Oral Motor Impairments Contribute to Weight Status of Adults with Severe Cerebral Palsy.

Adults with severe cerebral palsy (CP) are susceptible to malnutrition and metabolic disorders due to limited daily physical activity and challenges related to eating. We hypothesized that the condition of being underweight arises from inadequate energy intake due to difficulties in eating, rather than heightened total energy expenditure or an elevated resting metabolic rate. The present study encompassed 17 adults with severe CP (classified as GMFSC III-V). Energy intake, utilization, and expenditure were gauged via thorough dietary recordings and double-labeled water (DLW) analyses. Resting metabolic rates were assessed through indirect calorimetry, and metabolic health was investigated via blood samples. Oral motor function, eating assessment during meals, and weight fluctuations throughout the experimental period were also evaluated. We found significant correlations between weight, oral impairments (p < 0.01), and eating difficulties (p < 0.05). While total energy expenditure and daily consumption were similar between underweight (UW) and overweight (OW) individuals, significant variability in both expenditure and intake was evident within the UW group. Particularly, those with lower BMIs experienced heightened mealtime impairments and complications. Our present findings indicate that eating difficulties are the central concern for UW status in this population.

Predicting resting energy expenditure: a critical appraisal.

BACKGROUND: The most commonly used prediction models for resting energy expenditure (REE) are Harris-Benedict (1919), Schofield (1985), Owen (1986), and Mifflin-St Jeor (1990), based on height, weight, age and gender, and Cunningham (1991), based on body composition. METHODS: Here, the five models are compared with reference data, consisting of individual REE measurements (n = 353) from 14 studies, covering a large range of participant characteristics. RESULTS: For white adults, prediction of REE with the Harris-Benedict model approached measured REE most closely, with estimates within 10% for more than 70% of the reference population. DISCUSSION: Sources of differences between measured and predicted REE include measurement validity and measurement conditions. Importantly, a 12- to 14-h overnight fast may not be sufficient to reach post-absorptive conditions and may explain differences between predicted REE and measured REE. In both cases complete fasting REE may not have been achieved, especially in participants with high energy intake. CONCLUSION: In white adults, measured resting energy expenditure was closest to predicted values with the classic Harris-Benedict model. Suggestions for improving resting energy expenditure measurements, as well as prediction models, include the definition of post-absorptive conditions, representing complete fasting conditions with respiratory exchange ratio as indicator.

Solving the conundrum of intra-specific variation in metabolic rate: A multidisciplinary conceptual and methodological toolkit: New technical developments are opening the door to an understanding of why metabolic rate varies among individual animals of a species: New technical developments are opening the door to an understanding of why metabolic rate varies among individual animals of a species.

Researchers from diverse disciplines, including organismal and cellular physiology, sports science, human nutrition, evolution and ecology, have sought to understand the causes and consequences of the surprising variation in metabolic rate found among and within individual animals of the same species. Research in this area has been hampered by differences in approach, terminology and methodology, and the context in which measurements are made. Recent advances provide important opportunities to identify and address the key questions in the field. By bringing together researchers from different areas of biology and biomedicine, we describe and evaluate these developments and the insights they could yield, highlighting the need for more standardisation across disciplines. We conclude with a list of important questions that can now be addressed by developing a common conceptual and methodological toolkit for studies on metabolic variation in animals.

Total daily energy expenditure has declined over the past three decades due to declining basal expenditure, not reduced activity expenditure.

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.

Prediction of activity-related energy expenditure under free-living conditions using accelerometer-derived physical activity.

The purpose of the study was to develop prediction models to estimate physical activity (PA)-related energy expenditure (AEE) based on accelerometry and additional variables in free-living adults. In 50 volunteers (20-69 years) PA was determined over 2 weeks using the hip-worn Actigraph GT3X + as vector magnitude (VM) counts/minute. AEE was calculated based on total daily EE (measured by doubly-labeled water), resting EE (indirect calorimetry), and diet-induced thermogenesis. Anthropometry, body composition, blood pressure, heart rate, fitness, sociodemographic and lifestyle factors, PA habits and food intake were assessed. Prediction models were developed by context-grouping of 75 variables, and within-group stepwise selection (stage I). All significant variables were jointly offered for second stepwise regression (stage II). Explained AEE variance was estimated based on variables remaining significant. Alternative scenarios with different availability of groups from stage I were simulated. When all 11 significant variables (selected in stage I) were jointly offered for stage II stepwise selection, the final model explained 70.7% of AEE variance and included VM-counts (33.8%), fat-free mass (26.7%), time in moderate PA + walking (6.4%) and carbohydrate intake (3.9%). Alternative scenarios explained 53.8-72.4% of AEE. In conclusion, accelerometer counts and fat-free mass explained most of variance in AEE. Prediction was further improved by PA information from questionnaires. These results may be used for AEE prediction in studies using accelerometry.

