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The assessment of physical activity and sedentary behaviors

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The health benefits of physical activity are widely accepted. Emerging research also indicates that sedentary behaviors can carry negative health consequences regardless of physical activity level. This dissertation explored four projects that examined measurement properties of physical activity and sedentary behavior monitors. Project one identified the oxygen costs of four…

The health benefits of physical activity are widely accepted. Emerging research also indicates that sedentary behaviors can carry negative health consequences regardless of physical activity level. This dissertation explored four projects that examined measurement properties of physical activity and sedentary behavior monitors. Project one identified the oxygen costs of four other care activities in seventeen adults. Pushing a wheelchair and pushing a stroller were identified as moderate-intensity activities. Minutes spent engaged in these activities contribute towards meeting the 2008 Physical Activity Guidelines. Project two identified the oxygen costs of common cleaning activities in sixteen adults. Mopping a floor was identified as moderate-intensity physical activity, while cleaning a kitchen and cleaning a bathtub were identified as light-intensity physical activity. Minutes spent engaged in mopping a floor contributes towards meeting the 2008 Physical Activity Guidelines. Project three evaluated the differences in number of minutes spent in activity levels when utilizing different epoch lengths in accelerometry. A shorter epoch length (1-second, 5-seconds) accumulated significantly more minutes of sedentary behaviors than a longer epoch length (60-seconds). The longer epoch length also identified significantly more time engaged in light-intensity activities than the shorter epoch lengths. Future research needs to account for epoch length selection when conducting physical activity and sedentary behavior assessment. Project four investigated the accuracy of four activity monitors in assessing activities that were either sedentary behaviors or light-intensity physical activities. The ActiGraph GT3X+ assessed the activities least accurately, while the SenseWear Armband and ActivPAL assessed activities equally accurately. The monitor used to assess physical activity and sedentary behaviors may influence the accuracy of the measurement of a construct.
ContributorsMeckes, Nathanael (Author) / Ainsworth, Barbara E (Thesis advisor) / Belyea, Michael (Committee member) / Buman, Matthew (Committee member) / Gaesser, Glenn (Committee member) / Wharton, Christopher (Christopher Mack), 1977- (Committee member) / Arizona State University (Publisher)
Created2012
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Validation of the Rapid Eating and Activity Assessment for diet quality measurement in young adult males

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The Rapid Eating and Activity Assessment for Participants Short Version (REAP-S), represents a method for rapid diet quality assessment, however, few studies have tested its validity. The Healthy Eating Index-2005 (HEI-2005) and the Diet Quality Index Revised (DQI-R) are tools that effectively assess diet quality, however, both are complex and…

The Rapid Eating and Activity Assessment for Participants Short Version (REAP-S), represents a method for rapid diet quality assessment, however, few studies have tested its validity. The Healthy Eating Index-2005 (HEI-2005) and the Diet Quality Index Revised (DQI-R) are tools that effectively assess diet quality, however, both are complex and time consuming. The objective of this study was to evaluate the validity of the REAP-S against the HEI-2005 and the DQI-R. Fifty males, 18 to 33 years of age, completed the REAP-S as well as a 24-hour diet recall. HEI-2005 and DQI-R scores were determined for each 24-hour recall. Scores from the REAP-S were evaluated against the HEI-2005 and DQI-R scores using Spearman rank order correlations and chi square. Modifications were also made to the original method of scoring the REAP-S to evaluate how the correlations transformed when certain questions were removed. The correlation coefficient for REAP-S and the HEI-2005 was 0.367 (P=0.009), and the correlation coefficient for REAP-S and the DQI-R was 0.323 (P=0.022). Chi square determined precision of the REAP-S to the HEI-2005 for overall diet quality at 64% and 62% for the DQI-R and REAP-S. Scores that were considered extreme (n=21) by the HEI-2005 (scores <40 and >60) had 76% precision with REAP-S. The correlation for the modified version of scoring REAP-S with the overall HEI-2005 and DQI-R were 0.395 (P=0.005) and 0.417 (P=0.003) respectively. Chi square statistics revealed the REAP-S accurately captured the diets of high quality versus low quality with 64% precision to the HEI-2005 and 62% of the DQI-R. When evaluating the modified REAP-S scores against the extreme HEI-2005 scores, precision increased to 81%. It appears the REAP-S is an acceptable tool to rapidly assess diet quality. It has a significant, moderate correlation to both the HEI-2005 and the DQI-R, with strong precision as well. Both correlation and precision is strengthened when values are compared to only the extreme scores of the HEI-2005; however, more research studies are needed to evaluate the validity of REAP-S in a more diverse population and to evaluate if changes to select questions can improve its accuracy in assessing diet quality.
ContributorsFawcett, Rachael (Author) / Johnston, Carol (Thesis advisor) / Mayol-Kreiser, Sandra (Committee member) / Wharton, Christopher (Christopher Mack), 1977- (Committee member) / Arizona State University (Publisher)
Created2012