Ethnic inequalities in the access of cancer screening services for women´s in Peru

Ethnic inequalities in the access of cancer screening services for women´s in Peru | 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 Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Ethnic inequalities in the access of cancer screening services for women´s in Peru Claudio Intimayta-Escalante This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4078937/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 24 Jul, 2024 Read the published version in BMC Women's Health → Version 1 posted 20 You are reading this latest preprint version Abstract Background Despite guidelines and increased healthcare resources, there are disparities in coverage of screening cancer services for non-white communities, addressing these health inequalities is crucial in multicultural countries like Peru. For this reason, the aim was evaluating ethnic inequalities in the women proportion that use cancer screening services in Peruvians regions. Methods An ecological was used to assess the ethnic inequalities in the proportion of women use of general cancer screening, clinical breast examination, mammography, and pap test in the 25 regions of Peru. The inequalities were approach by estimating the GINI coefficient among ethnic groups based on various sociodemographic characteristics, and the annual variation of the GINI coefficient. Results In Peruvians regions there is greater inequality in general cancer screening services among the indigenous (GINI: 0.321) and afroperuvians (GINI: 0.415), which have a GINI coefficient almost twice that of the white or mestizo group (GINI: 0.183). Also, sociodemographic characteristics such as low educational level, low income, living in rural areas, being over 64 years old, and lack of health insurance mediate these inequalities in the use of cancer screening services. In the temporal variation, an increase in inequality was identified to afroperuvians and indigenous groups after 2020. Conclusion In Peruvian regions there are marked ethnic inequalities in use of cancer screening services for indigenous and afroperuvians groups compared to the white or mestizo group, especially in those regions with larger populations with adverse socioeconomic conditions that have worsened for these ethnic groups after the COVID-19 pandemic in Peru. Early Detection of Cancer Sociodemographic Factors Health Inequities Ethnicity Peru Figures Figure 1 Figure 2 BACKGROUND Breast and cervical cancer are the two most prevalent forms of cancer affecting women worldwide ( 1 , 2 ). In high-income countries, early access to screening tests and prompt treatment has resulted in a decrease in mortality from these cancers ( 3 ). However, in lower-middle-income countries like Peru, breast cancer remains one of the top causes of death among women ( 4 ). Currently many organizations recommend that women undergo a clinical breast examination at age 21, a Papanicolaou test at age 30, and a mammogram at age 50 ( 5 , 6 ). However, despite guidelines for cancer screening and increased healthcare resources, there are persistent disparities in coverage to secondary prevention services for non-white communities ( 7 – 9 ). This results in higher cancer mortality rates among non-white ethnic groups ( 9 – 11 ). Inequalities in coverage to healthcare screening services can be modified by socioeconomic factors (income, education, and age), as well as personal factors (health conditions, fears, preferences, and religion), and geographical factors (location of residence or distance to health centers) ( 12 – 15 ). Addressing these health inequalities is a critical issue in multicultural countries like Peru ( 16 ). For this reason, the aim of the study was to assess ethnic inequalities in the use of a cancer screening services for women across different regions in Peru. METHODS Study Design An ecological study was conducted to analyze the use of a cancer screening services in the 25 regions in Peru over the five-year period from 2017 to 2021. The indicator evaluated in each region was the proportion of women over 18 years of age who use cancer screening services in the departments of Peru surveyed by the Demographic and Family Health Survey (ENDES in Spanish). Definition of Outcomes The assessment of cancer screening in the ENDES is performed with specific questions for evaluated if Peruvians women had a general screening for any type of cancer (Did you have a general check-up or screening for any cancer?) in those with 18 years old or more, clinical breast examination (Have you ever had a clinical breast exam performed by a physician or other health professional?) in those with 18 years old or more, Papanicolaou smear test (Have you ever had a Pap smear test performed by a physician or other health professional?) in those between 18 and 64 years old, or mammography test (Have you ever had a mammogram performed by a physician/health professional?) in those with 30 years old or more. Sociodemographic Conditions We also examined how sociodemographic characteristics affected cancer screening coverage for women. These characteristics included age group (18 to 30, 31 to 49, 50 to 64, and 65 years old or more), educational level (without education, primary, high school, or higher education), wealth index (ranging from the wealthiest first quintile to the least wealthy fifth quintile), area of residence (urban or rural), health insurance status (have or don't have), residence area (urban or rural), health insurance (no or yes), and ethnic groups in Peru (white or mestizo, indigenous including Quechua or Aymara, Afro-Peruvian, or other). Statistical analysis The data analysis was performed using Stata v.17.0. The analysis of inequalities related to the proportion of women use of cancer screening services was based on their ethnic group. This was achieved by estimating the GINI Coefficient, which measures inequality in the distribution of a specific population as a percentage. This approach allowed for the observation of how only a portion of the evaluated population has use to a resource or service compared to another group. A GINI Coefficient of 0 represents no inequality, while a score of 1 indicates absolute inequality. The comparison on the distribution of cancer screening services among women and specific ethnic groups was graph on Lorenz curves. Also was compared the median (Me) and interquartile range (IQR) of the percentage of women use of cancer screening services for each ethnic group using quartiles and Kruskal-Wallis test´s. Additionally, we conducted a stratified analysis of sociodemographic characteristics (age group, education level, wealth index, area of residence, and health insurance) among all surveyed women and specific ethnic groups using equiplots. The analysis also assessed the annual change in the GINI Coefficient for each ethnic group over the period from 2017 to 2021. Ethical aspects A request for ethical committee evaluation was not necessary as the data collection process for ENDES was carried out with the informed consent of participants. Furthermore, the data obtained from the National Institute of Statistics and Informatics (INEI) platform does not contain personally identifiable information and is secure ( http://iinei.inei.gob.pe/microdatos/ ). RESULTS The analysis of the 25 regions in Peru over a five-year period revealed that women who identify as white or mestizo have less inequality for use to cancer screening services compared to women who identify as indigenous or afroperuvians (Table 1). The GINI coefficient and Lorenz curves indicate that use to cancer screening services among all women surveyed in the Peruvian regions is like use among white or mestizo women. However, use of cancer screening services is more unequal among indigenous and afroperuvians (Fig. 1 ). The evaluation of the screening services revealed greater ethnic inequality in use to mammograms, while the Papanicolaou test had the least inequality (Fig. 1 ). The equiplots showed that the most important sociodemographic factors related to inequalities in cancer screening coverage in Peruvians regions were lack of education, being 65 years or older, and having no health insurance or being in the lowest wealth quintile (Fig. 2 A). Lack of education, being between 18 and 30 years old or 65 years or older, being in the lowest wealth quintile, and living in a rural area were the key factors for inequalities in clinical breast examination (Fig. 2 B). Lack of education, being in the lowest wealth quintile, and living in a rural area were the key factors for inequalities in mammography screening (Fig. 2 C). Meanwhile, lack of education, having no health insurance, and being in the lowest wealth quintile were the key factors for inequalities in the Papanicolaou test (Fig. 2 D). The annual variation of the GINI coefficient in the Peruvian regions showed that inequalities in cancer screening were greater in the afroperuvians and indigenous groups, especially in 2021. Also, inequalities in clinical breast examination were higher for afroperuvians after 2020, while they decreased for indigenous and white or mestizo groups. The greatest annual variation in the GINI index was observed in mammography screening, particularly for the afroperuvians and indigenous groups. The lowest annual variation in the GINI coefficient was observed in the Papanicolaou test, except for the indigenous group (Table 2 ). DISCUSSION The study aimed to evaluate ethnic inequalities in the proportion of women use of cancer screening services in Peruvians regions. It was found that the indigenous and afroperuvians ethnic groups faced greater inequalities compared to the white or mestizo group. The study suggests that language and cultural barriers may prevent indigenous groups (quechua or aymara women) from use to these services ( 16 ). Meanwhile, afroperuvians could experience discrimination and racism that hinder their access to healthcare ( 17 , 18 ). This exclusion can also lead to difficulties in obtaining adequate treatment, resulting in worse disease outcomes ( 9 ). Additionally, sociodemographic factors such as education, age, and wealth index also play a role in use of cancer screening services. Education, in particular, is a modifiable condition that can be targeted by public policies to improve coverage ( 19 ). On the other hand, wealth inequality shows that lower income is a major barrier to accessing these services ( 20 , 21 ). However, the unequal distribution of resources and healthcare personnel in Peru's regions also impedes use of cancer screening ( 22 ). Targeting cancer screening to specific age groups may be cost-effective, but