Department of Nutrition for Health and Development, World Health Organization, 20 Avenue Appia, 1211 Geneva 27, Switzerland.
Dr Mercedes de Onis, Department of Nutrition for Health and Development, World Health Organization, 1211 Geneva 27, Switzerland. E-mail: deonism{at}who.int
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Abstract |
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Methods The database includes population-based surveys that fulfil a set of criteria. Data are checked for validity and consistency and raw data sets are analysed following a standard procedure to obtain comparable results. Prevalences of wasting, stunting, under- and overweight in preschool children are presented using z-scores based on the National Center for Health Statistics (NCHS)/WHO international reference population. New surveys are included on a continuous basis and updates are published bimonthly on the databases web site.
Results To date, the database contains child anthropometric information derived from 846 surveys. With 412 national surveys from 138 countries and 434 sub-national surveys from 155 countries, the database covers 99% and 64% of the under 5 year olds in developing and developed countries, respectively. This wealth of information enables international comparison of nutritional data, helps identifying populations in need, evaluating nutritional and other public health interventions, monitoring trends in child growth, and raising political awareness of nutritional problems.
Conclusions The 15 years experience of the database can be regarded as a success story of international collaboration in standardizing child growth data. We recommend this model for monitoring other nutritional health conditions that as yet lack comparable data.
Accepted 7 January 2003
Child growth is internationally recognized as an important public health indicator for monitoring nutritional status and health in populations. Children who suffer from growth retardation as a result of poor diets and/or recurrent infections tend to have more frequent episodes of severe diarrhoea and are more susceptible to several infectious diseases, such as malaria, meningitis, and pneumonia.13 A number of studies have demonstrated the association between increasing severity of anthropometric deficits and mortality, and the substantial contribution to child mortality of all degrees of malnutrition is now widely accepted.4 In addition, there is strong evidence that impaired growth is associated with delayed mental development, poor school performance, and reduced intellectual capacity.57
The internationally recommended way to assess malnutrition at population level is to take body or anthropometric measurements (e.g. weight and height). Based on combinations of these body measurements anthropometric indices are constructed. These indices are essential for the interpretation of body measurements as, for example, weight alone has no meaning unless it is related to an individuals age or height.8 In children the three most commonly used anthropometric indices are weight-for-height, height-for-age, and weight-for-age. These indices can be expressed in terms of z-scores, percentiles, or percentage of median, which enable comparison of a child or a group of children with a reference population.
For many years the WHO Department of Nutrition has been using anthropometric data to monitor trends in child malnutrition. A major difficulty has been the non-uniformity of survey analyses and presentation of their results. Although numerous nutritional surveys have been conducted since the 1970s, many of them have used distinct definitions of malnutrition (i.e. different anthropometric indices, reporting systems, cutoff points, and reference values) thus making comparison of results between studies difficult. This lack of comparable data prompted the beginning of WHOs systematic collection and standardization of information on the nutritional status of the worlds under-5 population. The WHO Global Database on Child Growth and Malnutrition (henceforth referred to as the database) was initiated in 1986 to compile, standardize, and disseminate results of nutritional surveys performed worldwide. The specific objectives of this database are to: characterize nutritional status; enable international comparisons of nutritional data; identify populations in need; help evaluate nutritional and health interventions; monitor secular trends in child growth; and raise political awareness of nutritional problems. A distinct feature of the database is the systematic analysis of raw data sets in a standard format to produce comparable results. This paper describes the methodology applied in the database and provides examples of how the compiled information is used for promoting the healthy growth and development of children.
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Methods |
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Criteria for inclusion and data quality control
The main criteria for including surveys in the database are:
Before inclusion of a survey in the database the sampling method applied is reviewed to ensure population-based representativeness at the administrative level that applies (e.g. national, regional, province, district, local). The majority of national surveys use multistage random sampling methods with only a few countriessuch as Argentina, Chile, Croatia, Uruguay, and Venezuelabasing their estimates on national nutritional surveillance systems with high population coverage. Surveys generally apply standard measurement techniques, such as measuring supine length up to 24 months of age and standing height from 24 months onwards.8 Detailed information on the procedures and sampling method used in each survey is given in the comprehensive survey reports that are archived in the databases documentation centre and made available to users on request.
