Effect of Socioeconomic Status on Cervical Cancer Screening Behaviour Among Mothers of Adolescent Girls in Lagos, Nigeria: A Secondary Analysis of the mHealth-HPVac Study

Effect of Socioeconomic Status on Cervical Cancer Screening Behaviour Among Mothers of Adolescent Girls in Lagos, Nigeria: A Secondary Analysis of the mHealth-HPVac Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Effect of Socioeconomic Status on Cervical Cancer Screening Behaviour Among Mothers of Adolescent Girls in Lagos, Nigeria: A Secondary Analysis of the mHealth-HPVac Study Kehinde S. OKUNADE, Adaiah SOIBI-HARRY, Ayomide I. FAYINTO, Hameed ADELABU, and 10 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8126074/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 12 You are reading this latest preprint version Abstract Background Cervical cancer remains a preventable malignancy with high morbidity and mortality in low- and middle-income countries (LMICs). Screening uptake is suboptimal in sub-Saharan Africa, and the influence of socioeconomic status (SES) on screening behaviour among women remains insufficiently explored. Aim To determine the effect of SES on cervical cancer screening uptake among mothers of vaccine-eligible adolescent girls in Lagos, Nigeria. Methods This secondary analysis used baseline data from the mHealth-HPVac trial, including 180 sexually active mothers of unvaccinated girls aged 9–14 years. The primary outcome was self-reported cervical cancer screening within the previous 10 years. A multivariable logistic regression model was used to examine the association between SES and screening uptake, adjusting for age and tribe. Education and income were tested as an interaction term but excluded due to model instability. Results Overall, 51.7% of participants reported prior cervical screening. Women who had been screened were significantly older than unscreened women (45.4 ± 6.7 vs 41.7 ± 7.2 years; p < 0.001). Screening uptake did not differ significantly by marital status, education, employment, income class, tribe, or residential distance to screening facilities. In adjusted models, neither middle-income (adjusted odds ratio = 1.72, 95% CI: 0.75–3.98) nor high-income status (adjusted odds ratio = 1.22, 95% CI: 0.45–3.30) was associated with screening. Conclusion Cervical cancer screening uptake among mothers in Lagos is moderate, and SES was not independently associated with screening. Interventions should target structural or behavioural factors rather than focusing solely on economic disparities. Larger, adequately powered population-based studies are therefore needed to validate these findings and better delineate the socioeconomic gradients in screening behaviour among Nigerian women. Cervical cancer screening uptake socioeconomic status education Nigeria Introduction Cervical cancer remains one of the most consequential yet preventable malignancies affecting women globally [ 1 ]. Recent estimates from GLOBOCAN 2020 place it as the fourth most common cancer among women worldwide, accounting for over 604,000 new cases and 342,000 deaths annually [ 1 ]. The burden is profoundly inequitable, with approximately 90% of global cervical cancer mortality occurring in LMICs, driven largely by gaps in prevention, screening, and early detection [ 2 ]. Sub-Saharan Africa (SSA) bears the highest age-standardised incidence and mortality rates globally, with an incidence of 40.1 per 100,000 women—nearly seven times that of high-income regions [ 3 ]. Nigeria contributes significantly to this burden, recording an estimated 15,000 new cases annually and over 8,000 deaths, making cervical cancer the second leading cause of female cancer mortality in the country [ 4 ]. The socioeconomic consequences of cervical cancer are profound, with women in their productive years often bearing the burden, which ripples through families, workplaces and communities. Evidence demonstrates that early detection through cytology, HPV testing, or visual inspection substantially reduces cervical cancer incidence and mortality [ 3 ]. Yet, screening uptake in SSA remains critically low, often below 25% [ 5 , 6 ]. Socioeconomic status (SES) is a well-established determinant of screening behaviour globally. Higher education and income levels have consistently been associated with improved health literacy, autonomous decision-making, and preventive health practices, including cervical screening [ 7 , 8 ]. However, emerging evidence from LMICs suggests that this relationship may be more complex, with contextual cultural, structural, and gender-related factors mediating how SES influences screening behaviour [ 9 ]. Particularly among mothers, key actors in family health-seeking behaviours, the role of SES in shaping cervical screening decision-making remains insufficiently explored. This secondary analysis of the mHealth-HPVac study, an HPV vaccination intervention trial among mothers of unvaccinated adolescent girls in Lagos, Nigeria [ 10 , 11 ], offers a unique opportunity to leverage high-quality baseline data collected from a diverse urban population of women to provide a timely and rigorous examination of SES-related disparities in cervical cancer screening behaviour. By modelling socioeconomic indicators while adjusting for key demographic and access variables, the study aims to clarify whether SES independently predicts screening uptake in this population. Therefore, the objective of this study is to determine the effect of SES on cervical cancer screening behaviour among mothers of vaccine-eligible adolescent girls in Lagos, Nigeria. The central hypothesis is that higher SES, measured through a composite SES index comprising education and occupation, will be positively associated with cervical screening uptake, independent of access-related factors. Participants and Methods Study Design and Settings This study is a descriptive cross-sectional design using the baseline data obtained from the “ mHealth-HPVac ” trial [ 10 , 11 ], a recently completed randomised, parallel-arm controlled study conducted from June 2024 to March 2025. The parent trial enrolled mothers of unvaccinated girls aged 9–14 years attending routine care at the General Outpatient (GOP) Clinics of the Lagos University Teaching Hospital (LUTH), Lagos, Nigeria. LUTH, the main teaching hospital of the College of Medicine, University of Lagos, is situated in an urban, socioeconomically diverse Lagos metropolis, providing a suitable environment for examining how socioeconomic gradients influence cervical cancer screening behaviour. Study population For this secondary analysis, we included the complete baseline dataset of 180 sexually active women from the primary study [ 11 ]. Eligibility for inclusion required women to have full sociodemographic, socioeconomic, and cervical cancer screening history data. Women with a previous diagnosis of cervical cancer, those of non-Nigerian nationality, or individuals unable to provide reliable responses due to cognitive impairment were excluded. Study endpoints/outcomes The primary outcome was the association between socioeconomic status (SES) and screening uptake, and the secondary outcome was the modifying effect of formal educational attainment on the association between income status and screening behaviour. Cervical cancer screening uptake was defined as self-reported receipt of at least one Pap test or HPV-based screening within the past 10 years, with verification through clinic records where available. The income class was derived using a transparent and replicable method informed by the Demographic and Health Survey (DHS) wealth index framework, which combines educational attainment and occupational level [ 12 ]. Educational attainment was categorised as None/Primary, Secondary, or Tertiary. Employment status was categorized as Unskilled, Semi-skilled, or Skilled/Professional. Variables extracted for analysis included age, parity, tribe, marital status, educational attainment, employment status, residential distance to the nearest screening facility, cervical cancer awareness, and screening uptake. Sample size calculation As this study was a secondary analysis of baseline data from the mHealth-HPVac trial [ 11 ], the sample size was fixed at 180 participants. To assess the adequacy of this sample for detecting the association between SES and cervical cancer screening uptake, we performed post-hoc sample size calculation using standard formulas for comparing two proportions [ 13 ] with 80% power and a two-sided alpha of 5%. Under plausible assumptions for cervical cancer screening, with a prevalence of 40–50%, this sample size provides adequate power to detect approximately a 20-percentage-point difference in screening uptake. We also evaluated the adequacy of the sample for multivariable logistic regression using the events-per-variable (EPV) rule. With 93 women (51.7%) reporting prior screening (events), the dataset supports the inclusion of approximately 6–8 predictor variables at EPV ≈ 10, indicating that the planned adjusted model is statistically appropriate. Participants Sampling and Study Procedure We collected data in the primary study [ 11 ] through interviewer-administered electronic case report forms (eCRFs) on REDCap, hosted on secure institutional servers. The eCRF, previously published elsewhere as Supplementary Material 3 [ 10 ], captured sociodemographic characteristics, economic indicators (education and occupation), reproductive history, and cervical cancer awareness and screening behaviour. Residential distance was calculated using participants’ addresses geocoded to the nearest health facility offering screening. Quality control measures included daily supervision of data collectors, range and logic checks in REDCap, and weekly data audits. Identifiable information was stored separately from research data using unique study codes to preserve confidentiality in line with ICH-GCP (E6[R2]) guidelines. Data Analysis Data analysis was conducted in Stata version 18 (StataCorp LLC, Texas, USA). Missing values were addressed using multiple imputation by chained equations under the assumption of missing at random. Descriptive statistics were used to summarize participants’ characteristics using means and standard deviation for normally distributed variables and medians with interquartile ranges for skewed variables. The association between SES indicators and screening uptake was examined using multivariable logistic regression. Significant variables ( p < 0.2) in the univariable model (age and tribe) were included as covariates to adjust for potential confounding. Model diagnostics, including multicollinearity assessment, goodness-of-fit tests, and residual analysis, were performed to ensure appropriate model specification. To examine whether educational attainment modified the effect of income on screening behaviour, an education × income interaction term was tested. However, inclusion of this interaction resulted in numerical instability, characterized by inflated variance inflation factors (VIF > 10), wide confidence intervals, and