Article Text

Village-level climate and weather variability, mediated by village-level crop yield, is associated with linear growth in children in Uganda
  1. Paddy Ssentongo1,
  2. Djibril M Ba1,
  3. Claudio Fronterre2,
  4. Vernon M Chinchilli1
  1. 1Public Health Science, Penn State Health Milton S Hershey Medical Center, Hershey, Pennsylvania, USA
  2. 2Centre for Health Informatics, Computing and Statistics, Lancaster University, Lancaster, UK
  1. Correspondence to Dr Paddy Ssentongo; pssentongo{at}pennstatehealth.psu.edu

Abstract

Introduction To investigate total annual precipitation, precipitation anomaly and aridity index in relation to linear growth in children under 5 in Uganda and quantify the mediating role of crop yield.

Methods We analysed data of 5219 children under 5 years of age who participated in the 2016 Uganda Demographic and Health Survey. Annual crop yield in kilograms per hectare for 42 crops at a 0.1° (~10 km at the equator) spatial resolution square grid was obtained from the International Food Policy Research Institute. Normalised rainfall anomaly and total precipitation were derived from the African Rainfall Estimation Algorithm Version 2 product. Linear regression models were used to associate total annual precipitation and anomalies with height-for-age z-scores and to explore the mediating role of crop yield qualitatively. The intervening effects were quantitatively estimated by causal mediation models.

Results Twenty-nine per cent of children were stunted (95% CI 28% to 31%). After adjusting for major covariates, higher total annual precipitation was significantly associated with increasing height-for-age z-scores. At the mean, an increase of 1 standard deviation in local annual rainfall was associated with a 0.07-point higher z-score. Aridity index and precipitation anomaly were not associated with height-for-age z scores in altitude-adjusted models. Crop yields of nuts, seeds, cereals and pulses were significant mediating factors. For instance, 38% of the association between total annual precipitation with height-for-age z-scores can be attributed to the yield of sesame seeds.

Conclusions Higher total annual precipitation at the village-level was significantly associated with higher height-for-age z-scores among children in Uganda. This association can be partially explained by higher crop yield, especially from seeds and nuts. This study suggests that more attention should be paid to villages with lower annual rainfall amounts to improve water availability for agriculture.

  • nutritional and metabolic disorders
  • public health
  • stunting
  • epidemiology
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Footnotes

  • Handling editor Seye Abimbola

  • Twitter @Jeddy777

  • Contributors PS envisioned the study, extracted data, analysed data, drafted the manuscript and made subsequent revisions. DMB, CF and VMC provided critical revisions to the manuscript.

  • Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.

  • Competing interests None declared.

  • Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.

  • Patient consent for publication Not required.

  • Ethics approval The Uganda Demographic and Health Survey (UDHS) protocols and guidelines, including biomarker collection, were reviewed and approved by the Ugandan Ministry of Health (MOH) Ethical Review Committee and the Institutional Review Board of ICF International, USA. All research and methods were performed per the regulations and guidelines of the Ugandan MOH and ICF International, USA Ethical Review Committee, and the Institutional Review Board, respectively.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Data availability statement Data are available in a public, open access repository. The data sets were accessed after taking permission from Measure DHS. Data sets under the project Mapping Malnutrition in Children in Africa. The analysed dataset is available from: https://dhsprogram.com/data/dataset/Uganda_Standard-DHS_2016.cfm?flag=1. Data are available for download from the website after acquiring permission from Measure DHS.