Timing of daily calorie loading affects appetite and hunger responses without changes in energy metabolism in healthy subjects with obesity.

Morning loaded calorie intake in humans has been advocated as a dietary strategy to improve weight loss. This is also supported by animal studies suggesting time of eating can prevent weight gain. However, the underlying mechanisms through which timing of eating could promote weight loss in humans are unclear. In a randomized crossover trial (NCT03305237), 30 subjects with obesity/overweight underwent two 4-week calorie-restricted but isoenergetic weight loss diets, with morning loaded or evening loaded calories (45%:35%:20% versus 20%:35%:45% calories at breakfast, lunch, and dinner, respectively). We demonstrate no differences in total daily energy expenditure or resting metabolic rate related to the timing of calorie distribution, and no difference in weight loss. Participants consuming the morning loaded diet reported significantly lower hunger. Thus, morning loaded intake (big breakfast) may assist with compliance to weight loss regime through a greater suppression of appetite.

Human total, basal and activity energy expenditures are independent of ambient environmental temperature.

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.

Extreme duration exercise affects old and younger men differently.

AIM & METHODS: Extreme endurance exercise provides a valuable research model for understanding the adaptive metabolic response of older and younger individuals to intense physical activity. Here, we compare a wide range of metabolic and physiologic parameters in two cohorts of seven trained men, age 30 ± 5 years or age 65 ± 6 years, before and after the participants travelled ≈3000 km by bicycle over 15 days. RESULTS: Over the 15-day exercise intervention, participants lost 2-3 kg fat mass with no significant change in body weight. V̇O2 max did not change in younger cyclists, but decreased (p = 0.06) in the older cohort. The resting plasma FFA concentration decreased markedly in both groups, and plasma glucose increased in the younger group. In the older cohort, plasma LDL-cholesterol and plasma triglyceride decreased. In skeletal muscle, fat transporters CD36 and FABPm remained unchanged. The glucose handling proteins GLUT4 and SNAP23 increased in both groups. Mitochondrial ROS production decreased in both groups, and ADP sensitivity increased in skeletal muscle in the older but not in the younger cohort. CONCLUSION: In summary, these data suggest that older but not younger individuals experience a negative adaptive response affecting cardiovascular function in response to extreme endurance exercise, while a positive response to the same exercise intervention is observed in peripheral tissues in younger and older men. The results also suggest that the adaptive thresholds differ in younger and old men, and this difference primarily affects central cardiovascular functions in older men after extreme endurance exercise.

Physical activity and fat-free mass during growth and in later life.

BACKGROUND: Physical activity may be a way to increase and maintain fat-free mass (FFM) in later life, similar to the prevention of fractures by increasing peak bone mass. OBJECTIVES: A study is presented of the association between FFM and physical activity in relation to age. METHODS: In a cross-sectional study, FFM was analyzed in relation to physical activity in a large participant group as compiled in the International Atomic Energy Agency Doubly Labeled Water database. The database included 2000 participants, age 3-96 y, with measurements of total energy expenditure (TEE) and resting energy expenditure (REE) to allow calculation of physical activity level (PAL = TEE/REE), and calculation of FFM from isotope dilution. RESULTS: PAL was a main determinant of body composition at all ages. Models with age, fat mass (FM), and PAL explained 76% and 85% of the variation in FFM in females and males < 18 y old, and 32% and 47% of the variation in FFM in females and males ≥ 18 y old, respectively. In participants < 18 y old, mean FM-adjusted FFM was 1.7 kg (95% CI: 0.1, 3.2 kg) and 3.4 kg (95% CI: 1.0, 5.6 kg) higher in a very active participant with PAL = 2.0 than in a sedentary participant with PAL = 1.5, for females and males, respectively. At age 18 y, height and FM-adjusted FFM was 3.6 kg (95% CI: 2.8, 4.4 kg) and 4.4 kg (95% CI: 3.2, 5.7 kg) higher, and at age 80 y 0.7 kg (95% CI: -0.2, 1.7 kg) and 1.0 kg (95% CI: -0.1, 2.1 kg) higher, in a participant with PAL = 2.0 than in a participant with PAL = 1.5, for females and males, respectively. CONCLUSIONS: If these associations are causal, they suggest physical activity is a major determinant of body composition as reflected in peak FFM, and that a physically active lifestyle can only partly protect against loss of FFM in aging adults.

