ArticlePloS one2020
Abnormal birth weight in urban Nigeria: An examination of related factors.
Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
7 citing papers in PubMed, 20 citations in OpenAlex.
- Acceptability, Adherence, and Provision Through Antenatal Care: Evidence on Multiple Micronutrient Supplementation in Pakistan and Nigeria.Nutrients · 2026Article
- Pathway linking unwanted pregnancy to low birth weight in Indonesia: A conditional mediation analysis.Heliyon · 2024Article
- Dietary diversity and other predictors of low birth weight in Gurage Zone, Ethiopia: Prospective study.PloS one · 2024Article
- Maternal risk factors for low birthweight and macrosomia: a cross-sectional study in Northern Region, Ghana.Journal of health, population, and nutrition · 2023Article
- Antenatal care utilization on low birth weight children among women with high-risk births.F1000Research · 2023Article
- Biomass fuel use and birth weight among term births in Nigeria.PLOS global public health · 2022Article
- Outcomes and Disease Spectrum of LBW Neonates in a Secondary Health Facility.Journal of healthcare engineeringObservational
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 2 institutions in 1 country.
Funding
Abstract
There is a knowledge gap on abnormal birth weight in urban Nigeria where specific community contexts can have a significant impact on a child's health. Abnormal birth weight, classified into low birth weight and high birth weight, is often associated with adverse health outcomes and a leading risk for neonatal morbidity and mortality. The study used datasets from the birth recode file of 2013 and 2018 Nigeria Demographic and Health Survey (NDHS); a weighted sample of pooled 9,244 live births by 7,951 mothers within ten years (2008-2018) in urban Nigeria. The effects of individual, healthcare utilization and community-level variables on the two abnormal birth weight categories were explored with a multinomial logistic regression models using normal birth weight as a reference group. In urban Nigeria, the overall prevalence of ABW was 18.3%; high birth weight accounted for the majority (10.7%) of infants who were outside the normal birth weight range. Predictors of LBW were community (region), child characteristic (the type of birth) and household (wealth index) while that of HBW were community (regions), child characteristics (birth intervals and sex), maternal characteristic (education) and healthcare utilization (ANC registration). LBW was significantly more prevalent in the northern part while HBW was more common in the southern part of urban Nigeria. This pattern conforms to the expected north-south dichotomy in health indicators and outcomes. These differences can be linked to suggested variation in regional exposure to urbanization in Nigeria.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.