Seasonal Variation in Hemoglobin A1c: Is It the Same in Both Hemispheres?
Bibliographic record
Abstract
INTRODUCTION: There are several reports from locations in the northern hemisphere of seasonal variation in hemoglobin A1c (HbA1c) levels with higher values noted in the cooler months. The variation has been attributed to holiday seasons, temperature differences, and changes in diet. This article describes the seasonal variation in both hemispheres and in a country on the equator with minimal temperature variation. METHODS: The mean and median HbA1c by month was calculated for a maximum of 2 years for HbA1c data from the different locations: Edmonton and Calgary, Canada; Singapore; Melbourne, Australia; and Marshfield, Wisconsin. The mean monthly temperature for each location was found from available meteorological information. RESULTS: In both northern and southern hemispheres, the HbA1c was higher in cooler months and lower in the warmer months. In Singapore, where there is minimal temperature variation, there is also minimal variation in HbA1c values over the year. The difference in HbA1c over a year appears to be related to the difference in temperature. CONCLUSION: Hemoglobin A1c is higher in cooler months and lower in the warmer months in both hemispheres. In a country with minimal monthly temperature variation, there is only minimal variation in HbA1c values through the year. In all locations, the mean and median HbA1c declined over the study period, possibly due to better glycemic control of patients with diabetes or an increase in use of HbA1c as a screening test for diabetes or a combination of both.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".