The relationship between Social Determinants of Health and Access to Reproductive Health Services among Afghan Migrant Women based on the World Health Organization Model in Iran: path analysis

The relationship between Social Determinants of Health and Access to Reproductive Health Services among Afghan Migrant Women based on the World Health Organization Model in Iran: path analysis | 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 The relationship between Social Determinants of Health and Access to Reproductive Health Services among Afghan Migrant Women based on the World Health Organization Model in Iran: path analysis Zahra Bayat Jozani, Zohreh Mahmoodi, Amirhossein Takian, Farima Mohamadi, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8817187/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract Introduction Despite global commitments to universal reproductive health coverage, migrant women face profound structural barriers in low- and middle-income host countries. This study aimed to investigate the relationship between social determinants of health and access to reproductive health services. Methods A cross-sectional study was conducted in Tehran, Iran, involving 350 Afghan migrant women recruited through purposive convenience sampling. Data were collected using a researcher-developed questionnaire that included demographic and obstetric characteristics, as well as social determinants of health. Statistical analyses were performed using SPSS version 27, and the hypothesized model was examined through path analysis using LISREL version 8.8. Results The mean age of participants was 31.4 ± 7.8 years. Path analysis revealed that non-governmental organizations (NGOs) had the strongest positive direct effect on access to services (B = 0.15), while social capital exerted the strongest negative direct effect (B = -0.12). Indirectly, education showed a positive causal effect (0.015) on access through improved living conditions and health-seeking behaviors. Governance regulations (B = 0.25) and social class (B = 0.14) demonstrated the strongest positive relationships with access across both direct and indirect paths. Conclusion Governance regulations emerged as the strongest predictor of access to reproductive health services. Without upstream reforms in legal structures and residency protocols, superficial interventions will not yield sustainable improvements. NGOs play a vital role in bridging governmental gaps, whereas the negative impact of social capital highlights structural isolation as a barrier to health-seeking behaviors. Key recommendations include revising residency policies, rebuilding social trust, and strengthening civil society organizations to mitigate structural discrimination. Afghan migrants Reproductive health services Social determinants of health Path analysis Iran Migrant women Figures Figure 1 Figure 2 Figure 3 Introduction Access to sexual and reproductive health services is not just a medical need, but a fundamental human right and a cornerstone of sustainable development ( 1 ). Despite international efforts to reduce health inequalities, migrant women remain among the most vulnerable groups, excluded from formal care due to the intersection of legal, cultural, and economic barriers. This gap in access has dire consequences such as increased maternal mortality, unwanted pregnancies, and unsafe abortions, which not only challenge individual health but also public health equity ( 2 ). Iran is one of the leading host countries for migrants, currently housing approximately 5 million Afghan refugees according to official statistics. Consequently, the country faces significant challenges in providing access to sexual and reproductive health (SRHR) services for migrant women. These difficulties—stemming from structural barriers, stigma, and high costs—are particularly acute for those without legal residency permits. ( 3 , 4 , 5 ). Global evidence consistently demonstrates that migrant women, particularly those with irregular legal status, experience disproportionately poor reproductive health outcomes, including higher rates of maternal mortality, unintended pregnancy, unsafe abortion, and sexually transmitted infections (8 − 6). These disparities are driven not merely by individual factors but by social determinants of health (SDH), including migration policies, legal status, insurance coverage, stigma, and discriminatory practices within health systems ( 6 – 9 ). The World Health Organization’s Commission on Social Determinants of Health (CSDH) framework provides a robust conceptual model for understanding how structural determinants (governance, macroeconomic policies, cultural norms) and intermediary determinants (material circumstances, psychosocial factors, health system characteristics) interact to produce health inequities( 10 ) The "Commission on Social Determinants of Health" (CSDH) framework has been widely used in global health research, but its empirical application using structural equation modelling (SEM), particularly among migrant populations in the Middle East, has received limited attention ( 11 ). Iran is one of the countries that hosts a very large Afghan refugee population; however, a study examining multiple aspects of access to reproductive health services for this vulnerable group from a social determinant of health perspective is not available. Therefore, the present study was conducted with the aim of investigating the relationship between social determinants of health based on the World Health Organization's CSDH framework and access to reproductive health services among Afghan immigrant women residing in Iran, using path analysis to identify the direct and indirect effects of influencing factors. The findings of this study can provide a reliable evidence base for designing more coherent and policy-driven interventions, and can be applied not only in Iran but also in other middle-income countries hosting migrant populations. Method This cross-sectional analytical study was conducted on 350 Afghan immigrant women of reproductive age (18 to 50 years) from October 2024 to April 2025. Participants from Imam Khomeini, Baharloo, and Arash hospitals (referral hospitals), health centers affiliated with Tehran University of Medical Sciences, municipal health centers in densely populated immigrant areas, and some community-based locations (using information from Tehran Municipality and non-governmental organizations), and so on. Additionally, to better reach less accessible individuals and complete the sample, in addition to university centers, municipal centers and migrant gathering places (meeting spots recommended by key informants) were selected and included in the study using convenience sampling. The sample size of 350 individuals was deemed sufficient based on the requirements of structural equation modelling (SEM) and path analysis, according to the guidelines of Munro and Kline, and considering the 14 variables within the framework of social determinants of health ( 12 , 13 ). This sample size provides a reasonable ratio (approximately 25 observations per observed variable) and ensures stable estimates, adequate statistical power, and model convergence. Inclusion criteria included: women with Afghan citizenship or second-generation Afghan immigrants, who were of reproductive age (18–50 years old), had resided in Tehran for more than 6 months, and were able to speak Persian or Dari. Exclusion criteria: Incomplete completion or unwillingness to complete the questionnaire at any stage of the study, self-reported severe physical or mental disability preventing participation in the study. Questionnaire : Given the lack of a valid and standardized questionnaire on access to reproductive health services for immigrant women based on social determinants of health in Iranian society, an initial qualitative study was conducted. At this stage, in-depth semi-structured interviews were conducted with 20 Afghan migrant women of reproductive age and 10 key informants from healthcare providers (such as doctors, midwives, and health center managers) and officials from the Ministry of Health and non-governmental organizations. Qualitative data were analyzed using direct qualitative content analysis, considering the presence of the social determinants of health model. Based on the extracted themes and patterns, an initial set of questions for the questionnaire was designed. Then, the proposed questions were reviewed and approved in a nominal group technique session with the participation of experts (including reproductive health specialists, Ministry of Health officials, migration sociologists, and population and migration specialists). Then, face and content validity were evaluated qualitatively (expert opinions in a nominal group meeting and linguistic/cultural review by immigrants) and quantitatively. In the qualitative phase, the questionnaire was validated for cultural validity and comprehensibility by 10 Afghan immigrant women, and final revisions were made. After addressing the issues raised in both validity assessments from the participants' perspectives, the quantitative phase was also conducted. For face validity assessment, the Impact Score of each item was calculated; items with an Impact Score ≥ 1.5 were considered acceptable, and items with lower scores were removed or revised. Additionally, content validity was also examined using the Content Validity Index (CVI) and the Content Validity Ratio (CVR). Items with CVI ≥ 0.79 and CVR ≥ 0.62 were retained. Out of a total of 69 items, 68 had acceptable CVI, and one item with a CVI of 0.73 was retained after content modification. The content validity index at the scale level (S-CVI/Ave) was found to be 0.91, indicating excellent content validity of the instrument. The internal consistency of the instrument was calculated using Cronbach's alpha, which yielded an overall value of 0.89 (subscale range 0.76 to 0.88). Additionally, test-retest reliability was calculated using the intraclass correlation coefficient (ICC), which was 0.83 with a 95% confidence interval. Overall, the results obtained indicate the desirable validity and reliability of the instrument for use in the study population. The final questionnaire included sections such as demographic characteristics (21 items); obstetric and fertility history (17 items) and service utilization (31 items, mostly binary or multiple-choice); and social determinants of health (69 items, 5-point Likert scale), which covered structural, intermediate, and intersectional factors. Data collection: After obtaining the necessary permits from the Ethics Committee of Tehran University of Medical Sciences and acquiring the required approvals, we commenced our