<?xml version="1.0" encoding="ISO-8859-1"?><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
<front>
<journal-meta>
<journal-id>0004-0622</journal-id>
<journal-title><![CDATA[Archivos Latinoamericanos de Nutrición]]></journal-title>
<abbrev-journal-title><![CDATA[ALAN]]></abbrev-journal-title>
<issn>0004-0622</issn>
<publisher>
<publisher-name><![CDATA[Sociedad Latinoamericana de Nutrición]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S0004-06222013000200003</article-id>
<title-group>
<article-title xml:lang="en"><![CDATA[At risk or not: Comparing normative and criterion-referenced Body Mass Index standards among Mexican American children]]></article-title>
<article-title xml:lang="es"><![CDATA[A riesgo o no: comparando índices de masa corporal normativos e índices basados en criterios en niños méxico-americanos]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[de Heer]]></surname>
<given-names><![CDATA[F]]></given-names>
</name>
<xref ref-type="aff" rid="A01"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Morera]]></surname>
<given-names><![CDATA[O]]></given-names>
</name>
<xref ref-type="aff" rid="A02"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Warren]]></surname>
<given-names><![CDATA[M]]></given-names>
</name>
<xref ref-type="aff" rid="A03"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Chaudhari]]></surname>
<given-names><![CDATA[L]]></given-names>
</name>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[de Heer]]></surname>
<given-names><![CDATA[H D]]></given-names>
</name>
</contrib>
</contrib-group>
<aff id="A01">
<institution><![CDATA[,Northern Arizona University College of Health and Human Services ]]></institution>
<addr-line><![CDATA[El Paso Texas]]></addr-line>
</aff>
<aff id="A02">
<institution><![CDATA[,Northern Arizona University College of Health and Human Services ]]></institution>
<addr-line><![CDATA[ Arizona]]></addr-line>
</aff>
<aff id="A03">
<institution><![CDATA[,Northern Arizona University College of Health and Human Services ]]></institution>
<addr-line><![CDATA[ Arizona]]></addr-line>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>06</month>
<year>2013</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>06</month>
<year>2013</year>
</pub-date>
<volume>63</volume>
<numero>2</numero>
<fpage>126</fpage>
<lpage>133</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://ve.scielo.org/scielo.php?script=sci_arttext&amp;pid=S0004-06222013000200003&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://ve.scielo.org/scielo.php?script=sci_abstract&amp;pid=S0004-06222013000200003&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://ve.scielo.org/scielo.php?script=sci_pdf&amp;pid=S0004-06222013000200003&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="en"><p><![CDATA[Most childhood obesity research has classified participants by normative standards for Body Mass Index (BMI) through population percentiles or values corresponding to overweight adults (World Health Organization (WHO), Centers for Disease Control and Prevention (CDC) and the International Obesity Task Force (IOTF)). In 2006, criterion-referenced standards (FitnessGram®) were developed (revised in 2010) which directly associate BMI values with adverse health outcomes. This study assessed agreement between normative and criterion-referenced standards. Participants included 653 Mexican American 3rd to 5th graders living in the U.S.-Mexico border area who participated in a health promotion project. At baseline, agreement was compared between normative and criterion-referenced classifications. At follow-up, agreement between classifications on changes (e.g. from overweight to healthy weight) was assessed. According to FitnessGram® standards, 53.0% of participants were overweight or obese at baseline. Compared to FitnessGram®, the IOTF and CDC standards classified 15% fewer participants as obese/high risk. The WHO standards were closely related to FitnessGram® (kappa=.925) and showed significantly greater agreement with FitnessGram® than the CDC (kappa=.925 versus 0.722, p<.001) and IOTF standards (kappa=.925 versus .682, p<.001). Compared to the FitnessGram® (8.9%), the WHO and CDC (8.6%) were similar, but IOTF standards lower (6.5%) in how many children improved following the health program. Despite acceptable agreement between the different indices, several normative classifications may underestimate the proportion of children who are at risk for BMI-related adverse health consequences.]]></p></abstract>
