The purpose of this study was to develop a regression equation to predict VO2max based on non-exercise (N-EX) data. All participants (N = 100), aged 18-65 years old, successfully completed a maximal graded exercise test (GXT) to assess VO2max (mean ± SD; 39.96 mL∙kg-¹∙min&sup-1; ± 9.54 mL∙kg-¹∙min-¹). The N-EX data collected just before the maximal GXT included the participant's age, gender, body mass index (BMI), perceived functional ability (PFA) to walk, jog, or run given distances, and current physical activity (PA-R) level. Multiple linear regression generated the following N-EX prediction equation (R = .93, SEE = 3.45 mL∙kg-¹∙min-¹, %SEE = 8.62): VO2max (mL∙kg-¹∙min-¹) = 48.0730 + (6.1779 x gender) - (0.2463 x age) - (0.6186 x BMI) + (0.7115 x PFA) + (0.6709 x PA-R). Cross validation using PRESS (predicted residual sum of squares) statistics revealed minimal shrinkage (Rp = .91 and SEEp = 3.63 mL∙kg-¹∙min-¹); thus, this model should yield acceptable accuracy when applied to an independent sample of adults (aged 18-65) with a similar cardiorespiratory fitness level. Based on standardized β-weights the PFA variable (0.41) was the most effective at predicting VO2max followed by age (-0.34), gender (0.33), BMI (-0.27), and PA-R (0.16). This study provides a N-EX regression model that yields relatively accurate results and is a convenient way to predict VO2max in adult men and women.
","abstract_html":"<p>The purpose of this study was to develop a regression equation to predict VO2max based on non-exercise (N-EX) data. All participants (N = 100), aged 18-65 years old, successfully completed a maximal graded exercise test (GXT) to assess VO2max (mean ± SD; 39.96 mL∙kg-¹∙min&sup-1; ± 9.54 mL∙kg-¹∙min-¹). The N-EX data collected just before the maximal GXT included the participant's age, gender, body mass index (BMI), perceived functional ability (PFA) to walk, jog, or run given distances, and current physical activity (PA-R) level. Multiple linear regression generated the following N-EX prediction equation (R = .93, SEE = 3.45 mL∙kg-¹∙min-¹, %SEE = 8.62): VO2max (mL∙kg-¹∙min-¹) = 48.0730 + (6.1779 x gender) - (0.2463 x age) - (0.6186 x BMI) + (0.7115 x PFA) + (0.6709 x PA-R). Cross validation using PRESS (predicted residual sum of squares) statistics revealed minimal shrinkage (Rp = .91 and SEEp = 3.63 mL∙kg-¹∙min-¹); thus, this model should yield acceptable accuracy when applied to an independent sample of adults (aged 18-65) with a similar cardiorespiratory fitness level. Based on standardized β-weights the PFA variable (0.41) was the most effective at predicting VO2max followed by age (-0.34), gender (0.33), BMI (-0.27), and PA-R (0.16). This study provides a N-EX regression model that yields relatively accurate results and is a convenient way to predict VO2max in adult men and women.</p>","abstract_has_math":false,"creators":["Bradshaw, Danielle I."],"institution":"Brigham Young University - Provo","degree_name":"MS","degree_level":null,"degree_discipline":null,"degree_department":null,"school":null,"contributors":[],"advisors":[],"committee_chairs":[],"committee_members":[],"year":null,"date_issued":"","date_published":null,"updated_at":"2026-07-24T01:28:54Z","subjects":["exercise testing","cardiorespiratory fitness","predicting VO2max","VO2","non-exercise","regression model","non-exercise regression model","Exercise Science"],"languages":["English"],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://scholarsarchive.byu.edu/etd/1144","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:creator","label":"Author","values":["Bradshaw, Danielle I."]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date","label":"Dc Date","values":["2003-12-19T08:00:00Z"]},{"key":"dc:publisher","label":"Institution","values":["Brigham Young University - Provo"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]},{"key":"thesis:degree_name","label":"Degree Name","values":["MS"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["exercise testing","cardiorespiratory fitness","predicting VO2max","VO2","non-exercise","regression model","non-exercise regression model","Exercise Science"]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language","label":"Dc Language","values":["English"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://scholarsarchive.byu.edu/etd/1144","https://scholarsarchive.byu.edu/context/etd/article/2143/viewcontent/ETD_CISOPTR_79.pdf"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Life Sciences; Exercise Sciences","0;Physical Education
