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

An estimated 52 million children are wasted (16 million severely wasted) and 155 million children are stunted [1]. Each year, approximately 800,000 deaths are attributable to wasting, 60% of these attributable to severe wasting (SAM), and over one million deaths are attributable to stunting. These figures are based on prevalence estimates from cross-sectional surveys. Wasting is an acute condition and many wasted children will either recover or die within a few weeks. Estimating the number of wasted children present in a population over a given period of time using unadjusted prevalence estimates is likely to miss many new (i.e. incident) cases and significantly underestimate burden and attributable deaths [2]. A recent estimate of the annual global SAM burden that attempts to account for incident cases suggests that 110 million cases per year might be a more accurate estimate for severe wasting alone [3, 4]. Wasting and stunting are also estimated to be associated with the loss of 64.6 and 54.9 million disability-adjusted life years (DALYs) respectively, accounting for 14.8 and 12.6% of the total global DALYs lost for children under five years of age [5]. Recent global analyses reported that substantial progress has been made in reducing the number of stunted children [1, 6]. There has, however, been less progress in reducing the number of wasted children. It seems unlikely that the World Health Assembly goals of a 40% reduction in the prevalence of stuntedness and reducing and maintaining the prevalence of wasting below 5% will be met by the 2025 target date [6].

A number of recent reviews have noted that addressing wasting and stunting as separate issues, as has historically been the case, may not be justified [7–11]. Wasting and stunting are often present in the same populations and there is evidence suggesting that they share many causal factors [12, 13]. Investigations into whether there is a direct causal relationship between wasting and stunting is ongoing and a number of gaps in the evidence base have been identified [14]. One of these evidence gaps relates to the recognition that children can be both wasted and stunted at the same time [6, 15]. The factors leading to this state of ‘concurrence’ are poorly understood but evidence indicates that considerable excess mortality is experienced by children who are concurrently wasted, stunted, and underweight [16].

National estimates of the prevalence and burden of children concurrently wasted and stunted (a condition referred to as WaSt throughout this article) have recently been made for 84 countries [17]. Prevalence ranged between zero and 8% and exceeded 5% in 9 of the 84 countries for which estimates were made.

Questions remain regarding mortality and developmental risks associated with WaSt, which children are most affected, how WaSt cases may be practictably identified at facility and community level, and implications for programs, health policy and planning, and development policy.

This article reports on an analysis of a large database of cross sectional nutritional anthropometry surveys and aims to answer six basic questions: The degree of overlap between being wasted, being stunted, and being underweight; the maximum possible weight-for-age z-score (WAZ) in children with WaSt; the direction and strength of the association between being wasted and being stunted; the severity of wasting and stunting in WaSt cases; the prevalence of WaSt by age and sex; and how WaSt cases may be identified. The analysis of the overlap between being wasted, being stunted, and being underweight was prompted by work demonstrating considerable excess mortality in children who were concurrently wasted, stunted, and underweight who have been described as having “multiple anthropometric deficits” [16].

All children who were simultaneously wasted and stunted were also underweight (see Fig. 1). No child in the database with WHZ < − 2 and HAZ < − 2 had a WAZ ≥ − 2.

The maximum WAZ in children who are simultaneously wasted and stunted was WAZ ≈ − 2.36 for males and WAZ ≈ − 2.42 for females when the WHO growth standards are used. Low WHZ and low HAZ have a joint effect on WAZ which varies with age and sex (see Fig. 2).

The median WHZ in wasted only cases was − 2.47 compared to − 2.52 in WaSt cases (p < 0.0001) with probability of superiority = 0.522 (95% CI = 0.519–0.525) The median HAZ in stunted only cases was − 2.81 compared to − 2.98 in WaSt cases (p < 0.0001) with probability of superiority = 0.555 (95% CI = 0.554–0.556).

The male to female WaSt prevalence ratio found in 46 countries for which sufficient data (i.e. n ≥ 30 WaSt cases) was available are shown in Table 3. The pooled analysis showed the male to female prevalence ratio for WaST to be 1.63 (95% CI = 1.63–1.65). Figure 3 shows prevalence of WaSt by age and sex found in all 51 countries with age-specific male to female prevalence ratios.

