Francesca Battista, Marco Vecchiato, Kiril Chernis, Sara Faggian, Federica Duregon, Nicola Borasio, Sara Ortolan, Giacomo Pucci, Andrea Ermolao, Daniel Neunhaeuserer
{"title":"Determinants of Longitudinal Changes in Exercise Blood Pressure in a Population of Young Athletes: The Role of BMI.","authors":"Francesca Battista, Marco Vecchiato, Kiril Chernis, Sara Faggian, Federica Duregon, Nicola Borasio, Sara Ortolan, Giacomo Pucci, Andrea Ermolao, Daniel Neunhaeuserer","doi":"10.3390/jcdd12020074","DOIUrl":null,"url":null,"abstract":"<p><strong>Aim: </strong>Higher exercise blood pressure in adults correlates with many cardiometabolic markers. The aim of this study was to investigate the main determinants of longitudinal variations in exercise blood pressure in young athletes.</p><p><strong>Methods: </strong>A longitudinal retrospective study was conducted on adolescent athletes who underwent at least two sport-related pre-participation screening visits, including exercise testing with a standardized incremental ramp protocol on treadmill. Blood pressure was assessed at rest (SBP<sub>rest</sub>), at the 3rd minute of exercise (SBP<sub>3min</sub>), and at peak exercise (SBP<sub>peak</sub>). Predictors of blood pressure response (i.e., respective changes vs. baseline (Δ)) were determined by multivariate regression models after adjustment for age, sex, follow-up duration, related baseline SBP values, characteristics of sport, and ΔBMI.</p><p><strong>Results: </strong>A total of 351 young athletes (mean age at baseline 13 ± 2 years, 54% boys, average follow-up duration 3.4 ± 2.2 years) were enrolled. BMI increased by 1.5 ± 1.8 kg/m<sup>2</sup> (<i>p</i> < 0.001) during follow-up. At baseline, mean SBP<sub>rest</sub> was 103 ± 14 mmHg, mean SBP<sub>3min</sub> 124 ± 18 mmHg, and mean SBPpeak 154 ± 23 mmHg. A significant between-visit increase in SBP<sub>rest</sub> (ΔSBP<sub>rest</sub> 7.0 ± 17.4 mmHg; <i>p</i> < 0.001), ΔSBP<sub>3min</sub> (4.8 ± 11 mmHg, <i>p</i> < 0.001), and ΔSBP<sub>peak</sub> (11.7 ± 24 mmHg, <i>p</i> < 0.001) was observed. ΔSBP<sub>3min</sub> was significantly predicted by male sex (<i>p</i> < 0.01), baseline BMI (<i>p</i> < 0.01), ΔBMI (<i>p</i> < 0.01), and number of practiced sports (<i>p</i> < 0.05), whereas ΔSBP<sub>peak</sub> was positively predicted by male gender (<i>p</i> < 0.01), baseline BMI (<i>p</i> < 0.05), and ΔBMI (<i>p</i> < 0.01) and negatively by baseline resting heart rate (<i>p</i> < 0.01). In a logistic regression model, ΔBMI was the only independent determinant of passing from a lower to an upper quartile of SBP<sub>3min</sub> (<i>p</i> < 0.001), while ΔBMI and male sex were independent determinants of moving to a higher quartile of SBP<sub>peak</sub> (<i>p</i> < 0.001).</p><p><strong>Conclusions: </strong>Increase in BMI during development and male sex are independent determinants of the increase in exercise blood pressure, both at light and maximal intensity, in a population of adolescent athletes.</p>","PeriodicalId":15197,"journal":{"name":"Journal of Cardiovascular Development and Disease","volume":"12 2","pages":""},"PeriodicalIF":2.4000,"publicationDate":"2025-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11856185/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Cardiovascular Development and Disease","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.3390/jcdd12020074","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CARDIAC & CARDIOVASCULAR SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
Aim: Higher exercise blood pressure in adults correlates with many cardiometabolic markers. The aim of this study was to investigate the main determinants of longitudinal variations in exercise blood pressure in young athletes.
Methods: A longitudinal retrospective study was conducted on adolescent athletes who underwent at least two sport-related pre-participation screening visits, including exercise testing with a standardized incremental ramp protocol on treadmill. Blood pressure was assessed at rest (SBPrest), at the 3rd minute of exercise (SBP3min), and at peak exercise (SBPpeak). Predictors of blood pressure response (i.e., respective changes vs. baseline (Δ)) were determined by multivariate regression models after adjustment for age, sex, follow-up duration, related baseline SBP values, characteristics of sport, and ΔBMI.
Results: A total of 351 young athletes (mean age at baseline 13 ± 2 years, 54% boys, average follow-up duration 3.4 ± 2.2 years) were enrolled. BMI increased by 1.5 ± 1.8 kg/m2 (p < 0.001) during follow-up. At baseline, mean SBPrest was 103 ± 14 mmHg, mean SBP3min 124 ± 18 mmHg, and mean SBPpeak 154 ± 23 mmHg. A significant between-visit increase in SBPrest (ΔSBPrest 7.0 ± 17.4 mmHg; p < 0.001), ΔSBP3min (4.8 ± 11 mmHg, p < 0.001), and ΔSBPpeak (11.7 ± 24 mmHg, p < 0.001) was observed. ΔSBP3min was significantly predicted by male sex (p < 0.01), baseline BMI (p < 0.01), ΔBMI (p < 0.01), and number of practiced sports (p < 0.05), whereas ΔSBPpeak was positively predicted by male gender (p < 0.01), baseline BMI (p < 0.05), and ΔBMI (p < 0.01) and negatively by baseline resting heart rate (p < 0.01). In a logistic regression model, ΔBMI was the only independent determinant of passing from a lower to an upper quartile of SBP3min (p < 0.001), while ΔBMI and male sex were independent determinants of moving to a higher quartile of SBPpeak (p < 0.001).
Conclusions: Increase in BMI during development and male sex are independent determinants of the increase in exercise blood pressure, both at light and maximal intensity, in a population of adolescent athletes.