<?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>0036-3634</journal-id>
<journal-title><![CDATA[Salud Pública de México]]></journal-title>
<abbrev-journal-title><![CDATA[Salud pública Méx]]></abbrev-journal-title>
<issn>0036-3634</issn>
<publisher>
<publisher-name><![CDATA[Instituto Nacional de Salud Pública]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S0036-36342007000900014</article-id>
<title-group>
<article-title xml:lang="en"><![CDATA[Methodology of the fasting sub-sample from the Mexican Health Survey, 2000]]></article-title>
<article-title xml:lang="es"><![CDATA[Metodología de la submuestra de suero de la Encuesta Nacional de Salud 2000]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Barquera]]></surname>
<given-names><![CDATA[Simón]]></given-names>
</name>
<xref ref-type="aff" rid="A01"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Carrión]]></surname>
<given-names><![CDATA[Citlalli]]></given-names>
</name>
<xref ref-type="aff" rid="A01"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Campos]]></surname>
<given-names><![CDATA[Ismael]]></given-names>
</name>
<xref ref-type="aff" rid="A01"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Espinosa]]></surname>
<given-names><![CDATA[Juan]]></given-names>
</name>
<xref ref-type="aff" rid="A01"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Rivera]]></surname>
<given-names><![CDATA[Juan]]></given-names>
</name>
<xref ref-type="aff" rid="A01"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Olaiz-Fernández]]></surname>
<given-names><![CDATA[Gustavo]]></given-names>
</name>
<xref ref-type="aff" rid="A02"/>
</contrib>
</contrib-group>
<aff id="A01">
<institution><![CDATA[,Instituto Nacional de Salud Pública  ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>México</country>
</aff>
<aff id="A02">
<institution><![CDATA[,Secretaría de Salud  ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>México</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>00</month>
<year>2007</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>00</month>
<year>2007</year>
</pub-date>
<volume>49</volume>
<fpage>s421</fpage>
<lpage>s426</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_arttext&amp;pid=S0036-36342007000900014&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_abstract&amp;pid=S0036-36342007000900014&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_pdf&amp;pid=S0036-36342007000900014&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="en"><p><![CDATA[OBJECTIVE: To report the comparative results of the sub-sample of fasting adults selected for the biochemical measurement of cardiovascular risk factors and the rest of the Mexican Health Survey (MHS) (2000) participants. MATERIAL AND METHODS: The nationally representative, cross-sectional Mexican Health Survey (2000) was analyzed. Survey participants reporting a fasting state period of 9- to 12-h were included in a sub-sample (n= 2 535) and compared with all other participants (n= 41 126). Prevalence and 95% confidence intervals (95%CI) were calculated for socio-demographic, anthropometric, health and personal background characteristics and compared between groups using Pearson chi2 to determine significant differences. Mean and 95%CI and a T-test were calculated to analyze continuous variables. RESULTS: From the 45 294 adults participating in the MHS, 5.59% were at fasting state. The fasting sub-sample (FS) had a higher male-to-female ratio and was on average 3.5 years younger than the non-fasting participants (NF) and had a 1.5cm wider average waist circumference. No differences were found in location, country region, socio-economic status, indigenous population, or literacy. Also, no differences were found in weight, height, BMI, systolic and diastolic blood pressure, prevalence of diabetes mellitus, previous medical diagnosis of dislypidemias, or tobacco or alcohol consumption. CONCLUSION: This paper documents the characteristics of the fasting sub-sample from the Mexican Health Survey (MHS). Overall, the non-fasting participants had no relevant differences that can contribute to generate biased results in the analysis of biochemical indicators of cardiovascular risk.]]></p></abstract>
