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Meta-Analysis
. 2020 Jul 13;15(7):e0236025.
doi: 10.1371/journal.pone.0236025. eCollection 2020.

Effect of menstrual cycle on resting metabolism: A systematic review and meta-analysis

Melissa J Benton  1 , Andrea M Hutchins  2 , J Jay Dawes  3
Affiliations
Meta-Analysis

Effect of menstrual cycle on resting metabolism: A systematic review and meta-analysis

Melissa J Benton et al. PLoS One. .

Abstract

Background: The need to control for the potential influence of menstrual cycle phase on resting metabolism (RMR) places a burden on research participants who must self-report onset of menstruation and researchers who must schedule metabolic testing accordingly.

Purpose: To systematically review and analyze existing research to determine the effect of menstrual cycle on RMR.

Methods: We searched PubMed, CINAHL, MEDLINE, SPORTDiscus, and Scopus databases using the search terms "menstrual cycle and metabolic rate" and "menstrual cycle and energy expenditure." Eligibility criteria were English language, single-group repeated measures design, and RMR as either a primary or secondary outcome. Risk of bias was assessed based on study sample, measurement, and control of confounders. Differences between the follicular and luteal phases of the menstrual cycle were analyzed using the standardized mean difference in effect size.

Results: Thirty English-language studies published between 1930 and December 2019 were included in the systematic review, and 26 studies involving 318 women were included in the meta-analysis. Overall, there was a small but significant effect favoring increased RMR in the luteal phase (ES = 0.33; 95% CI = 0.17, 0.49, p < 0.001).

Discussion: Limitations include risk of bias regarding measurement of both menstrual cycle and RMR. Sample sizes were small and studies did not report control of potential confounders. Sub-group analysis demonstrated that in more recent studies published since 2000, the effect of menstrual phase was reduced and not statistically significant (ES = 0.23; 95% CI = -0.00, 0.47; p = 0.055). Until larger and better designed studies are available, based on our current findings, researchers should be aware of the potential confounding influence of the menstrual cycle and control for it by testing consistently in one phase of the cycle when measuring RMR in pre-menopausal women.

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Flow diagram of selection process based on PRISMA guidelines.
Fig 2
Fig 2. Quality assessment: Risk of bias in individual studies.
Fig 3
Fig 3. Forest plot of effect sizes for all 26 studies included in the meta-analysis.
Studies are listed by first author and year of publication. The overall effect (ES = 0.33) was calculated using a random effects (RE) model and favors an increase in RMR during the luteal phase compared to the follicular phase. (ns) = non-smokers; (s) = smokers; (sd) = standard diet.
Fig 4
Fig 4. Funnel plot of effect sizes for all studies included in the meta-analysis.
Egger’s test is non-significant (p = 0.721), indicating low risk of publication bias.
Fig 5
Fig 5. Forrest plot of sub-group analysis of studies with samples of more than 10 participants.
(ns) = non-smokers.
Fig 6
Fig 6. Forrest plot of sub-group analysis of studies published in 2000 and after.
(ns) = non-smokers; (s) = smokers; (sd) = standard diet.
See this image and copyright information in PMC

References

    1. Ravussin E, Lillioja S, Anderson TE, Christin L, Bogardus C. Determinants of 24-hour energy expenditure in man. Methods and results using a respiratory chamber. J Clin Invest. 1986;78(6):1568–78. 10.1172/JCI112749 - DOI - PMC - PubMed
    1. Hume DJ, Yokum S, Stice E. Low energy intake plus low energy expenditure (low energy flux), not energy surfeit, predicts future body fat gain. Am J Clin Nutr. 2016;103(6):1389–96. 10.3945/ajcn.115.127753 - DOI - PMC - PubMed
    1. Lam YY, Redman LM, Smith SR, Bray GA, Greenway FL, Johannsen D, et al. Determinants of sedentary 24-h energy expenditure: equations for energy prescription and adjustment in a respiratory chamber. Am J Clin Nutr. 2014;99(4):834–42. 10.3945/ajcn.113.079566 - DOI - PMC - PubMed
    1. Smith DA, Dollman J, Withers RT, Brinkman M, Keeves JP, Clark DG. Relationship between maximum aerobic power and resting metabolic rate in young adult women. J Appl Physiol (1985). 1997;82(1):156–63. - PubMed
    1. Binzen CA, Swan PD, Manore MM. Postexercise oxygen consumption and substrate use after resistance exercise in women. Med Sci Sports Exerc. 2001;33(6):932–8. 10.1097/00005768-200106000-00012 - DOI - PubMed