Regional Disparities and Sociodemographic Determinants of Institutional Delivery Dropout (IDD) among Women in Nigeria: Analysis of the 2018 Demographic and Health Survey

Regional Disparities and Sociodemographic Determinants of Institutional Delivery Dropout (IDD) among Women in Nigeria: Analysis of the 2018 Demographic and Health Survey | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Regional Disparities and Sociodemographic Determinants of Institutional Delivery Dropout (IDD) among Women in Nigeria: Analysis of the 2018 Demographic and Health Survey Jamilu Sani, Abubakar Yakubu Abbani, Muazu Alhaji Shamaki, Umar Idris Boku, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6455632/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 Institutional delivery is a critical component of maternal healthcare that reduces the risk of maternal and neonatal morbidity and mortality. While antenatal care (ANC) coverage has improved in Nigeria, a significant number of women who attend ANC still deliver outside health facilities—a phenomenon referred to as institutional delivery dropout (IDD). This study examined the prevalence, regional disparities, and sociodemographic determinants of IDD among women of reproductive age in Nigeria. Methods This cross-sectional study utilized data from the 2018 Nigeria Demographic and Health Survey (NDHS). The analysis included 16,100 women aged 15–49 years who reported at least one ANC visit and provided information on the place of delivery for their most recent birth. Descriptive statistics, bivariate analysis using crude odds ratios (COR), and multivariable logistic regression were conducted to assess predictors of institutional delivery. All analyses accounted for the complex survey design and applied sampling weights. Results The prevalence of IDD in Nigeria was 48%. Marked regional disparities were observed, with the highest dropout in the North West (75.9%) and the lowest in the South East (17.1%). In bivariate analysis, maternal education, wealth index, religion, residence, and region were significantly associated with institutional delivery. Multivariable analysis confirmed that higher education (AOR = 5.14; 95% CI: 4.12–6.41), higher wealth (AOR = 4.65; 95% CI: 3.80–5.69), Christian religion (AOR = 0.60; 95% CI: 0.53–0.69), urban residence (AOR = 1.14; 95% CI: 1.02–1.25), and southern regional residence were associated with increased likelihood of institutional delivery. Conclusion Nearly half of Nigerian women who attend ANC still deliver outside health facilities, reflecting a serious breakdown in the maternal healthcare continuum. Sociodemographic inequalities and regional disparities play a substantial role in institutional delivery decisions. Addressing IDD requires targeted interventions that improve health facility access, enhance service quality, and challenge sociocultural norms—especially in underserved regions. These findings underscore the need for regionally targeted interventions to improve maternal health outcomes and reduce preventable maternal deaths in Nigeria. Institutional delivery dropout (IDD) Antenatal care (ANC) Maternal health Health facility delivery Nigeria NDHS Regional disparities Sociodemographic factors Healthcare utilization Figures Figure 1 Figure 2 Figure 3 Background Institutional delivery, defined as childbirth assisted by skilled health professionals within a health facility, is a critical intervention for reducing maternal and neonatal morbidity and mortality ( 1 , 2 ). Globally, it has been recognized as an essential component of the continuum of care for maternal health, and its importance is underscored in efforts to achieve Sustainable Development Goal (SDG) 3, which aims to reduce the global maternal mortality ratio to less than 70 per 100,000 live births by 2030 ( 3 , 4 ). Despite global progress, sub-Saharan Africa continues to bear a disproportionate