it may also limit use for older populations with higher morbidity rates ( 23 , 24 ). The study observed that ethnic inequalities in using cancer screening services were decreasing until 2020, but the COVID-19 pandemic led to a reduction in public policies aimed at closing the gap ( 25 , 26 ). This resulted in a sharp increase in inequalities among afroperuvians and indigenous groups, while the white or mestizo group showed a reduction in inequalities ( 27 ). Living in rural areas and being farther away from the capital (Lima) also exacerbates disparities in use of these services, particularly for non-white ethnic groups ( 27 – 29 ). Periodic monitoring with screening tests presents an opportunity to address these disparities, especially for non-white ethnic groups ( 30 – 33 ). However, there is evidence of greater inequalities in mammogram performance among ethnic groups in Peru, which may be due to centralization of healthcare resources ( 34 ). Other factors such as discomfort with cancer screening procedures or fear of the disease can also reduce the proportion of women using these services ( 35 , 36 ). The study provides an approximation of ethnic inequalities in use to health screening services for cancer. However, the ecological approach does not allow extrapolating the findings to an individual level. In addition, some ethnic groups may be underrepresented in the DHS. And although respondents were over 18 years of age, many were not in the target age group for some screening tests. Additionally, in the COVID-19 pandemic, many women from non-white ethnic groups may have experienced more difficulties in use of health services ( 37 ). CONCLUSIONS In conclusion, in Peruvians regions there are ethnic inequalities in the use of cancer screening services for women. Indigenous and afroperuvians ethnic groups face a greater inequality in comparison to the white or mestizo group. This inequality is particularly pronounced in regions with a higher concentration of women facing adverse socioeconomic conditions, and it has exacerbated in non-white ethnic groups after the COVID-19 pandemic in Peru. Declarations Ethics approval and consent to participate A request for ethical committee evaluation was not necessary as the data collection process for Demographic Health Survey in Peru was carried out with the informed consent of participants. Furthermore, the data obtained from the National Institute of Statistics and Informatics platform does not contain personally identifiable information and is secure to be used (http://iinei.inei.gob.pe/microdatos/). Consent for publication Not applicable Available of data and materials The dataset supporting the conclusions of this article is available in the INEI repository: https://proyectos.inei.gob.pe/microdatos/ Competing interests The authors declare that they have no competing interests Funding The study was self-funded Authors' contributions: CIE participated in the conception and design of the study, the data management and data analysis. All authors participated in the interpretation of the results, the writing and review of manuscript. Finally, all authors of this research approved the final version of the manuscript. Acknowledgements: Not applicable References Bray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2018;68(6):394–424. Ferlay J, Colombet M, Soerjomataram I, Mathers C, Parkin DM, Piñeros M, Znaor A, Bray F. Estimating the global cancer incidence and mortality in 2018: GLOBOCAN sources and methods. Int J Cancer. 2019;144(8):1941–53. Shah SC, Kayamba V, Peek RM Jr, Heimburger D. Cancer Control in Low- and Middle-Income Countries: Is It Time to Consider Screening? J Glob Oncol. 2019;5:1–8. Global Burden of Disease Cancer Collaboration, Fitzmaurice C, Akinyemiju TF, et al. Global, Regional, and National Cancer Incidence, Mortality, Years of Life Lost, Years Lived With Disability, and Disability-Adjusted Life-Years for 29 Cancer Groups, 1990 to 2016: A Systematic Analysis for the Global Burden of Disease Study. JAMA Oncol. 2018;4(11):1553–68. Kitchen FL, Cox CM. Papanicolaou Smear. [Updated 2022 Oct 17]. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2022 Jan-. Available from: https://www.ncbi.nlm.nih.gov/books/NBK470165/ . Ren W, Chen M, Qiao Y, Zhao F. Global guidelines for breast cancer screening: A systematic review. Breast. 2022;64:85–99. Martins T, Abel G, Ukoumunne OC, Mounce LTA, Price S, Lyratzopoulos G, et al. Ethnic inequalities in routes to diagnosis of cancer: a population-based UK cohort study. Br J Cancer. 2022;127(5):863–71. Ferreira CS, Rodrigues J, Moreira S, Ribeiro F, Longatto-Filho A. Breast cancer screening adherence rates and barriers of implementation in ethnic, cultural and religious minorities: A systematic review. Mol Clin Oncol. 2021;15(1):139. Seneviratne S, Campbell I, Scott N, Shirley R, Lawrenson R. Impact of mammographic screening on ethnic and socioeconomic inequities in breast cancer stage at diagnosis and survival in New Zealand: a cohort study. BMC Public Health. 2015;15:46. Whitaker KD, Wang X, Ascha M, Showalter TN, Lewin HG, Calip GS, et al. Racial inequities in second-line treatment and overall survival among patients with metastatic breast cancer. Breast Cancer Res Treat. 2022;196(1):163–73. Marcelino AC, Gozzi B, Cardoso-Filho C, Machado H, Zeferino LC, Vale DB. Race disparities in mortality by breast cancer from 2000 to 2017 in Sao Paulo, Brazil: a population-based retrospective study. BMC Cancer. 2021;21(1):998. Musselwhite LW, Oliveira CM, Kwaramba T, de Paula Pantano N, Smith JS, Fregnani JH, et al. Racial/Ethnic Disparities in Cervical Cancer Screening and Outcomes. Acta Cytol. 2016;60(6):518–26. Krieger N, Singh N, Waterman PD. Metrics for monitoring cancer inequities: residential segregation, the Index of Concentration at the Extremes (ICE), and breast cancer estrogen receptor status (USA, 1992–2012). Cancer Causes Control. 2016;27(9):1139–51. Onega T, Hubbard R, Hill D, Lee CI, Haas JS, Carlos HA, et al. Geographic access to breast imaging for US women. J Am Coll Radiol. 2014;11(9):874–82. Harper S, Lynch J, Meersman SC, Breen N, Davis WW, Reichman MC. Trends in area-socioeconomic and race-ethnic disparities in breast cancer incidence, stage at diagnosis, screening, mortality, and survival among women ages 50 years and over (1987–2005). Cancer Epidemiol Biomarkers Prev. 2009;18(1):121–31. Salaverry O. Interculturalidad en Salud. Simposio: Interculturalidad en Salud. Rev Peru Med Exp Salud Publica. 2010;27(1):80–93. Wells KRR. Health disparities in receipt of screening mammography in Latinas: a critical review of recent literature. Cancer Control. 2007;14(4):369–79. Agenor M, Krieger N, Austin SB, Haneuse S, Gottlieb BR. At the intersection of sexual orientation, race/ethnicity, and cervical cancer screening: assessing Pap test use disparities by sex of sexual partners among black, Latina, and white U.S. women. Soc Sci Med. 2014;116:110–8. Zajacova A, Lawrence EM. The Relationship Between Education and Health: Reducing Disparities Through a Contextual Approach. Annu Rev Public Health. 2018;39:273–89. MINSA. Plan Nacional de Prevención y Control de Cáncer de Cuello Uterino 2017–2021 (R.M. Nº 440–2017/MINSA). Dirección General de Intervenciones Estratégicas en Salud Pública / Dirección de Prevención y Control de Cáncer – Lima. 2017. http://bvs.minsa.gob.pe/local/MINSA/4232.pdf . [Accessed 4 January 2023.]. MINSA. Plan Nacional de Prevención y Control de Cáncer de Mama en el Perú 2017–2021 (R.M. Nº 442–2017/MINSA). Dirección General de Intervenciones Estratégicas en Salud Pública / Dirección de Prevención y Control de Cáncer – Lima. 2017. http://bvs.minsa.gob.pe/local/MINSA/4234.pdf . [Accessed 4 January 2023.]. Thoumi A, Bond SJ, Dotson ME, et al. Policy Considerations to Promote Equitable Cervical Cancer Screening and Treatment in Peru. Ann Glob Health. 2021;87(1):116. Sazlina SG. Health screening for older people-what are the current recommendations? Malays Fam Physician. 2015;10(1):2–10. Du B, Mu Y. The Relationship Between Health Changes and Community Health Screening Participation Among Older People. Front Public Health. 2022;10:870157. Cancino RS, Su Z, Mesa R, et al. The Impact of COVID-19 on Cancer Screening: Challenges and Opportunities. JMIR Cancer. 2020;6(2):e21697. Luu T. Reduced Cancer Screening Due to Lockdowns of the COVID-19 Pandemic: Reviewing Impacts and Ways to Counteract the Impacts. Front Oncol. 2022;12:955377. Collins J, Bowie D, Shannon G et al. A descriptive analysis of health practices, barriers to healthcare and the unmet need for cervical cancer screening in the Lower Napo River region of the Peruvian Amazon. Women´s Health. 2019;15. Downey L. Spatial Measurement, Geography, and Urban Racial Inequality. Soc Forces. 2003;81(3):937–52. Disponible en:. https://www.jstor.org/stable/3598181 . Lymperopoulou K, Finney N. Socio-spatial factors associated with ethnic inequalities in districts of England and Wales, 2001–2011. Urban Stud. 2016;54(11):2540–60. Glanz K, Resch N, Lerman C, Rimer BK. Black-White differences in factors influencing mammography use among employed female health maintenance organization members. Ethn Health. 1996;1(3):207–20. Schwartz C, Chukwudozie IB, Tejeda S, Vijayasiri G, Abraham I, Remo M, et al. Association of Population Screening for Breast Cancer Risk With Use of Mammography Among Women in Medically Underserved Racial and Ethnic Minority Groups. JAMA Netw Open. 2021;4(9):e2123751. Edwards QT, Li AX, Pike MC, Kolonel LN, Ursin G, Henderson BE, et al. Ethnic differences in the use of regular mammography: the multiethnic cohort. Breast Cancer Res Treat. 2009;115(1):163–70. Sabatino SCR, Uhler R, Breen N, Tangka F, Shaw K. Disparities in mammography use among US women aged 40–64 years, by race, ethnicity, income, and health insurance status, 1993 and 2005. Med Care. 2008;46(7):692–700. Unger-Saldaña K, Cedano Guadiamos M, Burga Vega A et al. Delays to diagnosis and barriers to care for breast cancer in Mexico and Peru: a cross sectional study. Lancet Global Health. 2020. 8(Supp. 1). S16. Ashkar LK, Zaki YH. Female patients' perception of pain caused by mammography in the Western Region of Saudi Arabia. Saudi Med J. 2017;38(7):768–71. Ludman EJ, Ichikawa LE, Simon GE, Rohde P, Arterburn D, Operskalski BH, Linde JA, Jeffery RW. Breast and cervical cancer screening specific effects of depression and obesity. Am J Prev Med. 2010;38(3):303–10. Monsivais P, Amiri S, Robison J, Pflugeisen C, Kordas G, Amram O. Racial and socioeconomic inequities in breast cancer screening before and during the COVID-19 pandemic: analysis of two cohorts of women 50 years +. Breast Cancer. 