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Systematic Review
 Socioeconomic factors affecting breast and cervical cancer screening compliance in Asian National Cancer Centers Alliance countries: a systematic review
Seowoo Bae1*orcid, Ye Ji Kang1*orcid, Jeonghoon Ahn2orcid, Bo-Hyoung Jang3orcid, Kui Son Choi1,4orcid, Hyeon Ji Lee1orcid, Mina Suh1,4orcid
Epidemiol Health 2025;47:e2025050.
DOI: https://doi.org/10.4178/epih.e2025050
Published online: August 28, 2025

1National Cancer Control Institute, National Cancer Center, Goyang, Korea

2Department of Health Convergence, Ewha Womans University, Seoul, Korea

3Department of Preventive Medicine, Kyung Hee University College of Korean Medicine, Seoul, Korea

4Graduate School of Cancer Science and Policy, National Cancer Center, Goyang, Korea

Correspondence: Mina Suh National Cancer Control Institute, National Cancer Center, 323 Ilsan-ro, Ilsandong-gu, Goyang 10408, Korea E-mail: omnibus@ncc.re.kr
*Bae & Kang contributed equally to this work as joint first authors.
• Received: May 26, 2025   • Accepted: August 13, 2025

© 2025, Korean Society of Epidemiology

This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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  • Breast and cervical cancers are the most frequently diagnosed cancers in women. The Asian National Cancer Centers Alliance (ANCCA) has strengthened cancer control efforts in the Asia region; however, only a few countries have achieved sufficient participation rates. This systematic review aimed to synthesize the existing evidence on socioeconomic factors influencing women’s compliance with breast and cervical cancer screening in ANCCA countries. This study was conducted as a systematic review, with studies collected from PubMed, Cochrane Library, Scopus, and Embase. All included studies employed cross-sectional designs to identify socioeconomic factors affecting compliance with breast or cervical cancer screening. Study selection, quality assessment, and data extraction were carried out by 2 independent reviewers with cross-checking. In total, 48 studies were reviewed. Education level and family history were associated with participation in breast cancer screening, while education level, household income, marital status, and medical insurance were linked with cervical cancer screening. When stratified by Human Development Index (HDI) level or by the presence of a National Cancer Screening Program, differences were observed in the factors influencing screening compliance. Nevertheless, higher education consistently correlated with higher screening rates for both cancer types, regardless of HDI level. This systematic review identified multiple socioeconomic factors that shape breast and cervical cancer screening compliance in Asian countries. To reduce disparities in participation, tailored multi-strategy approaches adapted to each country’s specific context are required. These findings may provide useful evidence for future research and policy initiatives aimed at addressing health equity issues.
  • Keywords: Early detection of cancer, Breast neoplasm, Uterine cervical neoplasm, Socioeconomic factors, Systematic review
Breast and cervical cancer screening compliance among women is influenced by various socioeconomic factors. Higher education consistently increased screening participation for both cancers, whereas other factors differed by cancer type. To reduce disparities and promote health equity, multi-strategy approaches tailored to each country’s specific context are required.
Breast and cervical cancers are the most commonly diagnosed cancers among women worldwide [1], contributing disproportionately to morbidity and mortality in low- and middle-income countries (LMICs) [2]. In 2022, breast cancer accounted for approximately 2.3 million new cases, representing 11.6% of all cancers, and around 666,000 deaths (6.9%). Cervical cancer contributed 661,021 new cases (3.3%) and 348,189 deaths (3.6%) [1].
To address this global health burden, the World Health Organization (WHO) recommends organized national screening programs to ensure early detection and timely treatment of breast and cervical cancers [2,3]. Specifically for cervical cancer, the WHO has set a goal of elimination by 2030, emphasizing widespread human papillomavirus (HPV) vaccination alongside regular screening [2].
With nearly 60% of the world’s population residing in Asia, the region carries a considerable cancer burden, underscoring the urgent need for effective control strategies [4]. The Asian National Cancer Centers Alliance (ANCCA) has been pivotal in fostering regional collaboration, disseminating best practices, and supporting evidence-based policy implementation across member countries to improve cancer control, including screening for breast and cervical cancers [5,6].
Despite these efforts, prevention and management strategies remain highly variable across countries [5,6]. ANCCA’s comparative analysis found that although 15 member countries (71%) provide breast cancer screening, only 8 (38%) operate organized programs, often substituting clinical breast examinations (CBE) or ultrasound for mammography due to infrastructure constraints [5]. Breast cancer screening rates vary widely, ranging from 6.7% in Bangladesh to 64% in Korea [6]. For cervical cancer, most countries offer national screening programs, yet participation remains low, with only 5 reporting coverage above 50% [5].
Disparities in screening compliance arise not only from healthcare infrastructure but also from broader socioeconomic and structural determinants, including income, education, health literacy, policy priorities, and accessibility of care. Socioeconomic factors are well established as major influences on participation. For instance, individuals with higher levels of education are more likely to undergo screening. Although several studies have examined these issues within individual countries or regions, comparative research that integrates findings across Asia remains limited [7].
Therefore, this study aimed to analyze the socioeconomic factors influencing participation in breast and cervical cancer screening across ANCCA member countries, while also comparing differences in the impact of these factors between cancer types. In addition, countries were grouped by income level and by the presence of a national screening program to examine patterns among those with similar healthcare infrastructure.
The Preferred Reporting Items for Systematic reviews and Meta-Analysis (PRISMA) statement was used as a guideline in conducting this study. The study protocol was registered in PROSPERO on May 3, 2024 (ID No. CRD42024544549).
The purpose of this review was to identify socioeconomic factors associated with compliance with breast or cervical cancer screening in ANCCA member countries, focusing on women aged 20 years and older. Guided by the conceptual frameworks of the World Report on Social Determinants of Health Equity [8] and the Health at a Glance 2023 report [9], this study specifically selected socioeconomic variables including age, household income, education level, employment status, residential area (urban vs. rural), marital status, family history of cancer, and health insurance coverage as potential determinants of screening behavior. These factors represent internationally recognized social determinants of health, which shape healthcare access, participation in preventive services, and uptake of cancer screening.
Because of the heterogeneity in study designs and outcome measures among the included studies, a qualitative synthesis was employed. A socioeconomic factor was considered associated with screening compliance if more than half of the studies that examined it reported a statistically significant association. This threshold was established to ensure consistency in interpretation across diverse study contexts. The primary outcome was screening compliance for breast or cervical cancer, and only cross-sectional studies were included. Although the initial search did not restrict study design, most eligible studies identified during screening were cross-sectional. As the goal of this review was to assess screening compliance at a single point in time, cross-sectional studies were deemed most appropriate. To maintain methodological consistency and minimize heterogeneity, only cross-sectional studies were ultimately retained.
Search strategy
PubMed, Cochrane Library, Embase, and Scopus were searched on March 22, 2024, using the following strategy:
(Breast neoplasms[MESH] OR “breast cancer” OR Uterine cervical neoplasms[MESH] OR “cervical cancer”) AND (Early detection of cancer[MESH] OR screen* OR Mammography[MESH] OR pap smear OR “pap test”) AND (“screening adherence” OR “compliance adherence” OR “participation” OR “adherence” OR “compliance”) AND (“factor” OR “facilitator” OR “barrier” OR “socioeconomic” OR “inequality”) AND (“Afghanistan” OR “Armenia” OR “Azerbaijan” OR “Bahrain” OR “Bangladesh” OR “Bhutan” OR “Brunei” OR “Cambodia” OR “China” OR “Cyprus” OR “Georgia” OR “India” OR “Indonesia” OR “Iran” OR “Iraq” OR “Israel” OR “Japan” OR “Jordan” OR “Kazakhstan” OR “Kuwait” OR “Kyrgyzstan” OR “Laos” OR “Lebanon” OR “Malaysia” OR “Maldives” OR “Mongolia” OR “Myanmar” OR “Nepal” OR “Korea” OR “Oman” OR “Pakistan” OR “Palestine” OR “Philippines” OR “Qatar” OR “Russia” OR “Saudi Arabia” OR “Singapore” OR “Sri Lanka” OR “Syria” OR “Taiwan” OR “Tajikistan” OR “Thailand” OR “Timor-Leste” OR “Turkey” OR “Turkmenistan” OR “United Arab Emirates” OR “Uzbekistan” OR “Vietnam” OR “Yemen”). The search strategy was designed to incorporate the target cancer, screening outcomes, socioeconomic determinants, and the full list of Asian countries.
