ArticleJAMA network open2023
Population-Modifiable Risk Factors Associated With Childhood Stunting in Sub-Saharan Africa.
Article in JAMA network open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 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
14 citing papers in PubMed, 17 citations in OpenAlex.
- Predicting and identifying determinants of stunting among school-aged children in Ethiopia: a machine learning approach.Journal of health, population, and nutrition · 2026Article
- Urban-rural disparities in child linear growth: a decomposition analysis of digital, physical, and socioeconomic environments in seven least-developed countries.Journal of global health · 2026Article
- Trends in Stunting Prevalence and Sex-based Disparities among Children under Five in Somalia, 2000-2024: A Secondary Analysis of WHO Model-based Estimates.Journal of epidemiology and global health · 2026Article
- Predicting severe stunting and its determinants among under-five in Eastern African Countries: A machine learning algorithms.PloS one · 2026Article
- Mortality and risk factors of small vulnerable newborns in 32 low- and middle-income countries.BMC medicine · 2025Article
- Association between poor mental health in mothers and child stunting: a population-based cross-sectional study in Rwanda.BMJ open · 2025Article
- Determinants of Stunting Among Children Aged 0.5 to 12 Years in Peninsular Malaysia: Findings from the SEANUTS II Study.Nutrients · 2025Article
- Stunting Among Low-Income Families in Indonesia: Is Mother's Employment a Risk Factor?Journal of research in health sciences · 2025Article
- Population attributable fractions for modifiable risk factors of neonatal, infant, and under-five mortality in 48 low- and middle-income countries.Journal of global health · 2025Article
- Article
- Birth weight mediates the association of maternal undernutrition with child undernutrition prevalence in West Africa.European journal of clinical nutrition · 2024Article
- Prevalence of stunting and its correlates among children under 5 in Afghanistan: the potential impact of basic and full vaccination.BMC pediatrics · 2024Article
- Population modifiable risk factors associated with neonatal mortality in 35 sub-Saharan Africa countries: analysis of data from demographic and health surveys.EClinicalMedicine · 2024Article
- Population modifiable risk factors associated with under-5 acute respiratory tract infections and diarrhoea in 25 countries in sub-Saharan Africa (2014-2021): an analysis of data from demographic and health surveys.EClinicalMedicine · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
14 authors at 8 institutions in 4 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Importance: Identifying modifiable risk factors associated with childhood stunting in sub-Saharan Africa (SSA) is imperative for the development of evidence-based interventions and to achieve the Sustainable Development Goals. Objective: To evaluate key modifiable risk factors associated with childhood stunting in SSA. Design, Setting, and Participants: This cross-sectional study examined the most recent (2014-2021) Demographic and Health Surveys data for children younger than 5 years from 25 SSA countries. Exposures: Modifiable risk factors included history of diarrhea within 2 weeks, consumption of dairy products, maternal body mass index, maternal educational level, antenatal care visits, place of birth, wealth index, type of toilet, and type of cooking fuel. Main Outcomes and Measures: Stunting and severe stunting, measured using the height-for-age z score, were the main outcomes. Children who scored below -2.0 SDs or -3.0 SDs were classified as having stunted or severely stunted growth, respectively. Relative risks and 95% CIs were computed using generalized linear latent and mixed models and log-binomial link functions. Population-attributable fractions (PAFs) were calculated using adjusted relative risks and prevalence estimates for key modifiable risk factors. Results: This study included 145 900 children from 25 SSA countries. The mean (SD) age of the children was 29.4 (17.3) months, and 50.6% were male. The highest PAFs of severe childhood stunting were observed for mothers lacking a formal education (PAF, 21.9%; 95% CI, 19.0%-24.8%), children lacking consumption of dairy products (PAF, 20.8%; 95% CI, 16.8%-24.9%), unclean cooking fuel (PAF, 9.5%; 95% CI, 2.6%-16.3%), home birth (PAF, 8.3%; 95% CI, 6.3%-10.0%), and low-income household (PAF, 5.8%; 95% CI, 3.4%-8.0%). These 5 modifiable risk factors were associated with 51.6% (95% CI, 40.5%-60.9%) of the severe childhood stunting in SSA. Conclusions and Relevance: This cross-sectional study identified 5 modifiable risk factors that were associated with 51.6% of severe childhood stunting in SSA. These factors should be a priority for policy makers when considering future child health interventions to address chronic malnutrition in SSA.
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.