Investigation of seasonality of human spontaneous physical activity and energy expenditure in respiratory chamber in Phoenix, Arizona.

OBJECTIVE: The existence of seasonal changes in energy metabolism is uncertain. We investigated the relationship between the seasons and spontaneous physical activity (SPA), energy expenditure (EE), and other components measured in a respiratory chamber. METHODS: Between 1985-2005, 671 healthy adults (aged 28.8 ± 7.1 years; 403 men) in Phoenix, Arizona had a 24-hour stay in the respiratory chamber equipped with radar sensors; SPA (expressed as a percentage over the time interval), the energy cost of SPA, EE, and respiratory exchange ratio (RER) were measured. RESULTS: In models adjusted for known covariates, SPA (%) was lower during summer (7.2 ± 2.9, p = 0.0002), spring (7.5 ± 2.9, p = 0.025), and fall (7.6 ± 3, p = 0.038) compared to winter (8.3 ± 3.5, reference). Conversely, energy cost of SPA (kcal/h/%) was higher during summer (2.18 ± 0.83, p = 0.0008), spring (2.186 ± 0.83, p = 0.017), and fall (2.146 ± 0.75, p = 0.038) compared to winter (2.006 ± 0.76). Protein (292 ± 117 kcal/day, ß = -21.2, p = 0.08) oxidation rates was lower in the summer compared to winter. Carbohydrate and lipid oxidation rates (kcal/day) did not differ across seasons. RER and 24-h EE did not differ by season. CONCLUSION: SPA, representing fidgeting-like behavior in the chamber, demonstrated a winter peak and summer nadir in humans living in a desert climate. These findings indicate that the physiological propensity for movement may be affected by seasonal factors. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov identifiers: NCT00340132, NCT00342732.

Greater anhedonia scores in healthy individuals are associated with less decline in 24-hour energy expenditure with fasting: Evidence for a link between behavioral traits and spendthrift phenotype.

Obesity rates are increasing and affecting mental health. It is important to understand how behavioral traits such as anhedonia are associated with physiologic traits that may predict weight-change in clinical and non-clinical populations. We studied whether 24-hour energy expenditure (24hEE) changes with fasting and overfeeding are associated with anhedonia in a healthy cohort. We performed behavioral assessments (physical anhedonia scale (PAS) and inventory for depressive symptoms (IDS)) followed by measures of 24hEE and urinary catecholamines in a whole-room indirect calorimeter (respiratory chamber) during energy balance, and then randomly during fasting and 2 different overfeeding diets. Participants (n=98) were medically healthy, between 18 and 55 years of age, with normal glucose regulation and weight-stable 6 months before admission. Women were premenopausal and not pregnant. Higher PAS was significantly associated with lesser decrease in 24hEE with fasting and higher urinary catecholamine excretion rates - consistent with spendthrift metabolism. As IDS increased, the association between anhedonia and the change in 24hEE from energy balance to fasting decreased (B-values were lower for change in EE). Here, higher PAS scores may reflect the ability to respond with appropriate homeostatic reactions which balance energy needs. IDS scores blunting this response may explain how anhedonia and depression can lead to weight gain.

Energy expenditure measurements are reproducible in different whole-room indirect calorimeters in humans.

OBJECTIVE: This study aimed to evaluate the agreement of commonly reported energy metabolism measurements obtained from two different whole-room indirect calorimeters (WRICs). METHODS: Nine healthy adult volunteers were evaluated over four separate 24-hour periods in a crossover design, twice in two different WRICs of different sizes, each operated according to the Room Indirect Calorimetry Operating and Reporting Standards published in 2020. The reproducibility of repeated measurements was quantified by the coefficient of variation (CV) and intraclass correlation coefficient (ICC). RESULTS: The CVs between and within each WRIC for average 24-hour carbon dioxide production rate (VCO2 ) and oxygen consumption rate (VO2 ), 24-hour energy expenditure (EE), and respiratory exchange ratio ranged from 1.5% to 3.6%, whereas sleep EE ranged from 3.1% to 5.5%. CVs for macronutrient oxidation rates and spontaneous physical activity were higher, ranging from 9.2% to 38.1%. ICCs of VCO2 , VO2 , 24-hour EE, and energy expenditure at zero activity were >0.95, indicating excellent reproducibility, whereas ICCs for lipid oxidation, awake and fed thermogenesis, and sleep EE ranged from 0.55 to 0.92, indicating moderate to high reproducibility. ICCs for respiratory exchange ratio and carbohydrate and protein oxidation rates were lower (<0.70). Spontaneous physical activity showed high reproducibility within chambers (ICC = 0.88) but differed substantially between chambers (ICC = 0.23). CONCLUSIONS: Cross-chamber reproducibility is high for common outcome measures assessed in the respiratory chamber. The results support efforts to promote standardization across WRICs to allow multicenter studies.

Trends in spontaneous physical activity and energy expenditure among adults in a respiratory chamber, 1985 to 2005.

