Disability-adjusted life years for severe acute malnutrition: implications of alternative model specifications.

OBJECTIVE: Reducing the burden of childhood severe acute malnutrition (SAM) is key to improving global child health outcomes. Assessing cost-effectiveness of nutrition interventions remains an important evidence gap. Disability-adjusted life years (DALYs) are a common indicator used in cost-effectiveness analyses. DALYs were established by the Global Burden of Disease (GBD) study. Recent iterations of the GBD have changed the methods used to calculate DALYs by dropping age-weighting and discounting (AD) and updating disability weights (DW). Cost-effectiveness analyses may use either local or international standard life expectancies (LE). Changes in model specifications for calculating DALYs may have implications for cost-effectiveness analyses using DALYs, interpreting historical DALY estimates, and related resource allocation decisions. The present study aimed to quantify the magnitude of change in estimates of DALYs attributable to SAM given recent methodological changes. DESIGN: From secondary data analysis, using parameter values from routine programme monitoring data for two SAM treatment programmes and published literature, eight calculation models were created to estimate DALYs with and without AD, using different sets of DW, and local v. standard LE. RESULTS: Different DW had a marginal effect on DALY estimates. Different LE had a small effect when AD was used, but a large effect when AD was not used. CONCLUSIONS: DALY estimates are sensitive to the model used. This complicates comparisons between studies using different models and needs to be accounted for in decision making. It seems sensible for analyses to report results using models with and without AD and using local and standard LE.

Acute Malnutrition Among Children, Mortality, and Humanitarian Interventions in Conflict-Affected Regions - Nigeria, October 2016-March 2017.

A public health emergency was declared by the Nigerian Federal Ministry of Health in northeastern Nigeria in June 2016 and escalated by the United Nations to a Level 3 Emergency in August 2016, after confirmation of wild poliovirus and measles outbreaks and evidence that prevalence of acute malnutrition exceeded emergency thresholds in areas newly liberated from Boko Haram control (1,2). To monitor rates of mortality, acute malnutrition among children, infectious disease morbidity, and humanitarian interventions after the emergency declaration, a series of cross-sectional household surveys were conducted in fall 2016 and winter 2017 in the northeastern states of Borno and Yobe using a cluster methodology. All-cause mortality among all age groups (crude mortality) and among children aged <5 years (under-five mortality) were above emergency thresholds in 2017 and significantly increased from 2016, despite evidence of increased preventive public health interventions, including measles vaccination. Access to treatment for common childhood illnesses remained very low, as evidenced by reports of fewer than one in six children in areas outside Borno's capital receiving any care for diarrhea. The data from these surveys provide evidence of excessively high mortality (particularly among children), highlight the impact of ongoing violence, and underscore the need for humanitarian efforts to scale up access to treatment services in conflict-affected areas.

An evaluation of an operations research project to reduce childhood stunting in a food-insecure area in Ethiopia.

OBJECTIVE: To determine which interventions can reduce linear growth retardation (stunting) in children aged 6-36 months over a 5-year period in a food-insecure population in Ethiopia. DESIGN: We used data collected through an operations research project run by Save the Children UK: the Child Caring Practices (CCP) project. Eleven neighbouring villages were purposefully selected to receive one of four interventions: (i) health; (iii) nutrition education; (iii) water, sanitation and hygiene (WASH); or (iv) integrated comprising all interventions. A comparison group of three villages did not receive any interventions. Cross-sectional surveys were conducted at baseline (2004) and for impact evaluation (2009) using the same quantitative and qualitative tools. The primary outcome was stunted growth in children aged 6-36 months measured as height (or length)-for-age Z-scores (mean and prevalence). Secondary outcomes were knowledge of health seeking, infant and young child feeding and preventive practices. SETTING: Amhara, Ethiopia. SUBJECTS: Children aged 6-36 months. RESULTS: The WASH intervention group was the only group to show a significant increase in mean height-for-age Z-score (+0·33, P = 0·02), with a 12·1 % decrease in the prevalence of stunting, compared with the baseline group. This group also showed significant improvements in mothers' knowledge of causes of diarrhoea and hygiene practices. The other intervention groups saw non-significant impacts for childhood stunting but improvements in knowledge relating to specific intervention education messages given. CONCLUSIONS: The study suggests that an improvement in hygiene practices had a significant impact on stunting levels. However, there may be alternative explanations for this and further evidence is required.

Assessment of monitoring systems in the management of severe acute malnutrition in northern Nigeria.

BACKGROUND: In northern Nigeria, UNICEF has supported introduction of a short message service (SMS) system for data transmission in the Community-based Management of Acute Malnutrition (CMAM) programme. The SMS system operates in parallel to the traditional paper-based system, and weekly data are transmitted directly from the health facilities to the federal level. For the paper system, monthly data summaries are passed through all levels of government. We assessed the data quality and performance of both CMAM information systems. METHODS: We undertook a contextualised study in one state in north-west Nigeria, with additional analysis of secondary data from five states. Fieldwork methods included: observation of the data system in nine selected facilities in three local government areas; recounting of data for admissions, exits, and ready-to-use therapeutic food (RUTF) utilisation; and interviews with health workers and government officials. RESULTS: While the small number of facilities does not enable robust generalisation of the quantitative findings, the strengths and weaknesses detected pertain to the whole programme, as they relate to how the system was designed and is operated. We found that the accuracy and reliability of CMAM data were deficient to a similar extent in the paper-based and SMS systems. For the audited month, we found large discrepancies between recounted data and paper records in regard to admissions, exits and RUTF cartons consumed in the majority of facilities visited. There was also a large discrepancy in the reported percentage of "deaths or defaulters" (6.5%) compared to 22% based on a recount of outpatient cards. Errors are mainly introduced during data collection and when completing tallies at facility level. CONCLUSION: Our findings indicate the need for improvements in the design of the monitoring system, training and supervision of data management, and communication of results; as well as clear evidence on how measures to improve data quality may affect performance of individual CMAM clinics. The CMAM default and death rates currently reported in Nigeria are likely to be under-estimates, and therefore provide a misleadingly good impression of CMAM programme performance.

Improving estimates of the burden of severe acute malnutrition and predictions of caseload for programs treating severe acute malnutrition: experiences from Nigeria.

BACKGROUND: The burden of severe acute malnutrition (SAM) is estimated using unadjusted prevalence estimates. SAM is an acute condition and many children with SAM will either recover or die within a few weeks. Estimating SAM burden using unadjusted prevalence estimates results in significant underestimation. This has a negative impact on allocation of resources for the prevention and treatment of SAM. A simple method for adjusting prevalence estimates intended to improve the accuracy of burden estimates and caseload predictions has been proposed. This method employs an incidence correction factor. Application of this method using the globally recommended incidence correction factor has led to programs underestimating burden and caseload in some settings. METHODS: A method for estimating a locally appropriate incidence correction factor from prevalence, population size, program caseload, and program coverage was developed and tested using data from the Nigerian national SAM treatment program. RESULTS: Applying the developed method resulted in errors in caseload prediction of about 10%. This is a considerable improvement upon the current method, which resulted in a 79.5% underestimate. Methods for improving the precision of estimates are proposed. CONCLUSIONS: It is possible to considerably improve predictions of caseload by applying a simple model to data that are readily available to program managers. This implies that more accurate estimates of burden may also be made using the same methods and data.