Access to Sexual and Reproductive Health Services for Migrant Women in Colombia: A Mixed Methods Approach

Access to Sexual and Reproductive Health Services for Migrant Women in Colombia: A Mixed Methods Approach | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Access to Sexual and Reproductive Health Services for Migrant Women in Colombia: A Mixed Methods Approach Laura Margarita Bello-Álvarez, Dauris Lineth Mejía-Pérez, Jorge Andres Rubio-Romero, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7359134/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Introduction: Migration and forced displacement present critical challenges to sexual and reproductive health (SRH) systems. Colombia hosts over 2.8 million Venezuelan migrants and a high number of internally displaced persons, offering a unique context to evaluate SRH service access and outcomes. Methods: A mixed-methods study was conducted using a parallel convergent design. Quantitative data were collected from 929 women hospitalized for obstetric events in Bogotá and Cali between November 2023 and May 2024. Outcomes and service access were compared across migrant, forcibly displaced, and non-migrant groups. Qualitative data were collected via semi-structured interviews with women, healthcare providers, and stakeholders. The data were analyzed using a combined Tanahashi Coverage Model, Social Determinants of Health, and Complex Systems Theory framework. Results: Quantitative findings revealed no significant differences in antenatal care utilization or testing rates across groups. However, maternal mortality and perinatal mortality were higher among migrant women. Forcibly displaced women had the lowest preeclampsia and severe maternal morbidity rates. Preconception care uptake was critically low in all groups (<18%). Qualitative insights exposed barriers such as legal precarity, insurance fragmentation, stigma, and limited cultural competence, undermining effective service coverage and care quality despite nominal access. Conclusions: While SRH service availability appeared equitable, effectiveness varied by migration status. Structural and systemic barriers compromise outcomes, especially for mobile populations. A complex systems lens reveals how fragmented governance, feedback loops, and sociocultural exclusion drive disparities. Addressing these requires adaptive, culturally responsive policies that account for layered vulnerabilities. Figures Figure 1 Figure 2 CONTRIBUTIONS TO LITERATURE This is the first study in Colombia, and one of the few in Latin America, to systematically compare access to sexual and reproductive health (SRH) services among migrant, forcibly displaced, and non-migrant women using a mixed-methods approach. The study demonstrates that while reported service coverage rates were similar across groups, effectiveness of care and outcomes varied, with migrant women experiencing higher maternal and perinatal mortality. Our findings highlight how structural barriers—such as legal precarity, fragmented insurance, stigma, and lack of cultural competence—undermine effective SRH access despite legal guarantees of universality. By applying complexity science and social determinants of health frameworks, the study provides novel insights into how health systems in low- and middle-income countries adapt, or fail to adapt, to migration-driven pressures. The results can inform policymakers and health professionals in designing more inclusive, culturally responsive, and adaptive SRH strategies to address layered vulnerabilities among mobile populations. BACKGROUND Human mobility represents a growing phenomenon with profound repercussions on public health systems. At its core, human mobility reflects both the pursuit of opportunity and the need for protection, linked directly to aspirations for improved living standards, healthcare, education, and overall well-being. In 2020, more than 281 million people, equivalent to 3.1% of the global population, were classified as international migrants, approximately half of whom are women ( 1 ). Migration responds to urgent health needs, including sexual and reproductive health (SRH) ( 2 – 4 ). Despite international commitments to human rights and universal health coverage, women in situations of mobility continue to face persistent barriers in accessing SRH services, even within well-established health systems. These individuals face unique vulnerabilities and frequently experience disruptions in their access to essential health services. Delay in prenatal care among undocumented migrants in Europe is associated with poorer perinatal outcomes ( 5 ). Late obstetric diagnoses, delays, and limitations stemming from immigration status, lack of knowledge about rights, and linguistic or cultural barriers have been reported in the United States and Canada ( 3 , 6 ). Colombia has emerged as a critical case within the regional migration landscape due to the large influx of Venezuelan nationals, which rose from 23,573 in 2014 to over 2.8 million by 2024 ( 7 ). This demographic shift has placed considerable strain on the healthcare system, particularly in urban centers such as Bogotá and Cali. Migrant women require a broad range of SRH services, including contraception, obstetric care, and support in cases of gender-based violence. The rise in severe maternal morbidity and mortality within this population reflects both the extent of their needs and the limited response capacity of the system ( 8 , 9 ). Although the country has adopted a progressive regulatory framework for external migrants, such as the Temporary Protection Statute ( 10 ), practical barriers persist, undermining effective access, continuity of care, and the quality of SRH services for both migrant and host populations. Colombian women forcibly displaced by the armed conflict simultaneously face severe structural barriers to SRH. In affected areas, more than 50% of women do not receive professional prenatal care, leading to adverse perinatal outcomes. ( 11 ) These conditions are associated with higher rates of adolescent fertility and maternal mortality, linked to limited access to contraceptives, fragmented prenatal care, gender violence, and insufficient preparedness among healthcare personnel to manage obstetric emergencies ( 12 ). Low levels of intergenerational sexual education and reduced contraceptive use among displaced adolescents have been documented in Bogotá ( 13 ). Administrative barriers and a lack of cultural adaptation in service provision have been attributed to exclusion from the healthcare system and limited access to prenatal care in Cali ( 14 ). These tensions are relevant in Latin America, and particularly in Colombia, given the sustained increase in both external migratory flows and internal forced displacement. Although regulatory frameworks that guarantee access to healthcare regardless of nationality or migratory status exist, actual access is marked by exclusion, misinformation, and institutional fragmentation ( 14 ). This gap between legal provisions and lived experiences underscores the need for studies that integrate quantitative and qualitative perspectives to understand perceived barriers, the social determinants involved, and institutional responses, especially in cities such as Bogotá and Cali, where all forms of human mobility converge. Despite Colombia’s progressive legal framework, many barriers persist in practice ( 10 , 15 ). These access gaps are compounded by structural factors, such as poverty, irregular legal status, fragmented insurance regimes, xenophobia, and limited cultural competence among health providers ( 16 , 17 ). A framework that captures both individual experience and system complexity is required to understand how these dimensions interact to shape health service use and outcomes. Although a growing body of literature exists on pregnant migrant women living in Colombia, most studies provide partial diagnoses based on exclusively quantitative or qualitative approaches. Understanding the interaction between structural conditions, institutional trajectories, and lived experiences requires a mixed-methods approach that can quantify access gaps while also exploring symbolic, cultural, and relational barriers ( 17 , 18 ). This study employs a multi-theoretical analytic framework that combines three lenses. The Tanahashi model for health service coverage conceptualizess service access in five dimensions: availability, accessibility, acceptability, contact (utilization), and effective coverage ( 19 ). This model enables a structured analysis of the stages at which health service access is either enabled or interrupted. The Social Determinants of Health (SDH) framework identifies how health inequities are created or exacerbated by upstream factors, such as legal status, income, education, ethnicity, and gender-based violence ( 20 ). This lens highlights the structural roots of unequal access to SRH across different populations. Thirdly complex systems theory (CST), which views health systems as adaptive, nonlinear, and interconnected networks. This approach seeks to facilitate the interpretation of how the Colombian healthcare system has organized or struggled to adapt in response to the pressures of migration and displacement, revealing feedback loops, fragmentation, and unintended consequences in service delivery ( 21 , 22 ). Together, these frameworks offer a comprehensive lens through which to analyze both the barriers and facilitators of SRH access and the health system’s organizational response to human mobility. This study aimed to assess differences in maternal and perinatal outcomes between migrant, forcibly displaced, and non-migrant women, examine barriers and facilitators for SRH services access through the lived experiences of women in diverse mobility contexts, healthcare professionals, and stakeholders, and analyze how the Colombian healthcare system has adapted to address the SRH needs of mobile and vulnerable populations. METHODS A mixed-methods study was conducted using a parallel convergent design according to Creswell’s model ( 17 ) (Fig. 1 ). Quantitative Study Design This prospective cohort study included women of reproductive age who sought care for obstetric events (delivery regardless of the route or fetal outcome, abortion / miscarriage care, ectopic pregnancy, and gestational trophoblastic disease) and who were invited to participate during admission to the obstetrics and gynecology wards at two hospitals. We used a non-probabilistic, sequential sampling method, inviting all women who sought services at the participating institutions during the study period (November 2023 - May 2024), regardless of their immigration status, health services coverage, or other variables that might have influenced sample selection. Inclusion and exclusion criteria All pregnant women who were admitted to participating hospitals for obstetric care and who agreed to participate were included in the study. Healthcare professionals on call at the obstetrics and gynecology wards at any of the hospitals during one of the sessions of qualitative data collection and who accepted to be interviewed with audio or audio and video recording and stakeholders related to the local, regional, or national SRH response who accepted to participate in interviewing with audio or audio and video recording. Women, healthcare providers, and stakeholders who refused to participate in the study and those who had communication difficulties or did not understand the scope of the study were excluded. Data Collection The study was conducted in Cali at the Hospital Universitario del Valle Evaristo García and in Bogotá at the Hospital de Engativa - Sub Red Integrada de Servicios Norte de Bogotá D.C . Patients were recruited at the time of obstetric care admission. Data were collected from the time of admission for obstetric care until discharge. Data were collected using a Google Forms® formulary that was applied to every woman who agreed to participate in the study. Data on social and demographic characteristics, obstetric history, clinical variables for current pregnancy, access to reproductive health care services (preconception and antenatal care, contraception, STI screening and treatment, gender-based violence), and maternal and neonatal outcomes of current pregnancy were collected. Data Analysis The primary exposure variable was migratory status, which was classified into three categories: migrant, forcibly displaced, and non-migrant. Participants were grouped accordingly. Descriptive statistics were used to characterize the study population. Quantitative variables were assessed for normality using the Shapiro-Wilk or Kolmogorov-Smirnov tests. Variables following a normal distribution were summarized using means and standard deviations and analyzed using analysis of variance (ANOVA) tests, whereas non-normally distributed variables were described using medians and interquartile ranges and analyzed with Kruskal-Wallis tests. The absolute and relative frequencies of the categorical variables were described and compared using the chi-square test. Associations between migratory status and access to sexual and reproductive health (SRH) services, as well as maternal and perinatal outcomes, were first evaluated through univariate analyses using chi-square tests. Subsequently, multivariate logistic regression models were constructed for each outcome variable, with migratory status being the main independent variable. These models were adjusted for potential confounding variables identified a priori based on theoretical relevance and previous literature, including age, parity, education level, health insurance status, ethnicity, and city of care.All statistical analyses were performed using STATA v.18®, and a two-tailed p-value of < 0.05 was considered statistically significant. Qualitative Study Design and Theoretical Framework This qualitative study employed a phenomenological-hermeneutic design to explore the lived experiences of migrant, forcibly displaced, and non-migrant women in accessing sexual and reproductive health (SRH) services in Colombia. The study also examined the experiences of local, regional, and national healthcare providers caring for migrant women and stakeholders. Rooted in phenomenology, the study sought to understand how individuals perceive and make meaning of healthcare encounters, while the hermeneutic approach allowed for interpretation of these experiences within broader structural and institutional contexts. The analytic framework was developed by integrating the three complementary models mentioned above. These frameworks enabled a multilevel, interdisciplinary examination of access barriers and facilitators, linking personal narratives with health system dynamics. (Fig. 2 ) Study Population and Sampling Strategy Women included in the quantitative branch of the study were invited to participate in the qualitative branch. We selected five women from each migratory status group (migrant, forcibly displaced, and non-migrant) by sequential sampling during three interviews, one every two months during the study period in each city. Women who agreed to participate were interviewed in a private space inside each hospital before discharge. During the same session, we interviewed healthcare providers on call at each hospital’s obstetrics and gynecology ward. The professionals included in the study were randomly selected only by chance of being on call during the qualitative data collection session. Stakeholders were invited to participate using a snowball strategy, inviting professionals linked to the different local or regional health secretariats and organizations linked to the Ministry of Health response for SRH. Although the delegates of the Ministry of Health were invited to participate in the study, this key stakeholder did not provide a positive response. We interviewed 44 people, 30 women, and 14 healthcare professionals between service providers and stakeholders. Data Collection Procedures Semi-structured interviews were conducted in Spanish to gather data, guided by a tool aligned with the Tanahashi dimensions and informed by the SDH framework. The guide explored perceptions of service availability, legal and economic access, experiences of stigma or cultural dissonance, quality of provider interactions, and perceived health outcomes. The guide for health professionals and stakeholders focused on system design, legal framework, resource coordination, migration response, and equity implementation. All interviews were audio and video recorded, transcribed verbatim using Trint®, and revised by two researchers. Two trained researchers (LMBA, DLMP) with expertise in qualitative SRH research and migrant health conducted the interviews in private, safe settings. Data Analysis A multi-framework analytic strategy was applied. Phenomenological coding was used to identify experiential themes across narratives inductively. A deductive coding phase followed, categorizing content into the five Tanahashi dimensions. The SDH framework was used to map each barrier or facilitator to structural determinants (e.g., legal status, poverty, and discrimination). Complex systems theory was employed for interpretive synthesis, examining how interactions among policies, institutions, and feedback mechanisms shape access outcomes and health system resilience. This layered approach allowed individual voices to be heard while situating them within broader structural and systemic patterns. AtlasTi 24® software was used for coding, and analytical triangulation was conducted by two independent researchers (LMBA and DLMP). Ethical considerations The ethics committees of Universidad del Valle (Code: 034 − 022) and Hospital Universitario del Valle (Code: 050-2023) in Cali and Universidad Nacional de Colombia (B.FM.1.002-CE-224-23) and Hospital Engativa (Code: SNACEI-142) in Bogotá approved this protocol. Written informed consent was obtained before data collection and for participation in the study’s quantitative branch. In the case of underaged women, informed assent was obtained from the adolescents and consent was obtained from the parents, carer, or legal guardian. The participants included in the qualitative branch of the study provided written consent for interview participation and for audio and/or video recording of the interview. RESULTS Quantitative Results We collected data from 929 women, 424 (45.6%) in Bogotá and 505 (55,4%) in Cali. A total of 250 (26.9%) women were migrant, 134 (14,4%) were forcibly displaced, and 545 (58,7%) were non-migrant women. Additionally, 116 (86.6%) displaced women were enrolled in Cali, and 150 (60%) migrant women were enrolled in Bogotá. The median age of the migrant women in the sample was 24 years (IQR: 20–29), ranging from 13 to 53 years. The majority of respondents (94.8%) resided in urban areas, and 87.2% originated