IARC 60th Anniversary - 19-21 May 2026
Session : 21/05/26 - Posters
Exploring lifestyle confounding in the association between tattoos and cancer: A latent class analysis of tattooing and cervical cancer risk
MCCARTY R. 1, BOUAOUN L. 1, ZINS M. 2,3,4, GOLDBERG M. 2, RIBET C. 2, KAB S. 2, EZZEDINE K. 5,6, SCHÜZ J. 1, FOERSTER M. 1
1 International Agency for Research on Cancer, Lyon, France; 2 Université Paris Cité, Université Paris-Saclay, UVSQ, INSERM, Paris, France; 3 Université Paris Cité and Université Sorbonne Paris Nord, Inserm, INRAE, Centre for Research in Epidemiology and Statistics (CRESS), Paris, France; 4 Centre d'Epidémiologie Clinique, Hôpital Hôtel Dieu, AP-HP, Paris, France; 5 Department of Dermatology, Henri-Mondor University Hospital, Créteil, France; 6 Epidemiology in Dermatology and Evaluation of Therapeutics (EpiDermE), EA 7379, Paris-Est Créteil University, Créteil, France
Background: Recent studies have reported increased hematologic cancer risk associated with tattooing, an exposure highly correlated with sociodemographic and lifestyle patterns.
Objectives: We aimed to explore how confounding can influence associations between tattooing and cancer by examining cervical cancer, a malignancy unlikely to be causally related to tattooing. We specifically assessed whether lifestyle-related confounding may confound observed associations between tattooing and cervical cancer.
Methods: We analyzed data from 50,769 women in the Cancer Risk Associated with the Body Art of Tattooing (CRABAT) study nested within the French national Constances cohort. Latent class analysis (LCA) was applied to group women into latent lifestyle profiles based on sociodemographic, lifestyle, and health-related variables, and logistic regression models estimated associations between tattoos and cervical cancer, adjusting for confounders and latent lifestyle profiles. Additional models were stratified by latent lifestyle profile.
Results: We selected a five-profile LCA model to balance model fit and interpretability. The profiles were characterized as: older unmarried women (14%), younger women (12%), older married women in rural areas (20%), risk-takers with higher substance use and sexual partners (22%), and socially-advantaged women with higher education/income (31%). In minimally adjusted models, women with tattoos had a higher cervical cancer risk (OR=1.54 [95% CI 1.15–2.05]). Associations were attenuated after adjusting for known confounders (1.33 [0.99–1.77]), and a bit further after adjusting for latent profiles (1.29 [0.95–1.73]). Stratified models showed strong variations, with ORs ranging from 0.99 [0.37–2.61] in the younger profile to 2.56 [1.23–5.34] in the socially-advantaged profile.
Conclusions: While elevated risk among tattooed individuals persisted after adjustment for known confounders, LCA was able to differentiate risk patterns between latent lifestyle profiles. LCA may be useful when complex confounding is likely, such as in studies of tattoos and cancer risk.