Studies investigating participation in breast or cervical cancer screening were included, and only those published after 2010 were considered. Studies were excluded if: (1) the study population was not the general population (e.g. high-risk groups with adenomas or a history of cancer, or healthcare providers); (2) they were unrelated to breast or cervical cancer; (3) they lacked outcomes related to screening adherence or compliance; (4) they did not include comparisons across levels of socioeconomic factors (e.g., age, income level, education level, employment status, residential area [urban or rural], marital status, health insurance coverage, or family history); (5) they did not have a cross-sectional design; (6) they did not involve human participants (e.g., animal studies); (7) they were not conducted in 1 of the 21 ANCCA countries; (8) they were not written in English; (9) they were in the gray literature (e.g., research reports, conference materials, or unpublished manuscripts); (10) they were study protocols; (11) the full text was not available; and (12) there were other reasonable grounds for exclusion (e.g. conference abstracts).
Titles and abstracts were screened in the first round, followed by full-text review. Both rounds were independently conducted by 2 researchers. Disagreements were resolved by re-evaluation or consultation with a third researcher until consensus was reached.
Quality assessment
The quality of the included studies was assessed using the Appraisal Tool to Assess the Quality of Cross-Sectional Studies developed by the British Medical Journal. This tool, created through a Delphi process, includes 20 items. A scoring system was applied, assigning 1 point for “yes” and 0 points for both “no” and “cannot tell/do not know,” resulting in a maximum score of 20. Studies scoring 19-20 points were classified as very low risk of bias, 17-18 as low risk, 15-16 as moderate risk, and below 14 as high risk of bias. In this review, studies scoring below 16 were excluded.
Systematic review
A qualitative synthesis was performed to determine whether each socioeconomic factor had a significant effect on participation in breast or cervical cancer screening. For factors found to significantly influence screening participation, results were summarized using odds ratios (ORs) with 95% confidence intervals (CIs).
Subgroup analysis
Countries were categorized by their economic and social development levels using the Human Development Index (HDI), developed by the United Nations Development Programme. The HDI is a composite index integrating life expectancy, education (mean and expected years of schooling), and income (gross national income per capita). Countries are classified into 4 categories, from group 1 (very high) to group 4 (low). In this study, subgroup analyses compared group 1 (very high) with groups 2-3 (high and medium). None of the included countries fell into group 4 (low).
In addition, a subgroup analysis was conducted for breast cancer based on whether countries provided a National Cancer Screening Program (NCSP). Studies conducted prior to the implementation of such programs were excluded from this analysis. For cervical cancer, subgroup analysis was not performed because all included studies were from countries that had already implemented national screening programs.
Ethics statement
No ethical approval or informed consent were not required since this study was based on published articles only, and did not involve any human subject data.
Search outcomes
A total of 1,015 articles were identified (PubMed: 166, Cochrane: 209, Scopus: 327, and Embase: 313), with 204 duplicates removed. After title and abstract screening, many studies were excluded, leaving 325 articles for full-text review. Of these, 52 studies met the inclusion criteria. Following quality assessment, 4 studies were excluded for failing to meet the predefined threshold of 16 points. Consequently, 48 studies were included in the final analysis. The process of study selection is illustrated in Figure 1.
Study characteristics
All 48 studies used a cross-sectional design to evaluate socioeconomic factors associated with participation in breast or cervical cancer screening. Among these, 27 studies examined breast cancer screening [10-36], while 29 studies focused on cervical cancer screening [11,13,15,18,19,27,29,31,37-57]. Eight studies investigated both breast and cervical cancer screening and were classified under both categories. In total, 12 countries were represented in this review.
Table 1 summarizes the characteristics of studies on breast cancer screening. Korea and China contributed the highest number of studies, with 6 each. Iran contributed 5 studies, while Indonesia, Thailand, Japan, Mongolia, and Malaysia provided between 1 and 3 studies each. Screening methods varied across studies, including breast self-examination, CBE, mammography, and ultrasonography. Sample sizes ranged from 206 to 4,042,332 participants.
Among the 29 studies on cervical cancer screening, China and Korea contributed the most, with 8 and 5 studies, respectively. Iran contributed 4 studies, Malaysia 3, and Thailand 2, while several other countries contributed 1 study each. Screening modalities included Pap smear testing, pelvic examination, and HPV testing. Sample sizes ranged from 77 to 21,422 participants (Table 2).
Age associations with participation in breast and cervical cancer screening
Many studies on breast cancer focused on women aged 40 years and older. Of the 23 studies that analyzed age as a factor influencing screening participation, 17 demonstrated significant associations. Overall, screening rates tended to be lower in age groups younger than 40 or older than 60, with the highest rates typically among women in their 40s and 50s. For instance, Gang et al. [10] reported that women aged 40-49 had higher mammography screening rates than those under 39 (OR, 2.37; 95% CI, 1.10 to 5.12). Conversely, Teo et al. [28] found that women aged 50 and older were less likely to undergo screening compared with those younger than 50 (OR, 0.57; 95% CI, 0.34 to 0.94).
For cervical cancer, study populations were generally younger than those in breast cancer studies. Among the 23 studies that analyzed age, 14 reported significant associations, but no consistent directional trend was observed across age groups. The influence of age on screening compliance for each study is detailed in Supplementary Materials 1 and 2.
Socioeconomic factors associated with participation in breast and cervical cancer screening
Table 3 presents the socioeconomic factors associated with participation in breast and cervical cancer screening as identified in the included studies.
For breast cancer screening, educational level and family history of breast cancer were most frequently identified as significant determinants. More than half of the studies found that women with higher education levels or with a family history of breast cancer were more likely to participate in screening. For example, Anwar et al. [18] reported that women with at least a high school education were significantly more likely to undergo breast cancer screening compared to those with less education (OR, 4.26; 95% CI, 3.39 to 5.36) (Supplementary Material 3). Similarly, studies comparing women with no formal education to those with some education consistently found higher participation rates in the latter group [16,17,23,32,36] (Supplementary Material 3). With regard to family history, Grosse Frie et al. [16] found that women with a family history of breast cancer were more likely to participate in screening than those without (OR, 1.24; 95% CI, 1.10 to 1.39).
For cervical cancer, education level was again a major determinant, but additional factors were consistently associated with screening participation, including household income, marital status, and medical insurance coverage. For example, Lee et al. [11] reported that women in higher income quintiles were more likely to undergo cervical cancer screening than those in the lowest quintile, with adjusted ORs of 2.16 (95% CI, 1.08 to 4.31) for the fourth quintile and 3.39 (95% CI, 1.66 to 6.92) for the fifth quintile (Supplementary Material 4).
Marital status was also strongly associated with participation. Amin et al. [44] demonstrated that married women had substantially higher odds of screening compared with single women (OR, 45.84; 95% CI, 29.46 to 71.34) (Supplementary Material 5).
Furthermore, 4 studies consistently showed that women with medical insurance were more likely to participate in screening than those without coverage [18,40,45,48] (Supplementary Material 5).
Socioeconomic factors affecting cancer screening participation rate by Human Development Index classification
As shown in Table 4, this study examined the socioeconomic factors influencing screening participation, stratified by the HDI group of each country. The classification of ANCCA member countries by HDI level is illustrated in Figure 2.