from urban settings. Educational attainment was concentrated at the secondary level (72.8%), with 19.2% achieving tertiary education and 0.4% completed postgraduate studies. Regarding marital status, 89.2% were married and 10.8% were single. Ethnically, 98.4% identified themselves as non-Indigenous and non-Afro descendants. The income levels of migrant women were notably low, with a mean weekly income of 83 USD (SD: 47.5). A substantial proportion (76.8%) lived below the monetary poverty line (less than $ 109 USD per month) and 17.2% below the extreme poverty line (less than $ 54 USD per month). ( 23 ) In terms of social security, only 3.6% of the population contributed to the healthcare system, 54% were subsidized, and 42.4% remained uninsured. Reports of gender violence affected 10% of migrant women. The median age of forcibly displaced women was 25.5 years (IQR: 21–31), ranging from 13 to 40 years. Unlike migrants, a significant portion (64.9%) originated from rural areas, yet 81.3% resided in urban areas at the time of the study. Educational attainment was similar to that of migrants, with 69.4% completing secondary education and 17.2% attaining tertiary education. In terms of ethnicity, 60.4% of these women identified themselves as Afro descendant and 9.7% as Indigenous. Forcibly displaced women had a mean weekly income of USD 67 (SD: 39.5), which was lower than that of migrants. The proportion of people living below the monetary poverty line was higher (86.6%), and 35.8% were living in extreme poverty. Regarding social security, 11.9% contributed, 88.1% were subsidized, and none were uninsured. Experiences of gender violence were reported by 11.2% of forcibly displaced women. The median age of non-migrant women was 26 years (IQR: 22–31), ranging from 13–48 years, with a slightly higher representation in the tertiary education category (27.5%). Most non-migrant respondents (88.3%) resided in urban areas, and 82.2% originated from urban settings. The majority were married (82.2%) and identified themselves as non-Indigenous and non-Afrodescendants (77.2%). Their mean weekly income was USD 108 (SD: 78.2), the highest among the three groups. Despite higher incomes, 57.1% and 11.2% of the non-migrant respondents lived below the monetary poverty line and below the extreme poverty line, respectively. In terms of social security, 24.2% of this population contributed to the health care system, 75.4% were subsidized by the system, and 0.4% were uninsured. Gender violence was reported by 8.4% of non-migrant women (Table 1 ). Table 1 Social and demographic characteristics Age Migrant Displaced Non migrant Total P Mean 25.3 26.1 26.8 26.3 0.804 SD 6.43 6.34 6.59 6.54 N 250 134 545 929 Min 13 13 13 13 Max 53 40 48 53 City Migrant Displaced Non migrant Total p Bogota 150 (60%) 18 (13.4%) 256 (46.9%) 424 (45.6%) 0.000 Cali 100 (40%) 116 (86.6%) 289 (53%) 505 (55.4%) Total 250 (100%) 134 (100%) 545 (100%) 929 (100%) Marital Status Migrant Displaced Non migrant Total p Single 27 (10.8%) 33 (24.6%) 97 (17.8%) 157 (16.9%) 0.002 Maried 223 (89.2%) 101 (75.4%) 448 (82.2%) 772 (83.1%) Total 250 (100%) 134 (100%) 545 (100%) 929 (100%) Ethnicity Migrant Displaced Non migrant Total p Afrodescendant 3 (1.2%) 81 (60.44%) 117 (21.5%) 201 (21.6%) 0.000 Indigenous 1 (0.4%) 13(9.7%) 7(1.3%) 21 (2.3%) None 246 (98.4%) 40 (29.8%) 421 (77.2%) 707 /76.1%) Total 250 (100%) 134 (100%) 545 (100%) 929 (100%) Education Attainment Migrant Displaced Non migrant Total p Iliteracy 0 (0) 5 (3.7%) 2 (0.37%) 7 (0.75%) 0.000 Primary 19 (7.6%) 13 (9.7%) 37 (6.7%) 69(7.4%) Secondary 182 (72.8%) 93(69.4%) 353 (64.8%) 628 (67.6%) Tertiary 48(19.2%) 23(17.2%) 150 (27.5%) 221 (23.8%) Postgraduate 1 (0.4%) 0 (0%) 3(0.55%) 4 (0.4%) Schooling years Migrant Displaced Non migrant Total p Mean 10.7 9.9 10.8 10.6 0.001 SD 2.78 3.3 2.6 2.79 N 250 134 545 929 Area of Origin Migrant Displaced Non migrant Total p Urban 218 (87.2%) 47 (35.1%) 448 (82.2%) 713 (76.8%) 0.000 Rural 32 (12.8%) 87 (64.9%) 97 (17.8%) 216 (23.2%) Total 250 (100%) 134 (100%) 545 (100%) 929 (100%) Area of Residence Migrant Displaced Non migrant Total p Urban 236 (94.4%) 107 (79.8%) 478 (87.7%) 0 0.000 Rural 14 (5.6%) 27 (20.2%) 67 (12.3%) 108(11.6%) Total 250 (100%) 134 (100%) 545 (100%) 929 (100%) Family Income in USD/week Migrant Displaced Non migrant Total p Mean 83 67 108 95 0.000 SD 47.5 39.5 78.2 68.3 N 250 134 545 929 Family living below monetary poverty line Migrant Displaced Non migrant Total p No 58 (23,2%) 18 (13,4%) 234 (42,9%) 310 (33,4%) 0.000 Yes 192 (76,8%) 116 (86,6%) 311 (57,1%) 619 (66,7%) Total 250 (100%) 134 (100%) 545 (100%) 929 (100%) Family living below extreme poverty line Migrant Displaced Non migrant Total p No 207 (82,8%) 86 (64,2%) 484 (88,8%) 777 (83,6%) 0.000 Yes 43 (17,2%) 48 (35,8%) 61 (11,2%) 152 (16,4%) Total 250 (100%) 134 (100%) 545 (100%) 929 (100%) Social Security Afiliation Migrant Displaced Non migrant Total p Contribute 7 (2.8%) 13 (9.7%) 120 (22%) 140 (15.1%) 0.000 Subsidized 135 (54.8%) 118 (88.1%) 411 (75.4%) 664 (71.5%) Special Regime 2 (0.8%) 3 (2.2%) 12 (2.2%) 17 (1.83%) Non Affiliated 106 (42.4%) 0 (0%) 2 (0,37%) 108 (11.6%) Total 250 (100%) 134 (100%) 545 (100%) 929 (100%) Gender Violence Victim Migrant Displaced Non migrant Total p No 225 (90%) 119 (88.8%) 499 (91.6%) 843 (90.8%) 0.550 Yes 25 (10%) 15 (11.2%) 46 (8.4%) 86 (8.3%) Total 250 (100%) 134 (100%) 545 (100%) 929 (100%) OR 100.2 (60.5–165.8) p0.000 113.6 (61.7 -209.1) p 0.000 Obstetric Outcomes Migrant women had a mean number of pregnancies of 1.98 (SD: 1.24), slightly higher than non-migrants (1.88). The proportion of pregnancies resulting in vaginal or cesarean births was slightly lower among migrants (92.7%) than among non-migrants (93.4%), although the difference was not statistically significant (p = 0.129). The rate of pregnancy loss was higher among migrants (7.3%) than among non-migrants (6.6%). Vaginal births were more common among migrants (62.9%) than among non-migrants (57.7%). The mean gestational age at birth was nearly identical between the groups (37.8 vs. 37.9 weeks, p = 0.854). The mean neonatal birth weight was slightly higher among migrants (2943.3 vs. 2929.4 g, p = 0.894). Preterm birth rates were slightly lower among migrants (15.3%) than among non-migrants (16.1%), with an OR of 0.94 (95%CI 0.61–1.45, p = 0.789). The proportion of small vulnerable newborns ( 24 ) was also slightly lower among migrants (28.3%) than among non-migrants (30.5%), with an OR of 0.90 (95%CI 0.64–1.27, p = 0.552). Neonatal Intensive Care Unit (NICU) admissions were lower among migrant newborns (17.9%) than among non-migrants (22.4%), although the adjusted OR was not significant (0.68, 95% CI: 0.45–1.02, p = 0.065). We observed 4 and 1 stillbirths for the migrants and non-migrants groups, respectively (1.6% vs. 0.2%) with an OR of 7.4 (0.82–66.87, p = 0.075) although the small number of events makes this association not statistically significant. Furthermore, perinatal mortality was higher among migrants (37.3 vs. 18.7 per 1,000 live births). Maternal mortality occurred only among migrants at a rate of 400 per 100,000 live births. This was the only group in which this critical maternal outcome occurred. Preeclampsia was reported in 16.4% of migrant women compared with 18.7% of non-migrants, although the difference was not statistically significant. Severe maternal morbidity was slightly lower among migrants (18.4%) than among non-migrants (20.5%, p = 0.045). Forcibly displaced women had a slightly higher mean number of pregnancies (2.22, SD: 1.54) than non-migrants (1.88). Pregnancy loss was significantly lower among displaced women (2.3%) than among non-migrants (6.6%). Vaginal delivery was slightly more common among displaced women (64.8%) than among non-migrants (57.7%), whereas cesarean sections were less common (35.2% vs. 42.3%, p = 0.210). The gestational age and birth weight were similar across both groups, with no statistically significant differences. Preterm birth rates were the lowest among displaced women (10.2%) compared to non-migrants (16.1%), with an OR of 0.59 (0.32–1.09, p = 0.097). The rates of small vulnerable newborns were also slightly lower (29.9% vs. 30.5%, OR: 0.97, 95% CI: 0.64–1.49, p = 0.898). NICU admissions were lower among displaced women (16.1%) than among non-migrants (22.4%), although the difference was not statistically significant (adjusted OR: 0.94, 95% CI: 0.54–1.63, p = 0.830). The stillbirth rate was also lower among displaced women (0.8% vs. 0.2%, p = 0.146). Perinatal mortality was lower among displaced women at 7.5 per 1,000 live births compared with 18.7 per 1,000 among non-migrants. No maternal deaths were reported in this group. Preeclampsia was significantly lower among displaced women (8.2% vs. 18.7%, p = 0.014). Severe maternal morbidity was also lower among displaced women (11.2%) than among non-migrants (20.5%, p = 0.045) (Table 2 ). Table 2 Maternal and neonatal outcomes Number of pregnancies Migrant Displaced Non migrant Total p Mean 1.98 2.22 1.88 1.95 0.003 SD 1.24 1.54 1.25 1.29 N 250 134 545 929 Pregnancy Outcome Migrant Displaced Non migrant Total p Vaginal/ Cesaran Birth 229 (91.6%) 128 (95.5%) 499 (91.4%) 856 (92%) 0.445 Miscarriage 13 (5.2%) 3 (2.2%) 27 (4.9%) 43 (4.6%) Ectopic Preganancy 4 (1.6%) 0 (0%) 8 (1.5%) 13 (1.3%) Molar Pregnancy 1 (0.4%) 0 (0%) 0 (0%) 1 (0.1%) Abortion 3 (1.2%) 3 (2.2%) 12 (2.2%) 18 (1.9%) Total 250 (100%) 134 (100%) 545 (100%) 929 (100%) Delivery Route Migrant Displaced Non migrant Total p Vaginal Birth 144 (62.9%) 83 (64.8%) 288 (57.7%) 515 (60.2%) 0.210 Cesarean Section 85 (37.1%) 45 (35.2%) 211 (42.3%) 341 (39.8%) Total 229 (100%) 128 (100%) 499 (100%) 856 (100%) Gestational Age at birth Migrant Displaced Non migrant Total p Mean 35.6 37 35.6 35.8 0.000 SD 8.2 5.3 7.9 7.7 N 250 134 545 929 Neonatal Birthweigth Migrant Displaced Non migrant Total p Mean 2943.3 2950.6 2929.4 2936.3 0.811 SD 534.7 514.5 616.7 520.7 N 229 128 498 855 Preterm Birth Migrant Displaced Non migrant Total p No 194(84.7%) 115 (89.8%) 419 (83.9%) 727 (85%) 0.245 Yes 35 (15.3%) 13 (10.2%) 80 (16.1%) 128 (15%) Total 229 (100%) 128 (100%) 499 (100%) 856 (100%) Small Vulnerable Newborn Migrant Displaced Non migrant Total p No 162 (71.7%) 89 (70.1%) 344 (69.5%) 595 (70.2%) 0.837 Yes 64 (28.3%) 38 (29.9%) 151 (30.5%) 253 (29.8%) Total 226 (100%) 127 (100%) 495 (100%) 848 (100%) Neonatal Intensive Care Unit Admition Migrant Displaced Non migrant Total p No 179 (82.1%) 104 (83.9%) 394 (77.6%) 677 (79.7%) 0.170 Yes 39 (17.9%) 20 (16.1%) 114 (22.4%) 173 (20.3%) Total 218 (100%) 124 (100%) 508 (100%) 850 (100%) Stillbirth Migrant Displaced Non migrant Total p No 246 (98.4%) 133 (99.2%) 544 (99.8%) 923 (99.3%) 0.068 Yes 4 (1.6%) 1 (0.8%) 1 (0.2%) 6 (0.65%) Total 250 (100%) 134 (100%) 545 (100%) 929 (100%) Perinatal Mortality Migrant Displaced Non migrant Total p No 241(96.4%) 133 (99.2%) 535 (98.2%) 909 (97.8%) 0.135 Yes 9 (3.6%) 1 (0.8%) 10 (1.8%) 20 (2.2%) Total 250 (100%) 134 (100%) 545 (100%) 929 (100%) Perinatal Mortality Rate 37.3/1000 livebirths 7.5/1000 livebirths 18.7/1000 livebirths 22/1000 livebirths RR 1.96 (0.81–4.77) p 0.207 0.41 (0.05–3.15) p 0.702 Maternal Mortality Migrant Displaced Non migrant Total p No 249 (99.6%) 134 545 (100%) 928 (99.0%) 0.257 Yes 1 (0.4%) 0 (0%) 0 (0%) 1 (0.1%) Total 250 (100%) 134 (100%) 545 929 (100%) Maternal Mortality Rate 400/100000 livebirths Preeclampsia Migrant Displaced Non migrant Total p No 209 (83.6%) 123 (91.8%) 443 (81.3%) 775 (83.4%) 0.014 Yes 41 (16.4%) 11 (8.2%) 102 (18.7%) 154 (16.6%) Total 250 (100%) 134 (100%) 545 (100%) 929 (100%) Postpartum Haemorrage Migrant Displaced Non migrant Total p No 242 (96.9%) 131 (97.8%) 524 (96.2%) 897 (96.6%) 0.636 Yes 8 (3.2%) 3 (2.2%) 21 (3.8%) 32 (3.4%) Total 250 (100%) 134 (100%) 545 (100%) 929 (100%) Severe Maternal Morbidity (Near Miss) Migrant Displaced Non migrant Total p No 204 (81.6%) 119 (88.8%) 433 (79.5%) 756 (81.4%) 0.045 Yes 46 (18.4%) 15 (11.2%) 112 (20.5%) 173 (18.6%) Total 250 (100%) 134 (100%) 545 (100%) 929 (100%) Access to Sexual and Reproductive Health Services The average number of antenatal visits was similar across the groups, with migrant women attending 5.7 visits, forcibly displaced women attending 5.8 visits, and non-migrant women attending 5.9 visits (p = 0.150). Similarly, the mean gestational age at the first antenatal visit showed no significant differences (10.3, 10.8, and 11.2 weeks for migrants, displaced, and non-migrants, respectively; p = 0.259). These findings suggest that antenatal care attendance is equitable regardless of migration status. The syphilis screening rates were comparably high among migrants (99.2%), forcibly displaced women (99.2%), and non-migrants (98.7%) (p = 0.764). The prevalence of gestational syphilis did not significantly differed between groups (5.2% among migrants, 6.7% among displaced, and 5.1% among non-migrants; p = 0.760). Similarly, congenital syphilis rates were consistent at 4.0%, 4.5%, and 3.8%, respectively (p = 0.947). All groups received a comparable average number of HIV tests during pregnancy (2.4–2.5 tests, p = 0.999). The prevalence of HIV diagnosis before and during pregnancy was low and did not differ significantly by group (pregestational: migrants, 0.4%; displaced, 1.5%; non-migrants, 1.5%; p = 0.40707; during pregnancy: migrants, 0.8%; displaced, 1.5%; non-migrants, 0.4%, p = 0.325), although internally displaced women had a higher prevalence of HIV infection than the other two groups.Hepatitis B testing rates were similarly high (91.2%; migrants, 94.1%; displaced, 94.5%; non-migrantsp = 0.208). Uptake of preconception care was low across all groups (17.6%, 17.2%, and 18.3% migrants, displaced, and non-migrants, respectively; p = 0.935), indicating a critical gap in early maternal health interventions. Preconception contraceptive use was reported by 44% of migrants, 35.1% of displaced, and 43.8% of non-migrants (p = 0.161). Knowledge about abortion access was moderately low but comparable among groups (migrants, 45.6%; displaced, 52.2%; non-migrants, 47.0%; p = 0.444). Reports of gender-based violence victimization were similar across populations (3.2%, 3.8%, and 4.6%, respectively; p = 0.647) (Table 3 ). Table 3 SRH Service Access Number of Antenatal Visits Migrant Displaced Non migrant Total p Mean 5.7 5.8 5.9 5.8 0.150 SD 3.3 3.2 2.9 3.1 N 250 134 545 929 Gestational age at First Antenatal Visit Migrant Displaced Non migrant Total p Mean 10.3 10.8 11.2 10.9 0.259 SD 7.3 8.3 7.7 7.7 N 250 134 545 929 Syphilis tested Migrant Displaced Non migrant Total p No 2 (0.8%) 1 (0.8%) 7 (1.3%) 10 (1.1%) 0.764 Yes 248 (99.2%) 133 (99.2%) 538 (98.7%) 919 (98.9%) Total 250 (100%) 134 (100%) 545 (100%) 929 (100%) Gestational Syphilis Migrant Displaced Non migrant Total p No 237 (94.8%) 125 (93.3%) 517 (94.9%) 879 (94.6%) 0.760 Yes 13 (5.2%) 9 (6.7%) 28 (5.1%) 50 (5.4%) Total 250 (100%) 134 (100%) 545 (100%) 929 (100%) Congenital Syphylis Migrant Displaced Non migrant Total p No 240 (96%) 128 (95.5%) 524 (96.2%) 892 (96%) 0.947 Yes 10 (4%) 6 (4.5%) 21 (3.8%) 37 (4%) Total 250 (100%) 134 (100%) 545 (100%) 929 (100%) Number of HIV Test During Pregnancy Migrant Displaced Non migrant Total p Mean 2.4 2.5 2.5 2.4 0.999 SD 0.97 0.97 0.97 0.97 N 250 134 545 929 HIV Pregestational Diagnosis Migrant Displaced Non migrant Total p No 249 (99.6%) 132 (98.5%) 537 (98.5%) 918 (98.8%) 0.407 Yes 1 (0.4%) 2 (1.5%) 8 (1.5%) 11 (1.2%) Total 250 (100%) 134 (100%) 545 (100%) 929 (100%) HIV Diagnosis During Preganancy Migrant Displaced Non migrant Total p No 247 (99.2%) 130 (98.5%) 535 (99.6%) 912 (99.4%) 0.325 Yes 2 (0.8%) 2 (1.5%) 2 (0.4%) 6 (0.6%) Total 250 (100%) 134 (100%) 545 (100%) 929 (100%) Hepatitis B Test Migrant Displaced Non migrant Total p No 22 (8.8%) 8 (5.9%) 30 (5.5%) 60 (6.5%) 0.208 Yes 228 (91.2%) 126 (94.1%) 515 (94.5%) 869 (93.5%) Total 250 (100%) 134 (100%) 545 (100%) 929 (100%) Preconceptional Care Migrant Displaced Non migrant Total p No 206 (82.4%) 111 (82.8%) 445 (81.6%) 762 (82%) 0.935 Yes 44 (17.6%) 23 (17.2%) 100 (18.3%) 167 (18%) Total 250 (100%) 134 (100%) 545 (100%) 929 (100%) Preconceptional Contraception Migrant Displaced Non migrant Total p No 140 (56%) 87 (64.9%) 306 (56.2%) 533 (57.4%) 0.161 Yes 110 (44%) 47 (35.1%) 239 (43.8%) 396 (42.6%) Total 250 (100%) 134 (100%) 545 (100%) 929 (100%) Abortion Access Knowledge Migrant Displaced Non migrant Total p No 136 (54.4%) 64 (47.8%) 289 (53%) 489 (52.6%) 0.444 Yes 114 (45.6%) 70 (52.2%) 256 (47%) 440 (47.4%) Total 250 (100%) 134 (100%) 545 (100%) 929 (100%) Gender Violence Victim Migrant Displaced Non migrant Total p No 239 (96.8%) 128 (96.2%) 516 (95.4%) 883 (95.9%) 0.647 Yes 8 (3.2%) 5 (3.8%) 25 (4.6%) 38 (4.1%) Total 250 (100%) 134 (100%) 545 (100%) 929 (100%) OR 0.69 (0.31–1.55) p 0.371 0.81 (0.30–2.15) p 0.667 Qualitative Results Availability of the services Qualitative narratives revealed gaps between service presence and true availability. Professionals highlighted bureaucratic and network limitations, especially for migrant women without insurance, leading to delays in access unless care was an emergency. This situation was supported by the reports of migrants. “We are not regulars; that’s why they don’t care for us.” Migrant woman in Bogotá “These guarantees are subject to the allocated budgets. Initially, the budgets were assigned by different international entities (…) A couple of years ago, they went through the Ministry, the governor’s offices, and then, (…) the responsibility was transferred, but not the financial resources. So, there's been a decline in the quality of hiring (for the hospital)” Healthcare provider in Cali Accessibility of the services The women in all groups had similar gestational ages and service uptake at the first antenatal visit. However, poverty and insurance inequities have emerged as major barriers to accessibility. Qualitative data reinforced this, as women described travel costs, unaffordable medication, and bureaucratic hurdles. “I couldn’t buy the pills.” I went to the midwife and took herbs.” Displaced woman in Cali “I had to travel to another city for having the ultrasound, and the cost was around $20.000 pesos (5 USD). I can do it because I work, but there are women who can´t afford it”. Non-migrant woman in Bogotá Acceptability of the services Despite similar antenatal attendance, qualitative insights revealed significant psychosocial and cultural barriers. Migrant women recounted their experiences of disrespect and xenophobia. “They told me to undress quickly, being rude, and speaking however they wanted.” Migrant woman in Cali “With that name, had to be a ‘veneca [i] . ’” Migrant woman Cali “They told me: You came here only to give birth.” (You) are filling this country with all these foreign children.” Migrant woman Bogota “There is a significant cultural barrier that we have had to learn to deal with, not