Estimating child mortality due to diarrhoea in developing countries

710 Bulletin of the World Health Organization | September 2008, 86 (9) Estimating child mortality due to diarrhoea in developing countries Cynthia Boschi-Pinto,a Lana Velebit b & Kenji Shibuya c 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. Bulletin of the World Health Organization 2008;86:710–717. Une traduction en français de ce résumé figure à la fin de l’article. Al final del artículo se facilita una traducción al español. .ةلاقلما هذهل لماكلا صنلا ةياهن في ةصلاخلا هذهل ةيبرعلا ةمجترلا a Child and Adolescent Health, World Health Organization, 20 avenue Appia, 1211 Geneva 27, Switzerland. b TB/HIV and Drug Resistance, WHO, Geneva, Switzerland. c Measurement and Health Information Systems, WHO, Geneva, Switzerland. Correspondence to Cynthia Boschi-Pinto (e-mail: pintoc@who.int). doi:10.2471/BLT.07.050054 (Submitted: 19 November 2007 – Revised version received: 30 November 2007 – Accepted: 4 December 2007 – Published online: 30 May 2008 ) Introduction The Millennium Development Goals (MDGs) were adopted in 2000 with the aim of reducing the severe gaps be- tween rich and poor populations. Most countries have endorsed Goal 4 of the MDGs to “reduce by two thirds [between 1990 and 2015] the mortality rate among children under-five”.1,2 Reliable informa- tion on the magnitude, patterns and trends of causes of death of children aged less than 5 years helps decision-makers to assess programmatic needs, prioritize interventions and monitor progress. It is also crucial for planning and evaluat- ing effectiveness of health services and interventions. Yet, data are very scarce in low-income settings where they are most needed and estimations are neces- sary for these areas. In the 1980s, Snyder and Merson3 generated one of the earliest attempts to estimate the worldwide burden of diarrhoeal diseases, demonstrating the substantial health onus due to diar- rhoeal diseases on mortality among children aged less than 5 years. In the following decades, subsequent reviews updated these initial estimates us- ing similar methods of assessment.4,5 These initial estimates were based on average values derived from a limited set of studies without taking into ac- count the epidemiological variations across different regions. Responding to international demand and to the need for better evidence-based cause-specific mortality, the Child Health Epidemiol- ogy Reference Group (CHERG) – an independent group of technical experts jointly coordinated by WHO and the United Nations Children’s Fund (UNICEF) – 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.6–10 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-existing civil registration data. Methods Data sources Common sources of data for cause-spe- cific mortality include vital registration systems, sample registration systems, nationally representative household surveys, sentinel Demographic Surveil- lance Sites (DSS) or epidemiological studies of cause-specific mortality. In countries that account for 98% of un- der-5 deaths worldwide, there is very limited or virtually no functioning vital registration system in place to support attribution of causes of deaths.11–14 A sample registration system, which re- ports causes of death on a regular basis, is currently available only in China and its coverage and quality for under-5 deaths is challenging.15 Nationally representative household surveys such as Demographic Health Surveys (DHS) and UNICEF’s Multiple Indicator Research Child mortality due to diarrhoea in developing countries 711Bulletin of the World Health Organization | September 2008, 86 (9) Cynthia Boschi-Pinto et al. Cluster Surveys (MICS) do not usu- ally report on causes of death, and DSS data were not available until very recently.16 Epidemiological studies cur- rently constitute the main source of data available and were therefore used in this review for estimating diarrhoea- specific mortality. Search strategy Studies included in the analysis were identified through a systematic search of the scientific literature published since 1980. Medline was searched us- ing the terms: “developing