<abstract abstract-type="short" xml:lang="es"><p><![CDATA[OBJETIVO: Reportar los resultados comparativos de la sub-muestra de adultos en ayuno, seleccionados para la medición bioquímica de factores de riesgo cardiovascular y el resto de los participantes de la Encuesta Nacional de Salud (ENSA) 2000. MATERIAL Y MÉTODOS: Se analizó la ENSA, una encuesta transversal y representativa a nivel nacional. Los participantes que reportaron un período de ayuno de 9- a 12-h se incluyeron en la submuestra (n= 2,535) y se compararon con el resto de los participantes (n= 41,126). Se calculó la prevalencia e intervalo de confianza del 95% (IC95%) para las características sociodemográficas, antropométricas, de salud y antecedentes personales, y se compararon entre los grupos utilizando ² de Pearson para determinar diferencias significativas. Asimismo, se calcularon medianas con su IC95% y prueba de T para analizar las variables continuas. RESULTADOS: De los 45 294 adultos que participaron en la ENSA, 5.59% estuvieron en ayuno. La submuestra de ayuno (SA) tuvo una razón hombre-mujer más alta y fue en promedio 3.5 años más joven que el resto de los participantes (NA). Asimismo, tuvieron una cintura promedio 1.5cm más grande. No se encontraron diferencias en localidad, región, nivel socioeconómico, población indígena o educación. Tampoco se encontraron diferencias en peso, talla, IMC, presión sistólica ni diastólica, prevalencia de diabetes mellitus, diagnóstico previo de dislipidemias, y consumo de tabaco y alcohol. CONCLUSIÓN: Esta comunicación documenta las características de la muestra de ayuno de la ENSA. En general, los participantes en ayuno no tuvieron diferencias relevantes que puedan contribuir a generar resultados sesgados en el análisis de indicadores bioquímicos de riesgo cardiovascular.]]></p></abstract>
<kwd-group>
<kwd lng="en"><![CDATA[obesity]]></kwd>
<kwd lng="en"><![CDATA[diabetes mellitus high blood pressure]]></kwd>
<kwd lng="en"><![CDATA[national surveys]]></kwd>
<kwd lng="en"><![CDATA[Mexico]]></kwd>
<kwd lng="es"><![CDATA[obesidad]]></kwd>
<kwd lng="es"><![CDATA[diabetes mellitus]]></kwd>
<kwd lng="es"><![CDATA[presión arterial alta]]></kwd>
<kwd lng="es"><![CDATA[Encuesta Nacional de Salud]]></kwd>
<kwd lng="es"><![CDATA[México]]></kwd>
</kwd-group>
</article-meta>
</front><body><![CDATA[ <p align="right"><font face="Verdana, Arial, Helvetica, sans-serif" size="2"><b>ART&Iacute;CULO    ESPECIAL</b></font></p>     <p>&nbsp;</p>     <p><a name="top"></a><font face="Verdana, Arial, Helvetica, sans-serif" size="4"><b>Methodology    of the fasting sub-sample from the Mexican Health Survey, 2000</b></font></p>     <p>&nbsp;</p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="3"><b>Metodolog&iacute;a    de la submuestra de suero de la Encuesta Nacional de Salud 2000</b></font></p>     <p>&nbsp;</p>    <p>&nbsp;</p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2"><b>Sim&oacute;n    Barquera, MD, MS, PhD<sup>I</sup>; Citlalli Carri&oacute;n MC, M en C<sup>I</sup>;    Ismael Campos, MD, MS<sup>I</sup>; Juan Espinosa, MS<sup>I</sup>; Juan Rivera,    MS, PhD<sup>I</sup>; Gustavo Olaiz-Fern&aacute;ndez, MD, MSP<sup>II</sup></b></font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2"><sup>I</sup>Instituto    Nacional de Salud P&uacute;blica. M&eacute;xico    <br>   <sup>II</sup>Secretar&iacute;a    de Salud. M&eacute;xico</font></p>     ]]></body>
<body><![CDATA[<p>&nbsp;</p>     <p>&nbsp;</p> <hr size="1" noshade>    <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2"><b>ABSTRACT</b></font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2"><b>OBJECTIVE:</b>    To report the comparative results of the sub-sample of fasting adults selected    for the biochemical measurement of cardiovascular risk factors and the rest    of the Mexican Health Survey (MHS) (2000) participants.    <br>   <b>MATERIAL    AND METHODS:</b> The nationally representative, cross-sectional Mexican Health    Survey (2000) was analyzed. Survey participants reporting a fasting state period    of 9- to 12-h were included in a sub-sample (n= 2 535) and compared with all    other participants (n= 41 126). Prevalence and 95% confidence intervals (95%CI)    were calculated for socio-demographic, anthropometric, health and personal background    characteristics and compared between groups using Pearson <font face="Symbol">c</font><sup>2</sup>    to determine significant differences. Mean and 95%CI and a T-test were calculated    to analyze continuous variables.    <br>   <b>RESULTS:</b> From the 45 294 adults participating in the MHS, 5.59% were    at fasting state. The fasting sub-sample (FS) had a higher male-to-female ratio    and was on average 3.5 years younger than the non-fasting participants (NF)    and had a 1.5cm wider average waist circumference. No differences were found    in location, country region, socio-economic status, indigenous population, or    literacy. Also, no differences were found in weight, height, BMI, systolic and    diastolic blood pressure, prevalence of diabetes mellitus, previous medical    diagnosis of dislypidemias, or tobacco or alcohol consumption.    <br>   <b>CONCLUSION:</b> This paper documents the characteristics of the fasting sub-sample    from the Mexican Health Survey (MHS). Overall, the non-fasting participants    had no relevant differences that can contribute to generate biased results in    the analysis of biochemical indicators of cardiovascular risk.</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2"><b>Keywords: </b>obesity;    diabetes mellitus high blood pressure; national surveys; Mexico</font></p> <hr size="1" noshade>    <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2"><b>RESUMEN</b></font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2"><b>OBJETIVO:</b>    Reportar los resultados comparativos de la sub-muestra de adultos en ayuno,    seleccionados para la medici&oacute;n bioqu&iacute;mica de factores de riesgo    cardiovascular y el resto de los participantes de la Encuesta Nacional de Salud    (ENSA) 2000.    ]]></body>
<body><![CDATA[<br>   <b>MATERIAL Y M&Eacute;TODOS:</b> Se analiz&oacute; la ENSA, una encuesta transversal    y representativa a nivel nacional. Los participantes que reportaron un per&iacute;odo    de ayuno de 9- a 12-h se incluyeron en la submuestra (n= 2,535) y se compararon    con el resto de los participantes (n= 41,126). Se calcul&oacute; la prevalencia    e intervalo de confianza del 95% (IC95%) para las caracter&iacute;sticas sociodemogr&aacute;ficas,    antropom&eacute;tricas, de salud y antecedentes personales, y se compararon    entre los grupos utilizando <sup>2</sup> de Pearson para determinar diferencias    significativas. Asimismo, se calcularon medianas con su IC95% y prueba de T    para analizar las variables continuas.    <br>   <b>RESULTADOS:</b> De los 45 294 adultos que participaron en la ENSA, 5.59%    estuvieron en ayuno. La submuestra de ayuno (SA) tuvo una raz&oacute;n hombre-mujer    m&aacute;s alta y fue en promedio 3.5 a&ntilde;os m&aacute;s joven que el resto    de los participantes (NA). Asimismo, tuvieron una cintura promedio 1.5cm m&aacute;s    grande. No se encontraron diferencias en localidad, regi&oacute;n, nivel socioecon&oacute;mico,    poblaci&oacute;n ind&iacute;gena o educaci&oacute;n. Tampoco se encontraron    diferencias en peso, talla, IMC, presi&oacute;n sist&oacute;lica ni diast&oacute;lica,    prevalencia de diabetes mellitus, diagn&oacute;stico previo de dislipidemias,    y consumo de tabaco y alcohol.    <br>   <b>CONCLUSI&Oacute;N:</b> Esta comunicaci&oacute;n documenta las caracter&iacute;sticas    de la muestra de ayuno de la ENSA. En general, los participantes en ayuno no    tuvieron diferencias relevantes que puedan contribuir a generar resultados sesgados    en el an&aacute;lisis de indicadores bioqu&iacute;micos de riesgo cardiovascular.</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2"><b>Palabras clave: </b>   obesidad; diabetes mellitus; presi&oacute;n arterial alta; Encuesta Nacional    de Salud; M&eacute;xico</font></p> <hr size="1" noshade>    <p>&nbsp;</p>    <p>&nbsp;</p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">The prevalence    and characteristics of chronic diseases and obesity in Mexico have been documented    using diverse national databases such as the Mexican Nutrition Surveys I and    II (1988, 1999),<sup>1,2</sup> and the Mexican Chronic Diseases Survey (1994),<sup>3</sup>    among others. During 1999 and 2000, the National Institute of Public Health    implemented a national health survey (Mexican Health Survey 2000) that is representative    of adult men and women 20 years of age or older from across all the states and    urban and rural locations.