Mapping neonatal vulnerability using the Small Vulnerable Newborn (SVN) framework-secondary analysis of PRISMA Pakistan study.
retrospective_cohort · Level III
Where this comes from
- Record sourced from PubMed, PMID 39911163.
- Also identified by DOI 10.1016/j.lansea.2025.100535 and PMC identifier 11795797.
- Licence recorded as CC BY.
- The licence permits redistribution, so the abstract is shown in full and the full text is available from the publisher.
Abstract
Despite progress in global neonatal mortality, South Asia continues to lag behind in reducing neonatal deaths. The Small Vulnerable Newborn (SVN) framework has been proposed to integrate preterm birth (PT), small for gestational age (SGA), and low birth weight. However, there is lack of data on the burden and risk factors of SVN in Pakistan, a country which has one of the highest neonatal deaths globally. This study aimed to estimate the incidence of SVN, and identify risk factors among pregnant women in Pakistan. This secondary analysis leverages data from PRISMA (Pregnancy Risk Infant Surveillance, and Measurement Alliance)-Pakistan. Women presenting ≤20 weeks gestation and, with birth weights recorded within 72 h post-delivery were analysed. Newborns were classified into categories of SVN. Multinomial and binomial regression models were used to examine associations between maternal characteristics and SVN categories, as well as neonatal mortality. The overall incidence of SVN was 46% (n = 771) with Term + SGA being the most common category (n = 461, 27.5%), followed by PT + AGA (n = 210, 12.5%) and PT + SGA (n = 41, 2.5%). Maternal undernutrition (MUAC <23 cm) increased the risk of SVN by 17% (aRR 1.17, 95% CI 1.05-1.31). SVN also emerged as a significant predictor of neonatal mortality, quadrupling the risk (aRR 4.52, 95% CI 2.42-8.46). This study adds to the growing body of evidence on Pakistan's alarming burden of SVN, with every second newborn at risk. Identification and targeted interventions are imperative to mitigate adverse birth outcomes and optimize child growth and development. No funding was received for this secondary data analysis.