Mapping child growth failure across low- and middle-income countries

Journal article


Kinyoki, D., Osgood-Zimmerman, A., Pickering, B., Schaeffler, L., Ausloos, M., Herteliu, C., Kassenbaum, N. and Hay, S. (2020). Mapping child growth failure across low- and middle-income countries. Nature. 577 (7789), pp. 231-234.
AuthorsKinyoki, D., Osgood-Zimmerman, A., Pickering, B., Schaeffler, L., Ausloos, M., Herteliu, C., Kassenbaum, N. and Hay, S.
Abstract

Childhood malnutrition is associated with high morbidity and mortality globally1. Undernourished children are more likely to experience cognitive, physical, and metabolic developmental impairments that can lead to later cardiovascular disease, reduced intellectual ability and school attainment, and reduced economic productivity in adulthood2. Child growth failure (CGF), expressed as stunting, wasting, and underweight in children under five years of age (0–59 months), is a specific subset of undernutrition characterized by insufficient height or weight against age-specific growth reference standards3,4,5. The prevalence of stunting, wasting, or underweight in children under five is the proportion of children with a height-for-age, weight-for-height, or weight-for-age z-score, respectively, that is more than two standard deviations below the World Health Organization’s median growth reference standards for a healthy population6. Subnational estimates of CGF report substantial heterogeneity within countries, but are available primarily at the first administrative level (for example, states or provinces)7; the uneven geographical distribution of CGF has motivated further calls for assessments that can match the local scale of many public health programmes8. Building from our previous work mapping CGF in Africa9, here we provide the first, to our knowledge, mapped high-spatial-resolution estimates of CGF indicators from 2000 to 2017 across 105 low- and middle-income countries (LMICs), where 99% of affected children live1, aggregated to policy-relevant first and second (for example, districts or counties) administrative-level units and national levels. Despite remarkable declines over the study period, many LMICs remain far from the ambitious World Health Organization Global Nutrition Targets to reduce stunting by 40% and wasting to less than 5% by 2025. Large disparities in prevalence and progress exist across and within countries; our maps identify high-prevalence areas even within nations otherwise succeeding in reducing overall CGF prevalence. By highlighting where the highest-need populations reside, these geospatial estimates can support policy-makers in planning interventions that are adapted locally and in efficiently directing resources towards reducing CGF and its health implications.

Year2020
JournalNature
Journal citation577 (7789), pp. 231-234
PublisherSpringer Science and Business Media LLC
ISSN0028-0836
Digital Object Identifier (DOI)doi:10.1038/s41586-019-1878-8
Publication dates
PrintJan 2020
Online08 Jan 2020
Publication process dates
Accepted14 Nov 2019
Deposited10 Feb 2020
Publisher's version
License
CC BY 4.0
File Access Level
Open
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https://openresearch.lsbu.ac.uk/item/88zz1

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Global, regional, and national age-sex specific mortality for 264 causes of death, 1980–2016: a systematic analysis for the Global Burden of Disease Study 2016
Naghavi, Mohsen, Abajobir, Amanuel Alemu, Abbafati, Cristiana, Abbas, Kaja M, Abd-Allah, Foad, Abera, Semaw Ferede, Aboyans, Victor, Adetokunboh, Olatunji, Afshin, Ashkan, Agrawal, Anurag, Ahmadi, Alireza, Ahmed, Muktar Beshir, Aichour, Amani Nidhal, Aichour, Miloud Taki Eddine, Aichour, Ibtihel, Aiyar, Sneha, Alahdab, Fares, Al-Aly, Ziyad, Alam, Khurshid, Alam, Noore, Alam, Tahiya, Alene, Kefyalew Addis, Al-Eyadhy, Ayman, Ali, Syed Danish, Alizadeh-Navaei, Reza, Alkaabi, Juma M, Alkerwi, Ala'a, Alla, François, Allebeck, Peter, Allen, Christine, Al-Raddadi, Rajaa, Alsharif, Ubai, Altirkawi, Khalid A, Alvis-Guzman, Nelson, Amare, Azmeraw T, Amini, Erfan, Ammar, Walid, Amoako, Yaw Ampem, Anber, Nahla, Andersen, Hjalte H, Andrei, Catalina Liliana, Androudi, Sofia, Ansari, Hossein, Antonio, Carl Abelardo T, Anwari, Palwasha, Ärnlöv, Johan, Arora, Megha, Artaman, Al, Aryal, Krishna Kumar, Asayesh, Hamid, Asgedom, Solomon W, Atey, Tesfay Mehari, Avila-Burgos, Leticia, Avokpaho, Euripide 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