<sup>4</sup> This survey collected casual blood samples    of most of the participants interviewed. These samples were frozen for future    studies, giving an invaluable opportunity to study biochemical indicators for    risk of chronic diseases and provide information regarding the actual status    of diverse diseases such as dislypidemias, high blood pressure, diabetes mellitus    and their association with obesity. The purpose of this brief report is to communicate    the comparative results of the sub-sample of fasting adults, which were selected    for the biochemical measurement of cardiovascular risk factors, and the rest    of the survey participants.</font></p>     <p>&nbsp;</p>    <p><font face="Verdana, Arial, Helvetica, sans-serif" size="3"><b>Material and Methods</b></font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">The present study    used data from the nationally representative, cross-sectional MHS, implemented    in 2000.<sup>4</sup> A multi-stage sampling procedure was used. A detailed description    of the sampling design and methods is available in another publication.<sup>5</sup>    From the primary sampling units, a total of 45 726 households were selected,    from which 24 856 men and 26 747 women over the age of 20 years from urban and    rural areas participated in the survey. A structured questionnaire was used    to obtain socio-demographic data, family history, clinical symptoms, and medical    treatment for various chronic diseases. A single blood sample was drawn by trained    personnel from approximately 44 000 cases and the serum was frozen at 150º    C degrees until analysis.</font></p>     ]]></body>
<body><![CDATA[<p><font face="Verdana, Arial, Helvetica, sans-serif" size="2"><b>Anthropometric    variables</b></font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">Following internationally    accepted techniques, standardized personnel measured height to the nearest 0.1    cm using a stadiometer (model 202, Seca Ltd, Birmingham, UK) and weight using    a digital scale (1631 solar scale, Tanita Corp, Tokyo, Japan) with a margin    of error of 5mm and 0.1kg, respectively. Waist circumference (WC) was measured    at the midpoint between the highest part of the iliac crest and the lowest part    of the ribs margin of the median axial line. The body mass index (BMI) was calculated    by dividing the weight in kilograms by the height in m<sup>2</sup> and was categorized    according to the World Health Organization (WHO) cut-off points into: normal    weight (18.5-24.9 kg/m<sup>2</sup>), overweight (25-29.9 kg/m<sup>2</sup>) and    obesity (<U>&gt;</u>30 kg/m<sup>2</sup>);<sup>6</sup> if WC was <u>&gt;</u>102    cm in males or <u>&gt;</u> 88 cm in females, the subject was classified as having    abdominal adiposity based on the National Institutes of Health guidelines.<sup>7</sup></font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2"><b>Geographic regions</b></font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">The regions were    defined as follows: North region (Baja California, Southern Baja California,    Coahuila, Durango, Nuevo Leon, Sonora, Sinaloa, Tamaulipas and Zacatecas), Central    region (Aguascalientes, Colima, Guanajuato, Hidalgo, Jalisco, Mexico, Michoacan,    Nayarit, Queretaro, San Luis Potosi and Tlaxcala), Metropolitan area of Mexico    City, and South Region (Campeche, Chiapas, Guerrero, Morelos, Oaxaca, Puebla,    Quintana Roo, Tabasco, Veracruz and Yucatan). This regionalization scheme has    been used in many epidemiologic transition analyses for within-country comparisons.<sup>8,9</sup></font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2"><b>Socioeconomic    status index</b></font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">For the purpose    of this study, a principal components analysis (PCA) was performed on household    characteristics (flooring material, ceiling, walls, water source, drainage,    number of persons residing in the household, and number of domestic appliances).    The main factor extracted explained 40.4% of the total variance with a Kaiser-Mayer-Olkin    (KMO) measure of sampling adequacy= 0.83 and was used as a proxy for socioeconomic    status (SES). This factor had large loadings for household and community characteristics    such as sewer system, indoor plumbing, refrigerator, and television. Small loadings    were observed for variables such as communal food distribution and number of    people residing in the household. For the purpose of this article, this factor    was divided into tertiles and used as a proxy for low, medium, and high socio-economic    level.