Cancer in female firefighters: The clinicobiological, psychological, and social perspectives
Bibliographic record
Abstract
Objectives: This study explored how demographic characteristics, life experiences, and firefighting exposures have an impact on cancer among female firefighters, and described the types and biologic characteristics of cancers as reported by women in the fire service. Methods: The online survey was available from June 2019 to July 2020. Questions related to demographic characteristics, lifestyle factors, firefighting exposures, and cancer diagnoses. Descriptive analyses characterized variables by the presence or absence of cancer. Qualitative data provided insight into both firefighting and cancer experiences among women. Results: There were 1,344 female firefighter respondents from 12 different countries, 256 of whom provided information on their cancer diagnosis. North American respondents made up 92% of the total. Those with cancer were older, had been in the fire service longer, had more career fires and toxic exposures, and were less likely to still be in active service. They also reported more tobacco use, and more full-term pregnancies. There were no differences in family history of cancer between the two groups. The average age at diagnosis was 39.0 years. The major types of cancer reported included breast (25.4%), cervical (21.1%), melanoma (20.7%), base cell/skin (16.4%), and uterine (14.8%). The cancer was detected when seeking medical attention for symptoms (42.1%), during routine health screening (29.8%), and during specific cancer screening (28.1%). The stage of cancer was reported by 44.5%, and 30.9% included the histopathological grade. Treatments included surgery (72.7%), chemotherapy (14.8%), radiotherapy (13.7%), and observation (13.7%). Challenges associated with cancer included psychosocial (33.2%), financial (18.8%), physical (6.6%), and spiritual (6.3%). Concerns about reporting a cancer experience to their employer included the desire to keep health information private (11.3%), a feeling of vulnerability (7.4%), and being perceived as weak (7.0%). Lack of support from their employer or insurer was also noted. Conclusion: Female firefighters experienced a wide variety of different types of cancers which may come earlier than similar cancers in the public. These findings can help inform resource allocation, the development of new policies, and the need for broader presumptive coverage to support female firefighters diagnosed with cancer.
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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 | 0.004 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".