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Relationship amongst three activity monitors commonly used to quantify physical activity
S302
Friday 2 November Posters / Journal of Science and Medicine in Sport 15 (2012) S265–S327
including weekdays and weekend days in a sample of 571 women and 315 men aged 18–92-years living in the Kanto region. The algorithm used to classify locomotive and non-locomotive activities and the intensity of these physical activities (metabolic equivalents) has been developed previously (Oshima, 2010; Ohkawara, 2011). The duration in minutes of locomotive and non-locomotive activities for light, moderate, and vigorous intensity was evaluated using a triaxial accelerometer. Results: For women, participants older than 70 years spent significantly less time in non-locomotive and total moderate-tovigorous PA (MVPA), and total light activity than those in the other age groups, and less time in locomotive MVPA and light activity than those aged 18–49 years. Time in locomotive and total MVPA, and locomotive light activity for women aged between 50–69 years was also significantly lower compared with those aged 18–49 years. On the other hand, time in non-locomotive activity for women aged between 50–69 years was significantly higher than those in the other age groups. For men, the time in locomotive and total MVPA and locomotive light activity for those older than 70 years was significantly lower than those in the other age groups. There was no significant difference between the male age groups for nonlocomotive time at MVPA and light activity and total light activity. There was also no significant difference in men between the groups aged 50–69 years and 18–49 years. Discussion: Elderly people, especially women, spent less time, in not only locomotive MVPA and light activity, but also in nonlocomotive MVPA. This finding indicated that evaluation of nonlocomotive activity is important. This study was supported by Health Sciences Research Grants (Research on Health Science) from the Ministry of Health, Labor and Welfare (to C. Tanaka and S. Tanaka) and a grant from Meiji Yasuda Life Foundation of Health and Welfare in 2009 (to C. Tanaka).
son’s correlation and Lin’s concordance. Range of agreement across the 5 days is reported. Results: Women wore the devices on average 12.6 ± 1.7 (h·d-1). Overall concordance of PAEE amongst the 3 devices was nonexistent to very low (Rc = -0.01 to 0.46), and this was reflected by significant differences in means between devices. As the AG was designed to measure activity rather than PAEE, the relationship between its activity counts and PAEE from the SW and AH were explored. The devices were low-to-moderately correlated (SW: r = 0.47 to 0.72; AH: r = 0.13 to 0.35). Concordance of MVPA among the 3 devices was also non-existent to very low (Rc = 0.05 to 0.61), with a low-to-moderate correlation (r = 0.05 to 0.75). Discussion: Whilst the three devices all purported to measure PAEE and MVPA, they had very poor agreement on the measures. Some of the differences may have arisen from participants not wearing the devices correctly, and may explain day to day variance. Caution should be exercised when selecting a wearable physical activity monitor, and also in the interpretation of results from using such devices. As a means of understanding which of these devices more accurately quantify physical activity during free-living, validation of each of these devices against a reference method such as doubly-labelled water is necessary. http://dx.doi.org/10.1016/j.jsams.2012.11.735 733 Reduction of sitting time in sedentary men and women. A randomized controlled trial (Sedentary Intervention Trial) M. Aadahl 1,∗ , A. Linneberg 1 , D. Witte 2 , T. Jørgensen 1 1 2
http://dx.doi.org/10.1016/j.jsams.2012.11.734 732 Relationship amongst three activity monitors commonly used to quantify physical activity J. Yee 1,∗ , B. Abell 1 , G. Davis 1 , L. Ward 1,2 , D. Black 1 , S. Kilbreath 1 1
Faculty of Health Sciences, University of Sydney School of Chemistry and Molecular Biosciences, University of Queensland 2
Introduction: There is a wide variety of activity monitors available for quantifying physical activity and predicting energy expenditure under free-living conditions, each utilising different technologies. This study explored relationships amongst the ActiGraphTM (AG), ActiHeart® (AH) and Sensewear® (SW) monitors in describing physical activity energy expenditure (PAEE) and time spent doing moderate-to-vigorous intensity physical activity (MVPA) during free-living. Methods: All participants (n = 32) wore the AG accelerometer at the waist, the SW positioned midway at the posterior aspect of the upper right arm, and the AH attached to electrodes just below the apex of the sternum during all waking hours for a period of 7 days. Only data from 5 days in which there was a minimum of 10 hours wearing time were analysed. Simultaneous measurements related to physical activity were continuously recorded by all 3 devices. Customised software specific to AG and SW were used to derive average PAEE (kJ·hr-1) and minutes of MVPA for each day. Software specific to the AH was used to derive average PAEE, but minutes of MVPA was extracted from raw data. For the AG, average counts were also extracted. Each day was analysed separately, using Pear-