poor model convergence. For this reason, the interaction term was excluded from the final model to ensure analytical robustness. Results are presented as adjusted odds ratios (aORs) with 95% confidence intervals. Ethical Considerations Ethical approvals for the primary study[ 11 ] were obtained from the Health Research Ethics Committee of the College of Medicine, University of Lagos (approval number: CMUL/HREC/5/24/1464 obtained on 15th May 2024) and Lagos University Teaching Hospital (approval number: ADM/DSCST/HREC/APP/6566 obtained on 10th May 2024). Written informed consent was obtained from each participant before enrollment, with a detailed explanation of the study objectives, confidentiality safeguards, and the rights to voluntary participation. Participants were assured that declining or withdrawing from the study would not affect their access to clinical services. Data confidentiality was strictly maintained through encryption and password-protected databases. The study aligns with the Declaration of Helsinki and Nigeria’s National Code of Health Research Ethics, ensuring the protection of participants’ autonomy, privacy, and welfare. Results A total of 180 women with complete baseline data were included in the analysis. Overall, 93 women reported having undergone cervical cancer screening within the previous 10 years, yielding a screening uptake of 51.7% (95% confidence interval: 44.1–59.2). The mean age of participants was 43.6 ± 7.2 years, and women who had been screened were significantly older than those who had never been screened (45.4 ± 6.7 vs. 41.7 ± 7.2 years; p < 0.001). Table 1 presents participant characteristics by screening status. No statistically significant differences were observed between screened and unscreened women across key sociodemographic variables, including marital status, educational attainment, employment category, income class, tribe, and residential distance to a screening facility. Table 1: Characteristics of enrolled women stratified by their screening uptake (n = 180) Characteristics Uptake (%) Non-uptake (%) p -value Participants 93 (51.7) 87 (48.3) Age, years 45.4 ± 6.7 41.7 ± 7.2 <0.001 Residential distance to screening facility, km a 13.0 (7.1–22.5) 10.1 (5.0–22.0) 0.325 Previous pregnancies One to two 36 (38.7) 24 (27.6) 0.285 Three to four 43 (46.2) 47 (54.0) More than four 14 (15.1) 16 (18.4) Marital status Married 74 (79.6) 69 (79.3) 0.966 Not married 19 (20.4) 18 (20.7) Educational level None/Primary 6 (6.5) 12 (13.8) 0.259 Secondary 39 (41.9) 33 (37.9) Tertiary 48 (51.6) 42 (48.3) Employment status Unskilled 14 (15.1) 13 (15.0) 0.726 Semi-skilled 55 (59.1) 47 (54.0) Skilled/professional 24 (25.8) 27 (31.0) Income class Low 13 (14.0) 19 (21.8) 0.245 Middle 62 (66.7) 48 (55.2) High 18 (19.3) 20 (23.0) Tribe Yoruba 29 (31.2) 32 (36.8) 0.157 Igbo 47 (50.5) 32 (36.8) Others 17 (18.3) 23 (26.4) Abbreviations: IQR, interquartile range; SD, standard deviation. a Wilcoxon rank sum test. After adjusting for age and tribe in a logistic regression model, income class was not found to be independently associated with screening uptake. Compared with women in the low-income category, those in the middle-income (adjusted OR = 1.72, 95% CI: 0.75–3.98) and high-income (adjusted OR = 1.22, 95% CI: 0.45–3.30) categories had higher but statistically nonsignificant odds of screening. An interaction term between education and income level was initially included to examine potential effect modification; however, its inclusion led to model instability, reflected by excessively large standard errors and poor model convergence. For this reason, the interaction term was removed, and the final model was estimated without it [Table 2]. Table 2: Multivariable analyses of effects of socioeconomic status on cervical cancer screening uptake (n=180) SES Indicators Number of screened mothers Adjusted OR (95% CI) Income class High 18/38 (47.4%) 1.22 (0.45 – 3.30) Middle 62/110 (56.4%) 1.72 (0.75 – 3.98) Low 13/38 (40.6%) 1.00 (reference) Age >45 years 39/57 (68.4%) 7.96 (2.28 – 27.78) 35 – 45 years 50/104 (48.1%) 3.61 (1.10 – 11.84) <35 years 4/19 (21.1%) 1.00 (reference) Tribe Yoruba 29/61 (47.5%) 1.78 (0.79 – 4.01) Igbo 47/79 (59.5%) 1.11 (0.47 – 2.61) Others 17/40 (42.5%) 1.00 (reference) Abbreviations: CI, confidence interval; OR, odds ratio; SES, socioeconomic status Inclusion of the Education and Income interaction term rendered the model unstable (large standard errors and poor convergence); hence, the interaction term was excluded from the final model. Discussion This descriptive cross-sectional analysis of the mHealth-HPVac study data assessed the effect of socioeconomic status (SES) on cervical cancer screening uptake among mothers of vaccine-eligible adolescent girls in Lagos, Nigeria. Approximately half (51.7%) of the participants reported having been screened for cervical cancer within the last ten years, indicating a moderate but suboptimal level of screening uptake relative to the national [14] and World Health Organization (WHO) target [15]. This is consistent with reports from similar urban Nigerian settings [16], where cervical cancer screening remains suboptimal despite the known benefits of early detection and prevention, despite the WHO-recommended projection of 70% screening coverage among women aged 35–45 years by 2030 as part of the global strategy to eliminate cervical cancer as a public health problem [15]. The observed coverage in this study underscores the persistent gap between global aspirations and local realities in many low- and middle-income countries (LMICs), including Nigeria. Consistent with previous studies, age was the only variable significantly associated with screening uptake in our analysis, with older women more likely to have been screened compared to their younger counterparts. This finding aligns with reports from other Nigerian and sub-Saharan African studies showing that screening uptake increases with age [17–19], possibly due to cumulative health encounters, higher risk perception, and increased exposure to reproductive health education [17,20]. Conversely, younger women may underestimate their risk or perceive cervical cancer screening as unnecessary until they experience symptoms, a misconception that contributes to delayed screening. Contrary to expectations, SES was not independently associated with screening uptake after adjusting for age and tribe. This result diverges from the broader literature, which consistently identifies socioeconomic position as a key determinant of cervical cancer screening uptake in both high- and low-resource settings [21–24]. A plausible explanation may be that, within the urban context of Lagos, socioeconomic disparities exert less influence due to the relatively high concentration of health facilities and targeted awareness programs that have improved access across social strata. Moreover, cultural attitudes, perceived stigma, and fear of diagnosis have been shown to outweigh economic factors in determining health-seeking behaviour for cervical screening in Nigeria [25–28]. This finding may also reflect the availability of subsidised or free screening programs within Lagos, such as those implemented by non-governmental organisations [29], which may have attenuated the influence of economic status on screening participation. It is also possible that self-reported income and occupational status do not fully capture economic empowerment or financial decision-making autonomy among women, particularly in patriarchal household structures common in the study setting. Furthermore, in testing for effect modification, the interaction term between education and income rendered the multivariable model unstable due to multicollinearity and large standard errors, suggesting interdependence between these variables. This statistical instability has been reported in similar population studies where socioeconomic status indicators are highly correlated [30,31]. Future research employing composite socioeconomic indices or principal component analysis may better capture multidimensional socioeconomic effects on screening behaviour. This study has a few limitations. First, the cross-sectional nature of the analysis and the likely recall bias due to the reliance on self-reported cervical cancer screening history and our inability to verify all screening records could preclude causal inference. Second, analysis of SES relies primarily on education and employment. However, SES is multidimensional and thus exclusion of household assets, housing characteristics, or family economic size, which were not available in the datasets, may limit validity. Third, the sample was hospital-based, limiting generalizability to community settings. Fourth, due to the study’s secondary analytical framework, residual confounding from unmeasured or inadequately captured variables cannot be excluded. Fifth, as the study participants were mothers attending an outpatient clinic at a tertiary hospital, who are likely more health-aware than the general population, there is a high likelihood of unduly inflated screening uptake estimates, reduced SES variability, and limited generalizability to community samples. Finally, while the study is sufficiently powered to assess broad socioeconomic disparities, it may be underpowered to detect modest associations, which could have limited the comprehensiveness of the explanatory model and partly accounted for the lack of statistically significant associations between SES and screening uptake. Larger, adequately powered population-based studies are therefore needed to validate these findings and better delineate the socioeconomic gradients in screening behaviour among Nigerian women. Nonetheless, the study provides valuable insights into the complex interplay between socioeconomic status and cervical cancer screening behaviours in an urban Nigerian population. Conclusion Our study showed a moderate cervical cancer screening uptake in the enrolled cohort of mothers of vaccine-eligible adolescent girls in Lagos, Nigeria. Socioeconomic status was not independently associated with screening uptake. These findings highlight the need to address structural and behavioural barriers that may be more critical to screening uptake than focusing solely on economic or educational disparities. Future studies with larger samples and longitudinal designs could provide further insight into the complex determinants of cervical cancer screening behaviour in Nigerian women. Declarations Acknowledgements The authors are particularly grateful to the participating women who generously shared their time, enabling us to conduct this important study. We would also like to express our appreciation to the personnel at the Research Management Office of the College of Medicine, University of Lagos, for their support in obtaining the funding for this study. Ethics approval and consent to participate Ethical approvals for the primary study were obtained from the Health Research Ethics Committee of the College of Medicine, University of Lagos (approval