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Predictors of discordance in self-report versus device-measured physical activity measurement
Authors:Jessica Gorzelitz  Paul E. Peppard  Kristen Malecki  Keith Gennuso  F. Javier Nieto  Lisa Cadmus-Bertram
Affiliation:1. Department of Kinesiology, University of Wisconsin-Madison, Madison;2. Department of Population Health Sciences, University of Wisconsin-Madison, Madison;3. University of Wisconsin Population Health Institute, Madison;4. College of Public Health and Health Sciences, Oregon State University, Corvallis
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.
Keywords:Accelerometry  Epidemiology  Methods  Population health  Physical activity assessment
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