional study will include a national sample of 230 youth with DS, stratified by age (5-11 and 12-18 years of age) and sex. Doubly Labeled Water analysis will provide the criterion body fat%, fat-free mass, and TDEE. To increase accessibility and decrease the burden on participants, the entire study, including obtaining consent and data collection, is conducted virtually within the participant's home environment on weekdays and weekends. The study team supervises all data collection via a video conferencing platform, e.g., Zoom. This study will (1) examine and determine average TDEE based on age and sex, (2) develop a prediction equation based on measured TDEE to predict energy requirements with a best-fit model based on fat-free mass, sex, age, and height and/or weight, and (3) use 24-hour dietary recalls, a nutrition and physical activity screener, wearable devices, and sleep questionnaire to describe the patterns and quality of dietary intake, sleep, and physical activity status in youth with DS. Discussion: The lack of accurate information on energy expenditure and weight-related behaviors in youth with DS significantly impedes the successful prevention and treatment of obesity for this vulnerable population. The findings of this study will provide a further understanding of weight-related behaviors as obesity risk factors, currently not well understood for this population. This study will advance the science of weight management in individuals with disabilities and shift clinical practice paradigms.
ABSTRACT
BACKGROUND: The association of TEE with all-cause mortality is uncertain, as is the dependence of this association on age. OBJECTIVES: To examine the association between TEE and all-cause mortality, and its age interaction, in a Women's Health Initiative (WHI) cohort of postmenopausal United States women (1992-present). METHODS: A cohort of 1131 WHI participants having DLW TEE assessment of â¼10.0 y (median) following WHI enrollment with â¼13.7 y (median) of subsequent follow-up, was used to study the EE associations with all-cause mortality. To enhance the comparability of TEE and total EI, key analyses excluded participants having >5% weight change between WHI enrollment and DLW assessment. The influence of participant age on mortality associations was examined, as was the ability of concurrent and earlier weight and height measurements to explain the results. RESULTS: There were 308 deaths following the TEE assessment through 2021. TEE was unrelated to overall mortality (P = 0.83) in this cohort of generally healthy, older (mean 71 y at TEE assessment) United States women. However, this potential association varied with age (P = 0.003). Higher TEE was associated with a higher mortality rate at the age of 60 y and a lower mortality rate at the age of 80 y. Within the weight-stable subset (532 participants, 129 deaths), TEE was weakly positively related to overall mortality (P = 0.08). This association also varied with age (P = 0.03), with mortality HRs (95% CIs) for a 20% increment in TEE of 2.33 (1.24, 4.36) at the age of 60 y, 1.49 (1.10, 2.02) at 70 y of age, and 0.96 (0.66, 1.38) at 80 y of age. This pattern remained, although was somewhat attenuated, following control for baseline weight and weight changes between WHI enrollment and TEE assessment. CONCLUSIONS: Higher EE is associated with higher all-cause mortality among younger postmenopausal women, only partially explained by weight and weight change. This study is registered with clinicaltrials.gov identifier: NCT00000611.