Research Centre for Prevention and Health Steno Diabetes Center A/S, Gentofte, Denmark
Introduction: Prospective epidemiological studies suggest that prolonged leisure time sedentary behaviour, in particularTVviewing, is associated with an increased risk of type 2 diabetes, cardiovascular disease and all cause mortality in adults. Sedentary leisure time behaviour is also associated with cardiometabolic biomarkers in cross sectional and longitudinal studies. A few intervention studies with small numbers of study participants have demonstrated a reduction in sitting time among adults using individual lifestyle counseling. The purpose of the present study was to investigate 1) whether it is possible to reduce amount of daily sitting time using individually tailored, theory-based motivational counseling and 2) whether a reduction in sedentary time is reflected in cardiometabolic biomarkers and anthropometric measures. Methods: From an on-going population-based epidemiological study including men and women between 18 and 69 years of age (the Health2010 Study), participants who self-reported at least 3.5 hours of leisure time sitting per day, were invited to participate in the present randomized controlled trial. As determined by power calculation, a total of 171 participants, who gave written informed consent, went through an extensive baseline health examination including blood samples and measurement of height, weight, waist circumference, blood pressure, muscle strength, cardiorespiratory fitness. Participants wore an activPALTM monitor for 7 days and were then randomized to either a control group (usual lifestyle) or an intervention group. The primary outcome measure was sedentary time measured by activPALTM . The intervention consisted of 4 individual theory-based counseling sessions conducted by trained nurses over the following 6 months. The intervention focused on individual goal setting and written materials with key messages and ideas for reduction of sitting time were handed out at each session (booklets, postcards and stickers). After 6 months, all par-
Friday 2 November Posters / Journal of Science and Medicine in Sport 15 (2012) S265–S327
including weekdays and weekend days in a sample of 571 women and 315 men aged 18–92-years living in the Kanto region. The algorithm used to classify locomotive and non-locomotive activities and the intensity of these physical activities (metabolic equivalents) has been developed previously (Oshima, 2010; Ohkawara, 2011). The duration in minutes of locomotive and non-locomotive activities for light, moderate, and vigorous intensity was evaluated using a triaxial accelerometer. Results: For women, participants older than 70 years spent significantly less time in non-locomotive and total moderate-tovigorous PA (MVPA), and total light activity than those in the other age groups, and less time in locomotive MVPA and light activity than those aged 18–49 years. Time in locomotive and total MVPA, and locomotive light activity for women aged between 50–69 years was also significantly lower compared with those aged 18–49 years. On the other hand, time in non-locomotive activity for women aged between 50–69 years was significantly higher than those in the other age groups. For men, the time in locomotive and total MVPA and locomotive light activity for those older than 70 years was significantly lower than those in the other age groups. There was no significant difference between the male age groups for nonlocomotive time at MVPA and light activity and total light activity. There was also no significant difference in men between the groups aged 50–69 years and 18–49 years. Discussion: Elderly people, especially women, spent less time, in not only locomotive MVPA and light activity, but also in nonlocomotive MVPA. This finding indicated that evaluation of nonlocomotive activity is important. This study was supported by Health Sciences Research Grants (Research on Health Science) from the Ministry of Health, Labor and Welfare (to C. Tanaka and S. Tanaka) and a grant from Meiji Yasuda Life Foundation of Health and Welfare in 2009 (to C. Tanaka).
