The purpose of this study was to develop a multiple linear regression model to predict treadmill VO2max scores using both exercise and nonexercise data. One hundred five college-aged participants (53 male, 52 female, mean age 23.5 ± 2.8 yrs) successfully completed a submaximal cycle ergometer test and a maximal graded exercise test (GXT) on a motorized treadmill. The submaximal cycle protocol required participants to achieve a steady-state heart rate (HR) equal to at least 70% of age-predicted maximum HR (220-age), while the maximal treadmill GXT required participants to exercise to volitional fatigue. Relevant submaximal cycle ergometer test data included a mean (± SD) ending steady-state HR and ending workrate equal to 164.2 ± 13.0 and 115.3 ± 27.0, respectively. Relevant nonexercise data included a mean (± SD) body mass (kg), perceived functional ability [PFA] score, and physical activity rating [PA-R] score of 74.2 ± 15.1, 15.7 ± 4.3, and 4.7 ± 2.1, respectively. Multiple linear regression was used to generate the following prediction of cardiorespiratory fitness (R = 0.91, SEE = 3.36 ml∙kg-¹∙min-¹): VO2max = 54.513 + 9.752 (gender, 1 = male, 0 = female) − 0.297 (body mass, kg) + 0.739 (PFA, 2-26) + 0.077 (work rate, watts) − 0.072 (steady-state HR). Each predictor variable was statistically significant (p < .05) with beta weights for gender, body mass, PFA, exercise workrate, and steady-state HR equal to 0.594, -0.544, 0.388, 0.305, and -0.116, respectively. The predicted residual sums of squares (PRESS) statistics reflected minimal shrinkage (RPRESS = 0.90, SEEPRESS = 3.56 ml∙kg-¹∙min-¹) for the multiple linear regression model. In summary, the submaximal cycle ergometer protocol and accompanying prediction model yield relatively accurate VO2max estimates in healthy college-aged participants using both exercise and nonexercise data.

Maximal oxygen consumption (VO2max) is considered by many to be the best overall measure of an individual's cardiovascular health. Collecting the measurement, however, requires subjecting an individual to prolonged periods of intense exercise until their maximal level, the point at which their body uses no additional oxygen from the air despite increased exercise intensity, is reached. Collecting VO2max data also requires expensive equipment and great subject discomfort to get accurate results. Because of this inherent difficulty, it is often avoided despite its usefulness. In this research, we propose a set of Bayesian hierarchical models to predict VO2max levels in adolescents, ages 12 through 17, using less extreme measurements. Two models are developed separately, one that uses submaximal exercise data and one that uses physical fitness questionnaire data. The best submaximal model was found to include age, gender, BMI, heart rate, rate of perceived exertion, treadmill miles per hour, and an interaction between age and heart rate. The second model, designed for those with physical limitations, uses age, gender, BMI, and two separate questionnaire results measuring physical activity levels and functional ability levels, as well as an interaction between the physical activity level score and gender. Both models use separate model variances for males and females.

The purpose of this study was to develop a personalized step test and a valid regression model that used non-exercise data and data collected during the step test to estimate VO2max in males and females 18 to 30 years of age. All participants (N= 80) successfully completed a step test with the starting step rate and step height being determined by the self-reported perceived functional ability (PFA) score and participant's height, respectively. All participants completed a maximal graded exercise test (GXT) to measure VO2max. Multiple linear regression analysis yielded the following equation (R = 0.90, SEE = 3.43 mL/kg/min): 45.938 + 9.253(G) - 0.140(KG) + 0.670(PFA) + 0.429(FSR) - 0.149(45sRHR) to predict VO2max (mL/kg/min) where: G is gender (0=female;1=male), KG is body mass in kg, PFA is the sum of the two PFA questions, FSR is the final step rate (step-ups/min), and 45sRHR is the recovery heart rate 45 seconds following the conclusion of the step test. Each independent variable was significant (p < 0.05) in predicting VO2max and the resulting regression equation accounted for roughly 83% (R2=0.8281) of the shared variance of measured VO2max. Based on the standardized B-weights, gender (0.606) explained the largest proportion of variance in VO2max values followed by PFA (0.315), body mass (-0.256), FSR (-0.248), and the 45sRHR (-0.238). The cross validation statistics (RPRESS = 0.88, SEEPRESS = 3.57 (mL/kg/min-1) show minimal shrinkage in the accuracy of the regression model. This study presents a relatively accurate model to predict VO2max from a submaximal step test that is convenient, easy to administer, and individualized.