</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2"><b>Diabetes mellitus    and high blood pressure definitions</b></font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">Blood samples were    collected and blood glucose was assessed using a capillary glucose test with    a glucometer (Accutrend Sensor Comfort, Lakeside; Roche Diagnostic Corporation,    Indianapolis, IN, USA) in fasting conditions. The American Diabetes Association's    criteria were utilized to identify diabetes mellitus, defined as the presence    of diabetes symptoms along with a casual plasma glucose concentration 200 mg/dl    or a fasting glucose 126 mg/dl and/or a previous diagnosis by a physician.<sup>10</sup>    Blood pressure was measured twice. The first reading was carried out after at    least five minutes of rest in a seated position. The same trained nurse took    both measures within five minutes of each other on the subjects' right arm using    an aneroid sphygmomanometer (TJX-10, ADEX Products, Mexico City, Mexico). The    first Korotkoff noise marked the systolic blood pressure and the fifth noise,    the diastolic blood pressure. Criteria from the Expert Panel on Detection, Evaluation,    and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III),<sup>7</sup>    were utilized to identify high blood pressure, documented if the subject presented    a diastolic blood pressure <u>&gt;</u>130 mmHg on the first reading and/or if    the diastolic blood pressure was <u>&gt;</u>85 mmHg, and they were confirmed    by means of a second measure. In addition, all patients who said to have been    previously diagnosed with hypertension by a physician were considered to have    high blood pressure.</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2"><b>Other sociodemographic    variables</b></font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">Education was stratified    into three groups: 1) primary or less, 2) more than primary and less than high    school education, and 3) high school or more education. Literacy was defined    as the percentage of the population capable of reading. Participants living    in a household in which an indigenous language was spoken were considered to    be indigenous.<sup>11</sup></font></p>     ]]></body>
<body><![CDATA[<p><font face="Verdana, Arial, Helvetica, sans-serif" size="2"><b>Identification    of the fasting sub-sample</b></font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">During the interview    the participants reported as either having or not having a 9- to 12-h fasting    state period. With this information, all individuals identified as positive    were included in the fasting sub-sample (n= 2 535). No attempt was made in the    original National Health Survey design to obtain a probabilistic sample of fasting    adults; therefore, this subgroup is considered a casual sub-sample from the    National Health Survey.</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2"><b>Statistical    analysis</b></font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">Due to the characteristics    of the survey, the present study adjusted for the complex multistage sample    design using the STATA 8.2 "SVY" module.<a name="top1"></a><a href="#back1"><sup>*</sup></a></font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">To compare fasting    with non-fasting cases, their prevalence and corresponding 95% confidence intervals    (95%CI) were calculated and a Pearson X<sup>2</sup> test was used to establish    significant differences between categories. Mean and 95%CI were calculated for    continuous variables. Information related to their socio-demographic characteristics,    health conditions, and personal and family background were analyzed.</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2"><b>Ethical considerations</b></font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">Consent for participation    was obtained from all participants. The project was approved by the scientific    and ethics committees of the Mexican National Institute of Public Health. In    addition, data collection was implemented considering the confidentiality and    reserve rights stipulated by the Mexican Statistical and Geographic information    law.