Aggregate predictions improve accuracy when calculating metabolic variables used to guide treatment

Advancing body composition assessment in patients with cancer: First comparisons of traditional versus multicompartment models

BACKGROUND AND AIMS

Measurement of body composition using computed tomography (CT) scans may be a viable clinical tool for low muscle mass assessment in oncology. However, longitudinal assessments are often infeasible with CT. Clinically accessible body composition technologies can be used to track changes in fat-free mass (FFM) or muscle, though their accuracy may be impacted by cancer-related physiological changes. The purpose of this study was to examine the agreement among accessible body composition method with criterion methods for measures of whole-body FFM measurements and, when possible, muscle mass for the classification of low muscle in patients with cancer.

METHODS

Patients with colorectal cancer were recruited to complete measures of whole-body DXA, air displacement plethysmography (ADP), and bioelectrical impedance analysis (BIA). These measures were used alone, or in combination to construct the criterion multicompartment (4C) mode for estimating FFM. Patients also underwent abdominal CT scans as part of routine clinical assessment. Agreement of each method with 4C model was analyzed using mean constant error (CE = criterion - alternative), linear regression including root mean square error (RMSE), Bland-Altman limits of agreement (LoA) and mean percentage difference (MPD). Additionally, appendicular lean soft tissue index (ALSTI) measured by DXA and predicted by CT were compared for the absolute agreement, while the ALSTI values and skeletal muscle index by CT were assessed for agreement on the classification of low muscle mass.

RESULTS

Forty-five patients received all measures for the 4C model and 25 had measures within proximity of clinical CT measures. Compared to 4C, DXA outperformed ADP and BIA by showing the strongest overall agreement (CE = 1.96 kg, RMSE = 2.45 kg, MPD = 98.15 ± 2.38%), supporting its use for body composition assessment in patients with cancer. However, CT cutoffs for skeletal muscle index or CT-estimated ALSTI were lower than DXA ALSTI (average 1.0 ± 1.2 kg/m2) with 24.0% to 32.0% of patients having a different low muscle classification by CT when compared to DXA.

CONCLUSIONS

Despite discrepancies between clinical body composition assessment and the criterion multicompartment model, DXA demonstrates the strongest agreement with 4C. Disagreement between DXA and CT for low muscle mass classification prompts further evaluation of the measures and cutoffs used with each technique. Multicompartment models may enhance our understanding of body composition variations at the individual patient level and improve the applicability of clinically accessible technologies for classification and monitoring change over time.

A century of exercise physiology: concepts that ignited the study of human thermoregulation. Part 2: physiological measurements

In this, the second of four historical reviews on human thermoregulation during exercise, we examine the research techniques developed by our forebears. We emphasise calorimetry and thermometry, and measurements of vasomotor and sudomotor function. Since its first human use (1899), direct calorimetry has provided the foundation for modern respirometric methods for quantifying metabolic rate, and remains the most precise index of whole-body heat exchange and storage. Its alternative, biophysical modelling, relies upon many, often dubious assumptions. Thermometry, used for >300 y to assess deep-body temperatures, provides only an instantaneous snapshot of the thermal status of tissues in contact with any thermometer. Seemingly unbeknownst to some, thermal time delays at some surrogate sites preclude valid measurements during non-steady state conditions. To assess cutaneous blood flow, immersion plethysmography was introduced (1875), followed by strain-gauge plethysmography (1949) and then laser-Doppler velocimetry (1964). Those techniques allow only local flow measurements, which may not reflect whole-body blood flows. Sudomotor function has been estimated from body-mass losses since the 1600s, but using mass losses to assess evaporation rates requires precise measures of non-evaporated sweat, which are rarely obtained. Hygrometric methods provide data for local sweat rates, but not local evaporation rates, and most local sweat rates cannot be extrapolated to reflect whole-body sweating. The objective of these methodological overviews and critiques is to provide a deeper understanding of how modern measurement techniques were developed, their underlying assumptions, and the strengths and weaknesses of the measurements used for humans exercising and working in thermally challenging conditions.

Anthropometry, body composition and chronic disease risk factors among Zambian school-aged children who experienced severe malnutrition in early childhood

There is limited information as to whether people who experience severe acute malnutrition (SAM) as young children are at increased risk of overweight, high body fat and associated chronic diseases in later life. We followed up, when aged 7-12 years, 100 Zambian children who were hospitalised for SAM before age 2 years and eighty-five neighbourhood controls who had never experienced SAM. We conducted detailed anthropometry, body composition assessment by bioelectrical impedance and deuterium dilution (D2O) and measured blood lipids, Hb and HbA1c. Groups were compared by linear regression following multiple imputation for missing variables. Children with prior SAM were slightly smaller than controls, but differences, controlling for age, sex, socio-economic status and HIV exposure or infection, were significant only for hip circumference, suprailiac skinfold and fat-free mass index by D2O. Blood lipids and HbA1c did not differ between groups, but Hb was lower by 7·8 (95 % CI 0·8, 14·7) g/l and systolic blood pressure was 3·4 (95 % CI 0·4, 6·4) mmHg higher among the prior SAM group. Both anaemia and high HbA1c were common among both groups, indicating a population at risk for the double burden of over- and undernutrition and associated infectious and chronic diseases. The prior SAM children may have been at slightly greater risk than the controls; this was of little clinical significance at this young age, but the children should be followed when older and chronic diseases manifest.