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Bakgrund: Atleter och idrottare har olika förutsättningar när det kommer till prestation beroende på kroppsammansättning och fysiska kvaliteter. Att bygga muskler, träna styrka eller löpträna är olika träningsformer för att utveckla olika kvaliteter som kan vara olika viktiga i olika idrotter. Syfte: Syftet med denna studie var att undersöka skillnader i utvalda fysiska kvaliteter hos styrketränande och löpare Metod: Detta var en tvärsnittsstudie med strategiskt urval av två grupper, en löpare (n=6) och en styrketränare (n=12). Båda gruppernas fysik analyserades med ett kroppsammansättningstest. Styrkan och fysisk fitness testades genom ett handgripstest och ett VO2max test för att få fram värden av gruppens fysiska kvalitéter. Gruppernas fysiska kvaliteter ställdes sedan mot varandra. Resultat: Löpargruppen hade signifikant högre VO2max än styrketränargruppen. I övrigt fanns det inga signifikanta skillnader. Konklusion: VO2max visade sig vara högre bland löpare än hos styrketränande vilket går i linje med tidigare forskning.

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Syfte och frågeställningar Syftet med denna studie var att undersöka vilka fysiologiska effekter sex veckors högintensiv intervallträning (HIIT) på löpband med hyperoxi (&gt;20,94  % syre) samt med normoxi (normal rumsluft) hade under kontrollerade former. De frågeställningar som hjälpte att besvara syftet var: (1) Hur förändras VO2max efter sex veckors högintensiv träning? (2) Hur förändras prestationen efter sex veckors högintensiv träning? (3) Hur påverkas löpekonomin av sex veckors HIIT? (4) Vilka fysiologiska effekter gav hyperoxiträning?   Metod I studien deltog initialt åtta manliga vältränade löpare varav fem stycken fullföljde studien. Karaktäristiken för de fem försökspersonerna (FP) var: ålder (år) 27,6 ± 5,8, längd (cm)180,9 ± 5,0, vikt (kg) 68,6 ± 6,2, årsbästa 10 km (mm:ss) 33:44 ± 01:11 och VO2max (ml/kg/min) 69,0 ± 2,3. FP delades in i test- och kontrollgrupp och studien var utformat som en single-blind. Under en sex veckors träningsperiod tränade FP två gånger per vecka under kontrollerade former i laboratoriemiljö på löpband. Träningen bestod av HIIT i 3-6 st x 6 min arbete med 4 min vila. Hyperoxigruppen fick tillgång till intermittent extra syre genom Oxelerate. Normoxigruppen fick normal rumsluft administrerad genom samma apparatur. Det gjordes tester innan och efter träningsperioden som bestod av ett submaximalt test för att fastställa laktattröskel och löpekonomi, samt ett maximalt syreupptagningstest där även prestationen mättes.   Resultat De signifikanta (P &lt;0,05) resultat studien kunde visa på var att prestationen förbättrades för alla FP efter sex veckors HIIT (414,6 ± 85,8 till 460,6 ± 80,4 sekunder). Maxlaktatet blev signifikant högre hos hyperoxigruppen (17,7 %) och signifikant lägre hos normoxigruppen (-19,1 %).   Slutsats HIIT gav en signifikant ökad prestation för alla FP. Hyperoxi hade bara effekt på maxlaktat. Löpekonomin och VO2max var oförändrad efter sex veckors HIIT. / <p>Uppsatsen tilldelades stipendiemedel ur Överste och Fru Adolf Johnssons fond för HT 2014.</p>

