Measurement of physical activity and sedentary behavior in breast cancer survivors
Background Breast cancer survivors’ self-perceived physical activity (PA) and sitting time (ST) may differ significantly from the general population and other survivor groups, so it is important that PA and ST measurement tools are compared within the breast cancer survivor population.
Objective To compare accelerometer and self-report estimates of PA and ST in breast cancer survivors.
Methods 414 breast cancer survivors (age, 56.8 years [SD, 9.2 years]; BMI, 26.2 kg/m2 [5.4 kg/m2]) wore an accelerometer for 7 consecutive days and completed a modified Godin Leisure-Time Exercise Questionnaire (GLTEQ), the International Physical Activity Questionnaire (IPAQ), and the Sitting Time Questionnaire (STQ) which all measured hours/minutes of activity/sitting per day. Mean differences and correlations of ST, light PA (LPA; ≤1.5 metabolic equivalents [METs]), and moderate and vigorous PA (MVPA; ≥3 METs) were compared using random-intercept mixed-effects regression models and the Spearman rank correlation coefficient (Spearman’s rho [rs], where rs = 1 means a perfect positive correlation, and rs = -1 means a perfect negative correlation).
Results Mean daily durations of MVPA were: accelerometer, 20.2 minutes; GLTEQ, 23.6 minutes (Pdiff = .02); and IPAQ, 87.4 minutes (Pdiff < .001). Correlations between accelerometer-estimated MVPA were moderate for the GLTEQ (rs = 0.56) and poor for the IPAQ (rs = 0.02). Mean daily durations of LPA were 239.5 minutes for the accelerometer and 15.4 minutes for the GLTEQ (Pdiff < .001); the measures were not correlated (rs = 0.004). Mean daily durations of ST were: accelerometer, 603.9 minutes; STQ, 611.8 minutes (Pdiff = 0.9); and IPAQ, 303.8 minutes (Pdiff < 0.001). Correlations with the accelerometer were fair (STQ: rs = 0.26; IPAQ: rs = 0.30). Differences in estimates varied by disease stage, age, presence of chronic conditions, and race.
Limitations Participants were predominantly white, highly educated, and high earners, which reduced generalizability.
Conclusions Congruency of measurement was dependent on tool, intensity of activity, and participant characteristics. Target outcome, implementation context, and population should be considered when choosing a measurement for physical activity or sitting time in breast cancer survivors.
Funding National Institute on Aging: #F31AG034025 (Dr Phillips), #AG020118 (Dr McAuley); National Cancer Institute: #K07CA196840 (Dr Phillips), #T32CA193193 (Dr Welch).†
Accepted for publication December 2, 2017
Correspondence whitney.welch@northwestern.edu
Disclosures The authors report no disclosures/conflicts of interest.
Citation JCSO 2018;16(1):e21-e29
†See Acknowledgment at end of article.
©2018 Frontline Medical Communications
doi https://doi.org/10.12788/jcso.0387
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Methods
Participants and procedures
This study consisted of a subsample of women who participated in a larger study whose findings have been reported elsewhere by Phillips and McAuley.27 In that study, breast cancer survivors (n = 1,631) were recruited nationally to participate in a 6-month prospective study on quality of life. Eligibility criteria included being aged 18 years or older, having had a diagnosis of breast cancer, being English speaking, and having access to the internet. Once consented to participate in the study, 500 women were randomly selected to wear the accelerometer.
Participants in this group were mailed an accelerometer, an activity log, instructions for use, and a self-addressed stamped envelope to return the monitor. They were asked to wear the accelerometer during all waking hours for 7 consecutive days of usual activity. They were also sent a secure link to complete 3 activity questionnaires online. The questionnaires were to be completed by the end of the 7-day monitoring period. Only women with 3 or more valid days of accelerometer data and complete data on variables of interest (n = 414) were included in the present analyses. All of the participants consented to the study procedures approved by the University of Illinois Institutional Review Board.
Measures
Demographics. The participants self-reported their age, level of education, height, and weight. Their body mass index (BMI; kg/m2) was estimated using the standard equation. They also self-reported their health and cancer history, detailing breast cancer disease stage, time since diagnosis, treatment type, and whether they had had a cancer recurrence. They were also asked to report whether they had ever been diagnosed (Yes/No) with 18 chronic conditions (eg, diabetes, arthritis).
,Godin Leisure-Time Exercise Questionnaire.16 The GLTEQ assessed participants’ weekly frequency and mean amount of time performing MVPA (moderate exercise, such as fast walking, combined with vigorous exercise, such as jogging), and LPA (light/mild exercise, eg, easy walking) during the previous 7 days. The mean daily duration (in minutes) for each intensity category (MVPA, LPA) was calculated using activity frequencies and the amount of time spent in each activity presented as minutes/day.
The International Physical Activity Questionnaire.14 The IPAQ evaluated participants’ physical activity of at least moderate intensity in 4 domains of everyday life: job-related physical activity, transportation, housework/caring for family, and leisure-time activity. Within each domain, participants were asked the number of days per week and time per day (hours and minutes) spent performing MVPA. To estimate sitting time, the questionnaire asks participants to report the total amount of time spent sitting per day in 2 conditions, during weekdays and during weekends. The present analysis averaged sitting time for a typical 7-day (5 week days, 2 weekend days) period. We multiplied reported minutes per day and frequency per week of each activity category (MVPA and ST) to calculate the mean number of minutes per day.29,30
Sitting Time Questionnaire.17,28 The STQ estimated the mean time (hours and minutes) participants spent sitting each day on weekdays and at weekends within 5 domains: while traveling to and from places, at work, watching television, using a computer at home, and at leisure, not including watching television (eg, visiting friends, movies, dining out). Mean minutes per day of ST were calculated using all sitting domains.
Actigraph accelerometer (model GT1M, Health One Technology, Fort Walton Beach, FL). The Actigraph GT1M is a reliable and objective measure of physical activity.31-33 Participants wore the monitor on the right hip for 7 consecutive days during all waking hours, except when bathing or swimming. Activity data was analyzed in 1-minute intervals. A valid day of accelerometer wear time was defined as ≥600 minutes with no more than 60 minutes of consecutive zero-values, with allowance of 2 minutes or fewer of observations <100 counts/minute within the nonwear interval.34 Each minute of wear time was classified according to intensity (counts/min) using the following cut-points:34 sedentary, <100 counts/min; LPA, 100-2,019 counts/min; and MVPA, ≥2,020 count/min. Mean daily durations (min/day) spent in each behavior were estimated by dividing the number of minutes in each category by the number of valid days.
Statistical analysis
All statistical analyses were completed in SPSS Statistics 23 (IBM, Chicago, IL). Descriptive statistics were used to define participant characteristics. Rank-order correlation between the methods was assessed using Spearman’s rho (rs) and results were interpreted as follows: rs = 0.10, small; 0.30, moderate; and 0.50, strong.35 Within each activity intensity group, we jointly modeled daily minutes of self-report and accelerometer data using a random-intercept mixed-effects regression model. Differences between measurement tools were assessed based on regression coefficients with accelerometer as the reference category. Finally, we did a post hoc analysis of leisure-time–only MVPA from the IPAQ to compare with other estimates of MVPA.