<abstract abstract-type="short" xml:lang="es"><p><![CDATA[Muchos de los estudios sobre la obesidad infantil clasifican a los participantes por índices normativas para el índice de masa corporal (IMC) usando valores de percentil de población o valores correspondientes a adultos con sobrepeso (Organización Mundial de la Salud (WHO), Centros para el Control y Prevención de Enfermedades (CDC) y la Comisión International Sobre la Obesidad (OITF)). En 2006, índices con referencias a criterios (Fitness-Gram®) fueron creados asociando valores de IMC directamente a valores de impacto de salud adversos. Este estudio determino las equivalencias de los índices normativos y los con referencias a criterios. Los participantes incluyeron estudiantes (N=653), niveles 3°-5, viviendo en la frontera EEUU-México. Al inicio, se comparó la equivalencia entre el IMC basado en las clasificaciones normativas y los con referencias a criterios. La equivalencia entre las clasificaciones de los cambios fue evaluada. Según las normas Fitness-Gram®, 53.0% tenían sobrepeso o eran obesos aunque las normas OITF y CDC indicaron menos de 15% fueron clasificados con obesidad/alto riesgo. Las normas WHO fueron más cercanamente relacionadas con las de FitnessGram® (kappa=.925) y mostraron significativamente mayor equivalencia con las de FitnessGram® que a las del CDC (kappa= .925 V .722, p<.001) e IOTF (kappa=.925 V .669, p<.001). Los índices FitnessGram® (8.9%), WHO y CDC (8.6%) fueron similares en cuanto el número de niños que mejoraron siguiendo el programa, pero el índice IOTF fue menor (6.3%). Aunque había un acuerdo aceptable entre los índices diferentes, varios pueden subestimar la proporción a riesgo y las consecuencias adversas relacionadas al IMC.]]></p></abstract>
<kwd-group>
<kwd lng="en"><![CDATA[Obesity]]></kwd>
<kwd lng="en"><![CDATA[Overweight]]></kwd>
<kwd lng="en"><![CDATA[BMI]]></kwd>
<kwd lng="en"><![CDATA[FitnessGram®]]></kwd>
<kwd lng="es"><![CDATA[Obesidad]]></kwd>
<kwd lng="es"><![CDATA[Sobrepeso]]></kwd>
<kwd lng="es"><![CDATA[IMC]]></kwd>
<kwd lng="es"><![CDATA[FitnessGram®]]></kwd>
</kwd-group>
</article-meta>
</front><body><![CDATA[ <p align="center"><font face="Verdana"><b>At risk or not: Comparing normative  and criterion-referenced Body Mass Index standards among Mexican American  children</b></font></p>     <p align="center"><font face="Verdana" size="2"><b>F de Heer,O Morera, M Warren,  L Chaudhari, H D de Heer</b></font></p>     <p align="justify"><font face="Verdana" size="2">Physical Therapy and  Orthopaedic Manual Therapy Practice de Heer, Voorburg, The Netherlands</font></p>     <p align="justify"><font face="Verdana" size="2">University of Texas at El Paso,  Department of Psychology, El Paso, Texas</font></p>     <p align="justify"><font face="Verdana" size="2">Northern Arizona University,  Department of Physical Therapy and Athletic Training, Flagstaff, Arizona</font></p>     <p align="justify"><font face="Verdana" size="2">Northern Arizona University,  College of Health and Human Services, Flagstaff, Arizona</font></p>     <p align="justify"><font face="Verdana" size="2"><b>SUMMARY</b>. Most childhood  obesity research has classified participants by normative standards for Body  Mass Index (BMI) through population percentiles or values corresponding to  overweight adults (World Health Organization (WHO), Centers for Disease Control  and Prevention (CDC) and the International Obesity Task Force (IOTF)). In 2006,  criterion-referenced standards (FitnessGram®) were developed (revised in 2010)  which directly associate BMI values with adverse health outcomes. This study  assessed agreement between normative and criterion-referenced standards.  Participants included 653 Mexican American 3rd to 5th graders living in the U.S.-Mexico  border area who participated in a health promotion project. At baseline,  agreement was compared between normative and criterion-referenced  classifications. At follow-up, agreement between classifications on changes (e.g.  from overweight to healthy weight) was assessed. According to FitnessGram®  standards, 53.0% of participants were overweight or obese at baseline. Compared  to FitnessGram®, the IOTF and CDC standards classified 15% fewer participants as  obese/high risk. The WHO standards were closely related to FitnessGram®  (kappa=.925) and showed significantly greater agreement with FitnessGram® than  the CDC (kappa=.925 versus 0.722, p&lt;.001) and IOTF standards (kappa=.925 versus  .682, p&lt;.001). Compared to the FitnessGram® (8.9%), the WHO and CDC (8.6%) were  similar, but IOTF standards lower (6.5%) in how many children improved following  the health program. Despite acceptable agreement between the different indices,  several normative classifications may underestimate the proportion of children  who are at risk for BMI-related adverse health consequences.