son’s correlation and Lin’s concordance. Range of agreement across the 5 days is reported. Results: Women wore the devices on average 12.6 ± 1.7 (h·d-1). Overall concordance of PAEE amongst the 3 devices was nonexistent to very low (Rc = -0.01 to 0.46), and this was reflected by significant differences in means between devices. As the AG was designed to measure activity rather than PAEE, the relationship between its activity counts and PAEE from the SW and AH were explored. The devices were low-to-moderately correlated (SW: r = 0.47 to 0.72; AH: r = 0.13 to 0.35). Concordance of MVPA among the 3 devices was also non-existent to very low (Rc = 0.05 to 0.61), with a low-to-moderate correlation (r = 0.05 to 0.75). Discussion: Whilst the three devices all purported to measure PAEE and MVPA, they had very poor agreement on the measures. Some of the differences may have arisen from participants not wearing the devices correctly, and may explain day to day variance. Caution should be exercised when selecting a wearable physical activity monitor, and also in the interpretation of results from using such devices. As a means of understanding which of these devices more accurately quantify physical activity during free-living, validation of each of these devices against a reference method such as doubly-labelled water is necessary. http://dx.doi.org/10.1016/j.jsams.2012.11.735 733 Reduction of sitting time in sedentary men and women. A randomized controlled trial (Sedentary Intervention Trial) M. Aadahl 1,∗ , A. Linneberg 1 , D. Witte 2 , T. Jørgensen 1 1 2
http://dx.doi.org/10.1016/j.jsams.2012.11.734 732 Relationship amongst three activity monitors commonly used to quantify physical activity J. Yee 1,∗ , B. Abell 1 , G. Davis 1 , L. Ward 1,2 , D. Black 1 , S. Kilbreath 1 1
Faculty of Health Sciences, University of Sydney School of Chemistry and Molecular Biosciences, University of Queensland 2
Introduction: There is a wide variety of activity monitors available for quantifying physical activity and predicting energy expenditure under free-living conditions, each utilising different technologies. This study explored relationships amongst the ActiGraphTM (AG), ActiHeart® (AH) and Sensewear® (SW) monitors in describing physical activity energy expenditure (PAEE) and time spent doing moderate-to-vigorous intensity physical activity (MVPA) during free-living. Methods: All participants (n = 32) wore the AG accelerometer at the waist, the SW positioned midway at the posterior aspect of the upper right arm, and the AH attached to electrodes just below the apex of the sternum during all waking hours for a period of 7 days. Only data from 5 days in which there was a minimum of 10 hours wearing time were analysed. Simultaneous measurements related to physical activity were continuously recorded by all 3 devices. Customised software specific to AG and SW were used to derive average PAEE (kJ·hr-1) and minutes of MVPA for each day. Software specific to the AH was used to derive average PAEE, but minutes of MVPA was extracted from raw data. For the AG, average counts were also extracted. Each day was analysed separately, using Pear-
Research Centre for Prevention and Health Steno Diabetes Center A/S, Gentofte, Denmark
Introduction: Prospective epidemiological studies suggest that prolonged leisure time sedentary behaviour, in particularTVviewing, is associated with an increased risk of type 2 diabetes, cardiovascular disease and all cause mortality in adults. Sedentary leisure time behaviour is also associated with cardiometabolic biomarkers in cross sectional and longitudinal studies. A few intervention studies with small numbers of study participants have demonstrated a reduction in sitting time among adults using individual lifestyle counseling. The purpose of the present study was to investigate 1) whether it is possible to reduce amount of daily sitting time using individually tailored, theory-based motivational counseling and 2) whether a reduction in sedentary time is reflected in cardiometabolic biomarkers and anthropometric measures. Methods: From an on-going population-based epidemiological study including men and women between 18 and 69 years of age (the Health2010 Study), participants who self-reported at least 3.5 hours of leisure time sitting per day, were invited to participate in the present randomized controlled trial. As determined by power calculation, a total of 171 participants, who gave written informed consent, went through an extensive baseline health examination including blood samples and measurement of height, weight, waist circumference, blood pressure, muscle strength, cardiorespiratory fitness. Participants wore an activPALTM monitor for 7 days and were then randomized to either a control group (usual lifestyle) or an intervention group. The primary outcome measure was sedentary time measured by activPALTM . The intervention consisted of 4 individual theory-based counseling sessions conducted by trained nurses over the following 6 months. The intervention focused on individual goal setting and written materials with key messages and ideas for reduction of sitting time were handed out at each session (booklets, postcards and stickers). After 6 months, all par-