Seasonal variation in body mass, body composition and activity-induced energy expenditure: a long-term study.

BACKGROUND/OBJECTIVES: Seasonal variation in body mass is a model for the study of body mass regulation. Here a long-term study is presented on body mass, body composition, and activity-induced energy expenditure in a subject with a large seasonal variation in body mass of about 3.0 kg. SUBJECT/METHODS: Body mass was assessed daily over >20 consecutive years. Daily assessment of activity-induced energy expenditure was performed over the last 10 years. Body composition was assessed monthly for 1 year in the middle and at the end of the observation interval. Additionally, data were compared with data on body composition, resting energy expenditure, and total daily energy expenditure of the same subject as a participant in published studies. RESULTS: Body mass showed a pronounced seasonal variation, associated with a synchronous variation in physical activity. Body mass peaked in the cold winter months when physical activity reached the lowest annual value and decreased to the lowest value in mid-summer when daily physical activity peaked. The seasonal variation in body mass consisted mainly of body fat. Longitudinally, over the past 8 years of the observation interval, average fat-free mass showed a decrease of 1.0 kg and fat mass increased 0.8 kg. CONCLUSIONS: In a subject with a pronounced seasonal variation in physical activity, activity-induced variation in energy requirement was covered by an annual variation in body mass, mainly as fat. Maintenance of activity-induced energy expenditure did not protect against loss of fat-free body mass with advancing age.

Substrate utilization and metabolic profile in response to overfeeding with a high-fat diet in South Asian and white men: a sedentary lifestyle study.

BACKGROUND: For the same BMI, South Asians have a higher body fat percentage, a higher liver fat content and a more adverse metabolic profile than whites. South Asians may have a lower fat oxidation than whites, which could result in an unfavorable metabolic profile when exposed to increased high-fat foods consumption and decreased physical activity as in current modern lifestyle. OBJECTIVE: To determine substrate partitioning, liver fat accumulation and metabolic profile in South Asian and white men in response to overfeeding with high-fat diet under sedentary conditions in a respiration chamber. DESIGN: Ten South Asian men (BMI, 18-29 kg/m2) and 10 white men (BMI, 22-33 kg/m2), matched for body fat percentage, aged 20-40 year were included. A weight maintenance diet (30% fat, 55% carbohydrate, and 15% protein) was given for 3 days. Thereafter, a baseline measurement of liver fat content (1H-MRS) and blood parameters was performed. Subsequently, subjects were overfed (150% energy requirement) with a high-fat diet (60% fat, 25% carbohydrate, and 15% protein) over 3 consecutive days while staying in a respiration chamber mimicking a sedentary lifestyle. Energy expenditure and substrate use were measured for 3 × 24-h. Liver fat and blood parameters were measured again after the subjects left the chamber. RESULTS: The 24-h fat oxidation as a percentage of total energy expenditure did not differ between ethnicities (P = 0.30). Overfeeding increased liver fat content (P = 0.02), but the increase did not differ between ethnicities (P = 0.64). In South Asians, overfeeding tended to increase LDL-cholesterol (P = 0.08), tended to decrease glucose clearance (P = 0.06) and tended to elevate insulin response (P = 0.07) slightly more than whites. CONCLUSIONS: Despite a similar substrate partitioning and similar accretion of liver fat, overfeeding with high-fat under sedentary conditions tended to have more adverse effects on the lipid profile and insulin sensitivity in South Asians.