2022;29(4):740–6. Tables Table 1. Distribution of the proportion of women who were screened for cancer screening by department in Peru since 2017 to 2021. Distribution by Ethnic Group Lowest Quartile Third Quartile Second Quartile Highest Quartile p value Me (IQR) Me (IQR) Me (IQR) Me (IQR) Proportion of Women with Cancer Screening in Regions All Women 24.82 (20.48 – 25.61) 30.36 (29.13 – 32.20) 36.29 (34.82 – 38.30) 44.52 (41.98 – 51.45) <0.001 White or mixed 25.73 (20.03 – 27.97) 33.44 (32.50 – 34.81) 39.48 (39.41 – 41.23) 53.73 (46.15 – 61.98) <0.001 Quechua or aimara 16.96 (8.61 – 19.69) 25.29 (23.94 – 27.47) 33.52 (31.25 – 35.90) 49.76 (42.46 – 55.44) <0.001 Afroperuvians 0 (0 – 11.43) 23.15 (19.46 – 24.61) 33.08 (31.17 – 35.57) 63.08 (47.49 – 83.59) <0.001 Proportion of Women with Clinical Breast Examination in Regions All Women 23.06 (20.40 – 25.51) 30.60 (29.42 – 32.71) 41.60 (38.35 – 44.18) 54.19 (49.67 – 58.26) <0.001 White or mixed 31.63 (23.35 – 32.82) 42.32 (38.61 – 45.05) 52.39 (48.47 – 55.17) 64.55 (59.80 – 69.59) <0.001 Quechua or aimara 16.66 (0 – 19.57) 26.53 (23.64 – 27.29) 34.63 (32.55 – 37.63) 51.91 (45.92 – 64.08) <0.001 Afroperuvians 3.82 (0 – 13.14) 27.52 (24.20 – 32.68) 40.34 (39.12 – 44.99) 59.15 (52.20 – 78.60) <0.001 Proportion of Women with Mammography in Regions All Women 15.02 (12.48 – 16.36) 20.39 (19.12 – 21.72) 26.35 (24.18 – 30.04) 38.31 (33.18 – 43.84) <0.001 White or mixed 20.89 (15.29 – 23.50) 29.96 (27.64 – 32.94) 42.46 (39.52 – 44.76) 55.61 (50.22 – 60.61) <0.001 Quechua or aimara 6.59 (0 – 11.46) 16.95 (15.79 – 18.53) 25.60 (22.54 – 28.25) 47.39 (40.10 – 60.73) <0.001 Afroperuvians 0 12.26 (8.00 – 17.55) 27.57 (25.74 – 29.28) 53.17 (39.93 – 74.32) <0.001 Proportion of Women with Pap Test in Regions All Women 72.39 (62.59 – 74.86) 80.11 (77.68 – 80.73) 84.76 (83.38 – 85.81) 88.31 (86.78 – 90.43) <0.001 White or mixed 74.69 (67.09 – 76.92) 80.91 (80.11 – 82.18) 87.22 (85.26 – 88.71) 93.43 (91.14 – 96.74) <0.001 Quechua or aimara 60.46 (45.29 – 68.39) 76.13 (74.71 – 78.85) 84.41 (81.80 – 85.58) 92.32 (88.87 – 100.00) <0.001 Afroperuvians 63.33 (52.25 – 70.06) 76.12 (74.04 – 79.73) 87.85 (85.53 – 90.43) 100.00 (100.00 – 100.00) <0.001 Me: Median , IQR: Interquartile Range Table 2. Temporal evolution of ethnic inequalities in the distribution of cancer screening services in Peruvian regions between 2017 to 2021 Cancer Screening Services according to Ethnic Groups GINI Coefficient for Each Year 2017 2018 2019 2020 2021 General Cancer Screening All Women 0.117 0.116 0.113 0.097 0.127 White or Mestizo 0.200 0.173 0.111 0.113 0.113 Indigenous* 0.442 0.315 0.201 0.229 0.294 Afroperuvians 0.506 0.421 0.279 0.273 0.295 Clinical Breast Cancer Examination All Women 0.197 0.152 0.172 0.175 0.184 White or Mestizo 0.253 0.127 0.140 0.159 0.171 Indigenous* 0.344 0.343 0.267 0.347 0.266 Afroperuvians 0.608 0.318 0.341 0.198 0.301 Mammography All Women 0.245 0.213 0.212 0.206 0.225 White or Mestizo 0.286 0.170 0.218 0.173 0.227 Indigenous* 0.393 0.415 0.392 0.441 0.326 Afroperuvians 0.667 0.484 0.473 0.340 0.526 Papanicolaou Test All Women 0.050 0.027 0.060 0.042 0.053 White or Mestizo 0.093 0.055 0.052 0.043 0.054 Indigenous* 0.137 0.147 0.081 0.096 0.136 Afroperuvians 0.191 0.152 0.107 0.062 0.070 *This category groups Quechua or Aymara, ethnic groups with their own language Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 24 Jul, 2024 Read the published version in BMC Women's Health → Version 1 posted Editorial decision: Revision requested 18 Apr, 2024 Reviews received at journal 17 Apr, 2024 Reviewers agreed at journal 16 Apr, 2024 Reviews received at journal 15 Apr, 2024 Reviews received at journal 15 Apr, 2024 Reviews received at journal 13 Apr, 2024 Reviewers agreed at journal 10 Apr, 2024 Reviewers agreed at journal 10 Apr, 2024 Reviewers agreed at journal 10 Apr, 2024 Reviewers agreed at journal 08 Apr, 2024 Reviewers agreed at journal 08 Apr, 2024 Reviewers agreed at journal 08 Apr, 2024 Reviewers agreed at journal 05 Apr, 2024 Reviewers agreed at journal 05 Apr, 2024 Reviewers agreed at journal 05 Apr, 2024 Reviewers invited by journal 05 Apr, 2024 Editor invited by journal 04 Apr, 2024 Editor assigned by journal 02 Apr, 2024 Submission checks completed at journal 18 Mar, 2024 First submitted to journal 11 Mar, 2024 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 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-4078937","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":280726954,"identity":"01b600eb-314c-4b10-a636-362d8b031dc4","order_by":0,"name":"Claudio Intimayta-Escalante","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABB0lEQVRIiWNgGAWjYDACdiDmMQASzBC+HIg48ACfFmaoFh6wlgQGY7CWBIJaoBikJbEBQuMG/M3MzyTeFNjk2bNzJ37m/WGXPj/s8EOgLXZyug3YtUgcZjOTnGOQVszDzLtZmichOXfj7TQDoJZkY7MD2LUYMDOYSfMYHE7sYebdANTCnLtxdgJIy4HEbTi1sH+Dadn8myehPt1wdvoHAlp44LZsA9pyOEFeOge/LRKHeYotgX5J7DnMu81yTtpxww3SOQUHEgxw+4W/vX3jjTd/bBLb+89uvvHGplpefnb65g8fKuzkcGlBAUygyDEAqzQgQjkIMP4AEvINRKoeBaNgFIyCEQMALGRZFoZS+IcAAAAASUVORK5CYII=","orcid":"","institution":"Universidad Nacional Mayor de San Marcos","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Claudio","middleName":"","lastName":"Intimayta-Escalante","suffix":""}],"badges":[],"createdAt":"2024-03-12 01:25:15","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4078937/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4078937/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12905-024-03225-6","type":"published","date":"2024-07-24T16:15:55+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":53059867,"identity":"8998baaa-fad5-43c1-adfb-86938791e193","added_by":"auto","created_at":"2024-03-20 07:18:49","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":67488,"visible":true,"origin":"","legend":"\u003cp\u003eLorenz curves of the women proportion use of cancer screening services according to ethnic groups in the departments of Peru since 2017 to 2021\u003c/p\u003e","description":"","filename":"Picture1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4078937/v1/f732394019ca169bea720c45.jpg"},{"id":53059868,"identity":"08668e57-e7bf-46fe-962e-91d2fa2acf6e","added_by":"auto","created_at":"2024-03-20 07:18:49","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":589415,"visible":true,"origin":"","legend":"\u003cp\u003eEquiplots of the women proportion use of cancer screening services according to sociodemographic characteristics between ethnic groups in the departments of Peru since 2017 to 2021\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eA. \u003c/strong\u003eScreening for any cancer\u003cstrong\u003e, B.\u003c/strong\u003e Clinical breast examination\u003cstrong\u003e, C.\u003c/strong\u003e Mammography screening\u003cstrong\u003e, D.\u003c/strong\u003ePapanicolaou test.\u003c/p\u003e","description":"","filename":"Picture2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-4078937/v1/808d7c4c14fd80a641cd67ca.jpg"},{"id":61596325,"identity":"6ed83ba6-6872-4699-98f1-ae3d214eef63","added_by":"auto","created_at":"2024-08-01 17:26:38","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1264281,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4078937/v1/1ca7580e-991a-4af1-8882-f97981a8e519.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Ethnic inequalities in the access of cancer screening services for women´s in Peru","fulltext":[{"header":"BACKGROUND","content":"\u003cp\u003eBreast and cervical cancer are the two most prevalent forms of cancer affecting women worldwide (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). In high-income countries, early access to screening tests and prompt treatment has resulted in a decrease in mortality from these cancers (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). However, in lower-middle-income countries like Peru, breast cancer remains one of the top causes of death among women (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eCurrently many organizations recommend that women undergo a clinical breast examination at age 21, a Papanicolaou test at age 30, and a mammogram at age 50 (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). However, despite guidelines for cancer screening and increased healthcare resources, there are persistent disparities in coverage to secondary prevention services for non-white communities (\u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). This results in higher cancer mortality rates among non-white ethnic groups (\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eInequalities in coverage to healthcare screening services can be modified by socioeconomic factors (income, education, and age), as well as personal factors (health conditions, fears, preferences, and religion), and geographical factors (location of residence or distance to health centers) (\u003cspan additionalcitationids=\"CR13 CR14\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). Addressing these health inequalities is a critical issue in multicultural countries like Peru (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). For this reason, the aim of the study was to assess ethnic inequalities in the use of a cancer screening services for women across different regions in Peru.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Design\u003c/h2\u003e \u003cp\u003eAn ecological study was conducted to analyze the use of a cancer screening services in the 25 regions in Peru over the five-year period from 2017 to 2021. The indicator evaluated in each region was the proportion of women over 18 years of age who use cancer screening services in the departments of Peru surveyed by the Demographic and Family Health Survey (ENDES in Spanish).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eDefinition of Outcomes\u003c/h2\u003e \u003cp\u003eThe assessment of cancer screening in the ENDES is performed with specific questions for evaluated if Peruvians women had a general screening for any type of cancer (Did you have a general check-up or screening for any cancer?) in those with 18 years old or more, clinical breast examination (Have you ever had a clinical breast exam performed by a physician or other health professional?) in those with 18 years old or more, Papanicolaou smear test (Have you ever had a Pap smear test performed by a physician or other health professional?) in those between 18 and 64 years old, or mammography test (Have you ever had a mammogram performed by a physician/health professional?) in those with 30 years old or more.