Assessing Cardiorespiratory Fitness Without Performing Exercise Testing
Low cardiorespiratory fitness (CRF) is associated with increased risk of chronic diseases and mortality; however, CRF assessment is usually not performed in many healthcare settings. The purpose of this study is to extend previous work on a non–exercise test model to predict CRF from health indicato...
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| Veröffentlicht in: | American journal of preventive medicine 2005-10, Vol.29 (3), p.185-193 |
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| creator | Jurca, Radim Jackson, Andrew S. LaMonte, Michael J. Morrow, James R. Blair, Steven N. Wareham, Nicholas J. Haskell, William L. van Mechelen, Willem Church, Timothy S. Jakicic, John M. Laukkanen, Raija |
| description | Low cardiorespiratory fitness (CRF) is associated with increased risk of chronic diseases and mortality; however, CRF assessment is usually not performed in many healthcare settings. The purpose of this study is to extend previous work on a non–exercise test model to predict CRF from health indicators that are easily obtained.
Participants were men and women aged 20 to 70 years whose CRF level was quantified with a maximal or submaximal exercise test as part of the National Aeronautics and Space Administration/Johnson Space Center (NASA,
n=1863), Aerobics Center Longitudinal Study (ACLS,
n=46,190), or Allied Dunbar National Fitness Survey (ADNFS,
n=1706). Other variables included gender, age, body mass index, resting heart rate, and self-reported physical activity levels.
All variables used in the multiple linear regression models were independently related to the CRF in each of the study cohorts. The multiple correlation coefficients obtained within NASA, ACLS, and ADNFS participants, respectively, were 0.81, 0.77, and 0.76. The standard error of estimate (SEE) was 1.45, 1.50, and 1.97 metabolic equivalents (METs) (1 MET=3.5 ml O
2 uptake
·
kilograms of body mass
−1
·
minutes
−1), respectively, for the NASA, ACLS, and ADNFS regression models. All regression models demonstrated a high level of cross-validity (0.72 |
| doi_str_mv | 10.1016/j.amepre.2005.06.004 |
| format | Article |
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Participants were men and women aged 20 to 70 years whose CRF level was quantified with a maximal or submaximal exercise test as part of the National Aeronautics and Space Administration/Johnson Space Center (NASA,
n=1863), Aerobics Center Longitudinal Study (ACLS,
n=46,190), or Allied Dunbar National Fitness Survey (ADNFS,
n=1706). Other variables included gender, age, body mass index, resting heart rate, and self-reported physical activity levels.
All variables used in the multiple linear regression models were independently related to the CRF in each of the study cohorts. The multiple correlation coefficients obtained within NASA, ACLS, and ADNFS participants, respectively, were 0.81, 0.77, and 0.76. The standard error of estimate (SEE) was 1.45, 1.50, and 1.97 metabolic equivalents (METs) (1 MET=3.5 ml O
2 uptake
·
kilograms of body mass
−1
·
minutes
−1), respectively, for the NASA, ACLS, and ADNFS regression models. All regression models demonstrated a high level of cross-validity (0.72<R<0.80). The highest cross-validation coefficients were seen when the NASA regression model was applied to the ACLS and ADNFS cohorts (R=0.76 and R=0.75, respectively).
This study suggests that CRF may be accurately estimated in adults from a non–exercise test model including gender, age, body mass index, resting heart rate, and self-reported physical activity.</description><identifier>ISSN: 0749-3797</identifier><identifier>EISSN: 1873-2607</identifier><identifier>DOI: 10.1016/j.amepre.2005.06.004</identifier><identifier>PMID: 16168867</identifier><language>eng</language><publisher>Netherlands: Elsevier Inc</publisher><subject>Adult ; Aged ; Cardiovascular Physiological Phenomena ; Cohort Studies ; Exercise Test ; Female ; Humans ; Lung - physiology ; Male ; Middle Aged ; Physical Fitness - physiology ; Regression Analysis ; Respiration ; Texas</subject><ispartof>American journal of preventive medicine, 2005-10, Vol.29 (3), p.185-193</ispartof><rights>2005 American Journal of Preventive Medicine</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c503t-20f919f45c74b254e94532aa104300cbc40d1c1e0a4fbb36bd68d805624b7fff3</citedby><cites>FETCH-LOGICAL-c503t-20f919f45c74b254e94532aa104300cbc40d1c1e0a4fbb36bd68d805624b7fff3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S0749379705002151$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,776,780,3537,27901,27902,65306</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/16168867$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Jurca, Radim</creatorcontrib><creatorcontrib>Jackson, Andrew S.</creatorcontrib><creatorcontrib>LaMonte, Michael J.</creatorcontrib><creatorcontrib>Morrow, James R.</creatorcontrib><creatorcontrib>Blair, Steven N.</creatorcontrib><creatorcontrib>Wareham, Nicholas J.</creatorcontrib><creatorcontrib>Haskell, William L.</creatorcontrib><creatorcontrib>van Mechelen, Willem</creatorcontrib><creatorcontrib>Church, Timothy S.</creatorcontrib><creatorcontrib>Jakicic, John M.</creatorcontrib><creatorcontrib>Laukkanen, Raija</creatorcontrib><title>Assessing Cardiorespiratory Fitness Without Performing Exercise Testing</title><title>American journal of preventive medicine</title><addtitle>Am J Prev Med</addtitle><description>Low cardiorespiratory fitness (CRF) is associated with increased risk of chronic diseases and mortality; however, CRF assessment is usually not performed in many healthcare settings. The purpose of this study is to extend previous work on a non–exercise test model to predict CRF from health indicators that are easily obtained.