countries”, “mortality/death”, different spellings of “diarrhoea” and combinations of these terms. No restriction was placed on publication language. The search identified a total of 804 papers of which 207 were kept for re- view 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-specific propor- tional mortality data; (ii) a minimum of 25 total deaths; (iii) a maximum of 25% of unknown or undetermined causes of death; (iv) community-based studies with at least 1 year of follow-up; and (v) follow-up time multiple of 12 months to minimize seasonal effects. Data were abstracted onto standard- ized paper forms by two independent abstractors, double-entered into an electronic database, and validated. Table 1 (available at: http://www.who. int/bulletin/volumes/86/9/07-050054/ en/index.html) summarizes the main characteristics of the studies retained for the final analysis. Adjustment of age groups As not all studies reported on age ranges that were suitable for immediate inclu- sion 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 (0–59 months), allowing for the inclusion of a greater number of studies in the analysis. Proportional mortality model A traditional approach to estimating cause-specific mortality is to model mortality rates. Instead, we have de- cided to model proportional mortality as this is the measure of interest when assessing causes of death by country. Moreover, as the WHO process for es- timating causes of death is based on the estimation of under-5 mortality level, followed by the allocation of the causes of under-5 mortality,6 proportional mortality is a more pertinent outcome that can be used in the completion of the estimation process. We employed a weighted regres- sion 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.6,10,17 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 vari- ables included were: under-5 all-cause mortality and dummy variables for mid-year of study and for nine WHO subregions.18 All-cause under-5 mortality was obtained for the same (or comparable) site from which the proportional diar- rhoea mortality information was de- rived, as follows: (i) directly abstracted or calculated from available data in the study (30 studies); (ii) obtained from the authors when not possible to cal- culate from published data (three stud- ies); (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-5 mortality rates were reported in differ- ent measures (rates, risks or ratios) in the publications, we have transformed those provided as mortality rates (5m0) into a single metric – the probability (risk) of a child dying before reaching the age of 5 years (5q0). 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.18 The nine low- and middle-income subregions included in the model are: African Region (AFR) D and E; Region of the Americas (AMR) B and D; South-East Asia Region (SEAR) B and D, Eastern Mediterranean Region (EMR) B and D and Western Pacific Region (WPR) B. Other potentially important vari- ables considered for inclusion in the model, such as coverage of oral rehy- dration 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. The regression coefficients obtained from the final model were used to pre- dict the proportion of deaths from diar- rhoea at country level by using national information on under-5 mortality in 2004 and data for the corresponding subregion. The number of deaths from diarrhoea in the year 2004 was esti- mated by applying the model-predicted diarrhoea-proportional mortality to the number of under-5 deaths in each country. These were then aggregated to provide subregional, regional, and global (low- and middle-income coun- tries) estimates. Detailed information on the estimates of all-cause under-5 deaths can be found elsewhere.19 Uncertainty analysis Uncertainty estimates were generated using the standard errors obtained from the prediction model and running 10 000 Monte Carlo simulations. Results Study characteristics Of the 68 studies that met the inclusion criteria, 47 were kept in the analysis because they provided data that en- abled us to either abstract or calculate site-specific under-5 mortality rates (Table 1). 