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eSociodemographic Conditions\u003c/h2\u003e \u003cp\u003eWe also examined how sociodemographic characteristics affected cancer screening coverage for women. These characteristics included age group (18 to 30, 31 to 49, 50 to 64, and 65 years old or more), educational level (without education, primary, high school, or higher education), wealth index (ranging from the wealthiest first quintile to the least wealthy fifth quintile), area of residence (urban or rural), health insurance status (have or don't have), residence area (urban or rural), health insurance (no or yes), and ethnic groups in Peru (white or mestizo, indigenous including Quechua or Aymara, Afro-Peruvian, or other).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eThe data analysis was performed using Stata v.17.0. The analysis of inequalities related to the proportion of women use of cancer screening services was based on their ethnic group. This was achieved by estimating the GINI Coefficient, which measures inequality in the distribution of a specific population as a percentage. This approach allowed for the observation of how only a portion of the evaluated population has use to a resource or service compared to another group. A GINI Coefficient of 0 represents no inequality, while a score of 1 indicates absolute inequality. The comparison on the distribution of cancer screening services among women and specific ethnic groups was graph on Lorenz curves. Also was compared the median (Me) and interquartile range (IQR) of the percentage of women use of cancer screening services for each ethnic group using quartiles and Kruskal-Wallis test\u0026acute;s.\u003c/p\u003e \u003cp\u003eAdditionally, we conducted a stratified analysis of sociodemographic characteristics (age group, education level, wealth index, area of residence, and health insurance) among all surveyed women and specific ethnic groups using equiplots. The analysis also assessed the annual change in the GINI Coefficient for each ethnic group over the period from 2017 to 2021.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eEthical aspects\u003c/h2\u003e \u003cp\u003eA request for ethical committee evaluation was not necessary as the data collection process for ENDES was carried out with the informed consent of participants. Furthermore, the data obtained from the National Institute of Statistics and Informatics (INEI) platform does not contain personally identifiable information and is secure (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://iinei.inei.gob.pe/microdatos/\u003c/span\u003e\u003cspan address=\"http://iinei.inei.gob.pe/microdatos/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e"},{"header":"RESULTS","content":"\u003cp\u003eThe analysis of the 25 regions in Peru over a five-year period revealed that women who identify as white or mestizo have less inequality for use to cancer screening services compared to women who identify as indigenous or afroperuvians (Table\u0026nbsp;1). The GINI coefficient and Lorenz curves indicate that use to cancer screening services among all women surveyed in the Peruvian regions is like use among white or mestizo women. However, use of cancer screening services is more unequal among indigenous and afroperuvians (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The evaluation of the screening services revealed greater ethnic inequality in use to mammograms, while the Papanicolaou test had the least inequality (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe equiplots showed that the most important sociodemographic factors related to inequalities in cancer screening coverage in Peruvians regions were lack of education, being 65 years or older, and having no health insurance or being in the lowest wealth quintile (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA). Lack of education, being between 18 and 30 years old or 65 years or older, being in the lowest wealth quintile, and living in a rural area were the key factors for inequalities in clinical breast examination (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). Lack of education, being in the lowest wealth quintile, and living in a rural area were the key factors for inequalities in mammography screening (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC). Meanwhile, lack of education, having no health insurance, and being in the lowest wealth quintile were the key factors for inequalities in the Papanicolaou test (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eD).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe annual variation of the GINI coefficient in the Peruvian regions showed that inequalities in cancer screening were greater in the afroperuvians and indigenous groups, especially in 2021. Also, inequalities in clinical breast examination were higher for afroperuvians after 2020, while they decreased for indigenous and white or mestizo groups. The greatest annual variation in the GINI index was observed in mammography screening, particularly for the afroperuvians and indigenous groups. The lowest annual variation in the GINI coefficient was observed in the Papanicolaou test, except for the indigenous group (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThe study aimed to evaluate ethnic inequalities in the proportion of women use of cancer screening services in Peruvians regions. It was found that the indigenous and afroperuvians ethnic groups faced greater inequalities compared to the white or mestizo group. The study suggests that language and cultural barriers may prevent indigenous groups (quechua or aymara women) from use to these services (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). Meanwhile, afroperuvians could experience discrimination and racism that hinder their access to healthcare (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). This exclusion can also lead to difficulties in obtaining adequate treatment, resulting in worse disease outcomes (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAdditionally, sociodemographic factors such as education, age, and wealth index also play a role in use of cancer screening services. Education, in particular, is a modifiable condition that can be targeted by public policies to improve coverage (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). On the other hand, wealth inequality shows that lower income is a major barrier to accessing these services (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). However, the unequal distribution of resources and healthcare personnel in Peru's regions also impedes use of cancer screening (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). Targeting cancer screening to specific age groups may be cost-effective, but it may also limit use for older populations with higher morbidity rates (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe study observed that ethnic inequalities in using cancer screening services were decreasing until 2020, but the COVID-19 pandemic led to a reduction in public policies aimed at closing the gap (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). This resulted in a sharp increase in inequalities among afroperuvians and indigenous groups, while the white or mestizo group showed a reduction in inequalities (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). Living in rural areas and being farther away from the capital (Lima) also exacerbates disparities in use of these services, particularly for non-white ethnic groups (\u003cspan additionalcitationids=\"CR28\" citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e).\u003c/p\u003e \u003cp\u003ePeriodic monitoring with screening tests presents an opportunity to address these disparities, especially for non-white ethnic groups (\u003cspan additionalcitationids=\"CR31 CR32\" citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e). However, there is evidence of greater inequalities in mammogram performance among ethnic groups in Peru, which may be due to centralization of healthcare resources (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e). Other factors such as discomfort with cancer screening procedures or fear of the disease can also reduce the proportion of women using these services (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe study provides an approximation of ethnic inequalities in use to health screening services for cancer. However, the ecological approach does not allow extrapolating the findings to an individual level. In addition, some ethnic groups may be underrepresented in the DHS. And although respondents were over 18 years of age, many were not in the target age group for some screening tests. Additionally, in the COVID-19 pandemic, many women from non-white ethnic groups may have experienced more difficulties in use of health services (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e).\u003c/p\u003e"},{"header":"CONCLUSIONS","content":"\u003cp\u003eIn conclusion, in Peruvians regions there are ethnic inequalities in the use of cancer screening services for women. Indigenous and afroperuvians ethnic groups face a greater inequality in comparison to the white or mestizo group. This inequality is particularly pronounced in regions with a higher concentration of women facing adverse socioeconomic conditions, and it has exacerbated in non-white ethnic groups after the COVID-19 pandemic in Peru.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA request for ethical committee evaluation was not necessary as the data collection process for Demographic Health Survey in Peru was carried out with the informed consent of participants. Furthermore, the data obtained from the National Institute of Statistics and Informatics platform does not contain personally identifiable information and is secure to be used (http://iinei.inei.gob.pe/microdatos/).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailable of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe dataset supporting the conclusions of this article is available in the INEI repository: https://proyectos.inei.gob.pe/microdatos/\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was self-funded\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCIE participated in the conception and design of the study, the data management and data analysis. All authors participated in the interpretation of the results, the writing and review of manuscript. Finally, all authors of this research approved the final version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements:\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBray F, Ferlay J, Soerjomataram I, Siegel RL, Torre LA, Jemal A. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2018;68(6):394\u0026ndash;424.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFerlay J, Colombet M, Soerjomataram I, Mathers C, Parkin DM, Pi\u0026ntilde;eros M, Znaor A, Bray F. Estimating the global cancer incidence and mortality in 2018: GLOBOCAN sources and methods. Int J Cancer. 