study. Initially, the researcher visited the mentioned centers. After identifying eligible individuals, the study objectives were explained to them by the principal investigator and a Dari-speaking Afghan midwifery student (as a field assistant and to increase the credibility of the information). They were all assured that their information would be kept confidential. Then, if they were willing to participate in the study, written informed consent was obtained from them. Completing each questionnaire took 45 to 70 minutes. Datal analysis : In this study, the goodness-of-fit of a simultaneous relational model of social determinants of health (SDH) affecting access to reproductive services for Afghan immigrants was examined based on the World Health Organization model ( 10 ). Initially, it was normal, and quantitative variables were examined using the Kolmogorov-Smirnov test. Generalised path analysis is an extension of ordinary regression that, in addition to showing direct effects, also reveals indirect effects and the impact of each variable on the dependent variables. Using the results obtained, a logical interpretation of the observed relationships and correlations can be provided. Data analysis was performed using SPSS-27 and LISREL-8.8 software. To examine the relationship between the research variables, Pearson correlation tests and path analysis tests were used. The relationships between the variables were expanded, and the total effect of each variable on another was evaluated by summing the "direct effect" and the "total indirect effect." The model fit was confirmed as acceptable, considering threshold values above 0.9 for the Comparative Fit Index (CFI), Goodness of Fit Index (GFI), and Bentler-Bonett Normed Fit Index (NFI), as well as a value less than 0.05 for the Root Mean Square Error of Approximation (RMSEA). Finally, the developed and evaluated model of social determinants of health (SDH) affecting access to Afghan immigrant fertility services was designed and tested based on the World Health Organization (WHO) framework. Results Demographic and fertility characteristics In the present study, information from 350 Afghan immigrant women was examined. The average age of the participants was 31.4 ± 8.7 In terms of residency status, over 70% lacked valid residency permits or had an unclear status, and only 6.6% benefited from health insurance. The majority of housewives (88 percent) and over 60 percent of them had primary education or less. The spouses' employment was reported as temporary in 83.4% of cases, with an average residency period of 7.5 years (Table 1 ). Table 1 Demographic Status of Afghan Migrant Women Participating in the Study Variable Count/ percentage Variable Count/ percentage Age Mean (SD): 31.4 (7.8) years Husband’s education Husband’s age Mean (SD): 37.2 (6.3) years • Illiterate 89 (25.4%) Duration of residence in Iran Mean (SD): 7.5 (5.2) years • Primary: 106 (30.3%) Household monthly income Mean (SD): 13.4 (4.6) million IRR • Middle/high school (incomplete) 151 (43.1%) Education • Diploma or higher 4 (1.1%) • Primary 124 (35.4%) Place of birth • Middle/high school (incomplete): 136 (38.9%) • Iran 12 (3.4%) • Diploma or higher: 2 (0.6%) • Afghanistan 338 (96.6%) Husband’s place of birth: Afghanistan 342 (97.8%) Polygamy 27 (7.7%) • Iran 8 (2.3%) Have Health insurance coverage 23(6.6%) • No of children Median: 3 Childbearing desire before migration 216(61.7%) In examining reproductive health indicators, the median number of children for these women was 3. The highest frequency is related to the 3 to 4 children group (38.3%), but the data distribution shows that society tends towards large households, with 51.1% of families having a population between 6 and 8 people. The desire to have children has increased significantly after immigration, rising from 61.7% to 89.7%. Additionally, the history of abortion has increased after migration, reaching 23.7%. In terms of delivery method, the rate of hospital births increased from 42.6% to 60.2% after migration, but 25.4% of deliveries still take place at home (Table 1 ). Correlation between variables Pearson correlation analysis between the variables showed that the variable of access to health services (Access service) has the strongest positive and significant correlation with institutional and structural factors. The highest correlation coefficients were observed with governance (r = 0.415**), macroeconomic policies (r = 0.382**), NGO activities (r = 0.364**), health-seeking behaviors (r = 0.316**), social class (r = 0.311**), and living conditions (r = 0.301**), for all of them) p < 0.01(. In contrast, the only significant negative relationship was with public policy (r = -0.130*), )p < 0.05(; other negative relationships were not significant (Table 2 ). Table 2 Correlation of Structural Factors with Intermediary and Mediating Social Determinants: of Access to Reproductive Health Services Among Afghan Migrant Women Correlation SOCIAL CLASS LIVING CONDITION QULITY SERVICE SOCIAL CAPITAL SOCIAL SUPORT SOCIAL POLICY STIGMA NGO GOVERNANC MACRO ECONOMIC POLICY CULTURE SERVICE PUBLIC POLICY HEALTH SEEKING BEHAVIOR ACCESS SERVISE SOCIAL CLASS 1 .155 ** .141 ** -0.001 .142 ** 0.089 0.077 .200 ** .257 ** .348 ** 0.065 0.104 .269 ** .311 ** LIVING CONDITION 1 .273 ** 0.037 .180 ** 0.041 .214 ** .174 ** .231 ** .241 ** 0.068 − .123 * .252 ** .301 ** QULITY SERVICE 1 0.017 .154 ** .134 * .117 * 0.1 .141 ** .189 ** 0.066 -0.094 .230 ** .160 ** SOCIAL CAPITAL 1 .265 ** 0.009 0.001 0.064 0.057 0.028 .122 * -0.031 0.059 -0.05 SOCIAL SUPORT 1 -0.05 0.083 -0 0.093 .136 * .152 ** -0.065 0.048 .164 ** SOCIAL POLICY 1 0.002 0.005 .116 * 0.096 0.06 0.092 0.104 0.063 STIGMA 1 .190 ** .109 * 0.092 0.01 0.037 .115 * .173 ** NGO 1 .397 ** .381 ** 0.071 − .136 * .362 ** .364 ** GOVERNANC 1 .402 ** 0.061 -0.079 .376 ** .415 ** MACRO ECONOMIC POLICY 1 .139 ** − .128 * .323 ** .382 ** CULTURE SERVICE 1 -0.004 0.021 .166 ** PUBLIC POLICY 1 -0.086 − .130 * HEALTH SEEKING BEHAVIOR 1 .316 ** ACCESS SERVISE 1 **. Correlation is significant at the 0.01 level (2-tailed). *. Correlation is significant at the 0.05 level (2-tailed). Path analysis Based on the results of the path analysis, after examining the paths that were significant based on t-value ≥ 1.96 (Figs. 1and 2), among the variables with a direct causal relationship to service access, non-governmental organizations had the highest positive effect (B = 0.15) and social capital had the highest negative effect (B=-0.12). This suggests that within this specific community, strong internal social ties might actually act as a barrier possibly due to heightened social stigma or traditional pressures which inhibits women from seeking reproductive health services. In the indirect pathway, education was the sole variable to demonstrate a significant positive causal effect (B = 0.015). This impact was mediated through living conditions and health-seeking behavior, suggesting that higher educational attainment enhances access to services by improving material circumstances and health-related proactivity. Among the variables that were significantly associated with access to reproductive health services through both direct and indirect paths, governance rules (B = 0.25) and social class (B = 0.14) exhibited the strongest positive causal relationships. Essentially, as these structural factors improve, the accessibility of reproductive health services for the target population increases proportionally (Table 3 ; Figs. 1 , 2). The comprehensive set of fit indices indicates that the conceptual model explaining the social determinants of reproductive health access among immigrant women aligns well with the empirical data. Consequently, the results of this path analysis can be interpreted with high statistical confidence (Table 4 ). Finally, taking into account the influential variables identified within the specific context of Iranian society, the final adapted and validated WHO model was developed. This model was updated by incorporating new components relevant to the context of Afghan migrants in Iran(Fig. 3 ). Table 3 Direct and Indirect Effects of Social Determinants of health with Access to Reproductive Health in Afghan Migrant Women n = 350 Variables Direct Effect s Indirect Effects Total Effect T-VALUE R2 Education (EDU) - *0.015552 *0.015552 - 0.34 Social Class (Sclass) *0.14 *0.00408 *0.14408 2.79 Social Support (SS) *0.09 *0.0144- *0.0756 1.97 Social Policy (Sp) 0.01 0.0074636 0.002536 0.23 Governance and Government Policies (GOV) *0.20 *0.050316 *0.250316 3.06 Macroeconomic Policies (MEP) 0.1 0.041796 0.041796 1.95 Cultural and Social Values (CSV) *0.11 0.0012- 0.11* 2.44 Public Policy (PP) 0.07- 0.0005- 0.0705- -1.62 Living Conditions (LC) 0.12* 0.126 0.12* 2.54* Social Capital (SocialC) -0.12* - - -2.70* Stigma 0.06 - - 1.38 Non-Governmental Organization (NGO) 0.15* 0.005304 0.15* 2.93 Health Seeking Behavior (HSB) 0.07 0.0204 0.0204 1.39 An asterisk (*) indicates a statistically significant effect T-Value > 1.96 Table 4 Goodness of fit indices for the model X 2 df X 2 /df NFI NNFI CFI GFI AGFI RMSEA Index 34.46 26 34.46/26 0.97 0.97 0.99 0.99 0.94 0.31 Standard X 2 /df 0.90 < 0.05 Discussion The primary finding of our study, derived from path analysis, indicates that among the variables with a significant causal relationship to reproductive health service access, governance regulations exerted the greatest overall positive effect through both direct and indirect pathways. This suggests that enhancing governance and legal frameworks—specifically residency, insurance, and employment laws—simultaneously facilitates access to reproductive health services for immigrant women through multiple avenues. This finding aligns perfectly with the World Health Organization’s Conceptual Framework for Social Determinants of Health (CSDH), which identifies governance as a fundamental structural determinant influencing all other health outcomes ( 10 ). Furthermore, consistent with the result of Marmot study, health inequality is viewed as a manifestation of the inequitable distribution of power and resources, which in this context, is reflected in housing, insurance, and employment policies ( 11 ). Furthermore, the significant indirect effect of governance underscores the mediating role of other factors, such as NGOs and living conditions. In the direct pathway, Non-Governmental Organizations (NGOs) exhibited the most substantial positive effect, highlighting their critical role in facilitating access to reproductive health services. This aligns with existing literature on migrant populations, which suggests that in countries with restrictive immigration policies, NGOs often function as a compensatory support network, bridging