"]},{"key":"dc:description.abstract","label":"Abstract","values":["The purpose of this study was to develop a regression equation to predict VO2max based on non-exercise (N-EX) data. All participants (N = 100), aged 18-65 years old, successfully completed a maximal graded exercise test (GXT) to assess VO2max (mean ± SD; 39.96 mL∙kg-¹∙min&sup-1; ± 9.54 mL∙kg-¹∙min-¹). The N-EX data collected just before the maximal GXT included the participant's age, gender, body mass index (BMI), perceived functional ability (PFA) to walk, jog, or run given distances, and current physical activity (PA-R) level. Multiple linear regression generated the following N-EX prediction equation (R = .93, SEE = 3.45 mL∙kg-¹∙min-¹, %SEE = 8.62): VO2max (mL∙kg-¹∙min-¹) = 48.0730 + (6.1779 x gender) - (0.2463 x age) - (0.6186 x BMI) + (0.7115 x PFA) + (0.6709 x PA-R). Cross validation using PRESS (predicted residual sum of squares) statistics revealed minimal shrinkage (Rp = .91 and SEEp = 3.63 mL∙kg-¹∙min-¹); thus, this model should yield acceptable accuracy when applied to an independent sample of adults (aged 18-65) with a similar cardiorespiratory fitness level. Based on standardized β-weights the PFA variable (0.41) was the most effective at predicting VO2max followed by age (-0.34), gender (0.33), BMI (-0.27), and PA-R (0.16). This study provides a N-EX regression model that yields relatively accurate results and is a convenient way to predict VO2max in adult men and women.
"]},{"key":"dc:format","label":"Dc Format","values":["application:pdf"]},{"key":"dc:source","label":"Dc Source","values":["Brigham Young University - Provo"]},{"key":"dc:title","label":"Title","values":["An Accurate VO2max Non-exercise Regression Model for 18 to 65 Year Old Adults"]}]}],"canonical_facts":{"dc:creator":["Bradshaw, Danielle I."],"dc:date":["2003-12-19T08:00:00Z"],"dc:description":["Life Sciences; Exercise Sciences","0;Physical Education
"],"dc:description.abstract":["The purpose of this study was to develop a regression equation to predict VO2max based on non-exercise (N-EX) data. All participants (N = 100), aged 18-65 years old, successfully completed a maximal graded exercise test (GXT) to assess VO2max (mean ± SD; 39.96 mL∙kg-¹∙min&sup-1; ± 9.54 mL∙kg-¹∙min-¹). The N-EX data collected just before the maximal GXT included the participant's age, gender, body mass index (BMI), perceived functional ability (PFA) to walk, jog, or run given distances, and current physical activity (PA-R) level. Multiple linear regression generated the following N-EX prediction equation (R = .93, SEE = 3.45 mL∙kg-¹∙min-¹, %SEE = 8.62): VO2max (mL∙kg-¹∙min-¹) = 48.0730 + (6.1779 x gender) - (0.2463 x age) - (0.6186 x BMI) + (0.7115 x PFA) + (0.6709 x PA-R). Cross validation using PRESS (predicted residual sum of squares) statistics revealed minimal shrinkage (Rp = .91 and SEEp = 3.63 mL∙kg-¹∙min-¹); thus, this model should yield acceptable accuracy when applied to an independent sample of adults (aged 18-65) with a similar cardiorespiratory fitness level. Based on standardized β-weights the PFA variable (0.41) was the most effective at predicting VO2max followed by age (-0.34), gender (0.33), BMI (-0.27), and PA-R (0.16). This study provides a N-EX regression model that yields relatively accurate results and is a convenient way to predict VO2max in adult men and women.
"],"dc:format":["application:pdf"],"dc:identifier":["https://scholarsarchive.byu.edu/etd/1144","https://scholarsarchive.byu.edu/context/etd/article/2143/viewcontent/ETD_CISOPTR_79.pdf"],"dc:language":["English"],"dc:publisher":["Brigham Young University - Provo"],"dc:source":["Brigham Young University - Provo"],"dc:subject":["exercise testing","cardiorespiratory fitness","predicting VO2max","VO2","non-exercise","regression model","non-exercise regression model","Exercise Science"],"dc:title":["An Accurate VO2max Non-exercise Regression Model for 18 to 65 Year Old Adults"],"dc:type":["Thesis"],"thesis:degree_name":["MS"]},"updated_at":"2026-07-24T01:28:54Z"}