number: CMUL/HREC/5/24/1464 obtained on 15th May 2024) and Lagos University Teaching Hospital (approval number: ADM/DSCST/HREC/APP/6566 obtained on 10th May 2024). The study was conducted ethically according to the World Medical Association Declaration of Helsinki. Informed consent was secured from each participant. Confidentiality, anonymity, and the right of participants to withdraw consent were maintained throughout and after the study was conducted. Consent for publication Not applicable. Author contributions Kehinde S. Okunade, Adaiah Soibi-Harry, and Muisi A. Adenekan contributed to the study's conception and design. All authors performed material preparation, data collection and analysis. Kehinde S. Okunade, Ayomide I. Fayinto, and Yusuf A. Oshodi wrote the first draft of the manuscript. All authors commented on previous versions of the manuscript and approved the final manuscript. Competing interests The author declares no competing interests in the publication of this article. Availability of data and materials The authors intend to grant access to the datasets used and/or analysed in the study upon reasonable request from the corresponding author (Kehinde S. Okunade). Funding The lead author (Kehinde S. Okunade) received protected time for this work through funding from the Conquer Cancer International Innovation Grant under Project ID 2024IIG-2761200216, the National Cancer Institute and Fogarty International Centre of the National Institutes of Health under Award Number K43TW011930. The content of this paper is solely the responsibility of the authors and does not necessarily represent the official views of the Conquer Cancer Foundation, the National Cancer Institute, Fogarty International Centre, or the National Institutes of Health. The funders had no role in the conceptualisation, the decision to publish, or the preparation of the manuscript. References Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J Clin. 2021;71:209–49. https://doi.org/10.3322/caac.21660 . Bruni L, Serrano B, Roura E, Alemany L, Cowan M, Herrero R, et al. Cervical cancer screening programmes and age-specific coverage estimates for 202 countries and territories worldwide: a review and synthetic analysis. Lancet Glob Health. 2022;10:e1115–27. https://doi.org/10.1016/S2214-109X(22)00241-8 . Arbyn M, Weiderpass E, Bruni L, de Sanjosé S, Saraiya M, Ferlay J, et al. Estimates of incidence and mortality of cervical cancer in 2018: a worldwide analysis. Lancet Glob Health. 2020;8:e191–203. https://doi.org/10.1016/S2214-109X(19)30482-6 . Daniel FM, Ike WI, Gbuchie Anurika M, Udofia James S, Chinyere Kalu P, Ebizo Ikpa S, Knowledge. Attitude, and Prevalence Towards Cervical Cancer Screening Among Women in a Nigerian Urban Municipality. Int J Med Students. 2023;S91. https://doi.org/10.5195/ijms.2023.2369 . Perkins RB, Guido RS, Castle PE, Chelmow D, Einstein MH, Garcia F et al. 2019 ASCCP Risk-Based Management Consensus Guidelines for Abnormal Cervical Cancer Screening Tests and Cancer Precursors ASCCP Risk-Based Management Consensus Guidelines Committee 2020. https://doi.org/10.1097/LGT.0000000000000525 Okunowo AA, Daramola ES, Soibi-Harry AP, Ezenwankwo FC, Kuku JO, Okunade KS, et al. Women’s knowledge of cervical cancer and uptake of Pap smear testing and the factors influencing it in a Nigerian tertiary hospital. J Cancer Res Pract. 2018. https://doi.org/10.1016/j.jcrpr.2018.02.001 . Altová A, Kulhánová I, Reisser K, Netrdová P, Brož J, Eikemo TA, et al. Educational inequalities in cervical cancer screening participation in 24 European countries. Public Health. 2024;233:1–7. https://doi.org/10.1016/j.puhe.2024.04.036 . Asgedom YS, Kassie GA, Habte A, Ketema DB, Aragaw FM. Socioeconomic inequality in cervical cancer screening uptake among women in sub-Saharan Africa: a decomposition analysis of Demographic and Health Survey data. BMJ Open. 2024;14:e088753. https://doi.org/10.1136/bmjopen-2024-088753 . Petersen Z, Jaca A, Ginindza TG, Maseko G, Takatshana S, Ndlovu P, et al. Barriers to uptake of cervical cancer screening services in low-and-middle-income countries: a systematic review. BMC Womens Health. 2022;22:486. https://doi.org/10.1186/s12905-022-02043-y . Okunade KS, Adejimi AA, Adekanye TV, Allsop MJ, Adelabu H, Thomas-Ogodo O, et al. Impact of mobile health technologies on human papillomavirus vaccination uptake among mothers of unvaccinated girls aged 9–14 years in Lagos, Nigeria (mHealth-HPVac): study protocol of a randomised controlled trial. BMC Cancer. 2024;24:751. https://doi.org/10.1186/s12885-024-12538-6 . Okunade KS, Fayinto AI, Adekanye TV, Allsop MJ, Adelabu H, Soibi-Harry A et al. Randomized Controlled Trial of Impact of Mobile Health Technologies on Human Papillomavirus Vaccination Uptake in Mothers of Vaccine-Eligible Girls in Lagos, Nigeria (mHealth-HPVac). JCO Glob Oncol 2025. https://doi.org/10.1200/GO-25-00150 Rutstein Shea Oscar Johnson Kiersten. DHS Comparative Reports No. 6:The DHS Wealth Index. Maryland USA: Calverton; 2004. Charan J, Biswas T. How to Calculate Sample Size for Different Study Designs in Medical Research? Indian J Psychol Med. 2013;35:121–6. https://doi.org/10.4103/0253-7176.116232 . World Health Organisation. Costing the National Strategic Plan on Prevention and Control of Cervical Cancer. Nigeria; 2020. pp. 2017–21. Singh D, Vignat J, Lorenzoni V, Eslahi M, Ginsburg O, Lauby-Secretan B et al. Global estimates of incidence and mortality of cervical cancer in 2020: a baseline analysis of the WHO Global Cervical Cancer Elimination Initiative. Lancet Glob Health 2022. https://doi.org/10.1016/S2214-109X(22)00501-0 Okunade KS, John-Olabode S, Adejimi AA, Oshodi YA, Osunwusi B, Ugwu AO et al. Predictors of Pap smear testing uptake among women in Lagos, Nigeria. Ecancermedicalscience 2022;16. https://doi.org/10.3332/ecancer.2022.1368 Ba DM, Ssentongo P, Musa J, Agbese E, Diakite B, Traore CB, et al. Prevalence and determinants of cervical cancer screening in five sub-Saharan African countries: A population-based study. Cancer Epidemiol. 2021;72:101930. https://doi.org/10.1016/j.canep.2021.101930 . Tiruneh FN, Chuang K-Y, Ntenda PAM, Chuang Y-C. Individual-level and community-level determinants of cervical cancer screening among Kenyan women: a multilevel analysis of a Nationwide survey. BMC Womens Health. 2017;17:109. https://doi.org/10.1186/s12905-017-0469-9 . Compaore S, Ouedraogo CMR, Koanda S, Haynatzki G, Chamberlain RM, Soliman AS. Barriers to Cervical Cancer Screening in Burkina Faso: Needs for Patient and Professional Education. J Cancer Educ. 2016;31:760–6. https://doi.org/10.1007/s13187-015-0898-9 . Emagneneh T, Mulugeta C, Ejigu B, Alamrew A, Abebaw N, Yessuf A, et al. Uptake of cervical cancer screening and its associated factors in Africa: an umbrella review of systematic reviews and meta-analyses. BMC Public Health. 2025;25:2968. https://doi.org/10.1186/s12889-025-24173-2 . Seifu BL, Negussie YM, Asnake AA, Asebe HA, Fente BM, Asmare ZA, et al. Wealth-related inequalities of women’s cervical cancer screening in 11 Sub-Saharan African countries: evidence from a pooled decomposition analysis. Sci Rep. 2025;15:12289. https://doi.org/10.1038/s41598-025-96347-2 . Asgedom YS, Kassie GA, Habte A, Ketema DB, Aragaw FM. Socioeconomic inequality in cervical cancer screening uptake among women in sub-Saharan Africa: a decomposition analysis of Demographic and Health Survey data. BMJ Open. 2024;14:e088753. https://doi.org/10.1136/bmjopen-2024-088753 . Ilevbare OE, Adegoke AA, Adelowo CM. Drivers of cervical cancer screening uptake in Ibadan. Nigeria Heliyon. 2020;6:e03505. https://doi.org/10.1016/j.heliyon.2020.e03505 . Dozie UW, Ebirim CIC, Dike CR, Dozie INS, Ibe SNO, Abanobi OC. Determinants of cervical cancer screening uptake among female undergraduates in a tertiary institution in south eastern Nigeria: a cross sectional study. J Prev Med Hyg. 2021;62:E213–21. https://doi.org/10.15167/2421-4248/jpmh2021.62.1.1828 . Mafiana JJ, Dhital S, Halabia M, Wang X. Barriers to uptake of cervical cancer screening among women in Nigeria: a systematic review. Afr Health Sci. 2022;22:295–309. https://doi.org/10.4314/ahs.v22i2.33 . Gwom Dung D, Matthew Mamman S, Musa Magaji J, SOCIO-CULTURAL FACTORS INFLUENCING, THE PRACTICE OF CERVICAL CANCER SCREENING AMONG WOMEN IN ANTENATAL AND POST NATAL CLINIC IN DALHATU ARAF SPECIALIST HOSPITAL LAFIA., NASARAWA STATE, NIGERIA. vol. 14. 2024. Bello I, Aliyu Z, Aliyu A, Abubakar S, Aminu Abbas A. Sociocultural Factors in Cervical Cancer Screening uptake among Women of Reproductive Age in Kaduna Metropolis, Kaduna State, Nigeria. Texila Adv J Multidisciplinary Health Res. 2025. https://doi.org/10.21522./TAJMHR.2016.05.01.Art020. Isa Modibbo F, Dareng E, Bamisaye P, Jedy-Agba E, Adewole A, Oyeneyin L, et al. Qualitative study of barriers to cervical cancer screening among Nigerian women. BMJ Open. 2016;6:e008533. https://doi.org/10.1136/bmjopen-2015-008533 . Okunade K, Salako O, Adenekan M, Sunmonu O, Salawu K, Sekumade A, et al. The uptake of cervical cancer control services at a cancer information service center in Lagos, Nigeria. Nigerian J Gen Pract. 2018;16:20. https://doi.org/10.4103/NJGP.NJGP_21_17 . Wadolowska L, Kowalkowska J, Lonnie M, Czarnocinska J, Jezewska-Zychowicz M, Babicz-Zielinska E. Associations between physical activity patterns and dietary patterns in a representative sample of Polish girls aged 13–21 years: a cross-sectional study (GEBaHealth Project). BMC Public Health. 