10.1177/1056789514562152

Vollständiger Abstract

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BackgroundCyclical hormonal fluctuations across the menstrual cycle influence physiological systems beyond the reproductive system, including cardiovascular, gastrointestinal, and neurological systems, and are associated with changes in menstrual symptoms. These changes may influence physical activity behaviours and exercise performance; however, evidence remains limited. Digital health applications enable analysis of these patterns at scale using real-world longitudinal data.ObjectivesInvestigate how step counts and energy expenditure change over the follicular and luteal phases of the menstrual cycle.DesignThis is a cohort study analysing step count and exercise log data recorded in the Flo app by women tracking their ovulation and menstrual cycle.MethodsThis study analysed step count and exercise log data from 5,703 Flo app users. Cycle phases were estimated using user-reported period start and end dates combined with ovulation test results. Differences in step count and energy expenditure were examined across the phases of the menstrual cycle.ResultsMedian step counts varied across cycle phases (p=0.003), with the lowest step counts during the mid-follicular phase and the highest counts during the late luteal phase. Linear mixed models showed step counts were higher in all other cycle phases compared with bleeding days, with the largest difference 1.8% higher in the late luteal phase compared with bleeding days. Mixed models revealed energy expenditure during gym workouts differed by cycle phase, with the early luteal phase showing a 5.2% greater energy expenditure compared to bleeding days.ConclusionWe found measurable but small effects of menstrual cycle phase on step counts and energy expenditure during gym workouts in a large group of Flo app users. While statistically significant, the small magnitude of effects by cycle phase on step counts and energy expenditure suggests the differences may have minimal clinical or practical relevance, though further research is needed.

Abstract: PubMed · Datensatz