Anthropometry, body composition, early growth and chronic disease risk factors among Zambian adolescents exposed or not to perinatal maternal HIV

Early life exposures and growth patterns may affect long-term risk of chronic non-communicable diseases (NCD). We followed up in adolescence two Zambian cohorts (n 322) recruited in infancy to investigate how two early exposures - maternal HIV exposure without HIV infection (HEU) and early growth profile - were associated with later anthropometry, body composition, blood lipids, Hb and HbA1c, blood pressure and grip strength. Although in analyses controlled for age and sex, HEU children were thinner, but not shorter, than HIV-unexposed, uninfected (HUU) children, with further control for socio-demographic factors, these differences were not significant. HEU children had higher HDL-cholesterol than HUU children and marginally lower HbA1c but no other biochemical or clinical differences. We identified three early growth profiles - adequate growth, declining and malnourished - which tracked into adolescence when differences in anthropometry and body fat were still seen. In adolescence, the early malnourished group, compared with the adequate group, had lower blood TAG and higher HDL, lower grip strength (difference: -1·87 kg, 95 % CI -3·47, -0·27; P = 0·02) and higher HbA1c (difference: 0·5 %, 95 % CI 0·2, 0·9; P = 0·005). Lower grip strength and higher HbA1c suggest the early malnourished children could be at increased risk of NCD in later life. Including early growth profile in analyses of HIV exposure reduced the associations between HIV and outcomes. The results suggest that perinatal HIV exposure may have no long-term effects unless accompanied by poor early growth. Reducing the risk of young child malnutrition may lessen children's risk of later NCD.

Longitudinal associations between sport participation and fat mass with body posture in children: A 5-year follow-up from the Czech ELSPAC study

The main purpose of the study was to examine longitudinal associations between sport participation and fat mass with body posture in children. We used data from children recruited in the Czech European Longitudinal Study of Pregnancy and Childhood (CELSPAC) at the ages of 11 y (n = 1065), 13 y (n = 811) and 15 y (n = 974). Information on body posture, practicing sport in a club and at a competitive level, and skinfold thicknesses (biceps, triceps, subscapula, suprailiaca and thigh) from pediatrician’s medical records were collected. Body posture was inspected by a pediatrician. The sum of 5 skinfolds was used as a proxy of fat mass. The 85th and 95th percentiles defined ‘overfat’ and ‘obese’children. Practicing sport in a club and at a competitive level were included as ‘yes/no’ answers. General linear mixed models with risk ratios (RR) and 95% confidence intervals (95% CI) were calculated. Overall, 35.6% of children and adolescents had impaired body posture; the prevalence of ’incorrect’ body posture increased by age (from 41.0% to 28.0%, p<0.001). Practicing sport in a club and at a competitive level decreased by follow-up (p<0.001), while the level of ‘overfat’ and ‘obese’ children increased (p<0.01). In separate models, ’incorrect’ body posture was associated with non-practicing sport in clubs (RR = 1.68; 95% CI 1.43–1.97, p<0.001) or at competitive level (RR = 1.61; 95% CI 1.37–1.88, p<0.001) and with being ’overfat’ (RR = 2.05; 95% CI 1.52–2.75, p<0.001) and ’obese’ (RR = 2.15; 95% CI 1.68–2.75, p<0.001). When all variables were put simultaneously into the model additionally adjusted for sex, self-rated health and baseline body posture, similar associations remained. This study shows, that not participating in sport and being overfat/obese are longitudinally associated with ‘incorrect’ body posture. Therefore, the detection of these risk factors in childhood, through the development of school- and community-based interventions, should be advocated.

Resting Energy Expenditure in the Elderly: Systematic Review and Comparison of Equations in an Experimental Population

Elderly patients are at risk of malnutrition and need an appropriate assessment of energy requirements. Predictive equations are widely used to estimate resting energy expenditure (REE). In the study, we conducted a systematic review of REE predictive equations in the elderly population and compared them in an experimental population. Studies involving subjects older than 65 years of age that evaluated the performance of a predictive equation vs. a gold standard were included. The retrieved equations were then tested on a sample of 88 elderly subjects enrolled in an Italian nursing home to evaluate the agreement among the estimated REEs. The agreement was assessed using the intraclass correlation coefficient (ICC). A web application, equationer, was developed to calculate all the estimated REEs according to the available variables. The review identified 68 studies (210 different equations). The agreement among the equations in our sample was higher for equations with fewer parameters, especially those that included body weight, ICC = 0.75 (95% CI = 0.69-0.81). There is great heterogeneity among REE estimates. Such differences should be considered and evaluated when estimates are applied to particularly fragile populations since the results have the potential to impact the patient's overall clinical outcome.

Body composition during outpatient treatment of severe acute malnutrition: Results from a randomised trial testing different doses of ready-to-use therapeutic foods

BACKGROUND & AIMS

Treatment of children with uncomplicated severe acute malnutrition (SAM) is based on ready-to-use therapeutic foods (RUTF) prescribed based on body weight and administered at home. Treatment performance is typically monitored through weight gain. We previously reported that a reduced dose of RUTF resulted in weight gain velocity similar to standard dose. Here we investigate the change in body composition of children treated for SAM and compare it to community controls, and describe the effect of a reduced RUTF dose on body composition at recovery.

METHODS

Body composition was measured via bio-electrical impedance analysis at admission and recovery among a sub-group of children with SAM participating in a clinical trial and receiving a reduced or a standard dose of RUTF. Non-malnourished children were measured to represent community controls. Linear mixed regression models were fitted.

RESULTS

We obtained body composition data from 452 children at admission, 259 at recovery and 97 community controls. During SAM treatment the average weight increased by 1.20 kg of which 0.55 kg (45%) was fat-free mass (FFM) and 0.67 kg (55%) was fat mass (FM). At recovery, children treated for SAM had 1.27 kg lower weight, 0.38 kg lower FFM, and 0.90 kg lower FM compared to community controls. However, their fat-free mass index (FFMI) was not different from community controls (Δ0.2 kg/m2; 95% CI -0.1, 0.4). No differences were observed in FFM, FM or fat mass index (FMI) between the study arms at recovery. However, FFMI was 0.35 kg/m2 higher at recovery with the reduced compared to standard dose (p = 0.007) due to slightly lower height (Δ0.22 cm; p = 0.25) and higher FFM (Δ0.11 kg; p = 0.078) in the reduced dose group.

