Associations between Measures of Adolescent Physical Activity and zBMI
Background: Physical activity (PA) is a potential target for obesity intervention. Various measures are used to assess PA, but relationships with BMI are inconsistent across assessment methods. The purpose of this study was to assess the relationships among PA assessment methods and their relationsh...
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Veröffentlicht in: | Obesity (Silver Spring, Md.) Md.), 2021-12, Vol.29, p.62-63 |
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description | Background: Physical activity (PA) is a potential target for obesity intervention. Various measures are used to assess PA, but relationships with BMI are inconsistent across assessment methods. The purpose of this study was to assess the relationships among PA assessment methods and their relationships with adolescent zBMI. Methods: We conducted a secondary data analysis in 177 adolescents who had multiple assessments over a 2 year period. Physical activity assessments were conducted over a 1-week period 1) previous 24-hr PA recall (PAR) 2) 1-wk of wrist based Actigraphy 3) selfreport via International Physical Activity Questionnaire- Short Form (IPAQ-SF). We used Pearson-correlation and linear regression to test the hypotheses that 1) methods of PA assessment will be weakly correlated with one another and 2) that objective PA measurement (accelerometer) will be more strongly associated with adolescent zBMI than subjective methods. Results: zBMI was weakly, inversely associated with 24hr PAR in both unadjusted (n = 177, r = -0.17, p = 0.021) and adjusted (n = 142, B = -0.00005, p = 0.014) models. Average step count derived from Actigraphy was weakly correlated with IPAQ-S assessment of average walking min per day (r = .24, p = 0.049) and overall average PA minutes per day (r = .26, p = 0.033), but not other PA intensities. Conclusions: Our findings suggest that actigraphy and IPAQ-SF PA assessments are similar in estimation of overall PA time, but not PA intensity. Some of these inconsistencies may stem from limited validity and reliability of self-report PA questionnaires among adolescents and biases of accelerometer data due to issues of wearability and under-estimation of specific PA activities (such as biking and swimming). The 24-hr PAR may be a more useful and less burdensome tool for obtaining adolescent PA data that is significantly associated with adolescent weight status. |
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Various measures are used to assess PA, but relationships with BMI are inconsistent across assessment methods. The purpose of this study was to assess the relationships among PA assessment methods and their relationships with adolescent zBMI. Methods: We conducted a secondary data analysis in 177 adolescents who had multiple assessments over a 2 year period. Physical activity assessments were conducted over a 1-week period 1) previous 24-hr PA recall (PAR) 2) 1-wk of wrist based Actigraphy 3) selfreport via International Physical Activity Questionnaire- Short Form (IPAQ-SF). We used Pearson-correlation and linear regression to test the hypotheses that 1) methods of PA assessment will be weakly correlated with one another and 2) that objective PA measurement (accelerometer) will be more strongly associated with adolescent zBMI than subjective methods. Results: zBMI was weakly, inversely associated with 24hr PAR in both unadjusted (n = 177, r = -0.17, p = 0.021) and adjusted (n = 142, B = -0.00005, p = 0.014) models. Average step count derived from Actigraphy was weakly correlated with IPAQ-S assessment of average walking min per day (r = .24, p = 0.049) and overall average PA minutes per day (r = .26, p = 0.033), but not other PA intensities. Conclusions: Our findings suggest that actigraphy and IPAQ-SF PA assessments are similar in estimation of overall PA time, but not PA intensity. Some of these inconsistencies may stem from limited validity and reliability of self-report PA questionnaires among adolescents and biases of accelerometer data due to issues of wearability and under-estimation of specific PA activities (such as biking and swimming). The 24-hr PAR may be a more useful and less burdensome tool for obtaining adolescent PA data that is significantly associated with adolescent weight status.</description><identifier>ISSN: 1930-7381</identifier><identifier>EISSN: 1930-739X</identifier><language>eng</language><publisher>Silver Spring: Blackwell Publishing Ltd</publisher><subject>Exercise ; Teenagers</subject><ispartof>Obesity (Silver Spring, Md.), 2021-12, Vol.29, p.62-63</ispartof><rights>Copyright Blackwell Publishing Ltd. Dec 2021</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780</link.rule.ids></links><search><creatorcontrib>Ziegler, Amanda</creatorcontrib><creatorcontrib>Hatzinger, Lori</creatorcontrib><creatorcontrib>Mansouri, Tegan</creatorcontrib><creatorcontrib>Barich, Rachel</creatorcontrib><creatorcontrib>Temple, Jennifer</creatorcontrib><title>Associations between Measures of Adolescent Physical Activity and zBMI</title><title>Obesity (Silver Spring, Md.)