The Effects of Magnesium Supplementation on Exercise Performance
Bibliographic record
Abstract
OBJECTIVES: Magnesium (Mg) status, although difficult to assess, is suspected to be marginal in many individuals, especially athletes, and this has led to the common use of Mg supplements. The purpose of this article is to critique research that has addressed Mg supplementation in athletes. DATA SOURCES: The primary database was Medline, which was searched for English articles from 1966 to June 1999 using the words "magnesium" and "supplementation." STUDY SELECTION: Only experimental studies dealing with human subjects, Mg supplementation, and exercise performance were critiqued (n = 12). DATA EXTRACTION: Quality of critiqued articles was based on 1) use of cross-over designs, 2) how and if Mg status was assessed, 3) whether treatment was solely Mg supplementation, 4) duration of supplementation, 5) subject number, and 6) degree of experimental control. Articles were classified into "no effect" and "positive effect," and also were examined in regard to the type of performance outcome (strength, anaerobic-lactacid, and aerobic). DATA SYNTHESIS: Mg is a cofactor to over 325 enzymatic reactions, and a deficiency of the mineral therefore has many physiological and exercise performance implications. Low dietary intakes, as found in many female athletes, coupled with increased urinary losses with exercise, may eventually lead to an Mg deficiency. Strength of evidence favors those studies finding no effect of Mg supplementation, regardless of whether the performance outcome was strength, anaerobic-lactacid, or aerobic. Analysis was confounded due to: 1) variable exercise modes, intensities, and durations, 2) variable training states and ages of subjects, 3) subject selection favoring males and gender differences has not been probed, 4) Mg dosage has ranged from 1 day to 3 months and from 116 mg/day to 500 mg/day, 5) multivitamins/minerals have been ingested with the Mg, 6) with one exception, Mg status was either not reported or reliant on total Mg (TMg), 7) lack of a cross-over design, 8) only one study made note of controlling exercise prior to exercise testing and blood assay, and 9) typical Mg intake measured was only measured in three of the studies. CONCLUSIONS: Most evidence indicates no effect of Mg supplementation on performance (strength, anaerobic-lactacid, and aerobic). When only peak treadmill speed during a VO2 max test is examined, the strength of evidence is equivocal. Trained subjects appear to benefit less than untrained subjects, but this observation requires further study. Little research has focused on physically active females who may be at the highest risk for Mg deficiency. Research has been confounded by numerous factors.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".