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Measuring severe obesity in pediatrics using body mass index-derived metrics from the Centers for Disease Control and Prevention and World Health Organization: a secondary analysis of CANadian Pediatric Weight management Registry (CANPWR) data
To examine the (i) relationships between various body mass index (BMI)-derived metrics for measuring severe obesity (SO) over time based the Centers for Disease Control and Prevention (CDC) and World Health Organization (WHO) references and (ii) ability of these metrics to discriminate children and...
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Published in: | European journal of pediatrics 2023-08, Vol.182 (8), p.3679-3690 |
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creator | Ball, Geoff D. C. Sharma, Atul K. Moore, Sarah A. Metzger, Daniel L. Klein, Doug Morrison, Katherine M. |
description | To examine the
(i)
relationships between various body mass index (BMI)-derived metrics for measuring severe obesity (SO) over time based the Centers for Disease Control and Prevention (CDC) and World Health Organization (WHO) references and
(ii)
ability of these metrics to discriminate children and adolescents based on the presence of cardiometabolic risk factors. In this cohort study completed from 2013 to 2021, we examined data from 3- to 18-year-olds enrolled in the CANadian Pediatric Weight management Registry. Anthropometric data were used to create nine BMI-derived metrics based on the CDC and WHO references. Cardiometabolic risk factors were examined, including dysglycemia, dyslipidemia, and elevated blood pressure. Analyses included Pearson correlations, intraclass correlation coefficients (ICC), and receiver operator characteristic area-under-the-curve (ROC AUC). Our sample included 1,288 participants (n = 666 [52%] girls; n = 874 [68%] white). The prevalence of SO varied from 60–67%, depending on the definition. Most BMI-derived metrics were positively and significantly related to one another (r = 0.45–1.00); ICCs revealed high tracking (0.90–0.94). ROC AUC analyses showed CDC and WHO metrics had a modest ability to discriminate the presence of cardiometabolic risk factors, which improved slightly with increasing numbers of risk factors. Overall, most BMI-derived metrics rated poorly in identifying presence of cardiometabolic risk factors.
Conclusion
: CDC BMI percent of the 95
th
percentile and WHO BMIz performed similarly as measures of SO, although neither showed particularly impressive discrimination. They appear to be interchangeable in clinical care and research in pediatrics, but there is a need for a universal standard. WHO BMIz may be useful for clinicians and researchers from countries that recommend using the WHO growth reference.
What is Known:
• Severe obesity in pediatrics is a global health issue.
• Few reports have evaluated body mass index (BMI)-derived metrics based on the World Health Organization growth reference.
What is New:
• Our analyses showed that the Centers for Disease Control and Prevention BMI percent of the 95
th
percentile and World Health Organization (WHO) BMI z-score (BMIz) performed similarly as measures of severe obesity in pediatrics.
• WHO BMIz should be a useful metric to measure severe obesity for clinicians and researchers from countries that recommend using the WHO growth reference. |
doi_str_mv | 10.1007/s00431-023-05039-4 |
format | article |
fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_2822377845</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>2822377845</sourcerecordid><originalsourceid>FETCH-LOGICAL-c419t-7048e485d438c2992c0b0372c889c99476be4c27c2d27f86d7e1b49bbc0975bd3</originalsourceid><addsrcrecordid>eNp9kk1vEzEQhlcIRD_gD3BAI3EphwXb68S73KrwUaRCowqU48prTxJXu3ZqeyvSv80fYNK0gDhwsj3zzDvj0VsULzh7wxlTbxNjsuIlE1XJJqxqSvmoOOSyEiVnavr4r_tBcZTSFaOihtdPi4NKiankdXVY_PyCOo3R-RUkvMGIEDpMLm_BedigdTpHZxKMaYd0wW5h0ClR1uKP0mJ0N2hhwD21jGGAvEaYoc8YKRAivHeJelAs-BxDD9pbmEdq5rML_u65CLG3cIa6z2u4iCvt3a3eZd-BprlM8FbHLaG63yaXICxhdvpV03Qe5g9DwgLdap1pPq9XOJA8XOLKpUyVJ4TPF5evweqsnxVPlrpP-Pz-PC6-f_zwbXZWnl98-jw7PS-N5E0uFZM1ynpiZVUb0TTCsI7R5kxdN6ZppJp2KI1QRlihlvXUKuSdbLrOsEZNOlsdFyd73U0M1yOm3A4uGex77TGMqRW1EJVStZwQ-uof9CqMkb67oyZKKsW4IkrsKRNDShGX7Sa6gTbTctbuLNHuLdGSJdo7S7SSil7eS4_dgPZ3yYMHCKj2QNrsfIDxT-__yP4C5MHFSA</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2857477017</pqid></control><display><type>article</type><title>Measuring severe obesity in pediatrics using body mass index-derived metrics from the Centers for Disease Control and Prevention and World Health Organization: a secondary analysis of CANadian Pediatric Weight management Registry (CANPWR) data</title><source>Springer Nature</source><creator>Ball, Geoff D. C. ; Sharma, Atul K. ; Moore, Sarah A. ; Metzger, Daniel L. ; Klein, Doug ; Morrison, Katherine M.</creator><creatorcontrib>Ball, Geoff D. C. ; Sharma, Atul K. ; Moore, Sarah A. ; Metzger, Daniel L. ; Klein, Doug ; Morrison, Katherine M. ; CANadian Pediatric Weight management Registry (CANPWR) Investigators ; on behalf of the CANadian Pediatric Weight management Registry (CANPWR) Investigators</creatorcontrib><description>To examine the
(i)
relationships between various body mass index (BMI)-derived metrics for measuring severe obesity (SO) over time based the Centers for Disease Control and Prevention (CDC) and World Health Organization (WHO) references and
(ii)
ability of these metrics to discriminate children and adolescents based on the presence of cardiometabolic risk factors. In this cohort study completed from 2013 to 2021, we examined data from 3- to 18-year-olds enrolled in the CANadian Pediatric Weight management Registry. Anthropometric data were used to create nine BMI-derived metrics based on the CDC and WHO references. Cardiometabolic risk factors were examined, including dysglycemia, dyslipidemia, and elevated blood pressure. Analyses included Pearson correlations, intraclass correlation coefficients (ICC), and receiver operator characteristic area-under-the-curve (ROC AUC). Our sample included 1,288 participants (n = 666 [52%] girls; n = 874 [68%] white). The prevalence of SO varied from 60–67%, depending on the definition. Most BMI-derived metrics were positively and significantly related to one another (r = 0.45–1.00); ICCs revealed high tracking (0.90–0.94). ROC AUC analyses showed CDC and WHO metrics had a modest ability to discriminate the presence of cardiometabolic risk factors, which improved slightly with increasing numbers of risk factors. Overall, most BMI-derived metrics rated poorly in identifying presence of cardiometabolic risk factors.
Conclusion
: CDC BMI percent of the 95
th
percentile and WHO BMIz performed similarly as measures of SO, although neither showed particularly impressive discrimination. They appear to be interchangeable in clinical care and research in pediatrics, but there is a need for a universal standard. WHO BMIz may be useful for clinicians and researchers from countries that recommend using the WHO growth reference.
What is Known:
• Severe obesity in pediatrics is a global health issue.
• Few reports have evaluated body mass index (BMI)-derived metrics based on the World Health Organization growth reference.
What is New:
• Our analyses showed that the Centers for Disease Control and Prevention BMI percent of the 95
th
percentile and World Health Organization (WHO) BMI z-score (BMIz) performed similarly as measures of severe obesity in pediatrics.