CONCLUSIONS

Almost half of the weight gain during SAM treatment was FFM. Compared to community controls, children recovered from SAM had a lower FM while their height-adjusted FFM was similar. There was no evidence of a differential effect of a reduced RUTF dose on the tissue accretion of treated children when compared to standard treatment.

Filling the weight gap: Estimating body weight and BMI using height, chest and upper arm circumference of Swiss conscripts in the first half of the 20th century

We estimate weight and BMI values based on height, chest circumference, and mid upper arm circumference measures of Swiss conscripts in the city of Zurich for each year between 1904 and 1932. Height, chest circumference, and mid upper arm circumference were measured each year from 1904 to 1951. Body weight is available from 1933 to 1951. We used prediction equations from the literature, and also developed our own equations, which we tested and validated on the dataset from 1933 to 1951. We used a representative sample of usually 19-year-old Swiss males (N = 88,792, coverage > 88 %). There was an increase in average height and chest circumference between 1904 and 1951. During both world wars, chest circumference, mid upper arm circumference, weight, and BMI decreased, while height stagnated. Overall mean weight and BMI increased from 1904 to 1951, but decreased during the Great Depression. After World War II, weight quickly returned to the pre-war and pre-Great Depression level, while BMI had not reached the 1933 level by 1951. Average weights of the lower and middle socioeconomic groups were catching up with average weight of the upper socioeconomic group from 1904 to 1951. The convergence in height is less pronounced. Finally, we show that it is possible to accurately predict mean weight and BMI from other anthropometric measurements. We suggest that our estimation approach could be replicated for other historical populations to obtain more information on how nutritional status changed over time.

Validity of predictive equations to estimate RMR in females with varying BMI

Estimation of RMR using prediction equations is the basis for calculating energy requirements. In the present study, RMR was predicted by Harris-Benedict, Schofield, Henry, Mifflin-St Jeor and Owen equations and measured by indirect calorimetry in 125 healthy adult women of varying BMI (17-44 kg/m2). Agreement between methods was assessed by Bland-Altman analyses and each equation was assessed for accuracy by calculating the percentage of individuals predicted within ± 10 % of measured RMR. Slopes and intercepts of bias as a function of average RMR (mean of predicted and measured RMR) were calculated by regression analyses. Predictors of equation bias were investigated using univariate and multivariate linear regression. At group level, bias (the difference between predicted and measured RMR) was not different from zero only for Mifflin-St Jeor (0 (sd 153) kcal/d (0 (sd 640) kJ/d)) and Henry (8 (sd 163) kcal/d (33 (sd 682) kJ/d)) equations. Mifflin-St Jeor and Henry equations were most accurate at the individual level and predicted RMR within 10 % of measured RMR in 71 and 66 % of participants, respectively. For all equations, limits of agreement were wide, slopes of bias were negative, and intercepts of bias were positive and significantly (P < 0⋅05) different from zero. Increasing age, height and BMI were associated with underestimation of RMR, but collectively these variables explained only 15 % of the variance in estimation bias. Overall accuracy of equations for prediction of RMR is low at the individual level, particularly in women with low and high RMR. The Mifflin-St Jeor equation was the most accurate for this dataset, but prediction errors were still observed in about one-third of participants.

Resting energy expenditure in Parkinson's disease patients under dopaminergic treatment

Background: Weight homeostasis is complex in Parkinson's disease (PD) and body weight changes substantially throughout the course of the disease. We designed a case-control study to (i) investigate whether PD is associated with changes in resting energy expenditure (REE), (ii) to assess how accurately REE could be predicted for individuals with PD utilizing the equations constructed for healthy individuals, and (iii) to eventually construct a new equation.Materials & Methods: Measured REE (mREE) was compared between 122 PD patients and 122 gender and body mass index (BMI)-matched controls. The accuracy of estimated REE by 5 common equations (Harris/Benedict-1919, Roza/Shizgal-1984, Mifflin St. Jeor, WHO/FAO and aggregate formula) was investigated in PD using Bland-Altman analysis and reported as the frequency of accurate predictions (±10%). Concordance correlation coefficients (CCC) were also calculated. Then, we regressed a new REE equation - using gender, age, weight, height and Hoehn-Yahr stage - and validated it in an independent sample (N = 100).Results: No significant difference in mREE was recorded between the whole PD sample and healthy controls. However, mREE was increased in patients with BMI ≥ 30 kg/m² and Hoehn-Yahr stage ≥ 3. Limited accuracy was present in the available REE equations (accurate prediction [±10%] frequency, <60% for all). For the new equation, the proportion of accurate prediction was 67.0% (overestimation, 24.0%) and CCC was 0.77.Conclusion: PD patients are not commonly characterized by an increase in REE. This is limited to patients suffering from obesity and more severe disease. Common REE equations appear to be inaccurate. The new predictive equation proposed in this study provided better REE estimates.

Accuracy of Resting Energy Expenditure Predictive Equations in Patients With Cancer

BACKGROUND

Our purpose was to assess the accuracy of resting energy expenditure (REE) equations in patients with newly diagnosed stage I-IV non-small cell lung, rectal, colon, renal, or pancreatic cancer.

METHODS

In this cross-sectional study, REE was measured using indirect calorimetry and compared with 23 equations. Agreement between measured and predicted REE was assessed via paired t-tests, Bland-Altman analysis, and percent of estimations ≤ 10% of measured values. Accuracy was measured among subgroups of body mass index (BMI), stage (I-III vs IV), and cancer type (lung, rectal, and colon) categories. Fat mass (FM) and fat-free mass (FFM) were assessed using dual x-ray absorptiometry.