<sup>12</sup></font></p>     <p>&nbsp;</p>    <p><font face="Verdana, Arial, Helvetica, sans-serif" size="3"><b>Results</b></font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">From the 45 294    adults participating in the survey, 5.59% were at fasting state during the blood    collection (n= 2 535). <a href="#tab1">Table I</a> summarizes the socio-demographic    characteristics of the fasting and non-fasting participants. A slightly higher    male-to-female ratio was observed in the fasting group. In addition, the prevalence    of participants with high school or more education was higher (35.5 fasting    versus 29.3% non-fasting). There were no significant differences in location    (rural/urban), country region, socio-economic status index, indigenous population,    or literacy. <a href="#tab2">Table II</a> summarizes personal characteristics    such as anthropometric information and prevalence for diabetes mellitus (DM)    or high blood pressure (HBP). The fasting group was on average 3.5 years younger    than the non-fasting group. No differences were found in the average height,    weight, BMI, or systolic and diastolic blood pressure. By BMI category, there    were no differences between fasting and non-fasting groups for the prevalence    of normal, overweight, and obese participants. Waist circumference of non-fasting    participants was on average 1.5 cm wider compared to the fasting group (93 cm    <i>versus</i> 91.5 cm, respectively). The non-fasting group showed 4.6% more    cases of central obesity using the ATPIII criteria compared to the fasting group    (40.9 <i>versus</i> 36.3% respectively). These differences were maintained after    disaggregating by sex, but remained insignificant. The prevalence of DM was    similar in both groups, but the survey found that this condition was more prevalent    in the fasting group. There were no significant differences in high blood pressure    prevalence. A remarkably low percentage of the population had a previous medical    diagnosis of high blood cholesterol in both non-fasting and fasting groups (<a href="#tab2">Table    II</a>). <a href="#tab3">Table III</a> presents the personal and family background    of the participants. No difference was observed between the groups for tobacco    and alcohol consumption. Finally, no difference was observed for family history    of DM, HBP, and cardiovascular disease.</font></p>     ]]></body>
<body><![CDATA[<p><a name="tab1"></a></p>     <p>&nbsp;</p>     <p align="center"><img src="/img/revistas/spm/v49s3/13t1.gif"></p>     <p>&nbsp;</p>     <p><a name="tab2"></a></p>     <p>&nbsp;</p>     <p align="center"><img src="/img/revistas/spm/v49s3/13t2.gif"></p>     <p>&nbsp;</p>     <p><a name="tab3"></a></p>     <p>&nbsp;</p>     ]]></body>
<body><![CDATA[<p align="center"><img src="/img/revistas/spm/v49s3/13t3.gif"></p>     <p>&nbsp;</p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="3"><b>Discussion</b></font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">This paper documents    the characteristics of the fasting sub-sample from the Mexican Health Survey    (MHS). Overall, the non-fasting and fasting groups have no relevant differences    that can contribute to bias in the interpretation of biochemical cardiovascular    risk indicators in the latter group.</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">It is likely that    fasting samples were collected earlier, explaining why the frequency of males    in the fasting group was higher than the rest the sample. Abdominal obesity    was significantly different between the groups, even after adjusting by age;    however, it was not significantly different after stratifying by sex.</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">The grouping into    four country regions, in which three regions aggregate states and Mexico City    as a single region, resulted in a very low proportion of cases for this area.    This could compromise some analyses that are stratified by region, this results    must be analyzed carefully.