only with the indigenous women, but with foreigners, because it is the crash of two different cultures.” Sometimes we don´t understand how they talk about some health conditions. “We must learn more about this” Healthcare provider Bogota Contact (Utilization) Qualitative accounts suggest that this contact is often superficial or non-patient-centered and limited by the availability of resources. “Nobody asks how you’re feeling. They just give you pills, and that’s it.” Non-migrant woman from Bogota. “Sometimes, we try to do the best we can in one visit,; however, the number of patients is too high. We are not enough people to care for all these women” Healthcare provider from Cali Effective Coverage and Health Outcomes “When I started with my EPS, (…) and I would request an appointment and they would never give me one, you know?know?” They never responded. So, I wanted to pay at the hospital. I went about three times when I had just gotten pregnant. And three times, they told me: “No, you can't because the appointments will be too expensive for you”.you.” (…) At that time, I could afford to pay for them, that’s why I was asking. And they wouldn’t schedule the appointment to me. They told me no.” Forcibly displaced woman Bogotá (she had a stillbirth) DISCUSSION This study represents the first analysis in Colombia and one of the few in Latin America that systematically compares access to SRH services among migrant, internally displaced, and non-migrant women using a mixed-methods approach. The findings highlight significant differences in sociodemographic conditions and structural barriers that affect effective access to essential health services. Although no statistically significant differences were observed in reported coverage rates, qualitative data revealed persistent limitations in care experiences, particularly for women in conditions of mobility or without formal affiliation to the health system. Additionally, disparities in clinical outcomes were identified, migrant women exhibited higher rates of maternal and perinatal mortality. The use of preventive services, such as preconception care and contraceptive use prior to pregnancy, was low across all groups. These limitations in effective coverage, combined with barriers related to treatment and institutional organization, call for a rethinking of the concept of access and the adoption of approaches that are more responsive to cumulative vulnerability (25, 26). Our data reveal significant disparities in social and demographic characteristics across the three groups. Forcibly displaced women reported the lowest income levels, highest poverty rates, and greater representation of afro descendant and indigenous identities compared to both migrants and non-migrants. Migrants showed higher secondary education completion rates but lower income levels than non-migrants. Non-migrant women had higher income levels but also faced substantial economic vulnerability, as indicated by the poverty rates. As well as reported in studies made in Canada, where migrants and refugee women had worse outcomes in reproductive health, as well as greater vulnerabilities (3). Displaced women experienced the highest levels of poverty, lower income, and greater ethnic minority representation. Overall, no statistically significant differences were observed in SRH service access or outcomes between migrant, forcibly displaced, and non-migrant women. These findings suggest that, within the studied context, migrant and displaced women have comparable access to essential reproductive health services as non-migrant women. This study shows differences with previously reported data from Colombia in different moments of the uptake of the legal framework for migrants’ assimilation, where most of the data showed poorer access and outcomes in migrant women. (27) These results can be related with a better understanding and applicability of the legislation between migrants and a better adaptation of the healthcare system to the migratory crisis. Nonetheless, the uniformly low uptake of preconception care and contraception across all groups underscores the need for targeted interventions to improve early reproductive health engagement. Our results are similar to other studies in LMIC where the uptake of preconception care ranges between 3 and 20% in migrant and non-migrant women.(28, 29) Further research should explore underlying factors influencing these gaps to inform effective policy and programmatic responses. From the Tanahashi perspective, each dimension of service coverage revealed distinct limitations in the Colombian health system’s ability to ensure equitable SRH access. Quantitative findings showed similar antenatal contact and testing rates across all groups; however, effective coverage was compromised, migrants experienced worse maternal and perinatal outcomes, and these outcome disparities underscore a breakdown in the translation of contact into meaningful health benefit. Qualitative data provided critical insights into these patterns. Despite nominal service availability, both migrant and displaced women reported delayed access due to bureaucratic hurdles, regional insurer fragmentation, and legal status barriers. Some of these barriers, especially fragmentation of care, were perceived and reported by non-migrant women. These structural constraints reduced functional accessibility, particularly for migrants lacking formal insurance. This situation repeats in other contexts where SRH services utilization is limited by the healthcare system structure. (17) Moreover, women across groups described interactions with the health system as transactional and emotionally disengaged, revealing a widespread absence of patient-centered and culturally responsive care. Migrant women in particular reported xenophobic encounters and stigmatizing language, undermining their trust in the system and diminishing service acceptability. Unfortunately, these experiences are reported all over the world including high and LMIC. (30, 31) To interpret these findings, we applied a CST framework. Health systems are not static or linear but adaptive, interconnected entities composed of multiple agents and feedback loops. (32) In this context, emergent disparities in maternal outcomes, despite similar reported coverage, reflect deeper system dynamics. Legal exclusion, insurance fragmentation, and stigma operate as reinforcing feedback loops that perpetuate marginalization. The system’s limited adaptive capacity, evidenced by its inability to dynamically respond to migration or displacement stressors, further entrenches inequity. For instance, while policies acknowledge the need for inclusive and intercultural health strategies, their operationalization remains uneven and reactive, rather than anticipatory or responsive. (33) The nonlinear nature of care access also explains the disconnect between quantitative and qualitative data. Small logistical or administrative barriers (e.g., waiting for insurer authorization) led to disproportionately large consequences (e.g., delays in antenatal care, poor outcomes), particularly for mobile or uninsured populations. These dynamics expose a critical tension in the Colombian system given by a structural emphasis on formal coverage and insurer-defined pathways, with insufficient mechanisms to accommodate complex, intersecting vulnerabilities such as displacement, poverty, ethnicity, and legal precarity. Our study shows an innovative integration of a contextual framework that aims to expand the understanding of SRHS access for women in vulnerable situations, such as mobility. At the same time our data reinforces the need for understanding health care as permanently changing system that has differential results to different populations based on their individual vulnerabilities (26), and the approach to healthcare needs to improve the understanding of such vulnerabilities in SRH outcomes. Declarations Ethics, Consent to Participate, and Consent to Publish declarations The ethics committees of Universidad del Valle (Code: 034-022) and Hospital Universitario del Valle (Code: 050-2023) in Cali and Universidad Nacional de Colombia (B.FM.1.002-CE-224-23) and Hospital Engativá (Code: SNACEI-142) in Bogotá approved this protocol. Written informed consent was obtained from all participants prior to data collection. In the case of underaged women, informed assent was obtained from the adolescents, and consent was obtained from parents, carers, or legal guardians. Consent for publication Written informed consent for publication of anonymized data was obtained from all participants. FUNDING This study was funded by the Research Fund of World Women Bank Foundation Colombia, call to field work for research groups 2022 under contract 020-2023 with Universidad del Valle as resources administrator. The funders had no role in the design of the study, data collection, analysis, interpretation of results, or the decision to submit the manuscript for publication. COMPETING INTEREST DECLARATION The authors declare that they have no competing interests. Author Contribution LMBA and DLMP: Conceptualization, study design, data collection, data analysis, manuscript draftingJARR: Data collection, manuscript revisionMSC: Quantitative analysis, methodological guidance, manuscript revisionJZ: Statistical analysis and methodological oversight, manuscript revisionOAG: Clinical supervision, manuscript revisionAll authors reviewed and approved the final manuscript Acknowledgement Pilar Castro, Estefania Aguado, Isabella Guerrero and Brandon David Tovar we acknowledge your excelent work and support during the data collection of this study. Data Availability Data will be available on reasonable request to authors. References Informe sobre las Migraciones en el Mundo 20222022. Alarcão V, Stefanovska-Petkovska M, Virgolino A, Santos O, Costa, A. Intersections of Immigration and Sexual/Reproductive Health: An Umbrella Literature Review with a Focus on Health Equity Social Sciences. 2021;10(2):63. 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Medical Xenophobia: The Voices of Women Refugees in Durban, Kwazulu-Natal, South Africa. bioRxiv. 2019:603753. Leon YB, Soun B, Sudhinaraset M. Structural racism and sexual and reproductive healthcare experiences: A qualitative study among undocumented Asian and Latina. Soc Sci Med. 2025;382:118374. Therrien MC, Normandin JM, Denis JL. Bridging complexity theory and resilience to develop surge capacity in health systems. J Health Organ Manag. 2017;31(1):96-109. Anderson J, Chaturvedi A, Cibulskis M. Simulation tools for developing policies for complex systems: Modeling the health and safety of refugee communities. Health Care Management Science. 2007;10(4):331-9. Footnotes i. “Veneca” means original from Venezuela. It is sometimes used as a depictive term in Colombia. Additional Declarations No competing interests reported. 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Colombia","correspondingAuthor":false,"prefix":"","firstName":"Dauris","middleName":"Lineth","lastName":"Mejía-Pérez","suffix":""},{"id":518258483,"identity":"cb756cd4-c2dd-4e10-8fb8-46045013fcfb","order_by":2,"name":"Jorge Andres Rubio-Romero","email":"","orcid":"","institution":"Universidad Nacional de Colombia","correspondingAuthor":false,"prefix":"","firstName":"Jorge","middleName":"Andres","lastName":"Rubio-Romero","suffix":""},{"id":518258484,"identity":"cb69f3fd-f39b-4997-b25c-0eebb62c7053","order_by":3,"name":"Mercedes Salcedo-Cifuentes","email":"","orcid":"","institution":"Universidad del Valle","correspondingAuthor":false,"prefix":"","firstName":"Mercedes","middleName":"","lastName":"Salcedo-Cifuentes","suffix":""},{"id":518258485,"identity":"f17e9562-6ae9-4b05-b14f-31437c613437","order_by":4,"name":"Javier Zamora","email":"","orcid":"","institution":"Hospital Ramón y Cajal (IRYCIS)","correspondingAuthor":false,"prefix":"","firstName":"Javier","middleName":"","lastName":"Zamora","suffix":""},{"id":518258486,"identity":"c821d788-b9a8-4774-a201-3b2feb0a33ba","order_by":5,"name":"Abonia-González Orlando","email":"","orcid":"","institution":"Universidad del Valle","correspondingAuthor":false,"prefix":"","firstName":"Abonia-González","middleName":"","lastName":"Orlando","suffix":""}],"badges":[],"createdAt":"2025-08-12 21:08:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7359134/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7359134/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":91948712,"identity":"b69b951e-9e3e-4883-a80b-9673bf2d8ed9","added_by":"auto","created_at":"2025-09-23 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06:17:30","extension":"html","order_by":9,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":189377,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7359134/v1/8a9da1e71ff004a7c1f6c148.html"},{"id":91948703,"identity":"c901d20b-c012-4fcb-97b1-6dfab47e9a55","added_by":"auto","created_at":"2025-09-23 06:09:30","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":668542,"visible":true,"origin":"","legend":"\u003cp\u003eMixed methods design\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7359134/v1/26b6d43dd8feb839523b38e1.png"},{"id":91950076,"identity":"83497dc9-8a8e-4654-a90a-0b1b3d017da5","added_by":"auto","created_at":"2025-09-23 06:25:30","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":498915,"visible":true,"origin":"","legend":"\u003cp\u003eIntegrated Comprehensive Analytical Framework for Understanding SRH Access among migrant and displaced women\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7359134/v1/2e7c6f6fbb8717d9d6207efe.png"},{"id":91951427,"identity":"e417748c-66dd-46db-94ed-ff279853d2dc","added_by":"auto","created_at":"2025-09-23 06:41:34","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2453602,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7359134/v1/e43792a6-45eb-4fb4-aab7-80144ca7402c.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eAccess to Sexual and Reproductive Health Services for Migrant Women in Colombia: A Mixed Methods Approach\u003c/p\u003e","fulltext":[{"header":"CONTRIBUTIONS TO LITERATURE","content":"\u003cul\u003e\n \u003cli\u003eThis is the first study in Colombia, and one of the few in Latin America, to systematically compare access to sexual and reproductive health (SRH) services among migrant, forcibly displaced, and non-migrant women using a mixed-methods approach.\u003c/li\u003e\n \u003cli\u003eThe study demonstrates that while reported service coverage rates were similar across groups, effectiveness of care and outcomes varied, with migrant women experiencing higher maternal and perinatal mortality.\u003c/li\u003e\n \u003cli\u003eOur findings highlight how structural barriers\u0026mdash;such as legal precarity, fragmented insurance, stigma, and lack of cultural competence\u0026mdash;undermine effective SRH access despite legal guarantees of universality.\u003c/li\u003e\n \u003cli\u003eBy applying complexity science and social determinants of health frameworks, the study provides novel insights into how health systems in low- and middle-income countries adapt, or fail to adapt, to migration-driven pressures.\u003c/li\u003e\n \u003cli\u003eThe results can inform policymakers and health professionals in designing more inclusive, culturally responsive, and adaptive SRH strategies to address layered vulnerabilities among mobile populations.\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"BACKGROUND","content":"\u003cp\u003eHuman mobility represents a growing phenomenon with profound repercussions on public health systems. At its core, human mobility reflects both the pursuit of opportunity and the need for protection, linked directly to aspirations for improved living standards, healthcare, education, and overall well-being. In 2020, more than 281\u0026nbsp;million people, equivalent to 3.1% of the global population, were classified as international migrants, approximately half of whom are women (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). Migration responds to urgent health needs, including sexual and reproductive health (SRH) (\u003cspan additionalcitationids=\"CR3\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Despite international commitments to human rights and universal health coverage, women in situations of mobility continue to face persistent barriers in accessing SRH services, even within well-established health systems. These individuals face unique vulnerabilities and frequently experience disruptions in their access to essential health services. Delay in prenatal care among undocumented migrants in Europe is associated with poorer perinatal outcomes (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Late obstetric diagnoses, delays, and limitations stemming from immigration status, lack of knowledge about rights, and linguistic or cultural barriers have been reported in the United States and Canada (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eColombia has emerged as a critical case within the regional migration landscape due to the large influx of Venezuelan nationals, which rose from 23,573 in 2014 to over 2.8\u0026nbsp;million by 2024 (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). This demographic shift has placed considerable strain on the healthcare system, particularly in urban centers such as Bogot\u0026aacute; and Cali. Migrant women require a broad range of SRH services, including contraception, obstetric care, and support in cases of gender-based violence. The rise in severe maternal morbidity and mortality within this population reflects both the extent of their needs and the limited response capacity of the system (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). Although the country has adopted a progressive regulatory framework for external migrants, such as the Temporary Protection Statute (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e), practical barriers persist, undermining effective access, continuity of care, and the quality of SRH services for both migrant and host populations.