<?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>0042-9686</journal-id>
<journal-title><![CDATA[Bulletin of the World Health Organization]]></journal-title>
<abbrev-journal-title><![CDATA[Bull World Health Organ]]></abbrev-journal-title>
<issn>0042-9686</issn>
<publisher>
<publisher-name><![CDATA[World Health Organization]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S0042-96862008000900015</article-id>
<article-id pub-id-type="doi">10.1590/S0042-96862008000900015</article-id>
<title-group>
<article-title xml:lang="en"><![CDATA[Estimating child mortality due to diarrhoea in developing countries]]></article-title>
<article-title xml:lang="fr"><![CDATA[Estimation de la mortalité infanto-juvénile due à la diarrhée dans les pays en développement]]></article-title>
<article-title xml:lang="es"><![CDATA[Mortalidad en la niñez por diarrea en los países en desarrollo]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Boschi-Pinto]]></surname>
<given-names><![CDATA[Cynthia]]></given-names>
</name>
<xref ref-type="aff" rid="A01"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Velebit]]></surname>
<given-names><![CDATA[Lana]]></given-names>
</name>
<xref ref-type="aff" rid="A02"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Shibuya]]></surname>
<given-names><![CDATA[Kenji]]></given-names>
</name>
<xref ref-type="aff" rid="A03"/>
</contrib>
</contrib-group>
<aff id="A01">
<institution><![CDATA[,World Health Organization Child and Adolescent Health ]]></institution>
<addr-line><![CDATA[Geneva ]]></addr-line>
<country>Switzerland</country>
</aff>
<aff id="A02">
<institution><![CDATA[,WHO TB/HIV and Drug Resistance ]]></institution>
<addr-line><![CDATA[Geneva ]]></addr-line>
<country>Switzerland</country>
</aff>
<aff id="A03">
<institution><![CDATA[,WHO Measurement and Health Information Systems ]]></institution>
<addr-line><![CDATA[Geneva ]]></addr-line>
<country>Switzerland</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>09</month>
<year>2008</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>09</month>
<year>2008</year>
</pub-date>
<volume>86</volume>
<numero>9</numero>
<fpage>710</fpage>
<lpage>717</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielosp.org/scielo.php?script=sci_arttext&amp;pid=S0042-96862008000900015&amp;lng=en&amp;nrm=iso&amp;tlng=en"></self-uri><self-uri xlink:href="http://www.scielosp.org/scielo.php?script=sci_abstract&amp;pid=S0042-96862008000900015&amp;lng=en&amp;nrm=iso&amp;tlng=en"></self-uri><self-uri xlink:href="http://www.scielosp.org/scielo.php?script=sci_pdf&amp;pid=S0042-96862008000900015&amp;lng=en&amp;nrm=iso&amp;tlng=en"></self-uri><abstract abstract-type="short" xml:lang="en"><p><![CDATA[OBJECTIVE: The major objective of this study is to provide estimates of diarrhoea mortality at country, regional and global level by employing the Child Health Epidemiology Reference Group (CHERG) standard. METHODS: A systematic and comprehensive literature review was undertaken of all studies published since 1980 reporting under-5 diarrhoea mortality. Information was collected on characteristics of each study and its population. A regression model was used to relate these characteristics to proportional mortality from diarrhoea and to predict its distribution in national populations. FINDINGS: Global deaths from diarrhoea of children aged less than 5 years were estimated at 1.87 million (95% confidence interval, CI: 1.56-2.19), approximately 19% of total child deaths. WHO African and South-East Asia Regions combined contain 78% (1.46 million) of all diarrhoea deaths occurring among children in the developing world; 73% of these deaths are concentrated in just 15 developing countries. CONCLUSION: Planning and evaluation of interventions to control diarrhoea deaths and to reduce under-5 mortality is obstructed by the lack of a system that regularly generates cause-of-death information. The methods used here provide country-level estimates that constitute alternative information for planning in settings without adequate data.]]></p></abstract>
<abstract abstract-type="short" xml:lang="fr"><p><![CDATA[OBJECTIF: Le principal objectif de cette étude est de fournir des estimations de la mortalité par diarrhée aux niveaux mondial, régional et national, en utilisant la norme du Groupe de référence pour l'épidémiologie de la santé de l'enfant (CHERG). MÉTHODES: Une revue systématique et exhaustive de la littérature a été réalisée sur l'ensemble des études publiées depuis 1980 et traitant de la mortalité par diarrhée des moins de cinq ans. Des informations ont été recueillies sur les caractéristiques de chaque étude et de sa population. Un modèle par régression a été utilisé pour relier ces caractéristiques à la mortalité proportionnelle par diarrhée et pour prédire sa distribution dans les populations nationales. RÉSULTATS: A l'échelle mondiale, le nombre de décès par diarrhée chez les moins de cinq ans a été estimé à 1,87 million (intervalle de confiance à 95 %, IC : 1,56-2,19), soit approximativement 19 % du nombre total de décès d'enfants. La Région africaine et la Région de l'Asie du Sud-est de l'OMS totalisent 78 % (1,46 millions) des décès par diarrhée se produisant chez les enfants du monde en développement et 73 % de ces décès se concentrent dans 15 pays en développement seulement. CONCLUSION: La planification et l'évaluation des interventions pour endiguer la mortalité par diarrhée et pour réduire la mortalité des moins de cinq ans se heurtent à l'absence de système générant régulièrement des données sur les causes de décès. Les méthodes utilisées dans cette étude fournissent des estimations nationales, qui constituent des données de substitution pour la planification dans les pays ne disposant pas de données appropriées.]]></p></abstract>
