Descriptive epidemiology of energy expenditure in the UK: Findings from the National Diet and Nutrition Survey 2008 – 2015

Background Little is known about population levels of energy expenditure as national surveillance systems typically employ only crude measures. The National Diet and Nutrition Survey (NDNS) in the UK measures energy expenditure in a 10% subsample by gold-standard doubly-labelled water (DLW). Methods DLW-subsample participants from the NDNS (383 males, 387 females) aged 4-91yrs were recruited between 2008 and 2015. Height and weight were measured, and bodyfat percentage was estimated by deuterium dilution. Results Absolute Total Energy Expenditure (TEE) increases steadily throughout childhood, ranging from 6.3 and 7.2 MJ/day in 4-7yr-old to 9.9 and 11.8 MJ/day for 14-16yr-old girls and boys, respectively. TEE peaked in 17-27yr-old women (10.9 MJ/day) and 28-43yr-old men (14.4 MJ/day), before decreasing gradually in old age. Physical Acitivty Energy Expenditure (PAEE) declines steadily with age from childhood (87.7 kJ/day/kg in 4-7yr olds) through to old age (38.9 kJ/day/kg in 71-91yr olds). Bodyfat percentage was strongly inversely associated with PAEE throughout life, irrespective of expressing PAEE relative to bodymass or fat-free mass. Compared to females with <30% bodyfat, females >40% recorded 28 kJ/day/kg and 17 kJ/day/kg fat-free mass less PAEE in analyses adjusted for age, geographical region, and time of assessment. Similarly, compared to males with <25% bodyfat, males >35% recorded 26 kJ/day/kg and 10 kJ/day/kg fat-free mass less PAEE. Conclusions This first nationally representative study reports levels of human energy expenditure as measured by gold-standard methodology; values may serve as reference for other population studies. Age, sex and body composition are main biological determinants of energy expenditure. Key messages First nationally representative study of human energy expenditure, covering the UK in the period 2008-2015 Total Energy Expenditure (MJ/day) increases steadily with age thoughout childhood and adolescence, peaks in the 3rd decade of life in women and 4th decade of life in men, before decreasing gradually in old age Physical Acitivty Energy Expenditure (kJ/day/kg or kJ/day/kg fat-free mass) declines steadily with age from childhood to old age, more steeply so in males Bodyfat percentage is strongly inversely associated with physical activity energy expenditure


Introduction
Little is known about population levels of energy expenditure (EE) as most national surveys use proxy methods for assessment, typically questionnaires. These may take the form of either self-reported dietary energy intake combined with measures of weight change 1 , or selfreported physical activity combined with estimates of resting EE 2 . The former approach is challenged not only by the necessary correction for any weight changes but also by possible underreporting of energy intake by overweight or obese individuals 3 . The latter approach does not need to make assumptions about energy balance as it is directly assessing the expenditure side; however, self-report methods for physical activity also have limited accuracy, and this applies particularly to derivatives such as estimates of energy expenditure 4 .
The use of objective methods in the form of wearable sensors such as accelerometers and heart rate monitors is typically preferred as the objective methods for large-scale population studies, since these provide information about intensity patterns as well as more precise estimates of energy expenditure when coupled with appropriate inference models 5-8 . Irrespective of the success of such inference models, feasibility is somewhat limited for methods using heart rate monitoring due to its requirement for individual calibration using an exercise test 9,10 , whereas the main limitation of accelerometry-based estimation of energy expenditure depends on the mix of specific behaviours in which the population under study is engaged as this relationship varies by activity type 11,12 . Preferably, one would therefore employ more direct, yet highly feasible, measurements of the quantity of interest for the surveillance of population trends in energy expenditure. The doubly-labeled water (DLW) technique is the gold-standard for measurement of energy expenditure during free-living 13 . This technique uses the stable isotopes deuterium ( 2 H) and Oxygen-18 ( 18 O) to directly measure rate of carbon dioxide production (rCO 2 ) over a period of 1-2 weeks, from which average total energy expenditure (TEE) can be calculated with high precision. Combined with simple anthropometric measurements, estimates of physical activity energy expenditure (PAEE) can also be derived. The DLW method is highly feasible in terms of low participant burden but it is unfortunately also expensive and hence is only seldom used in large studies.
The National Diet and Nutrition Survey (NDNS) employs a nationally representative sampling frame to assess dietary behaviours in the UK population 14 . One of the unique features of the NDNS is that a 10% subsample of all age groups 4years or older also had energy expenditure assessed using the DLW technique over 10 days of free-living. The aim of this study was to describe the variation in components of energy expenditure by key personal characteristics, geographical location, and over time.

