Predicting neurodevelopmental delay among two-year-old infants in Northern Uganda.
15 affiliations
- 1Department of Community and Public Health, Busitema University, Mbale, Uganda.
- 2Department of Research, Nikao Medical Center, Kampala, Uganda.
- 3Department of Paediatrics and Child Health, School of Medicine, Makerere University College of Health Sciences, Kampala, Uganda.
- 4Department of Health Policy, Planning and Management, School of Public Health, College of Health Sciences, Makerere University, Kampala, Uganda.
- 5Center for Internation Health, Department of Global Public Health and Primary Care, University of Bergen, Bergen, Norway.
- 6Department of Obstetrics and Gynaecology, Busitema University Faculty of Health Sciences, Mbale, Uganda.
- 7Department of Paediatrics and Child Health, Gulu University, Gulu, Uganda.
- 8Department of Obstetrics and Gynaecology, Gulu University, Gulu, Uganda.
- 9Department of Paediatrics and Child Health, University of Juba, Juba, South Sudan.
- 10Department of Research, Makerere University Hospital, Kampala, Uganda.
- 11Department of Nursing, School of Medicine, Kabale University, Kabale, Uganda.
- 12Division of Computational and Data Science, Washington University in St. Louis, St. Louis, MO, USA.
- 13Centre for Intervention Science and Maternal Child Health (CISMAC), Centre for International Health, University of Bergen, Bergen, Norway.
- 14Department of Epidemiology and Biostatistics, School of Public Health, Makerere University College of Health Sciences, Kampala, Uganda.
- 15Department of Paediatrics and Child Health, Kabale University, Kabale, Uganda.
Abstract
Background
Data on neurodevelopmental disabilities in sub-Saharan Africa are scarce. Identifying children at the highest risk of neurodevelopmental delay could enable health workers to target these groups more effectively, improve resource allocation and programmatic focus.Objective
To develop and assess a model for predicting neurodevelopmental delay among two-year-old infants in Northern Uganda using easily obtainable predictors.Methods
We studied children born to women enrolled in a cluster randomized controlled trial (January 2018-March 2019) evaluating the effect of peer counseling on health facility births. At the trial's final visit (day 50), 1,804 children were enrolled. In November 2020, we followed up 1,421 children (78.8%) and assessed their neurodevelopment at 2 years using the Malawi Developmental Assessment Tool. We used least absolute shrinkage and selection operator penalized regression with 10-fold cross-validation to select the best subset of predictors and assessed model performance using the area under the curve (AUC).Results
Of the 1,421 children, 70 (4.9%; 95% CI: 3.6-6.7%) had neurodevelopmental delays. Of the 19 candidate predictors, six were retained in the final model (lambda = 0.0076): moderate wasting, prolonged neonatal hospitalization (up to 28 days), maternal education, place of birth, preterm birth, and absence of skin-to-skin contact at birth. The model showed strong discriminative power (AUC 0.75) and reasonable calibration (calibration slope 1.37; calibration belt 0.536-0.727).Conclusion
We developed a promising tool for identifying infants at increased risk of neurodevelopmental delay in low-resource settings, which could help prioritize children for follow-up and specialized interventions.
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BibTeX
@article{mukunya2026predicting,
title = {{Predicting neurodevelopmental delay among two-year-old infants in Northern Uganda.}},
author = {David Mukunya and Grace Ndeezi and Gertrude Namazzi and Thorkild Tylleskär and Brendah Nambozo and Milton W Musaba and Beatrice Odongkara and Vincentina Achora and Justin Bruno Tongun and Josephine Tumuhamye and Agnes Napyo and Vicent Ssentumbwe and Victoria Nankabirwa and James K Tumwine},
journal = {Global health action},
year = {2026},
month = oct,
doi = {10.1080/16549716.2026.2748101},
url = {https://europepmc.org/article/MED/42876325},
note = {CC BY},
}
RIS
TY - JOUR
TI - Predicting neurodevelopmental delay among two-year-old infants in Northern Uganda.
AU - David Mukunya
AU - Grace Ndeezi
AU - Gertrude Namazzi
AU - Thorkild Tylleskär
AU - Brendah Nambozo
AU - Milton W Musaba
AU - Beatrice Odongkara
AU - Vincentina Achora
AU - Justin Bruno Tongun
AU - Josephine Tumuhamye
AU - Agnes Napyo
AU - Vicent Ssentumbwe
AU - Victoria Nankabirwa
AU - James K Tumwine
PY - 2026
DA - 2026/10/15
JO - Global health action
DO - 10.1080/16549716.2026.2748101
UR - https://europepmc.org/article/MED/42876325
AB - Background Data on neurodevelopmental disabilities in sub-Saharan Africa are scarce. Identifying children at the highest risk of neurodevelopmental delay could enable health workers to target these groups more effectively, improve resource allocation and programmatic focus.Objective To develop and assess a model for predicting neurodevelopmental delay among two-year-old infants in Northern Uganda using easily obtainable predictors.Methods We studied children born to women enrolled in a cluster randomized controlled trial (January 2018-March 2019) evaluating the effect of peer counseling on health facility births. At the trial's final visit (day 50), 1,804 children were enrolled. In November 2020, we followed up 1,421 children (78.8%) and assessed their neurodevelopment at 2 years using the Malawi Developmental Assessment Tool. We used least absolute shrinkage and selection operator penalized regression with 10-fold cross-validation to select the best subset of predictors and assessed model performance using the area under the curve (AUC).Results Of the 1,421 children, 70 (4.9%; 95% CI: 3.6-6.7%) had neurodevelopmental delays. Of the 19 candidate predictors, six were retained in the final model (lambda = 0.0076): moderate wasting, prolonged neonatal hospitalization (up to 28 days), maternal education, place of birth, preterm birth, and absence of skin-to-skin contact at birth. The model showed strong discriminative power (AUC 0.75) and reasonable calibration (calibration slope 1.37; calibration belt 0.536-0.727).Conclusion We developed a promising tool for identifying infants at increased risk of neurodevelopmental delay in low-resource settings, which could help prioritize children for follow-up and specialized interventions.
SN - 1654-9716
SN - 1654-9880
ER -