<abstract abstract-type="short" xml:lang="es"><p><![CDATA[OBJETIVO: El principal objetivo de este estudio fue aportar estimaciones de la mortalidad por diarrea a nivel de país, regional y mundial aplicando los criterios del Grupo de Referencia en Epidemiología de la Salud Infantil (CHERG). MÉTODOS: Se llevó a cabo una revisión sistemática y detallada de la bibliografía para identificar todos los estudios publicados desde 1980 en los que se notificaran cifras de la mortalidad por diarrea entre los menores de cinco años. Se reunió información sobre las características de cada estudio y la población estudiada, y se usó un modelo de regresión para relacionar esas características con la mortalidad proporcional por diarrea y predecir su distribución en la población de cada país. RESULTADOS: La mortalidad mundial por diarrea entre la población menor de cinco años se estimó en 1,87 millones (intervalo de confianza del 95%: 1,56-2,19), lo que supone aproximadamente el 19% de la mortalidad total en la niñez. Las regiones de África y Asia Sudoriental de la OMS acumulan entre ambas el 78% (1,46 millones) de todas las muertes por diarrea registradas entre los niños en el mundo en desarrollo; y el 73% de estas defunciones se concentran en sólo 15 países en desarrollo. CONCLUSIÓN: La planificación y evaluación de las intervenciones encaminadas a controlar la mortalidad por diarrea y reducir la mortalidad de los menores de cinco años se ve dificultada por la falta de un sistema que genere información sobre las causas de mortalidad de manera regular. Los métodos aquí utilizados aportan estimaciones a nivel de país a modo de información alternativa para las actividades de planificación en los entornos que carecen de datos suficientes.]]></p></abstract>
</article-meta>
</front><body><![CDATA[ <p align="right"><font size="2" face="Verdana"><b>RESEARCH</b></font></p>     <p>&nbsp;</p>     <p><font size="4" face="verdana"><b><a name="tx"></a>Estimating child mortality    due to diarrhoea in developing countries</b></font></p>     <p>&nbsp;</p>     <p><font size="3" face="verdana"><b>Estimation de la mortalit&eacute; infanto&#45;juv&eacute;nile    due &agrave; la diarrh&eacute;e dans les pays en d&eacute;veloppement</b></font></p>     <p>&nbsp;</p>     <p><font size="3" face="verdana"><b>Mortalidad en la ni&ntilde;ez por diarrea    en los pa&iacute;ses en desarrollo</b></font></p>     <p>&nbsp;</p>     <p>&nbsp;</p>     <p><font size="2" face="Verdana"><b>Cynthia Boschi&#45;Pinto<sup>I,</sup> <a href="#nt"><sup>1</sup></a>;    Lana Velebit<SUP>II</SUP>; Kenji Shibuya<SUP>III</sup></b></font></p>     ]]></body>
<body><![CDATA[<p><font size="2" face="Verdana"><SUP>I</sup>Child and Adolescent Health, World    Health Organization, 20 avenue Appia, 1211 Geneva 27, Switzerland    <br>   <SUP>II</sup>TB/HIV and Drug Resistance, WHO, Geneva, Switzerland    <br>   <SUP>III</sup>Measurement and Health Information Systems, WHO, Geneva, Switzerland</font></p>     <p>&nbsp;</p>     <p>&nbsp;</p> <hr size="1" noshade>     <p><font size="2" face="Verdana"><b>ABSTRACT</b></font></p>     <p><font size="2" face="Verdana"><b>OBJECTIVE:</b> The major objective of this    study is to provide estimates of diarrhoea mortality at country, regional and    global level by employing the Child Health Epidemiology Reference Group (CHERG)    standard.    <br>   <b>METHODS:</b> A systematic and comprehensive literature review was undertaken    of all studies published since 1980 reporting under&#45;5 diarrhoea mortality. Information    was collected on characteristics of each study and its population. A regression    model was used to relate these characteristics to proportional mortality from    diarrhoea and to predict its distribution in national populations.    <br>   <b>FINDINGS:</b> Global deaths from diarrhoea of children aged less than 5 years    were estimated at 1.87 million (95% confidence interval, CI: 1.56&#150;2.19), approximately    19% of total child deaths. WHO African and South&#45;East Asia Regions combined    contain 78% (1.46 million) of all diarrhoea deaths occurring among children    in the developing world; 73% of these deaths are concentrated in just 15 developing    countries.    <br>   <b>CONCLUSION:</b> Planning and evaluation of interventions to control diarrhoea    deaths and to reduce under&#45;5 mortality is obstructed by the lack of a system    that regularly generates cause&#45;of&#45;death information. The methods used here provide    country&#45;level estimates that constitute alternative information for planning    in settings without adequate data.</font></p> <hr size="1" noshade>     ]]></body>