The International Atomic Energy Agency International Doubly Labelled Water Database: Aims, Scope and Procedures.

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.

Molecular adaptation in adipose tissue in response to overfeeding with a high-fat diet under sedentary conditions in South Asian and Caucasian men.

For the same BMI, South Asians have a higher body fat percentage than Caucasians. There might be differences in the fatty acid (FA) handling in adipose tissue when both ethnicities are exposed to high-fat overfeeding. The objective of the present study was to investigate the molecular adaptation in relation to FA metabolism in response to overfeeding with a high-fat diet (OHFD) in South Asian and Caucasian men. Ten South Asian men (BMI 18-29 kg/m2) and ten Caucasian men (BMI 22-33 kg/m2), matched for body fat percentage, aged 20-40 years were included. A weight-maintenance diet (30 % fat, 55 % carbohydrate and 15 % protein) was given for 3 d followed by 3 d of overfeeding (150 % energy requirement) with a high-fat diet (60 % fat, 25 % carbohydrate and 15 % protein) while staying in a respiration chamber. Before and after overfeeding, abdominal subcutaneous fat biopsies were taken. Proteins were isolated, analysed and quantified for short-chain 3-hydroxyacyl-CoA dehydrogenase (HADH), carnitine palmitoyl-transferase 1α (CPT1a), adipose TAG lipase, perilipin A (PLINA), perilipin B, lipoprotein lipase and fatty acid binding protein 4 using Western blotting. OHFD decreased the HADH level (P < 0·05) in Caucasians more than in Asians (P < 0·05), but the baseline and after intervention HADH level was relatively higher in Caucasians. The level of CPT1a decreased in South Asians and increased in Caucasians (P < 0·05). PLINA did not change with diet but the level was higher in South Asians (P < 0·05). The observed differences in HADH and PLINA levels as well as in CPT1a response may be important for differences in the long-term regulation of energy (fat) metabolism in these populations.

Training-induced changes in daily energy expenditure: Methodological evaluation using wrist-worn accelerometer, heart rate monitor, and doubly labeled water technique.

INTRODUCTION: Wrist-mounted motion sensors can quantify the volume and intensity of physical activities, but little is known about their long-term validity. Our aim was to validate a wrist motion sensor in estimating daily energy expenditure, including any change induced by long-term participation in endurance and strength training. Supplemental heart rate monitoring during weekly exercise was also investigated. METHODS: A 13-day doubly labeled water (DLW) measurement of total energy expenditure (TEE) was performed twice in healthy male subjects: during two last weeks of a 12-week Control period (n = 15) and during two last weeks of a 12-week combined strength and aerobic Training period (n = 13). Resting energy expenditure was estimated using two equations: one with body weight and age, and another one with fat-free mass. TEE and activity induced energy expenditure (AEE) were determined from motion sensor alone, and from motions sensor combined with heart rate monitor, the latter being worn during exercise only. RESULTS: When body weight and age were used in the calculation of resting energy expenditure, the motion sensor data alone explained 78% and 62% of the variation in TEE assessed by DLW at the end of Control and Training periods, respectively, with a bias of +1.75 (p <.001) and +1.19 MJ/day (p = .002). When exercise heart rate data was added to the model, the combined wearable device approach explained 85% and 70% of the variation in TEE assessed by DLW with a bias of +1.89 and +1.75 MJ/day (p <.001 for both). While significant increases in TEE and AEE were detected by all methods as a result of participation in regular training, motion sensor approach underestimated the change measured by DLW: +1.13±0.66 by DLW, +0.59±0.69 (p = .004) by motion sensor, and +0.98±0.70 MJ/day by combination of motion sensor and heart rate. Use of fat-free mass in the estimation of resting energy expenditure removed the biases between the wearable device estimations and the golden standard reference method of TEE and demonstrated a training-induced increase in resting energy expenditure by +0.18±0.13 MJ/day (p <.001). CONCLUSIONS: Wrist motion sensor combined with a heart rate monitor during exercise sessions, showed high agreement with the golden standard measurement of daily TEE and its change induced by participation in a long-term training protocol. The positive findings concerning the validity, especially the ability to follow-up the change associated with a lifestyle modification, can be considered significant because they partially determine the feasibility of wearable devices as quantifiers of health-related behavior.