Disparities in Facility Delivery Among Women Receiving Antenatal Care in Zambia: A DHS-Based Analysis

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Whiteson Mbele, MD, MSc, 3. Luyando Namwenda, BS, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7001027/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Facility-based delivery is a key intervention for reducing maternal and neonatal mortality. While antenatal care (ANC) attendance is high in Zambia, disparities in access to skilled delivery persist. This study examined the determinants of facility-based delivery among women who attended ANC, focusing on sociodemographic and health system factors. Method We conducted a cross-sectional analysis using data from the 2018 Zambia Demographic and Health Survey. The sample included women aged 15–49 who had a live birth in the five years preceding the survey and attended at least one ANC visit during their most recent pregnancy. The primary outcome was facility-based delivery. Multivariable logistic regression models, adjusted for survey design, were used to estimate associations between facility delivery and factors including wealth, education, residence, ANC utilization, perceived distance barriers, and media exposure. Results Among 4,630 ANC-attending women, 93.0% delivered in a health facility. In adjusted models, women in the richer wealth quintile had higher odds of facility delivery compared to the poorest (AOR: 2.19; 95% CI: 1.08–4.43; p =0.03). Surprisingly, women who attended four or more ANC visits were less likely to deliver in a health facility compared to those with fewer visits (AOR: 0.75; 95% CI: 0.59–0.96; p =0.02). Exposure to media showed a borderline positive association with facility-based delivery (AOR: 1.29; 95% CI: 1.00–1.66; p =0.05). No significant associations were observed for education level, rural residence, or parity. Conclusion Improving the quality and content of ANC is essential to strengthen the link between antenatal contact and facility-based delivery, particularly among economically disadvantaged women. Policies that incorporate birth preparedness counseling, offer transport or delivery incentives, and explore the role of media exposure as a tool for promoting safe delivery may help reduce access barriers and advance equity in skilled childbirth services in Zambia. Obstetrics & Gynecology Maternal & Fetal Medicine Facility-based delivery Antenatal care Health disparities Demographic and Health Survey Zambia Figures Figure 1 INTRODUCTION Facility-based childbirth attended by skilled health personnel is one of the most effective interventions to reduce maternal and neonatal mortality. Globally, over 800 women die each day from preventable causes related to pregnancy and childbirth, with the majority of deaths occurring in low- and middle-income countries (LMICs) (1). The World Health Organization (WHO) emphasizes that increasing coverage of skilled birth attendance, particularly in well-equipped and respectful health facilities, is essential for achieving Sustainable Development Goal (SDG) targets for maternal health (2). Despite global efforts, many women in sub-Saharan Africa still deliver at home or in non-clinical settings, often without access to timely obstetric care (3,4). There has been substantial progress made in Zambia in expanding access to maternal health services. As of the 2018 Zambia Demographic and Health Survey (ZDHS), 96% of women with a recent live birth attended at least one antenatal care (ANC) visit, and 84% delivered in a health facility (5). However, the maternal mortality ratio remains high at 85 deaths per 100,000 live births, and gaps persist between service contact and effective care (6,7). The intrapartum period is a particularly high-risk phase, accounting for more than one-third of maternal deaths and a significant share of stillbirths and newborn fatalities during labor, childbirth, and the immediate postpartum period (8–10). Delivery at a health facility has consistently been associated with reductions in adverse maternal and neonatal outcomes. A large body of evidence demonstrates that women with obstetric complications who deliver in facilities experience significantly lower perinatal mortality risks compared to those delivering at home (11,12). As such, both global and national guidelines, including Zambia’s reproductive health policy, recommend that all pregnant women deliver at a health facility under the supervision of trained personnel (13). Antenatal care is an important gateway to the broader continuum of maternal health services. During routine visits, women receive risk screening, birth preparedness counseling, and referrals for skilled care. Accordingly, ANC attendance is often assumed to be predictive of facility-based delivery (14,15). However, studies from Ethiopia, Nigeria, Nepal, and Zambia suggest that this relationship is not guaranteed. Many women who complete four or more ANC visits still deliver outside the formal health system due to cost barriers, lack of transport, negative experiences with care, or sociocultural factors (16–19). These findings indicate that contact coverage alone is insufficient to ensure continuity of care unless accompanied by quality, trust, and accessibility. In Zambia, socioeconomic and geographic disparities remain major determinants of maternal health service use. Women from wealthier households and urban areas are significantly more likely to deliver in health facilities than their poorer, rural counterparts (20). While programs such as maternity waiting homes and Safe Motherhood Action Groups (SMAGs) have been introduced to close these gaps, evidence on their scalability and effectiveness remains mixed (21,22). Qualitative studies have highlighted persistent fears of disrespectful care, perceived or actual costs, and limited decision-making autonomy as barriers to facility-based delivery, even among ANC users (16,22). Despite a growing body of literature on predictors of facility-based delivery, few studies in Zambia focus specifically on women who accessed ANC services but delivered outside the formal health system. These women represent a distinct population: they have successfully entered the health system but remain vulnerable to drop-off before delivery. Identifying the factors that influence delivery location in this group is critical to strengthening care continuity and achieving equitable maternal health outcomes. This study aimed to examine the determinants of facility-based delivery among Zambian women who received antenatal care, using data from the 2018 DHS. Specifically, we investigated associations between delivery location and sociodemographic, economic, and health system factors, including ANC visit frequency, perceived distance barriers, and media exposure. By focusing on ANC users, this study seeks to identify structural and informational barriers that hinder transitions to safe delivery and to inform targeted, equity-focused strategies within Zambia’s maternal health system. METHODS Study Design We conducted a cross-sectional analysis using data from the 2018 Zambia Demographic and Health Survey (ZDHS), a nationally representative household survey implemented by the Zambia Statistics Agency in collaboration with the Ministry of Health and the DHS Program. The ZDHS employed a stratified two-stage sampling design and collected health, demographic, and reproductive information from women aged 15–49 years. Study Population Our analytic sample was restricted to women aged 15–49 who had a live birth in the five years preceding the survey and reported attending at least one antenatal care (ANC) visit during their most recent pregnancy. Women with missing data on place of delivery or ANC visit counts were excluded. Outcome Variable Place of delivery was the primary outcome, derived from DHS variable m15_1. Responses were recoded into a binary variable: 1 indicating facility-based delivery, including government hospitals and health centers, private hospitals/clinics, and mission health facilities (codes 11, 12, 21, 22, 23, and 26); and 0 indicating delivery at home or in other non-clinical settings, including births with relatives, traditional attendants, or elsewhere. Independent Variables Several sociodemographic and health system factors were examined as predictors of facility delivery. Education level (v106) was recoded as none, primary, and secondary/higher. Household wealth was assessed using the DHS wealth index (v190) and categorized into five groups: poorest, poorer, middle, richer, and richest. Place of residence was classified as either urban or rural based on the DHS coding (v025. Parity (v201) was classified as primiparous (one prior birth) or multiparous (two or more prior births). Antenatal care utilization was assessed through the number of ANC visits (m14_1), which was dichotomized as fewer than four visits versus four or more visits, in line with World Health Organization recommendations. Timing of first ANC visit (m13_1) was retained as a continuous variable. The receipt of iron supplements (m45_1) during pregnancy was included as a proxy for ANC quality in a sensitivity analysis. Perceived distance to the health facility as a barrier (v467d) was recoded into a binary variable. Media exposure was defined as access to any of television, radio, or newspapers (v158, v159, or v160) and categorized as yes if the respondent reported exposure to at least one of these media sources. Statistical Analysis All analyses accounted for the complex sampling design using the survey package in R. Sampling weights (v005), primary sampling units (v021), and strata (v022) were incorporated using the