2016;16:698. https://doi.org/10.1186/s12889-016-3367-4 . Fiandrino S, Dowd C, Martini G, Mejova Y, Omodei E, Paolotti D et al. Impact of food-related conflicts on self-reported food insecurity. Front Sustain Food Syst 2023;7. https://doi.org/10.3389/fsufs.2023.1239992 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 23 Apr, 2026 Reviews received at journal 10 Mar, 2026 Reviews received at journal 03 Mar, 2026 Reviewers agreed at journal 18 Feb, 2026 Reviewers agreed at journal 16 Feb, 2026 Reviewers agreed at journal 16 Feb, 2026 Reviewers agreed at journal 12 Feb, 2026 Reviewers agreed at journal 02 Feb, 2026 Reviewers invited by journal 08 Jan, 2026 Editor assigned by journal 22 Nov, 2025 Submission checks completed at journal 20 Nov, 2025 First submitted to journal 20 Nov, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8126074","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":571490651,"identity":"d0f52c59-1081-4003-94fb-703375c00208","order_by":0,"name":"Kehinde S. OKUNADE","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA9ElEQVRIiWNgGAWjYFACNhDBzMAPJA88AIskEKlFsgGoJYEkLQYH4IoJaJFvb0uTLqixljO+kXvwQEJNLQM/e44Bc8Ev3FoMzhw7Jj3jWLqx2Y28hAMJx44zSPa8MWCe2YdHi0R6mzQP2+HEbTdyDA4ksB1jMAAymHl78DhsBkjLv8P1m2eAtPw7xmBPSAvDjbRj0rxthxMMJIBaEttqGEAMZp4feP2SbM3bl24448wboJa+AzwSZ54VHOZtwOOw9jbD2zzfrOX523OMP3z4VifH35688THPHzwOQwOHeUDkAcY24rXUQWkSbBkFo2AUjIJhDwBt5lOmPRYeuwAAAABJRU5ErkJggg==","orcid":"","institution":"University of Lagos","correspondingAuthor":true,"prefix":"","firstName":"Kehinde","middleName":"S.","lastName":"OKUNADE","suffix":""},{"id":571490652,"identity":"b3e661d4-3c9a-4b9b-b144-caf35d8a33e6","order_by":1,"name":"Adaiah SOIBI-HARRY","email":"","orcid":"","institution":"Lagos University Teaching Hospital","correspondingAuthor":false,"prefix":"","firstName":"Adaiah","middleName":"","lastName":"SOIBI-HARRY","suffix":""},{"id":571490653,"identity":"979aadd7-a713-4933-b727-baf119faea7c","order_by":2,"name":"Ayomide I. FAYINTO","email":"","orcid":"","institution":"Lagos Island Maternity Hospital","correspondingAuthor":false,"prefix":"","firstName":"Ayomide","middleName":"I.","lastName":"FAYINTO","suffix":""},{"id":571490654,"identity":"b47111df-3d99-43fc-84a3-01003066d717","order_by":3,"name":"Hameed ADELABU","email":"","orcid":"","institution":"University of Lagos","correspondingAuthor":false,"prefix":"","firstName":"Hameed","middleName":"","lastName":"ADELABU","suffix":""},{"id":571490655,"identity":"808ee261-ade2-48ce-a1ba-3bf5d6fec15c","order_by":4,"name":"Iyabo Y. ADEMUYIWA","email":"","orcid":"","institution":"University of Lagos","correspondingAuthor":false,"prefix":"","firstName":"Iyabo","middleName":"Y.","lastName":"ADEMUYIWA","suffix":""},{"id":571490656,"identity":"f3e4361c-881d-4266-b379-09f372a0f531","order_by":5,"name":"Ayokunle M. OLUMODEJI","email":"","orcid":"","institution":"Lagos State University Teaching Hospital","correspondingAuthor":false,"prefix":"","firstName":"Ayokunle","middleName":"M.","lastName":"OLUMODEJI","suffix":""},{"id":571490657,"identity":"6899b29b-47cc-49c7-a164-f9ffa5d85634","order_by":6,"name":"Adetunji O. ADENEKAN","email":"","orcid":"","institution":"University of Lagos","correspondingAuthor":false,"prefix":"","firstName":"Adetunji","middleName":"O.","lastName":"ADENEKAN","suffix":""},{"id":571490658,"identity":"e1568ca8-7957-4eff-9aa5-8236d60c1c93","order_by":7,"name":"Muisi A. ADENEKAN","email":"","orcid":"","institution":"Lagos Island Maternity Hospital","correspondingAuthor":false,"prefix":"","firstName":"Muisi","middleName":"A.","lastName":"ADENEKAN","suffix":""},{"id":571490661,"identity":"f1dc51de-6de5-4df6-8ce5-b2ce77b5159e","order_by":8,"name":"Festus O. OLOWOSELU","email":"","orcid":"","institution":"University of Lagos","correspondingAuthor":false,"prefix":"","firstName":"Festus","middleName":"O.","lastName":"OLOWOSELU","suffix":""},{"id":571490666,"identity":"e8cad219-78e7-4d82-b49d-ba7b33baf94d","order_by":9,"name":"Temitope V. ADEKANYE","email":"","orcid":"","institution":"Lagos University Teaching Hospital","correspondingAuthor":false,"prefix":"","firstName":"Temitope","middleName":"V.","lastName":"ADEKANYE","suffix":""},{"id":571490670,"identity":"29052fea-35f7-4018-8f04-a542da71f12e","order_by":10,"name":"Olufemi THOMAS-OGODO","email":"","orcid":"","institution":"Lagos University Teaching Hospital","correspondingAuthor":false,"prefix":"","firstName":"Olufemi","middleName":"","lastName":"THOMAS-OGODO","suffix":""},{"id":571490676,"identity":"0b37faec-bc6f-4958-974a-57af7f35942e","order_by":11,"name":"Oziegbe OGHIDE","email":"","orcid":"","institution":"Lagos University Teaching Hospital","correspondingAuthor":false,"prefix":"","firstName":"Oziegbe","middleName":"","lastName":"OGHIDE","suffix":""},{"id":571490680,"identity":"640ba9e0-14b8-415b-bdec-ab3901ea53be","order_by":12,"name":"Yusuf A. OSHODI","email":"","orcid":"","institution":"Lagos State University Teaching Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yusuf","middleName":"A.","lastName":"OSHODI","suffix":""},{"id":571490685,"identity":"797bb2e3-3e9e-46ca-9336-f956952a40ed","order_by":13,"name":"Babasola O. OKUSANYA","email":"","orcid":"","institution":"University of Lagos","correspondingAuthor":false,"prefix":"","firstName":"Babasola","middleName":"O.","lastName":"OKUSANYA","suffix":""}],"badges":[],"createdAt":"2025-11-16 08:38:11","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8126074/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8126074/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":100358446,"identity":"ca020041-8400-448e-8eb5-fb222bf36f3e","added_by":"auto","created_at":"2026-01-16 07:21:05","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":200585,"visible":true,"origin":"","legend":"","description":"","filename":"DraftManuscriptv6.0.docx","url":"https://assets-eu.researchsquare.com/files/rs-8126074/v1/21fb0bfe9b6e8a68f96437e2.docx"},{"id":99895498,"identity":"8b68a4b1-e60d-48dc-9c8b-88fc2b9a58f5","added_by":"auto","created_at":"2026-01-09 14:39:49","extension":"json","order_by":1,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":14328,"visible":true,"origin":"","legend":"","description":"","filename":"f22251a05eae4ca9b1e4d8821038b11a.json","url":"https://assets-eu.researchsquare.com/files/rs-8126074/v1/a2089f77375bae666fa9fbf2.json"},{"id":99895495,"identity":"9f1b6fb1-e890-4690-996b-ffc3555c76ff","added_by":"auto","created_at":"2026-01-09 14:39:47","extension":"xml","order_by":2,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":103718,"visible":true,"origin":"","legend":"","description":"","filename":"f22251a05eae4ca9b1e4d8821038b11a1enriched.xml","url":"https://assets-eu.researchsquare.com/files/rs-8126074/v1/78df5a734c82a40de80635bf.xml"},{"id":99895490,"identity":"2f663b18-8555-4852-954e-32739bdcd167","added_by":"auto","created_at":"2026-01-09 14:39:46","extension":"xml","order_by":3,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":101415,"visible":true,"origin":"","legend":"","description":"","filename":"f22251a05eae4ca9b1e4d8821038b11a1structuring.xml","url":"https://assets-eu.researchsquare.com/files/rs-8126074/v1/dfb0650cbe4ab8dd5668ed59.xml"},{"id":99895493,"identity":"692b3e7a-d711-4a84-8084-9dd276609b88","added_by":"auto","created_at":"2026-01-09 14:39:46","extension":"html","order_by":4,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":114935,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8126074/v1/3bf9d66ec36582864471fed3.html"},{"id":100377231,"identity":"e52834b0-5ee8-417b-af90-4c22a870125b","added_by":"auto","created_at":"2026-01-16 08:47:28","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":891046,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8126074/v1/c4fef37e-ba78-4506-8712-687a1799ce36.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Effect of Socioeconomic Status on Cervical Cancer Screening Behaviour Among Mothers of Adolescent Girls in Lagos, Nigeria: A Secondary Analysis of the mHealth-HPVac Study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eCervical cancer remains one of the most consequential yet preventable malignancies affecting women globally [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Recent estimates from GLOBOCAN 2020 place it as the fourth most common cancer among women worldwide, accounting for over 604,000 new cases and 342,000 deaths annually [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. The burden is profoundly inequitable, with approximately 90% of global cervical cancer mortality occurring in LMICs, driven largely by gaps in prevention, screening, and early detection [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Sub-Saharan Africa (SSA) bears the highest age-standardised incidence and mortality rates globally, with an incidence of 40.1 per 100,000 women\u0026mdash;nearly seven times that of high-income regions [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Nigeria contributes significantly to this burden, recording an estimated 15,000 new cases annually and over 8,000 deaths, making cervical cancer the second leading cause of female cancer mortality in the country [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. The socioeconomic consequences of cervical cancer are profound, with women in their productive years often bearing the burden, which ripples through families, workplaces and communities.\u003c/p\u003e \u003cp\u003eEvidence demonstrates that early detection through cytology, HPV testing, or visual inspection substantially reduces cervical cancer incidence and mortality [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Yet, screening uptake in SSA remains critically low, often below 25% [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Socioeconomic status (SES) is a well-established determinant of screening behaviour globally. Higher education and income levels have consistently been associated with improved health literacy, autonomous decision-making, and preventive health practices, including cervical screening [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. However, emerging evidence from LMICs suggests that this relationship may be more complex, with contextual cultural, structural, and gender-related factors mediating how SES influences screening behaviour [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Particularly among mothers, key actors in family health-seeking behaviours, the role of SES in shaping cervical screening decision-making remains insufficiently explored.\u003c/p\u003e \u003cp\u003eThis secondary analysis of the \u003cem\u003emHealth-HPVac\u003c/em\u003e study, an HPV vaccination intervention trial among mothers of unvaccinated adolescent girls in Lagos, Nigeria [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], offers a unique opportunity to leverage high-quality baseline data collected from a diverse urban population of women to provide a timely and rigorous examination of SES-related disparities in cervical cancer screening behaviour. By modelling socioeconomic indicators while adjusting for key demographic and access variables, the study aims to clarify whether SES independently predicts screening uptake in this population. Therefore, the objective of this study is to determine the effect of SES on cervical cancer screening behaviour among mothers of vaccine-eligible adolescent girls in Lagos, Nigeria. The central hypothesis is that higher SES, measured through a composite SES index comprising education and occupation, will be positively associated with cervical screening uptake, independent of access-related factors.\u003c/p\u003e"},{"header":"Participants and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Design and Settings\u003c/h2\u003e \u003cp\u003eThis study is a descriptive cross-sectional design using the baseline data obtained from the \u0026ldquo;\u003cem\u003emHealth-HPVac\u003c/em\u003e\u0026rdquo; trial [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], a recently completed randomised, parallel-arm controlled study conducted from June 2024 to March 2025. The parent trial enrolled mothers of unvaccinated girls aged 9\u0026ndash;14 years attending routine care at the General Outpatient (GOP) Clinics of the Lagos University Teaching Hospital (LUTH), Lagos, Nigeria. LUTH, the main teaching hospital of the College of Medicine, University of Lagos, is situated in an urban, socioeconomically diverse Lagos metropolis, providing a suitable environment for examining how socioeconomic gradients influence cervical cancer screening behaviour.