Subject(s)
Energy Intake , Water , Humans , Female , Infant , Postmenopause , Energy Metabolism , Body WeightABSTRACT
OBJECTIVE: Body mass (BM) loss and body composition (BC) changes threaten astronauts' health and mission success. However, the energetic contribution of the exercise countermeasure to these changes has never been investigated during long-term missions. We studied energy balance and BC in astronauts during 6-month missions onboard the International Space Station. METHODS: Before and after at least 3 months in space, BM, BC, total and activity energy expenditure (TEE and AEE) were measured using the doubly labeled water method in 11 astronauts (2011-2017). Physical activity (PA) was assessed by the SensewearPro® activity-device. RESULTS: Three-month spaceflight decreased BM (- 1.20 kg [SE 0.5]; P = 0.04), mainly due to non-significant fat-free mass loss (FFM; - 0.94 kg [0.59]). The decrease in walking time (- 63.2 min/day [11.5]; P < 0.001) from preflight was compensated by increases in non-ambulatory activities (+ 64.8 min/day [18.8]; P < 0.01). Average TEE was unaffected but a large interindividual variability was noted. Astronauts were stratified into those who maintained (stable_TEE; n = 6) and those who decreased (decreased_TEE; n = 5) TEE and AEE compared to preflight data. Although both groups lost similar BM, FFM was maintained and FM reduced in stable_TEE astronauts, while FFM decreased and FM increased in decreased_TEE astronauts (estimated between-group-difference (EGD) in ΔFFMindex [FFMI] 0.87 kg/m2, 95% CI + 0.32 to + 1.41; P = 0.01, ΔFMindex [FMI] - 1.09 kg/m2, 95% CI - 2.06 to - 0.11 kg/m2; P = 0.03). The stable_TEE group had higher baseline FFMI, and greater baseline and inflight vigorous PA than the decreased_TEE group (P < 0.05 for all). ΔFMI and ΔFFMI were respectively negatively and positively associated with both ΔTEE and ΔAEE. CONCLUSION: Both ground fitness and inflight overall PA are associated with spaceflight-induced TEE and BC changes and thus energy requirements. New instruments are needed to measure real-time individual changes in inflight energy balance components.
Subject(s)
Astronauts , Body Composition , Humans , Energy Metabolism , ExerciseABSTRACT
Lower ambient temperature (Ta) requires greater energy expenditure to sustain body temperature. However, effects of Ta on human energetics may be buffered by environmental modification and behavioral compensation. We used the IAEA DLW database for adults in the USA (n = 3213) to determine the effect of Ta (-10 to +30°C) on TEE, basal (BEE) and activity energy expenditure (AEE) and physical activity level (PAL). There were no significant relationships (p > 0.05) between maximum, minimum and average Ta and TEE, BEE, AEE and PAL. After adjustment for fat-free mass, fat mass and age, statistically significant (p < 0.01) relationships between TEE, BEE and Ta emerged in females but the effect sizes were not biologically meaningful. Temperatures inside buildings are regulated at 18-25°C independent of latitude. Hence, adults in the US modify their environments to keep TEE constant across a wide range of external ambient temperatures.
ABSTRACT
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.
Subject(s)
Basal Metabolism , Body Composition , Body Weight , Energy Metabolism , Humans , Male , WaterABSTRACT
IMPORTANCE: Short sleep duration has been recognized as a risk factor for obesity. Whether extending sleep duration may mitigate this risk remains unknown. OBJECTIVE: 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. DESIGN, SETTING, AND PARTICIPANTS: 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. INTERVENTIONS: 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. MAIN OUTCOMES AND MEASURES: 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. RESULTS: 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. CONCLUSIONS AND RELEVANCE: 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. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT02253368.
Subject(s)
Energy Intake , Overweight , Adult , Body Mass Index , Humans , Male , Obesity/therapy , Overweight/therapy , Sleep , Young AdultABSTRACT
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.
Subject(s)
Diet , Nutrition Assessment , Biomarkers , Cohort Studies , Diet Surveys , Energy Intake , Female , Humans , Male , Mental Recall , Reproducibility of Results , Surveys and QuestionnairesABSTRACT
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.
Subject(s)
Deuterium , Mass Spectrometry/methods , Oxygen Isotopes , Water , Adult , Deuterium/analysis , Deuterium/chemistry , Female , Humans , Male , Oxygen Isotopes/analysis , Oxygen Isotopes/chemistry , Saliva/chemistry , Water/analysis , Water/chemistryABSTRACT
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.
Subject(s)
Developmental Disabilities , Down Syndrome , Adipose Tissue , Body Mass Index , Body Weight , Child , Female , Humans , Male , Obesity/complicationsABSTRACT
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.