<body><![CDATA[<p><font size="2" face="Verdana"><b>R&Eacute;SUM&Eacute;</b></font></p>     <p><font size="2" face="Verdana"><b>OBJECTIF:</b> Le principal objectif de cette    &eacute;tude est de fournir des estimations de la mortalit&eacute; par diarrh&eacute;e    aux niveaux mondial, r&eacute;gional et national, en utilisant la norme du Groupe    de r&eacute;f&eacute;rence pour l'&eacute;pid&eacute;miologie de la sant&eacute;    de l'enfant (CHERG).    <br>   <b>M&Eacute;THODES:</b> Une revue syst&eacute;matique et exhaustive de la litt&eacute;rature    a &eacute;t&eacute; r&eacute;alis&eacute;e sur l'ensemble des &eacute;tudes    publi&eacute;es depuis 1980 et traitant de la mortalit&eacute; par diarrh&eacute;e    des moins de cinq ans. Des informations ont &eacute;t&eacute; recueillies sur    les caract&eacute;ristiques de chaque &eacute;tude et de sa population. Un mod&egrave;le    par r&eacute;gression a &eacute;t&eacute; utilis&eacute; pour relier ces caract&eacute;ristiques    &agrave; la mortalit&eacute; proportionnelle par diarrh&eacute;e et pour pr&eacute;dire    sa distribution dans les populations nationales.    <br>   <b>R&Eacute;SULTATS:</b> A l'&eacute;chelle mondiale, le nombre de d&eacute;c&egrave;s    par diarrh&eacute;e chez les moins de cinq ans a &eacute;t&eacute; estim&eacute;    &agrave; 1,87 million (intervalle de confiance &agrave; 95 %, IC : 1,56&#45;2,19),    soit approximativement 19 % du nombre total de d&eacute;c&egrave;s d'enfants.    La R&eacute;gion africaine et la R&eacute;gion de l'Asie du Sud&#45;est de l'OMS    totalisent 78 % (1,46 millions) des d&eacute;c&egrave;s par diarrh&eacute;e    se produisant chez les enfants du monde en d&eacute;veloppement et 73 % de ces    d&eacute;c&egrave;s se concentrent dans 15 pays en d&eacute;veloppement seulement.    <br>   <b>CONCLUSION:</b> La planification et l'&eacute;valuation des interventions    pour endiguer la mortalit&eacute; par diarrh&eacute;e et pour r&eacute;duire    la mortalit&eacute; des moins de cinq ans se heurtent &agrave; l'absence de    syst&egrave;me g&eacute;n&eacute;rant r&eacute;guli&egrave;rement des donn&eacute;es    sur les causes de d&eacute;c&egrave;s. Les m&eacute;thodes utilis&eacute;es    dans cette &eacute;tude fournissent des estimations nationales, qui constituent    des donn&eacute;es de substitution pour la planification dans les pays ne disposant    pas de donn&eacute;es appropri&eacute;es.</font></p> <hr size="1" noshade>     <p><font size="2" face="Verdana"><b>RESUMEN</b></font></p>     <p><font size="2" face="Verdana"><b>OBJETIVO:</b> El principal objetivo de este    estudio fue aportar estimaciones de la mortalidad por diarrea a nivel de pa&iacute;s,    regional y mundial aplicando los criterios del Grupo de Referencia en Epidemiolog&iacute;a    de la Salud Infantil (CHERG).    <br>   <b>M&Eacute;TODOS:</b> Se llev&oacute; a cabo una revisi&oacute;n sistem&aacute;tica    y detallada de la bibliograf&iacute;a para identificar todos los estudios publicados    desde 1980 en los que se notificaran cifras de la mortalidad por diarrea entre    los menores de cinco a&ntilde;os. Se reuni&oacute; informaci&oacute;n sobre    las caracter&iacute;sticas de cada estudio y la poblaci&oacute;n estudiada,    y se us&oacute; un modelo de regresi&oacute;n para relacionar esas caracter&iacute;sticas    con la mortalidad proporcional por diarrea y predecir su distribuci&oacute;n    en la poblaci&oacute;n de cada pa&iacute;s.    <br>   <b>RESULTADOS:</b> La mortalidad mundial por diarrea entre la poblaci&oacute;n    menor de cinco a&ntilde;os se estim&oacute; en 1,87 millones (intervalo de confianza    del 95%: 1,56&#150;2,19), lo que supone aproximadamente el 19% de la mortalidad total    en la ni&ntilde;ez. Las regiones de &Aacute;frica y Asia Sudoriental de la OMS    acumulan entre ambas el 78% (1,46 millones) de todas las muertes por diarrea    registradas entre los ni&ntilde;os en el mundo en desarrollo; y el 73% de estas    defunciones se concentran en s&oacute;lo 15 pa&iacute;ses en desarrollo.    <br>   <b>CONCLUSI&Oacute;N:</b> La planificaci&oacute;n y evaluaci&oacute;n de las    intervenciones encaminadas a controlar la mortalidad por diarrea y reducir la    mortalidad de los menores de cinco a&ntilde;os se ve dificultada por la falta    de un sistema que genere informaci&oacute;n sobre las causas de mortalidad de    manera regular. Los m&eacute;todos aqu&iacute; utilizados aportan estimaciones    a nivel de pa&iacute;s a modo de informaci&oacute;n alternativa para las actividades    de planificaci&oacute;n en los entornos que carecen de datos suficientes.</font></p> <hr size="1" noshade>     ]]></body>
<body><![CDATA[<p align="center"><img src="/img/revistas/bwho/v86n9/a15img01.gif"></p> <hr size="1" noshade>     <p>&nbsp;</p>     <p>&nbsp;</p>     <p><font size="3" face="verdana"><b>Introduction</b></font></p>     <p><font size="2" face="Verdana">The Millennium Development Goals (MDGs) were    adopted in 2000 with the aim of reducing the severe gaps between rich and poor    populations. Most countries have endorsed Goal 4 of the MDGs to " <I>reduce    by two thirds</I> &#91;between 1990 and 2015&#93;<I> the mortality rate among children    under&#45;five</I>" .<SUP>1,2</SUP> Reliable information on the magnitude, patterns    and trends of causes of death of children aged less than 5 years helps decision&#45;makers    to assess programmatic needs, prioritize interventions and monitor progress.    It is also crucial for planning and evaluating effectiveness of health services    and interventions. Yet, data are very scarce in low&#45;income settings where they    are most needed and estimations are necessary for these areas.</font></p>     <p><font size="2" face="Verdana">In the 1980s, Snyder and Merson<SUP>3</SUP> generated    one of the earliest attempts to estimate the worldwide burden of diarrhoeal    diseases, demonstrating the substantial health onus due to diarrhoeal diseases    on mortality among children aged less than 5 years. In the following decades,    subsequent reviews updated these initial estimates using similar methods of    assessment.