svydesign() function. Descriptive statistics with weighted proportions were presented in Table 1. Multivariable logistic regression models were fitted using svyglm() to estimate adjusted odds ratios (AORs) and 95% confidence intervals (CIs) for factors associated with facility delivery. The primary model included sociodemographic and ANC-related predictors and is presented in Table 2. A sensitivity analysis incorporating iron tablet receipt was conducted to assess the potential impact of ANC quality (Table 3). An interaction model was fitted to test whether the association between ANC attendance and facility delivery varied by residence (Table 4). We also conducted a stratified analysis among primiparous women only, presented in Table 5. To visualize effect estimates from the main model, we generated a forest plot displaying adjusted odds ratios and their corresponding 95% confidence intervals. All analyses were conducted using R version 4.3.1. Ethical Considerations Ethical approval for the ZDHS was obtained by the Zambia Ministry of Health and ICF International through the ICF Institutional Review Board and the local ethics committee. All respondents provided informed consent before participation. No further ethical clearance was necessary for this secondary analysis of publicly available data. RESULTS A total of 4,630 women aged 15–49 years who had a recent live birth and attended at least one antenatal care (ANC) visit were included in the analysis. Among these, the vast majority (93.0%) delivered in a health facility, while 7.0% delivered at home or in other non-clinical settings. Table 1. Background Characteristics of Women with a Recent Birth (Zambia DHS 2018) Variable Category % (Proportion) Facility Delivery Yes 93.0 No 7.0 Education None 9.1 Primary 49.1 Secondary/Higher 41.8 Residence Urban 38.5 Rural 61.5 Wealth Quintile Poorest 22.6 Poorer 20.8 Middle 19.0 Richer 20.1 Richest 17.4 ANC Visits < 4 visits 34.9 ≥ 4 visits 65.1 Parity Primiparous 24.8 Multiparous 75.2 Distance Problem Not a big problem 68.4 A big problem 31.6 Media Exposure No 49.1 Yes 50.9 *Proportions are weighted using DHS sampling weights to account for the complex survey design In terms of education, 9.1% of women had no formal education, 49.1% had completed primary education, and 41.8% had attained secondary or higher education. The majority of respondents (61.5%) resided in rural areas, while 38.5% lived in urban settings. With respect to household wealth, 22.6% of women were in the poorest quintile, followed by 20.8% in the poorer, 19.0% in the middle, 20.1% in the richer, and 17.4% in the richest quintile. Regarding ANC utilization, 65.1% reported attending four or more visits during their most recent pregnancy, whereas 34.9% attended fewer than four. Approximately one in four women (24.8%) were primiparous, while the remaining 75.2% had previously given birth. Nearly one-third (31.6%) reported that distance to a health facility was a major problem in seeking care, while 68.4% did not perceive distance as a significant barrier. Media exposure, defined as access to at least one of television, radio, or newspapers, was evenly distributed, with 50.9% of women reporting some form of exposure and 49.1% reporting none. Table 2. Adjusted Odds Ratios (AOR) and 95% Confidence Intervals for Factors Associated with Facility Delivery Variable AOR 95% CI P-value Education: Primary vs None 1.03 0.68 – 1.56 0.88 Education: Secondary/Higher vs None 0.85 0.51 – 1.42 0.53 Residence: Rural vs Urban 0.87 0.45 – 1.68 0.68 Wealth: Poorer vs Poorest 0.97 0.72 – 1.31 0.83 Wealth: Middle vs Poorest 1.25 0.88 – 1.79 0.21 Wealth: Richer vs Poorest 2.19 1.08 – 4.43 0.03* Wealth: Richest vs Poorest 1.23 0.67 – 2.28 0.50 ≥4 ANC Visits vs <4 Visits 0.75 0.59 – 0.96 0.02* Multiparous vs Primiparous 1.07 0.79 – 1.45 0.68 Distance Problem (Yes vs No) 0.78 0.58 – 1.05 0.10 Media Exposure (Yes vs No) 1.29 1.00 – 1.66 0.05 *Significant at p < 0.05 Table 2 presents the results from the multivariable logistic regression model assessing factors associated with facility-based delivery among women who attended antenatal care (ANC). After adjusting for key sociodemographic and health system variables, several associations were observed. Women in the richer wealth quintile had significantly higher odds of delivering in a health facility compared to those in the poorest quintile (Adjusted Odds Ratio [AOR]: 2.19; 95% Confidence Interval [CI]: 1.08–4.43; p = 0.03). However, no significant associations were observed for the poorer, middle, or richest quintiles relative to the poorest. Contrary to expectations, women who attended four or more ANC visits had lower odds of facility-based delivery compared to those with fewer than four visits (AOR: 0.75; 95% CI: 0.59–0.96; p = 0.02). Media exposure showed a borderline significant association with higher odds of facility delivery (AOR: 1.29; 95% CI: 1.00–1.66; p = 0.05), whereas perceived distance to the health facility was negatively associated with facility delivery, though the relationship was not statistically significant (AOR: 0.78; 95% CI: 0.58–1.05; p = 0.10). There were no significant associations between facility delivery and education level, place of residence, or parity. Specifically, women with primary or secondary/higher education had similar odds of facility delivery as those with no education, and rural residence was not significantly associated with lower odds of facility use. Table 3. Sensitivity analysis: Factors associated with facility delivery Variable AOR 95% CI P-value Education: Primary vs None 1.02 0.67 – 1.56 0.92 Education: Secondary/Higher vs None 0.83 0.51 – 1.36 0.45 Residence: Rural vs Urban 0.87 0.45 – 1.68 0.67 Wealth: Poorer vs Poorest 0.97 0.72 – 1.31 0.83 Wealth: Middle vs Poorest 1.26 0.88 – 1.79 0.21 Wealth: Richer vs Poorest 2.19 1.09 – 4.40 0.03* Wealth: Richest vs Poorest 1.23 0.67 – 2.28 0.50 ≥4 ANC Visits vs <4 Visits 0.75 0.59 – 0.96 0.02* Took Iron Tablets During ANC 1.10 0.54 – 2.25 0.79 Distance Not a Big Problem vs Big 0.78 0.58 – 1.05 0.10 Media Exposure: Yes vs No 1.28 0.99 – 1.66 0.06 A sensitivity analysis was conducted to assess the robustness of the primary model by including an additional proxy indicator of antenatal care quality: whether the woman reported receiving iron supplementation during pregnancy. The general trends in associations were similar to those observed in the primary model (Table 3). Women in the richer wealth quintile continued to have significantly higher odds of facility-based delivery compared to those in the poorest quintile (AOR: 2.19; 95% CI: 1.09–4.40; p = 0.03). As in the primary analysis, women who attended four or more ANC visits had lower odds of delivering in a facility than those with fewer visits (AOR: 0.75; 95% CI: 0.59–0.96; p = 0.02). Including iron supplementation in the model did not meaningfully change the observed association. Iron tablet use during ANC was not significantly linked to facility-based delivery (AOR: 1.10; 95% CI: 0.54–2.25; p = 0.79), indicating it may be a limited proxy for ANC quality in this setting. Media exposure remained marginally associated with increased odds of facility delivery (AOR: 1.28; 95% CI: 0.99–1.66; p = 0.06), while distance to the facility remained a borderline non-significant factor (AOR: 0.78; 95% CI: 0.58–1.05; p = 0.10). Table 4. Adjusted Odds Ratios (AOR) and 95% Confidence Intervals for Facility Delivery with Interaction Between ANC Visits and Residence Variable AOR 95% CI P-value ANC ≥4 visits 0.87 0.57 – 1.33 0.53 Residence: Rural 1.02 0.45 – 2.28 0.97 ANC ≥4 * Rural (interaction term) 0.79 0.47 – 1.33 0.38 Primary education 1.03 0.68 – 1.56 0.90 Secondary/Higher education 0.83 0.51 – 1.36 0.46 Wealth: Poorer vs Poorest 0.97 0.72 – 1.31 0.84 Wealth: Middle vs Poorest 1.25 0.88 – 1.79 0.21 Wealth: Richer vs Poorest 2.19 1.09 – 4.40 0.03* Wealth: Richest vs Poorest 1.23 0.67 – 2.25 0.51 Distance not a big problem 0.78 0.58 – 1.04 0.09 Media exposure 1.28 0.99 – 1.66 0.06 To explore whether the association between ANC visit frequency and facility delivery varied by place of residence, an interaction term between ANC attendance (≥4 visits) and rural residence was included in the model (Table 4). The interaction term between having four or more ANC visits and rural residence was not statistically significant (AOR: 0.79; 95% CI: 0.47–1.33; p = 0.38), suggesting that the inverse association between high ANC attendance and facility delivery did not differ meaningfully between rural and urban settings. Similarly, the main effects for ANC ≥4 visits (AOR: 0.87; 95% CI: 0.57–1.33; p = 0.53) and rural residence (AOR: 1.02; 95% CI: 0.45–2.28; p = 0.97) were not significant in this model. As in previous models, women in the richer wealth quintile had significantly higher odds of facility delivery compared to those in the poorest quintile (AOR: 2.19; 95% CI: 1.09–4.40; p = 0.03). Other covariates, including education level, distance to facility, and media exposure, did not reach statistical significance, although media exposure remained marginally associated with increased odds of facility use (AOR: 1.28; 95% CI: 0.99–1.66; p = 0.06). Table 5. Stratified Logistic Regression for Facility Delivery Among Primiparous Women Variable AOR 95% CI P-value (Intercept) 15.1 [3.46, 65.95] <0.001 Primary education 1.03 [0.36, 2.93] 0.95 Secondary/Higher education 1.12 [0.39, 3.20] 0.83 Rural residence 0.60 [0.23, 1.56] 0.30 Poorer wealth quintile 1.30 [0.73, 2.33] 0.37 Middle wealth quintile 1.48 [0.76, 2.90] 0.25 Richer wealth quintile 2.61 [0.89, 7.68] 0.08 Richest wealth quintile 1.61 [0.53, 4.87] 0.40 ≥4 ANC visits 0.71 [0.47, 1.06] 0.09 Distance is