burden of maternal deaths, accounting for approximately 70% of all maternal deaths worldwide ( 5 ). Nigeria alone contributes nearly 20% of the global maternal mortality burden, with an estimated maternal mortality ratio of 512 per 100,000 live births as of the 2018 Nigeria Demographic and Health Survey (NDHS) ( 6 ). One of the major contributing factors to this high mortality is the low utilization of institutional delivery services, even among women who attend antenatal care (ANC) services. This phenomenon, which is commonly referred to as institutional delivery dropout (IDD), represents a critical gap in the maternal health service continuum and undermines the effectiveness of ANC in preventing adverse pregnancy outcomes ( 7 – 9 ). IDD reflects a missed opportunity for skilled attendance at birth, despite initial contact with the healthcare system through ANC. Numerous studies have shown that while ANC coverage is relatively high in Nigeria, a significant proportion of women who attend ANC ultimately deliver at home or in other non-institutional settings ( 10 – 13 ). This dropout pattern is concerning, as it suggests that barriers persist between ANC and delivery care. These barriers may include sociocultural norms, cost of delivery services, transportation challenges, perceived or experienced poor quality of care, and lack of autonomy in decision-making ( 14 – 17 ). Evidence indicates that IDD is not evenly distributed across populations and regions. Sociodemographic factors such as maternal education, age, parity, household wealth, religious beliefs, and geographic location are known to influence the likelihood of delivering in a health facility ( 1 , 2 , 18 ). In Nigeria, significant regional disparities exist in maternal health service utilization, reflecting differences in socioeconomic development, cultural practices, and health system infrastructure ( 15 , 19 ). Understanding the extent and drivers of institutional delivery dropout within the Nigerian context is essential for designing effective interventions aimed at improving maternal and neonatal outcomes ( 20 ). This study, therefore, seeks to examine the prevalence and regional disparities of institutional delivery dropout in Nigeria and to identify the sociodemographic factors associated with this phenomenon. By using nationally representative data from the 2018 NDHS, this study provides empirical insights into gaps in maternal healthcare utilization and offers evidence to guide policy and programmatic strategies for improving institutional delivery rates across the country. METHODS Study Design and Setting This study employed a cross-sectional design based on secondary data from the 2018 Nigeria Demographic and Health Survey (NDHS). The NDHS is a nationally representative survey conducted by the National Population Commission (NPC) in collaboration with ICF, covering all six geopolitical zones of Nigeria: North Central, North East, North West, South East, South South, and South West. These regions vary significantly in terms of socioeconomic development, cultural practices, and health infrastructure, which can influence maternal healthcare utilization, including place of delivery. Data Source and Sample Data were drawn from the Individual Recode (IR) file of the 2018 NDHS, which includes comprehensive information on women's reproductive health, demographic characteristics, and healthcare utilization. The analysis focused on women aged 15–49 years who reported at least one antenatal care (ANC) visit and provided information on the place of delivery for their most recent live birth within the five years preceding the survey. After applying the inclusion criteria, a weighted sample of 16,100 women was included in the analysis. Outcome Variable The primary outcome variable in this study was institutional delivery dropout (IDD), defined as the failure to deliver