Low resting metabolic rate in exercise-associated amenorrhea is not due to a reduced proportion of highly active metabolic tissue compartments

Abstract

Exercising women with menstrual disturbances frequently display a low resting metabolic rate (RMR) when RMR is expressed relative to body size or lean mass. However, normalizing RMR for body size or lean mass does not account for potential differences in the size of tissue compartments with varying metabolic activities. To explore whether the apparent RMR suppression in women with exercise-associated amenorrhea is a consequence of a lower proportion of highly active metabolic tissue compartments or the result of metabolic adaptations related to energy conservation at the tissue level, RMR and metabolic tissue compartments were compared among exercising women with amenorrhea (AMEN; n = 42) and exercising women with eumenorrheic, ovulatory menstrual cycles (OV; n = 37). RMR was measured using indirect calorimetry and predicted from the size of metabolic tissue compartments as measured by dual-energy X-ray absorptiometry (DEXA). Measured RMR was lower than DEXA-predicted RMR in AMEN (1,215 ± 31 vs. 1,327 ± 18 kcal/day, P < 0.001) but not in OV (1,284 ± 24 vs. 1,252 ± 17, P = 0.16), resulting in a lower ratio of measured to DEXA-predicted RMR in AMEN (91 ± 2%) vs. OV (103 ± 2%, P < 0.001). AMEN displayed proportionally more residual mass ( P < 0.001) and less adipose tissue ( P = 0.003) compared with OV. A lower ratio of measured to DXA-predicted RMR was associated with lower serum total triiodothyronine ( ρ = 0.38, P < 0.001) and leptin ( ρ = 0.32, P = 0.004). Our findings suggest that RMR suppression in this population is not the result of a reduced size of highly active metabolic tissue compartments but is due to metabolic and endocrine adaptations at the tissue level that are indicative of energy conservation.

Indices of Resting Metabolic Rate Accurately Reflect Energy Deficiency in Exercising Women

“…Numerous studies have documented the suppression of TT 3 in amenorrheic (De Souza et al, 2003;Laughlin & Yen, 1996;Scheid et al, 2009;Vanheest et al, 2014) and energy-and estrogen-deficient women Southmayd et al, 2019), as well as in an animal model where a significant decline in circulating TT 3 was coincident with the induction of amenorrhea (Williams et al, 2001). Our findings confirmed the previous report that associated DXA RMR ratio to TT 3 (Koehler et al, 2016), and further demonstrates that this association is also comparable to the Harris-Benedict and Cunningham ratios. Although a 0.90 RMR ratio cutoff, originally derived from the Harris-Benedict prediction equation (De Souza et al, 2007a, has been used with Cunningham 1980 and DXA prediction equations (Staal et al, 2018), no investigators have determined whether this universal cutoff value is suitable for all prediction equations.…”

“…Participants were scanned on a Lunar Prodigy DXA scanner (enCORE 2002 software, version 6.50.069; General Electric, Madison, WI; n = 87), Lunar iDXA scanner (enCORE 2008 software, version 12.10.113; General Electric; n = 117), or Hologic QDR4500W DXA scanner (Hologic, Bedford, MA; n = 13). Cross-calibration studies consistent with the guidelines of the International Society for Clinical Densitometry were performed to remove bias and have been previously described (Koehler et al, 2016). Using data from the DXA analyses, organ tissue mass of the brain, skeletal muscle, bone, adipose tissue, and residual mass were determined as outlined by Hayes et al (2002), using published tissue-specific metabolic rates to determine DXA-predicted RMR (Elia, 1992), and as previously described (Koehler et al, 2016).…”

“…RMR was assessed via indirect calorimetry using a ventilated hood (Sensor-Medics Vmax Series; CareFusion, Yorba Linda, CA) as previously described Scheid et al, 2009). Four prediction equations, commonly used in an exercising population, were utilized to estimate RMR: (a) Harris-Benedict equation (Harris & Benedict, 1918); (b) DXA equation (Hayes et al, 2002;Koehler et al, 2016); (c) Cunningham 1980 equation, which utilizes lean body mass (Cunningham, 1980); and (d) Cunningham 1991 equation, which utilizes fat-free mass (Cunningham, 1991).…”

“…Whether or not the use of lean body mass and fat-free mass interchangeably may impact the result of predicted RMR and RMR ratio is unknown. Most recently, dual-energy X-ray absorptiometry (DXA) modeling, based on tissue-specific metabolic rates (Gallagher et al, 1998;Hayes et al, 2002), may represent a unique and more accurate depiction of metabolic rate and has been applied to exercising women (Koehler et al, 2016). Because there are several equations in use for exercising women and as different prediction equations may provide variable estimates of metabolic rate (Staal et al, 2018), it is necessary to assess the ability of each ratio to predict energy deficiency and evaluate the appropriateness of the ratio ≤0.90 as an indicator of energy deficiency.…”

Characterizing the resting metabolic rate ratio in ovulatory exercising women over 12 months

“…Cross-calibration studies consistent with the guidelines of the ISCD were performed to remove bias, as previously described. 38 DXAderived organ tissue mass of the brain, skeletal muscle, bone, adipose tissue, residual mass, 39 and tissue-specific metabolic rates were used to calculate DXA-predicted RMR, 40 as previously described. 38…”