RESUMO
BACKGROUND: Exercise intensity (eg, target heart rate [HR]) is a fundamental component of exercise prescription to elicit health benefits in cancer survivors. Despite the validity of chest-worn monitors, their feasibility in community and unsupervised exercise settings may be challenging. As wearable technology continues to improve, consumer-based wearable sensors may represent an accessible alternative to traditional monitoring, offering additional advantages. OBJECTIVE: The purpose of this study was to examine the agreement between the Polar H10 chest monitor and Fitbit Inspire HR for HR measurement in breast cancer survivors enrolled in the intervention arm of a randomized, pilot exercise trial. METHODS: Participants included breast cancer survivors (N=14; aged 38-72 years) randomized to a 12-week aerobic exercise program. This program consisted of three 60-minute, moderate-intensity walking sessions per week, either in small groups or one-on-one, facilitated by a certified exercise physiologist and held at local community fitness centers. As originally designed, the exercise prescription included 36 supervised sessions at a fitness center. However, due to the COVID-19 pandemic, the number of supervised sessions varied depending on whether participants enrolled before or after March 2020. During each exercise session, HR (in beats per minute) was concurrently measured via a Polar H10 chest monitor and a wrist-worn Fitbit Inspire HR at 5 stages: pre-exercise rest; midpoint of warm-up; midpoint of exercise session; midpoint of cool-down; and postexercise recovery. The exercise physiologist recorded the participant's HR from each device at the midpoint of each stage. HR agreement between the Polar H10 and Fitbit Inspire HR was assessed using Lin concordance correlation coefficient (rc) with a 95% CI. Lin rc ranges from 0 to 1.00, with 0 indicating no concordance and 1.00 indicating perfect concordance. Relative error rates were calculated to examine differences across exercise session stages. RESULTS: Data were available for 200 supervised sessions across the sample (session per participant: mean 13.33, SD 13.7). By exercise session stage, agreement between the Polar H10 monitor and the Fitbit was highest during pre-exercise seated rest (rc=0.76, 95% CI 0.70-0.81) and postexercise seated recovery (rc=0.89, 95% CI 0.86-0.92), followed by the midpoint of exercise (rc=0.63, 95% CI 0.55-0.70) and cool-down (rc=0.68, 95% CI 0.60-0.74). The agreement was lowest during warm-up (rc=0.39, 95% CI 0.27-0.49). Relative error rates ranged from -3.91% to 3.09% and were greatest during warm-up (relative error rate: mean -3.91, SD 11.92%). CONCLUSIONS: The Fitbit overestimated HR during peak exercise intensity, posing risks for overexercising, which may not be safe for breast cancer survivors' fitness levels. While the Fitbit Inspire HR may be used to estimate exercise HR, precautions are needed when considering participant safety and data interpretation. TRIAL REGISTRATION: Clinicaltrials.gov NCT03980626; https://clinicaltrials.gov/study/NCT03980626?term=NCT03980626&rank=1.
RESUMO
PURPOSE: Increasing evidence suggests rural breast cancer survivors (BCS) may experience greater burden in symptoms known to be associated with cancer-associated cognitive decline (CACD). Yet, little is known about CACD in rural BCS. This study (1) examined differences in cognitive function, moderate-to-vigorous physical activity (MVPA), and other CACD correlates and (2) tested the effects of MVPA on cognitive function in rural versus urban BCS. METHODS: Rural and urban BCS (N = 80), matched on age, education, and time since diagnosis from a larger study, completed cognitive tasks assessing processing speed (Trails-B, Mazes, Task-Switch) and working memory (spatial working memory) and questionnaires assessing subjective memory impairment (SMI), MVPA, and CACD correlates (i.e., sleep quality, fatigue, anxiety/depression). Some participants (n = 62) wore an accelerometer to objectively estimate MVPA. Multiple linear regression and multivariate analysis of covariance were used to test study aims. RESULTS: Rural BCS (n = 40, M = 61.1±8.4 years-old) performed significantly slower on Trails-B (p<0.01) compared with urban BCS (n = 40, M = 61.0±8.2 years-old) and engaged in less objectively-estimated daily MVPA (mean difference = 13.83±4.73 minutes; p = 0.01). No significant differences in SMI, self-reported MVPA, or CACD correlates were observed (all p>0.28). Regression models did not reveal a significant interaction between MVPA and cognitive performance (all p>0.1); however, estimated marginal means models indicated that the effect of MVPA on processing speed was evident only among rural BCS (Trails-B, p = 0.04; Mazes, p = 0.03). CONCLUSIONS: Findings suggest rural BCS may suffer greater CACD and engage in less MVPA. Additional research is warranted to further examine CACD and more effectively promote MVPA in rural BCS.