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eStudy population\u003c/h3\u003e\n\u003cp\u003eFor this secondary analysis, we included the complete baseline dataset of 180 sexually active women from the primary study [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Eligibility for inclusion required women to have full sociodemographic, socioeconomic, and cervical cancer screening history data. Women with a previous diagnosis of cervical cancer, those of non-Nigerian nationality, or individuals unable to provide reliable responses due to cognitive impairment were excluded.\u003c/p\u003e\n\u003ch3\u003eStudy endpoints/outcomes\u003c/h3\u003e\n\u003cp\u003eThe primary outcome was the association between socioeconomic status (SES) and screening uptake, and the secondary outcome was the modifying effect of formal educational attainment on the association between income status and screening behaviour. Cervical cancer screening uptake was defined as self-reported receipt of at least one Pap test or HPV-based screening within the past 10 years, with verification through clinic records where available. The income class was derived using a transparent and replicable method informed by the Demographic and Health Survey (DHS) wealth index framework, which combines educational attainment and occupational level [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Educational attainment was categorised as None/Primary, Secondary, or Tertiary. Employment status was categorized as Unskilled, Semi-skilled, or Skilled/Professional. Variables extracted for analysis included age, parity, tribe, marital status, educational attainment, employment status, residential distance to the nearest screening facility, cervical cancer awareness, and screening uptake.\u003c/p\u003e\n\u003ch3\u003eSample size calculation\u003c/h3\u003e\n\u003cp\u003eAs this study was a secondary analysis of baseline data from the \u003cem\u003emHealth-HPVac\u003c/em\u003e trial [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], the sample size was fixed at 180 participants. To assess the adequacy of this sample for detecting the association between SES and cervical cancer screening uptake, we performed post-hoc sample size calculation using standard formulas for comparing two proportions [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] with 80% power and a two-sided alpha of 5%. Under plausible assumptions for cervical cancer screening, with a prevalence of 40\u0026ndash;50%, this sample size provides adequate power to detect approximately a 20-percentage-point difference in screening uptake. We also evaluated the adequacy of the sample for multivariable logistic regression using the events-per-variable (EPV) rule. With 93 women (51.7%) reporting prior screening (events), the dataset supports the inclusion of approximately 6\u0026ndash;8 predictor variables at EPV\u0026thinsp;\u0026asymp;\u0026thinsp;10, indicating that the planned adjusted model is statistically appropriate.\u003c/p\u003e\n\u003ch3\u003eParticipants Sampling and Study Procedure\u003c/h3\u003e\n\u003cp\u003eWe collected data in the primary study [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] through interviewer-administered electronic case report forms (eCRFs) on REDCap, hosted on secure institutional servers. The eCRF, previously published elsewhere as Supplementary Material 3 [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], captured sociodemographic characteristics, economic indicators (education and occupation), reproductive history, and cervical cancer awareness and screening behaviour. Residential distance was calculated using participants\u0026rsquo; addresses geocoded to the nearest health facility offering screening. Quality control measures included daily supervision of data collectors, range and logic checks in REDCap, and weekly data audits. Identifiable information was stored separately from research data using unique study codes to preserve confidentiality in line with ICH-GCP (E6[R2]) guidelines.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eData Analysis\u003c/h2\u003e \u003cp\u003eData analysis was conducted in Stata version 18 (StataCorp LLC, Texas, USA). Missing values were addressed using multiple imputation by chained equations under the assumption of missing at random. Descriptive statistics were used to summarize participants\u0026rsquo; characteristics using means and standard deviation for normally distributed variables and medians with interquartile ranges for skewed variables. The association between SES indicators and screening uptake was examined using multivariable logistic regression. Significant variables (\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.2) in the univariable model (age and tribe) were included as covariates to adjust for potential confounding. Model diagnostics, including multicollinearity assessment, goodness-of-fit tests, and residual analysis, were performed to ensure appropriate model specification. To examine whether educational attainment modified the effect of income on screening behaviour, an education \u0026times; income interaction term was tested. However, inclusion of this interaction resulted in numerical instability, characterized by inflated variance inflation factors (VIF\u0026thinsp;\u0026gt;\u0026thinsp;10), wide confidence intervals, and poor model convergence. For this reason, the interaction term was excluded from the final model to ensure analytical robustness. Results are presented as adjusted odds ratios (aORs) with 95% confidence intervals.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eEthical Considerations\u003c/h3\u003e\n\u003cp\u003eEthical approvals for the primary study[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] were obtained from the Health Research Ethics Committee of the College of Medicine, University of Lagos (approval number: CMUL/HREC/5/24/1464 obtained on 15th May 2024) and Lagos University Teaching Hospital (approval number: ADM/DSCST/HREC/APP/6566 obtained on 10th May 2024). Written informed consent was obtained from each participant before enrollment, with a detailed explanation of the study objectives, confidentiality safeguards, and the rights to voluntary participation. Participants were assured that declining or withdrawing from the study would not affect their access to clinical services. Data confidentiality was strictly maintained through encryption and password-protected databases. The study aligns with the Declaration of Helsinki and Nigeria\u0026rsquo;s National Code of Health Research Ethics, ensuring the protection of participants\u0026rsquo; autonomy, privacy, and welfare.\u003c/p\u003e \u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eA total of 180 women with complete baseline data were included in the analysis. Overall, 93 women reported having undergone cervical cancer screening within the previous 10 years, yielding a screening uptake of 51.7% (95% confidence interval: 44.1\u0026ndash;59.2). The mean age of participants was 43.6\u0026thinsp;\u0026plusmn;\u0026thinsp;7.2 years, and women who had been screened were significantly older than those who had never been screened (45.4\u0026thinsp;\u0026plusmn;\u0026thinsp;6.7 vs. 41.7\u0026thinsp;\u0026plusmn;\u0026thinsp;7.2 years; \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Table\u0026nbsp;1 presents participant characteristics by screening status. No statistically significant differences were observed between screened and unscreened women across key sociodemographic variables, including marital status, educational attainment, employment category, income class, tribe, and residential distance to a screening facility.\u003c/p\u003e \u003cp\u003e \u003cb\u003eTable\u0026nbsp;1: Characteristics of enrolled women stratified by their screening uptake (n\u0026thinsp;=\u0026thinsp;180)\u003c/b\u003e \u003c/p\u003e\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"618\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 300px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharacteristics\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eUptake (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNon-uptake (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003ep\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 300px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eParticipants\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e93 (51.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e87 (48.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 300px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge, years\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e45.4 \u0026plusmn; 6.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e41.7 \u0026plusmn; 7.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 300px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eResidential distance to screening facility, km\u003csup\u003ea\u003c/sup\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e13.0 (7.1\u0026ndash;22.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e10.1 (5.0\u0026ndash;22.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e0.325\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 300px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrevious pregnancies\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 300px;\"\u003e\n \u003cp\u003eOne to two\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e36 (38.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e24 (27.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e0.285\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 300px;\"\u003e\n \u003cp\u003eThree to four\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e43 (46.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e47 (54.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 300px;\"\u003e\n \u003cp\u003eMore than four\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e14 (15.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e16 (18.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 300px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMarital status\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 300px;\"\u003e\n \u003cp\u003eMarried \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e74 (79.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e69 (79.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e0.966\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 300px;\"\u003e\n \u003cp\u003eNot married\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e19 (20.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e18 (20.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 300px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducational level\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 300px;\"\u003e\n \u003cp\u003eNone/Primary\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e6 (6.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e12 (13.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e0.259\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 300px;\"\u003e\n \u003cp\u003eSecondary\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e39 (41.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e33 (37.