Evidence map›Paper›PMID 41345721›Full record

ArticleMaternal health, neonatology and perinatology2025

Prevalence and determinants of macrosomia in low- and middle-income countries: a multilevel analysis of population survey data from 44 nations.

Oumer Abdulkadir Ebrahim, Kusse Urmale Mare, Kebede Gemeda Sabo, Abdulkerim Hassen Moloro, Begetayinoral Kussia Lahole, Setognal Birara Aychiluhm, Habtamu Solomon Demeke, Beriso Furo Wengoro

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Maternal health, neonatology and perinatology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Oumer Abdulkadir EbrahimDepartment of Public Health, College of Medicine and Health Sciences, Samara University, Samara, Ethiopia.
Kusse Urmale MareDepartment of Nursing, College of Medicine and Health Sciences, Samara University, Samara, Ethiopia. kussesinbo@gmail.com.
Kebede Gemeda SaboDepartment of Nursing, College of Medicine and Health Sciences, Samara University, Samara, Ethiopia.
Abdulkerim Hassen MoloroDepartment of Nursing, College of Medicine and Health Sciences, Samara University, Samara, Ethiopia.
Begetayinoral Kussia LaholeDepartment of Midwifery, College of Medicine and Health Sciences, Arba Minch University, Arba Minch, Ethiopia.
Setognal Birara AychiluhmDepartment of Epidemiology & Biostatistics, Institute of Public Health, College of Medicine & Health Sciences, University of Gondar, Gondar, Ethiopia.
Habtamu Solomon DemekeDepartment of Public Health, College of Medicine and Health Sciences, Samara University, Samara, Ethiopia.
Beriso Furo WengoroDepartment of Biomedical Sciences, College of Medicine and Health Sciences, Samara University, Samara, Ethiopia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAlthough excessive birth weight is associated with short-term and long-term effects for both neonates and mothers, there is a gap in our understanding of its prevalence and contributing factors in low- and middle-income countries. Moreover, previous studies primarily focused on low birth weight and were limited to a specific geographic area. Therefore, this study aimed to estimate the prevalence of macrosomia and identify its determinants using data from 44 countries.

methodsData were obtained from demographic and health surveys conducted between 2015 and 2022 across 44 LMICs and a weighted total of 343,898 birth records was included in the analysis. Mixed-effect logistic regression models were fitted to identify determinants of excessive birth weight and the models were compared based on log-likelihood and deviance values. A p-value less than 0.05 and an adjusted odds ratio with the corresponding 95% confidence interval were used to identify determinants of macrosomia.

resultsThe overall prevalence of excessive birth weight among neonates in LMCs was 7.1% [95% CI: 6.1%-8.1%], varying from 1.3% in India to 27% in Chad. The odds of excessive birth weight were higher in neonates born to mothers from households without health insurance [AOR (95% CI): 1.50 (1.36–1.65)], mothers with primary education [AOR (95% CI): 1.19 (1.09–1.31)], those born to multipara [AOR (95% CI): 1.13 (1.04–1.24), grand multipara [AOR (95% CI): 1.36 (1.20–1.54)], and overweight or obese mother [AOR (95% CI): 1.54 (1.44–1.66)]. Moreover, maternal age, number of antenatal care visits, sex of neonate, place of residence, and region were the other determinants of macrosomia.

conclusionAbout 7% of neonates in low- and middle-income countries had excessive weight at birth, with a significant variation across the countries. Therefore, strengthening programs aimed at improving maternal literacy and promoting healthy weight management before and during pregnancy is crucial. Moreover, improving access to antenatal care and health insurance and developing programs that address the specific needs of at-risk populations, such as older, multiparous, and rural women could help reduce the incidence of macrosomia.

Indexed as

Demographic and health surveyDeterminantsExcessive birth weightLow- and middle-income countriesMixed-effect analysis

Identifiers

PMID41345721
PMCPMC12679716

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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 Socratic graph.