The Effect of Sprint Interval Training on Body Composition of Postmenopausal Women

Yati N. Boutcher; Stephen H. Boutcher; Hye Y. Yoo; Jarrod D. Meerkin


Med Sci Sports Exerc. 2019;51(7):1413-1419. 

In This Article

Materials and Methods


Forty sedentary postmenopausal women (determined by self-reported cessation of menstruation) age between 47 to 59 yr with a body mass index (BMI) of between 25 and 35 kg·m−2 (≥23 kg·m−2 for women of Asian descent) were recruited, consented, and randomized into SIT (n = 20) or control (n = 20) groups. A recommended appropriate power in this type of research is 0.9. Thus, based on an effect size from our previous research,[7] sample sizes of 14 to 18 participants per group were estimated to provide a statistical power of 0.9 at an alpha of P < 0.05. Exclusion criteria included: taking medication that could interact negatively with exercise, nonnatural menopause (surgically induced), taking hormone replacement therapy, regularly exercising, and smoking. Before acceptance into the study a health history questionnaire was used to assess participants' medical history and a clearance letter from participants' general practitioner was required to confirm eligibility. A 7-d physical activity recall[17] was used to confirm a sedentary lifestyle and to estimate level of current physical activity. All participants were also required to complete a 3-d dietary form at preintervention and postintervention. This involved tabulating all foods consumed on three separate days consisting of two weekdays and one weekend day. The diets were analyzed using dietary analysis software (SERVE Nutrition Management Systems, Professional Edition, version 5.1.002, 2004, Australia). The preadmission interview included information about all procedures and requirements for the participant and informed consent was documented. This study was approved by the University of New South Wales, Australia Human Ethics committee. All procedures conformed to the standards of the Declaration of Helsinki.


The SIT group (n = 20) exercised three sessions a week for a total of 8 wk. Each session was conducted on a Monark Ergomedic 828E exercise bike and consisted of a 5-min warm-up of light pedaling at ~50 rpm, followed by 20 min of alternating 8-s sprints at near-maximal exertion and 12-s rest periods of light pedaling, and finally ending with a 5-min cool-down of light pedaling. The SIT load was set at 80% to 85% of each participant's peak HR with a pedal cadence between 100 and 125 rpm. Recovery was set at the same amount of resistance but at a pedal cadence of 50 rpm. Participants were instructed to keep their exercise intensity at a level which ensured their average exercise HR fell below their individual peak HR. Exercise intensity was increased when participant's average HR during SIT fell below their average HR recorded during the prior four exercise sessions. Each SIT session was supervised and HR was measured using a Polar Electro HR monitor. Participant's RPE, using Borg's scale,[18] was also recorded at 2-min intervals during SIT.


Anthropometric and resting measures. Height, weight, and BMI were initially collected at preadmission interview to confirm eligibility and were remeasured before intervention. Body mass index was calculated by dividing weight by height squared (kg·m−2). A three-lead electrocardiograph was used to determine resting HR, whereas blood pressure was assessed using an automatic arm-cuff blood pressure monitor (OMRON, Bannockburn, IL). Waist circumference was assessed at the naval using a measuring tape.

Lipid and glucose levels. Participants were instructed to fast for 10 h preintervention and postintervention, when 5 mL of venous blood from the antecubital vein was taken after at least 5 min of rest in an upright sitting position. Blood lipid profiles and glucose concentrations were immediately quantified from whole blood by automated enzymatic methods (Cholestech LDX, USA).

Body composition. Whole body dual-energy x-ray absorptiometry: A Hologic Horizon A (SN-300616M) (Hologic Inc., Bedford, MA) fan beam dual-energy x-ray absorptiometry (DXA) device was used for the study. A single trained operator completed all whole body scans, and analyzed the results, using the QDR system software for Windows v10 Hologic software APEX (Hologic). The operator was blinded regarding group allocation. Participants completed a single whole body scan. A QC procedure using the Hologic spine phantom was completed each morning before scanning of any participant. Every 3 months, a Hologic whole-body phantom was scanned to ensure there was no drift in whole-body values of lean mass and fat mass.

Whole-body composition: The Hologic whole-body scanning dimensions was 196 cm by 68 cm. The generous breadth of the Hologic scan table ensured adequate separation of the arms from the trunk in the whole body positioning. Total mass (kg), lean mass (kg), fat mass (kg) and fat percent was calculated for the whole body and for individual regions of interest. These whole body regions were the head, upper limbs, lower limbs, and trunk. Upon analysis, the software places a matrix over the body for regional analysis. The operator defines the placement of these lines: head (immediately below the mandible), trunk (enclosing the chest, midriff, and pelvis), the left and right upper limbs (the line is placed medial to the head of the humerus), and left and right legs (a line joins the outside of the thigh through to the middle of both legs by being placed through the femoral neck and lateral to the pubic ramus). Central fat, as a surrogate of visceral adipose tissue,[19] was auto generated by the scanning software and the placement of the visceral adipose tissue box was checked by the operator.

Aerobic fitness. A submaximal exercise test on an electronically braked cycle ergometer (Monark 319E, Stockholm, Sweden) was used to predict maximal oxygen uptake (V̇O2max) as an indicator of aerobic fitness. After a 5-min warm-up at 15 W, the load was slowly increased by 5 W every minute while the participant was instructed to maintain 60 rpm. The test was continued until participants reached 70% of their age-estimated maximum HR, calculated through the following equation:[20] maximal HR = 205.8 − 0.685 × age. Throughout the test participant's respiration gases were collected using a metabolic cart (TrueOne Model 2400; ParvoMedics Inc., Sandy, UT). Oxygen consumption (V̇O2) and carbon dioxide production (V̇CO2) were used to predict V̇O2max.[21] Participants received 10 min of familiarization with the metabolic cart and electronic bike before test initiation.

Statistical Analyses

Data were analyzed using IBM's Statistical Package for the Social Sciences (SPSS v25; IBM, USA). ANCOVA was used to determine if there were statistically significant differences in recorded variables. The pretest value for each variable was used as the covariate. Results were considered statistically significant when the P value was less than 0.05. Eta-squared (η2) was used to determine effect size, with values of 0.02, 0.13, and 0.26 and above being considered to be small, medium, and large effect sizes. Data are reported as mean and SD of the mean.