Country	M:F prevalence ratio [95% CI]b	Country	M:F prevalence ratio [95% CI]b
Afghanistan	1.39 [1.28,1.50]	Malawi	1.45 [1.23,1.71]
Angola	1.60 [1.39,1.85]	Mali	1.69 [1.40,2.05]
Bangladesh	1.36 [1.20,1.53]	Mauritania	1.70 [1.50,1.93]
Benin	1.44 [1.12,1.85]	Mozambique	2.00 [1.36,2.99]
Burkina Faso	1.85 [1.70,2.03]	Myanmar	1.45 [1.28,1.65]
Burundi	1.49 [1.29,1.71]	Nepal	1.36 [1.17,1.59]
Cameroon	1.93 [1.56,2.40]	Niger	1.49 [1.39,1.60]
Central African Republic	1.57 [1.39,1.76]	Nigeria	1.41 [1.32,1.51]
Chad	1.59 [1.52,1.66]	Pakistan	1.70 [1.48,1.95]
Congo - Kinshasa	1.72 [1.65,1.80]	Philippines	1.54 [1.19,2.01]
Cote d’Ivoire	1.94 [1.66,2.26]	Rwanda	1.44 [1.22,1.69]
Djibouti	1.62 [1.27,2.07]	Senegal	1.87 [1.48,2.37]
Eritrea	1.70 [1.12,2.63]	Sierra Leone	1.53 [1.42,1.66]
Ethiopia	1.87 [1.78,1.97]	Somalia	1.86 [1.78,1.94]
Gambia	2.11 [1.63,2.76]	South Sudan	1.73 [1.62,1.85]
Guinea	1.66 [1.28,2.17]	Sri Lanka	1.02 [0.76,1.37]
Guinea Bissau	1.63 [1.21,2.21]	Sudan	1.71 [1.62,1.79]
Haiti	1.74 [1.51,1.99]	Tajikistan	1.32 [0.99.1.77]
India	1.12 [0.94,1.33]	Tanzania	2.65 [1.80,3.98]
Indonesia	1.35 [0.91,2.02]	Thailand	1.46 [0.84,2.56]
Kenya	1.74 [1.62,1.88]	Togo	1.71 [1.35,2.18]
Liberia	1.58 [1.41,1.77]	Uganda	1.65 [1.50,1.82]
Madagascar	2.47 [1.74,3.54]	Zambia	1.17 [0.59,2.32]
		Pooled PRc	1.63 [1.60,1.65]

^aCountries with fewer than 30 WaSt cases (i.e. Albania, Guatemala, Jordan, Yemen, Zimbabwe) were excluded from this analysis

^bIntervals (ranges) are expressed in ISO 31–11 form. The form [a,b] expresses the interval a ≤ x ≤ b. For example, [1.60,1.65] is used to represent a 95% confidence interval that ranges between 1.60 and 1.65

^cCalculated using inverse variance-weighted average fixed effects (Cochran) meta-analysis

Wasting and stunting were found to be positively and significantly associated with each other in most (i.e. 37 of 51) of the countries from which data were available. The pooled estimate of the odds ratio between stunting and wasting was 1.40 (95% CI = 1.32–1.49). The direction of causality cannot be addressed using cross-sectional data but the results are consistent with WaSt being something other than coincidental wasting and stunting.

WaSt cases were both more severely wasted than wasted only cases, and more severely stunted than stunted only cases. Effect sizes are small and are probably insufficient to account for the heightened risk of mortality for WaSt shown in Table 5. This suggests a multiplicative rather than an additive interaction between wasting and stunting is occurring.

The male to female prevalence ratio for WaSt was significantly greater than one in most (i.e. 40 of 46) of the countries from which sufficient data were available. In no country was the male to female prevalence ratio significantly below one and all point estimates were above one. The pooled male to female prevalence ratio was 1.63 (95% CI = 1.60–1.65). WaSt appears to be a condition affecting males more than females. The pattern of prevalence by age and sex shown in Fig. 3 was consistently found in country-specific analyses. WaSt appears to be a condition that affects children aged below 30 months more than it does older children.

Both WAZ and MUAC performed better than chance at detecting cases of WaSt. The performance of WAZ was superior to that of MUAC. Cases of WaSt attending, for example, GMP programs and paediatric clinics could be detected with excellent sensitivity and good specificity using WAZ. Cases of WaSt could be detected in the community using MUAC but with only moderate sensitivity and specificity.

The key findings of the analysis presented in this article are that WaSt and “multiple anthropometric deficits” are the same condition, wastedness and stuntedness 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, and that WaSt can be detected with excellent sensitivity and good specificity using WAZ.

The use of WAZ < − 2 in the case-definition for “multiple anthropometric deficits” introduces a redundant term into the case-definition and the category should be abandoned in favour of the simpler and more descriptive category of WaSt.

There is no pressing need for studies to estimate excess mortality associated with WaSt since the available estimates for “multiple anthropometric deficits” may be used [16].

The heightened risk of mortality associated with WaSt means that further work on the aetiology, prevention, case-finding, and treatment of children with WaSt as well as the extent to which current interventions are reaching children with WaSt is urgently required. Work on the mechanisms of the interaction between wasting and stunting on mortality may also prove useful. Work on mortality could be done ethically using data from historical cohort studies.

Treatment of moderate wasting in stunted children should be regarded as a public health priority. Urgent consideration should be given to expanding the admission criteria of therapeutic feeding programs to include children who are WaSt. This could be achieved by admitting children with low WAZ identified in paediatric clinics, in GMP programs operating at clinics sites, and in the community. The WAZ threshold used for this purpose could be decided by examination of mortality data from historical cohort studies. The use of MUAC and WAZ is compatible with recent recommendations regarding entry criteria for programs treating SAM in infants aged under six months [41, 42]. How best to identify WaSt cases in community settings with no GMP program or a GMP program achieving only low coverage warrants further investigation.

Work on treatment effectiveness, duration of treatment, and relapse after cure for WaSt cases should be undertaken. Much of this could be done using existing program data since many WaSt cases may already be admitted to CMAM programs [43].

Consideration should be given to encouraging the routine reporting of the prevalence of WaSt from nutritional anthropometry surveys, broader surveys (e.g. Multiple Indicator Cluster Surveys and Demographic and Health Surveys), surveillance systems, and other nutrition information systems that collect and report on anthropometric data.