Sex differences in the cardiovascular consequences of the inspiratory muscle metaboreflex.
Joshua R SmithStephanie P KurtiShane M HammerAndrew M AlexanderKaylin D DidierStephanie P KurtiThomas J BarstowCraig A HarmsPublished in: American journal of physiology. Regulatory, integrative and comparative physiology (2016)
It is currently unknown whether sex differences exist in the cardiovascular consequences of the inspiratory muscle metaboreflex. We hypothesized that the activation of the inspiratory muscle metaboreflex will lead to less of an increase in mean arterial pressure (MAP) and limb vascular resistance (LVR) and less of a decrease in limb blood flow (Q̇L) in women compared with men. Twenty healthy men (n = 10, 23 ± 2 yr) and women (n = 10, 22 ± 3 yr) were recruited for this study. Subjects performed inspiratory resistive breathing tasks (IRBTs) at 2% or 65% of their maximal inspiratory mouth pressure (PIMAX). During the IRBTs, the breathing frequency was 20 breaths/min with a 50% duty cycle. At rest and during the IRBTs, MAP was measured via automated oscillometry, Q̇L was measured via Doppler ultrasound, and LVR was calculated. EMG was recorded on the leg to ensure no muscle contraction occurred. The 65% IRBT led to attenuated increases (P < 0.01) from baseline in women compared with men for MAP (W: 7.3 ± 2.0 mmHg; M: 11.1 ± 5.0 mmHg) and LVR (W: 17.7% ± 14.0%; M: 47.9 ± 21.0%), as well as less of a decrease (P < 0.01) in Q̇L (W: -7.5 ± 9.9%; M: -23.3 ± 10.2%). These sex differences in MAP, Q̇L, and LVR were still present in a subset of subjects matched for PIMAX The 2% IRBT resulted in no significant changes in MAP, Q̇L, or LVR across time or between men and women. These data indicate premenopausal women exhibit an attenuated inspiratory muscle metaboreflex compared with age-matched men.
Keyphrases
- polycystic ovary syndrome
- blood flow
- skeletal muscle
- high density
- pregnancy outcomes
- middle aged
- breast cancer risk
- cervical cancer screening
- insulin resistance
- magnetic resonance imaging
- deep learning
- type diabetes
- electronic health record
- adipose tissue
- heart rate
- postmenopausal women
- blood pressure
- contrast enhanced ultrasound