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 300px;\"\u003e\n \u003cp\u003eTertiary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e48 (51.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e42 (48.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 300px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEmployment status\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 300px;\"\u003e\n \u003cp\u003eUnskilled\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e14 (15.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e13 (15.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e0.726\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 300px;\"\u003e\n \u003cp\u003eSemi-skilled\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e55 (59.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e47 (54.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 300px;\"\u003e\n \u003cp\u003eSkilled/professional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e24 (25.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e27 (31.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 300px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIncome class\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 300px;\"\u003e\n \u003cp\u003eLow\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e13 (14.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e19 (21.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e0.245\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 300px;\"\u003e\n \u003cp\u003eMiddle\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e62 (66.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e48 (55.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 300px;\"\u003e\n \u003cp\u003eHigh \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e18 (19.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e20 (23.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 300px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTribe \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 300px;\"\u003e\n \u003cp\u003eYoruba\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e29 (31.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e32 (36.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e0.157\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 300px;\"\u003e\n \u003cp\u003eIgbo \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e47 (50.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e32 (36.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 300px;\"\u003e\n \u003cp\u003eOthers\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e17 (18.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 114px;\"\u003e\n \u003cp\u003e23 (26.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAbbreviations: IQR, interquartile range; SD, standard deviation.\u003c/p\u003e\n\u003cp\u003e\u003csup\u003ea\u003c/sup\u003eWilcoxon rank sum test.\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAfter adjusting for age and tribe in a logistic regression model, income class was not found to be independently associated with screening uptake. Compared with women in the low-income category, those in the middle-income (adjusted OR = 1.72, 95% CI: 0.75\u0026ndash;3.98) and high-income (adjusted OR = 1.22, 95% CI: 0.45\u0026ndash;3.30) categories had higher but statistically nonsignificant odds of screening. An interaction term between education and income level was initially included to examine potential effect modification; however, its inclusion led to model instability, reflected by excessively large standard errors and poor model convergence. For this reason, the interaction term was removed, and the final model was estimated without it [Table 2]. \u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2: Multivariable analyses of effects of\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003esocioeconomic status on\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003ecervical cancer screening uptake\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e(n=180)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"606\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 174px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSES Indicators\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 240px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of screened mothers\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAdjusted OR (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 174px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIncome class\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 240px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 174px;\"\u003e\n \u003cp\u003eHigh\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 240px;\"\u003e\n \u003cp\u003e18/38 (47.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003e1.22 (0.45 \u0026ndash; 3.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 174px;\"\u003e\n \u003cp\u003eMiddle\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 240px;\"\u003e\n \u003cp\u003e62/110 (56.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003e1.72 (0.75 \u0026ndash; 3.98)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 174px;\"\u003e\n \u003cp\u003eLow \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 240px;\"\u003e\n \u003cp\u003e13/38 (40.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003e1.00 (reference)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 174px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 240px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 174px;\"\u003e\n \u003cp\u003e\u0026gt;45 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 240px;\"\u003e\n \u003cp\u003e39/57 (68.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003e7.96 (2.28 \u0026ndash; 27.78)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 174px;\"\u003e\n \u003cp\u003e35 \u0026ndash; 45 years\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 240px;\"\u003e\n \u003cp\u003e50/104 (48.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003e3.61 (1.10 \u0026ndash; 11.84)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 174px;\"\u003e\n \u003cp\u003e\u0026lt;35 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 240px;\"\u003e\n \u003cp\u003e4/19 (21.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003e1.00 (reference)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 174px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTribe \u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 240px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 174px;\"\u003e\n \u003cp\u003eYoruba\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 240px;\"\u003e\n \u003cp\u003e29/61 (47.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003e1.78 (0.79 \u0026ndash; 4.01)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 174px;\"\u003e\n \u003cp\u003eIgbo \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 240px;\"\u003e\n \u003cp\u003e47/79 (59.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003e1.11 (0.47 \u0026ndash; 2.61)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 174px;\"\u003e\n \u003cp\u003eOthers\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 240px;\"\u003e\n \u003cp\u003e17/40 (42.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 192px;\"\u003e\n \u003cp\u003e1.00 (reference)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAbbreviations: CI, confidence interval; OR, odds ratio; SES, socioeconomic status\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eInclusion of the Education and Income interaction term rendered the model unstable (large standard errors and poor convergence); hence, the interaction term was excluded from the final model.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis descriptive cross-sectional analysis of the \u003cem\u003emHealth-HPVac\u003c/em\u003e study data assessed the effect of socioeconomic status (SES) on cervical cancer screening uptake among mothers of vaccine-eligible adolescent girls in Lagos, Nigeria. Approximately half (51.7%) of the participants reported having been screened for cervical cancer within the last ten years, indicating a moderate but suboptimal level of screening uptake relative to the national [14] and World Health Organization (WHO) target [15]. This is consistent with reports from similar urban Nigerian settings [16], where cervical cancer screening remains suboptimal despite the known benefits of early detection and prevention, despite the WHO-recommended projection of 70% screening coverage among women aged 35\u0026ndash;45 years by 2030 as part of the global strategy to eliminate cervical cancer as a public health problem [15]. The observed coverage in this study underscores the persistent gap between global aspirations and local realities in many low- and middle-income countries (LMICs), including Nigeria.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Consistent with previous studies, age was the only variable significantly associated with screening uptake in our analysis, with older women more likely to have been screened compared to their younger counterparts. This finding aligns with reports from other Nigerian and sub-Saharan African studies showing that screening uptake increases with age [17\u0026ndash;19], possibly due to cumulative health encounters, higher risk perception, and increased exposure to reproductive health education [17,20]. Conversely, younger women may underestimate their risk or perceive cervical cancer screening as unnecessary until they experience symptoms, a misconception that contributes to delayed screening.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eContrary to expectations, SES was not independently associated with screening uptake after adjusting for age and tribe. This result diverges from the broader literature, which consistently identifies socioeconomic position as a key determinant of cervical cancer screening uptake in both high- and low-resource settings [21\u0026ndash;24]. A plausible explanation may be that, within the urban context of Lagos, socioeconomic disparities exert less influence due to the relatively high concentration of health facilities and targeted awareness programs that have improved access across social strata. Moreover, cultural attitudes, perceived stigma, and fear of diagnosis have been shown to outweigh economic factors in determining health-seeking behaviour for cervical screening in Nigeria [25\u0026ndash;28]. This finding may also reflect the availability of subsidised or free screening programs within Lagos, such as those implemented by non-governmental organisations [29], which may have attenuated the influence of economic status on screening participation. It is also possible that self-reported income and occupational status do not fully capture economic empowerment or financial decision-making autonomy among women, particularly in patriarchal household structures common in the study setting. Furthermore, in testing for effect modification, the interaction term between education and income rendered the multivariable model unstable due to multicollinearity and large standard errors, suggesting interdependence between these variables. This statistical instability has been reported in similar population studies where socioeconomic status indicators are highly correlated [30,31]. Future research employing composite socioeconomic indices or principal component analysis may better capture multidimensional socioeconomic effects on screening behaviour.