Participants were men and women aged 20 to 70 years whose CRF level was quantified with a maximal or submaximal exercise test as part of the National Aeronautics and Space Administration/Johnson Space Center (NASA,
n=1863), Aerobics Center Longitudinal Study (ACLS,
n=46,190), or Allied Dunbar National Fitness Survey (ADNFS,
n=1706). Other variables included gender, age, body mass index, resting heart rate, and self-reported physical activity levels.
All variables used in the multiple linear regression models were independently related to the CRF in each of the study cohorts. The multiple correlation coefficients obtained within NASA, ACLS, and ADNFS participants, respectively, were 0.81, 0.77, and 0.76. The standard error of estimate (SEE) was 1.45, 1.50, and 1.97 metabolic equivalents (METs) (1 MET=3.5 ml O
2 uptake
·
kilograms of body mass
−1
·
minutes
−1), respectively, for the NASA, ACLS, and ADNFS regression models. All regression models demonstrated a high level of cross-validity (0.72<R<0.80). The highest cross-validation coefficients were seen when the NASA regression model was applied to the ACLS and ADNFS cohorts (R=0.76 and R=0.75, respectively).
This study suggests that CRF may be accurately estimated in adults from a non–exercise test model including gender, age, body mass index, resting heart rate, and self-reported physical activity.</description><subject>Adult</subject><subject>Aged</subject><subject>Cardiovascular Physiological Phenomena</subject><subject>Cohort Studies</subject><subject>Exercise Test</subject><subject>Female</subject><subject>Humans</subject><subject>Lung - physiology</subject><subject>Male</subject><subject>Middle Aged</subject><subject>Physical Fitness - physiology</subject><subject>Regression Analysis</subject><subject>Respiration</subject><subject>Texas</subject><issn>0749-3797</issn><issn>1873-2607</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2005</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqFkE1Lw0AQhhdRbK3-A5GcvCXOZr-SiyClrUJBDxWPy2Yzq1uapu6mYv-9KS1409PAzPO-Aw8h1xQyClTeLTPT4CZglgOIDGQGwE_IkBaKpbkEdUqGoHiZMlWqAbmIcQkAqqDlORlQSWVRSDUks4cYMUa_fk_GJtS-DRg3PpiuDbtk6rt1f0zefPfRbrvkBYNrQ7OHJ98YrI-YLDB2_eKSnDmzinh1nCPyOp0sxo_p_Hn2NH6Yp1YA69IcXElLx4VVvMoFx5ILlhtDgTMAW1kONbUUwXBXVUxWtSzqAoTMeaWcc2xEbg-9m9B-bvvfuvHR4mpl1thuo5aFKBQV4l-QlpLlgrEe5AfQhjbGgE5vgm9M2GkKem9aL_XBtN6b1iB1b7qP3Rz7t1WD9W_oqLYH7g8A9jq-PAYdrce1xdoHtJ2uW__3hx933JGY</recordid><startdate>20051001</startdate><enddate>20051001</enddate><creator>Jurca, Radim</creator><creator>Jackson, Andrew S.</creator><creator>LaMonte, Michael J.</creator><creator>Morrow, James R.</creator><creator>Blair, Steven N.</creator><creator>Wareham, Nicholas J.</creator><creator>Haskell, William L.</creator><creator>van Mechelen, Willem</creator><creator>Church, Timothy S.</creator><creator>Jakicic, John M.</creator><creator>Laukkanen, Raija</creator><general>Elsevier Inc</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7TS</scope><scope>7X8</scope></search><sort><creationdate>20051001</creationdate><title>Assessing Cardiorespiratory Fitness Without Performing Exercise Testing</title><author>Jurca, Radim ; Jackson, Andrew S. ; LaMonte, Michael J. ; Morrow, James R. ; Blair, Steven N. ; Wareham, Nicholas J. ; Haskell, William L. ; van Mechelen, Willem ; Church, Timothy S. ; Jakicic, John M. ; Laukkanen, Raija</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c503t-20f919f45c74b254e94532aa104300cbc40d1c1e0a4fbb36bd68d805624b7fff3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2005</creationdate><topic>Adult</topic><topic>Aged</topic><topic>Cardiovascular Physiological Phenomena</topic><topic>Cohort Studies</topic><topic>Exercise Test</topic><topic>Female</topic><topic>Humans</topic><topic>Lung - physiology</topic><topic>Male</topic><topic>Middle Aged</topic><topic>Physical Fitness - physiology</topic><topic>Regression Analysis</topic><topic>Respiration</topic><topic>Texas</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Jurca, Radim</creatorcontrib><creatorcontrib>Jackson, Andrew S.