2019;144(8):1941\u0026ndash;53.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShah SC, Kayamba V, Peek RM Jr, Heimburger D. Cancer Control in Low- and Middle-Income Countries: Is It Time to Consider Screening? J Glob Oncol. 2019;5:1\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGlobal Burden of Disease Cancer Collaboration, Fitzmaurice C, Akinyemiju TF, et al. Global, Regional, and National Cancer Incidence, Mortality, Years of Life Lost, Years Lived With Disability, and Disability-Adjusted Life-Years for 29 Cancer Groups, 1990 to 2016: A Systematic Analysis for the Global Burden of Disease Study. JAMA Oncol. 2018;4(11):1553\u0026ndash;68.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKitchen FL, Cox CM. Papanicolaou Smear. [Updated 2022 Oct 17]. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2022 Jan-. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ncbi.nlm.nih.gov/books/NBK470165/\u003c/span\u003e\u003cspan address=\"https://www.ncbi.nlm.nih.gov/books/NBK470165/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRen W, Chen M, Qiao Y, Zhao F. Global guidelines for breast cancer screening: A systematic review. Breast. 2022;64:85\u0026ndash;99.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMartins T, Abel G, Ukoumunne OC, Mounce LTA, Price S, Lyratzopoulos G, et al. Ethnic inequalities in routes to diagnosis of cancer: a population-based UK cohort study. Br J Cancer. 2022;127(5):863\u0026ndash;71.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFerreira CS, Rodrigues J, Moreira S, Ribeiro F, Longatto-Filho A. Breast cancer screening adherence rates and barriers of implementation in ethnic, cultural and religious minorities: A systematic review. Mol Clin Oncol. 2021;15(1):139.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSeneviratne S, Campbell I, Scott N, Shirley R, Lawrenson R. Impact of mammographic screening on ethnic and socioeconomic inequities in breast cancer stage at diagnosis and survival in New Zealand: a cohort study. BMC Public Health. 2015;15:46.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWhitaker KD, Wang X, Ascha M, Showalter TN, Lewin HG, Calip GS, et al. Racial inequities in second-line treatment and overall survival among patients with metastatic breast cancer. Breast Cancer Res Treat. 2022;196(1):163\u0026ndash;73.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMarcelino AC, Gozzi B, Cardoso-Filho C, Machado H, Zeferino LC, Vale DB. Race disparities in mortality by breast cancer from 2000 to 2017 in Sao Paulo, Brazil: a population-based retrospective study. BMC Cancer. 2021;21(1):998.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMusselwhite LW, Oliveira CM, Kwaramba T, de Paula Pantano N, Smith JS, Fregnani JH, et al. Racial/Ethnic Disparities in Cervical Cancer Screening and Outcomes. Acta Cytol. 2016;60(6):518\u0026ndash;26.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKrieger N, Singh N, Waterman PD. Metrics for monitoring cancer inequities: residential segregation, the Index of Concentration at the Extremes (ICE), and breast cancer estrogen receptor status (USA, 1992\u0026ndash;2012). Cancer Causes Control. 2016;27(9):1139\u0026ndash;51.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOnega T, Hubbard R, Hill D, Lee CI, Haas JS, Carlos HA, et al. Geographic access to breast imaging for US women. J Am Coll Radiol. 2014;11(9):874\u0026ndash;82.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHarper S, Lynch J, Meersman SC, Breen N, Davis WW, Reichman MC. Trends in area-socioeconomic and race-ethnic disparities in breast cancer incidence, stage at diagnosis, screening, mortality, and survival among women ages 50 years and over (1987\u0026ndash;2005). Cancer Epidemiol Biomarkers Prev. 2009;18(1):121\u0026ndash;31.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSalaverry O. Interculturalidad en Salud. Simposio: Interculturalidad en Salud. Rev Peru Med Exp Salud Publica. 2010;27(1):80\u0026ndash;93.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWells KRR. Health disparities in receipt of screening mammography in Latinas: a critical review of recent literature. Cancer Control. 2007;14(4):369\u0026ndash;79.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAgenor M, Krieger N, Austin SB, Haneuse S, Gottlieb BR. At the intersection of sexual orientation, race/ethnicity, and cervical cancer screening: assessing Pap test use disparities by sex of sexual partners among black, Latina, and white U.S. women. Soc Sci Med. 2014;116:110\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZajacova A, Lawrence EM. The Relationship Between Education and Health: Reducing Disparities Through a Contextual Approach. Annu Rev Public Health. 2018;39:273\u0026ndash;89.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMINSA. Plan Nacional de Prevenci\u0026oacute;n y Control de C\u0026aacute;ncer de Cuello Uterino 2017\u0026ndash;2021 (R.M. N\u0026ordm; 440\u0026ndash;2017/MINSA). Direcci\u0026oacute;n General de Intervenciones Estrat\u0026eacute;gicas en Salud P\u0026uacute;blica / Direcci\u0026oacute;n de Prevenci\u0026oacute;n y Control de C\u0026aacute;ncer \u0026ndash; Lima. 2017. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://bvs.minsa.gob.pe/local/MINSA/4232.pdf\u003c/span\u003e\u003cspan address=\"http://bvs.minsa.gob.pe/local/MINSA/4232.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. [Accessed 4 January 2023.].\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMINSA. Plan Nacional de Prevenci\u0026oacute;n y Control de C\u0026aacute;ncer de Mama en el Per\u0026uacute; 2017\u0026ndash;2021 (R.M. N\u0026ordm; 442\u0026ndash;2017/MINSA). Direcci\u0026oacute;n General de Intervenciones Estrat\u0026eacute;gicas en Salud P\u0026uacute;blica / Direcci\u0026oacute;n de Prevenci\u0026oacute;n y Control de C\u0026aacute;ncer \u0026ndash; Lima. 2017. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://bvs.minsa.gob.pe/local/MINSA/4234.pdf\u003c/span\u003e\u003cspan address=\"http://bvs.minsa.gob.pe/local/MINSA/4234.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. [Accessed 4 January 2023.].\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eThoumi A, Bond SJ, Dotson ME, et al. Policy Considerations to Promote Equitable Cervical Cancer Screening and Treatment in Peru. Ann Glob Health. 2021;87(1):116.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSazlina SG. Health screening for older people-what are the current recommendations? Malays Fam Physician. 2015;10(1):2\u0026ndash;10.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDu B, Mu Y. The Relationship Between Health Changes and Community Health Screening Participation Among Older People. Front Public Health. 2022;10:870157.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCancino RS, Su Z, Mesa R, et al. The Impact of COVID-19 on Cancer Screening: Challenges and Opportunities. JMIR Cancer. 2020;6(2):e21697.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLuu T. Reduced Cancer Screening Due to Lockdowns of the COVID-19 Pandemic: Reviewing Impacts and Ways to Counteract the Impacts. Front Oncol. 2022;12:955377.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCollins J, Bowie D, Shannon G et al. A descriptive analysis of health practices, barriers to healthcare and the unmet need for cervical cancer screening in the Lower Napo River region of the Peruvian Amazon. Women\u0026acute;s Health. 2019;15.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDowney L. Spatial Measurement, Geography, and Urban Racial Inequality. Soc Forces. 2003;81(3):937\u0026ndash;52. Disponible en:. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.jstor.org/stable/3598181\u003c/span\u003e\u003cspan address=\"https://www.jstor.org/stable/3598181\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLymperopoulou K, Finney N. Socio-spatial factors associated with ethnic inequalities in districts of England and Wales, 2001\u0026ndash;2011. Urban Stud. 2016;54(11):2540\u0026ndash;60.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGlanz K, Resch N, Lerman C, Rimer BK. Black-White differences in factors influencing mammography use among employed female health maintenance organization members. Ethn Health. 1996;1(3):207\u0026ndash;20.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSchwartz C, Chukwudozie IB, Tejeda S, Vijayasiri G, Abraham I, Remo M, et al. Association of Population Screening for Breast Cancer Risk With Use of Mammography Among Women in Medically Underserved Racial and Ethnic Minority Groups. JAMA Netw Open. 2021;4(9):e2123751.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEdwards QT, Li AX, Pike MC, Kolonel LN, Ursin G, Henderson BE, et al. Ethnic differences in the use of regular mammography: the multiethnic cohort. Breast Cancer Res Treat. 2009;115(1):163\u0026ndash;70.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSabatino SCR, Uhler R, Breen N, Tangka F, Shaw K. Disparities in mammography use among US women aged 40\u0026ndash;64 years, by race, ethnicity, income, and health insurance status, 1993 and 2005. Med Care. 2008;46(7):692\u0026ndash;700.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUnger-Salda\u0026ntilde;a K, Cedano Guadiamos M, Burga Vega A et al. Delays to diagnosis and barriers to care for breast cancer in Mexico and Peru: a cross sectional study. Lancet Global Health. 2020. 8(Supp. 1). S16.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAshkar LK, Zaki YH. Female patients' perception of pain caused by mammography in the Western Region of Saudi Arabia. Saudi Med J. 2017;38(7):768\u0026ndash;71.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLudman EJ, Ichikawa LE, Simon GE, Rohde P, Arterburn D, Operskalski BH, Linde JA, Jeffery RW. Breast and cervical cancer screening specific effects of depression and obesity. Am J Prev Med. 2010;38(3):303\u0026ndash;10.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMonsivais P, Amiri S, Robison J, Pflugeisen C, Kordas G, Amram O. Racial and socioeconomic inequities in breast cancer screening before and during the COVID-19 pandemic: analysis of two cohorts of women 50 years +. Breast Cancer. 2022;29(4):740\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"822\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"99.87849331713244%\" colspan=\"6\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 1.\u003c/strong\u003e\u0026nbsp; Distribution of the proportion of women who were screened for cancer screening by department in Peru since 2017 to 2021.