Breast cancer screening

In countries with very high HDI (group 1), including Singapore, Korea, Thailand, and Japan, education level and household income emerged as significant factors. In contrast, in countries with high to low HDI (groups 2-4), such as Iran, Indonesia, China, India, Mongolia, and Bhutan, screening participation was more strongly influenced by education level, employment status, and family history.

Cervical cancer screening

For cervical cancer screening, education level was the primary determinant in group 1 countries. In groups 2-4, a broader range of factors influenced participation, including education level, household income, employment status, and marital status.
The ORs for each factor with significant effects are presented in Supplementary Materials 6-10.
Socioeconomic factors affecting breast cancer screening participation rate by National Cancer Screening Program implementation classification
ANCCA member countries were also categorized according to whether or not they had implemented a NCSP. The list of countries providing NCSP is shown in Figure 2.
Among countries with NCSP, household income was identified as a significant factor influencing screening participation, particularly in Singapore, Korea, and Japan. By contrast, in countries without NCSP, education level, employment status, and region of residence were consistently significant determinants. Specifically, education was identified as a significant factor in Indonesia, India, China, and Thailand; employment status in India and China; and region of residence in Indonesia and China (Table 4). The ORs for each significant factor are provided in Supplementary Materials 11 and 12.
To our knowledge, this study is the only systematic review that explores socioeconomic factors influencing compliance with breast and cervical cancer screening across ANCCA countries. Unlike many studies that examine each cancer type separately, this research is notable in that it compares both cancers, highlighting how study designs vary and how the determinants of screening participation differ.
Before addressing the main findings, it is important to interpret the results with caution. Considerable heterogeneity existed across studies, including differences in screening methods and national contexts. As a result, only a qualitative synthesis was performed rather than a meta-analysis. A factor was considered to significantly influence screening compliance if more than half of the included studies reported such an effect. However, because these results are not based on pooled statistical estimates, they should not be regarded as conclusive evidence. Instead, they should be understood as indicative of potential trends.
In summary, education level and family history emerged as significant determinants of breast cancer screening compliance. For cervical cancer, education level was also a key factor, but additional determinants included household income, marital status, and medical insurance. These findings are consistent with evidence from the Korean National Cancer Screening Survey (2005-2015), which demonstrated greater socioeconomic inequalities in cervical cancer screening than in breast cancer screening [7]. Specifically, disparities in cervical cancer screening were quantified by a pooled slope index of inequality (SII) of 10.6% (95% CI, 8.1 to 13.2) and a relative index of inequality (RII) of 1.4 (95% CI, 1.3 to 1.6). By comparison, income-related disparities in breast cancer screening increased gradually over time, with a pooled SII of 5.9% (95% CI, 2.9 to 9.0) and an RII of 1.2 (95% CI, 0.9 to 1.3). These differences may partly reflect target age groups, as cervical cancer screening typically focuses on women in their 30s, who often exhibit greater socioeconomic variability, while breast cancer screening mainly targets women aged 40 and above, a group that generally has more stable socioeconomic profiles. Women in their 30s often have lower income levels compared with older age groups. Moreover, the higher proportion of single women in lower-income categories, who are less likely to participate in screening, may also contribute to these disparities [7].
When considering individual factors, education level consistently influenced screening compliance for both cancers. Notably, its effect was significant in both high-HDI and low-HDI countries. Education is a critical determinant of health literacy, which encompasses the ability to access, understand, and use health information and services for decision-making. Women with lower educational attainment face greater barriers to healthcare utilization, including cost, time, and distance. Consequently, higher levels of education are strongly associated with greater participation in cancer screening [58]. For example, in Korea, breast cancer screening showed the largest disparity by education level: among women aged over 40, the screening rate was 69.5% among those with education beyond college compared to 56.3% among those with only elementary schooling—a difference of 13.2 percentage points [59]. Similarly, participation in general health check-ups was higher among individuals with a college education compared with those with only elementary schooling (adjusted OR, 1.18) [60]. To reduce these disparities, countries should design screening strategies that address populations with lower educational attainment. This requires not only promotion and outreach initiatives but also multidimensional, tailored approaches that reflect the structure and characteristics of each healthcare system.
In breast cancer, but not in cervical cancer, family history was an important determinant of screening compliance. This difference likely reflects underlying etiology. Cervical cancer is primarily caused by infection with HPV, rather than genetic inheritance, whereas breast cancer has a well-documented hereditary component. A Lancet study reported that more than 12% of breast cancer patients had a family history of the disease [61]. BRCA1 and BRCA2 mutations are well-established genetic risk factors. Shih et al. [62] demonstrated that 42.9% of patients with multiple primary breast cancers carried either a BRCA1 or BRCA2 mutation (p<0.001). Compared with individuals without a family history, those with at least 1 first-degree relative with breast cancer had a significantly increased risk of developing the disease (hazard ratio [HR], 1.77; 95% CI, 1.58 to 1.97; p<0.001), and the risk more than doubled among those with 2 or more affected relatives (HR, 2.52; 95% CI, 1.83 to 3.47; p<0.001) [63].
In lower-HDI countries, employment status was a significant factor influencing screening compliance for both cancer types. Several explanations may account for why employed individuals are more likely to undergo cancer screening. These include access to workplace health screening programs, financial support for health check-ups, and greater awareness of the importance of screening through interactions with colleagues. Supporting evidence comes from a systematic review that found workplace-based health screening programs to be effective in improving knowledge and increasing screening uptake [64]. Similarly, a Korean study reported higher gastric cancer screening participation among full-time employees compared with non-regular workers or the self-employed. This was attributed to greater job security and more favorable working conditions among regular employees, which facilitated access to health screenings [65].
In countries offering NCSPs, household income remained a significant factor, whereas it was not in countries without such programs. Initially, it was anticipated that financial support through national programs would reduce disparities in screening access by income. However, the findings indicate that household income continues to exert an influence even in countries with national programs. This may be explained by persistent inequalities in the availability of private screening services. Indeed, participation in national screenings has been reported to be higher among lower-income groups, while higher-income individuals more frequently use private screening options [66]. Another explanation is that most of the countries with national screening programs in this study—Korea, Japan, and Singapore—belonged to HDI group 1. In this group, household income was consistently associated with screening compliance, suggesting that the inclusion of many high-HDI countries implementing NCSP contributed to the observed results.
This study has several limitations. First, the included studies presented quality concerns, as all were cross-sectional in design, which is inherently lower in strength of evidence compared with randomized controlled trials. Moreover, differences in study settings (e.g., target age groups and screening methods) and variations in reporting require caution in interpreting the synthesized findings. For breast cancer in particular, screening rates vary depending on the method used, and the factors influencing participation may therefore differ. This issue warrants further investigation in follow-up studies. Second, although the search encompassed 21 ANCCA countries, only 12 countries (10 for breast cancer screening and 12 for cervical cancer screening) were represented in the final analysis. Nonetheless, these countries spanned a broad range of HDI levels and healthcare systems, lending relevance to this study’s exploration of socioeconomic factors across the Asian region. Third, subgroup analyses were limited by small numbers of studies for certain variables. For example, within the HDI group 1 subgroup for breast cancer, only 1 or 2 studies examined factors such as region of residence and family history, making it difficult to determine their significance with confidence. Finally, this review was restricted to socioeconomic variables and did not include other potentially important determinants. Screening compliance is also shaped by knowledge, attitudes, healthcare environments, and system-level characteristics. For instance, in countries such as India and Malaysia, screening programs are either unavailable at the national level or limited to specific cancers, and there is often no consistent system for follow-up diagnosis and treatment after abnormal findings. These limitations contribute to low participation rates and large regional disparities [6]. Future research should therefore incorporate a wider range of variables, including healthcare system factors, to enable a more comprehensive analysis.
This systematic review identified socioeconomic factors influencing compliance with breast and cervical cancer screening in 12 Asian countries, based on evidence synthesized from multiple quantitative studies. For breast cancer, education level and family history were significant determinants of screening participation, while for cervical cancer, education, income level, marital status, and health insurance coverage were influential factors. However, the specific factors varied depending on HDI classification and the presence of a NCSP. To reduce disparities in screening compliance, multi-strategy approaches tailored to each country’s unique context are required. Furthermore, future studies should incorporate a broader set of determinants—including knowledge, attitudes, and healthcare system characteristics—to strengthen efforts promoting breast and cervical cancer screening across the Asian region.
Supplementary material is available at https://doi.org/10.4178/epih.e2025050.

Supplementary Material 1.

Age associations with participation in breast cancer screening
epih-47-e2025050-Supplementary-1.docx

Supplementary Material 2.