a problem (yes) 0.72 [0.42, 1.23] 0.23 Access to media (yes) 1.11 [0.73, 1.70] 0.62 To further explore whether the determinants of facility-based delivery differed by parity, a stratified logistic regression analysis was conducted among primiparous women (Table 5). None of the included predictors reached statistical significance at the p < 0.05 threshold, though some trends were observed. Women in the richer wealth quintile had higher, but not statistically significant, odds of facility delivery compared to the poorest quintile (AOR: 2.61; 95% CI: 0.89–7.68; p = 0.08). A comparable pattern was noted for women with four or more ANC visits, who had lower odds of delivering in a facility (AOR: 0.71; 95% CI: 0.47–1.06), although the association was not statistically significant (p = 0.09). Other variables, including education level, rural residence, distance to facility, and media exposure, were not significantly associated with place of delivery in this subgroup. DISCUSSION This study examined determinants of facility-based delivery among Zambian women who received at least one antenatal care (ANC) visit during their most recent pregnancy. While overall facility delivery coverage among ANC users was high (93.0%), we observed persistent disparities by wealth status and media exposure. Women in the richer wealth quintile had more than twice the odds of delivering in a health facility compared to the poorest women, highlighting ongoing structural inequities in access to skilled care despite similar ANC engagement. This pattern is consistent with prior analyses showing that wealth remains a key driver of institutional delivery in sub-Saharan Africa, even among women who access other maternal health services (23–25). An unexpected finding was that women with four or more ANC visits had significantly lower odds of delivering in a health facility compared to those with fewer visits. This contradicts most prior studies, which typically find a positive association between frequent ANC and skilled birth attendance (26–28). One possible explanation is selection bias, that is, women who anticipate home births due to cultural norms, cost concerns, or mistrust of facility-based care may still attend ANC for fetal monitoring, tetanus shots, or iron supplementation, without intending to deliver at a facility. Previous qualitative work in Zambia supports this interpretation, reporting that some women engage with ANC services while maintaining traditional delivery preferences or fearing mistreatment at health facilities (29,30). Another explanation relates to perceived quality of care. The WHO framework emphasizes that effective ANC must include not only contact frequency but also respectful communication, individualized counseling, and birth preparedness planning (31). If these components are lacking, higher ANC attendance may not translate into increased facility utilization. Moreover, ANC visits in rural or underserved areas may be delivered via outreach clinics or health posts with limited capacity to support delivery referrals, further weakening the link between ANC exposure and facility-based delivery (32). These findings underscore that coverage is not synonymous with quality, and that ANC interventions must be coupled with targeted efforts to build trust, improve referral systems, and address economic barriers. Our stratified analysis among primiparous women revealed broadly similar associations between wealth, ANC attendance, and delivery location, though the effects were less precise. This consistency suggests that wealth-related disparities in facility delivery persist across parity groups and merit broader policy attention. While we did not observe statistically significant associations with maternal education or rural residence in adjusted models, this may reflect reduced variability in these exposures among ANC-attending women or confounding by wealth and access factors. Media exposure was marginally associated with higher odds of facility delivery, echoing prior research that links health messaging through radio and television to improved maternal health behaviors (33,34). Expanding access to tailored mass communication campaigns, particularly in underserved areas, may help reinforce positive health-seeking norms and complement facility-based interventions. From a policy standpoint, our findings point to the need for equity-enhancing strategies within Zambia’s maternal health system. Targeted programs such as maternity waiting homes, transportation vouchers, or delivery incentives for low-income women could help close the gap between ANC attendance and skilled birth attendance. Zambia’s Safe Motherhood Action Groups (SMAGs) and community-based birth preparedness initiatives have shown promise in increasing institutional delivery rates, but broader scale-up and integration into ANC platforms may be needed (35,36). This study has several strengths, including use of a nationally representative dataset, focus on a key subpopulation of ANC users, and inclusion of interaction and stratified models. However, some limitations must be noted. The cross-sectional design limits causal inference. Additionally, self-reported data on ANC and delivery location may be subject to recall and social desirability bias. While Zambia has achieved high ANC and facility delivery coverage overall, gaps in equitable access remain. Merely attending ANC is not sufficient to ensure skilled delivery, particularly for socioeconomically disadvantaged women. Efforts to improve the quality, continuity, and trustworthiness of maternal health services, especially within ANC, are essential for realizing the full benefits of facility-based delivery and advancing universal health coverage goals. CONCLUSION Despite high ANC coverage in Zambia, disparities in facility-based delivery persist among ANC users, particularly by wealth status. The inverse association between frequent ANC visits and facility delivery highlights missed opportunities to translate contact into effective care. To close this gap, maternal health programs should strengthen birth preparedness counseling during ANC, expand transport and delivery incentives for low-income women, and improve the perceived quality and respectfulness of facility-based care. Advancing equity in maternal health will require not only increasing service contact but ensuring that services are trusted, accessible, and responsive to women’s needs. Declarations Ethics approval and consent to participate. All participants provided informed consent at the time of original data collection. The original survey received ethical approval from the Tropical Diseases Research Centre in Zambia and the Institutional Review Board of ICF International. As this was a secondary analysis of anonymized data, no additional consent was required. Ethics approval and consent to participate This study involved a secondary analysis of de-identified, publicly accessible data from the 2018 Zambia Demographic and Health Survey (ZDHS). The original survey protocol received ethical clearance from the Tropical Diseases Research Centre (TDRC) in Zambia and the ICF Institutional Review Board. Informed written consent was obtained from all participants during data collection. As the dataset is anonymized and publicly available, additional ethical approval was not required for this analysis. Consent for publication Not applicable. Availability of data and materials The datasets analyzed during the current study are available from the DHS Program repository: https://dhsprogram.com/data/available-datasets.cfm Competing interests The author declares that there are no competing interests. Funding No specific funding was received for this study. Authors' contributions PK, WM, and NN conceptualized the study, conducted the data analysis, and wrote the original draft. LN, CM, and HM contributed to review and editing of the manuscript. All authors read and approved the final manuscript. Acknowledgements The authors acknowledge the Demographic and Health Surveys (DHS) Program for granting access to the 2018 Zambia DHS data. References World Health Organization. Trends in Maternal Mortality: 2000 to 2020. Geneva: WHO; 2023. World Health Organization. Strategies toward ending preventable maternal mortality (EPMM). Geneva: WHO; 2015. Say L, Chou D, Gemmill A, Tunçalp Ö, Moller AB, Daniels J, et al. 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Tropical Medicine & International Health. 2015 Dec 28;20(12):1657–73. Moyer CA, Mustafa A. Drivers and deterrents of facility delivery in sub-Saharan Africa: A systematic review. Reprod Health. 2013;10(1). Berelie Y, Yeshiwas D, Yismaw L, Alene M. Determinants of institutional delivery service utilization in Ethiopia: A population based cross sectional study. BMC Public Health. 2020 Jul 8;20(1). Wang W, Alva S, Wang S, Fort A. DHS COMPARATIVE REPORTS 26 LEVELS AND TRENDS IN THE USE OF MATERNAL HEALTH SERVICES IN DEVELOPING COUNTRIES [Internet]. 2011. Available from: www.measuredhs.com. Accessed 25 June, 2025. Sialubanje C, Massar K, Hamer DH, Ruiter RAC. Reasons for home delivery and use of traditional birth attendants in rural Zambia: A qualitative study. BMC Pregnancy Childbirth. 2015 Sep 11;15(1). Bohren MA, Vogel JP, Hunter EC, Lutsiv O, Makh SK, Souza JP, et al. The Mistreatment of Women during Childbirth in Health Facilities Globally: A Mixed-Methods Systematic Review. PLoS Med. 2015 Jun 30;12(6):e1001847. Tunçalp Ӧ., Were W, MacLennan C, Oladapo O, Gülmezoglu A, Bahl R, et al. Quality of care for pregnant women and newborns—the WHO vision. BJOG. 2015 Jul;122(8):1045–9. Kruk ME, Kujawski S, Moyer CA, Adanu RM, Afsana K, Cohen J, et al. Next generation maternal health: external shocks and health-system innovations. The Lancet. 