TY - JOUR
T1 - Validity of activity monitors in health and chronic disease
T2 - a systematic review
AU - Van Remoortel, Hans
AU - Giavedoni, Santiago
AU - Raste, Yogini
AU - Burtin, Chris
AU - Louvaris, Zafeiris
AU - Gimeno-Santos, Elena
AU - Langer, Daniel
AU - Glendenning, Alastair
AU - Hopkinson, Nicholas S.
AU - Vogiatzis, Ioannis
AU - Peterson, Barry T.
AU - Wilson, Frederick
AU - Mann, Bridget
AU - Rabinovich, Roberto
AU - Puhan, Milo A.
AU - Troosters, Thierry
AU - Chiesi Farmaceutici, S. A.
AU - Brindicci, Caterina
AU - Higenbottam, Tim
AU - Troosters, Thierry
AU - Dobbels, Fabienne
AU - Decramer, Marc
AU - Tabberer, Margaret X.
AU - Rabinovich, Roberto A.
AU - McNee, William
AU - Vogiatzis, Ioannis
AU - Polkey, Michael
AU - Hopkinson, Nick
AU - Garcia-Aymerich, Judith
AU - Puhan, Milo
AU - Frei, Anja
AU - van der Molen, Thys
AU - De Jong, Corina
AU - de Boer, Pim
AU - Jarrod, Ian
AU - McBride, Paul
AU - Kamel, Nadia
AU - Rudell, Katja
AU - Wilson, Frederick J.
AU - Ivanoff, Nathalie
AU - Kulich, Karoly
AU - Glendenning, Alistair
AU - Karlsson, Niklas X.
AU - Corriol-Rohou, Solange
AU - Nikai, Enkeleida
AU - Damijen Erzen, Erzen
PY - 2012/7/9
Y1 - 2012/7/9
N2 - 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
AB - 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
KW - Activity monitoring
KW - Chronic diseases
KW - Doubly labelled water
KW - Indirect calorimetry
KW - Physical activity
KW - Systematic review
KW - Validation study
UR - http://www.scopus.com/inward/record.url?scp=84863534837&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84863534837&partnerID=8YFLogxK
U2 - 10.1186/1479-5868-9-84
DO - 10.1186/1479-5868-9-84
M3 - Article
C2 - 22776399
AN - SCOPUS:84863534837
SN - 1479-5868
VL - 9
JO - International Journal of Behavioral Nutrition and Physical Activity
JF - International Journal of Behavioral Nutrition and Physical Activity
M1 - 84
ER -