RESULTS

Among 125 patients, most had lung, colon, or rectal cancer (92%, BMI: 27.5 ± 5.6 kg/m² , age: 61 ± 11 years, REE: 1629 ± 321 kcal/d). Thirteen (56.5%) equations yielded REE values different than measured (P < 0.05). Limits of agreement were wide for all equations, with Mifflin-St. Jeor equation having the smallest limits of agreement, -21.7% to 11.3% (-394 to 203 kcal/d). Equations with FFM were not more accurate except for one equation (Huang with body composition; bias, limits of agreement: -0.3 ± 11.3% vs without body composition: 2.3 ± 10.1%, P < 0.001). Bias in body composition equations was consistently positively correlated with age and frequently negatively correlated with FM. Bias and limits of agreement were similar among subgroups of patients.

CONCLUSION

REE cannot be accurately predicted on an individual level, and bias relates to age and FM.

Objective Measures of Physical Activity and Cardiometabolic and Endocrine Biomarkers

PURPOSE

Although physical activity is an established risk factor for chronic disease prevention, the specific mechanisms underlying these relationships are poorly understood. We examined the associations between total activity counts and moderate-vigorous physical activity (MVPA) measured by accelerometer, and physical activity energy expenditure measured by doubly labeled water, with plasma levels of proinsulin, insulin, c-peptide, insulin growth factor binding protein-3, insulin growth factor-1, adiponectin, leptin, and leptin-sR.

METHODS

We conducted a cross-sectional analysis of 526 healthy US women in the Women's Lifestyle Validation Study, 2010 to 2012. We performed multiple linear regression models adjusting for potential lifestyle and health-related confounders to assess the associations between physical activity, measured in quartiles (Q) and biomarkers.

RESULTS

Participants in Q4 versus Q1 of total activity counts had lower proinsulin (-20%), c-peptide (-7%), insulin (-31%), and leptin (-46%) levels, and higher adiponectin (55%), leptin-sR (25%), and insulin growth factor-1 (9.6%) levels (all P trend ≤ 0.05). Participants in Q4 versus Q1 of MVPA had lower proinsulin (-26%), c-peptide (-7%), insulin (-32%), and leptin (-40%) levels, and higher adiponectin (31%) and leptin-sR (22%) levels (all P trend ≤ 0.05). Further adjustment for body mass index (BMI) attenuated these associations, but the associations with adipokines remained significant. Those in Q4 versus Q1 of physical activity energy expenditure had lower leptin (-21%) and higher leptin-sR (10%) levels (all P trend ≤ 0.05), after additional adjustment for BMI. In the sensitivity analysis, the associations were similar but attenuated when physical activity was measured using the subjective physical activity questionnaire.

CONCLUSIONS

Our data suggest that greater physical activity is modestly associated with favorable levels of cardiometabolic and endocrine biomarkers, where the strongest associations were found with accelerometer-measured physical activity. These associations may be only partially mediated through BMI, further supporting the role of physical activity in the reduction of cardiometabolic and endocrine disease risk, independent of adiposity.

Sleep Duration and Adiposity in Early Childhood: Evidence for Bidirectional Associations from the Born in Bradford Study

Study Objectives:

To examine independent associations of sleep duration with total and abdominal adiposity, and the bidirectionality of these associations, in a young biethnic sample of children from a disadvantaged location.

Methods:

Child sleep duration (h/day) was parent-reported by questionnaire and indices of total (body weight, body mass index, percent body fat (%BF), sum of skinfolds) and abdominal adiposity (waist circumference) were measured using standard anthropometric procedures at approximately 12, 18, 24, and 36 months of age in 1,338 children (58% South Asian; 42% White). Mixed effects models were used to quantify independent associations (expressed as standardised β-coefficients (95% confidence interval (CI)) of sleep duration with adiposity indices using data from all four time-points. Factors considered for adjustment in models included basic demographics, pregnancy and birth characteristics, and lifestyle behaviours.

Results:

With the exception of the sum of skinfolds, sleep duration was inversely and independently associated with indices of total and abdominal adiposity in South Asian children. For example, one standard deviation (SD) higher sleep duration was associated with reduced %BF by -0.029 (95% CI: −0.053, −0.0043) SDs. Higher adiposity was also independently associated with shorter sleep duration in South Asian children (for example, %BF: β = -0.10 (-0.16, -0.028) SDs). There were no significant associations in White children.

Conclusions:

Associations between sleep duration and adiposity are bidirectional and independent among South Asian children from a disadvantaged location. The results highlight the importance of considering adiposity as both a determinant of decreased sleep and a potential consequence.

Validation of energy intake from a web-based food recall for children and adolescents

The purpose of this study was to validate estimated energy intake from a web-based food recall, designed for children and adolescents. We directly compared energy intake to estimates of total energy expenditure, calculated from accelerometer outputs, combined with data on weight and sex or resting energy expenditure prediction equations. Children (8–9 years) and adolescents (12–14 years) were recruited through schools in Norway in 2013 (N = 253). Results showed that more than one third (36–37%) were identified as under-reporters of energy. In contrast, only 2–4% were defined as over-reporters of energy. The mean energy intake was under-reported with -1.83 MJ/day for the entire study sample. Increased underestimation was observed for overweight and obese participants, the oldest age group (12–14 years), boys, those with parents/legal guardians with low educational level and those living in non-traditional families. In conclusion, energy intake from the web-based food recall is significantly underestimated compared with total energy expenditure, and should be used with caution in young people.