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-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. Fig. 1 shows the location of the 47 studies retained from the literature search, revealing the regional distribu- tion of study sites as follows: 23 data points (41%) in AFR, 17 (30%) in SEAR, and 12 (21%) in AMR. There 712 Bulletin of the World Health Organization | September 2008, 86 (9) Research Child mortality due to diarrhoea in developing countries Cynthia Boschi-Pinto et al. 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.8,13 Studies were distributed around an average mid-surveillance year of 1990. Two studies were carried out in the 1970s. As for the remaining 54 data points, the mid-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-mortal- ity studies were seen more than high- mortality studies, reflecting the secular downward trend in child mortality that has been accompanied by a decrease in the proportion of deaths due to diar- rhoea. The age-adjusted (0–59 months) diarrhoea-proportional mortality ranged from 4.6% in Brazil in 199720 to 47.7% in Egypt in 1980.21 Model specifications The final regression model was (stan- dard errors in brackets): logit(% diarrhoea deaths) = 5.31 + 2.38(ln5q0) + 2.01(time) + 8.56(subregion) [3.67, 1.02, 0.97, 1.92] where ln5q0 is the natural logarithm of the risk of dying between birth and 5 years in the study site, time is a dummy variable for mid-year of study (1 for 1990 and after, 0 for before 1990) and subregion is a dummy variable for WHO subregions (1 for SEAR B and D combined, 0 for the other subregions). The goodness-of-fit was satisfactory, as reflected by the R² of 0.60. There was no systematic deviation among the residual. External validation 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 re- cently published surveys with available information from Bangladesh (DHS 2005),22 Cambodia (DHS 2005)23 and Liberia (Food Security and Nutritional Survey 2006).24 The difference in cause categories made direct comparison dif- ficult, particularly for Bangladesh and Cambodia. The only comparable data set was that from Liberia where the model-based estimate and empirically observed figure for the proportion of diarrhoea deaths were 15.9% (95% CI: 12.4–19.3) and 16.1%, respec- tively. 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. Subregional, regional and global estimates Estimates of diarrhoea-proportional mortality for nine low-and middle- income WHO subregions are shown in Table 2, together with point estimates of the number of deaths due to diar- rhoea and corresponding uncertainty ranges. The model-based global point estimate of 1.87 million (uncertainty range: 1.56–2.19) diarrhoea deaths corresponds to nearly 19% of the 10 Fig. 1. Distribution of epidemiological studies used in the analysis Diarrhoea - morbidity Diarrhoea - mortality Vital registration system coverage > 90% The Gambia Source : ref 13. Research Child mortality due to diarrhoea in developing countries 713Bulletin of the World Health Organization | September 2008, 86 (9) Cynthia Boschi-Pinto et al. million under-5 deaths that occurred in the world in 2004.14 AFR and SEAR assemble together 78% (1.46 million) of all diarrhoea deaths occurring in the developing world (Fig. 2). SEAR D suffers the highest aver- age burden of diarrhoea-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- 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. Country estimates Table 3 shows the top 15 countries ranked according to the number of under-5 deaths due to diarrhoeal dis- eases. These 15 countries account for 73% of all under-5 diarrhoeal deaths occurring worldwide. India alone is responsible for more than half a million diarrhoeal deaths. Discussion Despite several attempts to estimate mortality from diarrhoea over the past decades and in recent years, the un- certainty surrounding its current level remains quite high. This occurs partly because of the lack in quality and num- ber of available data and partly because of the lack of consistency in methods. We systematically reviewed studies that Table 2. Estimates of diarrhoea deaths among children aged less than 5 years in low- and middle-income regions of the world, 2004 WHO