</font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">In conclusion,    the strategy of analyzing the fasting participants for biochemical indicators    of chronic diseases could result in valid indicators for a sub-sample population    of the Mexican Health Survey without significant differences from the rest of    the survey participants in most socio-demographic, anthropometric, and health    conditions. However, the resulting number of cases limits the ability to detect    significant differences after stratifying by region or when analyzing events    that occur at a very low rate. In future surveys, new strategies will be implemented    to assure a higher number of participants at fasting state.</font></p>     <p>&nbsp;</p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="3"><b>Acknowledgments</b></font></p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">This study was    possible thanks to the Mexican National Council of Science and Technology (CONACyT)    grant number 37194-M (Barquera S, Olaiz G, Villalpando S, Rivera J, Gonz&aacute;lez    C, Sep&uacute;lveda J. Contribution of overweight and obesity to the development    of risk factors for chronic diseases: analysis of the National Health Survey).    We would like to acknowledge the assistance of Oswaldo Palma, MS, Rosalba Rojas,    MD, PhD, Carlos Conde, PhD and Ricardo Robledo, PhD, who provided valuable assistance    in identifying and processing the fasting sub-sample from the MHS.</font></p>     ]]></body>
<body><![CDATA[<p>&nbsp;</p>    <p><font face="Verdana, Arial, Helvetica, sans-serif" size="3"><b>References</b></font></p>     <!-- ref --><p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">1. Sepulveda-Amor,    J, Lezana, MA, Tapia-Conyer, R, Valdespino, JL, Madrigal, H, Kumate, J. Estado    nutricional de preescolares y mujeres en M&eacute;xico: resultados de una encuesta    probabil&iacute;stica poblacional. Gac Med Mex 1990;126:207-224.</font>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;[&#160;<a href="javascript:void(0);" onclick="javascript: window.open('/scielo.php?script=sci_nlinks&ref=9247267&pid=S0036-3634200700090001400001&lng=','','width=640,height=500,resizable=yes,scrollbars=1,menubar=yes,');">Links</a>&#160;]<!-- end-ref --><!-- ref --><p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">2. Rivera, J, Shamah,    T, Villalpando, S, Gonz&aacute;lez-Cossio, T, Hern&aacute;ndez, B, Sep&uacute;lveda,    J. 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Estados Unidos Mexicanos, 1980.</font>&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;[&#160;<a href="javascript:void(0);" onclick="javascript: window.open('/scielo.php?script=sci_nlinks&ref=9247278&pid=S0036-3634200700090001400012&lng=','','width=640,height=500,resizable=yes,scrollbars=1,menubar=yes,');">Links</a>&#160;]<!-- end-ref --><p>&nbsp;</p>     <p>&nbsp;</p>     <p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">Received on: October    30, 2006    <br>   Accepted on: February 7, 2007</font></p>     <p>&nbsp;</p>     <p>&nbsp;</p>     ]]></body>
<body><![CDATA[<p><font face="Verdana, Arial, Helvetica, sans-serif" size="2">Address reprint    requests to: Dr. Sim&oacute;n Barquera, Instituto Nacional de Salud P&uacute;blica.    Av. Universidad 655, Col. Santa Mar&iacute;a Ahuacatitl&aacute;n. 62508 Cuernavaca,    Morelos, Mexico. E-mail: <a href="mailto:sbarquera@insp.mx">sbarquera@insp.mx</a>    <br>   <a name="back1"></a><a href="#top1">*</a> Stata Corp. Stata reference manual.    Release 7. College Station, TX, USA. Stata Press, 2001. </font></p>      ]]></body><back>
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<given-names><![CDATA[M]]></given-names>
</name>
<name>
<surname><![CDATA[Mendoza]]></surname>
<given-names><![CDATA[L]]></given-names>
</name>
<name>
<surname><![CDATA[Palma]]></surname>
<given-names><![CDATA[O]]></given-names>
</name>
<name>
<surname><![CDATA[Velázquez]]></surname>
<given-names><![CDATA[O]]></given-names>
</name>
</person-group>
<source><![CDATA[Encuesta Nacional de Salud]]></source>
<year>2003</year>
<publisher-loc><![CDATA[Cuernavaca^eMorelos Morelos]]></publisher-loc>
<publisher-name><![CDATA[Instituto Nacional de Salud Pública]]></publisher-name>
</nlm-citation>
</ref>
<ref id="B12">
<label>12</label><nlm-citation citation-type="journal">
<article-title xml:lang="es"><![CDATA[Ley de Información Estadística y Geográfica]]></article-title>
<source><![CDATA[Diario Oficial de la Federación]]></source>
<year>1980</year>
</nlm-citation>
</ref>
</ref-list>
</back>
</article>