Objectively measured physical activity and longitudinal changes in adolescent body fatness: an observational cohort study

BACKGROUND

The data regarding prospective associations between physical activity (PA) and adiposity in youth are inconsistent.

OBJECTIVE

The objective of this study was to investigate associations between baseline levels of objectively measured PA and changes in adiposity over 2.5 years from mid-to-late adolescence.

METHODS

This was an observational cohort study in 728 school students (43% boys) from Cambridgeshire, United Kingdom. Fat mass index (FMI, kg m(-2) ) was estimated at baseline (mean ± standard deviation age: 15 ± 0.3 years) and follow-up (17.5 ± 0.3 years) by anthropometry and bioelectrical impedance. Habitual PA was assessed at baseline by ≥3 d combined heart rate and movement sensing. Average daily PA energy expenditure (PAEE) and the time (min d(-1) ) spent in light, moderate and vigorous intensity PA (LPA, MPA and VPA, respectively) was estimated. Multilevel models were used to investigate associations between baseline PA and change in FMI (ΔFMI). Adjustment for baseline age, sex, follow-up duration, area-level socioeconomic status, season of PA assessment, sedentary time, energy intake and sleep duration was made; baseline FMI was also added in a second model.

RESULTS

FMI increased significantly over follow-up (0.6 ± 1.2 kg m(-2) , P < 0.001). Baseline PAEE and LPA positively predicted ΔFMI in overfat participants (P ≤ 0.030), as did VPA in initially normal fat participants (P ≤ 0.044). There were further positive associations between PAEE and ΔFMI in normal fat participants, and between MPA and ΔFMI in both fat groups, when adjusted for baseline FMI (P ≤ 0.024).

CONCLUSIONS

Baseline PAEE and its subcomponents were positively associated with small and unlikely clinically relevant increases in ΔFMI. These counter-intuitive findings may be explained by behavioural changes during the course of study follow-up.

The independent prospective associations of activity intensity and dietary energy density with adiposity in young adolescents

There is limited evidence on the prospective association of time spent in activity intensity (sedentary (SED), moderate (MPA) or vigorous (VPA) physical activity) and dietary intake with adiposity indicators in young people. This study aimed to assess associations between (1) baseline objectively measured activity intensity, dietary energy density (DED) and 4-year change in adiposity and (2) 4-year change in activity intensity/DED and adiposity at follow-up. We conducted cohort analyses including 367 participants (10 years at baseline, 14 years at follow-up) with valid data for objectively measured activity (Actigraph), DED (4-d food diary), anthropometry (waist circumference (WC), %body fat (%BF), fat mass index (FMI), weight status) and covariates. Linear and logistic regression models were fit, including adjustment for DED and moderate-to-vigorous physical activity. Results showed that baseline DED was associated with change in WC (β for 1kJ/g difference: 0·71; 95% CI 0·26, 1·17), particularly in boys (1·26; 95% CI 0·41, 2·16 v. girls: 0·26; 95% CI −0·34, 0·87), but not with %BF, FMI or weight status. In contrast, baseline SED, MPA or VPA were not associated with any of the outcomes. Change in DED was negatively associated with FMI (β for 1kJ/g increase: −0·86; 95% CI −1·59, −0·12) and %BF (−0·86; 95% CI −1·25, −0·11) but not WC (−0·27; 95% CI −1·02, 0·48). Change in SED, MPA and VPA did not predict adiposity at follow-up. In conclusion, activity intensity was not prospectively associated with adiposity, whereas the directions of associations with DED were inconsistent. To inform public health efforts, future studies should continue to analyse longitudinal data to further understand the independent role of different energy-balance behaviours in changes in adiposity in early adolescence.

Magnitude and determinants of change in objectively-measured physical activity, sedentary time and sleep duration from ages 15 to 17.5y in UK adolescents: the ROOTS study

Background

Self-reported physical activity (PA) and sleep duration (SLP) change markedly throughout adolescence. We sought to quantify changes in objectively-measured PA, sedentary time (ST) and SLP through adolescence, and to investigate baseline body composition and baseline activity levels as determinants of change.

Methods

Individually calibrated combined heart rate and movement sensing was used to estimate PA energy expenditure (PAEE), SLP, daily ST and time in light (LPA), moderate (MPA), vigorous (VPA), and moderate-to-vigorous physical activity (MVPA) in 144 adolescents (50 % boys) of mean age 15.1(±0.3)y at baseline and 17.5(±0.3)y at follow-up. Changes in PA (ΔPA), ST (ΔST) and SLP (ΔSLP) were calculated as follow-up minus baseline values. Waist circumference (WC) was measured at baseline and follow-up, as was fat mass index (FMI) and fat-free mass index (FFMI) by a pooled estimation method including bio-impedance. Comparison of baseline and follow-up activity was made by mixed-model ANOVA. Linear regression adjusted for baseline demographics, total and weekend hours of monitor wear time and the seasons of activity measurements, was used to investigate baseline body composition as determinants of ΔPA, ΔST and ΔSLP. A further model adjusted for baseline of the outcome assessed baseline activity as a predictor of behaviour change, and investigated associations for baseline body composition independent of the baseline level of the outcome.

Results

From baseline to follow-up levels of MPA and VPA declined (p ≤ 0.039). The annual decline in MVPA was equivalent to -4.5 and -3.0 min/d in boys and girls, respectively. Baseline FMI, FFMI and WC were positively associated with ΔLPA and negatively associated with ΔST in boys when adjusted for baseline of the outcome (p ≤ 0.037 for all). SLP increased from baseline to follow-up (p = 0.004) but ΔSLP was not associated with baseline body composition (p ≥ 0.13). For all variables, higher baseline levels were associated with greater declines over time (p ≤ 0.003).

