Prostate and breast cancers are prevalent, yet a significant portion of their incidence remains unexplained. Hormone-mediated cancers, including ovarian, endometrial, thyroid, and melanoma, depend on endogenous hormones for growth and progression. Endocrine-disrupting chemicals (EDCs), such as phenols, parabens, and PFAS, are environmental toxicants that can impact hormone levels. Phenols and parabens are found in food packaging and personal care products, while PFAS are persistent in the environment and bioaccumulate in the body. Previous research suggests these chemicals affect estrogen, thyroid hormones, and testosterone levels. Despite their endocrine-disrupting potential, few epidemiological studies have assessed their relationship with endocrine-active cancer outcomes. This study aimed to use NHANES data (2005-2018) to conduct a cross-sectional analysis evaluating associations between current exposure levels to these chemicals and previous endocrine-active cancer diagnoses, focusing on sex-specific relationships. The results can inform the potential role of environmental toxicants in prospective cancer studies and guide targeted environmental health interventions.

While some case-control studies have shown positive or suggestive associations between breast cancer and BPA and PFAS, similar studies involving other emerging phenols or other cancer types are lacking. The NHANES dataset, with its nationwide biomonitoring and self-reported cancer diagnoses, provides an ideal resource for evaluating relationships between environmental chemicals and cancer outcomes. The existing literature highlights the endocrine disrupting potential of PFAS, phenols and parabens, implicating them in the disruption of estrogen, thyroid, and testosterone levels. This disruption is known to play a crucial role in carcinogenesis, making these chemicals potential risk factors for hormone-sensitive cancers.

This cross-sectional study utilized data from the NHANES (2005-2018). The study population included individuals aged 20 years and older with complete data on demographic variables, self-reported cancer diagnoses, and biomarker concentrations of seven PFAS and twelve phenols/parabens. Two separate analytical datasets were created – one for PFAS and one for phenols/parabens due to non-overlapping participants with measurements for different chemical panels. Data was separated by sex to evaluate sex-specific cancer associations. Biomarker assessment involved serum samples for PFAS (analyzed via high performance liquid chromatography-turbo ion spray ionization-tandem mass spectrometry) and urine samples for phenols/parabens (analyzed using online solid phase extraction coupled to high performance liquid chromatography and tandem mass spectrometry). Self-reported cancer diagnoses were obtained from medical conditions questionnaires. Logistic regression models were used to evaluate associations between exposure biomarkers and cancer outcomes, adjusting for age, cotinine, poverty-income ratio, race, education, BMI, and NHANES cycle. Phenol/paraben models also included urinary creatinine. Exposure biomarkers were natural log-transformed to account for right-skewed distributions. Concentrations below the limit of detection (LOD) were imputed with LOD/√2. Sensitivity analyses explored effect modification by race and accounted for survey sampling weights.

In women, higher PFDE, PFNA, and PFUA levels were associated with increased odds of previous melanoma. Higher DCP25 levels were associated with increased odds of previous ovarian cancer, along with BPA and BP3. Higher PFNA was associated with increased odds of previous uterine cancer, while higher ethyl paraben was inversely associated. Several PFAS were associated with previous ovarian and uterine cancers in White women, while MPAH or BPF was associated with previous breast cancer in non-White women. In men, there were few significant associations. Among men, there was a marginally significant positive association between PPB and prostate cancer. Significant racial differences were observed in associations between exposures and cancer outcomes, particularly for ovarian and uterine cancers in White women compared to other racial groups. These racial disparities suggest the importance of considering social and environmental factors in cancer research.

This study provides the first epidemiological assessment of phenols in relation to previous cancer diagnoses and the first NHANES study to explore racial/ethnic disparities in associations between phenols, parabens, and PFAS exposure and historical cancer diagnosis. The findings, particularly the sex-specific associations and racial disparities, warrant further investigation. The association of PFAS and phenols with melanoma in women suggests potential sex-mediated mechanisms, possibly involving estrogenic activity. The varying associations across racial groups reflect differences in exposure levels and potentially underlying metabolic factors. The findings highlight the need for future research to consider sex and race when investigating cancer mechanisms and risk factors, emphasizing the importance of comprehensive exposure assessments and targeted interventions.

This study demonstrates associations between several PFAS, phenols, and parabens and previous diagnoses of melanoma and ovarian cancer, particularly in women. Racial disparities in associations highlight the need for further research considering both exposure and inherent risk factors. Future prospective studies should focus on exploring sex-specific mechanisms and racial disparities to improve cancer prevention and risk assessment strategies. The findings also suggest a need to investigate the impact of these chemicals on cancer survivors and their treatments.

The cross-sectional design limits causal inference; reverse causation is possible. Exposure assessment relies on biomarker measurements which may not perfectly reflect historical exposure. Unmeasured confounding factors, such as family history and anatomical alterations, may influence results. Self-reported cancer diagnoses introduce potential outcome misclassification. The lack of information on time between cancer diagnosis and biomarker measurement is a limitation. Multiple comparison issues also need to be considered, and some findings might represent false positives. Finally, the study's reliance on survey regression methods needs to be interpreted cautiously regarding generalizability to all racial/ethnic groups.