Economic evaluation of nutrition interventions: Does one size fit all?

BACKGROUND: Nutrition interventions have specific features that might warrant modifications to the methods used for economic evaluations of healthcare interventions. AIM: The aim of the article is to identify these features and when they challenge the use of cost-utility analysis (CUA). METHODS: A critical review of the literature is conducted and a 2 by 2 classification matrix for nutrition interventions is proposed based on 1) who the main party responsible for the implementation and funding of the intervention is; and 2) who the target recipient of the intervention is. The challenges of conducting economic evaluations for each group of nutrition interventions are then analysed according to four main aspects: attribution of effects, measuring and valuing outcomes, inter-sectorial costs and consequences and equity considerations. RESULTS AND CONCLUSIONS: CUA is appropriate for nutrition interventions when they are funded from the healthcare sector, have no (or modest) spill-overs to other sectors of the economy and have only (or mainly) health consequences. For other interventions, typically involving different government agencies, with cost implications for the private sector, with important wellbeing consequences outside health and with heterogeneous welfare effects across socio-economic groups, other economic evaluation methods need to be developed in order to offer valid guidance to policy making. For these interventions, checklists for critical appraisal of economic evaluations may require some substantial changes.

Association between Anaemia in Children 6 to 23 Months Old and Child, Mother, Household and Feeding Indicators.

In Low and Lower-Middle-Income countries, the prevalence of anaemia in infancy remains high. In early childhood anaemia cause irreversible cognitive deficits and represents a higher risk of child mortality. The consequences of anaemia in infancy are a major barrier to overcome poverty traps. The aim of this study was to analyse, based on a multi-level approach, different factors associated with anaemia in children 6⁻23 months old based on recent available Standard Demographic Health Surveys (S-DHS). We identified 52 S-DHS that had complete information in all covariates of interest in our analysis between 2005 and 2015. We performed traditional logistic regressions and multilevel logistic regression analyses to study the association between haemoglobin concentrations and household, child, maternal, socio-demographic variables. In our sample, 70% of the 6⁻23 months-old children were anaemic. Child anaemia was strongly associated with maternal anaemia, household wealth, maternal education and low birth weight. Children fed with fortified foods, potatoes and other tubers had significantly lower rates of anaemia. Improving overall household living conditions, increasing maternal education, delaying childbearing and introducing iron rich foods at six months of age may reduce the likelihood of anaemia in toddlerhood.