service gaps to ensure effective healthcare access ( 14 , 15 ). The prominent role of NGOs is also consistent with reports from international organizations like UNHCR and IOM, which indicate that NGOs in Iran frequently fill systemic voids by providing social and supportive services that complement specialized reproductive healthcare for vulnerable groups. Conversely, in our path analysis, social capital demonstrated the strongest negative effect on the outcome variable. This finding resonates with evidence suggesting that social capital does not always confer a protective effect; in certain contexts, particularly within vulnerable populations and restrictive structures, certain dimensions of social capital may be associated with adverse health outcomes or hindered service access ( 16 – 18 ). Regarding the indirect pathways in the present analysis, only education showed a positive but modest effect on service access, mediated through living conditions and health-seeking behavior. This is consistent with patterns observed in Iranian studies, where education serves as a key driver that enhances access by improving socioeconomic status (e.g., income and material conditions) and fostering proactive health-seeking behaviors, such as timely consultations and the use of preventive services ( 21 – 23 ). Among the variables exhibiting significant relationships with healthcare access through both direct and indirect pathways, social class demonstrated the most substantial positive causal effect following governance regulations. This implies that improvements in socioeconomic factors are directly correlated with enhanced access to health services. This finding resonates with previous research on health inequalities in Iran, where lower socioeconomic status (SES) consistently acts as a primary barrier to healthcare. Studies indicate that many migrants in Iran predominantly occupy lower socioeconomic strata, facing challenges such as poverty, unemployment, lack of insurance, and legal constraints, which collectively hinder the utilization of preventive and curative services. Conversely, elevating social class—through increased income or employment stability—can significantly facilitate access ( 24 – 26 ). Systematic reviews further corroborate this pattern, emphasizing the need for supportive policies to improve the socioeconomic standing of these groups to mitigate access disparities ( 25 , 26 ). A noteworthy aspect of the LISREL outputs is the positioning of the stigma variable. Although the direct path coefficient from stigma to reproductive health access was not statistically significant, its intersection with social cohesion ( $ t = 13.06 $ ) identifies it as a potent structural variable. In the studied communities, social cohesion appears to be a double-edged sword: while it strengthens internal community bonds, it simultaneously reproduces stigma, thereby increasing the 'psychological cost' of deviating from group norms to seek healthcare. Consequently, the lack of a significant direct effect should not be misinterpreted as the ineffectiveness of stigma; rather, it suggests that its impact is channeled through health-seeking behaviors (HSB) and societal pressures within social capital (SocialC). This aligns with studies on migrant populations in Asian and African contexts, which found that social norms, stigma, and family restrictions limit access to sexual and reproductive health (SRH) services. Notably, contrary to the findings of Logie et al., who argue that social cohesion fosters collective agency and reduces stigma's impact, in this specific population, social cohesion appears to play a deterrent role. Study Limitations Our study had a few limitations that should be noted. First, because we used a cross-sectional design, we can only show associations between variables rather than definitive cause-and-effect relationships. Second, we relied on self-reported data, which might be affected by social desirability bias—especially given the sensitive nature of reproductive health. Finally, reaching undocumented migrant women was difficult due to their concerns about legal status, which may limit how much our findings apply to the entire migrant population. Conclusion Drawing on the Social Determinants of Health (SDH) framework, our findings clarify that healthcare access for Afghan migrant women is far more than a medical challenge; it is deeply rooted in complex structural layers. The model confirms that macro-level governance and residency laws act as the primary gatekeepers of health, with the power to either foster equity or perpetuate inequality. One of the most striking and thought-provoking insights from this study is the subtle yet potent role of social stigma. This stigma is so deeply intertwined with internal community cohesion that it shapes health-seeking behaviors regardless of legal status, often complicating even the supportive efforts of NGOs. Ultimately, unless governance shifts from an exclusionary approach toward Universal Health Coverage (UHC) and material living conditions improve, educational interventions alone will fall short. Ending the 'legal invisibility' of migrants and dismantling the barriers of stigma are not just public health necessities—they are moral prerequisites for upholding the fundamental right to health. Abbreviations RMSEA Root Mean Square Error of Approximation -NFI Normed Fit Index- GFI Goodness of Fit Index AGFI Adjusted Goodness of Fit Index- IFI Incremental Fit Index-NNFI Non-Normed Fit Index- RFI Relative Fit Inde EDU Education -Sclass Social class- SS Social support- Sp Social policy- GOV Government- MEP Macroeconomic policy- CSV Cultural and social Value- PP Public policy -LC Living condition – Social C Social cohesion-NGO non-governmental organization – HSB Health Seeking Behavior Declarations Acknowledgements : We gratefully acknowledge the Afghan migrant women participants for sharing their experiences, the staff of reproductive health clinics at Imam Khomeini, Baharloo, and Arash hospitals, affiliated health centers of Tehran University of Medical Sciences, and the Women’s Affairs Office of Tehran Municipality for their invaluable cooperation. Authors' contributions: Author A (Zahra Bayat Jozani) and E (Seyedeh Tahereh Mirmolaei) contributed to the study design Author A (Zahra Bayat Jozani) contributed to data collection. Author B (Zohreh Mahmoodi) and D (Farima Mohamadi) performed the data analysis and drafted the initial manuscript. Authors B (Zohreh Mahmoodi) and C (Amirhossein Takian) contributed to the study design, Authors A (Zahra Bayat Jozani) and E (Seyedeh Tahereh Mirmolaei), B (Zohreh Mahmoodi) and C (Amirhossein Takian) reviewed and revised the manuscript critically for intellectual content. All authors read and approved the final manuscript. Funding: No external funding was received. The study was conducted as part of the first author’s PhD dissertation at Tehran University of Medical Sciences Availability of Data and Materials: Datasets are not publicly available due to ethical restrictions protecting participant confidentiality in this vulnerable undocumented migrant population. De-identified data are available from the corresponding author on reasonable request, subject to Ethics Committee approval. Declarations Ethics approval and consent to participate This study was conducted in accordance with the Declaration of Helsinki and approved by the Joint Research Ethics Committee of the School of Nursing and Midwifery and the School of Rehabilitation, Tehran University of Medical Sciences (approval code: IR.TUMS.FNM.REC.1402.090; 12 July 2023). Written and verbal informed consent was obtained from all participants; for those with limited literacy, the form was read aloud and verbal consent audio-recorded with permission. Consent for publication Not applicable. Competing interests : The authors declare no competing interests. References -World Health Organization. Sexual and reproductive health [Internet]. Geneva: WHO; [cited 2026 Feb 7]. Available from: https://www.who.int/health-topics/sexual-and-reproductive-health Women -UN. 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Cham (CH): Springer; 2021. Chapter 5. Available from: https://www.ncbi.nlm.nih.gov/books/NBK585686/ 10.1007/978-3-030-64171-9_5 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 30 Mar, 2026 Reviews received at journal 27 Mar, 2026 Reviewers agreed at journal 20 Mar, 2026 Reviewers agreed at journal 18 Mar, 2026 Reviewers invited by journal 18 Mar, 2026 Editor assigned by journal 16 Mar, 2026 Editor invited by journal 22 Feb, 2026 Submission checks completed at journal 22 Feb, 2026 First submitted to journal 18 Feb, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8817187","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":609580738,"identity":"af5e0681-aaf2-4064-8853-472d6609993d","order_by":0,"name":"Zahra Bayat Jozani","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABAklEQVRIiWNgGAWjYBAC+wYeCIONv//5hw8gBjsBLYwQLQYMfBJn2BhngLQwE6tFjiGHjRnMJqSFmYH34Geemj8MbAxnjz22+bVNno+ZgfHDxxzcWtgY+JKleY4ZAN3Tl26c23fbsI2ZgVly5jbcWngYeAykediAWhgOGEjn9txmBGphY+bFo0WCgcf4N88/kJYEA2nLntv2BLUYMPCYSfO2gbTkmEkz/LidSFgLM1+a5dw+Yx42iWPJhr0Nt5PbmBmb8frFvr338I033+Tk5PubDz748ee27fz25oMfPuLRAooFJh5QMIAAYxuYbMCjHgIYf8CZfwgqHgWjYBSMghEIANPDRVxqZ8gWAAAAAElFTkSuQmCC","orcid":"","institution":"Tehran University of Medical Sciences","correspondingAuthor":true,"prefix":"","firstName":"Zahra","middleName":"Bayat","lastName":"Jozani","suffix":""},{"id":609580739,"identity":"64406817-a5a0-40ec-a36c-750e65e57676","order_by":1,"name":"Zohreh Mahmoodi","email":"","orcid":"","institution":"Alborz university of medical sciences","correspondingAuthor":false,"prefix":"","firstName":"Zohreh","middleName":"","lastName":"Mahmoodi","suffix":""},{"id":609580740,"identity":"503440ed-b31f-4214-9dfc-6172a1787ff2","order_by":2,"name":"Amirhossein Takian","email":"","orcid":"","institution":"Tehran University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Amirhossein","middleName":"","lastName":"Takian","suffix":""},{"id":609580741,"identity":"1529515b-51fb-432a-8403-fe7c8bbab173","order_by":3,"name":"Farima Mohamadi","email":"","orcid":"","institution":"Shahid Beheshti University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Farima","middleName":"","lastName":"Mohamadi","suffix":""},{"id":609580746,"identity":"e8692e56-174a-4b21-9de0-a4293ff0d3e8","order_by":4,"name":"Seyedeh Tahereh Mirmolaei","email":"","orcid":"","institution":"Tehran University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Seyedeh","middleName":"Tahereh","lastName":"Mirmolaei","suffix":""}],"badges":[],"createdAt":"2026-02-07 17:38:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8817187/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8817187/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":105187020,"identity":"e7591203-2f11-44d1-b8d4-f77451c6e597","added_by":"auto","created_at":"2026-03-23 08:42:43","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":183708,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePath Analysis of the Social Determinants of Health (SDH) Model Influencing Reproductive Health Access among Afghan Migrants; Based on T-values\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSolid lines (black/blue) indicate statistically significant pathways (T-value≥1.96, p \u0026lt; 0.05), while red lines represent non-significant relationships (T-value≥1.96)\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8817187/v1/ed49969eb044b288974e8503.png"},{"id":105187032,"identity":"bd92fb0b-2928-4901-a712-781577da0dfd","added_by":"auto","created_at":"2026-03-23 08:42:58","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":122311,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePath Analysis of the Social Determinants of Health (SDH) Model Influencing Reproductive Health Access among Afghan Migrants; Standardized Coefficients(B).