2016 Nov;388(10057):2296–306. Fatema K, Lariscy JT. Mass media exposure and maternal healthcare utilization in South Asia. SSM Popul Health. 2020 Aug;11:100614. Waiswa P, Akuze J, Peterson S, Kerber K, Tetui M, Forsberg BC, et al. Differences in essential newborn care at birth between private and public health facilities in eastern Uganda. Glob Health Action. 2015 Dec 31;8(1):24251. Manandhar DS, Osrin D, Shrestha BP, Mesko N, Morrison J, Tumbahangphe KM, et al. Effect of a participatory intervention with women’s groups on birth outcomes in Nepal: cluster-randomised controlled trial. The Lancet. 2004 Sep;364(9438):970–9. Sialubanje C, Massar K, Horstkotte L, Hamer DH, Ruiter RAC. Increasing utilisation of skilled facility-based maternal healthcare services in rural Zambia: the role of safe motherhood action groups. Reprod Health. 2017 Dec 10;14(1):81. Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7001027","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":477884086,"identity":"12679db9-0adb-4373-a17b-8c384b5b1d13","order_by":0,"name":"Powell Kafwanka, MD, MSc","email":"","orcid":"https://orcid.org/0009-0007-9713-9437","institution":"University of Zambia, Department of Epidemiology, School of Public Health.","correspondingAuthor":false,"prefix":"","firstName":"","middleName":"MD Powell","lastName":"Kafwanka","suffix":"MD"},{"id":477884087,"identity":"1dd163a0-5ecc-4464-a46a-7453166c50d7","order_by":1,"name":"2.\tWhiteson Mbele, MD, MSc","email":"","orcid":"https://orcid.org/0009-0006-0470-0081","institution":"Ministry of Health Zambia","correspondingAuthor":false,"prefix":"","firstName":"","middleName":"MD 2.\tWhiteson","lastName":"Mbele","suffix":"MD"},{"id":477884088,"identity":"ff624b42-96ce-4cca-a116-39af7c10dbfb","order_by":2,"name":"3.\tLuyando Namwenda, BS","email":"","orcid":"","institution":"University of Lusaka, School of Public Health","correspondingAuthor":false,"prefix":"","firstName":"BS","middleName":"3.\tLuyando","lastName":"Namwenda","suffix":""},{"id":477884089,"identity":"2b9728f9-16e4-4da5-873a-873bb0667f27","order_by":3,"name":"4.\tHannah Muturi, BSc, MSc","email":"","orcid":"","institution":"Kenyatta University","correspondingAuthor":false,"prefix":"","firstName":"MSc","middleName":"BSc 4.\tHannah","lastName":"Muturi","suffix":""},{"id":477884090,"identity":"07c7454e-b6f4-4d3c-95fc-c97c9c19e7aa","order_by":4,"name":"5.\tCaren Muyuni, BS, 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District Health Office","correspondingAuthor":true,"prefix":"","firstName":"","middleName":"MD 6.\tNewton","lastName":"Nyirenda","suffix":"MD"}],"badges":[],"createdAt":"2025-06-29 06:40:01","currentVersionCode":1,"declarations":{"humanSubjects":true,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":true,"humanSubjectConsent":true,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-7001027/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7001027/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":86135514,"identity":"6075c759-1670-4b3f-bdcd-8bca70baacf8","added_by":"auto","created_at":"2025-07-07 07:42:47","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":151983,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAdjusted Odds Ratios for Factors Associated with Facility-Based Delivery Among ANC-Attending Women, Zambia DHS 2018\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7001027/v1/ee6f3417bf847a7e64bd2bd3.png"},{"id":86136332,"identity":"f325bffe-18b5-4374-9ff4-d429438d7fec","added_by":"auto","created_at":"2025-07-07 07:50:48","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1086634,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7001027/v1/1f6a01aa-785a-4afb-a4e3-6c2e87cea9d0.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eDisparities in Facility Delivery Among Women Receiving Antenatal Care in Zambia: A DHS-Based Analysis\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eFacility-based childbirth attended by skilled health personnel is one of the most effective interventions to reduce maternal and neonatal mortality. Globally, over 800 women die each day from preventable causes related to pregnancy and childbirth, with the majority of deaths occurring in low- and middle-income countries (LMICs) (1). The World Health Organization (WHO) emphasizes that increasing coverage of skilled birth attendance, particularly in well-equipped and respectful health facilities, is essential for achieving Sustainable Development Goal (SDG) targets for maternal health (2). Despite global efforts, many women in sub-Saharan Africa still deliver at home or in non-clinical settings, often without access to timely obstetric care (3,4).\u003c/p\u003e\n\u003cp\u003eThere has been substantial progress made in Zambia in expanding access to maternal health services. As of the 2018 Zambia Demographic and Health Survey (ZDHS), 96% of women with a recent live birth attended at least one antenatal care (ANC) visit, and 84% delivered in a health facility (5). However, the maternal mortality ratio remains high at 85 deaths per 100,000 live births, and gaps persist between service contact and effective care (6,7). The intrapartum period is a particularly high-risk phase, accounting for more than one-third of maternal deaths and a significant share of stillbirths and newborn fatalities during labor, childbirth, and the immediate postpartum period (8\u0026ndash;10).\u003c/p\u003e\n\u003cp\u003eDelivery at a health facility has consistently been associated with reductions in adverse maternal and neonatal outcomes. A large body of evidence demonstrates that women with obstetric complications who deliver in facilities experience significantly lower perinatal mortality risks compared to those delivering at home (11,12). As such, both global and national guidelines, including Zambia\u0026rsquo;s reproductive health policy, recommend that all pregnant women deliver at a health facility under the supervision of trained personnel (13).\u003c/p\u003e\n\u003cp\u003eAntenatal care is an important gateway to the broader continuum of maternal health services. During routine visits, women receive risk screening, birth preparedness counseling, and referrals for skilled care. Accordingly, ANC attendance is often assumed to be predictive of facility-based delivery (14,15). However, studies from Ethiopia, Nigeria, Nepal, and Zambia suggest that this relationship is not guaranteed. Many women who complete four or more ANC visits still deliver outside the formal health system due to cost barriers, lack of transport, negative experiences with care, or sociocultural factors (16\u0026ndash;19). These findings indicate that contact coverage alone is insufficient to ensure continuity of care unless accompanied by quality, trust, and accessibility.\u003c/p\u003e\n\u003cp\u003eIn Zambia, socioeconomic and geographic disparities remain major determinants of maternal health service use. Women from wealthier households and urban areas are significantly more likely to deliver in health facilities than their poorer, rural counterparts (20). While programs such as maternity waiting homes and Safe Motherhood Action Groups (SMAGs) have been introduced to close these gaps, evidence on their scalability and effectiveness remains mixed (21,22). Qualitative studies have highlighted persistent fears of disrespectful care, perceived or actual costs, and limited decision-making autonomy as barriers to facility-based delivery, even among ANC users (16,22).\u003c/p\u003e\n\u003cp\u003eDespite a growing body of literature on predictors of facility-based delivery, few studies in Zambia focus specifically on women who accessed ANC services but delivered outside the formal health system. These women represent a distinct population: they have successfully entered the health system but remain vulnerable to drop-off before delivery. Identifying the factors that influence delivery location in this group is critical to strengthening care continuity and achieving equitable maternal health outcomes.\u003c/p\u003e\n\u003cp\u003eThis study aimed to examine the determinants of facility-based delivery among Zambian women who received antenatal care, using data from the 2018 DHS. Specifically, we investigated associations between delivery location and sociodemographic, economic, and health system factors, including ANC visit frequency, perceived distance barriers, and media exposure. By focusing on ANC users, this study seeks to identify structural and informational barriers that hinder transitions to safe delivery and to inform targeted, equity-focused strategies within Zambia\u0026rsquo;s maternal health system.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cp\u003e\u003cstrong\u003eStudy Design\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe conducted a cross-sectional analysis using data from the 2018 Zambia Demographic and Health Survey (ZDHS), a nationally representative household survey implemented by the Zambia Statistics Agency in collaboration with the Ministry of Health and the DHS Program. The ZDHS employed a stratified two-stage sampling design and collected health, demographic, and reproductive information from women aged 15\u0026ndash;49 years.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStudy Population\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOur analytic sample was restricted to women aged 15\u0026ndash;49 who had a live birth in the five years preceding the survey and reported attending at least one antenatal care (ANC) visit during their most recent pregnancy. Women with missing data on place of delivery or ANC visit counts were excluded.