Conclusions

Levels of higher-intensity PA decline from mid-to-late adolescence, whereas the duration of sleep increases. Changes in LPA and ST may be associated with baseline body composition, but the baseline level of the outcome is consistently the strongest predictor of changes in adolescent activity.

Prospective associations between sedentary time, sleep duration and adiposity in adolescents

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We examined sedentary time and sleep length relative to changes in youth adiposity.

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Sedentary time was not associated with change in adiposity in either gender.

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Sleep duration was significantly inversely associated with adiposity gain in boys.

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The association for sleep in boys was attenuated by physical activity and depression.

Objective

The objective of this study was to investigate whether objectively measured sedentary time and sleep duration are associated with changes in adiposity from mid- to late adolescence.

Methods

Students (n = 504, 42% boys) were recruited from schools in Cambridgeshire, UK. At baseline (mean age 15.0 ± 0.3 years), sedentary time was objectively measured by ≥3 days of combined heart rate and movement sensing. Concurrently, sleep duration was measured by combined sensing in conjunction with self-reported bed times. Fat mass index (FMI; kg/m²) was estimated at baseline and follow-up (17.5 ± 0.3 years) by anthropometry and bioelectrical impedance. FMI change (ΔFMI) was calculated by subtracting the baseline from follow-up values. Linear regression models adjusted for basic demographics, moderate-to-vigorous physical activity (MVPA), and depressive symptoms were used to investigate associations of sedentary time and sleep duration (mutually adjusted for one another) with ΔFMI.

Results

FMI increased by 0.5 and 0.6 kg/m² in boys and girls, respectively, but there was no association between sedentary time and ΔFMI in either gender (p ≥ 0.087), and no association between sleep duration and ΔFMI in girls (p ≥ 0.61). In boys, each additional hour of baseline sleep significantly reduced the ΔFMI by 0.13 kg/m² (p = 0.049), but there was little evidence for this association after adjusting for MVPA and depressive symptoms (p = 0.15).

Conclusions

Sedentary time may not determine changes in adiposity from mid- to late adolescence, nor may sleep duration in girls. However, sleep length may be inversely associated with adiposity gain in boys, depending on whether the relationship is confounded or mediated by MVPA and depression.

Accuracy of prediction equations for serum osmolarity in frail older people with and without diabetes

BACKGROUND

Serum osmolality is an accurate indicator of hydration status in older adults. Glucose, urea, and electrolyte concentrations are used to calculate serum osmolarity, which is an indirect estimate of serum osmolality, but which serum osmolarity equations best predict serum osmolality in the elderly is unclear.

OBJECTIVE

We assessed the agreement of measured serum osmolality with calculated serum osmolarity equations in older people.

DESIGN

Serum osmolality was measured by using freezing point depression in a cross-sectional study. Plasma glucose, urea, and electrolytes were analyzed and entered into 38 serum osmolarity-prediction equations. The Bland-Altman method was used to evaluate the agreement and differential bias between measured osmolality and calculated osmolarity. The sensitivity and specificity of the most-promising equations were examined against serum osmolality (reference standard).

RESULTS

A total of 186 people living in UK residential care took part in the Dehydration Recognition In our Elders study (66% women; mean ± SD age: 85.8 ± 7.9 y; with a range of cognitive and physical impairments) and were included in analyses. Forty-six percent of participants had impending or current dehydration (serum osmolality ≥295 mmol/kg). Participants with diabetes (n = 33; 18%) had higher glucose (P < 0.001) and serum osmolality (P < 0.01). Of 38 predictive equations used to calculate osmolarity, 4 equations showed reasonable agreement with measured osmolality. One [calculated osmolarity = 1.86 × (Na⁺ + K⁺) + 1.15 × glucose + urea +14; all in mmol/L] was characterized by narrower limits of agreement and the capacity to predict serum osmolality within 2% in >80% of participants, regardless of diabetes or hydration status. The equation's sensitivity (79%) and specificity (89%) for impending dehydration (≥295 mmol/kg) and current dehydration (>300 mmol/kg) (69% and 93%, respectively) were reasonable.

CONCLUSIONS

The assessment of a panel of equations for the prediction of serum osmolarity led to identification of one formula with a greater diagnostic performance. This equation may be used to predict hydration status in frail older people (as a first-stage screening) or to estimate hydration status in population studies. This trial was registered at the Research Register for Social Care (http://www.researchregister.org.uk) as 122273.

Validity of predictive equations for resting energy expenditure according to the body mass index in a population of 1726 patients followed in a Nutrition Unit

BACKGROUND & AIMS

The resting energy expenditure (REE) predictive formulas are often used in clinical practice to adapt the nutritional intake of patients or to compare to REE measured by indirect calorimetry. We aimed to evaluate which predictive equations was the best alternative to REE measurements according to the BMI.

METHODS

28 REE prediction equations were studied in a population of 1726 patients without acute or chronic high-grade inflammatory diseases followed in a Nutrition Unit for malnutrition, eating disorders or obesity. REE was measured by indirect calorimetry for 30 min after a fasting period of 12 h. Some formulas requiring fat mass and free-fat mass, body composition was measured by bioelectrical impedance analysis. The percentage of accurate prediction (±10%/REE measured) and Pearson r correlations were calculated.

RESULTS

Original Harris & Benedict equation provided 73.0% of accurate predictions in normal BMI group but only 39.3% and 62.4% in patients with BMI < 16 kg m(-2) and BMI ≥ 40 kg m(-2), respectively. In particularly, this equation overestimated the REE in 51.74% of patients with BMI < 16 kg m(-2). Huang equation involving body composition provided the highest percent of accurate prediction, 42.7% and 66.0% in patients with BMI < 16 and >40 kg m(-2), respectively.