</font></p>     <p align="justify"><font face="Verdana" size="2"><b>Key Words</b>: Obesity,  Overweight, BMI, FitnessGram®</font></p>     <p align="center"><font face="Verdana" size="2"><b>A riesgo o no: comparando  índices de masa corporal normativos e índices basados en criterios en niños  méxico-americanos.</b></font></p>     <p align="justify"><font face="Verdana" size="2"><b>RESUMEN</b>. Muchos de los  estudios sobre la obesidad infantil clasifican a los participantes por índices  normativas para el índice de masa corporal (IMC) usando valores de percentil de  población o valores correspondientes a adultos con sobrepeso (Organización  Mundial de la Salud (WHO), Centros para el Control y Prevención de Enfermedades  (CDC) y la Comisión International Sobre la Obesidad (OITF)). En 2006, índices  con referencias a criterios (Fitness-Gram®) fueron creados asociando valores de  IMC directamente a valores de impacto de salud adversos. Este estudio determino  las equivalencias de los índices normativos y los con referencias a criterios.  Los participantes incluyeron estudiantes (N=653), niveles 3°-5, viviendo en la  frontera EEUU-México. Al inicio, se comparó la equivalencia entre el IMC basado  en las clasificaciones normativas y los con referencias a criterios. La  equivalencia entre las clasificaciones de los cambios fue evaluada. Según las  normas Fitness-Gram®, 53.0% tenían sobrepeso o eran obesos aunque las normas  OITF y CDC indicaron menos de 15% fueron clasificados con obesidad/alto riesgo.  Las normas WHO fueron más cercanamente relacionadas con las de FitnessGram®  (kappa=.925) y mostraron significativamente mayor equivalencia con las de  FitnessGram® que a las del CDC (kappa= .925 V .722, p&lt;.001) e IOTF (kappa=.925 V  .669, p&lt;.001). Los índices FitnessGram® (8.9%), WHO y CDC (8.6%) fueron  similares en cuanto el número de niños que mejoraron siguiendo el programa, pero  el índice IOTF fue menor (6.3%). Aunque había un acuerdo aceptable entre los  índices diferentes, varios pueden subestimar la proporción a riesgo y las  consecuencias adversas relacionadas al IMC.</font></p>     ]]></body>
<body><![CDATA[<p align="justify"><font face="Verdana" size="2"><b>Palabras clave:</b>  Obesidad, Sobrepeso, IMC, FitnessGram®</font></p>     <p align="justify"><font face="Verdana" size="2">Recibido: 13-01-2013 Aceptado:  06-08-2013</font></p>     <p align="justify"><font face="Verdana" size="2"><b>INTRODUCTION</b></font></p>     <p align="justify"><font face="Verdana" size="2">Over the past decades, rates of  obesity and being overweight have increased strongly for children and  adolescents (1). Children are becoming overweight at a younger age, as almost a  quarter of pre-school children are currently obese or overweight (1). Given that  about 70% of overweight children continue to be overweight in adulthood (2), and  that rates of overweight and obesity are higher among rapidly growing minority  populations (3), obesity is expected to continue to be a major public health  challenge.</font></p>     <p align="justify"><font face="Verdana" size="2">The outcome variable most  commonly used in studies addressing childhood overweight/obesity has been Body  Mass Index (BMI). Although BMI is not a direct measure of body fat, it has been  found to be strongly associated with the most accurate body fat measures (r =  0.80-0.90) (4). Further, BMI is easy and inexpensive to measure. Importantly,  BMI has been found to be positively associated with risk factors for  cardiovascular diseases such as elevated blood pressure, adverse lipoprotein  profiles and diabetes (5). Different classification methods have been developed  that classify children according to their BMI.</font></p>     <p align="justify"><font face="Verdana" size="2">The Centers for Disease Control  and prevention (CDC) (6) and World Health Organization (WHO) (7) use ‘normative  reference standards’ to classify children according to their BMI relative to  their peers. According to the CDC and WHO BMI growth charts, being overweight is  defined as having a Body Mass Index of over the 85th percentile and obesity is  defined as having a BMI of over the 95th percentile.