Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/115407
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Type: Journal article
Title: Optima Nutrition: an allocative efficiency tool to reduce childhood stunting by better targeting of nutrition-related interventions
Author: Pearson, R.
Killedar, M.
Petravic, J.
Kakietek, J.
Scott, N.
Grantham, K.
Stuart, R.
Kedziora, D.
Kerr, C.
Skordis-Worrall, J.
Shekhar, M.
Wilson, D.
Citation: BMC Public Health, 2018; 18(1):384-1-384-12
Publisher: BioMed Central
Issue Date: 2018
ISSN: 1471-2458
1471-2458
Statement of
Responsibility: 
Ruth Pearson, Madhura Killedar, Janka Petravic, Jakub J. Kakietek, Nick Scott, Kelsey L. Grantham, Robyn M. Stuart, David J. Kedziora, Cliff C. Kerr, Jolene Skordis-Worrall, Meera Shekar and David P. Wilson
Abstract: Background: Child stunting due to chronic malnutrition is a major problem in low- and middle-income countries due, in part, to inadequate nutrition-related practices and insufficient access to services. Limited budgets for nutritional interventions mean that available resources must be targeted in the most cost-effective manner to have the greatest impact. Quantitative tools can help guide budget allocation decisions. Methods: The Optima approach is an established framework to conduct resource allocation optimization analyses. We applied this approach to develop a new tool, ‘Optima Nutrition’, for conducting allocative efficiency analyses that address childhood stunting. At the core of the Optima approach is an epidemiological model for assessing the burden of disease; we use an adapted version of the Lives Saved Tool (LiST). Six nutritional interventions have been included in the first release of the tool: antenatal micronutrient supplementation, balanced energy-protein supplementation, exclusive breastfeeding promotion, promotion of improved infant and young child feeding (IYCF) practices, public provision of complementary foods, and vitamin A supplementation. To demonstrate the use of this tool, we applied it to evaluate the optimal allocation of resources in 7 districts in Bangladesh, using both publicly available data (such as through DHS) and data from a complementary costing study. Results: Optima Nutrition can be used to estimate how to target resources to improve nutrition outcomes. Specifically, for the Bangladesh example, despite only limited nutrition-related funding available (an estimated $0.75 per person in need per year), even without any extra resources, better targeting of investments in nutrition programming could increase the cumulative number of children living without stunting by 1.3 million (an extra 5%) by 2030 compared to the current resource allocation. To minimize stunting, priority interventions should include promotion of improved IYCF practices as well as vitamin A supplementation. Once these programs are adequately funded, the public provision of complementary foods should be funded as the next priority. Programmatic efforts should give greatest emphasis to the regions of Dhaka and Chittagong, which have the greatest number of stunted children. Conclusions: A resource optimization tool can provide important guidance for targeting nutrition investments to achieve greater impact.
Keywords: Humans; Child Nutrition Disorders; Growth Disorders; Health Care Rationing; Child, Preschool; Infant; Infant, Newborn; Health Promotion; Cost-Benefit Analysis; Bangladesh
Description: Published online: 20 March 2018
Rights: © The Author(s). 2018, corrected publication April 2018. Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
RMID: 0030096361
DOI: 10.1186/s12889-018-5294-z
Appears in Collections:Public Health publications

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