OBJECTIVE: Using doubly labeled water method to validate the colmputer science application's activity monitor (CSA) in assessing physical activity of free-living adults in Beijing, in order to develop equations to predict total daily energy expenditure (TEE) and activity related energy expenditure (AEE) from activity counts (AC) and anthropometric variables. METHODS: A total of 72 healthy adults (33 males and 39 females, mean age 43.6 +/- 4.0 yr) were monitored for 7 consecutive days by CSA. TEE was simultaneously measured using doubly labeled water method. Average AC (counts/min(-1)) was compared with TEE, AEE and physical activity level (PAL). RESULTS: Physical activity determined by AC was significantly related to data on energy expenditures: TEE (r = 0.31, P < 0.01), AEE (r = 0.30, P < 0.05), and PAL (r = 0.26, P < 0.05). Multiple stepwise regression analysis showed that TEE was significantly influenced by gender, fat-free mass (FFM) or BMI and AC (R(2) = 0.52 - 0.70) while AEE was significantly influenced by gender, FFM and AC (R(2) = 0.25 - 0.32). CONCLUSION: AC from CSA activity monitor seemed a useful measure in studying the total amount of physical activity in free-living adults while AC significantly contributed to the explained variation in TEE and AEE.
OBJECTIVE: Using doubly labeled water method to validate the colmputer science application's activity monitor (CSA) in assessing physical activity of free-living adults in Beijing, in order to develop equations to predict total daily energy expenditure (TEE) and activity related energy expenditure (AEE) from activity counts (AC) and anthropometric variables. METHODS: A total of 72 healthy adults (33 males and 39 females, mean age 43.6 +/- 4.0 yr) were monitored for 7 consecutive days by CSA. TEE was simultaneously measured using doubly labeled water method. Average AC (counts/min(-1)) was compared with TEE, AEE and physical activity level (PAL). RESULTS: Physical activity determined by AC was significantly related to data on energy expenditures: TEE (r = 0.31, P < 0.01), AEE (r = 0.30, P < 0.05), and PAL (r = 0.26, P < 0.05). Multiple stepwise regression analysis showed that TEE was significantly influenced by gender, fat-free mass (FFM) or BMI and AC (R(2) = 0.52 - 0.70) while AEE was significantly influenced by gender, FFM and AC (R(2) = 0.25 - 0.32). CONCLUSION: AC from CSA activity monitor seemed a useful measure in studying the total amount of physical activity in free-living adults while AC significantly contributed to the explained variation in TEE and AEE.
Authors: Kevin Rudolf; Bianca Biallas; Lea A L Dejonghe; Christopher Grieben; Lisa-Marie Rückel; Andrea Schaller; Gerrit Stassen; Holger Pfaff; Ingo Froböse Journal: Int J Environ Res Public Health Date: 2019-12-06 Impact factor: 3.390