\u003c/p\u003e\u003cp\u003eColombian women forcibly displaced by the armed conflict simultaneously face severe structural barriers to SRH. In affected areas, more than 50% of women do not receive professional prenatal care, leading to adverse perinatal outcomes. (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e) These conditions are associated with higher rates of adolescent fertility and maternal mortality, linked to limited access to contraceptives, fragmented prenatal care, gender violence, and insufficient preparedness among healthcare personnel to manage obstetric emergencies (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Low levels of intergenerational sexual education and reduced contraceptive use among displaced adolescents have been documented in Bogot\u0026aacute; (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). Administrative barriers and a lack of cultural adaptation in service provision have been attributed to exclusion from the healthcare system and limited access to prenatal care in Cali (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThese tensions are relevant in Latin America, and particularly in Colombia, given the sustained increase in both external migratory flows and internal forced displacement. Although regulatory frameworks that guarantee access to healthcare regardless of nationality or migratory status exist, actual access is marked by exclusion, misinformation, and institutional fragmentation (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). This gap between legal provisions and lived experiences underscores the need for studies that integrate quantitative and qualitative perspectives to understand perceived barriers, the social determinants involved, and institutional responses, especially in cities such as Bogot\u0026aacute; and Cali, where all forms of human mobility converge.\u003c/p\u003e\u003cp\u003eDespite Colombia\u0026rsquo;s progressive legal framework, many barriers persist in practice (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). These access gaps are compounded by structural factors, such as poverty, irregular legal status, fragmented insurance regimes, xenophobia, and limited cultural competence among health providers (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). A framework that captures both individual experience and system complexity is required to understand how these dimensions interact to shape health service use and outcomes.\u003c/p\u003e\u003cp\u003eAlthough a growing body of literature exists on pregnant migrant women living in Colombia, most studies provide partial diagnoses based on exclusively quantitative or qualitative approaches. Understanding the interaction between structural conditions, institutional trajectories, and lived experiences requires a mixed-methods approach that can quantify access gaps while also exploring symbolic, cultural, and relational barriers (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThis study employs a multi-theoretical analytic framework that combines three lenses. The Tanahashi model for health service coverage conceptualizess service access in five dimensions: availability, accessibility, acceptability, contact (utilization), and effective coverage (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). This model enables a structured analysis of the stages at which health service access is either enabled or interrupted. The Social Determinants of Health (SDH) framework identifies how health inequities are created or exacerbated by upstream factors, such as legal status, income, education, ethnicity, and gender-based violence (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). This lens highlights the structural roots of unequal access to SRH across different populations. Thirdly complex systems theory (CST), which views health systems as adaptive, nonlinear, and interconnected networks. This approach seeks to facilitate the interpretation of how the Colombian healthcare system has organized or struggled to adapt in response to the pressures of migration and displacement, revealing feedback loops, fragmentation, and unintended consequences in service delivery (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). Together, these frameworks offer a comprehensive lens through which to analyze both the barriers and facilitators of SRH access and the health system\u0026rsquo;s organizational response to human mobility.\u003c/p\u003e\u003cp\u003eThis study aimed to assess differences in maternal and perinatal outcomes between migrant, forcibly displaced, and non-migrant women, examine barriers and facilitators for SRH services access through the lived experiences of women in diverse mobility contexts, healthcare professionals, and stakeholders, and analyze how the Colombian healthcare system has adapted to address the SRH needs of mobile and vulnerable populations.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cp\u003eA mixed-methods study was conducted using a parallel convergent design according to Creswell\u0026rsquo;s model (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e) (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eQuantitative Study Design\u003c/h2\u003e\u003cp\u003eThis prospective cohort study included women of reproductive age who sought care for obstetric events (delivery regardless of the route or fetal outcome, abortion / miscarriage care, ectopic pregnancy, and gestational trophoblastic disease) and who were invited to participate during admission to the obstetrics and gynecology wards at two hospitals. We used a non-probabilistic, sequential sampling method, inviting all women who sought services at the participating institutions during the study period (November 2023 - May 2024), regardless of their immigration status, health services coverage, or other variables that might have influenced sample selection.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eInclusion and exclusion criteria\u003c/h3\u003e\n\u003cp\u003eAll pregnant women who were admitted to participating hospitals for obstetric care and who agreed to participate were included in the study. Healthcare professionals on call at the obstetrics and gynecology wards at any of the hospitals during one of the sessions of qualitative data collection and who accepted to be interviewed with audio or audio and video recording and stakeholders related to the local, regional, or national SRH response who accepted to participate in interviewing with audio or audio and video recording. Women, healthcare providers, and stakeholders who refused to participate in the study and those who had communication difficulties or did not understand the scope of the study were excluded.\u003c/p\u003e\n\u003ch3\u003eData Collection\u003c/h3\u003e\n\u003cp\u003eThe study was conducted in Cali at the Hospital Universitario del Valle Evaristo Garc\u0026iacute;a and in Bogot\u0026aacute; at the Hospital de Engativa\u003cem\u003e-\u003c/em\u003eSub Red Integrada de Servicios Norte de Bogot\u0026aacute; \u003cem\u003eD.C\u003c/em\u003e. Patients were recruited at the time of obstetric care admission. Data were collected from the time of admission for obstetric care until discharge.\u003c/p\u003e\u003cp\u003e Data were collected using a Google Forms\u0026reg; formulary that was applied to every woman who agreed to participate in the study. Data on social and demographic characteristics, obstetric history, clinical variables for current pregnancy, access to reproductive health care services (preconception and antenatal care, contraception, STI screening and treatment, gender-based violence), and maternal and neonatal outcomes of current pregnancy were collected.\u003c/p\u003e\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e\u003ch2\u003eData Analysis\u003c/h2\u003e\u003cp\u003eThe primary exposure variable was migratory status, which was classified into three categories: migrant, forcibly displaced, and non-migrant. Participants were grouped accordingly. Descriptive statistics were used to characterize the study population. Quantitative variables were assessed for normality using the Shapiro-Wilk or Kolmogorov-Smirnov tests. Variables following a normal distribution were summarized using means and standard deviations and analyzed using analysis of variance (ANOVA) tests, whereas non-normally distributed variables were described using medians and interquartile ranges and analyzed with Kruskal-Wallis tests. The absolute and relative frequencies of the categorical variables were described and compared using the chi-square test.\u003c/p\u003e\u003cp\u003eAssociations between migratory status and access to sexual and reproductive health (SRH) services, as well as maternal and perinatal outcomes, were first evaluated through univariate analyses using chi-square tests. Subsequently, multivariate logistic regression models were constructed for each outcome variable, with migratory status being the main independent variable. These models were adjusted for potential confounding variables identified a priori based on theoretical relevance and previous literature, including age, parity, education level, health insurance status, ethnicity, and city of care.All statistical analyses were performed using STATA v.18\u0026reg;, and a two-tailed p-value of \u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eQualitative Study Design and Theoretical Framework\u003c/h3\u003e\n\u003cp\u003eThis qualitative study employed a phenomenological-hermeneutic design to explore the lived experiences of migrant, forcibly displaced, and non-migrant women in accessing sexual and reproductive health (SRH) services in Colombia. The study also examined the experiences of local, regional, and national healthcare providers caring for migrant women and stakeholders. Rooted in phenomenology, the study sought to understand how individuals perceive and make meaning of healthcare encounters, while the hermeneutic approach allowed for interpretation of these experiences within broader structural and institutional contexts.\u003c/p\u003e\u003cp\u003eThe analytic framework was developed by integrating the three complementary models mentioned above. These frameworks enabled a multilevel, interdisciplinary examination of access barriers and facilitators, linking personal narratives with health system dynamics. (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e)\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eStudy Population and Sampling Strategy\u003c/h2\u003e\u003cp\u003eWomen included in the quantitative branch of the study were invited to participate in the qualitative branch. We selected five women from each migratory status group (migrant, forcibly displaced, and non-migrant) by sequential sampling during three interviews, one every two months during the study period in each city.\u003c/p\u003e\u003cp\u003eWomen who agreed to participate were interviewed in a private space inside each hospital before discharge. During the same session, we interviewed healthcare providers on call at each hospital\u0026rsquo;s obstetrics and gynecology ward. The professionals included in the study were randomly selected only by chance of being on call during the qualitative data collection session.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eStakeholders were invited to participate using a snowball strategy, inviting professionals linked to the different local or regional health secretariats and organizations linked to the Ministry of Health response for SRH. Although the delegates of the Ministry of Health were invited to participate in the study, this key stakeholder did not provide a positive response.\u003c/p\u003e\u003cp\u003eWe interviewed 44 people, 30 women, and 14 healthcare professionals between service providers and stakeholders.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eData Collection Procedures\u003c/h3\u003e\n\u003cp\u003eSemi-structured interviews were conducted in Spanish to gather data, guided by a tool aligned with the Tanahashi dimensions and informed by the SDH framework. The guide explored perceptions of service availability, legal and economic access, experiences of stigma or cultural dissonance, quality of provider interactions, and perceived health outcomes. The guide for health professionals and stakeholders focused on system design, legal framework, resource coordination, migration response, and equity implementation.\u003c/p\u003e\u003cp\u003eAll interviews were audio and video recorded, transcribed verbatim using Trint\u0026reg;, and revised by two researchers. Two trained researchers (LMBA, DLMP) with expertise in qualitative SRH research and migrant health conducted the interviews in private, safe settings.\u003c/p\u003e\u003cdiv id=\"Sec10\" class=\"Section2\"\u003e\u003ch2\u003eData Analysis\u003c/h2\u003e\u003cp\u003eA multi-framework analytic strategy was applied. Phenomenological coding was used to identify experiential themes across narratives inductively. A deductive coding phase followed, categorizing content into the five Tanahashi dimensions. The SDH framework was used to map each barrier or facilitator to structural determinants (e.g., legal status, poverty, and discrimination). Complex systems theory was employed for interpretive synthesis, examining how interactions among policies, institutions, and feedback mechanisms shape access outcomes and health system resilience.\u003c/p\u003e\u003cp\u003eThis layered approach allowed individual voices to be heard while situating them within broader structural and systemic patterns. AtlasTi 24\u0026reg; software was used for coding, and analytical triangulation was conducted by two independent researchers (LMBA and DLMP).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eEthical considerations\u003c/h2\u003e\u003cp\u003e The ethics committees of Universidad del Valle (Code: 034\u0026thinsp;\u0026minus;\u0026thinsp;022) and Hospital Universitario del Valle (Code: 050-2023) in Cali and Universidad Nacional de Colombia (B.FM.1.002-CE-224-23) and Hospital Engativa (Code: SNACEI-142) in Bogot\u0026aacute; approved this protocol. Written informed consent was obtained before data collection and for participation in the study\u0026rsquo;s quantitative branch. In the case of underaged women, informed assent was obtained from the adolescents and consent was obtained from the parents, carer, or legal guardian. The participants included in the qualitative branch of the study provided written consent for interview participation and for audio and/or video recording of the interview.\u003c/p\u003e\u003c/div\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eQuantitative Results\u003c/h2\u003e\u003cp\u003eWe collected data from 929 women, 424 (45.6%) in Bogot\u0026aacute; and 505 (55,4%) in Cali. A total of 250 (26.9%) women were migrant, 134 (14,4%) were forcibly displaced, and 545 (58,7%) were non-migrant women. Additionally, 116 (86.6%) displaced women were enrolled in Cali, and 150 (60%) migrant women were enrolled in Bogot\u0026aacute;.\u003c/p\u003e\u003cp\u003eThe median age of the migrant women in the sample was 24 years (IQR: 20\u0026ndash;29), ranging from 13 to 53 years. The majority of respondents (94.8%) resided in urban areas, and 87.2% originated from urban settings. Educational attainment was concentrated at the secondary level (72.8%), with 19.2% achieving tertiary education and 0.4% completed postgraduate studies. Regarding marital status, 89.2% were married and 10.8% were single. Ethnically, 98.4% identified themselves as non-Indigenous and non-Afro descendants.\u003c/p\u003e\u003cp\u003eThe income levels of migrant women were notably low, with a mean weekly income of 83 USD (SD: 47.5). A substantial proportion (76.8%) lived below the monetary poverty line (less than \u003cspan\u003e$\u003c/span\u003e109 USD per month) and 17.2% below the extreme poverty line (less than\u003cspan\u003e$\u003c/span\u003e54 USD per month). (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e) In terms of social security, only 3.6% of the population contributed to the healthcare system, 54% were subsidized, and 42.4% remained uninsured. Reports of gender violence affected 10% of migrant women.\u003c/p\u003e\u003cp\u003eThe median age of forcibly displaced women was 25.5 years (IQR: 21\u0026ndash;31), ranging from 13 to 40 years. Unlike migrants, a significant portion (64.9%) originated from rural areas, yet 81.3% resided in urban areas at the time of the study. Educational attainment was similar to that of migrants, with 69.4% completing secondary education and 17.2% attaining tertiary education. In terms of ethnicity, 60.4% of these women identified themselves as Afro descendant and 9.7% as Indigenous.\u003c/p\u003e\u003cp\u003eForcibly displaced women had a mean weekly income of USD 67 (SD: 39.5), which was lower than that of migrants. The proportion of people living below the monetary poverty line was higher (86.6%), and 35.8% were living in extreme poverty. Regarding social security, 11.9% contributed, 88.1% were subsidized, and none were uninsured. Experiences of gender violence were reported by 11.2% of forcibly displaced women.\u003c/p\u003e\u003cp\u003eThe median age of non-migrant women was 26 years (IQR: 22\u0026ndash;31), ranging from 13\u0026ndash;48 years, with a slightly higher representation in the tertiary education category (27.5%). Most non-migrant respondents (88.3%) resided in urban areas, and 82.2% originated from urban settings. The majority were married (82.2%) and identified themselves as non-Indigenous and non-Afrodescendants (77.2%).\u003c/p\u003e\u003cp\u003eTheir mean weekly income was USD 108 (SD: 78.2), the highest among the three groups. Despite higher incomes, 57.1% and 11.2% of the non-migrant respondents lived below the monetary poverty line and below the extreme poverty line, respectively. In terms of social security, 24.2% of this population contributed to the health care system, 75.4% were subsidized by the system, and 0.4% were uninsured. Gender violence was reported by 8.4% of non-migrant women (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSocial and demographic characteristics\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003eAge\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMigrant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDisplaced\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNon migrant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eP\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMean\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e25.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e26.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e26.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e26.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003e0.804\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6.43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6.59\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e6.54\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e250\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e134\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e545\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e929\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMin\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e13\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMax\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e53\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e53\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eCity\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMigrant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDisplaced\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNon migrant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBogota\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e150 (60%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e18 (13.