Objective methods .1 The ‘Gold standard’

Calorimetry is a highly accurate and reliable measure of PA energy expenditure, but is only suitable for lab-based, not free-living, studies because of the non-portable, expensive equipment required.^169,170 Doubly labelled water (DLW) is considered the gold standard method of measuring of free-living PA.157,158,171

DLW requires participants to ingest a specified dose of water, labelled with two non-radioactive (i.e. stable) isotopes.¹⁷² The participant provides biological samples (urine, saliva or blood) prior to ingestion, post-ingestion after a period of equilibration, and each day for the duration of the monitoring period (often about 10 days).¹⁷² The deuterium (²H) is eliminated as water and the ¹⁸O is eliminated as water and carbon dioxide, so the difference between the two elimination rates is a measure of CO2 production, a marker of energy expenditure.¹⁷² Basal metabolic rate

(estimated, or measured by calorimetry) and diet induced thermogenesis (assumed to be 10%

of energy expenditure) are subtracted from energy expenditure to give PA energy expenditure. ^158,172

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As a measure of total energy expenditure, DLW is highly accurate,^172-175 and reliable.172,176,177

The main sources of error in DLW estimates of PA are: ingestion of an incorrect dose; error in laboratory techniques; inaccurate recording of results; and inaccurate estimation of basal metabolic rate.¹⁵⁵ DLW is safe and suitable for all age groups and can be used on large numbers of participants in epidemiological studies. The main burden for participants is the provision of daily biological samples throughout the measurement period.

DLW is more expensive than most other measures of free-living PA, incurring costs for the isotopes, collection and storage of biological samples, and laboratory analyses and

equipment.^169,172 The main limitations of DLW as a measure of PA the high costs and inability to capture information on PA subdomains such as intensity, frequency and duration.¹⁶⁹

1.8.1.1.2 Pedometers

Pedometers measure the number of steps that an individual takes within a specified time period. They are very easy to use, small and lightweight, non-invasive, little burden to participants, one of the cheapest available objective methods for measuring PA, and produce simple, easy-to-interpret data (steps/day) which are comparable across studies and relatively reliable (intra-class coefficients of approximately 0.6-0.7 across multiple days¹⁷⁸)155,179-182

Thus, in practical terms, pedometry is very convenient for large-scale studies.

However, pedometers cannot measure the intensity, duration or frequency of PA bouts,^180,181 are unable to detect non-step-based activities, such as cycling, swimming, and upper-body movement,^157,183 and give inaccurate step counts at slow (<2mph) walking speeds.¹⁸⁴ Differentiation of ST from non-wear-time requires the participant to complete a diary of times when the device was not worn, increasing participant burden,¹⁸⁵ and many pedometers lack the capacity to store daily output in their memory and instead rely on participants

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recording the data at the end of each day and resetting it for the following day.¹⁸⁵ This introduces risk of bias and error through participants forgetting to record, or

consciously/subconsciously misreporting, number of steps.¹⁸⁶ Moreover, unsealed pedometers are not tamper-proof, so participants are able to hit the reset button and can deliberately increase the recorded number of steps by shaking the device, producing invalid data.¹⁸³ It is also unclear how many days, and hours per day, of pedometer data are required for valid representation of habitual PA.^181,185 The Hawthorne Effect, whereby participants modify their behaviour because they are aware that they are being monitored,¹⁸⁷ is, to varying extents, a potential problem for all objective methods of measuring PA.^181,185 However, it is particularly pertinent to pedometry because many devices allow participants to see their output in real-time (i.e. they have access to continuous feedback about the number of steps they have taken¹⁸⁵) and research suggests that wearing a pedometer might increase participants’ PA.¹⁸⁸

Because of these limitations, pedometer-estimates of total PA are less accurate compared with accelerometer estimates of PA,¹⁸⁰ and a recent review highlighted the lack of evidence regarding validity and reliability of pedometer estimates of PA in children under the age of 6 years.¹⁸⁵ Overall, pedometers provide accurate and reliable assessment of step count among adolescents and children aged 6 years and above,¹⁸⁵ but converting the output to PAEE is difficult,¹⁸⁰ so it is recommended that pedometers be used only to measure step-based PA, not total PA.180,182,185

1.8.1.1.3 Accelerometers

Accelerometers are motion sensors which detect movement in one or more plane(s). A range of devices are available.^180,189 Most are worn on a belt at the hip, waist, chest or wrist. Some devices measure movement in one plane (uni-axial devices), while others detect movement in two (bi-axial devices) or three (tri-axial devices) planes. Uni-axial devices provide the

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simplest, easiest-to-process, output, but are unable to detect movement in other planes and are, therefore, generally thought to provide less valid estimates of PA than multi-axial

devices,¹⁵⁵ although several studies in children have reported little difference in PA estimates between uni-axial and tri-axial devices.^190,191