Age associations with participation in cervical cancer screening
epih-47-e2025050-Supplementary-2.docx

Supplementary Material 3.

Factors associated with participation in breast cancer screening (education level and family history)
epih-47-e2025050-Supplementary-3.docx

Supplementary Material 4.

Factors associated with participation in cervical cancer screening (education level, household income)
epih-47-e2025050-Supplementary-4.docx

Supplementary Material 5.

Factors associated with participation in cervical cancer screening (marriage status, medical insurance)
epih-47-e2025050-Supplementary-5.docx

Supplementary Material 6.

Socioeconomic factors associated with participation in breast cancer screening in HDI 1 group (Education level & Household income)
epih-47-e2025050-Supplementary-6.docx

Supplementary Material 7.

Socioeconomic factors associated with participation in breast cancer screening in HDI 2~3 group (Education level & Employment & Family history)
epih-47-e2025050-Supplementary-7.docx

Supplementary Material 8.

Socioeconomic factors associated with participation in cervical cancer screening in HDI 1 group (Education level)
epih-47-e2025050-Supplementary-8.docx

Supplementary Material 9.

Socioeconomic factors associated with participation in cervical cancer screening in HDI 2~3 group (Education level & Household income)
epih-47-e2025050-Supplementary-9.docx

Supplementary Material 10.

Socioeconomic factors associated with participation in cervical cancer screening in HDI 2~3 group (Marriage status & Employment)
epih-47-e2025050-Supplementary-10.docx

Supplementary Material 11.

Socioeconomic factors associated with participation in breast cancer screening in countries with National Screening Program (Household income)
epih-47-e2025050-Supplementary-11.docx

Supplementary Material 12.

Socioeconomic factors associated with participation in breast cancer screening in countries without National Screening Program (Education level & Employment & Region)
epih-47-e2025050-Supplementary-12.docx

Conflict of interest

The authors have no conflicts of interest to declare for this study.

Funding

This study is funded by Grant-in-Aid for Cancer Research and Control from the National Cancer Center of Korea (grant No. 24H1071-2).

Acknowledgements

None.

Author contributions

Conceptualization: Bae S, Kang YJ, Jang BH. Data curation: Bae S, Kang YJ. Formal analysis: Bae S, Kang YJ. Funding acquisition: Suh M, Lee HJ. Methodology: Bae S, Kang YJ, Jang BH, Ahn J. Project administration: Suh M, Choi KS. Writing – original draft: Bae S, Kang YJ. Writing – review & editing: Suh M, Ahn J, Jang BH, Choi KS, Lee HJ.

Figure 1.
Flow chart of the study selection process. ANCCA, Asian National Cancer Centers Alliance.
epih-47-e2025050f1.jpg
Figure 2.
21 Asian National Cancer Centers Alliance (ANCCA) countries classified into Human Development Index (HDI) level and National Breast Cancer Screening Program provision. NCSP, National Cancer Screening Program.
epih-47-e2025050f2.jpg
epih-47-e2025050f3.jpg
Table 1.
Summary of the 27 included studies about breast cancer screening participation among women in Asia
Study Country Study design Sample size (n) Age of participants (yr) Study period Screening method (BSE | CBE | Mammography) Quality score
Gang et al., 2013 [10] China Cross-sectional 406 ≥20 2011 Mammography 19
Lee et al., 2015 [11] China Cross-sectional 5,735 50-74 2007-2010 Mammography 17
Leung et al., 2012 [12] China Cross-sectional 1,533 ≥60 2006 Mammography, CBE, BSE 19
Sun et al., 2022 [13] China Cross-sectional 3,500 18-64 2018 Mammography, CBE 18
Wang et al., 2013 [14] China Cross-sectional 53,513 ≥18 2010 Any method 20
You et al., 2019 [15] China Cross-sectional 6,520 36-65 2013 Mammography, CBE 18
Grosse Frie et al., 2013 [16] India Randomized controlled trial, cross-sectional 52,011 30-69 2006 BSE 18
Kulkarni et al., 2019 [17] India Cross-sectional 14,770 30-64 2010-2014 CBE 19
Anwar et al., 2018 [18] Indonesia Cross-sectional 5,397 ≥40 2014-2015 BSE 18
Ahmadipour et al., 2016 [19] Iran Cross-sectional 240 18-64 2015 BSE, CBE, mammography 17
Allahverdipour et al., 2011 [20] Iran Cross-sectional 414 ≥40 2007 Mammography 18
Aminisani et al., 2016 [21] Iran Cross-sectional 561 ≥40 2014 Mammography 19
Ghanbari et al., 2020 [22] Iran Cross-sectional 1,472 15-45 2017 BSE, CBE, mammography 17
Samah et al., 2012 [23] Iran Cross-sectional 400 35-69 2009 Mammography 17
Okui, 2021 [24] Japan Cross-sectional 6,031 40-69 2010, 2013 Mammography 18
2010: 2,817
2013: 3,214
Tsunematsu et al., 2013 [25] Japan Cross-sectional 3,200 20-69 2012 Mammography 18
Yusof et al., 2014 [26] Malaysia Cross-sectional 206 40-74 2011 Mammography 18
Yerramilli et al., 2015 [27] Mongolia Cross-sectional 1,193 ≥30 2010 BSE 19
Teo et al., 2013 [28] Singapore Cross-sectional 208 40-75 2011 Mammography 18
Wee et al., 2012 [29] Singapore Cross-sectional 1,383 ≥40 2009-2011 Mammography 18
Hahm et al., 2011 [30] Korea Cross-sectional 777 ≥40 2007 Mammography or ultrasonography 17
Lee et al., 2010 [31] Korea Cross-sectional 2,609 ≥40 2005 Mammography or ultrasonography 17
Lee et al., 2010 [32] Korea Cross-sectional 2,583 ≥40 2005 Mammography or ultrasonography 18
Nari et al., 2023 [33] Korea Cross-sectional 4,042,332 ≥40 2018 Mammography 17
Oh et al., 2011 [34] Korea Cross-sectional 2,511,976 ≥40 2005-2008 Mammography 19
Son et al., 2017 [35] Korea Cross-sectional 1,193 ≥40 2012 Mammography 20
Mukem et al., 2014 [36] Thailand Cross-sectional 18,474 ≥20 2007 BSE, CBE, mammography 17

BSE, breast self-exam; CBE, clinical breast exam.