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e256 (46.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e424 (45.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCali\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e100 (40%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e116 (86.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e289 (53%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e505 (55.4%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e250 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e134 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e545 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e929 (100%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMarital Status\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMigrant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDisplaced\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNon migrant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSingle\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e27 (10.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e33 (24.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e97 (17.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e157 (16.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e0.002\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMaried\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e223 (89.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e101 (75.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e448 (82.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e772 (83.1%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e250 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e134 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e545 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e929 (100%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eEthnicity\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMigrant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDisplaced\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNon migrant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAfrodescendant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3 (1.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e81 (60.44%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e117 (21.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e201 (21.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIndigenous\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (0.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e13(9.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7(1.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e21 (2.3%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNone\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e246 (98.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e40 (29.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e421 (77.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e707 /76.1%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e250 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e134 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e545 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e929 (100%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eEducation Attainment\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMigrant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDisplaced\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNon migrant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIliteracy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0 (0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5 (3.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2 (0.37%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e7 (0.75%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePrimary\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e19 (7.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e13 (9.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e37 (6.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e69(7.4%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSecondary\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e182 (72.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e93(69.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e353 (64.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e628 (67.6%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTertiary\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e48(19.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e23(17.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e150 (27.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e221 (23.8%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePostgraduate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (0.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3(0.55%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4 (0.4%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSchooling years\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMigrant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDisplaced\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNon migrant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMean\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e10.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e9.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e10.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.79\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e250\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e134\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e545\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e929\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eArea of Origin\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMigrant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDisplaced\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNon migrant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUrban\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e218 (87.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e47 (35.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e448 (82.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e713 (76.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRural\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e32 (12.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e87 (64.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e97 (17.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e216 (23.2%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e250 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e134 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e545 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e929 (100%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eArea of Residence\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMigrant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDisplaced\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNon migrant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUrban\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e236 (94.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e107 (79.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e478 (87.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRural\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e14 (5.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e27 (20.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e67 (12.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e108(11.6%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e250 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e134 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e545 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e929 (100%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eFamily Income in USD/week\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMigrant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDisplaced\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNon migrant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMean\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e83\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e108\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e47.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e39.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e78.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e68.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e250\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e134\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e545\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e929\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eFamily living below monetary poverty line\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMigrant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDisplaced\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNon migrant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e58 (23,2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e18 (13,4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e234 (42,9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e310 (33,4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e192 (76,8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e116 (86,6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e311 (57,1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e619 (66,7%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e250 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e134 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e545 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e929 (100%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eFamily living below extreme poverty line\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMigrant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDisplaced\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNon migrant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e207 (82,8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e86 (64,2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e484 (88,8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e777 (83,6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e43 (17,2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e48 (35,8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e61 (11,2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e152 (16,4%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e250 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e134 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e545 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e929 (100%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eSocial Security Afiliation\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMigrant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDisplaced\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNon migrant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eContribute\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7 (2.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e13 (9.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e120 (22%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e140 (15.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"4\" rowspan=\"5\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSubsidized\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e135 (54.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e118 (88.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e411 (75.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e664 (71.5%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSpecial Regime\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2 (0.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3 (2.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e12 (2.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e17 (1.83%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNon Affiliated\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e106 (42.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2 (0,37%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e108 (11.6%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e250 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e134 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e545 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e929 (100%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eGender Violence Victim\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMigrant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDisplaced\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNon migrant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e225 (90%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e119 (88.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e499 (91.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e843 (90.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e0.550\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e25 (10%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e15 (11.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e46 (8.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e86 (8.3%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e250 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e134 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e545 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e929 (100%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e100.2 (60.5\u0026ndash;165.8) p0.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e113.6 (61.7 -209.1) p 0.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003eObstetric Outcomes\u003c/h2\u003e\u003cp\u003eMigrant women had a mean number of pregnancies of 1.98 (SD: 1.24), slightly higher than non-migrants (1.88). The proportion of pregnancies resulting in vaginal or cesarean births was slightly lower among migrants (92.7%) than among non-migrants (93.4%), although the difference was not statistically significant (p\u0026thinsp;=\u0026thinsp;0.129). The rate of pregnancy loss was higher among migrants (7.3%) than among non-migrants (6.6%).\u003c/p\u003e\u003cp\u003eVaginal births were more common among migrants (62.9%) than among non-migrants (57.7%). The mean gestational age at birth was nearly identical between the groups (37.8 vs. 37.9 weeks, p\u0026thinsp;=\u0026thinsp;0.854). The mean neonatal birth weight was slightly higher among migrants (2943.3 vs. 2929.4 g, p\u0026thinsp;=\u0026thinsp;0.894).\u003c/p\u003e\u003cp\u003ePreterm birth rates were slightly lower among migrants (15.3%) than among non-migrants (16.1%), with an OR of 0.94 (95%CI 0.61\u0026ndash;1.45, p\u0026thinsp;=\u0026thinsp;0.789). The proportion of small vulnerable newborns (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e) was also slightly lower among migrants (28.3%) than among non-migrants (30.5%), with an OR of 0.90 (95%CI 0.64\u0026ndash;1.27, p\u0026thinsp;=\u0026thinsp;0.552).\u003c/p\u003e\u003cp\u003eNeonatal Intensive Care Unit (NICU) admissions were lower among migrant newborns (17.9%) than among non-migrants (22.4%), although the adjusted OR was not significant (0.68, 95% CI: 0.45\u0026ndash;1.02, p\u0026thinsp;=\u0026thinsp;0.065). We observed 4 and 1 stillbirths for the migrants and non-migrants groups, respectively (1.6% vs. 0.2%) with an OR of 7.4 (0.82\u0026ndash;66.87, p\u0026thinsp;=\u0026thinsp;0.075) although the small number of events makes this association not statistically significant. Furthermore, perinatal mortality was higher among migrants (37.3 vs. 18.7 per 1,000 live births).\u003c/p\u003e\u003cp\u003eMaternal mortality occurred only among migrants at a rate of 400 per 100,000 live births. This was the only group in which this critical maternal outcome occurred. Preeclampsia was reported in 16.4% of migrant women compared with 18.7% of non-migrants, although the difference was not statistically significant. Severe maternal morbidity was slightly lower among migrants (18.4%) than among non-migrants (20.5%, p\u0026thinsp;=\u0026thinsp;0.045).\u003c/p\u003e\u003cp\u003eForcibly displaced women had a slightly higher mean number of pregnancies (2.22, SD: 1.54) than non-migrants (1.88). Pregnancy loss was significantly lower among displaced women (2.3%) than among non-migrants (6.6%).\u003c/p\u003e\u003cp\u003eVaginal delivery was slightly more common among displaced women (64.8%) than among non-migrants (57.7%), whereas cesarean sections were less common (35.2% vs. 42.3%, p\u0026thinsp;=\u0026thinsp;0.210). The gestational age and birth weight were similar across both groups, with no statistically significant differences.\u003c/p\u003e\u003cp\u003ePreterm birth rates were the lowest among displaced women (10.2%) compared to non-migrants (16.1%), with an OR of 0.59 (0.32\u0026ndash;1.09, p\u0026thinsp;=\u0026thinsp;0.097). The rates of small vulnerable newborns were also slightly lower (29.9% vs. 30.5%, OR: 0.97, 95% CI: 0.64\u0026ndash;1.49, p\u0026thinsp;=\u0026thinsp;0.898).\u003c/p\u003e\u003cp\u003eNICU admissions were lower among displaced women (16.1%) than among non-migrants (22.4%), although the difference was not statistically significant (adjusted OR: 0.94, 95% CI: 0.54\u0026ndash;1.63, p\u0026thinsp;=\u0026thinsp;0.830). The stillbirth rate was also lower among displaced women (0.8% vs. 0.2%, p\u0026thinsp;=\u0026thinsp;0.146).\u003c/p\u003e\u003cp\u003ePerinatal mortality was lower among displaced women at 7.5 per 1,000 live births compared with 18.7 per 1,000 among non-migrants. No maternal deaths were reported in this group. Preeclampsia was significantly lower among displaced women (8.2% vs. 18.7%, p\u0026thinsp;=\u0026thinsp;0.014). Severe maternal morbidity was also lower among displaced women (11.2%) than among non-migrants (20.5%, p\u0026thinsp;=\u0026thinsp;0.045) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eMaternal and neonatal outcomes\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003eNumber of pregnancies\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMigrant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDisplaced\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNon migrant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMean\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.98\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e0.003\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.29\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e250\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e134\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e545\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e929\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003ePregnancy Outcome\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMigrant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDisplaced\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNon migrant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVaginal/ Cesaran Birth\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e229 (91.