The Bidirectional Relationship Between Iron Deficiency Anemia and Chronic Headache Disorders: A Systematic Review and Meta‐Analysis
Bibliographic record
Abstract
Background and Objective: IDA and chronic headache disorders such as migraines and tension‐type headaches are common conditions that significantly affect quality of life. Emerging evidence suggests a bidirectional relationship between these two conditions. This systematic review and meta‐analysis aimed to explore and quantify the association between iron deficiency anemia (IDA) and chronic headache disorders, with a focus on understanding the bidirectional nature of this relationship. Methods: A comprehensive literature search was conducted across PubMed, Embase, and Web of Science to identify relevant studies published up until August 10, 2024. Observational studies examining the prevalence, incidence, or association between IDA and chronic headache disorders were included. Data were extracted and assessed for quality using the Newcastle–Ottawa Scale. Meta‐analyses were performed using a random‐effects model to calculate pooled prevalence rates and risk ratios (RRs), with heterogeneity assessed via the I 2 statistic and meta‐regression. A sensitivity analysis was conducted using the leave‐one‐out approach, and publication bias was evaluated through a funnel plot. Results: The meta‐analysis included 13 studies: five studies examined chronic headaches among patients with IDA, and eight studies examined IDA among patients with chronic headaches. The pooled prevalence of chronic headaches among patients with IDA was 38% (95% CI: 15%–69%). In addition, 20% (95% CI: 10%–35%) of patients with chronic headaches were found to have IDA. Anemic patients were found to have a 76% higher risk of developing chronic headaches compared to nonanemic individuals (RR: 1.76; 95% CI: 1.22–2.52). Significant heterogeneity was observed across the studies. Conclusion: This meta‐analysis demonstrates a significant association between IDA and chronic headache disorders, with a pooled prevalence of 38% for chronic headaches in IDA patients and 20% for IDA in chronic headache patients. IDA was associated with a 76% higher risk of chronic headaches. Routine screening for IDA in high‐risk populations may improve headache outcomes, but further longitudinal studies are needed to establish causality and refine management strategies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.017 | 0.039 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.013 | 0.037 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 source (direct Gemma or distilled Codex), 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".