Table 2.
Summary of the 29 included studies about cervical cancer screening participation among women in Asia
Study Country Study design Sample size (n) Age of participants Study period Screening method (Pap smear test | Pelvic examination | HPV test) Quality score
Baussano et al., 2014 [37] Bhutan Cross-sectional 1,620 ≥25 2011-2012 HPV test, Pap smear test 19
Gu et al., 2010 [38] China Cross-sectional 167 25-50 2007 Specific method N/R 17
Lee et al., 2015 [11] China Cross-sectional 5,823 25-69 2007-2010 Pelvic examination, Pap smear test, mammography 17
Lin et al., 2021 [39] China Cross-sectional 8,639 30-60 2015 HPV test 19
Lin et al., 2021 [40] China Cross-sectional 12,017 21-60 2011 Specific method N/R 20
2011: 9,155 2014
2014: 2,862
Liu et al., 2017 [41] China Cross-sectional 405 30-65 2015 Specific method N/R 17
Sun et al., 2022 [13] China Cross-sectional 3,500 18-64 2018 Specific method N/R 18
You et al., 2019 [15] China Cross-sectional 6,520 36-65 2013 Specific method N/R 18
Zhang et al., 2023 [42] China Cross-sectional 4,518 18-65 2022 Pap smear, HPV test, colposcopy 18
Anwar et al., 2018 [18] Indonesia Cross-sectional 1,058 ≥40 2014-2015 Pap smear test 18
Kulkarni et al., 2022 [43] India Cross-sectional 21,422 30-65 2007-2012 Specific method N/R 17
Ahmadipour et al., 2016 [19] Iran Cross-sectional 240 18-64 2015 Pap smear test pelvic examination 17
Amin et al., 2020 [44] Iran Cross-sectional 15,975 ≥18 2016 Pap smear test 20
Aminisani et al., 2016 [45] Iran Cross-sectional 561 ≥40 2014 Pap smear test 17
Mosayebi et al., 2018 [46] Iran Cross-sectional 77 27-85 2014-2016 Pap smear test 20
Cui et al., 2022 [47] Japan Cross-sectional 816 20-39 2018 Any method 17
Al-Oseely et al., 2023 [48] Malaysia Cross-sectional 355 20-65 N/S Pap smear test 17
Siraj et al., 2019 [49] Malaysia Cross-sectional 300 ≥17 N/S Pap smear test 18
Yunus et al., 2018 [50] Malaysia Cross-sectional 316 20-65 2013 Pap smear test 19
Yerramilli et al., 2015 [27] Mongolia Cross-sectional 1,193 ≥30 2010 Pap smear test 19
Ranabhat et al., 2014 [51] Nepal Cross-sectional 607 ≥18 2013 Pap smear test 18
Wee et al., 2012 [29] Singapore Cross-sectional 438 ≥40 2009-2011 Pap smear test 18
Chang et al., 2017 [52] Korea Cross-sectional 3,734 15-39 2010-2012 Pap smear test 20
Chang et al., 2018 [53] Korea Cross-sectional 15,935 ≥30 2014-2015 Pap smear test 18
Lee et al., 2010 [31] Korea Cross-sectional 3,413 ≥30 2005 Pap smear test 17
Lee et al., 2013 [54] Korea Cross-sectional 17,105 ≥30 1998–2010 Pap smear test 20
Shin, et al., 2022 [55] Korea Cross-sectional 3,925 20-39 2017-2020 Pap smear test 18
Visanuyothin et al., 2015 [56] Thailand Cross-sectional 595 30-60 2012 Pap smear test 17
Wongwatcharanukul et al., 2014 [57] Thailand Cross-sectional 547 30-60 2012 Pap smear test 18

N/R, not recorded; N/S, not specified; Pap, Papanicolaou; HPV, human papillomavirus

Table 3.
Socioeconomic factors and associations (or non-associations) with participation in breast or cervical cancer screening
Socioeconomic factors Breast cancer screening
 Cervical cancer screening
Studies displaying a positive association (p<0.05) Studies displaying a negative association (p<0.05) Studies displaying no association (p≥0.05) Studies displaying a positive association (p<0.05) Studies displaying a negative association (p<0.05) Studies displaying no association (p≥0.05)
Higher education1,2 [10-12,14-19,23,24,27,28,32,36] - [13,20-22,26,29,30,35] [11,15,18,19,27,29,38-41,43-46,49,52,54,57] - [13,42,50,56]
Higher household income2 [11,15,24,28,29,30,35,36] - [13,16-19,23,26,31,32] [11,15,18,19,31,39,40,42,52-54] - [13,29,41,48,50,56]
Being employed [13,14,16,17,22-24] - [10,15,19,20,25,27,29,30,35] [13,19,27,29,37,40,42,49,53] [56] [15,38,43,47,48,50,52,54]
Being married2 [13,16,17,24,25,36] [12,14] [11,15,18,20,21,23,26,30,32] [13,37,38,40,42,44,47,55,56] [49] [11,15,18,39,41,48,50]
Urban residence [11,18] [27,30] [14,20,32] [11] [53] [18,42,44,51]
Medical insurance2 [18,22,23,32,36] [20] [11,13,26,34,35] [18,40,45,48] [11,13]
Family history1 [16,20,22,25] [21,23,28] [43] [56]