As part of routine data quality control, survey results are checked for inconsistencies between the malnutrition estimates based on height-for-age, weight-for-age, and weight-for-height. The observed standard deviations (SD) of the z-score distribution are used to assess the quality of the survey data. With accurate age estimates and anthropometric measurements, the SD of the observed z-score distributions should be relatively constant and close to the expected value of 1.0 for the reference distribution (ranging within approximately 0.2 units).8 Surveys with an SD outside the expected ranges require closer examination because of possible problems related to age assessment and/or anthropometric measurements. Surveys with obvious inaccurate data resulting from measurement error or incorrect age reporting are generally excluded.
Database work-flow
Figure 1 describes the work-flow of the database. Once a potentially relevant survey is identified and the documentation obtained, the methods are reviewed as described above. If the survey qualifies, the available information is extracted from the documents and filled into a standard data-entry form. To clarify any queries and obtain any additional results, the data holders are contacted and a collaboration established. In many occasions further analysis of the raw data is required. These analyses are conducted either by the data holders (with technical assistance from the database managers if necessary) or the raw data are provided to WHO for standard analysis. A software package named ANTHROwhich can be downloaded from the databases web site at http://www.who.int/nutgrowthdbwas developed to facilitate the analysis following the common format of the database. Final consistency checks across indicators take place before the results are entered into the computerized system. The full documentation and correspondence, as well as electronic copies of raw data and analysis files are archived.
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Detailed information on the use and interpretation of the anthropometric indices, cutoff points, and summary statistics included in the database has been published elsewhere8,9 and is also available online from the databases web site.
Current developments with regards to the reference data deserve special mention here. Anthropometric values are compared across individuals or populations in relation to a set of reference values and the choice of the reference population has a significant impact on the proportion of children identified as being under- and over-nourished. Since the late 1970s WHO has been recommending the NCHS growth reference, the so-called NCHS/WHO international reference population, for the comparison of child growth data. A detailed account of the history of the NCHS/WHO reference and general issues that need to be considered when using international reference data are discussed elsewhere.10,11 In the mid 1990s the NCHS/WHO international reference was found to have important technical and biological drawbacks.8,12 Consequently, an international effort co-ordinated by WHO is presently developing a new international growth reference for infants and young children.13 This new international reference, constructed from primary data collected for this purpose, includes a number of features which will result in a reference population substantially different from existing ones. An important characteristic is that it will be based on a truly international sample. Six countries, representing the major global geographical regions, are participating in this effort. Another notable feature is that it takes the breastfed infant as the biological norm, recognizing the health and nutritional benefits of breastfeeding.14 The extent to which the new curvesexpected to be available in 2005differ from the current ones in shape and the spread of values around the mean will affect the estimates of under- and over-nutrition that have been established using the NCHS/WHO international reference.
Data analysis
The analyses related to the database consist of two separate steps. The first step is the primary data analysis of raw data sets to produce standardized results as described above. To date more than 400 national and sub-national nutritional surveys have been analysed to produce standardized prevalences of underweight, wasting, stunting, and overweight. The analysis of raw data is essential because many nutritional surveys use distinct definitions of malnutrition making comparison across surveys impossible. This was also an important barrier to pooling individual survey data for deriving regional and global estimates. It implies gaining access to the raw data and description of codes and, then conducting the analysis of large and complex data files. After making the survey results comparable, in a second step, nationally representative survey data are pooled to derive regional and global estimates of under- and over-nutrition. Specific statistical methods used for this purpose (e.g. multilevel modelling) have been described elsewhere.9,1517
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Results |
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The wealth of information compiled in the database has made it possible to compare levels, trends, and geographical distributions of under- and overnutrition in preschool children worldwide. Initial results from the database were published in 199315 and updated in 1997.9 The latter publication also presented, for the first time, estimates of trends in child growth retardation in developing countries. A more recent analysis updated these earlier estimates and described regional and global trends in childhood malnutrition from 1980 to 2005.16 Figure 2 shows the distribution of stunting in developing countries according to the latest prevalence data, categorized as low, medium, high, and very high: <20%, 2029%, 3039%, and
40%, respectively. The map shows very high rates of stunting in many countries of sub-Saharan Africa, South-central Asia, and South-eastern Asia. In Latin America and the Caribbean the majority of countries have low or moderate rates. Country-specific prevalence rates disaggregated by sex, age group, area of residence, and administrative region can be found on the databases web site.