<SUP>4,5</SUP> These initial estimates were based on average values    derived from a limited set of studies without taking into account the epidemiological    variations across different regions. Responding to international demand and    to the need for better evidence&#45;based cause&#45;specific mortality, the Child Health    Epidemiology Reference Group (CHERG) &#150; an independent group of technical experts    jointly coordinated by WHO and the United Nations Children's Fund (UNICEF) &#150;    was established in 2001. CHERG has undertaken a systematic, extensive and comprehensive    literature review of published information and developed a methodological approach    that is transparent and consistent across different diseases and conditions    to produce estimates of the major causes of childhood deaths.<SUP>6&#150;10</SUP>    This study is an essential part of the overall CHERG efforts. Its main objective    is to provide estimates of deaths from diarrhoea in 2004 at all levels, mainly    for countries with incomplete or non&#45;existing civil registration data.</font></p>     <p>&nbsp;</p>     <p><font size="3" face="verdana"><b>Methods</b></font></p>     <p><font size="2" face="Verdana"><b>Data sources</b></font></p>     <p><font size="2" face="Verdana">Common sources of data for cause&#45;specific mortality    include vital registration systems, sample registration systems, nationally    representative household surveys, sentinel Demographic Surveillance Sites (DSS)    or epidemiological studies of cause&#45;specific mortality. In countries that account    for 98% of under&#45;5 deaths worldwide, there is very limited or virtually no functioning    vital registration system in place to support attribution of causes of deaths.<SUP>11&#150;14</SUP>    A sample registration system, which reports causes of death on a regular basis,    is currently available only in China and its coverage and quality for under&#45;5    deaths is challenging.<SUP>15</SUP> Nationally representative household surveys    such as Demographic Health Surveys (DHS) and UNICEF's Multiple Indicator Cluster    Surveys (MICS) do not usually report on causes of death, and DSS data were not    available until very recently.<SUP>16</SUP> Epidemiological studies currently    constitute the main source of data available and were therefore used in this    review for estimating diarrhoea&#45;specific mortality.</font></p>     ]]></body>
<body><![CDATA[<p><font size="2" face="Verdana"><b>Search strategy</b></font></p>     <p><font size="2" face="Verdana">Studies included in the analysis were identified    through a systematic search of the scientific literature published since 1980.    Medline was searched using the terms: " developing countries" , " mortality/death" ,    different spellings of " diarrhoea"  and combinations of these terms.    No restriction was placed on publication language.</font></p>     <p><font size="2" face="Verdana">The search identified a total of 804 papers of    which 207 were kept for review of abstracts. The reference sections of the studies    retrieved were reviewed to identify additional papers. Studies were then assessed    to ensure that they met the main inclusion criteria: (i) direct or derivable    diarrhoea&#45;specific proportional mortality data; (ii) a minimum of 25 total deaths;    (iii) a maximum of 25% of unknown or undetermined causes of death; (iv) community&#45;based    studies with at least 1 year of follow&#45;up; and (v) follow&#45;up time multiple    of 12 months to minimize seasonal effects. Data were abstracted onto standardized    paper forms by two independent abstractors, double&#45;entered into an electronic    database, and validated. <a href="#tab01">Table 1</a> (available at: <a href="http://www.who.int/bulletin/volumes/86/9/07&#45;050054/en/index.html" target="_blank">http://www.who.int/bulletin/volumes/86/9/07&#45;050054/en/index.html</a>)    summarizes the main characteristics of the studies retained for the final analysis.</font></p>     <p><a name="tab01"></a></p>     <p>&nbsp;</p>     <p align="center"><img src="/img/revistas/bwho/v86n9/a15tab01.gif"></p>     <p>&nbsp;</p>     <p><font size="2" face="Verdana"><b>Adjustment of age groups</b></font></p>     <p><font size="2" face="Verdana">As not all studies reported on age ranges that    were suitable for immediate inclusion in the analysis, we developed and applied    a correction algorithm to adjust for age groups. By doing so, all data referred    to the same age group (0&#150;59 months), allowing for the inclusion of a greater    number of studies in the analysis.</font></p>     <p><font size="2" face="Verdana"><b>Proportional mortality model</b></font></p>     ]]></body>
<body><![CDATA[<p><font size="2" face="Verdana">A traditional approach to estimating cause&#45;specific    mortality is to model mortality rates. Instead, we have decided to model proportional    mortality as this is the measure of interest when assessing causes of death    by country. Moreover, as the WHO process for estimating causes of death is based    on the estimation of under&#45;5 mortality level, followed by the allocation of    the causes of under&#45;5 mortality,<SUP>6</SUP> proportional mortality is a more    pertinent outcome that can be used in the completion of the estimation process.</font></p>     <p><font size="2" face="Verdana">We employed a weighted regression model to assess    the relationship between the observed proportion of deaths from diarrhoea and    potential explanatory variables, in an approach similar to those previously    used for estimating proportion of deaths from pneumonia.