region Mortality stratuma Average of diarrhoea-proportional mortality (%) Estimated diarrhoea deaths (thousands) Uncertainty ranges (thousands) African (AFR) D 17.8 402 346–455 E 17.5 365 315–413 Americas (AMR) B 13.3 35 30–40 D 14.9 14 12–16 Eastern Mediter- ranean (EMR) B 13.4 12 10–14 D 16.9 221 190–250 South-East Asia (SEAR) B 22.3 44 34–53 D 24.5 651 500–793 Western Pacific (WPR) B 13.8 105 90–118 World 18.7 1870 1558–2193 a 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. Fig. 2. Distribution of deaths due to diarrhoea in low- and middle-income countries in 5 WHO regions African South-East Asia Eastern Mediter- ranean Western Pacific W HO re gi on 0 Diarrhoea deaths (%) Americas 10 20 30 40 50 provided child cause-specific mortality published since 1980 and employed a rigorous and transparent approach to estimate current country, regional, and global diarrhoea mortality. Recent estimates Two recent studies presented global es- timates of child deaths due to diarrhoea that were equal to 2.5 million5 and 2.1 million.25 A third review has estimated that 22% of all deaths among under-5s in sub-Saharan Africa and 23% in south Asia were caused by diarrhoeal diseases in the year 2000.8 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.5 and Parashar et al.25 are most probably due to the different data and methods employed. In the present study, we performed a thorough literature review and took advantage of best available data to adjust for age, time, all-cause under-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-5 deaths.6–10 Second, the adjust- ment 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 714 Bulletin of the World Health Organization | September 2008, 86 (9) Research Child mortality due to diarrhoea in developing countries Cynthia Boschi-Pinto et al. Table 3. Countries accounting for three-quarters of deaths due to diarrhoea in the developing regions of the world, 2004 Country WHO subregiona Deaths due to diarrhoea (thousands) India SEAR D 535 Nigeria AFR D 175 Democratic Republic of the Congo AFR E 95 Ethiopia AFR E 86 Pakistan EMR D 77 China WPR B 74 Bangladesh SEAR D 69 Afghanistan EMR D 65 Indonesia SEAR B 39 Angola AFR D 34 Niger AFR D 33 Uganda AFR E 28 Myanmar SEAR D 26 United Republic of Tanzania AFR E 25 Mali AFR D 24 Total of 15 countries 1384 AFR, WHO African Region; AMR, WHO Region of the Americas; EMR, WHO Eastern Mediterranean Region; SEAR, WHO South-East Asia Region; WPR, Western Pacific Region. a 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. is intended to provide a correction for this common biased assumption. Finally, our approach enables estima- tion of diarrhoea mortality at country level, not just of regional averages. The method employed in our study is closer to that used by Morris et al.,8 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-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-Saharan Africa and south Asia. Other likely reasons for the dif- ferences are the different covariates included for modelling and the dif- ferent 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-Saharan Africa (24%) than the 18% estimated by the single-cause model proposed by Rowe et al.9 Besides, the all-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. Limitations There are some limitations intrinsic to the type of review and meta-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 pat- terns. However, using local variables in the model and national level variables to predict country estimates should ac- count, at least in part, for this potential site bias. The inclusion of mid-year of study in the model could be seen as reflecting both time and place of study as stud- ies 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 regres- sion model makes them equivalent for all countries. 