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. 2018 Jul 16:76:28.
doi: 10.1186/s13690-018-0277-1. eCollection 2018.

Children who are both wasted and stunted are also underweight and have a high risk of death: a descriptive epidemiology of multiple anthropometric deficits using data from 51 countries

Mark Myatt  1 , Tanya Khara  2 , Simon Schoenbuchner  3 , Silke Pietzsch  4 , Carmel Dolan  2 , Natasha Lelijveld  5   6 , André Briend  7   8
Affiliations

Children who are both wasted and stunted are also underweight and have a high risk of death: a descriptive epidemiology of multiple anthropometric deficits using data from 51 countries

Mark Myatt et al. Arch Public Health. .

Abstract

Background: Wasting and stunting are common. They are implicated in the deaths of almost two million children each year and account for over 12% of disability-adjusted life years lost in young children. Wasting and stunting tend to be addressed as separate issues despite evidence of common causality and the fact that children may suffer simultaneously from both conditions (WaSt). Questions remain regarding the risks associated with WaSt, which children are most affected, and how best to reach them.

Methods: A database of cross-sectional survey datasets containing data for almost 1.8 million children was compiled. This was analysed to determine the intersection between sets of wasted, stunted, and underweight children; the association between being wasted and being stunted; the severity of wasting and stunting in WaSt children; the prevalence of WaSt by age and sex, and to identify weight-for-age z-score and mid-upper arm circumference thresholds for detecting cases of WaSt. An additional analysis of the WHO Growth Standards sought the maximum possible weight-for-age z-score for WaSt children.

Results: All children who were simultaneously wasted and stunted were also underweight. The maximum possible weight-for-age z-score in these children was below - 2.35. Low WHZ and low HAZ have a joint effect on WAZ which varies with age and sex. WaSt and "multiple anthropometric deficits" (i.e. being simultaneously wasted, stunted, and underweight) are identical conditions. The conditions of being wasted and being stunted are positively associated with each other. WaSt cases have more severe wasting than wasted only cases. WaSt cases have more severe stunting than stunted only cases. WaSt is largely a disease of younger children and of males. Cases of WaSt can be detected with excellent sensitivity and good specificity using weight-for-age.

Conclusions: The category "multiple anthropometric deficits" can be abandoned in favour of WaSt. Therapeutic feeding programs should cover WaSt cases given the high mortality risk associated with this condition. Work on treatment effectiveness, duration of treatment, and relapse after cure for WaSt cases should be undertaken. Routine reporting of the prevalence of WaSt should be encouraged. Further work on the aetiology, prevention, case-finding, and treatment of WaSt cases as well as the extent to which current interventions are reaching WaSt cases is required.

Keywords: Anthropometry; Mortality; Multiple anthropometric deficits; Prevalence; Stunting; Wasting.

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Conflict of interest statement

This study performed a secondary analysis of data that had already been collected for prevalence assessment in emergency and development settings. No persons could be identified from the data. No clinical data were used. No experiments were performed on human subjects. Ethical approval for the work described in this article is not required under the Declaration of Helsinki (all revisions) and was not sought. Whenever possible, data were collected following ethical approval from locally responsible ethics committees. Some data were collected during complex emergencies when no locally responsible ethics committees were operating. In these cases ethical approval was granted solely by the institutional review bodies of the non-governmental organization (NGO) or United Nations organization (UNO) which collected the data. Permissions were sought and given by local ministries of health and, where appropriate, by local police departments and military and / or paramilitary commanders. Identifying data were collected for programmatic purposes (i.e. for recruitment of cases of acute malnutrition into feeding programs) but this data was either not entered or was removed prior to data being made available for analysis. Participation in the surveys was voluntary. Children were not (and could not be) measured without the consent of their parents or guardians. Verbal informed consent was sought from the primary caregiver of the child. Written consent is almost never sought in these types of survey: It is usually not required and levels of literacy are often low. The existence of the data is proof of consent.Not applicable.The authors declare that they have no competing interests.Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Figures

Fig. 1
Fig. 1
Venn diagram showing the relations between sets of children who are wasted, stunted and underweight in all 51 countries (n = 1,796,991)*. * Wasted (weight-for-height z-score < − 2.0), stunted (height-for-age z-score < − 2.0), and underweight (weight-for-age z-score < − 2.0) were defined using z-scores calculated using the WHO growth standards. The number of cases in each division is reported. The zero cell indicates that all WaSt cases were also underweight
Fig. 2
Fig. 2
Weight-for-age z-score (WAZ) at different ages for males and females aged between 6 and 59 months with WHZ = − 2.0 and HAZ = − 2.0 calculated using the WHO growth standards. All WaSt cases must also be underweight (i.e. present with WAZ < − 2.0)
Fig. 3
Fig. 3
Male and female WaSt prevalence by age group in all 51 countries. Intervals (ranges) are expressed in ISO 31–11 form. The form (a, b) expresses the interval a < x ≤ b. For example, (17, 29) is used to represent the set {18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29} of ages in months. Year-centred age-groups are used. The form (a, b) expresses the interval a ≤ x ≤ b. For example, [1.69, 1.78] is used to represent a 95% confidence interval that ranges between 1.69 and 1.78
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