This literature review shows that short term changes in the nutritional status of a population can be detected using weight, WFH/L, MUAC or TSF while H/LFA is a good measure of long term change. In addition to its responsiveness to nutritional stress, a number of important criteria need to be taken into account to identify the most appropriate and relevant measure or index to be used to detect changes: simplicity, acceptability, cost, independence of age, reliability and accuracy, sensitivity and specificity [32].

Any index that includes an age component requires that age be ascertained accurately and it is widely acknowledged that determining age correctly is problematic in many developing countries [33–36]. The use of multi-component indices (i.e. WFA, HFA, WFH, MUAC-for-Age, TSF-for-Age) is usually more complex [33, 37]. Moreover, transporting and carrying weight scales as well as height/length board is more logistically challenging than for MUAC tapes.

The measurement of weight, height and MUAC is widely accepted and commonly performed in nutrition surveillance and interventions. A study reported that younger children tended to become upset and agitated during both weight and height measurement but not during MUAC measurement [37]. TSF index is not currently used for surveillance or programming and would probably not be as acceptable as the measures above as it requires the measurement of the width of a fold of skin taken over the triceps muscle using a skinfold caliper.

The measurement of height and weight requires fairly costly equipment [37–39] while the MUAC tool – a tape measure – is cheap and easy to transport. A caliper is also relatively costly and may be harder to procure.

One way to ascertain age-independence is to adjust indices for age (i.e. WFA, HFA, MUAC-for-Age) but the issue of the accuracy of age remains. MUAC is relatively age and sex independent among 1–5 year olds [32, 37, 40–43] as well as WFH [39, 44]. It was also shown that MUAC alone, without correction for age, was a better predictor of death than indices based on height, weight and age [41–43, 45].

Although weight and height alone were shown to be more precisely measured [46–49], it was reported that MUAC has a better reliability than WFH and shows better performance in screening programmes [50]. It was also shown that in field conditions, minimally trained workers make fewer and smaller errors in screening children with MUAC than with WFH [37]. Indices usually require finding values in tally sheets or calculations that can lead to further errors. A recent paper shows that MUAC is more reliable than WFH [51] and another that MUAC outperforms weight-based measures of nutritional status in children with diarrhoea [52]. It was also shown to be less affected by dehydration than WFH [53]. As mentioned above, any index requiring the age (i.e. WFA or HFA) of the child is likely to be less accurate.

MUAC is increasingly recognised as a very useful index of nutritional status [50]. There is a consensus that MUAC is a better predictor of mortality than WFH [40, 45, 54–60] and it was recently reported that using MUAC alone is preferable for identifying high-risk malnourished children [61].

Table 5 summarises the characteristics of all relevant measures and indices reviewed. We focus on measures and indices that are currently in use in nutrition programming and nutrition surveillance (i.e. we did not discuss TSF, TSF-for-Age, MUAC-for-Age, MC, birth weight). Table 5 highlights the advantages of using MUAC over other measures or indices detecting short term changes.

These findings are consistent with the increasing interest in MUAC-only nutrition programming and use for admission and discharge to feeding programmes [62–66]. This concordance makes the findings of this review applicable and of interest to international policy makers and programme managers.

We acknowledge the limitations to our review, the most important being:

Great heterogeneity (population; setting; study design; methods; time periods; primary research question) between the studies found: this makes it difficult to carry out any quantitative analysis/meta-analysis to compare the performance of different measures and indices

A single reviewer performed the search which may have lead to errors or omissions

Publication bias: studies that were unable to assess changes or trends at population level are less likely to be published

The observational nature of the studies: it is not possible to directly ‘test’ the performance of one indicator against another in an interventional study

There is no gold standard measure of population nutritional status. Where no change is observed, we cannot know whether there really was no change in the population or whether a real change was simply not detected by indices used (i.e. not sensitive enough)

We did not look at over-nutrition. MUAC might not be the best index when measuring obesity, an increasing problem even in resource poor settings [67].

Balancing these limitations, a major strength of our review is that we explore a highly policy/practice-relevant question using a systematic approach. By highlighting the overall limited evidence base we hope to stimulate both more and better-quality future research in this area. We also provide a framework whereby policy makers and managers can think about the different aspects of indicator performance: different indicators may suit different questions and in choosing which is ‘best’ it is vital to consider context. Different aspects of malnutrition may be better monitored by different sets of indictors such as in DHS or MICS. The measurement or index to use also depends on the nature and intensity of the crises. In some crises where diets might still be sufficient to maintain weight but have lost adequacy in micronutrient, the change in stunting might be significant but not in wasting. This has been the case in recent conflicts [68]. Finally, we highlight an indicator – MUAC - that is still missing from many major surveys such as DHS. This is an important gap given MUAC’s good performance for detecting short term changes in population nutritional status. This has major implications for early warning systems or other assessments systems which only allow for limited field data collection because of time or budget constraints.

Future research should look at cost-effectiveness and logistics issues of different systems as this is critical to successful and sustained large-scale rollout of any system. Especially with the large number of sustainable development goals, there is increasing pressure to make efficient use of resources.