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. Misclas- sification of causes of death is likely to be random; therefore it does not nec- essarily 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 autopsy26,27 because there was not enough site-specific informa- tion from validation studies to enable an adequate adjustment.27 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-year of observa- tion 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. Public health implications 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 invalu- able tool for guiding decision-making and prioritizing interventions in child health strategies and planning in coun- tries where vital registration or other sources of community-based data on causes of death are not available. Im- portantly, such an estimation process is exceptionally useful for identifying gaps in information and for developing approaches to tackling data problems. Conclusion 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 Research Child mortality due to diarrhoea in developing countries 715Bulletin of the World Health Organization | September 2008, 86 (9) Cynthia Boschi-Pinto et al. Résumé Estimation de la mortalité infanto-juvénile due à la diarrhée dans les pays en développement 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. Resumen Mortalidad en la niñez por diarrea en los países en desarrollo 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. on a regular basis is one of the major obstacles for international and national planning to reduce under-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 es- timates. 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 per- formed using an innovative and best possible approach. Results presented here should thus allow settings without adequate information to draw a reason- able picture of the burden of under-5 diarrhoea mortality that should ulti- mately result in practical planning for the prioritization of interventions and decision-making. ■ Acknowledgements 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 provid- ing data related to the WHO mortality database. 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PMID:8100345 doi:10.1016/0140-6736(93)91879-Q صخلم ةيمانلا نادلبلا في لاهسلإا نع ةمجانلا لافطلأا تايفو ل َّدعم ريدقت ل َّدعلم تاريدقت لىع لوصحلا لولأا ماقلما في ةساردلا هذه تفدهتسا :ضرغلا ،يلماعلاو يميلقلإاو يرطقلا ىوتسلما لىع لاهسلإا نع ةمجانلا تايفولا .لفطلا ةحص تايئابول ةيعجرلما ةعومجلما رايعم مادختساب ذنم تَ ِرشُن يتلا تاساردلا عيمجل ةلماشو ةيجهنم ةعجارم تيرُجأ :ةقيرطلا .لاهسلإا ببسب ةسماخلا نس نود مه نيذلا لافطلأا تايفو لوح 1980 ماع مدخُتساو .اهيف ينكراشلما ددعو ةسارد لك صئاصخ لوح تامولعم تَع ِرمُجو نع ةمجانلا تايفولا ةبسن ينبو صئاصخلا هذه ينب طبرلل ف ُّوحتلل جذونم .ةينطولا ةيناكسلا تائفلا في هذه تايفولا ةبسن عُّزوتب ؤُّبنتللو ،لاهسلإا ببسب ،ةسماخلا نس نود مه نيذلا ،لافطلأا تايفو تر ِّدُق :تادوجولما ،%95 ةقث ةلصافب( لفط نويلم 1.87 وحنب ،يلماعلا ديعصلا لىع ،لاهسلإا تايفو عيمج نم %19 ددعلا اذه لِّثيمو ،)2.19 لىإ 1.56 نم تحوارت ذإ %78 ةبسنب ًاعم ايسآ قشر بونج ميلقإو يقيرفلأا ميلقلإا رثأتساو .لافطلأا لماعلا في لاهسلإا نع ةمجانلا لافطلأا تايفو عيمج نم )لفط نويلم 1.46( .ًايمان ًادلب 15 في تايفولا هذه نم %73 تز َّكرتو ؛يمانلا تايفولا ةحفاكم لىإ ةيمارلا ،ميـيقتلاو طيطختلا تلاخادم ضَّرعتت :جاتنتسلاا ،ةسماخلا نس نود مه نيذلا لافطلأا تايفو ضفخ لىإو لاهسلإا نع ةمجانلا لوح ةمظتنم تامولعم ديلوت لىع رداق ماظن لىإ راقتفلاا ببسب ليقارعلل ةيرطق تاريدقت ةساردلا هذه في ةمدختسلما ةقيرطلا م ِّدقتو .ةافولا بابسأ .ةيفاكلا تايطعلما لىإ رقتفت يتلا نكاملأا في طيطختلل ةليدب تامولعم لِّثتم Research Child mortality due to diarrhoea in developing countries 717Bulletin of the World Health Organization | September 2008, 86 (9) Cynthia Boschi-Pinto et al. 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PMID:9257395 doi:10.1016/S0277-9536(97)00019-1 Research Child mortality due to diarrhoea in developing countries ABulletin of the World Health Organization | September 2008, 86 (9) Cynthia Boschi-Pinto et al. Table 1. Main characteristics of the studies included in the analysis Reference Country Site WHO subregiona Period of studyb No. of under-5 deaths Proportion of diarrhoea deathsc (%) 28 Sierra Leone Rural areas of the districts of western Area and Porto Loko AFR D 1988–93 251 12.7 29 Liberia Robertsport and Bomi – urban areas; Grand Mountain and part of Lofa counties – rural areas AFR D 1984–85 414 13.7 29 Liberia Robertsport and Bomi – urban areas; Grand Mountain and part of Lofa counties – rural areas AFR D 1986–88 491 12.1 30 Gambia Upper River