<SUP>6,10,17</sup></font></p>     <p><font size="2" face="Verdana">Covariates included in the final model were those    available from the studies selected, so that the model could reflect the relationship    more accurately than in the conventional approach of using national averages.    The variables included were: under&#45;5 all&#45;cause mortality and dummy variables    for mid&#45;year of study and for nine WHO subregions.<SUP>18</sup></font></p>     <p><font size="2" face="Verdana">All&#45;cause under&#45;5 mortality was obtained for    the same (or comparable) site from which the proportional diarrhoea mortality    information was derived, as follows: (i) directly abstracted or calculated from    available data in the study (30 studies); (ii) obtained from the authors when    not possible to calculate from published data (three studies); (iii) obtained    from DHS data (11 studies); or (iv) obtained using a method similar to that    used for the adjustment of age groups (three studies). As under&#45;5 mortality    rates were reported in different measures (rates, risks or ratios) in the publications,    we have transformed those provided as mortality rates (<SUB>5</SUB><I>m</I><SUB>0</SUB>)    into a single metric &#150; the probability (risk) of a child dying before reaching    the age of 5 years (<SUB>5</SUB><I>q</I><SUB>0</SUB>).</font></p>     <p><font size="2" face="Verdana">WHO subregions are defined on the basis of levels    of child and adult mortality: A, very low child and very low adult mortality;    B, low child and low adult mortality; C, low child and high adult mortality;    D, high child and high adult mortality; E, high child and very high adult mortality.<SUP>18</SUP>    The nine low&#45; and middle&#45;income subregions included in the model are: African    Region (AFR) D and E; Region of the Americas (AMR) B and D; South&#45;East Asia    Region (SEAR) B and D, Eastern Mediterranean Region (EMR) B and D and Western    Pacific Region (WPR) B.</font></p>     <p><font size="2" face="Verdana">Other potentially important variables considered    for inclusion in the model, such as coverage of oral rehydration therapy, access    to clean water, and health system indicators, were only available for a very    limited number of studies at site level and thus could not be incorporated in    the model.</font></p>     <p><font size="2" face="Verdana">The regression coefficients obtained from the    final model were used to predict the proportion of deaths from diarrhoea at    country level by using national information on under&#45;5 mortality in 2004 and    data for the corresponding subregion. The number of deaths from diarrhoea in    the year 2004 was estimated by applying the model&#45;predicted diarrhoea&#45;proportional    mortality to the number of under&#45;5 deaths in each country. These were then aggregated    to provide subregional, regional, and global (low&#45; and middle&#45;income countries)    estimates. Detailed information on the estimates of all&#45;cause under&#45;5 deaths    can be found elsewhere.<SUP>19</sup></font></p>     <p><font size="2" face="Verdana"><b>Uncertainty analysis</b></font></p>     <p><font size="2" face="Verdana">Uncertainty estimates were generated using the    standard errors obtained from the prediction model and running 10 000 Monte    Carlo simulations.</font></p>     <p>&nbsp;</p>     ]]></body>
<body><![CDATA[<p><font size="3" face="verdana"><b>Results</b></font></p>     <p><font size="2" face="Verdana"><b>Study characteristics</b></font></p>     <p><font size="2" face="Verdana">Of the 68 studies that met the inclusion criteria,    47 were kept in the analysis because they provided data that enabled us to either    abstract or calculate site&#45;specific under&#45;5 mortality rates (<a href="#tab01">Table 1</a>).</font></p>     <p><font size="2" face="Verdana">Seven studies presented data for more than one    point in time, and one study provided data for different study populations,    adding up to 56 data points and representing a total of 210 000 all&#45;cause    deaths and 33 500 diarrhoea deaths. Three data points were from nationally    representative studies, seven from studies carried out in urban settings and    43 (77%) from those carried out in rural areas. This distribution compares well    with that of the rural and urban populations in the countries studied.</font></p>     <p><font size="2" face="Verdana"><a href="#fig01">Fig. 1</a> shows the location    of the 47 studies retained from the literature search, revealing the regional    distribution of study sites as follows: 23 data points (41%) in AFR, 17 (30%)    in SEAR, and 12 (21%) in AMR. There were very few studies or information available    from EMR or WPR. The scarcity of information in these two regions is a fact,    not only for diarrhoea mortality, but for other diseases and conditions as well.<SUP>8,13</sup></font></p>     <p><a name="fig01"></a></p>     <p>&nbsp;</p>     <p align="center"><img src="/img/revistas/bwho/v86n9/a15fig01.gif"></p>     <p>&nbsp;</p>     <p><font size="2" face="Verdana">Studies were distributed around an average mid&#45;surveillance    year of 1990. Two studies were carried out in the 1970s. As for the remaining    54 data points, the mid&#45;year of data collection was between 1980 and 1984 for    14 observations, between 1985 and 1989 for 26 observations and between 1990    and 1994 for 13 observations. Only one study was completely carried out after    1995. In recent years, low&#45;mortality studies were seen more than high&#45;mortality    studies, reflecting the secular downward trend in child mortality that has been    accompanied by a decrease in the proportion of deaths due to diarrhoea. The    age&#45;adjusted (0&#150;59 months) diarrhoea&#45;proportional mortality ranged from 4.6%    in Brazil in 1997<SUP>20</SUP> to 47.7% in Egypt in 1980.<SUP>21</sup></font></p>     ]]></body>