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;This study has a few limitations. First, the cross-sectional nature of the analysis and the likely recall bias due to the reliance on self-reported cervical cancer screening history and our inability to verify all screening records could preclude causal inference. Second, analysis of SES relies primarily on education and employment. However, SES is multidimensional and thus exclusion of household assets, housing characteristics, or family economic size, which were not available in the datasets, may limit validity. Third, the sample was hospital-based, limiting generalizability to community settings. Fourth, due to the study\u0026rsquo;s secondary analytical framework, residual confounding from unmeasured or inadequately captured variables cannot be excluded. Fifth, as the study participants were mothers attending an outpatient clinic at a tertiary hospital, who are likely more health-aware than the general population, there is a high likelihood of unduly inflated screening uptake estimates, reduced SES variability, and limited generalizability to community samples. Finally, while the study is sufficiently powered to assess broad socioeconomic disparities, it may be underpowered to detect modest associations, which could have limited the comprehensiveness of the explanatory model and partly accounted for the lack of statistically significant associations between SES and screening uptake. Larger, adequately powered population-based studies are therefore needed to validate these findings and better delineate the socioeconomic gradients in screening behaviour among Nigerian women. Nonetheless, the study provides valuable insights into the complex interplay between socioeconomic status and cervical cancer screening behaviours in an urban Nigerian population.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eOur study showed a moderate cervical cancer screening uptake in the enrolled cohort of mothers of vaccine-eligible adolescent girls in Lagos, Nigeria. Socioeconomic status was not independently associated with screening uptake. These findings highlight the need to address structural and behavioural barriers that may be more critical to screening uptake than focusing solely on economic or educational disparities. Future studies with larger samples and longitudinal designs could provide further insight into the complex determinants of cervical cancer screening behaviour in Nigerian women.\u003c/p\u003e\n"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors are particularly grateful to the participating women who generously shared their time, enabling us to conduct this important study. We would also like to express our appreciation to the personnel at the Research Management Office of the College of Medicine, University of Lagos, for their support in obtaining the funding for this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical approvals for the primary study were obtained from the Health Research Ethics Committee of the College of Medicine, University of Lagos (approval number: CMUL/HREC/5/24/1464 obtained on 15th May 2024) and Lagos University Teaching Hospital (approval number: ADM/DSCST/HREC/APP/6566 obtained on 10th May 2024).\u0026nbsp; The study was conducted ethically according to the World Medical Association Declaration of Helsinki. Informed consent was secured from each participant. Confidentiality, anonymity, and the right of participants to withdraw consent were maintained throughout and after the study was conducted.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eKehinde S. Okunade, Adaiah Soibi-Harry, and Muisi A. Adenekan contributed to the study\u0026apos;s conception and design. All authors performed material preparation, data collection and analysis.\u0026nbsp;Kehinde S. Okunade, Ayomide I. Fayinto, and Yusuf A. Oshodi wrote the first draft of the manuscript. All authors commented on previous versions of the manuscript and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe author declares no competing interests in the publication of this article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors intend to grant access to the datasets used and/or analysed in the study upon reasonable request from the corresponding author (Kehinde S. Okunade).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe lead author (Kehinde S. Okunade) received protected time for this work through funding from the Conquer Cancer International Innovation Grant under Project ID 2024IIG-2761200216, the National Cancer Institute and Fogarty International Centre of the National Institutes of Health under Award Number K43TW011930. The content of this paper is solely the responsibility of the authors and does not necessarily represent the official views of the Conquer Cancer Foundation, the National Cancer Institute, Fogarty International Centre, or the National Institutes of Health. The funders had no role in the conceptualisation, the decision to publish, or the preparation of the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eSung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries. CA Cancer J Clin. 2021;71:209\u0026ndash;49. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3322/caac.21660\u003c/span\u003e\u003cspan address=\"10.3322/caac.21660\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBruni L, Serrano B, Roura E, Alemany L, Cowan M, Herrero R, et al. Cervical cancer screening programmes and age-specific coverage estimates for 202 countries and territories worldwide: a review and synthetic analysis. Lancet Glob Health. 2022;10:e1115\u0026ndash;27. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/S2214-109X(22)00241-8\u003c/span\u003e\u003cspan address=\"10.1016/S2214-109X(22)00241-8\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eArbyn M, Weiderpass E, Bruni L, de Sanjos\u0026eacute; S, Saraiya M, Ferlay J, et al. Estimates of incidence and mortality of cervical cancer in 2018: a worldwide analysis. Lancet Glob Health. 2020;8:e191\u0026ndash;203. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/S2214-109X(19)30482-6\u003c/span\u003e\u003cspan address=\"10.1016/S2214-109X(19)30482-6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDaniel FM, Ike WI, Gbuchie Anurika M, Udofia James S, Chinyere Kalu P, Ebizo Ikpa S, Knowledge. Attitude, and Prevalence Towards Cervical Cancer Screening Among Women in a Nigerian Urban Municipality. Int J Med Students. 2023;S91. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.5195/ijms.2023.2369\u003c/span\u003e\u003cspan address=\"10.5195/ijms.2023.2369\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePerkins RB, Guido RS, Castle PE, Chelmow D, Einstein MH, Garcia F et al. 2019 ASCCP Risk-Based Management Consensus Guidelines for Abnormal Cervical Cancer Screening Tests and Cancer Precursors ASCCP Risk-Based Management Consensus Guidelines Committee 2020. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1097/LGT.0000000000000525\u003c/span\u003e\u003cspan address=\"10.1097/LGT.0000000000000525\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOkunowo AA, Daramola ES, Soibi-Harry AP, Ezenwankwo FC, Kuku JO, Okunade KS, et al. Women\u0026rsquo;s knowledge of cervical cancer and uptake of Pap smear testing and the factors influencing it in a Nigerian tertiary hospital. J Cancer Res Pract. 2018. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.jcrpr.2018.02.001\u003c/span\u003e\u003cspan address=\"10.1016/j.jcrpr.2018.02.001\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAltov\u0026aacute; A, Kulh\u0026aacute;nov\u0026aacute; I, Reisser K, Netrdov\u0026aacute; P, Brož J, Eikemo TA, et al. Educational inequalities in cervical cancer screening participation in 24 European countries. Public Health. 2024;233:1\u0026ndash;7. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.puhe.2024.04.036\u003c/span\u003e\u003cspan address=\"10.1016/j.puhe.2024.04.036\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAsgedom YS, Kassie GA, Habte A, Ketema DB, Aragaw FM. Socioeconomic inequality in cervical cancer screening uptake among women in sub-Saharan Africa: a decomposition analysis of Demographic and Health Survey data. BMJ Open. 2024;14:e088753. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1136/bmjopen-2024-088753\u003c/span\u003e\u003cspan address=\"10.1136/bmjopen-2024-088753\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePetersen Z, Jaca A, Ginindza TG, Maseko G, Takatshana S, Ndlovu P, et al. Barriers to uptake of cervical cancer screening services in low-and-middle-income countries: a systematic review. BMC Womens Health. 2022;22:486. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s12905-022-02043-y\u003c/span\u003e\u003cspan address=\"10.1186/s12905-022-02043-y\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOkunade KS, Adejimi AA, Adekanye TV, Allsop MJ, Adelabu H, Thomas-Ogodo O, et al. Impact of mobile health technologies on human papillomavirus vaccination uptake among mothers of unvaccinated girls aged 9\u0026ndash;14 years in Lagos, Nigeria (mHealth-HPVac): study protocol of a randomised controlled trial. BMC Cancer. 2024;24:751. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s12885-024-12538-6\u003c/span\u003e\u003cspan address=\"10.1186/s12885-024-12538-6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOkunade KS, Fayinto AI, Adekanye TV, Allsop MJ, Adelabu H, Soibi-Harry A et al. Randomized Controlled Trial of Impact of Mobile Health Technologies on Human Papillomavirus Vaccination Uptake in Mothers of Vaccine-Eligible Girls in Lagos, Nigeria (mHealth-HPVac). JCO Glob Oncol 2025. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1200/GO-25-00150\u003c/span\u003e\u003cspan address=\"10.1200/GO-25-00150\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRutstein Shea Oscar Johnson Kiersten. DHS Comparative Reports No. 6:The DHS Wealth Index. Maryland USA: Calverton; 2004.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCharan J, Biswas T. How to Calculate Sample Size for Different Study Designs in Medical Research? Indian J Psychol Med. 2013;35:121\u0026ndash;6. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.4103/0253-7176.116232\u003c/span\u003e\u003cspan address=\"10.4103/0253-7176.116232\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWorld Health Organisation. Costing the National Strategic Plan on Prevention and Control of Cervical Cancer. Nigeria; 2020. pp. 2017\u0026ndash;21.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSingh D, Vignat J, Lorenzoni V, Eslahi M, Ginsburg O, Lauby-Secretan B et al. Global estimates of incidence and mortality of cervical cancer in 2020: a baseline analysis of the WHO Global Cervical Cancer Elimination Initiative. Lancet Glob Health 2022. