Lower serum magnesium concentration is associated with diabetes, insulin resistance, and obesity in South Asian and white Canadian women but not men
Bibliographic record
Abstract
Background: A large proportion of adults in North America are not meeting recommended intakes for magnesium (Mg). Women and people of South Asian race may be at higher risk for Mg deficiency because of lower Mg intakes relative to requirements and increased susceptibility to diabetes, respectively.Objective: This study compared serum Mg concentrations in South Asian (n=276) and white (n=315) Canadian women and men aged 20–79 years living in Canada’s Capital Region and examined the relationship with diabetes, glucose control, insulin resistance, and body mass index.Results: Serum Mg concentration was lower in women of both races and South Asians of both genders. Racial differences in serum Mg were not significant after controlling for use of diabetes medication. A substantial proportion of South Asian (18%) and white (9%) women had serum Mg <0.75 mmol/L indicating hypomagnesemia. Use of diabetes medication and indicators of poorer glucose control, insulin resistance, and obesity were associated with lower serum Mg in women, but not in men.Conclusions: These results suggest that the higher incidence of diabetes in South Asians increases their risk for Mg deficiency and that health conditions that increase Mg requirements have a greater effect on Mg status in women than men.Keywords: adults; body mass index; glucose; homeostatic model assessment of insulin resistance; magnesium status; McAuley’s index; quantitative insulin sensitivity check index(Published: 5 May 2015)Citation: Food & Nutrition Research 2015, 59: 25974 - http://dx.doi.org/10.3402/fnr.v59.25974
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".