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e128 (95.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e499 (91.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e856 (92%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"5\" rowspan=\"6\"\u003e\u003cp\u003e0.445\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMiscarriage\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e13 (5.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3 (2.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e27 (4.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e43 (4.6%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEctopic Preganancy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4 (1.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8 (1.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e13 (1.3%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMolar Pregnancy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (0.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1 (0.1%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAbortion\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3 (1.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3 (2.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e12 (2.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e18 (1.9%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e250 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e134 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e545 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e929 (100%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003eDelivery Route\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMigrant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDisplaced\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNon migrant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVaginal Birth\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e144 (62.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e83 (64.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e288 (57.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e515 (60.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e0.210\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCesarean Section\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e85 (37.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e45 (35.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e211 (42.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e341 (39.8%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e229 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e128 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e499 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e856 (100%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003eGestational Age at birth\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMigrant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDisplaced\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNon migrant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMean\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e35.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e35.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e35.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e8.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e7.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e250\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e134\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e545\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e929\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003eNeonatal Birthweigth\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMigrant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDisplaced\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNon migrant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMean\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2943.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2950.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2929.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2936.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e0.811\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e534.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e514.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e616.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e520.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e229\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e128\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e498\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e855\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003ePreterm Birth\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMigrant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDisplaced\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNon migrant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e194(84.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e115 (89.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e419 (83.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e727 (85%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e0.245\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e35 (15.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e13 (10.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e80 (16.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e128 (15%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e229 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e128 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e499 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e856 (100%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003eSmall Vulnerable Newborn\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMigrant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDisplaced\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNon migrant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e162 (71.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e89 (70.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e344 (69.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e595 (70.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e0.837\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e64 (28.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e38 (29.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e151 (30.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e253 (29.8%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e226 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e127 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e495 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e848 (100%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003eNeonatal Intensive Care Unit Admition\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMigrant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDisplaced\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNon migrant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e179 (82.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e104 (83.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e394 (77.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e677 (79.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e0.170\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e39 (17.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e20 (16.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e114 (22.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e173 (20.3%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e218 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e124 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e508 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e850 (100%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003eStillbirth\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMigrant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDisplaced\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNon migrant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e246 (98.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e133 (99.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e544 (99.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e923 (99.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e0.068\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4 (1.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (0.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (0.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e6 (0.65%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e250 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e134 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e545 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e929 (100%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003ePerinatal Mortality\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMigrant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDisplaced\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNon migrant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e241(96.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e133 (99.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e535 (98.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e909 (97.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e0.135\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e9 (3.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (0.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10 (1.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e20 (2.2%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e250 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e134 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e545 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e929 (100%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePerinatal Mortality Rate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e37.3/1000 livebirths\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7.5/1000 livebirths\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e18.7/1000 livebirths\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e22/1000 livebirths\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.96 (0.81\u0026ndash;4.77) p 0.207\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.41 (0.05\u0026ndash;3.15) p 0.702\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003eMaternal Mortality\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMigrant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDisplaced\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNon migrant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e249 (99.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e134\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e545 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e928 (99.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e0.257\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (0.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0 (0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1 (0.1%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e250 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e134 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e545\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e929 (100%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMaternal Mortality Rate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e400/100000 livebirths\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c6\" namest=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003ePreeclampsia\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMigrant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDisplaced\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNon migrant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e209 (83.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e123 (91.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e443 (81.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e775 (83.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e0.014\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e41 (16.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e11 (8.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e102 (18.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e154 (16.6%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e250 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e134 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e545 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e929 (100%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003ePostpartum Haemorrage\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMigrant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDisplaced\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNon migrant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e242 (96.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e131 (97.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e524 (96.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e897 (96.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e0.636\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e8 (3.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3 (2.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e21 (3.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e32 (3.4%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e250 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e134 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e545 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e929 (100%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003eSevere Maternal Morbidity (Near Miss)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMigrant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDisplaced\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNon migrant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e204 (81.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e119 (88.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e433 (79.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e756 (81.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e0.045\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e46 (18.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e15 (11.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e112 (20.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e173 (18.6%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e250 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e134 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e545 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e929 (100%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003eAccess to Sexual and Reproductive Health Services\u003c/h2\u003e\u003cp\u003eThe average number of antenatal visits was similar across the groups, with migrant women attending 5.7 visits, forcibly displaced women attending 5.8 visits, and non-migrant women attending 5.9 visits (p\u0026thinsp;=\u0026thinsp;0.150). Similarly, the mean gestational age at the first antenatal visit showed no significant differences (10.3, 10.8, and 11.2 weeks for migrants, displaced, and non-migrants, respectively; p\u0026thinsp;=\u0026thinsp;0.259). These findings suggest that antenatal care attendance is equitable regardless of migration status.\u003c/p\u003e\u003cp\u003eThe syphilis screening rates were comparably high among migrants (99.2%), forcibly displaced women (99.2%), and non-migrants (98.7%) (p\u0026thinsp;=\u0026thinsp;0.764). The prevalence of gestational syphilis did not significantly differed between groups (5.2% among migrants, 6.7% among displaced, and 5.1% among non-migrants; p\u0026thinsp;=\u0026thinsp;0.760). Similarly, congenital syphilis rates were consistent at 4.0%, 4.5%, and 3.8%, respectively (p\u0026thinsp;=\u0026thinsp;0.947).\u003c/p\u003e\u003cp\u003eAll groups received a comparable average number of HIV tests during pregnancy (2.4\u0026ndash;2.5 tests, p\u0026thinsp;=\u0026thinsp;0.999). The prevalence of HIV diagnosis before and during pregnancy was low and did not differ significantly by group (pregestational: migrants, 0.4%; displaced, 1.5%; non-migrants, 1.5%; p\u0026thinsp;=\u0026thinsp;0.40707; during pregnancy: migrants, 0.8%; displaced, 1.5%; non-migrants, 0.4%, p\u0026thinsp;=\u0026thinsp;0.325), although internally displaced women had a higher prevalence of HIV infection than the other two groups.Hepatitis B testing rates were similarly high (91.2%; migrants, 94.1%; displaced, 94.5%; non-migrantsp\u0026thinsp;=\u0026thinsp;0.208).\u003c/p\u003e\u003cp\u003eUptake of preconception care was low across all groups (17.6%, 17.2%, and 18.3% migrants, displaced, and non-migrants, respectively; p\u0026thinsp;=\u0026thinsp;0.935), indicating a critical gap in early maternal health interventions. Preconception contraceptive use was reported by 44% of migrants, 35.1% of displaced, and 43.8% of non-migrants (p\u0026thinsp;=\u0026thinsp;0.161).\u003c/p\u003e\u003cp\u003eKnowledge about abortion access was moderately low but comparable among groups (migrants, 45.6%; displaced, 52.2%; non-migrants, 47.0%; p\u0026thinsp;=\u0026thinsp;0.444). Reports of gender-based violence victimization were similar across populations (3.2%, 3.8%, and 4.6%, respectively; p\u0026thinsp;=\u0026thinsp;0.647) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSRH Service Access\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003eNumber of Antenatal Visits\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMigrant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDisplaced\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNon migrant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMean\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e0.150\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e250\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e134\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e545\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e929\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003eGestational age at First Antenatal Visit\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMigrant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDisplaced\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNon migrant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMean\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e10.