Subject(s)
Breath Tests , Carbon Isotopes/chemistry , Dietary Sugars/administration & dosage , Adult , Biomarkers , Carbon Isotopes/metabolism , Cross-Over Studies , Dietary Sugars/metabolism , Female , Humans , Male , Middle AgedABSTRACT
BACKGROUND: The measurement of energy intake is central to the understanding of energy balance and predicting changes in body weight. Until recently, the most commonly used methods of assessing intake were self-reported diet recalls, diet diaries, or food-frequency questionnaires. These methods, however, are subject to systematic biases and are often inaccurate. AIM: Review the validations and applications of an expenditure/balance method for measuring energy intake. METHODS: Review the literature regarding the theory and practice of objectively measuring energy intake based on the principle of energy balance i.e., energy intake is calculated from the measured total energy expenditure plus the change in body energy stores (ES). The attainable precision is modeled and compared with the accuracy and precision of validations against known energy intake. RESULTS: Measurement of energy intake, calculated in this way, is accurate to within 2% and has a precision of 4-37% depending on the expenditure and body composition methods used and the time interval between measures. Applications of this expenditure/balance (EB) method have provided novel data on the compliance to dietary restriction and its association with physical activity interventions, and the effects of bariatric surgery on energy intake and weight gain. Practical limitations to this method, however, include cost and limited access to the analyses required by the DLW method. CONCLUSION: The EB method of objectively measuring energy intake is objective, accurate, and reasonably precise. It is practical for moderate-sized studies.
Subject(s)
Diet Records , Energy Intake , Energy Metabolism , Body Weight , Humans , Validation Studies as TopicABSTRACT
We have previously reported negative energy balance and health benefits during an Alaska backcountry expeditionary hunting (ABEH) immersion in two males. The purpose of our present study was to increase the number of participants, include females, and evaluate macronutrient intake and serum lipids. Four men (age: 46 ± 6 year, BMI: 26 ± 1 kg/m2 ) and three women (age: 46 ± 11 year, BMI: 25 ± 3 kg/m2 ) were recruited. Doubly labeled water methodology and dietary recall were utilized to assess energy expenditure and energy intake, respectively. Data were collected during pre- and post-ABEH visits. Body composition was measured using dual-energy x-ray absorptiometry and the cross-sectional area of skeletal muscle in the upper leg (XT), and intrahepatic lipid (IHL) was determined using magnetic resonance imaging and/or spectroscopy (MRI/MRS). Blood parameters were measured by LabCorp. Paired T-tests were used for statistical analysis. Data are reported as mean ± SD and considered significant at p < 0.05. Total energy intake was 7.7 ± 3.4 MJ/day and total energy expenditure was 17.4 ± 2.6 MJ/day, resulting in a negative energy balance of -9.7 ± 3.4 MJ/day. Protein intake(grams)/body weight(kilograms)/day was 1.0 ± 0.4. There were reductions in body weight (Δ-1.5 ± 0.7 kg), BMI (Δ-0.3 ± 0.2 kg/m2 ), fat mass (Δ-1.7 ± 0.9 kg), and IHL (Δ-0.3 ± 0.3% water peak). There were no changes in lean tissue mass (Δ0.6 ± 1.4 kg) or XT (Δ-1.3 ± 3.3 cm2 ). There were significant reductions in total cholesterol (Δ-44 ± 35 mg/dl), LDL-cholesterol (Δ-25 ± 14 mg/dl), VLDL-cholesterol (Δ-7 ± 7 mg/dl), and triglycerides (Δ-35 ± 33 mg/dl). The ABEH immersion resulted in considerable negative energy balance and provided comprehensive benefits in metabolic health without any reduction in skeletal muscle.
Subject(s)
Body Composition , Eating , Predatory Behavior , Sports/physiology , Absorptiometry, Photon/methods , Alaska , Animals , Energy Intake , Energy Metabolism , Female , Humans , Liver/metabolism , Male , Metabolome , Middle Aged , Muscle, Skeletal/physiology , WildernessABSTRACT
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).