• WHO BMIz should be a useful metric to measure severe obesity for clinicians and researchers from countries that recommend using the WHO growth reference.</description><identifier>ISSN: 1432-1076</identifier><identifier>ISSN: 0340-6199</identifier><identifier>EISSN: 1432-1076</identifier><identifier>DOI: 10.1007/s00431-023-05039-4</identifier><identifier>PMID: 37264183</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer Berlin Heidelberg</publisher><subject>Blood pressure ; Body mass index ; Body measurements ; Disease control ; Disease prevention ; Dyslipidemia ; Medicine ; Medicine & Public Health ; Obesity ; Pediatrics ; Public health ; Risk factors ; Weight control</subject><ispartof>European journal of pediatrics, 2023-08, Vol.182 (8), p.3679-3690</ispartof><rights>The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.</rights><rights>2023. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c419t-7048e485d438c2992c0b0372c889c99476be4c27c2d27f86d7e1b49bbc0975bd3</citedby><cites>FETCH-LOGICAL-c419t-7048e485d438c2992c0b0372c889c99476be4c27c2d27f86d7e1b49bbc0975bd3</cites><orcidid>0000-0002-9432-3120</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27903,27904</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/37264183$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Ball, Geoff D. C.</creatorcontrib><creatorcontrib>Sharma, Atul K.</creatorcontrib><creatorcontrib>Moore, Sarah A.</creatorcontrib><creatorcontrib>Metzger, Daniel L.</creatorcontrib><creatorcontrib>Klein, Doug</creatorcontrib><creatorcontrib>Morrison, Katherine M.</creatorcontrib><creatorcontrib>CANadian Pediatric Weight management Registry (CANPWR) Investigators</creatorcontrib><creatorcontrib>on behalf of the CANadian Pediatric Weight management Registry (CANPWR) Investigators</creatorcontrib><title>Measuring severe obesity in pediatrics using body mass index-derived metrics from the Centers for Disease Control and Prevention and World Health Organization: a secondary analysis of CANadian Pediatric Weight management Registry (CANPWR) data</title><title>European journal of pediatrics</title><addtitle>Eur J Pediatr</addtitle><addtitle>Eur J Pediatr</addtitle><description>To examine the
(i)
relationships between various body mass index (BMI)-derived metrics for measuring severe obesity (SO) over time based the Centers for Disease Control and Prevention (CDC) and World Health Organization (WHO) references and
(ii)
ability of these metrics to discriminate children and adolescents based on the presence of cardiometabolic risk factors. In this cohort study completed from 2013 to 2021, we examined data from 3- to 18-year-olds enrolled in the CANadian Pediatric Weight management Registry. Anthropometric data were used to create nine BMI-derived metrics based on the CDC and WHO references. Cardiometabolic risk factors were examined, including dysglycemia, dyslipidemia, and elevated blood pressure. Analyses included Pearson correlations, intraclass correlation coefficients (ICC), and receiver operator characteristic area-under-the-curve (ROC AUC). Our sample included 1,288 participants (n = 666 [52%] girls; n = 874 [68%] white). The prevalence of SO varied from 60–67%, depending on the definition. Most BMI-derived metrics were positively and significantly related to one another (r = 0.45–1.00); ICCs revealed high tracking (0.90–0.94). ROC AUC analyses showed CDC and WHO metrics had a modest ability to discriminate the presence of cardiometabolic risk factors, which improved slightly with increasing numbers of risk factors. Overall, most BMI-derived metrics rated poorly in identifying presence of cardiometabolic risk factors.
Conclusion
: CDC BMI percent of the 95
th
percentile and WHO BMIz performed similarly as measures of SO, although neither showed particularly impressive discrimination. They appear to be interchangeable in clinical care and research in pediatrics, but there is a need for a universal standard. WHO BMIz may be useful for clinicians and researchers from countries that recommend using the WHO growth reference.
What is Known:
• Severe obesity in pediatrics is a global health issue.
• Few reports have evaluated body mass index (BMI)-derived metrics based on the World Health Organization growth reference.
What is New:
• Our analyses showed that the Centers for Disease Control and Prevention BMI percent of the 95
th
percentile and World Health Organization (WHO) BMI z-score (BMIz) performed similarly as measures of severe obesity in pediatrics.