</font></p>     <p align="justify"><font face="Verdana" size="2">A key difference between the  two is that the CDC growth charts are a reference of how a population has  developed over a certain period. The CDC standards published in 2000 (6) are  based on the growth of a population of children in the U.S. from the 1960s  through 1994. In contrast, the WHO values for BMI are standards, aimed to  ‘describe the growth of healthy children who grew up under optimal conditions.’  A criticism of both the CDC and WHO percentiles are that the 85th and 95th  percentile cut-offs are arbitrary, and that constructing growth references based  on populations that longitudinally trend toward overweight and obesity will lead  to an underestimation of overweight/ obesity and an overestimation of  underweight (8).</font></p>     <p align="justify"><font face="Verdana" size="2">The International Obesity Task  Force (IOTF) standards have been developed (and updated in 2012) incorporating  data from six different countries including the United States and classify  children by different levels of ‘thinness’, normal weight, overweight and obese  (9,10). Instead of population percentiles, the standards were developed as the  children’s equivalent of adult overweight (BMI&#8805; 25kg/m2) and obesity (BMI&#8805;30kg/m2).  Since adult overweight and obesity have been associated with adverse health  consequences, these international standards are likely to relate children’s BMI  with health consequences. However, similar to the limitations of the CDC and WHO  standards, the IOTF cut-offs were not designed to define what BMI cut-off points  are the strongest predictors of future adverse health consequences.</font></p>     <p align="justify"><font face="Verdana" size="2">While adverse health  consequences of childhood obesity have long been known, only recently have  researchers begun to directly associate classifications of obesity with adverse  health consequences (5). In this context, Flegal and Ogden (11) have pointed out  that instead of debating how to define overweight and obesity, it might be more  important to consider what BMI cut-points best predict future health risks and  how to efficiently screen for such risks.</font></p>     <p align="justify"><font face="Verdana" size="2">In 2006, ‘criterion-referenced’  standards called ‘FitnessGram® standards’ were developed and revised in 2010  (12). The unique feature of these standards is that they classify a child  according to their health risk, rather than their status as overweight or obese.  Categories based on a child’s BMI include a BMI that is a) ‘very lean’, b) in  the ‘healthy fitness zone’, c) at ‘some risk’ or d) at ‘high risk’ for adverse  health consequences such as cardiovascular and metabolic conditions. The  complete FitnessGram® measurement protocol includes measures of body composition,  aerobic capacity, strength and flexibility and is currently implemented state-wide  in several states including Texas, the site of the current study.</font></p>     ]]></body>
<body><![CDATA[<p align="justify"><font face="Verdana" size="2">Several studies reported the  extent of agreement or discrepancies among the WHO, CDC and IOTF standards  (13-17). Most studies found moderately high agreement (kappa coefficients &gt;. 60)  (13, 14), although some reported that the odds of classifying a child as obese  or not obese varied substantially across these classifications (15-17). To date,  however, there is little knowledge about the extent to which the most commonly  used normative-referenced standards (CDC, WHO and IOTF) are in agreement with  criterion- referenced standards that directly associate BMI with health  consequences such as the FitnessGram® 2010 standards. Examining whether the most  commonly used standards indeed classify children as healthy whose body  composition may be associated with adverse health consequences can have  important implications for health promotion efforts.</font></p>     <p align="justify"><font face="Verdana" size="2">Using data from a randomized  after-school project conducted among a population of predominantly Hispanic  elementary school children (18), we assessed the extent of agreement between for  classification of children’s BMI across most commonly used normative standards  (CDC, WHO, IOTF) to the newly develop criterion-referenced standards (FitnessGram®).  We further assessed whether choosing a classification influenced conclusions  about the obesity prevention program’s impact (change in BMI from baseline to  follow-up).