\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8817187/v1/5014343ff5523ee8828820d9.png"},{"id":105187017,"identity":"895aa83d-3ee2-4c8a-b648-9fc8c22ed9ae","added_by":"auto","created_at":"2026-03-23 08:42:42","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":83601,"visible":true,"origin":"","legend":"\u003cp\u003eFinal developed WHO model (adapted from the CSDH framework with Iran-specific contextual components)\u003c/p\u003e\n\u003cp\u003eThe variables that were empirically tested in this study are highlighted in blue. Variables demonstrating a negative or inhibitory effect are highlighted in red.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8817187/v1/81bb6fddaa5ee7f1093aa155.png"},{"id":105187236,"identity":"e2801491-3497-47d1-b583-cf5e4575bb6e","added_by":"auto","created_at":"2026-03-23 08:43:40","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1298132,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8817187/v1/c6acffea-ca99-40a9-bad6-74b082f55488.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eThe relationship between Social Determinants of Health and Access to Reproductive Health Services among Afghan Migrant Women based on the World Health Organization Model in Iran: path analysis \u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAccess to sexual and reproductive health services is not just a medical need, but a fundamental human right and a cornerstone of sustainable development (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). Despite international efforts to reduce health inequalities, migrant women remain among the most vulnerable groups, excluded from formal care due to the intersection of legal, cultural, and economic barriers. This gap in access has dire consequences such as increased maternal mortality, unwanted pregnancies, and unsafe abortions, which not only challenge individual health but also public health equity (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIran is one of the leading host countries for migrants, currently housing approximately 5\u0026nbsp;million Afghan refugees according to official statistics. Consequently, the country faces significant challenges in providing access to sexual and reproductive health (SRHR) services for migrant women. These difficulties\u0026mdash;stemming from structural barriers, stigma, and high costs\u0026mdash;are particularly acute for those without legal residency permits. (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eGlobal evidence consistently demonstrates that migrant women, particularly those with irregular legal status, experience disproportionately poor reproductive health outcomes, including higher rates of maternal mortality, unintended pregnancy, unsafe abortion, and sexually transmitted infections (8\u0026thinsp;\u0026minus;\u0026thinsp;6). These disparities are driven not merely by individual factors but by social determinants of health (SDH), including migration policies, legal status, insurance coverage, stigma, and discriminatory practices within health systems (\u003cspan additionalcitationids=\"CR7 CR8\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). The World Health Organization\u0026rsquo;s Commission on Social Determinants of Health (CSDH) framework provides a robust conceptual model for understanding how structural determinants (governance, macroeconomic policies, cultural norms) and intermediary determinants (material circumstances, psychosocial factors, health system characteristics) interact to produce health inequities(\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eThe \"Commission on Social Determinants of Health\" (CSDH) framework has been widely used in global health research, but its empirical application using structural equation modelling (SEM), particularly among migrant populations in the Middle East, has received limited attention (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). Iran is one of the countries that hosts a very large Afghan refugee population; however, a study examining multiple aspects of access to reproductive health services for this vulnerable group from a social determinant of health perspective is not available. Therefore, the present study was conducted with the aim of investigating the relationship between social determinants of health based on the World Health Organization's CSDH framework and access to reproductive health services among Afghan immigrant women residing in Iran, using path analysis to identify the direct and indirect effects of influencing factors.\u003c/p\u003e \u003cp\u003eThe findings of this study can provide a reliable evidence base for designing more coherent and policy-driven interventions, and can be applied not only in Iran but also in other middle-income countries hosting migrant populations.\u003c/p\u003e"},{"header":"Method","content":"\u003cp\u003eThis cross-sectional analytical study was conducted on 350 Afghan immigrant women of reproductive age (18 to 50 years) from October 2024 to April 2025. Participants from Imam Khomeini, Baharloo, and Arash hospitals (referral hospitals), health centers affiliated with Tehran University of Medical Sciences, municipal health centers in densely populated immigrant areas, and some community-based locations (using information from Tehran Municipality and non-governmental organizations), and so on. Additionally, to better reach less accessible individuals and complete the sample, in addition to university centers, municipal centers and migrant gathering places (meeting spots recommended by key informants) were selected and included in the study using convenience sampling.\u003c/p\u003e\n\u003cp\u003eThe sample size of 350 individuals was deemed sufficient based on the requirements of structural equation modelling (SEM) and path analysis, according to the guidelines of Munro and Kline, and considering the 14 variables within the framework of social determinants of health (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). This sample size provides a reasonable ratio (approximately 25 observations per observed variable) and ensures stable estimates, adequate statistical power, and model convergence.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInclusion criteria\u003c/strong\u003e included: women with Afghan citizenship or second-generation Afghan immigrants, who were of reproductive age (18\u0026ndash;50 years old), had resided in Tehran for more than 6 months, and were able to speak Persian or Dari.\u003c/p\u003e\n\u003cp\u003eExclusion criteria: Incomplete completion or unwillingness to complete the questionnaire at any stage of the study, self-reported severe physical or mental disability preventing participation in the study.\u003c/p\u003e\n\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\n \u003ch2\u003e\u003cstrong\u003eQuestionnaire\u003c/strong\u003e:\u003c/h2\u003e\n \u003cp\u003eGiven the lack of a valid and standardized questionnaire on access to reproductive health services for immigrant women based on social determinants of health in Iranian society, an initial qualitative study was conducted. At this stage, in-depth semi-structured interviews were conducted with 20 Afghan migrant women of reproductive age and 10 key informants from healthcare providers (such as doctors, midwives, and health center managers) and officials from the Ministry of Health and non-governmental organizations. Qualitative data were analyzed using direct qualitative content analysis, considering the presence of the social determinants of health model. Based on the extracted themes and patterns, an initial set of questions for the questionnaire was designed.\u003c/p\u003e\n \u003cp\u003eThen, the proposed questions were reviewed and approved in a nominal group technique session with the participation of experts (including reproductive health specialists, Ministry of Health officials, migration sociologists, and population and migration specialists). Then, face and content validity were evaluated qualitatively (expert opinions in a nominal group meeting and linguistic/cultural review by immigrants) and quantitatively. In the qualitative phase, the questionnaire was validated for cultural validity and comprehensibility by 10 Afghan immigrant women, and final revisions were made. After addressing the issues raised in both validity assessments from the participants\u0026apos; perspectives, the quantitative phase was also conducted. For face validity assessment, the Impact Score of each item was calculated; items with an Impact Score\u0026thinsp;\u0026ge;\u0026thinsp;1.5 were considered acceptable, and items with lower scores were removed or revised.\u003c/p\u003e\n \u003cp\u003eAdditionally, content validity was also examined using the Content Validity Index (CVI) and the Content Validity Ratio (CVR). Items with CVI\u0026thinsp;\u0026ge;\u0026thinsp;0.79 and CVR\u0026thinsp;\u0026ge;\u0026thinsp;0.62 were retained. Out of a total of 69 items, 68 had acceptable CVI, and one item with a CVI of 0.73 was retained after content modification. The content validity index at the scale level (S-CVI/Ave) was found to be 0.91, indicating excellent content validity of the instrument.\u003c/p\u003e\n \u003cp\u003eThe internal consistency of the instrument was calculated using Cronbach\u0026apos;s alpha, which yielded an overall value of 0.89 (subscale range 0.76 to 0.88). Additionally, test-retest reliability was calculated using the intraclass correlation coefficient (ICC), which was 0.83 with a 95% confidence interval. Overall, the results obtained indicate the desirable validity and reliability of the instrument for use in the study population.