Date Published: May 12, 2018
Publisher: The American Society of Tropical Medicine and Hygiene
Author(s): Emily L. Deichsel, Kirkby D. Tickell, Jessica E. Long, Nelson L. Jumbe, Ali Rowhani-Rahbar, Judd L. Walson.
Despite the recognition of stunting as a public health priority, nutritional and nonnutritional interventions to reduce or prevent linear growth failure have demonstrated minimal impact. Investigators and policymakers face several challenges that limit their ability to assess the potential benefits of combining available interventions into a linear growth promotion package. We use two common but very different interventions, deworming and multiple micronutrient supplements, to illustrate barriers to recommending an optimal linear growth promotion package based on the currently available literature. These challenges suggest that combining individual- and population-based as well as model-based approaches would complement existing research using systematic review, meta-analysis, and factorial randomized trials, and help integrate existing fields of research to inform the development of optimal linear growth promotion packages for children living in resource-limited settings.
More than 165 million children worldwide are stunted (height-for-age z-score [HAZ] < −2), a marker of chronic malnutrition.1 Stunting is associated with substantial morbidity and mortality, including a 2-fold increase in the risk of death before age 5.1,2 Although stunting is a public health priority, current interventions have demonstrated minimal effect in reversing or preventing stunting. Estimates suggest that if available growth-promoting interventions reached 90% of their target population, stunting incidence would only be reduced by one-fifth.3 The combination of proximal etiologic causes of stunting, including lack of adequate nutrition, hormonal dysregulation, repeated infections, environmental enteric dysfunction, and chronic systemic inflammation, occurs within a complex network of more distal factors that underlie stunting.2 As a result of the multifactorial etiologies of stunting, successful prevention or treatment may require combined packages of interventions targeting multiple pathophysiologic pathways leading to stunting. The failure to prevent or reverse stunting may result from the complex interactions between prenatal and early childhood health insults that result in linear growth failure. Soil-transmitted helminths are among the world’s most common infections, affecting more than 25% of the world’s population.4 Children are most affected by severe infections that can have detrimental long-term effects, including stunting.5 Anthelmintic therapy (deworming) is administered to more than 100 million children annually, often in mass drug administration (MDA) programs, and there is some evidence to suggest a potential linear growth benefit from deworming.6 However, results from a recent Cochrane review of randomized trials assessing the growth benefits of deworming interventions are mixed. Although some individual trials demonstrate beneficial effects of deworming on childhood growth, the results of pooled analyses demonstrate no statistically significant effects (mean difference −0.02 cm, 95% confidence interval [CI]: −0.17, 0.12).6 Interpreting and applying these results requires a careful understanding of the distinction between efficacy and effectiveness in the context of clinical trial design. Results from trials of childhood multiple micronutrient interventions provide insight into the potential multiplicative or additive benefits provided by combining interventions into a package. However, although the methodological principles of evaluating the combined effects of interventions are well established, determining how combined interventions interact is complex.7,8 The chief aim of trialing multiple interventions is assessing whether the combination offers an added benefit over the single intervention, often referred to as additive effects. Additive effects assume that if treatment A has an effect EA over a control and treatment B has an effect EB over that same control, then the combination of A and B would have an effect EA+ EB.9 Additive effects assume that the interventions work via independent pathways. For example, it would be reasonable to assume that a handwashing intervention and a nutritional intervention do not use the same pathway and therefore, should not interact. However, many interventions have complex or uncertain mechanisms of action, and so it is advisable to test for interactions between combined interventions using factorial randomized trials. Guidance for the assumptions of additive effects have been previously reported.9 In rare circumstances, interactions can lead to a greater-than-expected treatment effect (i.e., EAB> EA+ EB), referred to as synergy. When an interaction leads to a treatment effect less than the sum of the combined treatments (i.e., EAB< EA+ EB) it is termed as antagonism. A common cause of antagonistic interactions is class effect. This occurs when interventions using similar pathways have comparable individual effect sizes but negligible additive effects, because the therapeutic utility of the shared pathway is already fully exploited by a single therapeutic. Anthelmintics and multiple micronutrient interventions serve as examples to highlight the complexity of assessing interventions targeting linear growth and of determining optimal combinations of interventions to achieve maximum potential benefit. Many interventions have not been evaluated for growth benefit in well-designed efficacy trials, and many trials of combined interventions were not designed to evaluate additive effects or antagonism. In addition, the diversity of interventions suggested for inclusion in a possible package targeting linear growth promotion may require delivery through a combination of delivery platforms. Therefore, recommending an optimal linear growth promotion package based on the currently available published literature with any certainty of its beneficial effect is challenging. This, in turn, limits the ability of policymakers to set guidelines for packages of interventions. Single intervention-based recommendations may be a missed opportunity to optimize childhood health. Source: http://doi.org/10.4269/ajtmh.17-0212