The Gender Divide in Multiple Sclerosis: A Review of the Environmental Factors Influencing the Increasing Prevalence of Multiple Sclerosis in Women (P4.024)
Bibliographic record
Abstract
OBJECTIVE: To explore possible factors contributing to the increasing disparity in MS prevalence between women and men not purely of a genetic basis. BACKGROUND: The prevalence of MS is rising, and in particular the prevalence of RRMS in women is rising faster than MS in men. DESIGN/METHODS: The PUBMED database was searched over the timeframe of 2005 to 2013 using keywords “multiple sclerosis” AND: “vitamin D” “obesity” “increasing female incidence” “in-vitro fertilisation” or “smoking”. Only papers written in English with appropriate abstracts were screened and 32 pertinent articles were reviewed and included in this literature review. RESULTS: Obesity, smoking, reduced serum levels vitamin D metabolites, and changes in the reproductive behaviour of women in the Western world all appear to be candidates for environmental factors that may be modifying disease development risk, and contributing to a growing gender divide in MS. Many factors share the property of impacting serum levels of various forms of estrogen. As well, sun avoidance behaviour, greater in women, may also contribute to the difference in gender prevalence. CONCLUSIONS: There is a growing gender divide in the rates of RRMS, with increasing rates in women compared to men. There are multiple environmental and lifestyle factors that could be playing a role in gender inequality in this disease.
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 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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| 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".