\u003c/p\u003e\n \u003cp\u003eThe final questionnaire included sections such as demographic characteristics (21 items); obstetric and fertility history (17 items) and service utilization (31 items, mostly binary or multiple-choice); and social determinants of health (69 items, 5-point Likert scale), which covered structural, intermediate, and intersectional factors.\u003c/p\u003e\n\u003c/div\u003e\n\u003ch3\u003eData collection:\u003c/h3\u003e\n\u003cp\u003eAfter obtaining the necessary permits from the Ethics Committee of Tehran University of Medical Sciences and acquiring the required approvals, we commenced our study. Initially, the researcher visited the mentioned centers. After identifying eligible individuals, the study objectives were explained to them by the principal investigator and a Dari-speaking Afghan midwifery student (as a field assistant and to increase the credibility of the information). They were all assured that their information would be kept confidential. Then, if they were willing to participate in the study, written informed consent was obtained from them. Completing each questionnaire took 45 to 70 minutes.\u003c/p\u003e\n\u003cdiv class=\"Heading\"\u003e\u003cstrong\u003eDatal analysis\u003c/strong\u003e:\u003c/div\u003e\n\u003cp\u003eIn this study, the goodness-of-fit of a simultaneous relational model of social determinants of health (SDH) affecting access to reproductive services for Afghan immigrants was examined based on the World Health Organization model (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eInitially, it was normal, and quantitative variables were examined using the Kolmogorov-Smirnov test. Generalised path analysis is an extension of ordinary regression that, in addition to showing direct effects, also reveals indirect effects and the impact of each variable on the dependent variables. Using the results obtained, a logical interpretation of the observed relationships and correlations can be provided. Data analysis was performed using SPSS-27 and LISREL-8.8 software. To examine the relationship between the research variables, Pearson correlation tests and path analysis tests were used. The relationships between the variables were expanded, and the total effect of each variable on another was evaluated by summing the \u0026quot;direct effect\u0026quot; and the \u0026quot;total indirect effect.\u0026quot;\u003c/p\u003e\n\u003cp\u003eThe model fit was confirmed as acceptable, considering threshold values above 0.9 for the Comparative Fit Index (CFI), Goodness of Fit Index (GFI), and Bentler-Bonett Normed Fit Index (NFI), as well as a value less than 0.05 for the Root Mean Square Error of Approximation (RMSEA). Finally, the developed and evaluated model of social determinants of health (SDH) affecting access to Afghan immigrant fertility services was designed and tested based on the World Health Organization (WHO) framework.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\n \u003ch2\u003eDemographic and fertility characteristics\u003c/h2\u003e\n \u003cp\u003eIn the present study, information from 350 Afghan immigrant women was examined. The average age of the participants was 31.4\u0026thinsp;\u0026plusmn;\u0026thinsp;8.7 In terms of residency status, over 70% lacked valid residency permits or had an unclear status, and only 6.6% benefited from health insurance. The majority of housewives (88 percent) and over 60 percent of them had primary education or less. The spouses\u0026apos; employment was reported as temporary in 83.4% of cases, with an average residency period of 7.5 years (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eDemographic Status of Afghan Migrant Women Participating in the Study\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"4\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eCount/ percentage\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003eCount/ percentage\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eMean (SD): 31.4 (7.8) years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eHusband\u0026rsquo;s education\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eHusband\u0026rsquo;s age\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eMean (SD): 37.2 (6.3) years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e\u0026bull; Illiterate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e89 (25.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eDuration of residence in Iran\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eMean (SD): 7.5 (5.2) years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e\u0026bull; Primary:\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e106 (30.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eHousehold monthly income\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eMean (SD): 13.4 (4.6) million IRR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e\u0026bull; Middle/high school (incomplete)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e151 (43.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eEducation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e\u0026bull; Diploma or higher\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e4 (1.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u0026bull; Primary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e124 (35.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003ePlace of birth\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u0026bull; Middle/high school (incomplete):\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e136 (38.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e\u0026bull; Iran\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e12 (3.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u0026bull; Diploma or higher:\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e2 (0.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e\u0026bull; Afghanistan\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e338 (96.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eHusband\u0026rsquo;s place of birth: Afghanistan\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e342 (97.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003ePolygamy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e27 (7.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u0026bull; Iran\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e8 (2.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eHave Health insurance coverage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\n \u003cp\u003e23(6.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u0026bull; No of children\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eMedian: 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eChildbearing desire before migration\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e216(61.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cp\u003eIn examining reproductive health indicators, the median number of children for these women was 3. The highest frequency is related to the 3 to 4 children group (38.3%), but the data distribution shows that society tends towards large households, with 51.1% of families having a population between 6 and 8 people. The desire to have children has increased significantly after immigration, rising from 61.7% to 89.7%. Additionally, the history of abortion has increased after migration, reaching 23.7%. In terms of delivery method, the rate of hospital births increased from 42.6% to 60.2% after migration, but 25.4% of deliveries still take place at home (Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\n \u003ch2\u003eCorrelation between variables\u003c/h2\u003e\n \u003cp\u003ePearson correlation analysis between the variables showed that the variable of access to health services (Access service) has the strongest positive and significant correlation with institutional and structural factors. The highest correlation coefficients were observed with governance (r\u0026thinsp;=\u0026thinsp;0.415**), macroeconomic policies (r\u0026thinsp;=\u0026thinsp;0.382**), NGO activities (r\u0026thinsp;=\u0026thinsp;0.364**), health-seeking behaviors (r\u0026thinsp;=\u0026thinsp;0.316**), social class (r\u0026thinsp;=\u0026thinsp;0.311**), and living conditions (r\u0026thinsp;=\u0026thinsp;0.301**), for all of them) p\u0026thinsp;\u0026lt;\u0026thinsp;0.01(. In contrast, the only significant negative relationship was with public policy (r = -0.130*), )p\u0026thinsp;\u0026lt;\u0026thinsp;0.05(; other negative relationships were not significant (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"left\" class=\"colspec\" colname=\"c15\" colnum=\"15\"\u003e\u003cbr\u003e\u003c/div\u003e\u0026nbsp;\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eCorrelation of Structural Factors with Intermediary and Mediating Social Determinants: of Access to Reproductive Health Services Among Afghan Migrant Women\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"15\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eCorrelation\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eSOCIAL CLASS\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eLIVING CONDITION\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003eQULITY SERVICE\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003eSOCIAL CAPITAL\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003eSOCIAL SUPORT\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003eSOCIAL POLICY\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c8\"\u003e\n \u003cp\u003eSTIGMA\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c9\"\u003e\n \u003cp\u003eNGO\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c10\"\u003e\n \u003cp\u003eGOVERNANC\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c11\"\u003e\n \u003cp\u003eMACRO ECONOMIC POLICY\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c12\"\u003e\n \u003cp\u003eCULTURE SERVICE\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c13\"\u003e\n \u003cp\u003ePUBLIC POLICY\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c14\"\u003e\n \u003cp\u003eHEALTH SEEKING BEHAVIOR\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c15\"\u003e\n \u003cp\u003eACCESS SERVISE\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eSOCIAL CLASS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e.155\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e.141\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e-0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e.142\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e0.089\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\n \u003cp\u003e0.077\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c9\"\u003e\n \u003cp\u003e.200\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\n \u003cp\u003e.257\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c11\"\u003e\n \u003cp\u003e.348\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c12\"\u003e\n \u003cp\u003e0.065\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c13\"\u003e\n \u003cp\u003e0.104\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c14\"\u003e\n \u003cp\u003e.269\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c15\"\u003e\n \u003cp\u003e.311\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eLIVING CONDITION\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e.273\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e0.037\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e.180\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e0.041\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\n \u003cp\u003e.214\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c9\"\u003e\n \u003cp\u003e.174\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\n \u003cp\u003e.231\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c11\"\u003e\n \u003cp\u003e.241\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c12\"\u003e\n \u003cp\u003e0.068\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c13\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.123\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c14\"\u003e\n \u003cp\u003e.252\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c15\"\u003e\n \u003cp\u003e.301\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eQULITY SERVICE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e0.017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e.154\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e.134\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\n \u003cp\u003e.117\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c9\"\u003e\n \u003cp\u003e0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\n \u003cp\u003e.141\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c11\"\u003e\n \u003cp\u003e.189\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c12\"\u003e\n \u003cp\u003e0.066\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c13\"\u003e\n \u003cp\u003e-0.094\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c14\"\u003e\n \u003cp\u003e.230\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c15\"\u003e\n \u003cp\u003e.160\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eSOCIAL CAPITAL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e.265\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c9\"\u003e\n \u003cp\u003e0.064\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\n \u003cp\u003e0.057\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c11\"\u003e\n \u003cp\u003e0.028\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c12\"\u003e\n \u003cp\u003e.122\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c13\"\u003e\n \u003cp\u003e-0.031\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c14\"\u003e\n \u003cp\u003e0.059\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c15\"\u003e\n \u003cp\u003e-0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eSOCIAL SUPORT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e-0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\n \u003cp\u003e0.083\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c9\"\u003e\n \u003cp\u003e-0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\n \u003cp\u003e0.093\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c11\"\u003e\n \u003cp\u003e.136\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c12\"\u003e\n \u003cp\u003e.152\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c13\"\u003e\n \u003cp\u003e-0.065\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c14\"\u003e\n \u003cp\u003e0.048\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c15\"\u003e\n \u003cp\u003e.164\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eSOCIAL POLICY\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c9\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\n \u003cp\u003e.116\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c11\"\u003e\n \u003cp\u003e0.096\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c12\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c13\"\u003e\n \u003cp\u003e0.092\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c14\"\u003e\n \u003cp\u003e0.104\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c15\"\u003e\n \u003cp\u003e0.063\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eSTIGMA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c9\"\u003e\n \u003cp\u003e.190\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\n \u003cp\u003e.109\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c11\"\u003e\n \u003cp\u003e0.092\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c12\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c13\"\u003e\n \u003cp\u003e0.037\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c14\"\u003e\n \u003cp\u003e.115\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c15\"\u003e\n \u003cp\u003e.173\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eNGO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c9\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\n \u003cp\u003e.397\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c11\"\u003e\n \u003cp\u003e.381\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c12\"\u003e\n \u003cp\u003e0.071\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c13\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.136\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c14\"\u003e\n \u003cp\u003e.362\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c15\"\u003e\n \u003cp\u003e.364\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eGOVERNANC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c11\"\u003e\n \u003cp\u003e.402\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c12\"\u003e\n \u003cp\u003e0.061\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c13\"\u003e\n \u003cp\u003e-0.079\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c14\"\u003e\n \u003cp\u003e.376\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c15\"\u003e\n \u003cp\u003e.415\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eMACRO ECONOMIC POLICY\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c11\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c12\"\u003e\n \u003cp\u003e.139\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c13\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.128\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c14\"\u003e\n \u003cp\u003e.323\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c15\"\u003e\n \u003cp\u003e.382\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eCULTURE SERVICE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c12\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c13\"\u003e\n \u003cp\u003e-0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c14\"\u003e\n \u003cp\u003e0.021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c15\"\u003e\n \u003cp\u003e.166\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003ePUBLIC POLICY\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c13\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c14\"\u003e\n \u003cp\u003e-0.086\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c15\"\u003e\n \u003cp\u003e\u0026minus;\u0026thinsp;.130\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eHEALTH SEEKING BEHAVIOR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c14\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c15\"\u003e\n \u003cp\u003e.316\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eACCESS SERVISE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c12\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c13\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c14\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c15\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"15\" nameend=\"c15\" namest=\"c1\"\u003e\n \u003cp\u003e**. Correlation is significant at the 0.01 level (2-tailed).\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"15\"\u003e*. Correlation is significant at the 0.05 level (2-tailed).\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e\n\u003ch3\u003ePath analysis\u003c/h3\u003e\n\u003cp\u003eBased on the results of the path analysis, after examining the paths that were significant based on t-value\u0026thinsp;\u0026ge;\u0026thinsp;1.96 (Figs.\u0026nbsp;1and 2), among the variables with a direct causal relationship to service access, non-governmental organizations had the highest positive effect (B\u0026thinsp;=\u0026thinsp;0.15) and social capital had the highest negative effect (B=-0.12). This suggests that within this specific community, strong internal social ties might actually act as a barrier possibly due to heightened social stigma or traditional pressures which inhibits women from seeking reproductive health services.\u003c/p\u003e\n\u003cp\u003eIn the indirect pathway, education was the sole variable to demonstrate a significant positive causal effect (B\u0026thinsp;=\u0026thinsp;0.015). This impact was mediated through living conditions and health-seeking behavior, suggesting that higher educational attainment enhances access to services by improving material circumstances and health-related proactivity.\u003c/p\u003e\n\u003cp\u003eAmong the variables that were significantly associated with access to reproductive health services through both direct and indirect paths, governance rules (B\u0026thinsp;=\u0026thinsp;0.25) and social class (B\u0026thinsp;=\u0026thinsp;0.14) exhibited the strongest positive causal relationships. Essentially, as these structural factors improve, the accessibility of reproductive health services for the target population increases proportionally (Table \u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e; Figs. \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, 2).