Related Experiment Video

Updated: Jul 31, 2025

Assessment and Evaluation of the High Risk Neonate: The NICU Network Neurobehavioral Scale

Assessment and Evaluation of the High Risk Neonate: The NICU Network Neurobehavioral Scale

Published on: August 25, 2014

Vulnerable newborn types: analysis of subnational, population-based birth cohorts for 541 285 live births in

D J Erchick¹, E A Hazel¹, J Katz¹

¹Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA.

BJOG : an International Journal of Obstetrics and Gynaecology

|May 8, 2023

Abstract

Objective:

To examine prevalence of novel newborn types among 541 285 live births in 23 countries from 2000 to 2021.

Design:

Descriptive multi-country secondary data analysis.

Setting:

Subnational, population-based birth cohort studies (n = 45) in 23 low- and middle-income countries (LMICs) spanning 2000-2021.

Population:

Liveborn infants.

Methods:

Subnational, population-based studies with high-quality birth outcome data from LMICs were invited to join the Vulnerable Newborn Measurement Collaboration. We defined distinct newborn types using gestational age (preterm [PT], term [T]), birthweight for gestational age using INTERGROWTH-21st standards (small for gestational age [SGA], appropriate for gestational age [AGA] or large for gestational age [LGA]), and birthweight (low birthweight, LBW [<2500 g], nonLBW) as ten types (using all three outcomes), six types (by excluding the birthweight categorisation), and four types (by collapsing the AGA and LGA categories). We defined small types as those with at least one classification of LBW, PT or SGA. We presented study characteristics, participant characteristics, data missingness, and prevalence of newborn types by region and study.

Results:

Among 541 285 live births, 476 939 (88.1%) had non-missing and plausible values for gestational age, birthweight and sex required to construct the newborn types. The median prevalences of ten types across studies were T+AGA+nonLBW (58.0%), T+LGA+nonLBW (3.3%), T+AGA+LBW (0.5%), T+SGA+nonLBW (14.2%), T+SGA+LBW (7.1%), PT+LGA+nonLBW (1.6%), PT+LGA+LBW (0.2%), PT+AGA+nonLBW (3.7%), PT+AGA+LBW (3.6%) and PT+SGA+LBW (1.0%). The median prevalence of small types (six types, 37.6%) varied across studies and within regions and was higher in Southern Asia (52.4%) than in Sub-Saharan Africa (34.9%).

Conclusions:

Further investigation is needed to describe the mortality risks associated with newborn types and understand the implications of this framework for local targeting of interventions to prevent adverse pregnancy outcomes in LMICs.

Keywords:

low birthweight newborn preterm birth small for gestational age

More Related Videos

A Novel Method for Involving Women of Color at High Risk for Preterm Birth in Research Priority Setting

A Novel Method for Involving Women of Color at High Risk for Preterm Birth in Research Priority Setting

Published on: January 12, 2018

Author Spotlight: Assessing the Feasibility of Using Amplitude-Integrated EEG During Neonatal Transport

Author Spotlight: Assessing the Feasibility of Using Amplitude-Integrated EEG During Neonatal Transport

Published on: June 21, 2024

Related Concept Videos

Prevalence and Incidence

Prevalence and Incidence

In statistical epidemiology and health sciences, two essential metrics—prevalence and incidence—are fundamental for understanding disease dynamics within a population. These measures enable public health officials, epidemiologists, and researchers to assess the burden of diseases, allocate resources effectively, and design impactful public health policies and interventions.
Prevalence indicates the proportion of individuals in a population who have a specific disease or health...

Statistical Methods for Analyzing Epidemiological Data

Statistical Methods for Analyzing Epidemiological Data

Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:

Bias in Epidemiological Studies

Bias in Epidemiological Studies

Biases can arise at various stages of research, from study design and data collection to analysis and interpretation. Recognizing and addressing these biases is essential to ensure the validity and reliability of epidemiological findings.Broadly speaking, biases in epidemiology fall into three main categories: selection bias, information bias, and confounding. A more detailed description of possible biases is:

Population Growth

Population Growth

Population size is dynamic, increasing with birth rates and immigration, and decreasing with death rates and emigration. In ideal conditions with unlimited resources, populations can increase exponentially, which plots as a J-shaped growth rate curve of population size against time. This type of curve is characteristic of newly-introduced invasive species, or populations that have suffered catastrophic declines and are rebounding.

Analysis of Population Pharmacokinetic Data

Analysis of Population Pharmacokinetic Data

Analysis of population pharmacokinetic data involves studying the behavior of drugs within diverse populations to understand their pharmacokinetic parameters. Traditional pharmacokinetic methods typically involve collecting samples from a few individuals and estimating these parameters. While these methods are commonly used, they have limitations in capturing the variability in drug response among individuals or heterogeneous populations. Population pharmacokinetics is employed to address these...

Relative Risk

Relative Risk

Relative risk (RR) is a statistical measure commonly used in epidemiology to compare the likelihood of a particular event occurring between two groups. This metric is important for evaluating the relationship between exposure to a specific risk factor and the probability of a particular outcome. It plays a crucial role in medical research, public health studies, and risk assessment. Relative risk quantifies how much more (or less) likely an event is to occur in an exposed group compared to an...

Articles linked to this work by shared authors, journal, and citation graph.

Validation of neurodevelopmental assessments for early detection of high-risk infants in Zimbabwe: protocol for the Child Development Observation study (ChiDO study).

BMJ paediatrics open·2026

Effect of a person-centered care intervention on return and sustained reengagement after treatment interruptions from HIV care in Zambia: A post-hoc analysis of a stepped-wedged cluster randomized trial.

PLoS medicine·2026

Integrating Genomic Studies into Large Birth Cohorts.

Genomics, proteomics & bioinformatics·2026

Genome-wide association analyses of gestational phenotypes identify context-specific genetic effects.

Nature genetics·2026

Effect of fortified balanced energy-protein supplementation during pregnancy and lactation on infant neurodevelopment: a community-based randomized controlled trial in rural Nepal.

medRxiv : the preprint server for health sciences·2026

'Prevention is better than cure': a mixed methods study of communities' and healthcare workers' perspectives on new adult and adolescent TB vaccines and their implementation in Zambia.

BMJ public health·2026

See all related articles