Asthma Prevalence Associated with Geographical Latitude and Regional Insolation in the United States of America and Australia
Bibliographic record
Abstract
BACKGROUND: It has been proposed that vitamin D deficiency may be responsible for an increase in the prevalence of allergic diseases and asthma worldwide. Human ability to generate physiologically required quantities of vitamin D through sun exposure is decreasing with increasing geographical latitude. OBJECTIVES: Considering that vitamin D deficiency is usually due to lack of outdoor sun exposure, this study is designed to test the hypothesis that a higher prevalence of asthma should be expected at high relative to low geographical latitudes. METHODS: Linear regression analyses are performed on asthma prevalence in the U.S. adult population vs. geographical latitude, insolation, air temperature, and air pollution (PM(2.5)) for 97 major metropolitan/micropolitan statistical areas of the continental United States of America and on general population asthma prevalence vs. geographical latitude in eight metropolitan areas of Australia. RESULTS: A 10° change in geographical latitude from southern to northern regions of the Eastern Seaboard is associated with a 2% increase in adult asthma prevalence (p<0.001). Total insolation in winter months is almost as strong as latitude in its ability to explain the observed spatial variation in the prevalence of asthma (r(2) = 0.43; p<0.001). Similar results are obtained using the Australian data (r(2) = 0.73; p<0.01), suggesting a consistent association between the latitude/insolation and asthma prevalence worldwide. CONCLUSIONS: The results of this study suggest that, as a known modulator of the immune response closely linked with the geographical latitude and erythemal UV irradiation, vitamin D may play an important role in the development/exacerbation of asthma.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".