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOutcome Variable\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePlace of delivery was the primary outcome, derived from DHS variable m15_1. Responses were recoded into a binary variable: 1 indicating facility-based delivery, including government hospitals and health centers, private hospitals/clinics, and mission health facilities (codes 11, 12, 21, 22, 23, and 26); and 0 indicating delivery at home or in other non-clinical settings, including births with relatives, traditional attendants, or elsewhere.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIndependent Variables\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSeveral sociodemographic and health system factors were examined as predictors of facility delivery. Education level (v106) was recoded as none, primary, and secondary/higher. Household wealth was assessed using the DHS wealth index (v190) and categorized into five groups: poorest, poorer, middle, richer, and richest. Place of residence was classified as either urban or rural based on the DHS coding (v025. Parity (v201) was classified as primiparous (one prior birth) or multiparous (two or more prior births).\u003c/p\u003e\n\u003cp\u003eAntenatal care utilization was assessed through the number of ANC visits (m14_1), which was dichotomized as fewer than four visits versus four or more visits, in line with World Health Organization recommendations. Timing of first ANC visit (m13_1) was retained as a continuous variable. The receipt of iron supplements (m45_1) during pregnancy was included as a proxy for ANC quality in a sensitivity analysis. Perceived distance to the health facility as a barrier (v467d) was recoded into a binary variable. Media exposure was defined as access to any of television, radio, or newspapers (v158, v159, or v160) and categorized as yes if the respondent reported exposure to at least one of these media sources.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll analyses accounted for the complex sampling design using the survey package in R. Sampling weights (v005), primary sampling units (v021), and strata (v022) were incorporated using the svydesign() function.\u003c/p\u003e\n\u003cp\u003eDescriptive statistics with weighted proportions were presented in Table 1. Multivariable logistic regression models were fitted using svyglm() to estimate adjusted odds ratios (AORs) and 95% confidence intervals (CIs) for factors associated with facility delivery. The primary model included sociodemographic and ANC-related predictors and is presented in Table 2. A sensitivity analysis incorporating iron tablet receipt was conducted to assess the potential impact of ANC quality (Table 3). An interaction model was fitted to test whether the association between ANC attendance and facility delivery varied by residence (Table 4). We also conducted a stratified analysis among primiparous women only, presented in Table 5.\u003c/p\u003e\n\u003cp\u003eTo visualize effect estimates from the main model, we generated a forest plot displaying adjusted odds ratios and their corresponding 95% confidence intervals. All analyses were conducted using R version 4.3.1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical Considerations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical approval for the ZDHS was obtained by the Zambia Ministry of Health and ICF International through the ICF Institutional Review Board and the local ethics committee. All respondents provided informed consent before participation. No further ethical clearance was necessary for this secondary analysis of publicly available data.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003eA total of 4,630 women aged 15\u0026ndash;49 years who had a recent live birth and attended at least one antenatal care (ANC) visit were included in the analysis. Among these, the vast majority (93.0%) delivered in a health facility, while 7.0% delivered at home or in other non-clinical settings.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1. Background Characteristics of Women with a Recent Birth (Zambia DHS 2018)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" width=\"608\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eCategory\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e% (Proportion)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eFacility Delivery\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e93.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e7.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eEducation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e9.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ePrimary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e49.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eSecondary/Higher\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e41.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eResidence\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eUrban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e38.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eRural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e61.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eWealth Quintile\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ePoorest\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e22.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ePoorer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e20.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMiddle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e19.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eRicher\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e20.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eRichest\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e17.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eANC Visits\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt; 4 visits\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e34.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026ge; 4 visits\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e65.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eParity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003ePrimiparous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e24.8\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eMultiparous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e75.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eDistance Problem\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eNot a big problem\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e68.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eA big problem\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e31.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eMedia Exposure\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e49.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e50.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e*Proportions are weighted using DHS sampling weights to account for the complex survey design\u003c/p\u003e\n\u003cp\u003eIn terms of education, 9.1% of women had no formal education, 49.1% had completed primary education, and 41.8% had attained secondary or higher education. The majority of respondents (61.5%) resided in rural areas, while 38.5% lived in urban settings.\u003c/p\u003e\n\u003cp\u003eWith respect to household wealth, 22.6% of women were in the poorest quintile, followed by 20.8% in the poorer, 19.0% in the middle, 20.1% in the richer, and 17.4% in the richest quintile. Regarding ANC utilization, 65.1% reported attending four or more visits during their most recent pregnancy, whereas 34.9% attended fewer than four.\u003c/p\u003e\n\u003cp\u003eApproximately one in four women (24.8%) were primiparous, while the remaining 75.2% had previously given birth. Nearly one-third (31.6%) reported that distance to a health facility was a major problem in seeking care, while 68.4% did not perceive distance as a significant barrier. Media exposure, defined as access to at least one of television, radio, or newspapers, was evenly distributed, with 50.9% of women reporting some form of exposure and 49.1% reporting none.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2. Adjusted Odds Ratios (AOR) and 95% Confidence Intervals for Factors Associated with Facility Delivery\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" width=\"557\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eAOR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eEducation: Primary vs None\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.68 \u0026ndash; 1.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eEducation: Secondary/Higher vs None\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.85\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.51 \u0026ndash; 1.42\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.53\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eResidence: Rural vs Urban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.45 \u0026ndash; 1.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.68\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eWealth: Poorer vs Poorest\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.72 \u0026ndash; 1.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.83\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eWealth: Middle vs Poorest\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.88 \u0026ndash; 1.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eWealth: Richer vs Poorest\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.08 \u0026ndash; 4.