</font></p>     <p align="justify"><font face="Verdana" size="2"><b>MATERIALS AND METHODS</b></font></p>     <p align="justify"><font face="Verdana" size="2"><b>Participants and Setting </b> </font></p>     <p align="justify"><font face="Verdana" size="2">The health promotion project  was initiated in 2008 in El Paso, Texas a major city located directly on the U.S.-  Mexico border. The health promotion project consisted of a 12-week after-school  physical activity and nutrition education program (18). The after-school program  was based on physical activities developed by the Coordinated Approach to  Children’s Health (CATCH) (19), a comprehensive child health program widely  implemented. The health education was based on the bilingual (English-Spanish)  Bienestar program (20). Bienestar is a health education program developed in  response to the rising diabetes rates among underserved Hispanic youth and  consists of 16 modules on for example healthy eating, exercise, drinking water  and diabetes (20). The current study sample included a total of 653 participants  across 70 classrooms and 6 schools. The mean age of the participants was 9.3  years (SD=1.0) and 50% were boys. In 4 of the 6 schools, over 80% of children  were of Hispanic descent, over half were socio-economically disadvantaged and  had limited English proficiency (21). Parental consent and children’s assent at  appropriate reading levels in Spanish or English was acquired before program  implementation. The institutional review board of the University and the school  district approved all procedures and measures.</font></p>     <p align="justify"><font face="Verdana" size="2"><b>Outcome measures</b></font></p>     <p align="justify"><font face="Verdana" size="2">The FitnessGram® protocol was  measured during Physical Education classes. The FitnessGram® protocol consists  of a test battery of multiple measures indicative of physical fitness including  body composition, aerobic capacity, muscular strength and flexibility (12). Each  of these measures has been independently associated with risk for chronic  conditions. For each FitnessGram ® measure, an individual receives a score which  is then classified as being in a healthy range or in an unhealthy range (associated  with adverse health consequences, for example, high BMI or low aerobic capacity).  FitnessGram® does not, however, provide a comprehensive risk score, and although  completing all measures provides a more complete picture of an individual’s  health status, each measure in itself is associated with health consequences.  For the current paper, we will only present the measure used for body  composition: BMI, calculated as weight in kilograms divided by height in meters.  Height and weight were measured using a Tanita BF 215 portable digital scale.  Participants were instructed to empty their pockets, take off their shoes and if  applicable, their jacket. They were then asked to step on the scale, and stand  up straight. During that time, the height rod was pulled up and placed gently on  the top of their head. Their height was recorded to the nearest 0.25 inch. Their  weight was read and recorded from the digital scale to the nearest 0.1 pound.  Their BMI was calculated using standard formulas of (Weight in Pounds) x 703 /  [(Height in inches) x (Height in inches)].</font></p>     <p align="justify"><font face="Verdana" size="2"><b>Classifications</b></font></p>     <p align="justify"><font face="Verdana" size="2">Five classifications were  compared for weight or health status based on BMI (Table 1): three were  normative reference standards 1) the CDC growth charts, 2) the WHO growth charts,  3) the IOTF standards, which classify children either as underweight (-1),  normal weight (0), overweight (1) or obese (2). These classifications were  compared to the criterion-referenced FitnessGram® 2006 and revised FitnessGram®  2010 standards for BMI. The ‘FG06’ BMI standards include categories (-1) below  healthy fitness zone, (0) in the healthy fitness zone and (1) ‘needing  improvement.’ The FitnessGram® 2010 (‘FG10’) BMI categories include very lean  (-1), in healthy fitness zons (0), at some risk for adverse health consequences  (1) and at high risk for adverse health consequences (2).</font></p>     <p align="justify">&nbsp;</p>     ]]></body>
