Adherence to heart rate-based intensity parameters predicts cardiovascular response to 12-weeks of aerobic cycling training in sedentary older adults
Year: 2026
Type: article
Study design: Clinical Trial
Abstract: Exercise improves cardiovascular health in older adults, yet variability in responsiveness remains. This study tested if prescribed exercise intensity adherence predicts individual differences in cardiovascular fitness gains following an intervention. From 2017 to 2022, nineteen sedentary older adults (69.78 ± 6.47 years) completed a 12-week aerobic cycling program in the Exercise Research Laboratory at the Atlanta VA Hospital. Participants trained 3× weekly, progressing from 20 to 45 min per session. Target intensity, expressed as percent heart rate reserve (HRR), increased from 50% to 80%. Cardiovascular fitness ( V ̇ O 2max ) was estimated pre- and post-intervention using the YMCA submaximal test. Attendance reflected the proportion of completed sessions. Intensity-based adherence was derived from the ratio of median HR to prescribed HR across sessions, modeled over time, and expressed as change from session 1 to 36. Estimated V ̇ O 2max increased significantly (21.51 ± 8.77 to 25.80 ± 9.42 ml/kg/min, p < .001). Attendance exceeded 90% and did not predict estimated V ̇ O 2max change, whereas HR adherence to prescribed intensity significantly predicted improvement (R 2 = 0.42, p = .01). Cardiovascular adaptations in older adults relate more strongly to prescribed HR adherence than attendance. Objective, trajectory-based adherence metrics may refine exercise prescriptions and improve prediction of individual responsiveness. • Cycling training improved VO2max by ~20% over 12 weeks. • Intensity adherence, not attendance, predicted VO2max gains in older adults. • Polynomial adherence trends explained 42% of VO2 variance.
Source: Preventive Medicine Reports
Language: English
Subfield: Complementary and alternative medicine
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $2,610
Awards: G199483855, G49566637
OpenAlex ID: W7125424876