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.03*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eWealth: Richest vs Poorest\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.67 \u0026ndash; 2.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026ge;4 ANC Visits vs \u0026lt;4 Visits\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.59 \u0026ndash; 0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.02*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMultiparous vs Primiparous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.79 \u0026ndash; 1.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.68\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eDistance Problem (Yes vs No)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.58 \u0026ndash; 1.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMedia Exposure (Yes vs No)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.00 \u0026ndash; 1.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e*Significant at p \u0026lt; 0.05\u003c/p\u003e\n\u003cp\u003eTable 2 presents the results from the multivariable logistic regression model assessing factors associated with facility-based delivery among women who attended antenatal care (ANC). After adjusting for key sociodemographic and health system variables, several associations were observed.\u003c/p\u003e\n\u003cp\u003eWomen in the richer wealth quintile had significantly higher odds of delivering in a health facility compared to those in the poorest quintile (Adjusted Odds Ratio [AOR]: 2.19; 95% Confidence Interval [CI]: 1.08\u0026ndash;4.43; \u003cem\u003ep\u003c/em\u003e = 0.03). However, no significant associations were observed for the poorer, middle, or richest quintiles relative to the poorest.\u003c/p\u003e\n\u003cp\u003eContrary to expectations, women who attended four or more ANC visits had lower odds of facility-based delivery compared to those with fewer than four visits (AOR: 0.75; 95% CI: 0.59\u0026ndash;0.96; \u003cem\u003ep\u003c/em\u003e = 0.02).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMedia exposure showed a borderline significant association with higher odds of facility delivery (AOR: 1.29; 95% CI: 1.00\u0026ndash;1.66; p = 0.05), whereas perceived distance to the health facility was negatively associated with facility delivery, though the relationship was not statistically significant (AOR: 0.78; 95% CI: 0.58\u0026ndash;1.05; p = 0.10).\u003c/p\u003e\n\u003cp\u003eThere were no significant associations between facility delivery and education level, place of residence, or parity. Specifically, women with primary or secondary/higher education had similar odds of facility delivery as those with no education, and rural residence was not significantly associated with lower odds of facility use.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3. Sensitivity analysis: Factors associated with facility delivery\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" width=\"533\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eAOR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eEducation: Primary vs None\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.67 \u0026ndash; 1.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eEducation: Secondary/Higher vs None\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.51 \u0026ndash; 1.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.45\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eResidence: Rural vs Urban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.45 \u0026ndash; 1.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eWealth: Poorer vs Poorest\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.72 \u0026ndash; 1.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.83\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eWealth: Middle vs Poorest\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.26\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.88 \u0026ndash; 1.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eWealth: Richer vs Poorest\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.09 \u0026ndash; 4.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.03*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eWealth: Richest vs Poorest\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.67 \u0026ndash; 2.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026ge;4 ANC Visits vs \u0026lt;4 Visits\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.59 \u0026ndash; 0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.02*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eTook Iron Tablets During ANC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.54 \u0026ndash; 2.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.79\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eDistance Not a Big Problem vs Big\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.58 \u0026ndash; 1.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.10\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMedia Exposure: Yes vs No\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.99 \u0026ndash; 1.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eA sensitivity analysis was conducted to assess the robustness of the primary model by including an additional proxy indicator of antenatal care quality: whether the woman reported receiving iron supplementation during pregnancy. The general trends in associations were similar to those observed in the primary model (Table 3).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWomen in the richer wealth quintile continued to have significantly higher odds of facility-based delivery compared to those in the poorest quintile (AOR: 2.19; 95% CI: 1.09\u0026ndash;4.40; \u003cem\u003ep\u003c/em\u003e = 0.03). As in the primary analysis, women who attended four or more ANC visits had lower odds of delivering in a facility than those with fewer visits (AOR: 0.75; 95% CI: 0.59\u0026ndash;0.96; \u003cem\u003ep\u003c/em\u003e = 0.02). Including iron supplementation in the model did not meaningfully change the observed association.\u003c/p\u003e\n\u003cp\u003eIron tablet use during ANC was not significantly linked to facility-based delivery (AOR: 1.10; 95% CI: 0.54\u0026ndash;2.25; \u003cem\u003ep\u003c/em\u003e = 0.79), indicating it may be a limited proxy for ANC quality in this setting. Media exposure remained marginally associated with increased odds of facility delivery (AOR: 1.28; 95% CI: 0.99\u0026ndash;1.66; \u003cem\u003ep\u003c/em\u003e = 0.06), while distance to the facility remained a borderline non-significant factor (AOR: 0.78; 95% CI: 0.58\u0026ndash;1.05; \u003cem\u003ep\u003c/em\u003e = 0.10).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4. Adjusted Odds Ratios (AOR) and 95% Confidence Intervals for Facility Delivery with Interaction Between ANC Visits and Residence\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" width=\"536\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eAOR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eANC \u0026ge;4 visits\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.57 \u0026ndash; 1.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.53\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eResidence: Rural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.45 \u0026ndash; 2.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eANC \u0026ge;4 * Rural (interaction term)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.47 \u0026ndash; 1.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.38\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ePrimary education\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.68 \u0026ndash; 1.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.90\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSecondary/Higher education\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.51 \u0026ndash; 1.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.46\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eWealth: Poorer vs Poorest\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.72 \u0026ndash; 1.31\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.84\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eWealth: Middle vs Poorest\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.88 \u0026ndash; 1.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eWealth: Richer vs Poorest\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.09 \u0026ndash; 4.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.03*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eWealth: Richest vs Poorest\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.67 \u0026ndash; 2.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.51\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eDistance not a big problem\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.58 \u0026ndash; 1.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMedia exposure\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.99 \u0026ndash; 1.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTo explore whether the association between ANC visit frequency and facility delivery varied by place of residence, an interaction term between ANC attendance (\u0026ge;4 visits) and rural residence was included in the model (Table 4).\u003c/p\u003e\n\u003cp\u003eThe interaction term between having four or more ANC visits and rural residence was not statistically significant (AOR: 0.79; 95% CI: 0.47\u0026ndash;1.33; \u003cem\u003ep\u003c/em\u003e = 0.38), suggesting that the inverse association between high ANC attendance and facility delivery did not differ meaningfully between rural and urban settings. Similarly, the main effects for ANC \u0026ge;4 visits (AOR: 0.87; 95% CI: 0.57\u0026ndash;1.33; \u003cem\u003ep\u003c/em\u003e = 0.53) and rural residence (AOR: 1.02; 95% CI: 0.45\u0026ndash;2.28; \u003cem\u003ep\u003c/em\u003e = 0.97) were not significant in this model.