Abstract
The assessment of physical activity in healthy populations and in those with chronic diseases is challenging. The aim of this systematic review was to identify whether available activity monitors (AM) have been appropriately validated for use in assessing physical activity in these groups. Following a systematic literature search we found 134 papers meeting the inclusion criteria; 40 conducted in a field setting (validation against doubly labelled water), 86 in a laboratory setting (validation against a metabolic cart, metabolic chamber) and 8 in a field and laboratory setting. Correlation coefficients between AM outcomes and energy expenditure (EE) by the criterion method (doubly labelled water and metabolic cart/chamber) and percentage mean differences between EE estimation from the monitor and EE measurement by the criterion method were extracted. Random-effects meta-analyses were performed to pool the results across studies where possible. Types of devices were compared using meta-regression analyses. Most validation studies had been performed in healthy adults (n = 118), with few carried out in patients with chronic diseases (n = 16). For total EE, correlation coefficients were statistically significantly lower in uniaxial compared to multisensor devices. For active EE, correlations were slightly but not significantly lower in uniaxial compared to triaxial and multisensor devices. Uniaxial devices tended to underestimate TEE (−12.07 (95%CI; -18.28 to −5.85) %) compared to triaxial (−6.85 (95%CI; -18.20 to 4.49) %, p = 0.37) and were statistically significantly less accurate than multisensor devices (−3.64 (95%CI; -8.97 to 1.70) %, p<0.001). TEE was underestimated during slow walking speeds in 69% of the lab validation studies compared to 37%, 30% and 37% of the studies during intermediate, fast walking speed and running, respectively. The high level of heterogeneity in the validation studies is only partly explained by the type of activity monitor and the activity monitor outcome. Triaxial and multisensor devices tend to be more valid monitors. Since activity monitors are less accurate at slow walking speeds and information about validated activity monitors in chronic disease populations is lacking, proper validation studies in these populations are needed prior to their inclusion in clinical trials.
Highlights
There is evidence that regular physical activity is associated with a reduced risk of mortality and contributes to the primary and secondary prevention of several chronic diseases [1]
The systematic literature search resulted in a total of 2875 abstracts which were scrutinised by four review teams across Europe
Correlations for active energy expenditure (AEE) between AEEAM and AEEDLW were higher in triaxial (0.59 (95%confidence interval (CI), 0.45 to 0.70)) and multisensor devices (0.54 (95%CI, 0.39 to 0.65)) compared to uniaxial (0.39) devices, p = 0.12 for triaxial and p = 0.32 for multisensor against uniaxial devices) (Figure 4) Types of devices accounted for only 12% of the between-study heterogeneity in the meta-regression analysis
Summary
There is evidence that regular physical activity is associated with a reduced risk of mortality and contributes to the primary and secondary prevention of several chronic diseases [1]. In patients with chronic obstructive pulmonary disease (COPD), regular physical activity leads to a lower risk of both COPD related hospital admissions and mortality [3]. Physical activity limitation is a major problem in patients with chronic diseases and needs to be accurately measured if therapies aimed at improving this are to be properly evaluated. Physical activity is defined as any bodily movement, produced by skeletal muscles, requiring energy expenditure [4]. Physical activity can be considered as “the totality of voluntary movement produced by skeletal muscles during everyday functioning” [5]. Questionnaires rely on the subject’s recollection of activities and allow categorization of patients by physical activity (very active, active, sedentary and inactive) [6], but may lack the precision needed to detect changes in physical activity on a day to day basis
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