Input of Sex Data Does Not Affect Metabolic Variables Returned from the COSMED K5 Unit During Exercise

There is a sex-data gap in sport and exercise, which results in an underrepresentation of female participants and increases the possibility of misgendering individuals who identify other than the female-male binary. A potential barrier to gender inclusivity could be that common exercise science equipment and software are limited to binary options for sex, excluding people who identify as gender minorities. PURPOSE: The purpose of this study was to evaluate whether sex data input into the COSMED K5 had a direct effect on metabolic outcome variables. METHODS: Seven adult participants (age = 29.6 ± 10.8 years, height = 172.6 ± 8.5 cm, body mass = 74.9 ± 12.8 kg) were fitted with the COSMED K5 and exercised for an overall duration of 20 minutes, divided into 2 five-minute walking (once with demographic sex as female, and once as male) and 2 five-minute running trials (once with demographic sex as female, and once as male). The order which sex was input into the demographic profile was randomly determined. A one-sided dependent t-test for each dependent variable was utilized to examine potential differences in input between the female and male sex conditions. P-values ≤ 0.05 were considered statistically significant. Cohen's d was used to calculate effect sizes, with negligible = 0.0-0.2, small = 0.2-0.49, medium = 0.5-0.79, and large = ≥ 0.8. RESULTS: Walking trials reported a mean relative VO2 of 13.3 ± 2.7 for females and 13.5 ± 2.6 for males (p = 0.49, d = 0.06), with a mean energy expenditure of 23.7 ± 6.1 kcal for females and 24.1 ± 6.7 kcal for males (p = 0.45, d = 0.04). The running trials revealed a mean relative VO2 of 31.0 ± 3.2 for females and 30.4 ± 3.5 for males (p = 0.47, d = 0.17), with a mean energy expenditure of 52.7 ± 8.1 kcal for females and 52.4 ± 7.8 kcal for males (p = 0.63, d = 0.04). There were no significant differences in metabolic variables between the input of sex during each exercise. CONCLUSIONS: Researchers should investigate other software and equipment that is not sex-dependent, develop considerations to be more inclusive, and employ a variety of different analyses to expand this area of research.