Division – rural area AFR D 1988–89 856 18.0 31 Senegal Pikine-Guédiawaye – urban suburb of Dakar AFR D 1983 42 26.2 32 Ghana Kassena-Nankana District AFR D 1989–91 685 29.7 33 Gambia Rural area AFR D 1982 150 16.3 34 Gambia Rural area AFR D 1984–86 171 15.8 34 Gambia Rural area AFR D 1985 316 26.7 35 Gambia Upper River Division – rural area AFR D 1989–93 3 776 9.3 36 Nigeria Akoko North AFR D 1987 120 32.5 37 Guinea-Bissau Bandim – urban area AFR D 1987–90 153 32.2 38 Senegal Mlomp – rural area in Ziguinchor region AFR D 1987 69 20.3 39 Senegal Niakhar district AFR D 1986 1 517 35.0 40 Democratic Republic of the Congo Kivu – rural area AFR E 1986–87 358 8.4 41 Burundi Nyanza-Lac district – rural area AFR E 1990–91 160 19.7 42 Central African Republic Bangui city – urban area AFR E 1983 188 19.1 43 South Africa Rural area AFR E 1994 156 38.9 44 United Republic of Tanzania Bagamoyo district – rural area AFR E 1983–84 325 16.9 44 United Republic of Tanzania Bagamoyo district – rural area AFR E 1985 347 12.7 45 United Republic of Tanzania Bagamoyo district – rural area AFR E 1987 596 14.8 46 Ethiopia Butajira district – rural lowlands and highlands; urban highland AFR E 1988 436 8.7 47 Zambia Lusaka – Lima Ward AFR E 1985 26 18.2 48 Mexico Nationally representative AMR B 1990 85 957 16.3 48 Mexico Nationally representative AMR B 1993 50 492 12.8 49 Brazil S. Paulo, metropolitan area – urban area AMR B 1980–82 … 11.7 49 Brazil S. Paulo, metropolitan area – urban area AMR B 1996–98 … 4.6 50 Brazil Trairi, Ceará – rural area AMR B 1984–85 101 32.0 51 Brazil Ceará – three municipalities in rural areas AMR B 1993–94 215 39.1 52 Brazil Pelotas city – urban area AMR B 1982–83 244 11.9 53 Brazil S. Luis capital city, Maranhão – three urban areas AMR B 1989 32 44.0 53 Brazil S. Luis capital city, Maranhão – three urban areas AMR B 1986 92 46.0 54 Brazil Pelotas city – urban area AMR B 1985 29 20.0 55 Brazil State of Rio Grande do Sul – two-thirds of urban population AMR B 1976 40 219 14.7 B Bulletin of the World Health Organization | September 2008, 86 (9) Research Child mortality due to diarrhoea in developing countries Cynthia Boschi-Pinto et al. Reference Country Site WHO subregiona Period of studyb No. of under-5 deaths Proportion of diarrhoea deathsc (%) 56 Brazil Pelotas city – urban area AMR B 1983 215 10.6 57 Somalia Two rural communities EMR D 1988 88 27.5 58 Pakistan Abbottabad district – rural area EMR D 1986 46 23.9 59 Egypt Menoufia governorate – rural area EMR D 1980 174 47.7 60 Indonesia Banyuasin district – five villages in rural area SEAR B 1983 51 21.6 61 India Ballabgarth, Haryana state – rural area SEAR D 1982–84 385 29.1 61 India Ballabgarth, Haryana state – rural area SEAR D 1992–94 221 25.3 62 India Lucknow – urban slums SEAR D 1993–94 71 18.3 63 India Gadchiroli district – rural area SEAR D 1988–89 161 11.1 64 India Jawan – nine villages in rural area SEAR D 1989 64 30.4 39 India Ballabgarh – rural area SEAR D 1989 811 18.0 65 Bangladesh Nationally representative SEAR D 1989–93 828 14.7 66 Bangladesh Nationally representative SEAR D 1992–96 678 15.5 67 Bangladesh Matlab – rural area SEAR D 1982–83 926 9.9 68 Bangladesh Matlab – rural community SEAR D 1975–77 7 858 26.7 69 Bangladesh Matlab – rural community SEAR D 1986–87 1 354 51.1 70 India Trichy district SEAR D 1985 80 41.8 71 Nepal Jumla district – mountainous rural area SEAR D 1988 2 101 42.2 72 India Rural area of Haryana SEAR D 1986 281 19.9 73 India Six rural and three urban areas representing eight major states SEAR D 1984 241 30.8 39 Bangladesh Matlab – rural area SEAR D 1989 1 573 15.0 74 China Guizhou province – three counties in a remote mountainous province WPR B 1986 3 075 10.0 AFR, WHO African Region; AMR, WHO Region of the Americas; EMR, WHO Eastern Mediterranean Region; SEAR, WHO South-East Asia Region; WPR, Western Pacific Region. a 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. b Some studies did not report mid-year of study and those have been either informed by contacting authors or approximately estimated from other available information in the study. c Proportion of diarrhoea deaths adjusted for age 0–59 months. (Table 1, cont.)