CONCLUSION

Usual predictive equations of REE are not suitable for predicting REE in patients with extreme BMI, in particularly in patients with BMI <16 kg m(-2). Indirect Calorimetry may still be recommended for an accurate assessment of REE in this population until the development of an adapted predictive equation.

Levels and patterns of objectively-measured physical activity volume and intensity distribution in UK adolescents: the ROOTS study

BACKGROUND

Few studies have quantified levels of habitual physical activity across the entire intensity range. We aimed to describe variability in total and intensity-specific physical activity levels in UK adolescents across gender, socio-demographic, temporal and body composition strata.

METHODS

Physical activity energy expenditure and minutes per day (min/d) spent sedentary and in light, moderate, and vigorous intensity physical activity were assessed in 825 adolescents from the ROOTS study (43.5% boys; mean age 15.0 ± 0.30 years), by 4 days of individually calibrated combined heart rate and movement sensing. Measurement days were classified as weekday or weekend and according to the three school terms: summer (April-July), autumn (September-December), and spring (January-March). Gender and age were self-reported and area-level SES determined by postcode data. Body composition was measured by anthropometry and bio-electrical impedance. Variability in physical activity and sedentary time was analysed by linear multilevel modelling, and logistic multilevel regression was used to determine factors associated with physical inactivity (<60 min moderate-to-vigorous intensity physical activity/d).

RESULTS

During awake hours (15.8 ± 0.9 hrs/d), adolescents primarily engaged in light intensity physical activity (517 min/d) and sedentary time (364 min/d). Boys were consistently more physically active and less sedentary than girls, but gender differences were smaller at weekends, as activity levels in boys dropped more markedly when transitioning from weekday to weekend. Boys were more sedentary on both weekend days compared to during the week, whereas girls were more sedentary on Sunday but less sedentary on Saturday. In both genders light intensity physical activity was lower in spring, while moderate physical activity was lower in autumn and spring terms, compared to the summer term; sedentary time was also higher in spring than summer term. Adolescents with higher fatness engaged in less vigorous intensity physical activity. Factors associated with increased odds of physical inactivity were female gender, both weekend days in boys, and specifically Sunday in girls.

CONCLUSIONS

Physical activity components vary by gender, temporal factors and body composition in UK adolescents. The available data indicate that in adolescence, girls should be the primary targets of interventions designed to increase physical activity levels.

Accuracy of aggregate 2- and 3-component models of body composition relative to 4-component for the measurement of changes in fat mass during weight loss in overweight and obese subjects

The 4-component (4-C) model is the reference method to measure fat mass (FM). Simpler 2-component (2-C) models are widely used to assess FM. We hypothesised that an aggregate 2-C model may improve accuracy of FM assessment during weight loss (WL). One hundred and six overweight and obese men and women were enrolled in different WL programs (fasting, very low energy diet, low energy diet). Body density, bone mineral content, and total body water were measured. FM was calculated using 2-C, 3-C, and 4-C models. Aggregate equations for 2-C, 3-C, and 4-C models were calculated, with the aggregate 4-C model assumed as the reference method. The aggregate approach postulates that the average of the individual estimates obtained from each model is more accurate than the best single measurement. The average WL was -7.5 kg. The agreement between 3-C and 4-C models for FM change was excellent (R(2) = 0.99). The aggregate 2-C equation was more accurate than individual 2-C estimates in measuring changes in FM. The aggregate model was characterised by a lower measurement error at baseline and post-WL. The relationship between the aggregate 3-C and 4-C component models was highly linear (R(2) = 0.99), whereas a lower linearity was found for the aggregate 2-C and 4-C model (R(2) = 0.72). The aggregate 2-C model is characterised by a greater accuracy than commonly applied 2-C equations for the measurement of FM during WL in overweight and obese men and women.

Use of fat mass and fat free mass standard deviation scores obtained using simple measurement methods in healthy children and patients: comparison with the reference 4-component model

Background

Clinical application of body composition (BC) measurements for individual children has been limited by lack of appropriate reference data.

Objectives

(1) To compare fat mass (FM) and fat free mass (FFM) standard deviation scores (SDS) generated using new body composition reference data and obtained using simple measurement methods in healthy children and patients with those obtained using the reference 4-component (4-C) model; (2) To determine the extent to which scores from simple methods agree with those from the 4-C model in identification of abnormal body composition.

Design

FM SDS were calculated for 4-C model, dual-energy X-ray absorptiometry (DXA; GE Lunar Prodigy), BMI and skinfold thicknesses (SFT); and FFM SDS for 4CM, DXA and bioelectrical impedance analysis (BIA; height²/Z)) in 927 subjects aged 3.8–22.0 y (211 healthy, 716 patients).

Results

DXA was the most accurate method for both FM and FFM SDS in healthy subjects and patients (mean bias (limits of agreement) FM SDS 0.03 (±0.62); FFM SDS −0.04 (±0.72)), and provided best agreement with the 4-C model in identifying abnormal BC (SDS ≤−2 or ≥2). BMI and SFTs were reasonable predictors of abnormal FM SDS, but poor in providing an absolute value. BIA was comparable to DXA for FFM SDS and in identifying abnormal subjects.

Conclusions

DXA may be used both for research and clinically to determine FM and FFM SDS. BIA may be used to assess FFM SDS in place of DXA. BMI and SFTs can be used to measure adiposity for groups but not individuals. The performance of simpler techniques in monitoring longitudinal BC changes requires investigation. Ultimately, the most appropriate method should be determined by its predictive value for clinical outcome.

BMI and an anthropometry-based estimate of fat mass percentage are both valid discriminators of cardiometabolic risk: a comparison with DXA and bioimpedance

OBJECTIVE

To determine whether categories of obesity based on BMI and an anthropometry-based estimate of fat mass percentage (FM% equation) have similar discriminative ability for markers of cardiometabolic risk as measurements of FM% by dual-energy X-ray absorptiometry (DXA) or bioimpedance analysis (BIA).