<body><![CDATA[<p><font size="2" face="Verdana"><b>Model specifications</b></font></p>     <p><font size="2" face="Verdana">The final regression model was (standard errors    in brackets):</font></p>     <p><font size="2" face="Verdana">logit(% <I>diarrhoea deaths</I>) = 5.31 +</font></p>     <p><font size="2" face="Verdana">2.38(<I>ln<SUB>5</SUB>q<SUB>0</sub></I>) +    2.01(<I>time</I>) +</font></p>     <p><font size="2" face="Verdana">8.56(<I>subregion</I>)</font></p>     <p><font size="2" face="Verdana">&#91;3.67, 1.02, 0.97, 1.92&#93;</font></p>     <p><font size="2" face="Verdana">where <I>ln<SUB>5</SUB>q<SUB>0</sub></I> is the    natural logarithm of the risk of dying between birth and 5 years in the study    site, <I>time</I> is a dummy variable for mid&#45;year of study (1 for 1990    and after, 0 for before 1990) and <I>subregion</I> is a dummy variable    for WHO subregions (1 for SEAR B and D combined, 0 for the other    subregions). The goodness&#45;of&#45;fit was satisfactory, as reflected by the <I>R</I>²    of 0.60. There was no systematic deviation among the residual.</font></p>     <p><font size="2" face="Verdana"><b>External validation</b></font></p>     <p><font size="2" face="Verdana">A simple validation technique that is commonly    used is to compare the model outputs with empirical data other than those used    in the model. We searched the latest data from DHS and other nationally representative    surveys in which verbal autopsy was used to obtain information on causes of    death among children aged less than 5 years. We have identified three recently    published surveys with available information from Bangladesh (DHS 2005),<SUP>22</SUP>    Cambodia (DHS 2005)<SUP>23</SUP> and Liberia (Food Security and Nutritional    Survey 2006).<SUP>24</SUP> The difference in cause categories made direct comparison    difficult, particularly for Bangladesh and Cambodia. The only comparable data    set was that from Liberia where the model&#45;based estimate and empirically observed    figure for the proportion of diarrhoea deaths were 15.9% (95% CI: 12.4&#150;19.3)    and 16.1%, respectively. This is not sufficient to validate the entire set of    extrapolations but it does illustrate the performance of our method in countries    where a vital registration system does not exist or is incomplete.</font></p>     <p><font size="2" face="Verdana"><b>Subregional, regional and global estimates</b></font></p>     ]]></body>
<body><![CDATA[<p><font size="2" face="Verdana">Estimates of diarrhoea&#45;proportional mortality    for nine low&#45;and middle&#45;income WHO subregions are shown in <a href="#tab02">Table 2</a>,    together with point estimates of the number of deaths due to diarrhoea and corresponding    uncertainty ranges. The model&#45;based global point estimate of 1.87 million (uncertainty    range: 1.56&#150;2.19) diarrhoea deaths corresponds to nearly 19% of the 10 million    under&#45;5 deaths that occurred in the world in 2004.<SUP>14</SUP> AFR and SEAR    assemble together 78% (1.46 million) of all diarrhoea deaths occurring in the    developing world (<a href="#fig02">Fig. 2</a>).</font></p>     <p><a name="tab02"></a></p>     <p>&nbsp;</p>     <p align="center"><img src="/img/revistas/bwho/v86n9/a15tab02.gif"></p>     <p>&nbsp;</p>     <p><a name="fig02"></a></p>     <p>&nbsp;</p>     <p align="center"><img src="/img/revistas/bwho/v86n9/a15fig02.gif"></p>     <p>&nbsp;</p>     <p><font size="2" face="Verdana">SEAR D suffers the highest average burden    of diarrhoea&#45;proportional mortality (25%) as well as highest numbers of death    (651 000 diarrhoea deaths). It follows AFR D (402 000 deaths),    AFR E (365 000 deaths), and EMR D (221 000). In SEAR B,    AFR D, and AFR E, the median of diarrhoea&#45;proportional mortality is    around 17%. The lowest proportions and numbers of death were observed in the    low child mortality region of the Americas (AMR B) and in EMR B.</font></p>     ]]></body>
<body><![CDATA[<p><font size="2" face="Verdana"><b>Country estimates</b></font></p>     <p><font size="2" face="Verdana"><a href="#tab03">Table 3</a> shows the top    15 countries ranked according to the number of under&#45;5 deaths due to diarrhoeal    diseases. These 15 countries account for 73% of all under&#45;5 diarrhoeal deaths    occurring worldwide. India alone is responsible for more than half a million    diarrhoeal deaths.</font></p>     <p><a name="tab03"></a></p>     <p>&nbsp;</p>     <p align="center"><img src="/img/revistas/bwho/v86n9/a15tab03.gif"></p>     <p>&nbsp;</p>     <p><font size="3" face="verdana"><b>Discussion</b></font></p>     <p><font size="2" face="Verdana">Despite several attempts to estimate mortality    from diarrhoea over the past decades and in recent years, the uncertainty surrounding    its current level remains quite high. This occurs partly because of the lack    in quality and number of available data and partly because of the lack of consistency    in methods. We systematically reviewed studies that provided child cause&#45;specific    mortality published since 1980 and employed a rigorous and transparent approach    to estimate current country, regional, and global diarrhoea mortality.</font></p>     <p><font size="2" face="Verdana"><b>Recent estimates</b></font></p>     <p><font size="2" face="Verdana">Two recent studies presented global estimates    of child deaths due to diarrhoea that were equal to 2.5 million<SUP>5</SUP>    and 2.1 million.<SUP>25</SUP> A third review has estimated that 22% of all deaths    among under&#45;5s in sub&#45;Saharan Africa and 23% in south Asia were caused by diarrhoeal    diseases in the year 2000.<SUP>8</sup></font></p>     ]]></body>