Accelerometer models that have been validated against DLW as a measure of free-living PA are currently considered one of the most effective field-based options for measuring

PA,¹⁵⁸ balancing cost (accelerometry is cheaper than DLW) with accuracy and reliability (accelerometry is superior to pedometers and subjective methods¹⁸⁰). Accelerometers are not subject to recall bias and provide objective, standardised data which captures frequency, duration and intensity of PA.^180,189 They are highly portable and easy to use in the field. The greater precision of accelerometers, compared with pedometers and subjective methods, also improves statistical power for a given sample size.¹⁸⁰

One of the main limitations of accelerometry is inability to detect non-ambulatory activities (e.g. rowing and cycling) or changes in intensity due to gradient or load.^192-194 Water-based activities might also go undetected as many devices are not waterproof. Also, for the safety of participants, ethics committees sometimes impose restrictions on the wearing of

accelerometers during contact sports.¹⁵⁵ Another key issue in estimating PA from accelerometry is the lack of consensus regarding which accelerometer thresholds or

regression equations should be used to convert accelerometer output to PAEE or time spent in different PA intensities.181,182,195-197

Detection of non-wear time is also difficult with accelerometry as low counts can be reflective of either ST or non-wear time.^198,199 There is also some dispute in the literature regarding the duration of PA monitoring required for the data to be sufficiently representative of habitual PA,^198,200 and the epoch length required for optimal accuracy.¹⁹⁷ Longer epochs (e.g. sampling at one minute intervals) generally permit a longer duration monitoring period as battery life and memory are preserved, but shorter

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epochs (e.g. sampling at 5-10 second intervals) tend to give more accurate estimates of PA, particularly among children.¹⁹⁷ The data processing stage can also be quite time consuming, and the logistics of using accelerometers in large scale studies can also be relatively labour intensive compared with some methods; all devices have to be charged, set-up, delivered to participants, collected/returned, and the data downloaded and processed.¹⁵⁵

1.8.1.1.4 Heart rate monitoring

Heart rate monitors are generally worn on a belt across the chest and assess the physiological response to PA by measuring heart rate within a specified time period. The main advantages of heart rate monitors are that they are easy to use, suitable for all age groups, can be used to measure free-living PA, are particularly effective at measuring high intensity PA, are

relatively cheap compared with DLW and some accelerometers, and produce simple output that is easy to interpret_.158,181,201,202

The main limitations of heart rate monitors are the requirement for individual-level calibration of the association between heart rate and energy expenditure,^171,202 which is often impractical for large scale studies, and inability to

differentiate between different sources of increases in heart rate (e.g. increases in heart rate due to emotional stimuli or pain versus increases due to PA).^203,204 As such, ‘noise’ is a greater source of measurement error for heart rate monitors than for accelerometers.²⁰³ Moreover, there is a time-lag between the onset of PA and the associated increase in heart rate, and, similarly, there is a delay in heart rate returning back to resting levels after PA.^154,155 This time-lag can reduce accuracy of PA estimates if intervals between PA bouts are not long enough to allow heart rate to return to resting, or near-resting, levels, and is therefore problematic for studies of children whose PA is characterised by frequent, short bouts of PA.¹⁵⁵ It is also a limitation if study participants differ significantly in their levels of cardiorespiratory fitness¹⁵⁵ because fitness level influences the speed at which heart rate

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returns to resting levels after exercise.²⁰⁴ Finally, many devices are not waterproof and therefore unable to measure water-based activities.

1.8.1.1.5 Combined motion sensing and heart rate monitoring

In recent years, technological and computing advances have contributed to the development of methods which combine both heart rate monitoring and motion sensing.²⁰² This approach is thought to improve accuracy and reliability of PA estimates by overcoming the limitations of using heart rate monitoring or accelerometry alone.^205-207 For example, heart rate data provides more accurate estimates for higher intensities of PA and exercise on a gradient (e.g.

uphill walking),²⁰² whereas accelerometry is more accurate at lower intensities.^201,202 The Actiheart monitor is an example of a combined heart rate monitor and motion sensor which has been validated and calibrated in adults and youth.190,191,205,207

However, to optimise accuracy of PA estimates, such devices require calibration at the individual level.²⁰² For example, the Actiheart monitor has a built-in step-test function for this purpose.²⁰² The Actiheart is waterproof, extremely lightweight (6 grams), and, unlike pedometers, the output cannot be tampered with. Thus, although more expensive than a standard accelerometer, pedometer or heart rate monitor, the Actiheart is a particularly attractive option for estimating free-living PA/ST in children.¹⁵⁵