Participants
Participants were recruited to the rolling programme in the main NDNS by stratified and clustered random sampling of households in the UK. NDNS data are weighted to account for any selection or response biases to ensure results are representative of the UK population 15 .
A total of 15,583 households were selected to take part in the main NDNS, and 8,974 households agreed (58% household response rate). From those households, 10,727 individuals agreed to take part and a subsample of these main NDNS participants were invited to take part in the DLW substudy, within which individuals were sampled according to pre-specified age/sex strata (4-10, 11-15, 16-49, 50-64, and 65+ years). The DLW substudy field work was carried out in two waves; for the first wave (2008-11), targets were 40 participants in each of the age/sex groups but for the second wave (2013-15), these were changed to 30 participants for each stratum for those aged 4-10 and those 65+ years, and to 50 participants for those aged 16-49 years. A total of 808 were invited to take part in the DLW substudy, of whom 770 participants provided sufficient data to derive valid EE estimates and they constitute the sample included in the present analysis. This subsample does not differ from the main NDNS (excluding children <4yrs) in terms of sex, body mass index (BMI), total energy intake, fruit and vegetable intake in g/day, free sugar intake (% total energy intake), and saturated fat intake (% total energy intake) but it was 2.6 years older 16 .
All adult participants provided informed written consent and all children provided assent with written consent from their legal guardian. The study was approved by the Oxfordshire A Research Ethics Committee (#07/H0604/113) and Cambridge South NRES Committee (#13/EE/0016).

Measurements
Anthropometric measurements were performed in participants' homes. Height was measured to the nearest millimeter using a portable stadiometer and bodymass was measured to the nearest 100g in light clothing using calibrated scales 17  Resting metabolic rate was estimated from anthropometry variables by averaging three prediction equations; one based on age, sex, height, and total bodymass derived in a large database 22 , and two based on smaller studies which also take into account body composition 23,24 . In order to calculate 24-hour resting energy expenditure (REE), we integrated this resting metabolic rate value over time, but with a small adjustment for the 5% lower metabolic rate observed during sleep 25 applied using age-specific sleep durations ranging from 8-12 hours/day 26 . The diet-induced thermogenesis (DIT) was assumed to constitute 10% of TEE 27 , and PAEE was calculated as the residual energy expenditure which sums with REE and DIT to make up TEE, according to the equation PAEE = TEE -REE -

Statistics
We expressed daily TEE in absolute (MJ/day) units and both TEE and PAEE in relative units (kJ/day/kg bodymass). As sensitivity analyses, we also expressed energy expenditure in units scaled to fat-free bodymass and in alometrically-scaled units of kJ/day/kg 2/3 bodymass, the latter based on the theoretical principle that absolute energy expenditure scales to bodily dimensions to the power of 2 and bodymass scales to bodily dimensions to the power of 3 28,29 . We present summary statistics (mean and standard deviation) of all estimates of energy expenditure by recruitment strata, ie age and sex groups. In addition, we present box plots London and South East as used previously 30 . We examine the association with obesity status by both body mass index (BMI) and bodyfat groups, stratified by sex and age groups. To examine independent associations, we performed a multiple linear regression analysis with mutual adjustment for all above factors, and with additional adjustment for season of measurement (expressed as two orthogonal sine functions; "winter" (with max=1 on January 1 st and min=-1 on July 1 st ) and "spring" (with max=1 on April 1 st and min=-1 on October 1 st ).

Results
Of the 770 participants with valid DLW data in the NDNS included in this analysis, the four constituent countries of the United Kingdom were represented with 568 participants from England, 50 from Scotland, 72 from Wales and 80 from Northern Ireland (Table 1).   (Table 2).
Across the sample, absolute TEE (MJ•day -1 ) was higher in individuals with higher BMI.
Overweight participants had higher TEE (MJ•day -1 ) than normal-weight participants, and obese participants accumulated higher TEE levels than overweight participants, a trend that was observed within nearly all age-and sex strata ( Figure 4). However, this relationship was inverse when TEE was expressed in relative terms. Obese males and females in all age groups recorded the lowest relative TEE and PAEE (kJ•day -1 •kg -1 ), whereas normal-weight individuals recorded the highest.
A similar relationship was also observed for TEE and PAEE across groups of differing bodyfat percentage, although the clear positive trend for absolute TEE was absent in the two adult age groups ( Figure 5). For relative TEE and PAEE (kJ•day -1 •kg -1 ), those with the highest bodyfat percentage recorded the lowest energy expenditure, whereas the slimmest individuals recorded the highest. The sole exception to this were men aged 65-91y with medium bodyfat who as a group accumulated more PAEE than their slimmer counterparts.
The multivariable regression analysis confirmed associations with BMI and body composition in both sexes (Table 2).
In sensitivity analyses modelling PAEE per kg fat-free mass (supplement table T2), individuals in the third tertile of fat mass index were less active; this inverse association was more consistent for bodyfat percentage groups. This sensitivity analysis also suggested a possible regional difference in activity levels, with non-English women expending more activity energy per kg fat-free mass, independent of other covariates.

Discussion
Here, we report gold-standard measured energy expenditure from a nationally representative This study also has some limitations. The study as a whole is not large, with only 770 individuals included in the present analyses. In addition, the majority of the sample came from England, with very few participants included in certain subgroup analyses. The generalisability of these small groups to the wider Northern Irish, Scottish and Welsh populations is therefore less certain. It is also possible that non-participating households may differ from participating households. Another limitation is that data are effectively snap-shot assessments taken at relatively short time intervals between the 2008 and 2015 which is unlikely to be sufficient to detect secular trends even if they truly occurred in the UK over this time period; given the slight increase in national obesity levels in the same period 45 , we suspect that absolute TEE levels may have also increased but that relative EE levels may have decreased in line with the observed associations with such indicators in our study.
In conclusion, age, sex and body composition are main biological determinants of human energy expenditure. Results from this nationally representative sample using gold-standard methodology may serve as reference values for other population studies.