<body><![CDATA[<p><font size="2" face="Verdana">The point estimate in our study resulted in 1.87    million deaths with an uncertainty range of 1.56 and 2.19 million deaths. These    results are slightly lower than those calculated in the three other recent reviews.    The main reasons for the differences encountered between this study and those    by Kosek et al.<SUP>5</SUP> and Parashar et al.<SUP>25</SUP> are most probably    due to the different data and methods employed.</font></p>     <p><font size="2" face="Verdana">In the present study, we performed a thorough    literature review and took advantage of best available data to adjust for age,    time, all&#45;cause under&#45;5 mortality, and regional mortality strata. Our approach    has four major advantages when compared to earlier estimates. First, the method    used here is transparent with all data sources available on the web. In addition,    it is consistent with the CHERG systematic review protocol and comparable to    the method used across different causes of under&#45;5 deaths.<SUP>6&#150;10</SUP> Second,    the adjustment for age groups had not been previously used in the estimation    of deaths from diarrhoea and has enabled the inclusion of a larger number of    data points in the analysis. Third, our study did not assume that the locations    where studies were carried out were representative of the whole country. The    use of local covariates to relate to proportional diarrhoea mortality and the    use of national level variables to extrapolate estimates to national levels    is intended to provide a correction for this common biased assumption. Finally,    our approach enables estimation of diarrhoea mortality at country level, not    just of regional averages.</font></p>     <p><font size="2" face="Verdana">The method employed in our study is closer to    that used by Morris et al.,<SUP>8</SUP> also developed within CHERG.One of the    possible reasons for the somewhat lower estimates calculated in our analysis    are the different sources of data. We have included 57 data points in our analysis    as opposed to the 38 included in the review by Morris et al., mostly from sub&#45;Saharan    Africa and south Asia. In our review, there is a larger number of studies from    the Americas, where the proportions of deaths due to diarrhoea are lower than    in sub&#45;Saharan Africa and south Asia. Other likely reasons for the differences    are the different covariates included for modelling and the different models    employed, which have diverse assumptions and statistical properties. It is worth    noting that the multicause model has also provided higher estimates for the    proportion of malaria deaths in sub&#45;Saharan Africa (24%) than the 18% estimated    by the single&#45;cause model proposed by Rowe et al.<SUP>9</SUP> Besides, the all&#45;cause    model has not taken into account the high proportion of HIV mortality in the    AFR E subregion. It is likely that this may have resulted in an overestimation    of the proportion of the other causes of death.</font></p>     <p><font size="2" face="Verdana"><b>Limitations</b></font></p>     <p><font size="2" face="Verdana">There are some limitations intrinsic to the type    of review and meta&#45;analysis used in our assessment. Locations where special    population studies are conducted are rarely representative of the entire countries    as they are usually carried out in populations that are either easy to access    or have atypical mortality patterns. However, using local variables in the model    and national level variables to predict country estimates should account, at    least in part, for this potential site bias.</font></p>     <p><font size="2" face="Verdana">The inclusion of mid&#45;year of study in the model    could be seen as reflecting both time and place of study as studies conducted    in different years could also be from different places. Yet, time distribution    of the studies within each region is very similar. Furthermore, the use of a    dichotomous dummy variable for controlling for time in the regression model    makes them equivalent for all countries.</font></p>     <p><font size="2" face="Verdana">Our estimates, as well as those obtained from    other reviews, rely on published epidemiological studies that used mostly verbal    autopsy methods in their assessment of causes of death. Consequently, they have    limitations that are inherent to this type of data such as misclassification    of causes of death due to imperfect sensitivity and specificity of the instrument.    Misclassification of causes of death is likely to be random; therefore it does    not necessarily imply that the distribution of these causes will be biased.    We have not attempted to correct for the possible measurement errors introduced    by the use of verbal autopsy<SUP>26,27</SUP> because there was not enough site&#45;specific    information from validation studies to enable an adequate adjustment.