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e10.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e11.2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e10.9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e0.259\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e7.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e250\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e134\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e545\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e929\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003eSyphilis tested\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMigrant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDisplaced\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNon migrant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2 (0.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (0.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7 (1.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e10 (1.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e0.764\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e248 (99.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e133 (99.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e538 (98.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e919 (98.9%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e250 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e134 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e545 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e929 (100%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003eGestational Syphilis\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMigrant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDisplaced\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNon migrant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e237 (94.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e125 (93.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e517 (94.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e879 (94.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e0.760\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e13 (5.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e9 (6.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e28 (5.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e50 (5.4%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e250 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e134 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e545 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e929 (100%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003eCongenital Syphylis\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMigrant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDisplaced\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNon migrant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e240 (96%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e128 (95.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e524 (96.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e892 (96%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e0.947\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e10 (4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6 (4.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e21 (3.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e37 (4%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e250 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e134 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e545 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e929 (100%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003eNumber of HIV Test During Pregnancy\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMigrant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDisplaced\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNon migrant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMean\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e0.999\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.97\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.97\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.97\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.97\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eN\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e250\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e134\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e545\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e929\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003eHIV Pregestational Diagnosis\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMigrant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDisplaced\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNon migrant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e249 (99.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e132 (98.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e537 (98.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e918 (98.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e0.407\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1 (0.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2 (1.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8 (1.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e11 (1.2%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e250 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e134 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e545 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e929 (100%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003eHIV Diagnosis During Preganancy\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMigrant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDisplaced\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNon migrant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e247 (99.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e130 (98.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e535 (99.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e912 (99.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e0.325\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2 (0.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2 (1.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2 (0.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e6 (0.6%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e250 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e134 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e545 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e929 (100%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003eHepatitis B Test\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMigrant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDisplaced\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNon migrant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e22 (8.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8 (5.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e30 (5.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e60 (6.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e0.208\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e228 (91.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e126 (94.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e515 (94.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e869 (93.5%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e250 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e134 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e545 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e929 (100%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003ePreconceptional Care\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMigrant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDisplaced\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNon migrant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e206 (82.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e111 (82.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e445 (81.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e762 (82%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e0.935\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e44 (17.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e23 (17.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e100 (18.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e167 (18%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e250 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e134 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e545 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e929 (100%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003ePreconceptional Contraception\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMigrant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDisplaced\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNon migrant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e140 (56%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e87 (64.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e306 (56.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e533 (57.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e0.161\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e110 (44%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e47 (35.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e239 (43.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e396 (42.6%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e250 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e134 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e545 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e929 (100%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003eAbortion Access Knowledge\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMigrant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDisplaced\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNon migrant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e136 (54.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e64 (47.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e289 (53%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e489 (52.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e0.444\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e114 (45.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e70 (52.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e256 (47%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e440 (47.4%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e250 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e134 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e545 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e929 (100%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e\u003cp\u003eGender Violence Victim\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMigrant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eDisplaced\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNon migrant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e239 (96.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e128 (96.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e516 (95.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e883 (95.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e0.647\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e8 (3.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5 (3.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e25 (4.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e38 (4.1%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e250 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e134 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e545 (100%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e929 (100%)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOR\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.69 (0.31\u0026ndash;1.55) p 0.371\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.81 (0.30\u0026ndash;2.15) p 0.667\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"3\" nameend=\"c6\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003eQualitative Results\u003c/h2\u003e\u003cdiv id=\"Sec17\" class=\"Section3\"\u003e\u003ch2\u003eAvailability of the services\u003c/h2\u003e\u003cp\u003eQualitative narratives revealed gaps between service presence and true availability. Professionals highlighted bureaucratic and network limitations, especially for migrant women without insurance, leading to delays in access unless care was an emergency. This situation was supported by the reports of migrants.\u003c/p\u003e\u003cp\u003e\u003cem\u003e\u0026ldquo;We are not regulars; that\u0026rsquo;s why they don\u0026rsquo;t care for us.\u0026rdquo; Migrant woman in Bogot\u0026aacute;\u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003e\u0026ldquo;These guarantees are subject to the allocated budgets. Initially, the budgets were assigned by different international entities (\u0026hellip;) A couple of years ago, they went through the Ministry, the governor\u0026rsquo;s offices, and then, (\u0026hellip;) the responsibility was transferred, but not the financial resources. So, there's been a decline in the quality of hiring (for the hospital)\u0026rdquo; Healthcare provider in Cali\u003c/em\u003e\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003eAccessibility of the services\u003c/h2\u003e\u003cp\u003eThe women in all groups had similar gestational ages and service uptake at the first antenatal visit. However, poverty and insurance inequities have emerged as major barriers to accessibility. Qualitative data reinforced this, as women described travel costs, unaffordable medication, and bureaucratic hurdles.\u003c/p\u003e\u003cp\u003e\u003cem\u003e\u0026ldquo;I couldn\u0026rsquo;t buy the pills.\u0026rdquo; I went to the midwife and took herbs.\u0026rdquo; Displaced woman in Cali\u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003e\u0026ldquo;I had to travel to another city for having the ultrasound, and the cost was around $20.000 pesos (5 USD). I can do it because I work, but there are women who can\u0026acute;t afford it\u0026rdquo;. Non-migrant woman in Bogot\u0026aacute;\u003c/em\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\u003ch2\u003eAcceptability of the services\u003c/h2\u003e\u003cp\u003eDespite similar antenatal attendance, qualitative insights revealed significant psychosocial and cultural barriers. Migrant women recounted their experiences of disrespect and xenophobia.\u003c/p\u003e\u003cp\u003e\u003cem\u003e\u0026ldquo;They told me to undress quickly, being rude, and speaking however they wanted.\u0026rdquo; Migrant woman in Cali\u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003e\u0026ldquo;With that name, had to be a \u0026lsquo;veneca\u003c/em\u003e\u003csup\u003e\u003cem\u003e[i]\u003c/em\u003e\u003c/sup\u003e.\u003cem\u003e\u0026rsquo;\u0026rdquo; Migrant woman Cali\u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003e\u0026ldquo;They told me: You came here only to give birth.\u0026rdquo; (You) are filling this country with all these foreign children.\u0026rdquo; Migrant woman Bogota\u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003e\u0026ldquo;There is a significant cultural barrier that we have had to learn to deal with, not only with the indigenous women, but with foreigners, because it is the crash of two different cultures.\u0026rdquo; Sometimes we don\u0026acute;t understand how they talk about some health conditions. \u0026ldquo;We must learn more about this\u0026rdquo; Healthcare provider Bogota\u003c/em\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec20\" class=\"Section2\"\u003e\u003ch2\u003eContact (Utilization)\u003c/h2\u003e\u003cp\u003eQualitative accounts suggest that this contact is often superficial or non-patient-centered and limited by the availability of resources.\u003c/p\u003e\u003cp\u003e\u003cem\u003e\u0026ldquo;Nobody asks how you\u0026rsquo;re feeling. They just give you pills, and that\u0026rsquo;s it.\u0026rdquo; Non-migrant woman from Bogota.\u003c/em\u003e\u003c/p\u003e\u003cp\u003e\u003cem\u003e\u0026ldquo;Sometimes, we try to do the best we can in one visit,; however, the number of patients is too high. We are not enough people to care for all these women\u0026rdquo; Healthcare provider from Cali\u003c/em\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec21\" class=\"Section2\"\u003e\u003ch2\u003eEffective Coverage and Health Outcomes\u003c/h2\u003e\u003cp\u003e\u003cem\u003e\u0026ldquo;When I started with my EPS, (\u0026hellip;) and I would request an appointment and they would never give me one, you know?know?\u0026rdquo; They never responded. So, I wanted to pay at the hospital. I went about three times when I had just gotten pregnant. And three times, they told me: \u0026ldquo;No, you can't because the appointments will be too expensive for you\u0026rdquo;.you.\u0026rdquo; (\u0026hellip;) At that time, I could afford to pay for them, that\u0026rsquo;s why I was asking. And they wouldn\u0026rsquo;t schedule the appointment to me. They told me no.\u0026rdquo; Forcibly displaced woman Bogot\u0026aacute; (she had a stillbirth)\u003c/em\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThis study represents the first analysis in Colombia and one of the few in Latin America that systematically compares access to SRH services among migrant, internally displaced, and non-migrant women using a mixed-methods approach. The findings highlight significant differences in sociodemographic conditions and structural barriers that affect effective access to essential health services. Although no statistically significant differences were observed in reported coverage rates, qualitative data revealed persistent limitations in care experiences, particularly for women in conditions of mobility or without formal affiliation to the health system.\u003c/p\u003e\n\u003cp\u003eAdditionally, disparities in clinical outcomes were identified, migrant women exhibited higher rates of maternal and perinatal mortality. The use of preventive services, such as preconception care and contraceptive use prior to pregnancy, was low across all groups. These limitations in effective coverage, combined with barriers related to treatment and institutional organization, call for a rethinking of the concept of access and the adoption of approaches that are more responsive to cumulative vulnerability (25, 26).