3 research outputs found
Effect of exercise intensity on percent body fat determined by leg-to-leg and segmental bioelectrical impedance analyses in adults
Purpose: We examined the impact that cycle ergometry exercise had on percent body fat (% BF) estimates when assessed using either leg-to-leg or segmental bioelectrical impedance analysis (LBIA; SBIA) and whether the intensity of the exercise bout impacts the %BF magnitude of change. Method: Seventy-four college-aged adults participated in this study. Participants visited the laboratory on three separate occasions. Testing included two 30-min exercise sessions (70% HRmax and 85% HRmax) and a 30-min no-exercise session, which served as the control. Results: Following exercise, significant (p \u3c .05) reductions in mean %BF were observed when using LBIA (70% HRmax = 0.3%; 85% HRmax = 0.5%) and SBIA (70% HRmax = 0.8%; 85% HRmax = 1.4%). The mean %BF reductions were significantly (p \u3c .04) greater following exercise at the higher intensity for both analyzers. Conclusions: Our findings indicate that cycle exercise performed before LBIA and SBIA body composition assessment reduces mean %BF estimates. In addition, the %BF reductions were found to be larger at the higher end of the American College of Sports Medicine/American Heart Association recommended intensity range (85% HRmax) and when the SBIA analyzer was used to conduct the assessment. Copyright © AAHPERD
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A Systematic Framework to Rapidly Obtain Data on Patients with Cancer and COVID-19: CCC19 Governance, Protocol, and Quality Assurance
When the COVID-19 pandemic began, formal frameworks to collect data about affected patients were lacking. The COVID-19 and Cancer Consortium (CCC19) was formed to collect granular data on patients with cancer and COVID-19 at scale and as rapidly as possible. CCC19 has grown from five initial institutions to 125 institutions with >400 collaborators. More than 5,000 cases with complete baseline data have been accrued. Future directions include increased electronic health record integration for direct data ingestion, expansion to additional domestic and international sites, more intentional patient involvement, and granular analyses of still-unanswered questions related to cancer subtypes and treatments.
When the COVID-19 pandemic began, formal frameworks to collect data about affected patients were lacking. The COVID-19 and Cancer Consortium (CCC19) was formed to collect granular data on patients with cancer and COVID-19 at scale and as rapidly as possible. CCC19 has grown from five initial institutions to 125 institutions with >400 collaborators. More than 5,000 cases with complete baseline data have been accrued. Future directions include increased electronic health record integration for direct data ingestion, expansion to additional domestic and international sites, more intentional patient involvement, and granular analyses of still-unanswered questions related to cancer subtypes and treatments