ArticleFrontiers in public health2025
Quantile regression application to identify key determinants of malnutrition in five West African countries of Gabon, Gambia, Liberia, Mauritania, and Nigeria.
Article in Frontiers in public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- The case for computational and artificial intelligence-based approaches for sustainable functional food systems for sub-Saharan Africa.Frontiers in nutrition · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
Background: Malnutrition remains one of the most pressing health challenges, particularly in developing nations across Africa, placing a significant burden on both public health agencies and the affected countries. In countries such as Gabon, Gambia, Mauritania, Liberia, and Nigeria, the burden of malnutrition exacerbates public health systems, strains economic resources, and hinders sustainable development, underscoring the urgent need for coordinated efforts at national and international levels. This study aimed to determine the scope and underlying factors contributing to the elevated incidence of malnutrition in West African countries, specifically Gabon, Gambia, Liberia, Mauritania, and Nigeria. Method: This study employed a quantile regression model to examine the determinants of malnutrition at various quantiles of interest across the Western African countries under consideration to facilitate focused policy measures and intervention strategies aimed at decreasing the prevalence. Results: For the lower quantiles (0.1 and 0.25), which indicate severe malnutrition, significant variables included the child's weight [quantile = 0.1, 95% CI(0.0063, 0.0103), quantile = 0.25, 95% CI(0.0054, 0.0107)], mother's education level [No education: quantile = 0.1, 95% CI(-49.7471, -32.1376), quantile = 0.25, 95% CI(-38.1513, -22.4438) Primary: quantile = 0.1, 95% CI(-24.8095, -5.7693), quantile = 0.25, 95% CI(-19.5273, -6.3424) Higher: quantile = 0.1, 95% CI(5.6499, 40.3274), quantile = 0.25, 95% CI(21.8158, 40.278)], drinking water source [Natural Sources: quantile = 0.1, 95% CI(0.6877, 24.384),Piped: quantile = 0.1, 95% CI(25.578, 45.2368), quantile = 0.25, 95% CI(22.2782, 34.8212), Bottle/Sachet: quantile = 0.25, 95% CI(3.438, 98.1675)], toilet type [Flush: quantile = 0.25, 95% CI(2.2598, 18.3457),Other: quantile = 0.1, 95% CI(8.7863, 24.504), quantile = 0.25, 95% CI(7.0995, 20.1119)], household wealth index [Poorest: quantile = 0.1, 95% CI(-52.5112, -16.9197), quantile = 0.25, 95% CI(-48.3804, -23.0633),Poorer: quantile = 0.1, 95% CI(-38.8744, -4.7586), quantile = 0.25, 95% CI(-34.6993, -9.1766), Middle: quantile = 0.25, 95% CI(-28.9491, -6.5834)], health care visits [No: quantile = 0.1, 95% CI(-19.293, -3.6393), quantile = 0.25, 95% CI(-17.2342, -5.6411)], consumption of fortified foods and tubers [No: quantile = 0.1, 95% CI(-36.3898, -12.0378), quantile = 0.25, 95% CI(-17.8127, -1.2374)], anemia status [Anemic: quantile = 0.1, 95% CI(-15.9326, -1.1929), quantile = 0.25, 95% CI(-12.3361, -1.5516)], mosquito net usage [No: quantile = 0.1, 95% CI(-22.0323, -0.8033), quantile = 0.25, 95% CI(-13.8107, 1.1366)], child's age [0 to 12 months: quantile = 0.1, 95% CI(81.6424, 105.7155), quantile = 0.25, 95% CI(61.4817, 78.5194),12 to 24 months: quantile = 0.1, 95% CI(0.5592, 24.933), 24 to 36 months: quantile = 0.1, 95% CI(7.9128, 40.2828)] and gender [Female: quantile = 0.1, 95% CI(4.5351, 17.9783), quantile = 0.25, 95% CI(5.0076, 15.4735)], and recent fever [No: quantile = 0.1, 95% CI(11.5663, 29.5984), quantile = 0.25, 95% CI(7.0313, 20.8918)]. Residence type was significant for the 0.25 quantile but not the 0.1 quantile [Rural: quantile = 0.25, 95% CI(-14.7051, -2.1455)]. At higher quantiles (0.75, 0.85, 0.9, and 0.95), factors such as the use of mosquito nets, formula feeding, and access to piped water remain significant, while socioeconomic determinants like maternal education and wealth index lose their influence. Common variables across all quantiles were mother's age, child's age (0 to 12 months), child's gender, and recent fever. Conclusion: These findings underscore the critical role of primary health care interventions in identifying and managing malnutrition, particularly among lower quantiles where severe malnutrition dominates. High-risk groups, such as teenagers and low-income mothers, should receive targeted support, including prenatal classes and counseling. Community caregivers can monitor at-risk individuals and ensure timely referrals, while collaborations with nonprofits can improve access to food and supplements. Promoting community food gardens, clean water access, and public workshops can further aid prevention and education efforts.
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.