Sex is an important consideration in biomedical research. Efforts to expand sex inclusion have had some success, but females are still underrepresented in both animal and human biomedical research despite increasing evidence in support of sex-inclusive study design. Hesitancy to include female subjects is partially due to the hypothesis that ovarian rhythms increase female variability and weaken statistical power. We recently used continuous skin temperature data from wearable devices to test this hypothesis and found that the data did not support the hypothesis that females, cycling or not, reduce statistical power. However, ovarian rhythms are not the only timescale of change that might shape variability in human data. Additionally, whereas temperature is linked to endocrine and physiological systems, physical activity captured by wearables may be more related to behavioral patterns that exist independently of endogenous physiological rhythms, and so is worthy of investigation separate from temperature.Here we used minute-level metabolic equivalent task (MET) data spanning 206 days each from 596 individuals to explore physical activity (PA), focusing on comparing the scale of sex differences in variability of PA to the scale of differences in variability arising at the timescales of days, weeks, menstrual cycles, and decades of life. We report that females have lower intra-individual variability than males as a whole and the presence of menstrual cycles did not increase variability. PA patterns reflective of behavioral patterns were found on weekly time scales and across decades of life. The exclusion of either sex was not supported by our analysis.