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Published on: March 7, 2019
Sex Differences in the Variability of Physical Activity Measurements Across Multiple Timescales Recorded by a
Kristin J Varner1, Lauryn Keeler Bruce2,3, Severine Soltani3
1Shu Chien-Gene Lay Department of Bioengineering, University of California San Diego, La Jolla, CA, United States.
Background:
A substantially lower proportion of female individuals participate in sufficient daily activity compared to male individuals despite the known health benefits of exercise. Investment in female sports and exercise medicine research may help close this gap; however, female individuals are underrepresented in this research. Hesitancy to include female participants is partly due to assumptions that biological rhythms driven by menstrual cycles and occurring on the timescale of approximately 28 days increase intraindividual biological variability and weaken statistical power. An analysis of continuous skin temperature data measured using a commercial wearable device found that temperature cycles indicative of menstrual cycles did not substantially increase variability in female individuals' skin temperature. In this study, we explore physical activity (PA) data as a variable more related to behavior, whereas temperature is more reflective of physiological changes.
Objective:
We aimed to determine whether intraindividual variability of PA is affected by biological sex, and if so, whether having menstrual cycles (as indicated by temperature rhythms) contributes to increased female intraindividual PA variability. We then sought to compare the effect of sex and menstrual cycles on PA variability to the effect of PA rhythms on the timescales of days and weeks and to the effect of nonrhythmic temporal structure in PA on the timescale of decades of life (age).
Methods:
We used minute-level metabolic equivalent of task data collected using a wearable device across a 206-day study period for each of 596 individuals as an index of PA to assess the magnitudes of variability in PA accounted for by biological sex and temporal structure on different timescales. Intraindividual variability in PA was represented by the consecutive disparity index.
Results:
Female individuals (regardless of whether they had menstrual cycles) demonstrated lower intraindividual variability in PA than male individuals (Kruskal-Wallis H=29.51; P<.001). Furthermore, individuals with menstrual cycles did not have greater intraindividual variability than those without menstrual cycles (Kruskal-Wallis H=0.54; P=.46). PA rhythms differed at the weekly timescale: individuals with increased or decreased PA on weekends had larger intraindividual variability (Kruskal-Wallis H=10.13; P=.001). In addition, intraindividual variability differed by decade of life, with older age groups tending to have less variability in PA (Kruskal-Wallis H=40.55; P<.001; Bonferroni-corrected significance threshold for 15 comparisons: P=.003). A generalized additive model predicting the consecutive disparity index of 24-hour metabolic equivalent of task sums (intraindividual variability of PA) showed that sex, age, and weekly rhythm accounted for only 11% of the population variability in intraindividual PA variability.
Conclusions:
The exclusion of people from PA research based on their biological sex, age, the presence of menstrual cycles, or the presence of weekly rhythms in PA is not supported by our analysis.
