Growth monitoring and the prognosis of mortality in low-income settings.

UNICEF’s 2014 progress report, “Committing to Child Survival: A Promise Renewed,” paints a picture of remarkable progress in combatting child mortality since the turn of the century (1). Yet, there is so much still to be achieved. Every day an estimated 16,000 children <5 y of age die, amassing to a total of 5.9 million deaths annually, the vast majority of which could and should have been avoided. There are numerous proximal and distal causes of these deaths, and many players in the global health community are contributing their expertise to tackle the residual burden from every angle. Nutritionists can play a vital role given that almost half of all child deaths can be attributed, either directly or indirectly, to undernutrition (2). In this issue of the Journal, Schwinger et al. (3) contribute to this endeavor by showing that assessment of a child’s recent growth trajectory provides a more accurate prognosis of likely death than the use of static measures of nutritional status. With the use of a historical cohort in the Democratic Republic of Congo (1989–1991) with data for regular anthropometric measurements in 5657 children ,5 y of age, they compared the antecedent nutritional status of the 264 children who died with that of those who survived. They found that a weight or length velocity score of, 23 predicted death within the next 3 mo with RRs of 7.9 and 11.8, respectively. Receiver operating characteristic analysis showed that weight and length velocity z scores had better predictive abilities (AUCs: 0.67 and 0.69) than the static measures of weight-for-age (AUC: 0.57) and length-for-age (AUC: 0.52) z scores. Among wasted children (weight-for-height z score ,22), the AUC of weight velocity z scores was 0.87. Absolute midupper arm circumference (MUAC) performed best among the attained indexes (AUC: 0.63), but longitudinal assessment of MUAC-based indexes did not increase the predictive value. The authors acknowledge several limitations of their study, but these are not likely to undermine the main conclusion and hence our discussion concentrates on the field implications of the results: How could we use these insights to further reduce child mortality in sub-Saharan Africa and South Asia where the burden is greatest? An AUC of,0.7 would not generally be considered sufficiently robust to warrant the development of a diagnostic or screening tool. The authors argue that their positive predictive value may have been limited by the relatively low mortality rate in the sample, but lower mortality rates are thankfully becoming the norm. They further argue that their results might underestimate the true value of velocity monitoring in other settings because 43% of the deaths were due to malaria and acute respiratory infections, which are not as strongly related to nutrition as, for example, diarrhea. This contention, however, is not supported by other studies in which casefatality rates for malaria and pneumonia are strongly predicted by height and (less so for malaria) by weight z scores (2, 4). Nonetheless, the central observation, that a deterioration in a child’s nutritional status provides an important pointer to ongoing pathology (be it of clinical or social origin) and flags a child as being at heightened risk of death, provides a welcome reinforcement of messages that have been taught to medical students and ancillary health staff for generations. A report by the United Nation’s Subcommittee on Nutrition in 1990 (5) reiterated the long-held view that “Concern is not with whether a child is on a given centile at one point in time, but whether its pattern of growth falls along the same centile band as age increases. This pattern provides more important information than the actual weight at any particular time. ” The committee recommended that an assessment of the relative performance, under field conditions, of growth monitoring and onetime screening should be undertaken (5). This is what Schwinger et al. have helpfully provided. However, we need to examine the extent to which these academic insights can be translated to actionable change in the field. On this point we are not optimistic. Even if the velocity scores had yielded exceptional sensitivity and specificity, the task of implementation would be daunting for several reasons. First, it is a sad fact that there are very few examples in low-income settings in which nutritional status is regularly monitored and diligently recorded on children’s road-to-health charts. The barriers relate to the supply, maintenance, and calibration of equipment; the detailed training required