in a health facility despite attending at least one antenatal care (ANC) visit. This variable was operationalized as a binary outcome to capture whether or not a woman utilized institutional delivery services following ANC attendance. Women who received at least one ANC visit but delivered outside a recognized health facility, such as at home or in other non-medical settings, were considered to have experienced institutional delivery dropout. In contrast, those who delivered in a health facility, including government hospitals, health centres, health posts, or private medical facilities, were classified as having completed the institutional delivery pathway. For analysis, institutional delivery dropout was coded as “1,” while institutional delivery was coded as “0.” Independent Variables The independent variables included sociodemographic and contextual factors based on previous literature and data availability. These were: Age group (15–19, 20–24, 25–29, 30–34, 35–39, 40–44, 45–49 years) Educational attainment (no education, primary, secondary, higher) Marital status (never in union, married, living with partner, widowed, divorced/separated) Religion (Christianity, Islam, others) Wealth index (poorest, poorer, middle, richer, richest) Working status (employed, not employed) Place of residence (urban, rural) Perceived distance to health facility (a big problem, not a big problem) Region of residence (North Central, North East, North West, South East, South South, South West) Statistical Analysis Descriptive statistics were used to summarize the characteristics of the study population. Categorical variables were presented as weighted frequencies and percentages. Bivariate logistic regression was performed to assess the unadjusted associations between each independent variable and institutional delivery, with crude odds ratios (CORs) and 95% confidence intervals (CIs) reported. To identify independent predictors of institutional delivery, multivariable logistic regression was conducted, adjusting for all covariates. Adjusted odds ratios (AORs) with corresponding 95% CIs were reported. A p-value < 0.05 was considered statistically significant. All analyses were conducted with consideration for the complex sampling design of the NDHS. This involved applying appropriate sampling weights, clustering, and stratification using the svy command in Stata version 17. To facilitate clear data interpretation, various visualizations were employed, including pie charts and bar plots. Furthermore, a regional map was generated using Python and GeoPandas, incorporating GADM shapefiles for Nigeria. This map effectively illustrated the spatial distribution and highlighted regional disparities in institutional delivery across the country. Ethical Considerations Ethical approval for the 2018 NDHS was obtained from the National Health Research Ethics Committee of Nigeria and the Institutional Review Board of ICF. Informed consent was obtained from all participants at the time of data collection. As this study involved secondary analysis of anonymized, publicly available data, no additional ethical clearance was required. Sociodemographic Characteristics Table 1 presents the sociodemographic characteristics of the 16,100 women included in the analysis. The most common age group was 25–29 years (26.4%), followed by 30–34 years (22.9%) and 20–24 years (18.8%). Approximately 33.9% of respondents had no formal education, while 38.2% attained secondary education and 11.3% completed higher education. A large majority were currently married (90.8%) and over half (55.3%) identified as Muslim. Employment was reported by 72.4% of the women. Slightly more respondents lived in rural areas (53.4%) compared to urban areas (46.6%). The North West region contributed the largest proportion of the sample (30.0%), followed by the South West (17.5%) and North East (17.0%). Table 