Socioeconomically targeted strategies for cervical cancer elimination: differential effects of education, income, and residence on cervical precancerous lesions and invasive cancer

Abstract
Objective
The pattern of socioeconomic status (SES) inequality across the natural history continuum of cervical cancer (from precancerous lesions to invasive cancer) remains unclear. This study aims to systematically investigate the associations between different dimensions of SES and risk at various stages of cervical lesions, providing scientific evidence for identifying high-risk populations and formulating targeted prevention and control strategies.

Methods
A case-control design was adopted. A total of 508 female patients who visited Department of Gynecology at the First Affiliated Hospital of Army Medical University between October 2024 and September 2025 were enrolled. Based on pathological diagnosis combined with international classification of diseases， 10th revision（ICD-10) coding, cervical intraepithelial neoplasia (CIN), cervical carcinoma in situ, and invasive cervical cancer were designated as 3 case groups, with the women free of cervical lesions serving as the control group. Four SES indicators, that is, education level, household income, occupational income, and area-level economic development, were collected via questionnaires. Given that the outcome, variable was ordinal and the proportionul odds assumption was violated three independent binary logistic regression models were constructed to analyze the associations between each SES indicator and different lesion stages, estimating ORs and 95%CIs, with adjustment for age, body mass index (BMI), and human papillomavirus (HPV) vaccination status as confounders. Multicollinearity was assessed using variance inflation factor (VIF), and sensitivity analysis was performed using multinomial logistic regression.

Results
A total of 508 patients were enrolled, including 74 (14.6%) in the lesion-free group, 213 (41.9%) in the CIN group, 110 (21.7%) in the carcinoma in situ group, and 111 (21.8%) in the invasive cervical cancer group. Multivariate logistic regression analysis revealed that high school education and above was associated with reduced risks of CIN (OR=0.475, 95%CI: 0.258 to 0.877, P=0.017) and invasive cervical cancer (OR=0.361, 95%CI: 0.175 to 0.746, P=0.006), but showed no statistically significant association with carcinoma in situ. occupational income >5 000 yuan was associated with a reduced risk of invasive cervical cancer (OR=0.332, 95%CI: 0.137 to 0.806, P=0.015). Women from non-affluent areas exhibited a 92% increased risk of invasive cervical cancer compared with those from affluent areas (OR=1.920, 95%CI: 1.005 to 3.668, P=0.048). No significant associations were observed between household income and cervical lesions at any stage. All VIF values for variables in Model 3 were <1.12, indicating absence of multicollinearity. Sensitivity analysis using multinomial logistic regression with the lesion-free group as the common reference showed that the relative risk ratios (RRRs) of SES indicators across lesion stages were consistent in direction with the independent binary models, suggesting robust findings.

Conclusion
The impact of socioeconomic disparities on cervical lesion risk among Chinese women exhibits dimensional heterogeneity. High school education and above is independently associated with reduced risks of CIN and invasive cervical carcinoma, whereas residence economic level and occupational income primarily influence the risk of invasive cervical cancer. Countermeasures Integration of screening into grassroots family planning systems, implementation of data-driven bottleneck analysis and micro-interventions, and strengthening of community mobilization and family engagement are recommended to systematically eliminate accessibility barriers faced by populations with low education level and in non-affluent areas regarding HPV vaccination, screening, and treatment, ensuring equitable progress toward cervical cancer elimination goals for disadvantaged populations.