Prevalence and Determinants of Stunting-Anemia and Wasting-Anemia Comorbidities and Micronutrient Deficiencies in Children Under 5 in the Least-Developed Countries: A Systematic Review and Meta-analysis
Bibliographic record
Abstract
CONTEXT: Despite shifting from addressing isolated forms of malnutrition to recognizing its multifaceted nature, evidence on the prevalence and determinants of micronutrient deficiencies, and their coexistence with undernutrition in children under 5, remains insufficient, unsystematic, and incohesive. OBJECTIVE: The aim of this systematic review and meta-analysis was to assess the prevalence and determinants of stunting-anemia and wasting-anemia comorbidities and micronutrient deficiencies in children under 5 in the least-developed countries (LDCs). DATA SOURCES: Electronic searches took place from January 15, 2023, to February 14, 2024, across multiple databases, including PubMed, Embase, Web of Science, SCOPUS, African Index Medicus (AIM), World Health Organization's Institutional Repository for Information Sharing (IRIS), and African Journals Online. The search spanned the years 2000 to 2024, yet it yielded eligible full-text English research articles from only 2005 to 2021 conducted in LDCs. Studies lacking quantitative data on malnutrition types and their determinants were excluded. DATA EXTRACTION: Two independent authors assessed articles for bias and quality using Hoy et al's 10-item scale and Newcastle-Ottawa Scale (NOS) criteria. Prevalence and other details were extracted using a Joanna Briggs Institute Excel template. Authors extracted adjusted odds ratios (aORs) for determinant factors such as sex and vitamin A and iron supplementation. DATA ANALYSIS: The search yielded 6248 articles from 46 LDCs. Sixty-nine articles, with a total sample size of 181 605, met inclusion criteria for the final meta-analysis. Vitamin A deficiency affected 16.32% of children, and iodine deficiency affected 43.41% of children. The pooled prevalence of wasting-anemia and stunting-anemia comorbidity was 5.44% and 19.47%, respectively. Stunting was associated with vitamin A deficiency (aOR: 1.54; 95% CI: 1.01-2.37), and not taking vitamin A supplementation was associated with iron-deficiency anemia (aOR: 1.37; 95% CI: 1.21-1.55). CONCLUSION: A significant proportion of children under 5 in LDCs experienced stunting-anemia and wasting-anemia comorbidities and micronutrient deficiencies. This study underscores the urgent need to address factors driving these burdens. SYSTEMATIC REVIEW REGISTRATION: PROSPERO registration no. CRD42023409483.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.007 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".