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Discussion |
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Despite an overall decrease of stunting in developing countries, in some, rates of stunting are rising, while in many others they remain disturbingly high.15,16 An important finding of these comparisons is the remarkable similarity of the patterns of growth faltering in developing countries, not only within a region but also globally, despite the different instruments and measuring methods used in the surveys. These results show that interventions during the earliest periods of life are likely to have the greatest impact in preventing child malnutrition. Special emphasis should thus be given to the development of effective interventions to stop the critical faltering that occurs from birth to 24 months.20
At the other extreme of the spectrum, findings from the database demonstrate that overweight is becoming a matter of growing concern and that attention needs to be paid to monitoring levels and trends of overweight during childhood not only in developed countries, but globally.17 The information compiled in the database helps identify countries and regions in need of population-wide interventions and provides a baseline for assessing progress.
In May 1999 the database was made accessible on the internet at the web address http://www.who.int/nutgrowthdb. The web siteupdated bimonthlyenables its users anywhere in the world to obtain at any time the latest information from the database. Following the launch of this web site the number of its users has been continuously increasing. To this point in time (August 2002), the databases web site has more than 7000 registrations and there are many direct links to it. In addition to the numerous individual users, the UN organizations such as the United Nations Administrative Committee on Coordination/ Sub-Committee on Nutrition (ACC/SCN), FAO, UNICEF, the UN Population Division of the Department of Economics and Social Affairs, and the World Bank use regularly the information included in this database for their routine reporting on child nutritional status and its association with other health and socioeconomic indicators.2127 Similarly, many national and international institutions and non-governmental organizations use the database as the source for information on child malnutrition.28,29
The 15 years experience of the database can be regarded as a success story of international collaboration in standardizing child growth data. This success can be measured by the wide acceptance of the databases principles, the range of uses of the data by different stakeholders, and the steadily growing network of collaborators. The database relies heavily on this network, which has been developing a dynamic of its own, leading to the early involvement of the database managers in large-scale surveys. This reflects the high interest of collaborators in supporting WHO in this global effort of monitoring child growth and malnutrition.
This effort is, however, not exempt from constraints. One main limitation of using anthropometry in assessing child nutritional status is its lack of specificity, as changes in body measurements are sensitive to many factors including intake of essential nutrients, infection, altitude, stress, and genetic background. When compiling this information in a database, an additional restriction is that data quality checks are limited to review of the information received in the reports and of summary statistics obtained after the standard analysis of raw data. Assessing the adherence to protocols by each survey team is not possible. Despite these limitations, we nevertheless consider that the experience of the WHO Global Database on Child Growth and Malnutrition could be a model to follow for monitoring other nutritional disorders and/or health conditions that lack comparable data.
While continuing its routine, the database faces a number of challenges. First, the release and implementation of the new international growth reference in 2005 will have noteworthy implications for the management of the database. These will include the addition of new indicators such as body mass index (BMI)-for-age and others, and the re-analysis of raw data sets applying the new reference population. Second, trends in nutritional status for countries undergoing nutritional transition indicate the need to pay close attention to the monitoring of overweight and obesity during childhood.17 To achieve this, users of population-based estimates should shift their concentration on the traditional indicator weight-for-age to focus more on length/height-for-age as well as weight-for-length/ height. This would permit identifying stunted children of low weight-for-age but normal weight-for-length/height, who should not receive excess energy since this could lead to obesity.30 Third, the association between prenatal and postnatal growth, and the magnitude of the problem of intrauterine growth retardation (IUGR) in developing countries31 underscore the need to incorporate into the database the monitoring of impaired fetal growth. A potential methodology that will facilitate the derivation of population-based estimates of IUGR is presently being developed. Monitoring the patterns and trends of IUGR is expected to trigger public health action in populations where interventions aimed at preventing fetal growth retardation are urgently needed. Lastly, the availability of reference data for motor development milestones being developed as part of the new international growth reference14 will provide the possibility to monitor motor development, establishing an important link between physical growth and development in children.
The future of human societies relies on children being able to achieve their optimal physical growth and development. The database serves to increase awareness of the magnitude of the problem of child malnutrition worldwide and to alert decision-makers to how much remains to be done in order to ensure childrens healthy growth and development.
KEY MESSAGES
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Acknowledgments |
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References |
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