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0.12150668286755771%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.431181485992692%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eDistribution by Ethnic Group\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.077953714981728%\"\u003e\n \u003cp\u003e\u003cstrong\u003eLowest Quartile\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.077953714981728%\"\u003e\n \u003cp\u003e\u003cstrong\u003eThird Quartile\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.077953714981728%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSecond Quartile\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.392204628501826%\"\u003e\n \u003cp\u003e\u003cstrong\u003eHighest Quartile\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.942752740560293%\" colspan=\"2\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003ep value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"24.13162705667276%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMe (IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.13162705667276%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMe (IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"24.13162705667276%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMe (IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.60511882998172%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMe (IQR)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.431181485992692%\"\u003e\n \u003cp\u003e\u003cstrong\u003eProportion of Women with Cancer Screening in Regions\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.077953714981728%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.077953714981728%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.077953714981728%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.392204628501826%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.942752740560293%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.431181485992692%\"\u003e\n \u003cp\u003eAll Women\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.077953714981728%\"\u003e\n \u003cp\u003e24.82 (20.48 \u0026ndash; 25.61)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.077953714981728%\"\u003e\n \u003cp\u003e30.36 (29.13 \u0026ndash; 32.20)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.077953714981728%\"\u003e\n \u003cp\u003e36.29 (34.82 \u0026ndash; 38.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.392204628501826%\"\u003e\n \u003cp\u003e44.52 (41.98 \u0026ndash; 51.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.942752740560293%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.431181485992692%\"\u003e\n \u003cp\u003eWhite or mixed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.077953714981728%\"\u003e\n \u003cp\u003e25.73 (20.03 \u0026ndash; 27.97)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.077953714981728%\"\u003e\n \u003cp\u003e33.44 (32.50 \u0026ndash; 34.81)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.077953714981728%\"\u003e\n \u003cp\u003e39.48 (39.41 \u0026ndash; 41.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.392204628501826%\"\u003e\n \u003cp\u003e53.73 (46.15 \u0026ndash; 61.98)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.942752740560293%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.431181485992692%\"\u003e\n \u003cp\u003eQuechua or aimara\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.077953714981728%\"\u003e\n \u003cp\u003e16.96 (8.61 \u0026ndash; 19.69)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.077953714981728%\"\u003e\n \u003cp\u003e25.29 (23.94 \u0026ndash; 27.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.077953714981728%\"\u003e\n \u003cp\u003e33.52 (31.25 \u0026ndash; 35.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.392204628501826%\"\u003e\n \u003cp\u003e49.76 (42.46 \u0026ndash; 55.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.942752740560293%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.431181485992692%\"\u003e\n \u003cp\u003eAfroperuvians\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.077953714981728%\"\u003e\n \u003cp\u003e0 (0 \u0026ndash; 11.43)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.077953714981728%\"\u003e\n \u003cp\u003e23.15 (19.46 \u0026ndash; 24.61)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.077953714981728%\"\u003e\n \u003cp\u003e33.08 (31.17 \u0026ndash; 35.57)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.392204628501826%\"\u003e\n \u003cp\u003e63.08 (47.49 \u0026ndash; 83.59)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.942752740560293%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.431181485992692%\"\u003e\n \u003cp\u003e\u003cstrong\u003eProportion of Women with Clinical Breast Examination in Regions\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.077953714981728%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.077953714981728%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.077953714981728%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.392204628501826%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.942752740560293%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.431181485992692%\"\u003e\n \u003cp\u003eAll Women\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.077953714981728%\"\u003e\n \u003cp\u003e23.06 (20.40 \u0026ndash; 25.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.077953714981728%\"\u003e\n \u003cp\u003e30.60 (29.42 \u0026ndash; 32.71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.077953714981728%\"\u003e\n \u003cp\u003e41.60 (38.35 \u0026ndash; 44.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.392204628501826%\"\u003e\n \u003cp\u003e54.19 (49.67 \u0026ndash; 58.26)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.942752740560293%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.431181485992692%\"\u003e\n \u003cp\u003eWhite or mixed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.077953714981728%\"\u003e\n \u003cp\u003e31.63 (23.35 \u0026ndash; 32.82)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.077953714981728%\"\u003e\n \u003cp\u003e42.32 (38.61 \u0026ndash; 45.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.077953714981728%\"\u003e\n \u003cp\u003e52.39 (48.47 \u0026ndash; 55.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.392204628501826%\"\u003e\n \u003cp\u003e64.55 (59.80 \u0026ndash; 69.59)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.942752740560293%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.431181485992692%\"\u003e\n \u003cp\u003eQuechua or aimara\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.077953714981728%\"\u003e\n \u003cp\u003e16.66 (0 \u0026ndash; 19.57)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.077953714981728%\"\u003e\n \u003cp\u003e26.53 (23.64 \u0026ndash; 27.29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.077953714981728%\"\u003e\n \u003cp\u003e34.63 (32.55 \u0026ndash; 37.63)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.392204628501826%\"\u003e\n \u003cp\u003e51.91 (45.92 \u0026ndash; 64.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.942752740560293%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.431181485992692%\"\u003e\n \u003cp\u003eAfroperuvians\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.077953714981728%\"\u003e\n \u003cp\u003e3.82 (0 \u0026ndash; 13.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.077953714981728%\"\u003e\n \u003cp\u003e27.52 (24.20 \u0026ndash; 32.68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.077953714981728%\"\u003e\n \u003cp\u003e40.34 (39.12 \u0026ndash; 44.99)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.392204628501826%\"\u003e\n \u003cp\u003e59.15 (52.20 \u0026ndash; 78.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.942752740560293%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.431181485992692%\"\u003e\n \u003cp\u003e\u003cstrong\u003eProportion of Women with Mammography in Regions\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.077953714981728%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.077953714981728%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.077953714981728%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.392204628501826%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.942752740560293%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.431181485992692%\"\u003e\n \u003cp\u003eAll Women\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.077953714981728%\"\u003e\n \u003cp\u003e15.02 (12.48 \u0026ndash; 16.36)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.077953714981728%\"\u003e\n \u003cp\u003e20.39 (19.12 \u0026ndash; 21.72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.077953714981728%\"\u003e\n \u003cp\u003e26.35 (24.18 \u0026ndash; 30.04)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.392204628501826%\"\u003e\n \u003cp\u003e38.31 (33.18 \u0026ndash; 43.84)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.942752740560293%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.431181485992692%\"\u003e\n \u003cp\u003eWhite or mixed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.077953714981728%\"\u003e\n \u003cp\u003e20.89 (15.29 \u0026ndash; 23.50)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.077953714981728%\"\u003e\n \u003cp\u003e29.96 (27.64 \u0026ndash; 32.94)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.077953714981728%\"\u003e\n \u003cp\u003e42.46 (39.52 \u0026ndash; 44.76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.392204628501826%\"\u003e\n \u003cp\u003e55.61 (50.22 \u0026ndash; 60.61)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.942752740560293%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.431181485992692%\"\u003e\n \u003cp\u003eQuechua or aimara\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.077953714981728%\"\u003e\n \u003cp\u003e6.59 (0 \u0026ndash; 11.46)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.077953714981728%\"\u003e\n \u003cp\u003e16.95 (15.79 \u0026ndash; 18.53)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.077953714981728%\"\u003e\n \u003cp\u003e25.60 (22.54 \u0026ndash; 28.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.392204628501826%\"\u003e\n \u003cp\u003e47.39 (40.10 \u0026ndash; 60.73)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.942752740560293%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.431181485992692%\"\u003e\n \u003cp\u003eAfroperuvians\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.077953714981728%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.077953714981728%\"\u003e\n \u003cp\u003e12.26 (8.00 \u0026ndash; 17.55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.077953714981728%\"\u003e\n \u003cp\u003e27.57 (25.74 \u0026ndash; 29.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.392204628501826%\"\u003e\n \u003cp\u003e53.17 (39.93 \u0026ndash; 74.