\u003c/p\u003e\n\u003cp\u003eThe comprehensive set of fit indices indicates that the conceptual model explaining the social determinants of reproductive health access among immigrant women aligns well with the empirical data. Consequently, the results of this path analysis can be interpreted with high statistical confidence (Table \u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e\n\u003cp\u003eFinally, taking into account the influential variables identified within the specific context of Iranian society, the final adapted and validated WHO model was developed. This model was updated by incorporating new components relevant to the context of Afghan migrants in Iran(Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eDirect and Indirect Effects of Social Determinants of health with Access to Reproductive Health in Afghan Migrant Women n\u0026thinsp;=\u0026thinsp;350\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"6\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eDirect Effect s\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003eIndirect Effects\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003eTotal Effect\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003eT-VALUE\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003eR2\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eEducation (EDU)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e*0.015552\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e*0.015552\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\" morerows=\"12\" rowspan=\"13\"\u003e\n \u003cp\u003e0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eSocial Class (Sclass)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e*0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e*0.00408\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e*0.14408\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e2.79\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eSocial Support (SS)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e*0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e*0.0144-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e*0.0756\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e1.97\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eSocial Policy (Sp)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.0074636\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e0.002536\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eGovernance and Government Policies (GOV)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e*0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e*0.050316\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e*0.250316\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e3.06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eMacroeconomic Policies (MEP)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e0.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.041796\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e0.041796\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e1.95\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eCultural and Social Values (CSV)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e*0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.0012-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e0.11*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e2.44\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003ePublic Policy (PP)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e0.07-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.0005-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e0.0705-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e-1.62\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eLiving Conditions (LC)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e0.12*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.126\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e0.12*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e2.54*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eSocial Capital (SocialC)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e-0.12*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e-2.70*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eStigma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e1.38\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eNon-Governmental Organization (NGO)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e0.15*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.005304\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e0.15*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e2.93\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003eHealth Seeking Behavior\u003c/p\u003e\n \u003cp\u003e(HSB)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e0.0204\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e0.0204\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e1.39\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003eAn asterisk (*) indicates a statistically significant effect T-Value\u0026thinsp;\u0026gt;\u0026thinsp;1.96\u003c/p\u003e\n\u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eGoodness of fit indices for the model\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"10\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003eX\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003edf\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003eX\u003csup\u003e2\u003c/sup\u003e/df\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003eNFI\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003eNNFI\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003eCFI\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c8\"\u003e\n \u003cp\u003eGFI\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c9\"\u003e\n \u003cp\u003eAGFI\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\" colname=\"c10\"\u003e\n \u003cp\u003eRMSEA\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eIndex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c2\"\u003e\n \u003cp\u003e34.46\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c3\"\u003e\n \u003cp\u003e26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c4\"\u003e\n \u003cp\u003e34.46/26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c5\"\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c6\"\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c7\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c8\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c9\"\u003e\n \u003cp\u003e0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\n \u003cp\u003e0.31\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colname=\"c1\"\u003e\n \u003cp\u003e\u003cstrong\u003eStandard\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e\n \u003cp\u003eX\u003csup\u003e2\u003c/sup\u003e/df\u0026thinsp;\u0026lt;\u0026thinsp;5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"5\" nameend=\"c9\" namest=\"c5\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colname=\"c10\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe primary finding of our study, derived from path analysis, indicates that among the variables with a significant causal relationship to reproductive health service access, governance regulations exerted the greatest overall positive effect through both direct and indirect pathways. This suggests that enhancing governance and legal frameworks\u0026mdash;specifically residency, insurance, and employment laws\u0026mdash;simultaneously facilitates access to reproductive health services for immigrant women through multiple avenues.\u003c/p\u003e \u003cp\u003eThis finding aligns perfectly with the World Health Organization\u0026rsquo;s Conceptual Framework for Social Determinants of Health (CSDH), which identifies governance as a fundamental structural determinant influencing all other health outcomes (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Furthermore, consistent with the result of Marmot study, health inequality is viewed as a manifestation of the inequitable distribution of power and resources, which in this context, is reflected in housing, insurance, and employment policies (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFurthermore, the significant indirect effect of governance underscores the mediating role of other factors, such as NGOs and living conditions. In the direct pathway, Non-Governmental Organizations (NGOs) exhibited the most substantial positive effect, highlighting their critical role in facilitating access to reproductive health services. This aligns with existing literature on migrant populations, which suggests that in countries with restrictive immigration policies, NGOs often function as a compensatory support network, bridging service gaps to ensure effective healthcare access (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe prominent role of NGOs is also consistent with reports from international organizations like UNHCR and IOM, which indicate that NGOs in Iran frequently fill systemic voids by providing social and supportive services that complement specialized reproductive healthcare for vulnerable groups.\u003c/p\u003e \u003cp\u003eConversely, in our path analysis, social capital demonstrated the strongest negative effect on the outcome variable. This finding resonates with evidence suggesting that social capital does not always confer a protective effect; in certain contexts, particularly within vulnerable populations and restrictive structures, certain dimensions of social capital may be associated with adverse health outcomes or hindered service access (\u003cspan additionalcitationids=\"CR17\" citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eRegarding the indirect pathways in the present analysis, only education showed a positive but modest effect on service access, mediated through living conditions and health-seeking behavior. This is consistent with patterns observed in Iranian studies, where education serves as a key driver that enhances access by improving socioeconomic status (e.g., income and material conditions) and fostering proactive health-seeking behaviors, such as timely consultations and the use of preventive services (\u003cspan additionalcitationids=\"CR22\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAmong the variables exhibiting significant relationships with healthcare access through both direct and indirect pathways, social class demonstrated the most substantial positive causal effect following governance regulations. This implies that improvements in socioeconomic factors are directly correlated with enhanced access to health services. This finding resonates with previous research on health inequalities in Iran, where lower socioeconomic status (SES) consistently acts as a primary barrier to healthcare. Studies indicate that many migrants in Iran predominantly occupy lower socioeconomic strata, facing challenges such as poverty, unemployment, lack of insurance, and legal constraints, which collectively hinder the utilization of preventive and curative services. Conversely, elevating social class\u0026mdash;through increased income or employment stability\u0026mdash;can significantly facilitate access (\u003cspan additionalcitationids=\"CR25\" citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). Systematic reviews further corroborate this pattern, emphasizing the need for supportive policies to improve the socioeconomic standing of these groups to mitigate access disparities (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eA noteworthy aspect of the LISREL outputs is the positioning of the stigma variable. Although the direct path coefficient from stigma to reproductive health access was not statistically significant, its intersection with social cohesion (\u003cspan\u003e$\u003c/span\u003et\u0026thinsp;=\u0026thinsp;13.06\u003cspan\u003e$\u003c/span\u003e) identifies it as a potent structural variable. In the studied communities, social cohesion appears to be a double-edged sword: while it strengthens internal community bonds, it simultaneously reproduces stigma, thereby increasing the 'psychological cost' of deviating from group norms to seek healthcare. Consequently, the lack of a significant direct effect should not be misinterpreted as the ineffectiveness of stigma; rather, it suggests that its impact is channeled through health-seeking behaviors (HSB) and societal pressures within social capital (SocialC). This aligns with studies on migrant populations in Asian and African contexts, which found that social norms, stigma, and family restrictions limit access to sexual and reproductive health (SRH) services. Notably, contrary to the findings of Logie et al., who argue that social cohesion fosters collective agency and reduces stigma's impact, in this specific population, social cohesion appears to play a deterrent role.