\u003c/p\u003e\n\u003cp\u003eAs in previous models, women in the richer wealth quintile had significantly higher odds of facility delivery compared to those in the poorest quintile (AOR: 2.19; 95% CI: 1.09\u0026ndash;4.40; \u003cem\u003ep\u003c/em\u003e = 0.03). Other covariates, including education level, distance to facility, and media exposure, did not reach statistical significance, although media exposure remained marginally associated with increased odds of facility use (AOR: 1.28; 95% CI: 0.99\u0026ndash;1.66; \u003cem\u003ep\u003c/em\u003e = 0.06).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 5. Stratified Logistic Regression for Facility Delivery Among Primiparous Women\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellpadding=\"0\" width=\"609\"\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eAOR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e95% CI\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003eP-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e(Intercept)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e15.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e[3.46, 65.95]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ePrimary education\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e[0.36, 2.93]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.95\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eSecondary/Higher education\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e[0.39, 3.20]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.83\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRural residence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e[0.23, 1.56]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003ePoorer wealth quintile\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e[0.73, 2.33]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.37\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eMiddle wealth quintile\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e[0.76, 2.90]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.25\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRicher wealth quintile\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e2.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e[0.89, 7.68]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eRichest wealth quintile\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e[0.53, 4.87]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.40\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003e\u0026ge;4 ANC visits\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e[0.47, 1.06]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eDistance is a problem (yes)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e[0.42, 1.23]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd\u003e\n \u003cp\u003eAccess to media (yes)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e1.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e[0.73, 1.70]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd\u003e\n \u003cp\u003e0.62\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eTo further explore whether the determinants of facility-based delivery differed by parity, a stratified logistic regression analysis was conducted among primiparous women (Table 5).\u003c/p\u003e\n\u003cp\u003eNone of the included predictors reached statistical significance at the \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05 threshold, though some trends were observed. Women in the richer wealth quintile had higher, but not statistically significant, odds of facility delivery compared to the poorest quintile (AOR: 2.61; 95% CI: 0.89\u0026ndash;7.68; \u003cem\u003ep\u003c/em\u003e = 0.08). A comparable pattern was noted for women with four or more ANC visits, who had lower odds of delivering in a facility (AOR: 0.71; 95% CI: 0.47\u0026ndash;1.06), although the association was not statistically significant (p = 0.09).\u003c/p\u003e\n\u003cp\u003eOther variables, including education level, rural residence, distance to facility, and media exposure, were not significantly associated with place of delivery in this subgroup.\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThis study examined determinants of facility-based delivery among Zambian women who received at least one antenatal care (ANC) visit during their most recent pregnancy. While overall facility delivery coverage among ANC users was high (93.0%), we observed persistent disparities by wealth status and media exposure. Women in the richer wealth quintile had more than twice the odds of delivering in a health facility compared to the poorest women, highlighting ongoing structural inequities in access to skilled care despite similar ANC engagement. This pattern is consistent with prior analyses showing that wealth remains a key driver of institutional delivery in sub-Saharan Africa, even among women who access other maternal health services (23\u0026ndash;25).\u003c/p\u003e\n\u003cp\u003eAn unexpected finding was that women with four or more ANC visits had significantly lower odds of delivering in a health facility compared to those with fewer visits. This contradicts most prior studies, which typically find a positive association between frequent ANC and skilled birth attendance (26\u0026ndash;28). One possible explanation is selection bias, that is, women who anticipate home births due to cultural norms, cost concerns, or mistrust of facility-based care may still attend ANC for fetal monitoring, tetanus shots, or iron supplementation, without intending to deliver at a facility. Previous qualitative work in Zambia supports this interpretation, reporting that some women engage with ANC services while maintaining traditional delivery preferences or fearing mistreatment at health facilities (29,30).\u003c/p\u003e\n\u003cp\u003eAnother explanation relates to perceived quality of care. The WHO framework emphasizes that effective ANC must include not only contact frequency but also respectful communication, individualized counseling, and birth preparedness planning (31). If these components are lacking, higher ANC attendance may not translate into increased facility utilization. Moreover, ANC visits in rural or underserved areas may be delivered via outreach clinics or health posts with limited capacity to support delivery referrals, further weakening the link between ANC exposure and facility-based delivery (32). These findings underscore that coverage is not synonymous with quality, and that ANC interventions must be coupled with targeted efforts to build trust, improve referral systems, and address economic barriers.\u003c/p\u003e\n\u003cp\u003eOur stratified analysis among primiparous women revealed broadly similar associations between wealth, ANC attendance, and delivery location, though the effects were less precise. This consistency suggests that wealth-related disparities in facility delivery persist across parity groups and merit broader policy attention. While we did not observe statistically significant associations with maternal education or rural residence in adjusted models, this may reflect reduced variability in these exposures among ANC-attending women or confounding by wealth and access factors.\u003c/p\u003e\n\u003cp\u003eMedia exposure was marginally associated with higher odds of facility delivery, echoing prior research that links health messaging through radio and television to improved maternal health behaviors (33,34). Expanding access to tailored mass communication campaigns, particularly in underserved areas, may help reinforce positive health-seeking norms and complement facility-based interventions.\u003c/p\u003e\n\u003cp\u003eFrom a policy standpoint, our findings point to the need for equity-enhancing strategies within Zambia\u0026rsquo;s maternal health system. Targeted programs such as maternity waiting homes, transportation vouchers, or delivery incentives for low-income women could help close the gap between ANC attendance and skilled birth attendance. Zambia\u0026rsquo;s Safe Motherhood Action Groups (SMAGs) and community-based birth preparedness initiatives have shown promise in increasing institutional delivery rates, but broader scale-up and integration into ANC platforms may be needed (35,36).\u003c/p\u003e\n\u003cp\u003eThis study has several strengths, including use of a nationally representative dataset, focus on a key subpopulation of ANC users, and inclusion of interaction and stratified models. However, some limitations must be noted. The cross-sectional design limits causal inference. Additionally, self-reported data on ANC and delivery location may be subject to recall and social desirability bias.\u003c/p\u003e\n\u003cp\u003eWhile Zambia has achieved high ANC and facility delivery coverage overall, gaps in equitable access remain. Merely attending ANC is not sufficient to ensure skilled delivery, particularly for socioeconomically disadvantaged women. Efforts to improve the quality, continuity, and trustworthiness of maternal health services, especially within ANC, are essential for realizing the full benefits of facility-based delivery and advancing universal health coverage goals.