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.942752740560293%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.431181485992692%\"\u003e\n \u003cp\u003e\u003cstrong\u003eProportion of Women with\u0026nbsp;\u003cbr\u003e\u0026nbsp;Pap Test in Regions\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.077953714981728%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.077953714981728%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.077953714981728%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.392204628501826%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.942752740560293%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.431181485992692%\"\u003e\n \u003cp\u003eAll Women\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.077953714981728%\"\u003e\n \u003cp\u003e72.39 (62.59 \u0026ndash; 74.86)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.077953714981728%\"\u003e\n \u003cp\u003e80.11 (77.68 \u0026ndash; 80.73)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.077953714981728%\"\u003e\n \u003cp\u003e84.76 (83.38 \u0026ndash; 85.81)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.392204628501826%\"\u003e\n \u003cp\u003e88.31 (86.78 \u0026ndash; 90.43)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.942752740560293%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.431181485992692%\"\u003e\n \u003cp\u003eWhite or mixed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.077953714981728%\"\u003e\n \u003cp\u003e74.69 (67.09 \u0026ndash; 76.92)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.077953714981728%\"\u003e\n \u003cp\u003e80.91 (80.11 \u0026ndash; 82.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.077953714981728%\"\u003e\n \u003cp\u003e87.22 (85.26 \u0026ndash; 88.71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.392204628501826%\"\u003e\n \u003cp\u003e93.43 (91.14 \u0026ndash; 96.74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.942752740560293%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.431181485992692%\"\u003e\n \u003cp\u003eQuechua or aimara\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.077953714981728%\"\u003e\n \u003cp\u003e60.46 (45.29 \u0026ndash; 68.39)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.077953714981728%\"\u003e\n \u003cp\u003e76.13 (74.71 \u0026ndash; 78.85)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.077953714981728%\"\u003e\n \u003cp\u003e84.41 (81.80 \u0026ndash; 85.58)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.392204628501826%\"\u003e\n \u003cp\u003e92.32 (88.87 \u0026ndash; 100.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.942752740560293%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.431181485992692%\"\u003e\n \u003cp\u003eAfroperuvians\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.077953714981728%\"\u003e\n \u003cp\u003e63.33 (52.25 \u0026ndash; 70.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.077953714981728%\"\u003e\n \u003cp\u003e76.12 (74.04 \u0026ndash; 79.73)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.077953714981728%\"\u003e\n \u003cp\u003e87.85 (85.53 \u0026ndash; 90.43)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.392204628501826%\"\u003e\n \u003cp\u003e100.00 (100.00 \u0026ndash; 100.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.942752740560293%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"93.06569343065694%\" colspan=\"5\"\u003e\n \u003cp\u003e\u003cstrong\u003eMe:\u003c/strong\u003e Median\u003cstrong\u003e, IQR:\u003c/strong\u003e Interquartile Range\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"6.934306569343065%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"501\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"100%\" colspan=\"11\" valign=\"bottom\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 2.\u003c/strong\u003e Temporal evolution of ethnic inequalities in the distribution of cancer screening services in Peruvian regions between 2017 to 2021\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"52.89421157684631%\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eCancer Screening Services\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eaccording to Ethnic Groups\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"47.10578842315369%\" colspan=\"9\"\u003e\n \u003cp\u003e\u003cstrong\u003eGINI Coefficient for Each Year\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20%\"\u003e\n \u003cp\u003e\u003cstrong\u003e2017\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e2018\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e2019\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e2020\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e2021\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"62.4%\" colspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eGeneral Cancer Screening\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\" colspan=\"2\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.4%\" colspan=\"2\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.4%\" colspan=\"2\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.4%\" colspan=\"2\" valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53%\" valign=\"bottom\"\u003e\n \u003cp\u003eAll Women\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\"\u003e\n \u003cp\u003e0.117\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\" colspan=\"2\"\u003e\n \u003cp\u003e0.116\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\" colspan=\"2\"\u003e\n \u003cp\u003e0.113\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\" colspan=\"2\"\u003e\n \u003cp\u003e0.097\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\" colspan=\"2\"\u003e\n \u003cp\u003e0.127\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53%\" valign=\"bottom\"\u003e\n \u003cp\u003eWhite or Mestizo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\"\u003e\n \u003cp\u003e0.200\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\" colspan=\"2\"\u003e\n \u003cp\u003e0.173\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\" colspan=\"2\"\u003e\n \u003cp\u003e0.111\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\" colspan=\"2\"\u003e\n \u003cp\u003e0.113\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\" colspan=\"2\"\u003e\n \u003cp\u003e0.113\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53%\" valign=\"bottom\"\u003e\n \u003cp\u003eIndigenous*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\"\u003e\n \u003cp\u003e0.442\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\" colspan=\"2\"\u003e\n \u003cp\u003e0.315\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\" colspan=\"2\"\u003e\n \u003cp\u003e0.201\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\" colspan=\"2\"\u003e\n \u003cp\u003e0.229\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\" colspan=\"2\"\u003e\n \u003cp\u003e0.294\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53%\" valign=\"bottom\"\u003e\n \u003cp\u003eAfroperuvians\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\"\u003e\n \u003cp\u003e0.506\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\" colspan=\"2\"\u003e\n \u003cp\u003e0.421\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\" colspan=\"2\"\u003e\n \u003cp\u003e0.279\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\" colspan=\"2\"\u003e\n \u003cp\u003e0.273\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\" colspan=\"2\"\u003e\n \u003cp\u003e0.295\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"71.8562874251497%\" colspan=\"5\"\u003e\n \u003cp\u003e\u003cstrong\u003eClinical Breast Cancer Examination\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.3812375249501%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.3812375249501%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.3812375249501%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53%\" valign=\"bottom\"\u003e\n \u003cp\u003eAll Women\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\"\u003e\n \u003cp\u003e0.197\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\" colspan=\"2\"\u003e\n \u003cp\u003e0.152\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\" colspan=\"2\"\u003e\n \u003cp\u003e0.172\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\" colspan=\"2\"\u003e\n \u003cp\u003e0.175\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\" colspan=\"2\"\u003e\n \u003cp\u003e0.184\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53%\" valign=\"bottom\"\u003e\n \u003cp\u003eWhite or Mestizo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\"\u003e\n \u003cp\u003e0.253\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\" colspan=\"2\"\u003e\n \u003cp\u003e0.127\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\" colspan=\"2\"\u003e\n \u003cp\u003e0.140\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\" colspan=\"2\"\u003e\n \u003cp\u003e0.159\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\" colspan=\"2\"\u003e\n \u003cp\u003e0.171\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53%\" valign=\"bottom\"\u003e\n \u003cp\u003eIndigenous*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\"\u003e\n \u003cp\u003e0.344\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\" colspan=\"2\"\u003e\n \u003cp\u003e0.343\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\" colspan=\"2\"\u003e\n \u003cp\u003e0.267\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\" colspan=\"2\"\u003e\n \u003cp\u003e0.347\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\" colspan=\"2\"\u003e\n \u003cp\u003e0.266\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53%\" valign=\"bottom\"\u003e\n \u003cp\u003eAfroperuvians\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\"\u003e\n \u003cp\u003e0.608\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\" colspan=\"2\"\u003e\n \u003cp\u003e0.318\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\" colspan=\"2\"\u003e\n \u003cp\u003e0.341\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\" colspan=\"2\"\u003e\n \u003cp\u003e0.198\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\" colspan=\"2\"\u003e\n \u003cp\u003e0.301\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMammography\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.4%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.4%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.4%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.4%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53%\" valign=\"bottom\"\u003e\n \u003cp\u003eAll Women\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\"\u003e\n \u003cp\u003e0.245\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\" colspan=\"2\"\u003e\n \u003cp\u003e0.213\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\" colspan=\"2\"\u003e\n \u003cp\u003e0.212\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\" colspan=\"2\"\u003e\n \u003cp\u003e0.206\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\" colspan=\"2\"\u003e\n \u003cp\u003e0.225\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53%\" valign=\"bottom\"\u003e\n \u003cp\u003eWhite or Mestizo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\"\u003e\n \u003cp\u003e0.286\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\" colspan=\"2\"\u003e\n \u003cp\u003e0.170\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\" colspan=\"2\"\u003e\n \u003cp\u003e0.218\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\" colspan=\"2\"\u003e\n \u003cp\u003e0.173\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\" colspan=\"2\"\u003e\n \u003cp\u003e0.227\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53%\" valign=\"bottom\"\u003e\n \u003cp\u003eIndigenous*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\"\u003e\n \u003cp\u003e0.393\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\" colspan=\"2\"\u003e\n \u003cp\u003e0.415\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\" colspan=\"2\"\u003e\n \u003cp\u003e0.392\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\" colspan=\"2\"\u003e\n \u003cp\u003e0.441\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\" colspan=\"2\"\u003e\n \u003cp\u003e0.326\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53%\" valign=\"bottom\"\u003e\n \u003cp\u003eAfroperuvians\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\"\u003e\n \u003cp\u003e0.667\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\" colspan=\"2\"\u003e\n \u003cp\u003e0.484\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\" colspan=\"2\"\u003e\n \u003cp\u003e0.473\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\" colspan=\"2\"\u003e\n \u003cp\u003e0.340\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\" colspan=\"2\"\u003e\n \u003cp\u003e0.526\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePapanicolaou Test\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.4%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.4%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.4%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"9.4%\" colspan=\"2\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53%\" valign=\"bottom\"\u003e\n \u003cp\u003eAll Women\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\"\u003e\n \u003cp\u003e0.050\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\" colspan=\"2\"\u003e\n \u003cp\u003e0.027\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\" colspan=\"2\"\u003e\n \u003cp\u003e0.060\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\" colspan=\"2\"\u003e\n \u003cp\u003e0.042\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\" colspan=\"2\"\u003e\n \u003cp\u003e0.053\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53%\" valign=\"bottom\"\u003e\n \u003cp\u003eWhite or Mestizo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\"\u003e\n \u003cp\u003e0.093\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\" colspan=\"2\"\u003e\n \u003cp\u003e0.055\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\" colspan=\"2\"\u003e\n \u003cp\u003e0.052\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\" colspan=\"2\"\u003e\n \u003cp\u003e0.043\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\" colspan=\"2\"\u003e\n \u003cp\u003e0.054\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53%\" valign=\"bottom\"\u003e\n \u003cp\u003eIndigenous*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\"\u003e\n \u003cp\u003e0.137\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\" colspan=\"2\"\u003e\n \u003cp\u003e0.147\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\" colspan=\"2\"\u003e\n \u003cp\u003e0.081\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\" colspan=\"2\"\u003e\n \u003cp\u003e0.096\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\" colspan=\"2\"\u003e\n \u003cp\u003e0.136\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"53%\" valign=\"top\"\u003e\n \u003cp\u003eAfroperuvians\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\"\u003e\n \u003cp\u003e0.191\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\" colspan=\"2\"\u003e\n \u003cp\u003e0.152\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\" colspan=\"2\"\u003e\n \u003cp\u003e0.107\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\" colspan=\"2\"\u003e\n \u003cp\u003e0.062\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.4%\" colspan=\"2\"\u003e\n \u003cp\u003e0.070\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"99.800796812749%\" colspan=\"10\" valign=\"bottom\"\u003e\n \u003cp\u003e*This category groups Quechua or Aymara, ethnic groups with their own language\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"0.199203187250996%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-womens-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmwh","sideBox":"Learn more about [BMC Women's Health](http://bmcwomenshealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bmwh/default.aspx","title":"BMC Women's Health","twitterHandle":"","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Early Detection of Cancer, Sociodemographic Factors, Health Inequities, Ethnicity, Peru","lastPublishedDoi":"10.21203/rs.3.rs-4078937/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4078937/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eDespite guidelines and increased healthcare resources, there are disparities in coverage of screening cancer services for non-white communities, addressing these health inequalities is crucial in multicultural countries like Peru. For this reason, the aim was evaluating ethnic inequalities in the women proportion that use cancer screening services in Peruvians regions.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eAn ecological was used to assess the ethnic inequalities in the proportion of women use of general cancer screening, clinical breast examination, mammography, and pap test in the 25 regions of Peru. The inequalities were approach by estimating the GINI coefficient among ethnic groups based on various sociodemographic characteristics, and the annual variation of the GINI coefficient.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eIn Peruvians regions there is greater inequality in general cancer screening services among the indigenous (GINI: 0.321) and afroperuvians (GINI: 0.415), which have a GINI coefficient almost twice that of the white or mestizo group (GINI: 0.183). Also, sociodemographic characteristics such as low educational level, low income, living in rural areas, being over 64 years old, and lack of health insurance mediate these inequalities in the use of cancer screening services. In the temporal variation, an increase in inequality was identified to afroperuvians and indigenous groups after 2020.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eIn Peruvian regions there are marked ethnic inequalities in use of cancer screening services for indigenous and afroperuvians groups compared to the white or mestizo group, especially in those regions with larger populations with adverse socioeconomic conditions that have worsened for these ethnic groups after the COVID-19 pandemic in Peru.\u003c/p\u003e","manuscriptTitle":"Ethnic inequalities in the access of cancer screening services for women´s in Peru","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-20 07:18:44","doi":"10.21203/rs.3.rs-4078937/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-04-18T07:56:09+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-04-17T18:17:00+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"4110c50e-2a4a-41be-a545-f8b314918570","date":"2024-04-16T13:45:36+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-04-16T02:45:48+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-04-15T18:40:23+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-04-13T14:45:22+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"a3031fed-6ca9-43cd-b04a-08e627685368","date":"2024-04-11T01:05:32+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"6837284a-1c0b-490f-927a-7e205a6a717f_SNPRID","date":"2024-04-10T18:00:03+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"6807fa68-ec1f-4b33-b0b1-a96228ab8707","date":"2024-04-10T12:12:26+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"1084a3c1-706e-4ebd-ac17-f39565338b65","date":"2024-04-09T00:04:17+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"b4a35558-5b46-4163-bc1f-52dd09bc90d5","date":"2024-04-08T20:37:16+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"0726096a-178b-4ba3-b05f-b0a58f51b148","date":"2024-04-08T16:32:32+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"fbb0399f-5001-4e64-974c-281468db04af","date":"2024-04-05T15:41:12+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"b020e46e-b8c8-45cb-96b6-105b8743ed9e","date":"2024-04-05T14:46:48+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"41c002fc-2e16-4ce4-9e98-42030940694c","date":"2024-04-05T12:14:33+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-04-05T08:09:24+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-04-04T14:46:29+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-04-02T04:24:44+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-03-18T06:40:28+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Women's Health","date":"2024-03-12T00:51:20+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-womens-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmwh","sideBox":"Learn more about [BMC Women's Health](http://bmcwomenshealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bmwh/default.aspx","title":"BMC Women's Health","twitterHandle":"","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"a85b85d9-dc1d-45c7-8012-63882fd5b15f","owner":[],"postedDate":"March 20th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-08-01T17:07:56+00:00","versionOfRecord":{"articleIdentity":"rs-4078937","link":"https://doi.org/10.1186/s12905-024-03225-6","journal":{"identity":"bmc-womens-health","isVorOnly":false,"title":"BMC Women's Health"},"publishedOn":"2024-07-24 16:15:55","publishedOnDateReadable":"July 24th, 2024"},"versionCreatedAt":"2024-03-20 07:18:44","video":"","vorDoi":"10.1186/s12905-024-03225-6","vorDoiUrl":"https://doi.org/10.1186/s12905-024-03225-6","workflowStages":[]},"version":"v1","identity":"rs-4078937","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4078937","identity":"rs-4078937","version":["v1"]},"buildId":"zQwnuV7TCBrMSSSToR1PI","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}