• WHO BMIz should be a useful metric to measure severe obesity for clinicians and researchers from countries that recommend using the WHO growth reference.</description><subject>Blood pressure</subject><subject>Body mass index</subject><subject>Body measurements</subject><subject>Disease control</subject><subject>Disease prevention</subject><subject>Dyslipidemia</subject><subject>Medicine</subject><subject>Medicine & Public Health</subject><subject>Obesity</subject><subject>Pediatrics</subject><subject>Public health</subject><subject>Risk factors</subject><subject>Weight control</subject><issn>1432-1076</issn><issn>0340-6199</issn><issn>1432-1076</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><recordid>eNp9kk1vEzEQhlcIRD_gD3BAI3EphwXb68S73KrwUaRCowqU48prTxJXu3ZqeyvSv80fYNK0gDhwsj3zzDvj0VsULzh7wxlTbxNjsuIlE1XJJqxqSvmoOOSyEiVnavr4r_tBcZTSFaOihtdPi4NKiankdXVY_PyCOo3R-RUkvMGIEDpMLm_BedigdTpHZxKMaYd0wW5h0ClR1uKP0mJ0N2hhwD21jGGAvEaYoc8YKRAivHeJelAs-BxDD9pbmEdq5rML_u65CLG3cIa6z2u4iCvt3a3eZd-BprlM8FbHLaG63yaXICxhdvpV03Qe5g9DwgLdap1pPq9XOJA8XOLKpUyVJ4TPF5evweqsnxVPlrpP-Pz-PC6-f_zwbXZWnl98-jw7PS-N5E0uFZM1ynpiZVUb0TTCsI7R5kxdN6ZppJp2KI1QRlihlvXUKuSdbLrOsEZNOlsdFyd73U0M1yOm3A4uGex77TGMqRW1EJVStZwQ-uof9CqMkb67oyZKKsW4IkrsKRNDShGX7Sa6gTbTctbuLNHuLdGSJdo7S7SSil7eS4_dgPZ3yYMHCKj2QNrsfIDxT-__yP4C5MHFSA</recordid><startdate>20230801</startdate><enddate>20230801</enddate><creator>Ball, Geoff D. C.</creator><creator>Sharma, Atul K.</creator><creator>Moore, Sarah A.</creator><creator>Metzger, Daniel L.</creator><creator>Klein, Doug</creator><creator>Morrison, Katherine M.</creator><general>Springer Berlin Heidelberg</general><general>Springer Nature B.V</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7RV</scope><scope>7TK</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8C1</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>K9-</scope><scope>K9.</scope><scope>KB0</scope><scope>M0R</scope><scope>M0S</scope><scope>M1P</scope><scope>NAPCQ</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0002-9432-3120</orcidid></search><sort><creationdate>20230801</creationdate><title>Measuring severe obesity in pediatrics using body mass index-derived metrics from the Centers for Disease Control and Prevention and World Health Organization: a secondary analysis of CANadian Pediatric Weight management Registry (CANPWR) data</title><author>Ball, Geoff D. C. ; Sharma, Atul K. ; Moore, Sarah A. ; Metzger, Daniel L. ; Klein, Doug ; Morrison, Katherine M.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c419t-7048e485d438c2992c0b0372c889c99476be4c27c2d27f86d7e1b49bbc0975bd3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Blood pressure</topic><topic>Body mass index</topic><topic>Body measurements</topic><topic>Disease control</topic><topic>Disease prevention</topic><topic>Dyslipidemia</topic><topic>Medicine</topic><topic>Medicine & Public Health</topic><topic>Obesity</topic><topic>Pediatrics</topic><topic>Public health</topic><topic>Risk factors</topic><topic>Weight control</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ball, Geoff D. C.</creatorcontrib><creatorcontrib>Sharma, Atul K.</creatorcontrib><creatorcontrib>Moore, Sarah A.</creatorcontrib><creatorcontrib>Metzger, Daniel L.</creatorcontrib><creatorcontrib>Klein, Doug</creatorcontrib><creatorcontrib>Morrison, Katherine M.</creatorcontrib><creatorcontrib>CANadian Pediatric Weight management Registry (CANPWR) Investigators</creatorcontrib><creatorcontrib>on behalf of the CANadian Pediatric Weight management Registry (CANPWR) Investigators</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>ProQuest Nursing & Allied Health Database</collection><collection>Neurosciences Abstracts</collection><collection>ProQuest - Health & Medical Complete保健、医学与药学数据库</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Public Health Database</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>Consumer Health Database</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>Consumer Health Database</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Nursing & Allied Health Premium</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>MEDLINE - Academic</collection><jtitle>European journal of pediatrics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Ball, Geoff D. C.