1 Factors displaying positive association with breast cancer screening.

2 Factors displaying positive association with cervical cancer screening.

Table 4.
Factors affecting cancer screening participation rate by HDI classification and NCSP provision classification
Classifications Factors Applicable countries List of studies
HDI classification
 Breast cancer screening
  1 (very high) Education level Singapore, Korea, Thailand [24,28,32,36]
Household income Singapore, Korea, Thailand, Japan [24,28-30,35,36]
  2-4 (high, moderate, low) Education level Iran, Indonesia, China, India, Mongolia [10-12,14-19,23,27]
Employment India, Iran, China [13,14,16,17,22,23]
Family history Iran, India [16,20,22]
 Cervical cancer screening
  1 (very high) Education level Korea, Malaysia, Singapore, Thailand [29,49,52,54,57]
  2-4 (high, moderate, low) Education level Iran, Indonesia, China, India, Mongolia [11,15,18,19,27,38-41,43-46]
Household income Iran, Indonesia, China [11,15,18,19,39,40,42]
Employment Iran, China, Mongolia, Bhutan [13,19,27,37,40,42]
Marriage status Iran, China, Bhutan [13,37,38,40,42,44]
NCSP provision classification
 Breast cancer screening
  National Program
   Provided Household income Singapore, Korea, Japan [24,28-30,35]
   Not provided Education level Indonesia, India, China, Thailand, China [10-12,14-18,36]
Employment India, China, [13,14,16,17]
Region Indonesia, China [11,18]

HDI, Human Development Index; NCSP, National Cancer Screening Program.

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      Socioeconomic factors affecting breast and cervical cancer screening compliance in Asian National Cancer Centers Alliance countries: a systematic review
      Image Image Image
      Figure 1. Flow chart of the study selection process. ANCCA, Asian National Cancer Centers Alliance.
      Figure 2. 21 Asian National Cancer Centers Alliance (ANCCA) countries classified into Human Development Index (HDI) level and National Breast Cancer Screening Program provision. NCSP, National Cancer Screening Program.
      Graphical abstract

      Figure 1.

      Figure 2.