\u003c/p\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eStudy Limitations\u003c/h2\u003e \u003cp\u003eOur study had a few limitations that should be noted. First, because we used a cross-sectional design, we can only show associations between variables rather than definitive cause-and-effect relationships. Second, we relied on self-reported data, which might be affected by social desirability bias\u0026mdash;especially given the sensitive nature of reproductive health. Finally, reaching undocumented migrant women was difficult due to their concerns about legal status, which may limit how much our findings apply to the entire migrant population.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eDrawing on the Social Determinants of Health (SDH) framework, our findings clarify that healthcare access for Afghan migrant women is far more than a medical challenge; it is deeply rooted in complex structural layers. The model confirms that macro-level governance and residency laws act as the primary gatekeepers of health, with the power to either foster equity or perpetuate inequality.\u003c/p\u003e \u003cp\u003eOne of the most striking and thought-provoking insights from this study is the subtle yet potent role of social stigma. This stigma is so deeply intertwined with internal community cohesion that it shapes health-seeking behaviors regardless of legal status, often complicating even the supportive efforts of NGOs. Ultimately, unless governance shifts from an exclusionary approach toward Universal Health Coverage (UHC) and material living conditions improve, educational interventions alone will fall short. Ending the 'legal invisibility' of migrants and dismantling the barriers of stigma are not just public health necessities\u0026mdash;they are moral prerequisites for upholding the fundamental right to health.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eRMSEA Root Mean Square Error of Approximation -NFI Normed Fit Index- GFI Goodness of Fit Index AGFI Adjusted Goodness of Fit Index- IFI Incremental Fit Index-NNFI Non-Normed Fit Index- RFI Relative Fit Inde EDU Education -Sclass Social class- SS Social support- Sp Social policy- GOV Government- MEP Macroeconomic policy- CSV Cultural and social Value- PP Public policy -LC Living condition – Social C Social cohesion-NGO non-governmental organization – HSB Health Seeking Behavior\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e: We gratefully acknowledge the Afghan migrant women participants for sharing their experiences, the staff of reproductive health clinics at Imam Khomeini, Baharloo, and Arash hospitals, affiliated health centers of Tehran University of Medical Sciences, and the Women’s Affairs Office of Tehran Municipality for their invaluable cooperation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors' contributions:\u003c/strong\u003e Author A (Zahra Bayat Jozani) and E (Seyedeh Tahereh Mirmolaei) contributed to the study design Author A (Zahra Bayat Jozani) contributed to data collection. Author B (Zohreh Mahmoodi) and D (Farima Mohamadi) performed the data analysis and drafted the initial manuscript. \u0026nbsp;Authors B (Zohreh Mahmoodi) and C (Amirhossein Takian) contributed to the study design, Authors A (Zahra Bayat Jozani) and E (Seyedeh Tahereh Mirmolaei), B (Zohreh Mahmoodi) and C (Amirhossein Takian) reviewed and revised the manuscript critically for intellectual content. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e No external funding was received. The study was conducted as part of the first author’s PhD dissertation at Tehran University of Medical Sciences\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of Data and Materials:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Datasets are not publicly available due to ethical restrictions protecting participant confidentiality in this vulnerable undocumented migrant population. De-identified data are available from the corresponding author on reasonable request, subject to Ethics Committee approval.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclarations Ethics approval and consent to participate\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was conducted in accordance with the Declaration of Helsinki and approved by the Joint Research Ethics Committee of the School of Nursing and Midwifery and the School of Rehabilitation, Tehran University of Medical Sciences (approval code: IR.TUMS.FNM.REC.1402.090; 12 July 2023). Written and verbal informed consent was obtained from all participants; for those with limited literacy, the form was read aloud and verbal consent audio-recorded with permission.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e Not applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e: The authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003e-World Health Organization. Sexual and reproductive health [Internet]. Geneva: WHO; [cited 2026 Feb 7]. 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Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ncbi.nlm.nih.gov/books/NBK585686/\u003c/span\u003e\u003cspan address=\"https://www.ncbi.nlm.nih.gov/books/NBK585686/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/978-3-030-64171-9_5\u003c/span\u003e\u003cspan address=\"10.1007/978-3-030-64171-9_5\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Afghan migrants, Reproductive health services, Social determinants of health, Path analysis, Iran, Migrant women","lastPublishedDoi":"10.21203/rs.3.rs-8817187/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8817187/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e \u003cb\u003eIntroduction\u003c/b\u003e Despite global commitments to universal reproductive health coverage, migrant women face profound structural barriers in low- and middle-income host countries. This study aimed to investigate the relationship between social determinants of health and access to reproductive health services.\u003c/p\u003e \u003cp\u003e \u003cb\u003eMethods\u003c/b\u003e A cross-sectional study was conducted in Tehran, Iran, involving 350 Afghan migrant women recruited through purposive convenience sampling. Data were collected using a researcher-developed questionnaire that included demographic and obstetric characteristics, as well as social determinants of health. Statistical analyses were performed using SPSS version 27, and the hypothesized model was examined through path analysis using LISREL version 8.8.\u003c/p\u003e \u003cp\u003e \u003cb\u003eResults\u003c/b\u003e The mean age of participants was 31.4\u0026thinsp;\u0026plusmn;\u0026thinsp;7.8 years. Path analysis revealed that non-governmental organizations (NGOs) had the strongest positive direct effect on access to services (B\u0026thinsp;=\u0026thinsp;0.15), while social capital exerted the strongest negative direct effect (B = -0.12). Indirectly, education showed a positive causal effect (0.015) on access through improved living conditions and health-seeking behaviors. Governance regulations (B\u0026thinsp;=\u0026thinsp;0.25) and social class (B\u0026thinsp;=\u0026thinsp;0.14) demonstrated the strongest positive relationships with access across both direct and indirect paths.\u003c/p\u003e \u003cp\u003e \u003cb\u003eConclusion\u003c/b\u003e Governance regulations emerged as the strongest predictor of access to reproductive health services. Without upstream reforms in legal structures and residency protocols, superficial interventions will not yield sustainable improvements. NGOs play a vital role in bridging governmental gaps, whereas the negative impact of social capital highlights structural isolation as a barrier to health-seeking behaviors. Key recommendations include revising residency policies, rebuilding social trust, and strengthening civil society organizations to mitigate structural discrimination.\u003c/p\u003e","manuscriptTitle":"The relationship between Social Determinants of Health and Access to Reproductive Health Services among Afghan Migrant Women based on the World Health Organization Model in Iran: path analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-23 08:38:23","doi":"10.21203/rs.3.rs-8817187/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-03-30T10:37:15+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-27T11:56:52+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"146467969788816263400214253028024667946","date":"2026-03-20T16:11:12+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"246869695846687452938137683701109570669","date":"2026-03-18T19:24:16+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-03-18T14:46:38+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-16T12:48:42+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-02-23T04:05:52+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-02-23T02:39:47+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Public Health","date":"2026-02-18T18:58:23+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"53b913dc-2924-4384-ad1d-162ee9740fb0","owner":[],"postedDate":"March 23rd, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-03-23T08:38:23+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-23 08:38:23","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8817187","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8817187","identity":"rs-8817187","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}