</title><description>Background: Physical activity (PA) is a potential target for obesity intervention. Various measures are used to assess PA, but relationships with BMI are inconsistent across assessment methods. The purpose of this study was to assess the relationships among PA assessment methods and their relationships with adolescent zBMI. Methods: We conducted a secondary data analysis in 177 adolescents who had multiple assessments over a 2 year period. Physical activity assessments were conducted over a 1-week period 1) previous 24-hr PA recall (PAR) 2) 1-wk of wrist based Actigraphy 3) selfreport via International Physical Activity Questionnaire- Short Form (IPAQ-SF). We used Pearson-correlation and linear regression to test the hypotheses that 1) methods of PA assessment will be weakly correlated with one another and 2) that objective PA measurement (accelerometer) will be more strongly associated with adolescent zBMI than subjective methods. Results: zBMI was weakly, inversely associated with 24hr PAR in both unadjusted (n = 177, r = -0.17, p = 0.021) and adjusted (n = 142, B = -0.00005, p = 0.014) models. Average step count derived from Actigraphy was weakly correlated with IPAQ-S assessment of average walking min per day (r = .24, p = 0.049) and overall average PA minutes per day (r = .26, p = 0.033), but not other PA intensities. Conclusions: Our findings suggest that actigraphy and IPAQ-SF PA assessments are similar in estimation of overall PA time, but not PA intensity. Some of these inconsistencies may stem from limited validity and reliability of self-report PA questionnaires among adolescents and biases of accelerometer data due to issues of wearability and under-estimation of specific PA activities (such as biking and swimming). The 24-hr PAR may be a more useful and less burdensome tool for obtaining adolescent PA data that is significantly associated with adolescent weight status.</description><subject>Exercise</subject><subject>Teenagers</subject><issn>1930-7381</issn><issn>1930-739X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><recordid>eNqNir0KwjAYAIMoWH_eIeBcSBpt7FjFokPBwcGtxPQrppRE-6VKfXodxNnpDu4GJOCJYKEUyXn48zUfkwlizdgyZisekCxFdNoob5xFegH_BLA0B4VdC0hdRdPSNYAarKfHa49Gq4am2puH8T1VtqSvTX6YkVGlGoT5l1OyyHan7T68te7eAfqidl1rP6mIYi4jJrkU4r_rDdcAPIA</recordid><startdate>20211201</startdate><enddate>20211201</enddate><creator>Ziegler, Amanda</creator><creator>Hatzinger, Lori</creator><creator>Mansouri, Tegan</creator><creator>Barich, Rachel</creator><creator>Temple, Jennifer</creator><general>Blackwell Publishing Ltd</general><scope>K9.</scope></search><sort><creationdate>20211201</creationdate><title>Associations between Measures of Adolescent Physical Activity and zBMI</title><author>Ziegler, Amanda ; Hatzinger, Lori ; Mansouri, Tegan ; Barich, Rachel ; Temple, Jennifer</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-proquest_journals_26172071733</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Exercise</topic><topic>Teenagers</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ziegler, Amanda</creatorcontrib><creatorcontrib>Hatzinger, Lori</creatorcontrib><creatorcontrib>Mansouri, Tegan</creatorcontrib><creatorcontrib>Barich, Rachel</creatorcontrib><creatorcontrib>Temple, Jennifer</creatorcontrib><collection>ProQuest Health & Medical Complete (Alumni)</collection><jtitle>Obesity (Silver Spring, Md.)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Ziegler, Amanda</au><au>Hatzinger, Lori</au><au>Mansouri, Tegan</au><au>Barich, Rachel</au><au>Temple, Jennifer</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Associations between Measures of Adolescent Physical Activity and zBMI</atitle><jtitle>Obesity (Silver Spring, Md.)</jtitle><date>2021-12-01</date><risdate>2021</risdate><volume>29</volume><spage>62</spage><epage>63</epage><pages>62-63</pages><issn>1930-7381</issn><eissn>1930-739X</eissn><abstract>Background: Physical activity (PA) is a potential target for obesity intervention. Various measures are used to assess PA, but relationships with BMI are inconsistent across assessment methods. The purpose of this study was to assess the relationships among PA assessment methods and their relationships with adolescent zBMI. Methods: We conducted a secondary data analysis in 177 adolescents who had multiple assessments over a 2 year period. Physical activity assessments were conducted over a 1-week period 1) previous 24-hr PA recall (PAR) 2) 1-wk of wrist based Actigraphy 3) selfreport via International Physical Activity Questionnaire- Short Form (IPAQ-SF). We used Pearson-correlation and linear regression to test the hypotheses that 1) methods of PA assessment will be weakly correlated with one another and 2) that objective PA measurement (accelerometer) will be more strongly associated with adolescent zBMI than subjective methods. Results: zBMI was weakly, inversely associated with 24hr PAR in both unadjusted (n = 177, r = -0.17, p = 0.021) and adjusted (n = 142, B = -0.00005, p = 0.014) models. Average step count derived from Actigraphy was weakly correlated with IPAQ-S assessment of average walking min per day (r = .24, p = 0.049) and overall average PA minutes per day (r = .26, p = 0.033), but not other PA intensities. Conclusions: Our findings suggest that actigraphy and IPAQ-SF PA assessments are similar in estimation of overall PA time, but not PA intensity. Some of these inconsistencies may stem from limited validity and reliability of self-report PA questionnaires among adolescents and biases of accelerometer data due to issues of wearability and under-estimation of specific PA activities (such as biking and swimming). The 24-hr PAR may be a more useful and less burdensome tool for obtaining adolescent PA data that is significantly associated with adolescent weight status.</abstract><cop>Silver Spring</cop><pub>Blackwell Publishing Ltd</pub></addata></record> |
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title | Associations between Measures of Adolescent Physical Activity and zBMI |
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