O objetivo deste estudo foi comparar indicadores ergoespirométricos entre um grupo de idosos não-treinados (GINT) e o grupo de idosos treinados (GIT) em corridas de longa distância e a associação com a qualidade de vida. Uma amostra de 46 indivíduos idosos, dos quais 27 (idade = 73,1 ± 4,3 anos) estavam engajados em treinamento para corridas de longa distância e 19 (idade = 73,5 ± 6,4 anos) idosos que não praticavam exercício físico regular. Todos foram submetidos à avaliação cardiorrespiratória e metabólica, utilizando se analisador metabólico de gases (CPX/D, MedGraphics®, EUA) acoplado a eletrocardiógrafo (HeartWere®, 6.4, BRA), ambos os sistemas computadorizados. A determinação da capacidade física máxima foi verificada em esteira rolante (Inbramed®, ATL10200, BRA) utilizando se protocolo escalonado contínuo (1,2 km.h-1 a cada dois minutos) e inclinação fixa de 1%. Os seguintes resultados verificados foram: No segundo limiar ventilatório (VT2) [GINT vs. GIT]: FC (bpm) [69,4 ± 9,9 vs. 65,4 ± 6,8; p <0,05]; RQ [1,03 ± 0,03 vs.1,01 ± 0,03; p <0,05]; PO2 (mL/bpm) [11,3 ± 2,4 vs.14.4 ± 2,8; p <0,05]. No pico do esforço: VO2max (mL/kg/min) [27 ± 5,4 vs. 39,3 ± 5,6; p <0,05], TT (min) [9,6 ± 2,9 vs. 16,4 ± 2,7; p <0,05] e velocidade de corrida (km.h-1) [9,7 ± 2,5 vs. 13,3 ± 2,5; p <0,05]. Para medir a qualidade de vida foi utilizado o questionário WHOQOL. WHOQOL pontos [GINT vs. GIT: [70 ± 5 versus 71 ± 6] Avaliou-se o uso de medicamentos de diferentes grupos farmacológicos através de entrevistas e análise de pedidos médicos. Concluindo, a capacidade de desempenho cardiorrespiratório do GIT foi significativamente maior do que o GINT. No entanto, a qualidade de vida não foi diferente entre os dois grupos. Houve diferença na proporção de medicamentos utilizados entre os grupos. O GIT aparece com maior incidência no uso de Antiarrítmicos, Antiinflamatórios e Relaxantes Musculares. Ao contrário, o GINT apresentou maior uso de Hipoglicemiantes e Anti-Coagulantes. A maior utilização de antiinflamatórios e analgésicos pelo GIT pode ser devido ao fato de que os corredores têm maior prevalência de lesão muscular. Já a maior utilização de Hipoglicemiantes e Anti-Coagulantes pelo GINT, demonstra a falta de proteção cardiovascular pelo sedentarismo / The main purpose of this study was to compare ergoespirometric indicators among a group of elderly untrained (GEU) and a group of elderly old trained (GET) in long-distance race and the association with quality of life. Twenty seven (age = 73.1 ± 4.3 years) were engaged in training for distance running and 19 (age = 73.5 ± 6.4 years) older adults who did not practice regular physical exercise. All were underwent a cardiopulmonary exercise test evaluation. To this end we used a gas explorer (CPX/D, breathby breath Medgraphics®, Saint Paul, MN, USA) coupled to an electrocardiograph (HeartWere®, 6.4, BRA). Both systems were computerized. The determination of the maximum physical capacity was assessed on a treadmill (Inbramed ®, ATL-10200, BRA) using incremental protocol (1.2 km.h-1every two minutes) and a fixed inclination of 1%. The following results were observed: In second ventilatory threshold (VT2) [GEU vs. GET]: HR (bpm) [69.4 ± 9.9 vs. 65.4 ± 6.8; p <0.05], RQ [1.03 ± 0.03 vs.1.01 ± 0.03; p <0.05]; PO2 (mL/bpm) [11.3 ±2.4 vs.14.4 ± 2.8, p <0.05]. At peak effort: VO2max (mL/kg/min) [27 ± 5.4 vs. 39.3 ± 5.6; p <0.05], TT (min) [9.6 ± 2.9 vs. 16.4 ± 2.7; p <0.05] and running speed (km.h-1) [9.7 ± 2.5 vs. 13.3 ± 2.5; p <0.05]. To measure quality of life we used the WHOQOL. WHOQOL points [GEU vs. GET: [70 ± 5 vs. 71 ± 6] evaluated the use of drugs from different pharmacological groups through interviews and medical applications. In conclusion, the cardiorespiratory capacity of the GET was significantly higher than the GEU. However, the quality of life was not different between the two groups. Differences in the proportion of medicines used by the groups. GET appears with a higher incidence in antiarrhythmics, anti-inflammatory and muscle relaxants. Instead, the GEU showed greater use of hypoglycemic and anti-coagulants. The increased use of antiinflammatory and muscle relaxants effects by the GET may be due to the fact that runners have a higher prevalence of muscle damage. Instead, the increased use of hypoglycemic and anti-coagulants by GEU, demonstrates the lack of cardiovascular protection by physical inactivity