<SUP>27</sup></font></p>     <p><font size="2" face="Verdana">It is also worth noting that most (68%) of the    data used in this review refer to studies that were carried out between the    late 1980s and early 1990s and that the latest mid&#45;year of observation was 1997.    This represents a lag time of almost 10 years. Currently, available data are    unable to capture possible recent changes in diarrhoea mortality either due    to changes in interventions, their coverage, or new emerging diseases and competing    causes of death, with the exception of HIV/AIDS which is captured by the use    of subregional levels of mortality.</font></p>     <p><font size="2" face="Verdana"><b>Public health implications</b></font></p>     <p><font size="2" face="Verdana">Estimates obtained here can be used as the starting    point for the monitoring of cause of death at country, regional and global levels    in the future. Clearly, such estimates do not replace empirical data. Nevertheless,    they are an invaluable tool for guiding decision&#45;making and prioritizing interventions    in child health strategies and planning in countries where vital registration    or other sources of community&#45;based data on causes of death are not available.    Importantly, such an estimation process is exceptionally useful for identifying    gaps in information and for developing approaches to tackling data problems.</font></p>     ]]></body>
<body><![CDATA[<p>&nbsp;</p>     <p><font size="3" face="Verdana"><b>Conclusion</b></font></p>     <p><font size="2" face="Verdana">Information on causes of death for children aged    less than 5 years has not increased significantly since the late 1980s. The    lack of systems able to generate representative quality data on a regular basis    is one of the major obstacles for international and national planning to reduce    under&#45;5 mortality. By providing best possible estimates of the distribution    of causes of death, CHERG methods have proven to be a transient alternative    to countries without adequate information. The main CHERG standards for estimating    the burden of mortality, used in this review include: (i) thorough literature    search; (ii) data abstraction exercise performed by two independent data abstractors    and with two independent data entries; (iii) very strict inclusion and exclusion    criteria; and (iv) use of local covariates to predict national estimates. We    strongly believe that these rigorous criteria ensured that inputs for the current    estimates consisted of the most valid information available and that the modelling    of local variables to predict national estimates was performed using an innovative    and best possible approach. Results presented here should thus allow settings    without adequate information to draw a reasonable picture of the burden of under&#45;5    diarrhoea mortality that should ultimately result in practical planning for    the prioritization of interventions and decision&#45;making. <img src="/img/revistas/bwho/v86n9/a02qdr_lar.jpg" align="absmiddle"></font></p>     <p><font size="2" face="verdana"><b>Acknowledgements</b></font></p>     <p><font size="2" face="Verdana">This work was done through CHERG, coordinated    by the Department of Child and Adolescent Health and Development and supported    by the Department of Measurement and Health Information Systems of WHO. We thank    Bob Black and members of CHERG for their critical review of the methods. We    thank Colin Mathers, Doris Ma Fat and Mie Inoue for providing data related to    the WHO mortality database. We also thank Cesar Victora and Bernardo Horta for    providing additional data from their cohort study.</font></p>     <p><font size="2" face="Verdana"><B>Funding:</b> The Bill and Melinda Gates Foundation    provided financial support for the work of CHERG.</font></p>     <p><font size="2" face="Verdana"><B>Competing interests:</b> None declared.</font></p>     <p>&nbsp;</p>     <p><font size="3" face="verdana"><b>References</b></font></p>     <!-- ref --><p><font size="2" face="Verdana">1. <I>United Nations Millennium Declaration 2000</i>.    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Morbidity pattern and cause specific mortality during infancy in ICDS projects.    <I>J Trop Pediatr</I> 1987;33:190&#45;3. PMID:3669135</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=269407&pid=S0042-9686200800090001500073&lng=','','width=640,height=500,resizable=yes,scrollbars=1,menubar=yes,');">Links</a>&#160;]<!-- end-ref --><!-- ref --><p><font size="2" face="Verdana">74. Huang W, Yu H, Wang F, Li G. Infant mortality    among various nationalities in the middle part of Guizhou, China. <I>Soc Sci    Med</I> 1997;45:1031&#45;40. PMID:9257395 doi:10.1016/S0277&#45;9536(97)00019&#45;1</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=269408&pid=S0042-9686200800090001500074&lng=','','width=640,height=500,resizable=yes,scrollbars=1,menubar=yes,');">Links</a>&#160;]<!-- end-ref --><p>&nbsp;</p>     <p>&nbsp;</p>     <p><font size="2" face="Verdana">(<i>Submitted: 19 November 2007 &#150; Revised    version received: 30 November 2007 &#150; Accepted: 4 December 2007 &#150; Published    online: 30 May 2008</i>)</font></p>     <p>&nbsp;</p>     <p>&nbsp;</p>     <p><font size="2" face="Verdana"><a name="nt"></a><a href="#tx">1</a> Correspondence    to Cynthia Boschi&#45;Pinto (e&#45;mail: <a href="mailto:pintoc@who.int">pintoc@who.int</a>).    ]]></body>
<body><![CDATA[<br>   doi:10.2471/BLT.07.050054</font></p>      ]]></body><back>
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