\u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eDespite high ANC coverage in Zambia, disparities in facility-based delivery persist among ANC users, particularly by wealth status. The inverse association between frequent ANC visits and facility delivery highlights missed opportunities to translate contact into effective care. To close this gap, maternal health programs should strengthen birth preparedness counseling during ANC, expand transport and delivery incentives for low-income women, and improve the perceived quality and respectfulness of facility-based care. Advancing equity in maternal health will require not only increasing service contact but ensuring that services are trusted, accessible, and responsive to women\u0026rsquo;s needs.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eEthics approval and consent to participate.\u003c/p\u003e\n\u003cp\u003eAll participants provided informed consent at the time of original data collection. The original survey received ethical approval from the Tropical Diseases Research Centre in Zambia and the Institutional Review Board of ICF International. As this was a secondary analysis of anonymized data, no additional consent was required.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study involved a secondary analysis of de-identified, publicly accessible data from the 2018 Zambia Demographic and Health Survey (ZDHS). The original survey protocol received ethical clearance from the Tropical Diseases Research Centre (TDRC) in Zambia and the ICF Institutional Review Board. Informed written consent was obtained from all participants during data collection. As the dataset is anonymized and publicly available, additional ethical approval was not required for this analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets analyzed during the current study are available from the DHS Program repository:\u003cbr\u003e\u0026nbsp;https://dhsprogram.com/data/available-datasets.cfm\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe author declares that there are no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo specific funding was received for this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePK, WM, and NN conceptualized the study, conducted the data analysis, and wrote the original draft. LN, CM, and HM contributed to review and editing of the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors acknowledge the Demographic and Health Surveys (DHS) Program for granting access to the 2018 Zambia DHS data.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWorld Health Organization. Trends in Maternal Mortality: 2000 to 2020. Geneva: WHO; 2023.\u003c/li\u003e\n\u003cli\u003eWorld Health Organization. Strategies toward ending preventable maternal mortality (EPMM). Geneva: WHO; 2015.\u003c/li\u003e\n\u003cli\u003eSay L, Chou D, Gemmill A, Tun\u0026ccedil;alp \u0026Ouml;, Moller AB, Daniels J, et al. Global causes of maternal death: a WHO systematic analysis. 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A systematic review of inequalities in the use of maternal health care in developing countries: examining the scale of the problem and the importance of context. Bull World Health Organ. 2007 Oct;85(10):812\u0026ndash;9. \u003c/li\u003e\n\u003cli\u003eGabrysch S, Campbell OM. Still too far to walk: Literature review of the determinants of delivery service use. BMC Pregnancy Childbirth. 2009 Dec 11;9(1):34. \u003c/li\u003e\n\u003cli\u003eBenova L, Macleod D, Footman K, Cavallaro F, Lynch CA, Campbell OMR. Role of the private sector in childbirth care: cross‐sectional survey evidence from 57 low‐ and middle‐income countries using Demographic and Health Surveys. Tropical Medicine \u0026amp; International Health. 2015 Dec 28;20(12):1657\u0026ndash;73. \u003c/li\u003e\n\u003cli\u003eMoyer CA, Mustafa A. Drivers and deterrents of facility delivery in sub-Saharan Africa: A systematic review. Reprod Health. 2013;10(1). \u003c/li\u003e\n\u003cli\u003eBerelie Y, Yeshiwas D, Yismaw L, Alene M. Determinants of institutional delivery service utilization in Ethiopia: A population based cross sectional study. BMC Public Health. 2020 Jul 8;20(1). \u003c/li\u003e\n\u003cli\u003eWang W, Alva S, Wang S, Fort A. DHS COMPARATIVE REPORTS 26 LEVELS AND TRENDS IN THE USE OF MATERNAL HEALTH SERVICES IN DEVELOPING COUNTRIES [Internet]. 2011. Available from: www.measuredhs.com. Accessed 25 June, 2025. \u003c/li\u003e\n\u003cli\u003eSialubanje C, Massar K, Hamer DH, Ruiter RAC. Reasons for home delivery and use of traditional birth attendants in rural Zambia: A qualitative study. BMC Pregnancy Childbirth. 2015 Sep 11;15(1). \u003c/li\u003e\n\u003cli\u003eBohren MA, Vogel JP, Hunter EC, Lutsiv O, Makh SK, Souza JP, et al. The Mistreatment of Women during Childbirth in Health Facilities Globally: A Mixed-Methods Systematic Review. PLoS Med. 2015 Jun 30;12(6):e1001847. \u003c/li\u003e\n\u003cli\u003eTun\u0026ccedil;alp Ӧ., Were W, MacLennan C, Oladapo O, G\u0026uuml;lmezoglu A, Bahl R, et al. Quality of care for pregnant women and newborns\u0026mdash;the WHO vision. BJOG. 2015 Jul;122(8):1045\u0026ndash;9. \u003c/li\u003e\n\u003cli\u003eKruk ME, Kujawski S, Moyer CA, Adanu RM, Afsana K, Cohen J, et al. Next generation maternal health: external shocks and health-system innovations. The Lancet. 2016 Nov;388(10057):2296\u0026ndash;306. \u003c/li\u003e\n\u003cli\u003eFatema K, Lariscy JT. Mass media exposure and maternal healthcare utilization in South Asia. SSM Popul Health. 2020 Aug;11:100614. \u003c/li\u003e\n\u003cli\u003eWaiswa P, Akuze J, Peterson S, Kerber K, Tetui M, Forsberg BC, et al. Differences in essential newborn care at birth between private and public health facilities in eastern Uganda. Glob Health Action. 2015 Dec 31;8(1):24251. \u003c/li\u003e\n\u003cli\u003eManandhar DS, Osrin D, Shrestha BP, Mesko N, Morrison J, Tumbahangphe KM, et al. Effect of a participatory intervention with women\u0026rsquo;s groups on birth outcomes in Nepal: cluster-randomised controlled trial. The Lancet. 2004 Sep;364(9438):970\u0026ndash;9. \u003c/li\u003e\n\u003cli\u003eSialubanje C, Massar K, Horstkotte L, Hamer DH, Ruiter RAC. Increasing utilisation of skilled facility-based maternal healthcare services in rural Zambia: the role of safe motherhood action groups. Reprod Health. 2017 Dec 10;14(1):81. \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Not applicable","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Facility-based delivery, Antenatal care, Health disparities, Demographic and Health Survey, Zambia ","lastPublishedDoi":"10.21203/rs.3.rs-7001027/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7001027/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e\u003cbr\u003e\nFacility-based delivery is a key intervention for reducing maternal and neonatal mortality. While antenatal care (ANC) attendance is high in Zambia, disparities in access to skilled delivery persist. This study examined the determinants of facility-based delivery among women who attended ANC, focusing on sociodemographic and health system factors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethod\u003c/strong\u003e\u003cbr\u003e\nWe conducted a cross-sectional analysis using data from the 2018 Zambia Demographic and Health Survey. The sample included women aged 15–49 who had a live birth in the five years preceding the survey and attended at least one ANC visit during their most recent pregnancy. The primary outcome was facility-based delivery. Multivariable logistic regression models, adjusted for survey design, were used to estimate associations between facility delivery and factors including wealth, education, residence, ANC utilization, perceived distance barriers, and media exposure.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e\u003cbr\u003e\nAmong 4,630 ANC-attending women, 93.0% delivered in a health facility. In adjusted models, women in the richer wealth quintile had higher odds of facility delivery compared to the poorest (AOR: 2.19; 95% CI: 1.08–4.43; \u003cem\u003ep\u003c/em\u003e=0.03). Surprisingly, women who attended four or more ANC visits were less likely to deliver in a health facility compared to those with fewer visits (AOR: 0.75; 95% CI: 0.59–0.96; \u003cem\u003ep\u003c/em\u003e=0.02). Exposure to media showed a borderline positive association with facility-based delivery (AOR: 1.29; 95% CI: 1.00–1.66; \u003cem\u003ep\u003c/em\u003e=0.05). No significant associations were observed for education level, rural residence, or parity.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e\u003cbr\u003e\nImproving the quality and content of ANC is essential to strengthen the link between antenatal contact and facility-based delivery, particularly among economically disadvantaged women. Policies that incorporate birth preparedness counseling, offer transport or delivery incentives, and explore the role of media exposure as a tool for promoting safe delivery may help reduce access barriers and advance equity in skilled childbirth services in Zambia.\u003c/p\u003e","manuscriptTitle":"Disparities in Facility Delivery Among Women Receiving Antenatal Care in Zambia: A DHS-Based Analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-07 07:42:43","doi":"10.21203/rs.3.rs-7001027/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"db8f9105-50eb-460c-97e0-16c413f6bdc4","owner":[],"postedDate":"July 7th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":50740756,"name":"Obstetrics \u0026 Gynecology"},{"id":50740757,"name":"Maternal \u0026 Fetal Medicine"}],"tags":[],"updatedAt":"2025-07-07T07:42:43+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-07 07:42:43","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7001027","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7001027","identity":"rs-7001027","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}