</creatorcontrib><creatorcontrib>LaMonte, Michael J.</creatorcontrib><creatorcontrib>Morrow, James R.</creatorcontrib><creatorcontrib>Blair, Steven N.</creatorcontrib><creatorcontrib>Wareham, Nicholas J.</creatorcontrib><creatorcontrib>Haskell, William L.</creatorcontrib><creatorcontrib>van Mechelen, Willem</creatorcontrib><creatorcontrib>Church, Timothy S.</creatorcontrib><creatorcontrib>Jakicic, John M.</creatorcontrib><creatorcontrib>Laukkanen, Raija</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Physical Education Index</collection><collection>MEDLINE - Academic</collection><jtitle>American journal of preventive medicine</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Jurca, Radim</au><au>Jackson, Andrew S.</au><au>LaMonte, Michael J.</au><au>Morrow, James R.</au><au>Blair, Steven N.</au><au>Wareham, Nicholas J.</au><au>Haskell, William L.</au><au>van Mechelen, Willem</au><au>Church, Timothy S.</au><au>Jakicic, John M.</au><au>Laukkanen, Raija</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Assessing Cardiorespiratory Fitness Without Performing Exercise Testing</atitle><jtitle>American journal of preventive medicine</jtitle><addtitle>Am J Prev Med</addtitle><date>2005-10-01</date><risdate>2005</risdate><volume>29</volume><issue>3</issue><spage>185</spage><epage>193</epage><pages>185-193</pages><issn>0749-3797</issn><eissn>1873-2607</eissn><abstract>Low cardiorespiratory fitness (CRF) is associated with increased risk of chronic diseases and mortality; however, CRF assessment is usually not performed in many healthcare settings. The purpose of this study is to extend previous work on a non–exercise test model to predict CRF from health indicators that are easily obtained.
Participants were men and women aged 20 to 70 years whose CRF level was quantified with a maximal or submaximal exercise test as part of the National Aeronautics and Space Administration/Johnson Space Center (NASA,
n=1863), Aerobics Center Longitudinal Study (ACLS,
n=46,190), or Allied Dunbar National Fitness Survey (ADNFS,
n=1706). Other variables included gender, age, body mass index, resting heart rate, and self-reported physical activity levels.
All variables used in the multiple linear regression models were independently related to the CRF in each of the study cohorts. The multiple correlation coefficients obtained within NASA, ACLS, and ADNFS participants, respectively, were 0.81, 0.77, and 0.76. The standard error of estimate (SEE) was 1.45, 1.50, and 1.97 metabolic equivalents (METs) (1 MET=3.5 ml O
2 uptake
·
kilograms of body mass
−1
·
minutes
−1), respectively, for the NASA, ACLS, and ADNFS regression models. All regression models demonstrated a high level of cross-validity (0.72<R<0.80). The highest cross-validation coefficients were seen when the NASA regression model was applied to the ACLS and ADNFS cohorts (R=0.76 and R=0.75, respectively).
This study suggests that CRF may be accurately estimated in adults from a non–exercise test model including gender, age, body mass index, resting heart rate, and self-reported physical activity.</abstract><cop>Netherlands</cop><pub>Elsevier Inc</pub><pmid>16168867</pmid><doi>10.1016/j.amepre.2005.06.004</doi><tpages>9</tpages><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
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| ispartof | American journal of preventive medicine, 2005-10, Vol.29 (3), p.185-193 |
| issn | 0749-3797 1873-2607 |
| language | eng |
| recordid | cdi_proquest_miscellaneous_68587155 |
| source | MEDLINE; ScienceDirect Journals (5 years ago - present) |
| subjects | Adult Aged Cardiovascular Physiological Phenomena Cohort Studies Exercise Test Female Humans Lung - physiology Male Middle Aged Physical Fitness - physiology Regression Analysis Respiration Texas |
| title | Assessing Cardiorespiratory Fitness Without Performing Exercise Testing |
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