Literature DB >> 33653730

Improving estimates of the burden of severe wasting: analysis of secondary prevalence and incidence data from 352 sites.

Sheila Isanaka1,2, Christopher T Andersen3, Simon Cousens4, Mark Myatt5, André Briend6,7, Julia Krasevec8, Chika Hayashi8, Amy Mayberry9, Louise Mwirigi8, Saul Guerrero8.   

Abstract

INTRODUCTION: Estimates of incident cases of severe wasting among young children are not available for most settings but are needed for optimal planning of treatment programmes and burden estimation. To improve programme planning, global guidance recommends a single 'incidence correction factor' of 1.6 be applied to available prevalence estimates to account for incident cases. This study aimed to update estimates of the incidence correction factor to improve programme planning and inform the approach to burden estimation for severe wasting.
METHODS: A global call was issued for secondary data from severe wasting treatment programmes including prevalence, population size, programme admission and programme coverage through a UNICEF-led effort. Site-specific incidence correction factors were calculated as the number of incident cases (annual programme admissions/programme coverage) divided by the number of prevalent cases (prevalence*population size). Estimates were aggregated by country, region and overall using inverse-variance weighted random-effects meta-analysis.
RESULTS: We estimated incidence correction factors from 352 sites in 20 countries. Estimates aggregated by country ranged from 1.3 (Nigeria) to 30.1 (Burundi). Excluding implausible values, the overall incidence correction factor was 3.6 (95% CI 3.4 to 3.9).
CONCLUSION: Our results suggest that incidence correction factors vary between sites and that the burden of severe wasting will often be underestimated using the currently recommended incidence correction factor of 1.6. Application of updated incidence correction factors represents a simple way to improve programme planning when incidence data are not available and could inform the approach to burden estimation. © Author(s) (or their employer(s)) 2021. Re-use permitted under CC BY. Published by BMJ.

Entities:  

Keywords:  child health; epidemiology; nutrition

Mesh:

Year:  2021        PMID: 33653730      PMCID: PMC7929878          DOI: 10.1136/bmjgh-2020-004342

Source DB:  PubMed          Journal:  BMJ Glob Health        ISSN: 2059-7908


  13 in total

1.  Estimates of the duration of untreated acute malnutrition in children from Niger.

Authors:  Sheila Isanaka; Rebecca F Grais; André Briend; Francesco Checchi
Journal:  Am J Epidemiol       Date:  2011-03-04       Impact factor: 4.897

2.  Incidence Correction Factors for Moderate and Severe Acute Child Malnutrition From 2 Longitudinal Cohorts in Mali and Burkina Faso.

Authors:  Francisco M Barba; Lieven Huybregts; Jef L Leroy
Journal:  Am J Epidemiol       Date:  2020-12-01       Impact factor: 4.897

3.  Improving Estimates of Numbers of Children With Severe Acute Malnutrition Using Cohort and Survey Data.

Authors:  Sheila Isanaka; Ellen O'Neal Boundy; Rebecca F Grais; Mark Myatt; André Briend
Journal:  Am J Epidemiol       Date:  2016-11-17       Impact factor: 4.897

4.  Using cross-sectional surveys to estimate the number of severely malnourished children needing to be enrolled in specific treatment programmes.

Authors:  Nancy M Dale; Mark Myatt; Claudine Prudhon; André Briend
Journal:  Public Health Nutr       Date:  2017-01-24       Impact factor: 4.022

5.  Stunting and wasting are associated with poorer psychomotor and mental development in HIV-exposed Tanzanian infants.

Authors:  Christine M McDonald; Karim P Manji; Roland Kupka; David C Bellinger; Donna Spiegelman; Rodrick Kisenge; Gernard Msamanga; Wafaie W Fawzi; Christopher P Duggan
Journal:  J Nutr       Date:  2012-12-19       Impact factor: 4.798

6.  Incidence and duration of severe wasting in two African populations.

Authors:  Michel Garenne; Douladel Willie; Bernard Maire; Olivier Fontaine; Roger Eeckels; André Briend; Jan Van den Broeck
Journal:  Public Health Nutr       Date:  2009-03-02       Impact factor: 4.022

7.  Methodology for estimating regional and global trends of child malnutrition.

Authors:  Mercedes de Onis; Monika Blössner; Elaine Borghi; Richard Morris; Edward A Frongillo
Journal:  Int J Epidemiol       Date:  2004-11-12       Impact factor: 7.196

Review 8.  Effect measures in prevalence studies.

Authors:  Neil Pearce
Journal:  Environ Health Perspect       Date:  2004-07       Impact factor: 9.031

Review 9.  Maternal and child undernutrition: consequences for adult health and human capital.

Authors:  Cesar G Victora; Linda Adair; Caroline Fall; Pedro C Hallal; Reynaldo Martorell; Linda Richter; Harshpal Singh Sachdev
Journal:  Lancet       Date:  2008-01-26       Impact factor: 79.321

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

Authors:  Assaye Bulti; André Briend; Nancy M Dale; Arjan De Wagt; Faraja Chiwile; Stanley Chitekwe; Chris Isokpunwu; Mark Myatt
Journal:  Arch Public Health       Date:  2017-11-09
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  2 in total

1.  Predictors of time to recovery and non-response during outpatient treatment of severe acute malnutrition.

Authors:  Suvi T Kangas; Cécile Salpéteur; Victor Nikièma; Christian Ritz; Henrik Friis; André Briend; Pernille Kaestel
Journal:  PLoS One       Date:  2022-05-31       Impact factor: 3.752

2.  Utilization patterns, outcomes and costs of a simplified acute malnutrition treatment programme in Burkina Faso.

Authors:  Ryoko Sato; Maguy Daures; Kevin Phelan; Susan Shepherd; Moumouni Kinda; Renaud Becquet; Robert Hecht; Stephen Resch
Journal:  Matern Child Nutr       Date:  2021-12-26       Impact factor: 3.092

  2 in total

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