</au><au>Sharma, Atul K.</au><au>Moore, Sarah A.</au><au>Metzger, Daniel L.</au><au>Klein, Doug</au><au>Morrison, Katherine M.</au><aucorp>CANadian Pediatric Weight management Registry (CANPWR) Investigators</aucorp><aucorp>on behalf of the CANadian Pediatric Weight management Registry (CANPWR) Investigators</aucorp><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Measuring severe obesity in pediatrics using body mass index-derived metrics from the Centers for Disease Control and Prevention and World Health Organization: a secondary analysis of CANadian Pediatric Weight management Registry (CANPWR) data</atitle><jtitle>European journal of pediatrics</jtitle><stitle>Eur J Pediatr</stitle><addtitle>Eur J Pediatr</addtitle><date>2023-08-01</date><risdate>2023</risdate><volume>182</volume><issue>8</issue><spage>3679</spage><epage>3690</epage><pages>3679-3690</pages><issn>1432-1076</issn><issn>0340-6199</issn><eissn>1432-1076</eissn><abstract>To examine the
(i)
relationships between various body mass index (BMI)-derived metrics for measuring severe obesity (SO) over time based the Centers for Disease Control and Prevention (CDC) and World Health Organization (WHO) references and
(ii)
ability of these metrics to discriminate children and adolescents based on the presence of cardiometabolic risk factors. In this cohort study completed from 2013 to 2021, we examined data from 3- to 18-year-olds enrolled in the CANadian Pediatric Weight management Registry. Anthropometric data were used to create nine BMI-derived metrics based on the CDC and WHO references. Cardiometabolic risk factors were examined, including dysglycemia, dyslipidemia, and elevated blood pressure. Analyses included Pearson correlations, intraclass correlation coefficients (ICC), and receiver operator characteristic area-under-the-curve (ROC AUC). Our sample included 1,288 participants (n = 666 [52%] girls; n = 874 [68%] white). The prevalence of SO varied from 60–67%, depending on the definition. Most BMI-derived metrics were positively and significantly related to one another (r = 0.45–1.00); ICCs revealed high tracking (0.90–0.94). ROC AUC analyses showed CDC and WHO metrics had a modest ability to discriminate the presence of cardiometabolic risk factors, which improved slightly with increasing numbers of risk factors. Overall, most BMI-derived metrics rated poorly in identifying presence of cardiometabolic risk factors.
Conclusion
: CDC BMI percent of the 95
th
percentile and WHO BMIz performed similarly as measures of SO, although neither showed particularly impressive discrimination. They appear to be interchangeable in clinical care and research in pediatrics, but there is a need for a universal standard. WHO BMIz may be useful for clinicians and researchers from countries that recommend using the WHO growth reference.
What is Known:
• Severe obesity in pediatrics is a global health issue.
• Few reports have evaluated body mass index (BMI)-derived metrics based on the World Health Organization growth reference.
What is New:
• Our analyses showed that the Centers for Disease Control and Prevention BMI percent of the 95
th
percentile and World Health Organization (WHO) BMI z-score (BMIz) performed similarly as measures of severe obesity in pediatrics.
• WHO BMIz should be a useful metric to measure severe obesity for clinicians and researchers from countries that recommend using the WHO growth reference.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><pmid>37264183</pmid><doi>10.1007/s00431-023-05039-4</doi><tpages>12</tpages><orcidid>https://orcid.org/0000-0002-9432-3120</orcidid><oa>free_for_read</oa></addata></record> |
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source | Springer Nature |
subjects | Blood pressure Body mass index Body measurements Disease control Disease prevention Dyslipidemia Medicine Medicine & Public Health Obesity Pediatrics Public health Risk factors Weight control |
title | Measuring severe obesity in pediatrics using body mass index-derived metrics from the Centers for Disease Control and Prevention and World Health Organization: a secondary analysis of CANadian Pediatric Weight management Registry (CANPWR) data |
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