      Graphical abstract

      Socioeconomic factors affecting breast and cervical cancer screening compliance in Asian National Cancer Centers Alliance countries: a systematic review
      Study Country Study design Sample size (n) Age of participants (yr) Study period Screening method (BSE | CBE | Mammography) Quality score
      Gang et al., 2013 [10] China Cross-sectional 406 ≥20 2011 Mammography 19
      Lee et al., 2015 [11] China Cross-sectional 5,735 50-74 2007-2010 Mammography 17
      Leung et al., 2012 [12] China Cross-sectional 1,533 ≥60 2006 Mammography, CBE, BSE 19
      Sun et al., 2022 [13] China Cross-sectional 3,500 18-64 2018 Mammography, CBE 18
      Wang et al., 2013 [14] China Cross-sectional 53,513 ≥18 2010 Any method 20
      You et al., 2019 [15] China Cross-sectional 6,520 36-65 2013 Mammography, CBE 18
      Grosse Frie et al., 2013 [16] India Randomized controlled trial, cross-sectional 52,011 30-69 2006 BSE 18
      Kulkarni et al., 2019 [17] India Cross-sectional 14,770 30-64 2010-2014 CBE 19
      Anwar et al., 2018 [18] Indonesia Cross-sectional 5,397 ≥40 2014-2015 BSE 18
      Ahmadipour et al., 2016 [19] Iran Cross-sectional 240 18-64 2015 BSE, CBE, mammography 17
      Allahverdipour et al., 2011 [20] Iran Cross-sectional 414 ≥40 2007 Mammography 18
      Aminisani et al., 2016 [21] Iran Cross-sectional 561 ≥40 2014 Mammography 19
      Ghanbari et al., 2020 [22] Iran Cross-sectional 1,472 15-45 2017 BSE, CBE, mammography 17
      Samah et al., 2012 [23] Iran Cross-sectional 400 35-69 2009 Mammography 17
      Okui, 2021 [24] Japan Cross-sectional 6,031 40-69 2010, 2013 Mammography 18
      2010: 2,817
      2013: 3,214
      Tsunematsu et al., 2013 [25] Japan Cross-sectional 3,200 20-69 2012 Mammography 18
      Yusof et al., 2014 [26] Malaysia Cross-sectional 206 40-74 2011 Mammography 18
      Yerramilli et al., 2015 [27] Mongolia Cross-sectional 1,193 ≥30 2010 BSE 19
      Teo et al., 2013 [28] Singapore Cross-sectional 208 40-75 2011 Mammography 18
      Wee et al., 2012 [29] Singapore Cross-sectional 1,383 ≥40 2009-2011 Mammography 18
      Hahm et al., 2011 [30] Korea Cross-sectional 777 ≥40 2007 Mammography or ultrasonography 17
      Lee et al., 2010 [31] Korea Cross-sectional 2,609 ≥40 2005 Mammography or ultrasonography 17
      Lee et al., 2010 [32] Korea Cross-sectional 2,583 ≥40 2005 Mammography or ultrasonography 18
      Nari et al., 2023 [33] Korea Cross-sectional 4,042,332 ≥40 2018 Mammography 17
      Oh et al., 2011 [34] Korea Cross-sectional 2,511,976 ≥40 2005-2008 Mammography 19
      Son et al., 2017 [35] Korea Cross-sectional 1,193 ≥40 2012 Mammography 20
      Mukem et al., 2014 [36] Thailand Cross-sectional 18,474 ≥20 2007 BSE, CBE, mammography 17
      Study Country Study design Sample size (n) Age of participants Study period Screening method (Pap smear test | Pelvic examination | HPV test) Quality score
      Baussano et al., 2014 [37] Bhutan Cross-sectional 1,620 ≥25 2011-2012 HPV test, Pap smear test 19
      Gu et al., 2010 [38] China Cross-sectional 167 25-50 2007 Specific method N/R 17
      Lee et al., 2015 [11] China Cross-sectional 5,823 25-69 2007-2010 Pelvic examination, Pap smear test, mammography 17
      Lin et al., 2021 [39] China Cross-sectional 8,639 30-60 2015 HPV test 19
      Lin et al., 2021 [40] China Cross-sectional 12,017 21-60 2011 Specific method N/R 20
      2011: 9,155 2014
      2014: 2,862
      Liu et al., 2017 [41] China Cross-sectional 405 30-65 2015 Specific method N/R 17
      Sun et al., 2022 [13] China Cross-sectional 3,500 18-64 2018 Specific method N/R 18
      You et al., 2019 [15] China Cross-sectional 6,520 36-65 2013 Specific method N/R 18
      Zhang et al., 2023 [42] China Cross-sectional 4,518 18-65 2022 Pap smear, HPV test, colposcopy 18
      Anwar et al., 2018 [18] Indonesia Cross-sectional 1,058 ≥40 2014-2015 Pap smear test 18
      Kulkarni et al., 2022 [43] India Cross-sectional 21,422 30-65 2007-2012 Specific method N/R 17
      Ahmadipour et al., 2016 [19] Iran Cross-sectional 240 18-64 2015 Pap smear test pelvic examination 17
      Amin et al., 2020 [44] Iran Cross-sectional 15,975 ≥18 2016 Pap smear test 20
      Aminisani et al., 2016 [45] Iran Cross-sectional 561 ≥40 2014 Pap smear test 17
      Mosayebi et al., 2018 [46] Iran Cross-sectional 77 27-85 2014-2016 Pap smear test 20
      Cui et al., 2022 [47] Japan Cross-sectional 816 20-39 2018 Any method 17
      Al-Oseely et al., 2023 [48] Malaysia Cross-sectional 355 20-65 N/S Pap smear test 17