OBJECTIVE: Fidgeting, a type of spontaneous physical activity (SPA), has substantial thermogenic potential. This research aims to examine secular trends in SPA and energy expenditure (EE) inside a respiratory chamber. METHODS: From 1985 to 2005, healthy adults (n = 678; mean age: 28.8 years; men: 60%; 522 Indigenous American, 129 White, and 27 Black) had a 24-hour stay in the respiratory chamber equipped with radar sensors. Body composition, glucose tolerance, fasting insulin, insulin action (hyperinsulinemic-euglycemic clamp), and insulin secretion (intravenous glucose tolerance test) were measured as covariates. RESULTS: SPA, adjusted for age, sex, race, and body composition, declined (r = -0.30, p < 0.0001), with a concomitant rise in the energy cost of SPA (r = 0.30, p < 0.0001). The 24-hour EE adjusted for covariates increased (r = 0.31, p < 0.0001), which was reflected in increases in EE during sleep (r = 0.18, p < 0.0001) and during the awake, fed condition (r = 0.28, p < 0.0001). The secular trends in SPA or 24-hour EE were unchanged with adjustment for measures related to glucose metabolism. CONCLUSIONS: Secular trend analyses showed a decline in fidgeting. However, this decline in SPA was partially counterbalanced by an increase in energy cost of this activity and a rise in EE. Nevertheless, our results support public health efforts to promote small but sustained changes in these behaviors.

Hydration biomarkers and copeptin: relationship with ad libitum energy intake, energy expenditure, and metabolic fuel selection.

BACKGROUND/OBJECTIVE: Evidence from non-human species indicate that hydration and arginine vasopressin (AVP) influence fuel selection, energy expenditure (EE), and food intake, but these relationships are unclear in humans. We sought to assess whether hydration biomarkers [24-h urine volume (UVol) and urine urea nitrogen concentration (UUN)] and copeptin (a surrogate for AVP) are associated with 24-h EE, respiratory quotient (RQ), and daily energy intake (DEI). SUBJECTS/METHODS: In a secondary analysis of collected data, we selected healthy adults (Group 1, n = 177) who had 24-h whole-room indirect calorimetry measurements in energy balance with 24-h urine collection and fasting copeptin measurements (n = 117), followed by 3 days ad libitum food intake. A separate group (Group 2, n = 284) with hydration markers and calorimetry measurements was also studied. The main outcome measures were 24-h RQ, 24-h EE, DEI, substrate oxidation. RESULTS: In Group 1, lower 24-h UVol and higher 24-h UUN, indicating lower hydration, were correlated with lower 24-h RQ (r = 0.35, p < 0.0001, and r = -0.29, p = 0.0001, respectively; results similar in Group 2) and predicted subsequent reduced DEI (r = 0.20, p = 0.01, and r = -0.27, p = 0.0003, respectively), adjusted for confounders. Copeptin was independently associated with 24-h lipid oxidation (r = -0.23, p = 0.01). In Group 2, lower hydration was associated with reduced 24-h EE (24-h UVol: r = 0.29, p < 0.0001; 24-h UUN: r = -0.25, p < 0.0001). CONCLUSIONS: Hydration biomarkers were associated with metabolic differences characterized by altered food intake, fuel selection, and possibly EE. Independently, copeptin was associated with higher lipid oxidation.

A Novel Approach to Predict 24-Hour Energy Expenditure Based on Hematologic Volumes: Development and Validation of Models Comparable to Mifflin-St Jeor and Body Composition Models.

BACKGROUND: Accurate prediction of 24-hour energy expenditure (24EE) relies on knowing body composition, in particular fat-free mass (FFM), the largest determinant of 24EE. FFM is closely correlated with hematologic volumes: blood volume (BV), red cell mass (RCM), and plasma volume (PV). However, it is unknown whether predicted hematologic volumes, based on easily collected variables, can improve 24EE prediction. OBJECTIVE: The aim was to develop and validate equations to predict 24EE based on predicted BV, RCM, and PV and to compare the accuracy and agreement with models developed from FFM and with the Mifflin-St Jeor equation, which is recommended for clinical use by the Academy of Nutrition and Dietetics. DESIGN: Participants had body composition measured by underwater weighing and 24EE by respiratory chamber. BV, RCM, and PV were calculated from five published equations. PARTICIPANTS/SETTING: Native American and white men and women were studied (n=351). Participants were healthy adults aged 18 to 49 years from the Phoenix, AZ, metropolitan area. MAIN OUTCOME MEASURE: Accuracy to within ±10% of measured 24EE and agreement by Bland-Altman analysis. STATISTICAL ANALYSIS: Regression models to predict 24EE from hematologic and body composition variables were developed in half the dataset and validated in the other half. RESULTS: Hematologic volumes were all strongly correlated with FFM in both men and women (r≥0.94). Whereas the accuracy of FFM alone was 69%, four hematologic volumes were individually more accurate (75% to 78%) in predicting 24EE. Equations based on hematologic volumes plus demographics had mean prediction errors comparable to those based on body composition plus demographics; although the Mifflin-St Jeor had modestly better mean prediction error, body composition, hematologic, and Mifflin-St Jeor models all had similar accuracy (approximately 80%). CONCLUSIONS: Prediction equations based on hematologic volumes were developed, validated, and found to be comparable to Mifflin-St Jeor and body composition models in this population of healthy adults.