Original article
Predictors of discordance in self-report versus device-measured physical activity measurement

https://doi.org/10.1016/j.annepidem.2018.03.016Get rights and content

Highlights

  • Greater education was associated with less discordance between physical activity measures.

  • Body mass index was not an independent predictor for difference between measures.

  • Seventy-five percent of participants self-reported meeting federal physical activity guidelines.

  • When assessed by accelerometer, only 19% of participants met the guidelines.

Abstract

Purpose

Accurate measurement of free-living physical activity is challenging in population-based research, whether using device-based or reported methods. Our purpose was to identify demographic predictors of discordance between physical activity assessment methods and to determine how these predictors modify the discordance between device-based and reported physical activity measurement methods.

Methods

Three hundred forty-seven adults from the Survey of the Health of Wisconsin wore the ActiGraph accelerometer for 7 days and completed the Global Physical Activity Questionnaire. Multivariate linear regression was conducted to assess predictors of discordance including gender, education, body mass index, marital status, and other individual level characteristics in physical activity reporting.

Results

Seventy-seven percent of men and 72% of women self-reported meeting the U.S. Centers for Disease Control and Prevention guidelines for aerobic activity but when measured by accelerometer, only 21% of men and 17% of women met guidelines. Demographic characteristics that predicted discordance between methods in multivariate regression included greater educational attainment (P < .001) and partnered status (P = .003).

Conclusions

These varying levels of discordance imply that comparisons of self-reported activity among groups defined by (or substantially varying by) educational attainment or marital status should be done with considerable caution as observed differences may be due, in part, to systematic, differential measurement biases among groups.

Introduction

Physical activity is a key determinant of health via reduced chronic disease risk, increased longevity, and improved quality of life [1]. Per the U.S. Centers for Disease Control and Prevention, the recommended amount of aerobic physical activity for healthy adults is 150 minutes per week of moderate-intensity physical activity, or 75 minutes of vigorous-intensity physical activity, or a combination of both collected in bouts of 10 minutes or more [2]. The guidelines focus on moderate-to-vigorous intensity physical activity (MVPA) because most health benefits are reaped at these intensities [3]. Physical activity comprises a complex and heterogeneous set of behaviors, including intentional exercise, lifestyle activity (e.g., housework, caregiving), walking or biking for transportation, and activity performed as part of work. This broad range of behavioral contexts, many of which can occur multiple times per day or may be performed on an irregular schedule, hinders the accurate and comprehensive measurement of physical activity both in individuals and across populations.

Self-report measures are particularly well-suited for population-based measurement of physical activity due to low cost and ease of implementation but subject to substantial measurement error—particularly over-reporting—and especially with recall periods longer than a few days [4]. On the other hand, device-measured measures of physical activity (i.e., accelerometers) have been found to be more precise and accurate than self-report measures [5] but are less widely used in population-based research due to limitations including comparatively higher cost and challenges to capturing some nonambulatory forms of locomotion. The most common physical activity at the population level is walking, and accelerometers are highly accurate for ambulatory activities, including walking, but less accurate for certain activities such as biking, and generally not used during swimming. Thus, in the typical U.S. sample, discrepancies between reported and device-based methods of physical activity measurement likely reflect a substantial degree of self-report measurement error, as opposed to major underestimation from accelerometry. While completely reliable and valid physical activity assessment is not attainable outside of a laboratory, reasonably accurate physical activity assessment is needed in population-based and other research settings, particularly when considering new opportunities for intervention and prevention. To avoid misinterpretation, questionnaire-based physical activity is referred to as ‘reported' activity, where activity captured by the accelerometer is referred to as ‘device-measured’ in this manuscript [6].

Few studies, however, have examined predictors of within-person discordance between device-based and reported measures of activity, especially in general population-based studies. Dyrstad et al. compared the International Physical Activity questionnaire with an ActiGraph accelerometer, assessing both sedentary time and physical activity. Overall, authors found that participants reported more vigorous activity and less sedentary time than device-measured accelerometry [7]. In that sample, men reported 47% more MVPA on the International Physical Activity questionnaire than did women, yet there were no gender differences in MVPA via accelerometry. This study provided some of the first indications that the consistency between reporting methods may be influenced by demographic characteristics such as age, sex, body mass index (BMI), and educational attainment; however, it primarily used bivariate analyses such as correlations and absolute differences in reporting to determine the agreement between methods.

Determining the role of individual characteristics that differentially influence physical activity reporting by population subgroups could identify predictors that are prone to over- or under-reporting their physical activity. Consequently, the predictors could then be used to guide future physical activity estimation protocols for research and surveillance. This study aimed to [1] measure the extent of disagreement between self-report questionnaire and waist-worn accelerometry in a general population-based sample and [2] examine potential predictors of discordance between methods, focusing on demographic characteristics and body habitus, measured using BMI (kg/m2). We hypothesized that demographic characteristics would influence the amount of discordance between self-reported and device-measured activity from the accelerometer. Specifically, we expected that higher discordance would be observed among individuals with lower educational attainment, those with BMI ≥ 30.0 kg/m2, and those who were unmarried/not living with a partner. These specific individual factors were expected to independently predict discordance due to their previously demonstrated effects on other types of health outcomes. These aims were assessed using a population-based sample of adults living in Wisconsin.

Section snippets

Participants and recruitment

Initiated in 2008, the Survey of the Health of Wisconsin (SHOW) is a series of annual population health examination surveys with a stratified, random cluster sampling design [8]. A detailed summary of the SHOW methods has been previously published [8]. All SHOW participants have provided self-reported assessment of physical activity collected via personal interview; accelerometry was added in 2014. A total of 531 adults 18+ years old participated in 2014 with 100% completing physical activity

Demographics and physical activity descriptive results

Table 1 summarizes the distribution of predictor variables for the analytic sample, which includes participants who satisfactorily completed both the self-report and device-based components. Of the 531 adults who participated in the 2014 survey, 500 (94%) consented to participate to accelerometry and 347 (65%) had sufficient valid accelerometer wear time to be included in the analysis. Overall, men self-reported an average of 17.2 (SD = 19.7) hours of MVPA per week, whereas women reported 13.4

Discussion

This study presents new data regarding individual-level predictors of discordance between self-reported and accelerometer-measured physical activity data. In this large population-based sample of adults, there were much higher volumes of physical activity estimated via self-report compared to accelerometer. Approximately 75% of the sample self-reported meeting physical activity guidelines, but only 19% of those participants met guidelines when assessed via accelerometer. We found that obesity

Conclusions

This study adds important new information about physical activity measurement and the role of predictors in discordance across physical activity methods. Significant predictors of lower discordance include marriage and higher educational attainment. The present study shows that self-reported measures lead to an overestimation of physical activity, but that the discrepancy in reporting is not differential by BMI or by obesity status. Therefore, our study supports the important conclusion that

Acknowledgments

The authors would like to thank the SHOW administrative, field, and scientific staff, as well as all SHOW participants for their contributions to this study.

This research was supported by the Wisconsin Partnership Program PERC Award (233 PRJ 25DJ) and the National Institutes for Health (5ULRR025011, 1RC2HL101468, and 1K07CA178870).

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