<body><![CDATA[<p align="justify"><font face="Verdana" size="2">An example of agreement is a  10-year old boy with a BMI of 18.5 kg/m<sup>2</sup>, who is considered normal  weight according to the IOTF standards, and at a healthy weight according to the  FitnessGram® 2010 standards. An example of a discrepancy is a 10-year old boy  with a BMI of 19.5 kg/m<sup>2</sup>, who is considered normal weight according  to the IOTF standards, but according to the FitnessGram® 2010 standards, this  child is at some risk for adverse health consequences.</font></p>     <p align="justify"><font face="Verdana" size="2"><b>Analyses</b></font></p>     <p align="justify"><font face="Verdana" size="2">We first assessed the  proportion agreement and kappa-coeffcients across approaches, calculated with  SPSS 17.0 frequencies and crosstabs. Secondly, we assessed whether each of the  kappa-coefficients were significantly different from the other kappa  coefficients following procedures by Barnhart and Williamson (22). Based on  these procedures, a macro in SAS (SAS Institute Inc., Cary, NC) using the SAS  PROC CATMOD procedure was used (22) to test for the equality of two kappa  statistics, with a significant pvalue indicating a statistical difference  between the two values. The rationale behind testing this was to assess whether,  for example one normative classification (e.g. WHO) agreed better with the  criterion-referenced standards (FitnessGram®) than the other normative  classifications.</font></p>     <p align="justify"><font face="Verdana" size="2">Finally, we compared the  proportion agreement across different classification systems regarding the  change in health status following participation in the study. So, if a  participant reduced their at-risk status from overweight to healthy weight by  CDC, WHO or IOTF standards, did they also change from unhealthy to healthy  according to the FitnessGram® values? These analyses were conducted with SPSS  17.0 and included McNemar tests for paired proportions.</font></p>     <p align="justify"><font face="Verdana" size="2"><b>RESULTS</b></font></p>     <p align="justify"><font face="Verdana" size="2">Agreement on baseline findings  The proportion of children that could be classified as overweight or obese  ranged from 29.6% (the FitnessGram ® 2006 standards) to 54.1% (the WHO standards;  Figure 1). The FitnessGram® 2010 standards classified 53% of participants as at  some or high risk for adverse health consequences.</font></p>     <p align="justify">&nbsp;</p>     <p align="justify"><font face="Verdana" size="2">We compared agreement across  the FitnessGram® 2010 and CDC, WHO and IOTF classifications (FitnessGram ® 2006  standards were not included in this comparison as this classification did not  have the same categories as the other classifications and coefficient kappa  could not be calculated).</font></p>     <p align="justify"><font face="Verdana" size="2">The WHO standards showed the  highest agreement with the FitnessGram® 2010 standards (kappa= 0.925), followed  by the CDC and FitnessGram® 2010 (kappa=0.722) and IOTF and FitnessGram® 2010  (0.682). The kappa statistics were significantly different from each other: the  agreement between the WHO and FitnessGram® 2010 (kappa=0.925) was significantly  greater than the agreement between the CDC and FitnessGram® 2010 (Kappa of 0.925  vs. 0.722; </font><font size="2" face="Times New Roman">&#967;</font><font face="Verdana" size="2"><sup>2</sup>(df=1)=21.03,  p&lt;.001 for the test of equivalence of kappa’s. Further, both the WHO (kappa  0.925 vs. 0.682; </font><font size="2" face="Times New Roman">&#967;</font><font face="Verdana" size="2"><sup>2</sup>(df=1)=35.16,  p&lt;.001) and CDC (kappa 0.722 vs. 0.682; </font> <font size="2" face="Times New Roman">&#967;</font><font face="Verdana" size="2"><sup>2</sup>(df=1)=5.85,  p=.012) showed better agreement with the FitnessGram® 2010 scores than the IOTF  values.</font></p>     <p align="justify"><font face="Verdana" size="2"><b>Agreement on impact of  health promotion program</b></font></p>     ]]></body>