      Siraj et al., 2019 [49] Malaysia Cross-sectional 300 ≥17 N/S Pap smear test 18
      Yunus et al., 2018 [50] Malaysia Cross-sectional 316 20-65 2013 Pap smear test 19
      Yerramilli et al., 2015 [27] Mongolia Cross-sectional 1,193 ≥30 2010 Pap smear test 19
      Ranabhat et al., 2014 [51] Nepal Cross-sectional 607 ≥18 2013 Pap smear test 18
      Wee et al., 2012 [29] Singapore Cross-sectional 438 ≥40 2009-2011 Pap smear test 18
      Chang et al., 2017 [52] Korea Cross-sectional 3,734 15-39 2010-2012 Pap smear test 20
      Chang et al., 2018 [53] Korea Cross-sectional 15,935 ≥30 2014-2015 Pap smear test 18
      Lee et al., 2010 [31] Korea Cross-sectional 3,413 ≥30 2005 Pap smear test 17
      Lee et al., 2013 [54] Korea Cross-sectional 17,105 ≥30 1998–2010 Pap smear test 20
      Shin, et al., 2022 [55] Korea Cross-sectional 3,925 20-39 2017-2020 Pap smear test 18
      Visanuyothin et al., 2015 [56] Thailand Cross-sectional 595 30-60 2012 Pap smear test 17
      Wongwatcharanukul et al., 2014 [57] Thailand Cross-sectional 547 30-60 2012 Pap smear test 18
      Socioeconomic factors Breast cancer screening
      		 Cervical cancer screening
      Studies displaying a positive association (p<0.05) Studies displaying a negative association (p<0.05) Studies displaying no association (p≥0.05) Studies displaying a positive association (p<0.05) Studies displaying a negative association (p<0.05) Studies displaying no association (p≥0.05)
      Higher education1,2 [10-12,14-19,23,24,27,28,32,36] - [13,20-22,26,29,30,35] [11,15,18,19,27,29,38-41,43-46,49,52,54,57] - [13,42,50,56]
      Higher household income2 [11,15,24,28,29,30,35,36] - [13,16-19,23,26,31,32] [11,15,18,19,31,39,40,42,52-54] - [13,29,41,48,50,56]
      Being employed [13,14,16,17,22-24] - [10,15,19,20,25,27,29,30,35] [13,19,27,29,37,40,42,49,53] [56] [15,38,43,47,48,50,52,54]
      Being married2 [13,16,17,24,25,36] [12,14] [11,15,18,20,21,23,26,30,32] [13,37,38,40,42,44,47,55,56] [49] [11,15,18,39,41,48,50]
      Urban residence [11,18] [27,30] [14,20,32] [11] [53] [18,42,44,51]
      Medical insurance2 [18,22,23,32,36] [20] [11,13,26,34,35] [18,40,45,48] [11,13]
      Family history1 [16,20,22,25] [21,23,28] [43] [56]
      Classifications Factors Applicable countries List of studies
      HDI classification
       Breast cancer screening
        1 (very high) Education level Singapore, Korea, Thailand [24,28,32,36]
      Household income Singapore, Korea, Thailand, Japan [24,28-30,35,36]
        2-4 (high, moderate, low) Education level Iran, Indonesia, China, India, Mongolia [10-12,14-19,23,27]
      Employment India, Iran, China [13,14,16,17,22,23]
      Family history Iran, India [16,20,22]
       Cervical cancer screening
        1 (very high) Education level Korea, Malaysia, Singapore, Thailand [29,49,52,54,57]
        2-4 (high, moderate, low) Education level Iran, Indonesia, China, India, Mongolia [11,15,18,19,27,38-41,43-46]
      Household income Iran, Indonesia, China [11,15,18,19,39,40,42]
      Employment Iran, China, Mongolia, Bhutan [13,19,27,37,40,42]
      Marriage status Iran, China, Bhutan [13,37,38,40,42,44]
      NCSP provision classification
       Breast cancer screening
        National Program
         Provided Household income Singapore, Korea, Japan [24,28-30,35]
         Not provided Education level Indonesia, India, China, Thailand, China [10-12,14-18,36]
      Employment India, China, [13,14,16,17]
      Region Indonesia, China [11,18]
      Table 1. Summary of the 27 included studies about breast cancer screening participation among women in Asia

      BSE, breast self-exam; CBE, clinical breast exam.

      Table 2. Summary of the 29 included studies about cervical cancer screening participation among women in Asia

      N/R, not recorded; N/S, not specified; Pap, Papanicolaou; HPV, human papillomavirus

      Table 3. Socioeconomic factors and associations (or non-associations) with participation in breast or cervical cancer screening

      Factors displaying positive association with breast cancer screening.

      Factors displaying positive association with cervical cancer screening.

      Table 4. Factors affecting cancer screening participation rate by HDI classification and NCSP provision classification

      HDI, Human Development Index; NCSP, National Cancer Screening Program.

      Table 1.

      Table 2.

      Table 3.

      Table 4.

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