Association of Estrogen in the Risks of Parkinson’s Disease in South Korean Women
Bibliographic record
Abstract
Parkinson's disease (PD) is a neurodegenerative disorder characterized by the death of neurons, resulting in symptoms such as shaking, stiffness, and impaired balance. Research suggests a potential link between estrogen, a female sex hormone, and PD risk, with studies indicating that estrogen may play a protective role against the disease. However, most research on this topic has been conducted on European populations, leaving the role of estrogen in PD risk among Asian women, particularly in South Korea, unclear. This study contributes to understanding the potential protective role of estrogen in PD by focusing on South Korean women. A case-control study design was employed, comparing responses from women with PD to healthy controls. The study investigated various reproductive life events, including menstruation, menopause, and hormone replacement therapy, using a questionnaire administered to participants in South Korea. Results revealed that PD patients were significantly older than controls, with differences in reproductive lifespan and age at menopause. Women who underwent surgical menopause showed an increased risk of PD, while hormone replacement therapy and oral contraceptive usage did not show consistent associations with PD risk. The study concludes that estrogen is neither a protective nor a risk factor for PD in South Korean women. This research contributes to the understanding of PD risk factors among South Korean women and highlights the need for further exploration into non-genetic gender-specific symptoms and societal influences on PD risk, aiming to reduce underrepresentation and medical discrimination in PD research.
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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 | 0.000 | 0.001 |
| 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) | 0.001 | 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".