\u003c/p\u003e\n\u003cp\u003eOur data reveal significant disparities in social and demographic characteristics across the three groups. Forcibly displaced women reported the lowest income levels, highest poverty rates, and greater representation of afro descendant and indigenous identities compared to both migrants and non-migrants. Migrants showed higher secondary education completion rates but lower income levels than non-migrants. Non-migrant women had higher income levels but also faced substantial economic vulnerability, as indicated by the poverty rates. As well as reported in studies made in Canada, where migrants and refugee women had worse outcomes in reproductive health, as well as greater vulnerabilities (3). \u0026nbsp;Displaced women experienced the highest levels of poverty, lower income, and greater ethnic minority representation.\u003c/p\u003e\n\u003cp\u003eOverall, no statistically significant differences were observed in SRH service access or outcomes between migrant, forcibly displaced, and non-migrant women. These findings suggest that, within the studied context, migrant and displaced women have comparable access to essential reproductive health services as non-migrant women. This study shows differences with previously reported data from Colombia in different moments of the uptake of the legal framework for migrants\u0026rsquo; assimilation, where most of the data showed poorer access and outcomes in migrant women. (27) \u0026nbsp;These results can be related with a better understanding and applicability of the legislation between migrants and a better adaptation of the healthcare system to the migratory crisis. Nonetheless, the uniformly low uptake of preconception care and contraception across all groups underscores the need for targeted interventions to improve early reproductive health engagement. Our results are similar \u0026nbsp;to other studies in LMIC where the uptake of preconception care ranges between 3 and 20% in migrant and non-migrant women.(28, 29) Further research should explore underlying factors influencing these gaps to inform effective policy and programmatic responses.\u003c/p\u003e\n\u003cp\u003eFrom the Tanahashi perspective, each dimension of service coverage revealed distinct limitations in the Colombian health system\u0026rsquo;s ability to ensure equitable SRH access. Quantitative findings showed similar antenatal contact and testing rates across all groups; however, effective coverage was compromised, migrants experienced worse maternal and perinatal outcomes, and these outcome disparities underscore a breakdown in the translation of contact into meaningful health benefit.\u003c/p\u003e\n\u003cp\u003eQualitative data provided critical insights into these patterns. Despite nominal service availability, both migrant and displaced women reported delayed access due to bureaucratic hurdles, regional insurer fragmentation, and legal status barriers. Some of these barriers, especially fragmentation of care, were perceived and reported by non-migrant women. These structural constraints reduced functional accessibility, particularly for migrants lacking formal insurance. This situation repeats in other contexts where SRH services utilization is limited by the healthcare system structure. (17)\u003c/p\u003e\n\u003cp\u003eMoreover, women across groups described interactions with the health system as transactional and emotionally disengaged, revealing a widespread absence of patient-centered and culturally responsive care. Migrant women in particular reported xenophobic encounters and stigmatizing language, undermining their trust in the system and diminishing service acceptability. Unfortunately, these experiences are reported all over the world including high and LMIC. (30, 31)\u003c/p\u003e\n\u003cp\u003eTo interpret these findings, we applied a CST framework. Health systems are not static or linear but adaptive, interconnected entities composed of multiple agents and feedback loops. (32) In this context, emergent disparities in maternal outcomes, despite similar reported coverage, reflect deeper system dynamics. Legal exclusion, insurance fragmentation, and stigma operate as reinforcing feedback loops that perpetuate marginalization. The system\u0026rsquo;s limited adaptive capacity, evidenced by its inability to dynamically respond to migration or displacement stressors, further entrenches inequity. \u0026nbsp;For instance, while policies acknowledge the need for inclusive and intercultural health strategies, their operationalization remains uneven and reactive, rather than anticipatory or responsive. (33)\u003c/p\u003e\n\u003cp\u003eThe nonlinear nature of care access also explains the disconnect between quantitative and qualitative data. Small logistical or administrative barriers (e.g., waiting for insurer authorization) led to disproportionately large consequences (e.g., delays in antenatal care, poor outcomes), particularly for mobile or uninsured populations. These dynamics expose a critical tension in the Colombian system given by a structural emphasis on formal coverage and insurer-defined pathways, with insufficient mechanisms to accommodate complex, intersecting vulnerabilities such as displacement, poverty, ethnicity, and legal precarity.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; Our study shows an innovative integration of a contextual framework that aims to expand the understanding of SRHS access for women in vulnerable situations, such as mobility. At the same time our data reinforces the need for understanding health care as permanently changing system that has differential results to different populations based on their individual vulnerabilities (26), and the approach to healthcare needs to improve the understanding of such vulnerabilities in SRH outcomes.\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eEthics, Consent to Participate, and Consent to Publish declarations\u003c/h2\u003e\n\u003cp\u003eThe ethics committees of Universidad del Valle (Code: 034-022) and Hospital Universitario del Valle (Code: 050-2023) in Cali and Universidad Nacional de Colombia (B.FM.1.002-CE-224-23) and Hospital Engativ\u0026aacute; (Code: SNACEI-142) in Bogot\u0026aacute; approved this protocol. Written informed consent was obtained from all participants prior to data collection. In the case of underaged women, informed assent was obtained from the adolescents, and consent was obtained from parents, carers, or legal guardians.\u003c/p\u003e\n\u003ch2\u003eConsent for publication\u003c/h2\u003e\n\u003cp\u003eWritten informed consent for publication of anonymized data was obtained from all participants.\u003c/p\u003e\n\u003ch2\u003eFUNDING\u003c/h2\u003e\n\u003cp\u003eThis study was funded by the Research Fund of World Women Bank Foundation Colombia, call to field work for research groups 2022 under contract 020-2023 with Universidad del Valle as resources administrator. The funders had no role in the design of the study, data collection, analysis, interpretation of results, or the decision to submit the manuscript for publication.\u003c/p\u003e\n\u003ch2\u003eCOMPETING INTEREST DECLARATION\u003c/h2\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\n\u003cp\u003eLMBA and DLMP: Conceptualization, study design, data collection, data analysis, manuscript draftingJARR: Data collection, manuscript revisionMSC: Quantitative analysis, methodological guidance, manuscript revisionJZ: Statistical analysis and methodological oversight, manuscript revisionOAG: Clinical supervision, manuscript revisionAll authors reviewed and approved the final manuscript\u003c/p\u003e\n\u003ch2\u003eAcknowledgement\u003c/h2\u003e\n\u003cp\u003ePilar Castro, Estefania Aguado, Isabella Guerrero and Brandon David Tovar we acknowledge your excelent work and support during the data collection of this study.\u003c/p\u003e\n\u003ch2\u003eData Availability\u003c/h2\u003e\n\u003cp\u003eData will be available on reasonable request to authors.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eInforme sobre las Migraciones en el Mundo 20222022.\u003c/li\u003e\n\u003cli\u003eAlarc\u0026atilde;o V, Stefanovska-Petkovska M, Virgolino A, Santos O, Costa, A. Intersections of Immigration and Sexual/Reproductive Health: An Umbrella Literature Review with a Focus on Health Equity Social Sciences. 2021;10(2):63.\u003c/li\u003e\n\u003cli\u003eMachado S, Wiedmeyer M-l, Watt S, Servin AE, Goldenberg S. Determinants and Inequities in Sexual and Reproductive Health (SRH) Care Access Among Im/Migrant Women in Canada: Findings of a Comprehensive Review (2008\u0026ndash;2018).\u003c/li\u003e\n\u003cli\u003eHall H. Towards Contraceptive Autonomy: Examining actors\u0026rsquo; inclusion of adolescent migrant girls\u0026rsquo; voices in responses to humanitarian crises: A case study of Venezuelan migrants in Colombia [PhD thesis] University of Southampton; 2024.\u003c/li\u003e\n\u003cli\u003eOsuide JO, Parsa AD, Mahmud I, Kabir R. The effect of limited access to antenatal care on pregnancy experiences and outcomes among undocumented migrant women in Europe: a systematic review Front Glob Womens Health 2024;5:1289784.\u003c/li\u003e\n\u003cli\u003eTierney KI, Pearce N, Miller E, Steiner A, Tighe K, Presberry J, et al. Barriers to Postpartum Care: A Mixed Methods Study of Midwestern Postpartum Women. Matern Child Health J. 2024;28(1):93-103. https://doi.org/10.1016/j.mchj.2024.04.010.\u003c/li\u003e\n\u003cli\u003eMinisterio de Salud y Protecci\u0026oacute;n Social. Estad\u0026iacute;sticas vitales y Migraci\u0026oacute;n. Observatorio Nacional de Migraciones. . Bogot\u0026aacute;2024.\u003c/li\u003e\n\u003cli\u003eRivillas JC, Devia Rodriguez R, Song G, Martel A. How do we reach the girls and women who are the hardest to reach? Inequitable opportunities in reproductive and maternal health care services in armed conflict and forced displacement settings in Colombia. PLOS ONE. 2018;13(1):e0188654.\u003c/li\u003e\n\u003cli\u003eProfamilia, International Planed Parenthood Federation I. Evaluaci\u0026oacute;n de las necesidades insatisfechas en salud sexual y salud reproductiva de la poblaci\u0026oacute;n migrante en cuatro ciudades de la frontera colombo-venezolana: Arauca, C\u0026uacute;cuta, Riohacha y Valledupar. Bogot\u0026aacute;, D.C. Bogota Profamilia; 2019.\u003c/li\u003e\n\u003cli\u003eDecreto 216 de 2021. Por el cual se adopta el Estatuto Temporal de Protecci\u0026oacute;n para Migrantes Venezolanos Bajo R\u0026eacute;gimen de Protecci\u0026oacute;n Temporal y se dictan otras disposiciones en materia migratoria, Decreto 2016 (2021).\u003c/li\u003e\n\u003cli\u003ePeralta - Jim\u0026eacute;nez JA, Urrego - Mendoza ZC. Salud sexual y reproductiva de mujeres afrocolombianas v\u0026iacute;ctimas del conflicto armado en Bojay\u0026aacute;, Choc\u0026oacute;, Colombia, 2019. Estudio de m\u0026eacute;todos mixtos.. Revista Colombiana de Obstetricia y Gonecolog\u0026iacute;a. 2022;73(1):11 - 27.\u003c/li\u003e\n\u003cli\u003ePeralta-Jim\u0026eacute;nez JA, Urrego-Mendoza ZC. Salud sexual y reproductiva en mujeres v\u0026iacute;ctimas del conflicto armado. Revista de Salud P\u0026uacute;blica. 2020;22:468-74.\u003c/li\u003e\n\u003cli\u003eWallis ND, Cadena Camargo Y, Krumeich A. Adolescent pregnancy amongst displaced women in Bogota: playing between the barbs of structural violence-a qualitative study. Reprod Health. 2024;21(1):118.\u003c/li\u003e\n\u003cli\u003eOrtiz-Ruiz N, D\u0026iacute;az-Grajales C, L\u0026oacute;pez-Paz Y, Zamudio-Espinosa DC, Espinosa-Mosquera L. Sexual and reproductive health needs of Venezuelan migrants in the municipality of Cali, Colombia. Rev Panam Salud Publica. 2023;47:e4.\u003c/li\u003e\n\u003cli\u003eLey 1448 de 2011 Por la cual se dictan medidas de atenci\u0026oacute;n, asistencia y reparaci\u0026oacute;n integral a las v\u0026iacute;ctimas del conflicto armado interno y se dictan otras disposiciones., 1448 (2011).\u003c/li\u003e\n\u003cli\u003eBouaddi O, Zbiri S, Belrhiti Z. Interventions to improve migrants\u0026apos; access to sexual and reproductive health services: a scoping review. BMJ Glob Health. 2023;8(6).\u003c/li\u003e\n\u003cli\u003eDarebo TD, Spigt M, Teklewold B, Badacho AS, Mayer N, Teklewold M. The sexual and reproductive healthcare challenges when dealing with female migrants and refugees in low and middle-income countries (a qualitative evidence synthesis). BMC Public Health. 2024;24(1):520.\u003c/li\u003e\n\u003cli\u003eSoeiro RE, de Siqueira Guida JP, da-Costa-Santos J, Costa ML. Sexual and reproductive health (SRH) needs for forcibly displaced adolescent girls and young women (10-24 years old) in humanitarian settings: a mixed-methods systematic review. Reprod Health. 2023;20(1):174.\u003c/li\u003e\n\u003cli\u003eTanahashi T. Health service coverage and its evaluation. Bull. World Health Organ. 1978;56(2):295-303.\u003c/li\u003e\n\u003cli\u003eCrear-Perry J, Correa-de-Araujo R, Lewis Johnson T, McLemore MR, Neilson E, Wallace M. Social and Structural Determinants of Health Inequities in Maternal Health. J Womens Health (Larchmt). 2021;30(2):230-5.\u003c/li\u003e\n\u003cli\u003ePlsek PE, Greenhalgh T. Complexity science: The challenge of complexity in health care. Bmj. 2001;323(7313):625-8.\u003c/li\u003e\n\u003cli\u003eBurton C, Elliott A, Cochran A, Love T. Do healthcare services behave as complex systems? Analysis of patterns of attendance and implications for service delivery. BMC Med. 2018;16(1):138. https://doi.org/10.1016/j.bmcmed.2018.09.010.\u003c/li\u003e\n\u003cli\u003eDepartamento Administrativo Nacional de Estad\u0026iacute;stica (DANE). Bolet\u0026iacute;n t\u0026eacute;cnico. Pobreza monetaria en Colombia (PM). A\u0026ntilde;o 2023. In: (DANE), editor. Bogota: Departamento Administrativo Nacional de Estad\u0026iacute;stica (DANE); 2024.\u003c/li\u003e\n\u003cli\u003eAshorn P, Ashorn U, Muthiani Y, Aboubaker S, Askari S, Bahl R et al. Small vulnerable newborns\u0026mdash;big potential for impact. The Lancet. 2023;401:1692 - 706.\u003c/li\u003e\n\u003cli\u003eHarakow HI, Hvidman L, Wejse C, Eiset AH. Pregnancy complications among refugee women: A systematic review. Acta Obstet Gynecol Scand. 2021;100(4):649-57.\u003c/li\u003e\n\u003cli\u003eSheikh J, Allotey J, Kew T, Khalil H, Galadanci H, Hofmeyr GJ, et al. Vulnerabilities and reparative strategies during pregnancy, childbirth, and the postpartum period: moving from rhetoric to action. eClinicalMedicine. 2024;67:102264.\u003c/li\u003e\n\u003cli\u003eMiranda J, Sanabria MF, Annicchiarico W, Alfieri N, Cortes MS. Maternal and perinatal health among pregnant patients in the context of a migratory crisis. Int J Gynaecol Obstet. 2023;163(2):416-22.\u003c/li\u003e\n\u003cli\u003eYou X, Tan H, Hu S, Wu J, Jiang H, Peng A, et al. Effects of preconception counseling on maternal health care of migrant women in China: a community-based, cross-sectional survey. BMC Pregnancy Childbirth. 2015;15:55.\u003c/li\u003e\n\u003cli\u003eAynalem YA, Paul P, Kung JY, Hussain A, Lassi Z, Meherali S. Understanding preconception care: a scoping review of knowledge, attitudes, and practices among reproductive age individuals, healthcare workers, and stakeholders in low- and middle-income countries. BMJ Open. 2025;15(6):e099143.\u003c/li\u003e\n\u003cli\u003eMunyaneza Y, Mhlongo EM. Medical Xenophobia: The Voices of Women Refugees in Durban, Kwazulu-Natal, South Africa. bioRxiv. 2019:603753.\u003c/li\u003e\n\u003cli\u003eLeon YB, Soun B, Sudhinaraset M. Structural racism and sexual and reproductive healthcare experiences: A qualitative study among undocumented Asian and Latina. Soc Sci Med. 2025;382:118374.\u003c/li\u003e\n\u003cli\u003eTherrien MC, Normandin JM, Denis JL. Bridging complexity theory and resilience to develop surge capacity in health systems. J Health Organ Manag. 2017;31(1):96-109.\u003c/li\u003e\n\u003cli\u003eAnderson J, Chaturvedi A, Cibulskis M. Simulation tools for developing policies for complex systems: Modeling the health and safety of refugee communities. Health Care Management Science. 2007;10(4):331-9.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Footnotes","content":"\u003cp\u003ei. \u0026ldquo;Veneca\u0026rdquo; means original from Venezuela. It is sometimes used as a depictive term in Colombia.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-7359134/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7359134/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eIntroduction:\u003c/strong\u003eMigration and forced displacement present critical challenges to sexual and reproductive health (SRH) systems. Colombia hosts over 2.8 million Venezuelan migrants and a high number of internally displaced persons, offering a unique context to evaluate SRH service access and outcomes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e A mixed-methods study was conducted using a parallel convergent design. Quantitative data were collected from 929 women hospitalized for obstetric events in Bogotá and Cali between November 2023 and May 2024. Outcomes and service access were compared across migrant, forcibly displaced, and non-migrant groups. Qualitative data were collected via semi-structured interviews with women, healthcare providers, and stakeholders. The data were analyzed using a combined Tanahashi Coverage Model, Social Determinants of Health, and Complex Systems Theory framework.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003eQuantitative findings revealed no significant differences in antenatal care utilization or testing rates across groups. However, maternal mortality and perinatal mortality were higher among migrant women. Forcibly displaced women had the lowest preeclampsia and severe maternal morbidity rates. Preconception care uptake was critically low in all groups (\u0026lt;18%). Qualitative insights exposed barriers such as legal precarity, insurance fragmentation, stigma, and limited cultural competence, undermining effective service coverage and care quality despite nominal access.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions:\u003c/strong\u003eWhile SRH service availability appeared equitable, effectiveness varied by migration status. Structural and systemic barriers compromise outcomes, especially for mobile populations. A complex systems lens reveals how fragmented governance, feedback loops, and sociocultural exclusion drive disparities. Addressing these requires adaptive, culturally responsive policies that account for layered vulnerabilities.\u003c/p\u003e","manuscriptTitle":"Access to Sexual and Reproductive Health Services for Migrant Women in Colombia: A Mixed Methods Approach","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-09-23 06:09:26","doi":"10.21203/rs.3.rs-7359134/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"f2f8f3a1-98d6-4084-ac2e-e46afaaa10e0","owner":[],"postedDate":"September 23rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-09-23T06:09:28+00:00","versionOfRecord":[],"versionCreatedAt":"2025-09-23 06:09:26","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7359134","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7359134","identity":"rs-7359134","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}