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/S2214-109X(22)00501-0\u003c/span\u003e\u003cspan address=\"10.1016/S2214-109X(22)00501-0\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOkunade KS, John-Olabode S, Adejimi AA, Oshodi YA, Osunwusi B, Ugwu AO et al. Predictors of Pap smear testing uptake among women in Lagos, Nigeria. Ecancermedicalscience 2022;16. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3332/ecancer.2022.1368\u003c/span\u003e\u003cspan address=\"10.3332/ecancer.2022.1368\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBa DM, Ssentongo P, Musa J, Agbese E, Diakite B, Traore CB, et al. Prevalence and determinants of cervical cancer screening in five sub-Saharan African countries: A population-based study. Cancer Epidemiol. 2021;72:101930. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.canep.2021.101930\u003c/span\u003e\u003cspan address=\"10.1016/j.canep.2021.101930\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTiruneh FN, Chuang K-Y, Ntenda PAM, Chuang Y-C. Individual-level and community-level determinants of cervical cancer screening among Kenyan women: a multilevel analysis of a Nationwide survey. BMC Womens Health. 2017;17:109. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s12905-017-0469-9\u003c/span\u003e\u003cspan address=\"10.1186/s12905-017-0469-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCompaore S, Ouedraogo CMR, Koanda S, Haynatzki G, Chamberlain RM, Soliman AS. Barriers to Cervical Cancer Screening in Burkina Faso: Needs for Patient and Professional Education. J Cancer Educ. 2016;31:760\u0026ndash;6. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s13187-015-0898-9\u003c/span\u003e\u003cspan address=\"10.1007/s13187-015-0898-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEmagneneh T, Mulugeta C, Ejigu B, Alamrew A, Abebaw N, Yessuf A, et al. Uptake of cervical cancer screening and its associated factors in Africa: an umbrella review of systematic reviews and meta-analyses. BMC Public Health. 2025;25:2968. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s12889-025-24173-2\u003c/span\u003e\u003cspan address=\"10.1186/s12889-025-24173-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSeifu BL, Negussie YM, Asnake AA, Asebe HA, Fente BM, Asmare ZA, et al. Wealth-related inequalities of women\u0026rsquo;s cervical cancer screening in 11 Sub-Saharan African countries: evidence from a pooled decomposition analysis. Sci Rep. 2025;15:12289. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/s41598-025-96347-2\u003c/span\u003e\u003cspan address=\"10.1038/s41598-025-96347-2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAsgedom YS, Kassie GA, Habte A, Ketema DB, Aragaw FM. Socioeconomic inequality in cervical cancer screening uptake among women in sub-Saharan Africa: a decomposition analysis of Demographic and Health Survey data. BMJ Open. 2024;14:e088753. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1136/bmjopen-2024-088753\u003c/span\u003e\u003cspan address=\"10.1136/bmjopen-2024-088753\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIlevbare OE, Adegoke AA, Adelowo CM. Drivers of cervical cancer screening uptake in Ibadan. Nigeria Heliyon. 2020;6:e03505. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/j.heliyon.2020.e03505\u003c/span\u003e\u003cspan address=\"10.1016/j.heliyon.2020.e03505\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDozie UW, Ebirim CIC, Dike CR, Dozie INS, Ibe SNO, Abanobi OC. Determinants of cervical cancer screening uptake among female undergraduates in a tertiary institution in south eastern Nigeria: a cross sectional study. J Prev Med Hyg. 2021;62:E213\u0026ndash;21. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.15167/2421-4248/jpmh2021.62.1.1828\u003c/span\u003e\u003cspan address=\"10.15167/2421-4248/jpmh2021.62.1.1828\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMafiana JJ, Dhital S, Halabia M, Wang X. Barriers to uptake of cervical cancer screening among women in Nigeria: a systematic review. Afr Health Sci. 2022;22:295\u0026ndash;309. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.4314/ahs.v22i2.33\u003c/span\u003e\u003cspan address=\"10.4314/ahs.v22i2.33\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGwom Dung D, Matthew Mamman S, Musa Magaji J, SOCIO-CULTURAL FACTORS INFLUENCING, THE PRACTICE OF CERVICAL CANCER SCREENING AMONG WOMEN IN ANTENATAL AND POST NATAL CLINIC IN DALHATU ARAF SPECIALIST HOSPITAL LAFIA., NASARAWA STATE, NIGERIA. vol. 14. 2024.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBello I, Aliyu Z, Aliyu A, Abubakar S, Aminu Abbas A. Sociocultural Factors in Cervical Cancer Screening uptake among Women of Reproductive Age in Kaduna Metropolis, Kaduna State, Nigeria. Texila Adv J Multidisciplinary Health Res. 2025. https://doi.org/10.21522./TAJMHR.2016.05.01.Art020.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIsa Modibbo F, Dareng E, Bamisaye P, Jedy-Agba E, Adewole A, Oyeneyin L, et al. Qualitative study of barriers to cervical cancer screening among Nigerian women. BMJ Open. 2016;6:e008533. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1136/bmjopen-2015-008533\u003c/span\u003e\u003cspan address=\"10.1136/bmjopen-2015-008533\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOkunade K, Salako O, Adenekan M, Sunmonu O, Salawu K, Sekumade A, et al. The uptake of cervical cancer control services at a cancer information service center in Lagos, Nigeria. Nigerian J Gen Pract. 2018;16:20. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.4103/NJGP.NJGP_21_17\u003c/span\u003e\u003cspan address=\"10.4103/NJGP.NJGP_21_17\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWadolowska L, Kowalkowska J, Lonnie M, Czarnocinska J, Jezewska-Zychowicz M, Babicz-Zielinska E. Associations between physical activity patterns and dietary patterns in a representative sample of Polish girls aged 13\u0026ndash;21 years: a cross-sectional study (GEBaHealth Project). BMC Public Health. 2016;16:698. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s12889-016-3367-4\u003c/span\u003e\u003cspan address=\"10.1186/s12889-016-3367-4\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFiandrino S, Dowd C, Martini G, Mejova Y, Omodei E, Paolotti D et al. Impact of food-related conflicts on self-reported food insecurity. Front Sustain Food Syst 2023;7. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3389/fsufs.2023.1239992\u003c/span\u003e\u003cspan address=\"10.3389/fsufs.2023.1239992\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Cervical cancer, screening uptake, socioeconomic status, education, Nigeria","lastPublishedDoi":"10.21203/rs.3.rs-8126074/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8126074/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eCervical cancer remains a preventable malignancy with high morbidity and mortality in low- and middle-income countries (LMICs). Screening uptake is suboptimal in sub-Saharan Africa, and the influence of socioeconomic status (SES) on screening behaviour among women remains insufficiently explored.\u003c/p\u003e\u003ch2\u003eAim\u003c/h2\u003e \u003cp\u003eTo determine the effect of SES on cervical cancer screening uptake among mothers of vaccine-eligible adolescent girls in Lagos, Nigeria.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis secondary analysis used baseline data from the \u003cem\u003emHealth-HPVac\u003c/em\u003e trial, including 180 sexually active mothers of unvaccinated girls aged 9\u0026ndash;14 years. The primary outcome was self-reported cervical cancer screening within the previous 10 years. A multivariable logistic regression model was used to examine the association between SES and screening uptake, adjusting for age and tribe. Education and income were tested as an interaction term but excluded due to model instability.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eOverall, 51.7% of participants reported prior cervical screening. Women who had been screened were significantly older than unscreened women (45.4\u0026thinsp;\u0026plusmn;\u0026thinsp;6.7 vs 41.7\u0026thinsp;\u0026plusmn;\u0026thinsp;7.2 years; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Screening uptake did not differ significantly by marital status, education, employment, income class, tribe, or residential distance to screening facilities. In adjusted models, neither middle-income (adjusted odds ratio\u0026thinsp;=\u0026thinsp;1.72, 95% CI: 0.75\u0026ndash;3.98) nor high-income status (adjusted odds ratio\u0026thinsp;=\u0026thinsp;1.22, 95% CI: 0.45\u0026ndash;3.30) was associated with screening.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eCervical cancer screening uptake among mothers in Lagos is moderate, and SES was not independently associated with screening. Interventions should target structural or behavioural factors rather than focusing solely on economic disparities. Larger, adequately powered population-based studies are therefore needed to validate these findings and better delineate the socioeconomic gradients in screening behaviour among Nigerian women.\u003c/p\u003e","manuscriptTitle":"Effect of Socioeconomic Status on Cervical Cancer Screening Behaviour Among Mothers of Adolescent Girls in Lagos, Nigeria: A Secondary Analysis of the mHealth-HPVac Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-09 14:39:11","doi":"10.21203/rs.3.rs-8126074/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-04-23T04:50:25+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-10T09:00:02+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-03T21:39:53+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"149759275847112516335392846076875734927","date":"2026-02-18T09:30:44+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"241199798728306408655066852116610881328","date":"2026-02-16T16:54:20+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"107162781950530029033290923540362401679","date":"2026-02-16T11:01:44+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"199613401209981917927439741400120937101","date":"2026-02-12T19:38:31+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"317687818660712405995321200443755551061","date":"2026-02-02T17:04:46+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-01-08T12:51:14+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-11-22T11:24:58+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-11-20T15:46:35+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Public Health","date":"2025-11-20T15:43:20+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"d88f406e-5689-4907-82d0-eb00ab6d53de","owner":[],"postedDate":"January 9th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-14T07:24:06+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-09 14:39:11","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8126074","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8126074","identity":"rs-8126074","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}