<body><![CDATA[<p align="justify"><font face="Verdana" size="2">We assessed the change in BMI  classification from baseline to 4-month follow-up among all participants (Figure  2). A healthy change occurred if the participants’ weight status changed from  overweight/some risk to healthy weight or from obese/high risk to overweight/  some risk. The proportion of children improving their BMI weight or health  status category ranged from 2.8% (FitnessGram® 2006) to 8.9% (Fitness-Gram®  2010), whereas the proportion of participants worsening their health or weight  status ranged from 1.8% (FitnessGram® 2006) to 4.2% (WHO). The proportion of  participants improving or worsening their BMI health status according to  FitnessGram® 2010 were significantly different from the change according to the  FitnessGram® 2006 standards (</font><font size="2" face="Times New Roman">&#967;</font><font face="Verdana" size="2"><sup>2</sup>  (df=3) = 28.29, p&lt;.001), but not significantly different from the normative  reference standards: the CDC (</font><font size="2" face="Times New Roman">&#967;</font><font face="Verdana" size="2"><sup>2</sup>  (df=3) =1.41, p=.702), WHO (</font><font size="2" face="Times New Roman">&#967;</font><font face="Verdana" size="2"><sup>2</sup>  (df=3) = 1.97, p=.374) or IOTF (</font><font size="2" face="Times New Roman">&#967;</font><font face="Verdana" size="2"><sup>2</sup>  (df=3) =2.44, p=.487).</font></p>     <p align="justify">&nbsp;</p>     <p align="justify"><font face="Verdana" size="2"><b>DISCUSSION</b></font></p>     <p align="justify"><font face="Verdana" size="2">The current study compared  classification methods of childhood weight and health status in a sample of of  predominantly Hispanic elementary school children living on the U.S.-Mexico  border. Particularly, we compared the most commonly used normative standards  including population percentiles (by the CDC and WHO) and the childhood  equivalence of adulthood overweight (IOTF) to health-related or  criterionreferenced standards (the FitnessGram® 2010 standards). The study  population was a high-risk population, which is reflected in all classifications  indicating that approximately half of the participants are at risk for adverse  health outcomes. The average agreement between all classifications was  moderately high, although the CDC population percentiles and IOTF standards  classified fewer children as at high risk/obese than the WHO and the FitnessGram®  2010 standards. Of the most commonly used standards, the WHO standards were most  closely related to the criterion- referenced standards.</font></p>     <p align="justify"><font face="Verdana" size="2">The current study found  moderately high agreement across all classifications, which is consistent with  prior research (13,14). However, put into perspective, the CDC and IOTF  standards classified approximately 5% of children as having a normal or healthy  body weight, whereas they may actually be at risk for adverse health  consequences. Although this percentage may seem small, this represents 33  children in this study alone. In addition, the proportion of children classified  as obese or high risk based on their BMI was approximately 15% higher with the  FitnessGram® 2010 (39.2%) and WHO (36.3%) classifications compared to the CDC  (26.1%) and IOTF (22.8%) classifications. This means close to 100 children in  this study would be classified as overweight/at some risk instead of obese/at  high risk for adverse health consequences. These findings thus suggest that the  WHO standards may be the most accurately predictive of health-related body  composition outcomes such as high blood pressure, cholesterol and glucose. These  findings are consistent with prior research by Ramirez and colleagues (17) who  found that among children in Northwest Mexico, the WHO standards classified  about twice as many (39% vs. 20% for CDC and 17% for IOTF) children as obese or  overweight. These findings are further consistent with a large cohort study in  Brazil by Vieira and colleagues (14), who reported that the IOTF standards had  high sensitivity in terms of classifying overweight, but may underestimate the  prevalence of obesity compared to the WHO standards.</font></p>     <p align="justify"><font face="Verdana" size="2">Impact of the health promotion  program was fairly consistent across classifications (with the exception of the  original FitnessGram® 2006 standards), with proportions of children improving  their BMI status (from obese to overweight or overweight to healthy weight)  ranging from 6-9% and 3-4% worsening. Although not significantly different, the  IOTF classification was over 2% lower than the other classifications. According  to the IOTF classification, 42 children improved their health status from obese  to overweight or from overweight to healthy weight, whereas the CDC, WHO and  FitnessGram® standards would have concluded that approximately 55 or 60 children  improved their health status. Thus, choosing a classification system can make  the difference in drawing a conclusion that a program is about 30% more or less  effective in improving children’s BMI status.