DESIGN AND METHODS

A study of 40-79-year-old male (n = 205) and female (n = 388) Finns. Weight, height, blood pressure, triacylglycerols, HDL cholesterol, and fasting blood glucose were measured. Body composition was assessed by DXA and BIA and a FM%-equation.

RESULTS

For grade 1 hypertension, dyslipidaemia, and impaired fasting glucose >6.1 mmol/L, the categories of obesity as defined by BMI and the FM% equation had 1.9% to 3.7% (P < 0.01) higher discriminative power compared to DXA. For grade 2 hypertension the FM% equation discriminated 1.2% (P = 0.05) lower than DXA and 2.8% (P < 0.01) lower than BIA. Receiver operation characteristics confirmed BIA as best predictor of grade 2 hypertension and the FM% equation as best predictor of grade 1 hypertension. All other differences in area under curve were small (≤0.04) and 95% confidence intervals included 0.

CONCLUSIONS

Both BMI and FM% equations may predict cardiometabolic risk with similar discriminative ability as FM% measured by DXA or BIA.

Validation of energy requirement references for exclusively breast-fed infants

In paediatric practice, mean reference energy requirements for groups are often used to predict individual infant energy requirements. References from the FAO/WHO/United Nations University are based on infants not fed according to the current infant feeding recommendations. The objective of the present study was to measure total energy expenditure (TEE) and determine energy requirements using criterion methods, and validate the use of TEE prediction equation and mean energy requirement references for predicting individual TEE and energy requirements, respectively, in infants who were exclusively breast-fed (EBF) to 6 months of age. EBF infants were included from Greater Glasgow for measurements at 3·5 (n 36) and 6 (n 33) months of age. TEE was measured using doubly labelled water and energy requirements were determined using the factorial approach. TEE and energy requirements were also predicted using equations based on body weight. Relationships between criterion methods and predictions were assessed using correlations. Paired t tests and Bland-Altman plots were used to assess agreement. At the population level, predicted and measured TEE were similar. The energy requirement reference significantly underestimated energy requirements by 7·2% at 3·5 months at the population level, but there was no bias at 6 months. Errors at individual levels were large and energy requirements were underestimated to a larger extent for infants with higher energy requirements. This indicates that references presently used in clinical practice to estimate energy requirements may not fully account for the different growth pattern of EBF infants. More studies in infants EBF to 6 months of age are needed to understand how growth of EBF infants influences energy requirements.

Early anthropometric indices predict short stature and overweight status in a cohort of Peruvians in early adolescence

While childhood malnutrition is associated with increased morbidity and mortality, less well understood is how early childhood growth influences height and body composition later in life. We revisited 152 Peruvian children who participated in a birth cohort study between 1995 and 1998, and obtained anthropometric and bioimpedance measurements 11-14 years later. We used multivariable regression models to study the effects of childhood anthropometric indices on height and body composition in early adolescence. Each standard deviation decrease in length-for-age at birth was associated with a decrease in adolescent height-for-age of 0.7 SD in both boys and girls (all P < 0.001) and 9.7 greater odds of stunting (95% CI 3.3-28.6). Each SD decrease in length-for-age in the first 30 months of life was associated with a decrease in adolescent height-for-age of 0.4 in boys and 0.6 standard deviation in girls (all P < 0.001) and with 5.8 greater odds of stunting (95% CI 2.6-13.5). The effect of weight gain during early childhood on weight in early adolescence was more complex to understand. Weight-for-length at birth and rate of change in weight-for-length in early childhood were positively associated with age- and sex-adjusted body mass index and a greater risk of being overweight in early adolescence. Linear growth retardation in early childhood is a strong determinant of adolescent stature, indicating that, in developing countries, growth failure in height during early childhood persists through early adolescence. Interventions addressing linear growth retardation in childhood are likely to improve adolescent stature and related-health outcomes in adulthood.

Do physical activity and aerobic fitness moderate the association between birth weight and metabolic risk in youth?: the European Youth Heart Study

OBJECTIVE

Lower birth weight has been associated with a greater risk of metabolic diseases. The aim of this study was examine whether physical activity and aerobic fitness may modify associations between birth weigh and metabolic risk.

RESEARCH DESIGN AND METHODS

The European Youth Heart Study is a population-based study of 9 and 15 year olds (n = 1,254). Birth weight was maternally reported. Skin fold measures were used to calculate body fat and fat mass index (FMI = fat mass [kilograms]/height²). Insulin was measured using fasting blood samples. Physical activity was measured using a hip-worn accelerometer (MTI Actigraph) for >600 min/day for ≥3 days and is expressed as "average activity" (counts per minute) and time spent in above moderate intensity activity (>2000 cpm). Aerobic fitness was assessed using a maximal cycle ergometry test (watts per kilogram fat-free mass).

RESULTS

Higher birth weight was associated with higher FMI (β = 0.49 [95% CI 0.21-0.80]; P = 0.001) and greater waist circumference (0.90 [0.32-1.47]; P < 0.001), adjusted for sex, age-group, sexual maturity, height, and socioeconomic status. Lower birth weight was associated with higher fasting insulin only after further adjustment for adolescent waist circumference and height (-0.059 [-0.107 to -0.011]; P = 0.016). There was no evidence for any modification of the associations after adjustment for physical activity or aerobic fitness.

CONCLUSIONS

The present study did not find any evidence that physical activity or aerobic fitness can moderate the associations among higher birth weight and increased fat mass and greater waist circumference or between lower birth weight and insulin resistance in healthy children and adolescents.