</font></p>     <p align="justify"><font face="Verdana" size="2">The largest differences were  found between the FitnessGram ® 2006 and 2010 standards. Interestingly, the  original FitnessGram® protocol (2006) was used during the intervention time of  the study (in 2008), but the reivsed version (2010) was published during the  study analysis phase. For the current study, while the FitnessGram® 2006 would  have classified fewer children as having an unhealthy weight, it would have also  led to the conclusion that the impact of the after-school program was smaller.</font></p>     <p align="justify"><font face="Verdana" size="2">Several important issues have  to be noted when interpreting the findings of the current study. For example,  prior research among children in Bolivia has found that none of the three major  standards (CDC, WHO and IOTF) were applicable to a population of Bolivian  adolescents (23). The authors indicated that all major growth references are  based on populations from Caucasian ancestry, and that South America, the Middle  East, the African Continent, and Central America have not been represented in  these references (23). Although the current study was conducted in the United  States, almost all children were of Mexican ancestry, which may have impacted  the classification.</font></p>     <p align="justify"><font face="Verdana" size="2">Another issue that has to be  taken into account is that other indicators of body composition were not  measured in the current study, such as waist circumference or body fat  percentage. This is important, as for example waist circumference has been shown  to have a stronger association with obesity-related health risk and recent  research has shown that the health risk of children may be classified  differently based on their BMI or waist circumference (24).</font></p>     <p align="justify"><font face="Verdana" size="2">Strengths &amp; Limitations An  important strength of the current study is that it is the first to compare  normative BMI-based reference standards with comparative reference standards.  This study further included a relatively high-risk population, for whom health  consequences can be potentially identified at an early age. Limitations of the  study include that the sample was fairly small and the setting of the study was  unique to the U.S.-Mexico border. As a result, findings of the current study may  not generalize to other populations. Other limitations include that the current  study did not take into account pubertal development, which may impact the  validity of the BMI classifications. Future studies may look at the predictive  value of a comprehensive risk score (such as taking into account all FitnessGram®  measurements or other indicators of body composition such as waist circumference)  and other factors including sex, age, ethnicity and family history (11).</font></p>     ]]></body>
<body><![CDATA[<p align="justify"><font face="Verdana" size="2"><b>CONCLUSIONS</b></font></p>     <p align="justify"><font face="Verdana" size="2">Comparing different  classifications of childhood weight showed that several normative  classifications may slightly underestimate the proportion of children who are at  risk for adverse health consequences as a result of their BMI. Of the currently  most frequently used classifications, the WHO standards are most closely related  to criterion-referenced standards that associate weight status with adverse  health outcomes. Accurately classifying children with respect to adverse health  consequences may be particularly important in areas with a large number of high  risk children with limited access to primary preventive services such as the U.S.-Mexico  border area.</font></p>     <p align="justify"><font face="Verdana" size="2"><b>ACKNOWLEDGEMENTS</b></font></p>     <p align="justify"><font face="Verdana" size="2">This project was supported by  pilot research grants from the Center for Border Health Research through the  Paso del Norte Health Foundation and by the pilot research grant mechanism of  the National Institutes of Health Hispanic Health Disparities Research Center (grant  P20MD002287-01).</font></p>     <p align="justify"><font face="Verdana" size="2"><b>REFERENCES</b></font></p>     <!-- ref --><p align="justify"><font face="Verdana" size="2">1. Ogden CL, Carroll MD, Curtin  LR, Lamb MM, Flegal KM. Prevalence of high Body Mass Index in US children and  adolescents, 2007-2008. 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