1 Sociodemographic Characteristics (N = 16,100) Variable Weighted Frequency Percent Age Group 15–19 802 4.98 20–24 3,019 18.76 25–29 4,247 26.38 30–34 3,684 22.88 35–39 2,683 16.67 40–44 1,193 7.41 45–49 471 2.92 Educational Level No Education 5,461 33.92 Primary 2,674 16.61 Secondary 6,147 38.18 Higher 1,818 11.29 Marital Status Never in Union 380 2.36 Married 14,615 90.78 Living with Partner 512 3.18 Widowed 209 1.30 Divorced/Separated 384 2.39 Religion Christianity 7,115 44.19 Islam 8,910 55.34 Others 75 0.47 Wealth Index Poorest 2,434 15.12 Poorer 3,102 19.27 Middle 3,516 21.84 Richer 3,563 22.13 Richest 3,485 21.65 Working Status No 4,442 27.59 Yes 11,658 72.41 Residence Urban 7,507 46.63 Rural 8,593 53.37 Region North Central 2,156 13.39 North East 2,738 17.00 North West 4,825 29.97 South East 2,009 12.48 South South 1,557 9.67 South West 2,816 17.49 Prevalence and Regional Disparities of Institutional Delivery Dropout The overall prevalence of institutional delivery dropout (IDD), defined as not delivering in a health facility despite attending at least one ANC visit, was found to be 48% (Fig. 1 ). Notably, there was a considerable regional variation in IDD (Fig. 2 ). The North West recorded the highest proportion of women with IDD (75.9%), followed by the North East (63.8%). In contrast, the South East had the lowest dropout rate (17.1%), followed by the South West (20.7%) and North Central (35.1%) (Fig. 3 ). Bivariate Associations with Institutional Delivery Dropout Bivariate logistic regression results are summarized in Table 2 . Increasing maternal age was associated with lower odds of IDD compared to adolescents aged 15–19 years. For instance, women aged 30–34 had 2.03 times the odds of institutional delivery compared to the reference group (COR = 2.03; 95% CI: 1.69–2.44), and those aged 35–39 had an even higher likelihood (COR = 2.22; 95% CI: 1.83–2.68). Educational attainment was strongly associated with lower IDD. Compared to women with no education, those with primary education had nearly three times the odds of delivering in a facility (COR = 2.91; 95% CI: 2.58–3.27), while those with secondary and higher education had markedly higher odds (COR = 6.88; 95% CI: 6.25–7.58 and COR = 23.50; 95% CI: 19.52–28.28, respectively). Religion also showed significant differences; Muslim women had substantially lower odds of delivering in a health facility compared to Christians (COR = 0.22; 95% CI: 0.20–0.24). Wealth index was positively associated with institutional delivery. Compared to the poorest group, women in the richest quintile had nearly 18 times the odds of delivering in a health facility (COR = 17.85; 95% CI: 15.24–20.91). Residence and distance to health facility were significant predictors. Rural women had significantly lower odds of institutional delivery than urban women (COR = 0.30; 95% CI: 0.28–0.33), and women who did not perceive distance as a major barrier had higher odds of institutional delivery (COR = 1.33; 95% CI: 1.22–1.45). Regional differences were striking. Compared to the North West, all other regions had significantly higher odds of institutional delivery. Women in the South East had the highest odds (COR = 15.33; 95% CI: 13.28–17.69), followed by those in the South West (COR = 12.09; 95% CI: 10.28–14.23), North Central (COR = 5.84; 95% CI: 5.18–6.59), and South South (COR = 4.74; 95% CI: 4.11–5.45). Table 2 Bivariate analysis of factors associated with IDD Variable Institutional Delivery COR (95% CI) p-value NO - IDD (%) YES (%) Age Group 15–19 (ref.) 494 (61.60) 308 (38.40) 1 20–24 1,649 (54.61) 1,371 (45.39) 1.33 (1.11, 1.61) 0.003 25–29 2,007 (47.26) 2,240 (52.74) 1.79 (1.49, 2.15) 0.000 30–34 1,626 (44.15) 2,058 (55.85) 2.03 (1.69, 2.44) 0.000 35–39 1,127 (41.99) 1,557 (58.01) 2.22 (1.83, 2.68) 0.000 40–44 572 (47.94) 621 (52.06) 1.74 (1.41, 2.16) 0.000 45–49 239 (50.82) 232 (49.18) 1.55 (1.19, 2.02) 0.001 Educational Level No Education (ref.) 4,156 (76.10) 1,305 (23.90) 1 Primary 1,397 (52.27) 1,277 (47.73) 2.91 (2.58, 3.27) 0.000 Secondary 1,944 (31.63) 4,203 (68.37) 6.88 (6.25, 7.58) 0.000 Higher 217 (11.93) 1,601 (88.07) 23.50 (19.52, 28.28) 0.000 Marital Status Never in Union (ref.) 137 (35.99) 243 (64.01) 1 Married 7,159 (48.98) 7,457 (51.02) 0.59 (0.47, 0.73) 0.000 Living with Partner 183 (35.76) 329 (64.24) 1.01 (0.75, 1.35) 0.946 Widowed 74 (35.69) 134 (64.31) 1.01 (0.69, 1.49) 0.947 Divorced/Separated 162 (42.03) 223 (57.97) 0.78 (0.56, 1.07) 0.122 Religion Christianity (ref.) 1,982 (27.85) 5,133 (72.15) 1 Islam 5,688 (63.83) 3,222 (36.17) 0.22 (0.20, 0.24) 0.000 Others 45 (59.93) 30 (40.07) 0.26 (0.16, 0.41) 0.000 Wealth Index Poorest (ref.) 1,961 (80.56) 473 (19.44) 1 Poorer 2,088 (67.31) 1,014 (32.69) 2.01 (1.76, 2.30) 0.000 Middle 1,777 (50.55) 1,738 (49.45) 4.05 (3.56, 4.62) 0.000 Richer 1,231 (34.56) 2,332 (65.44) 7.85 (6.84, 9.02) 0.000 Richest 657 (18.84) 2,828 (81.16) 17.85 (15.24, 20.91) 0.000 Distance to Health Facility Big problem (Ref) 1,975 (5.45) 1,720 (46.55) 1 Not a big problem 5,739 (4.27) 6,666 (53.73) 1.33 (1.22–1.45) 0.000 Working Status No (ref.) 2,569 (57.83) 1,873 (42.17) 1 Yes 5,146 (44.14) 6,513 (55.86) 1.74 (1.60, 1.89) 0.000 Residence Urban (ref.) 2,433 (32.40) 5,075 (67.60) 1 Rural 5,282 (61.47) 3,311 (38.53) 0.30 (0.28, 0.33) 0.000 Region North West (ref.) 3,663 (75.93) 1,161 (24.07) 1 North Central 756 (35.07) 1,400 (64.93) 5.84 (5.18, 6.59) 0.000 North East 1,747 (63.81) 991 (36.19) 1.79 (1.59, 2.02) 0.000 South East 343 (17.07) 1,666 (82.93) 15.33 (13.28, 17.69) 0.000 South South 622 (39.98) 934 (60.02) 4.74 (4.11, 5.45) 0.000 South West 583 (20.69) 2,233 (79.31) 12.09 (10.28, 14.23) 0.000 Multivariable Predictors of Institutional Delivery Dropout Table 3 presents the results from multivariable logistic regression analysis. After adjusting for covariates, educational attainment remained a strong predictor of institutional delivery. Women with higher education were over five times more likely to deliver in a health facility compared to those with no education (AOR = 5.14; 95% CI: 4.12–6.41). Those with secondary (AOR = 2.04; 95% CI: 1.79–2.32) and primary education (AOR = 1.31; 95% CI: 1.14–1.50) also had significantly increased odds. Wealth status continued to be positively associated with institutional delivery. The odds of delivering in a health facility increased progressively across wealth quintiles, reaching an AOR of 4.65 (95% CI: 3.80–5.69) among the richest. Muslim women remained significantly less likely than Christians to use health facilities for delivery (AOR = 0.60; 95% CI: 0.53–0.69). Women residing in rural areas had lower odds of institutional delivery compared to those in urban areas (AOR = 0.88; 95% CI: 0.80–0.98). Reporting distance to health facility as not being a major problem was associated with increased institutional delivery (AOR = 1.16; 95% CI: 1.05–1.29). Regional disparities persisted after adjustment. Compared to the North West, women in the South East had significantly higher odds of institutional delivery (AOR = 5.22; 95% CI: 4.30–6.33), followed by the South West (AOR = 4.17; 95% CI: 3.44–5.06), North Central (AOR = 3.83; 95% CI: 3.31–4.43), North East (AOR = 2.04; 95% CI: 1.80–2.33), and South South (AOR = 1.33; 95% CI: 1.09–1.62). Table 3 Multivariable analysis of factors associated with IDD Category Institutional Delivery AOR (95% CI) p-value NO - IDD (%) YES (%) Age Group 15–19 (ref.) 494 (61.60) 308 (38.40) 1 20–24 1,649 (54.61) 1,371 (45.39) 0.85 (0.67–1.06) 0.15 25–29 2,007 (47.26) 2,240 (52.74) 0.80 (0.64–0.99) 0.044 30–34 1,626 (44.15) 2,058 (55.85) 0.82 (0.66–1.03) 0.092 35–39 1,127 (41.99) 1,557 (58.01) 0.92 (0.73–1.16) 0.491 40–44 572 (47.94) 621 (52.06) 0.89 (0.68–1.17) 0.421 45–49 239 (50.82) 232 (49.18) 1.10 (0.81–1.50) 0.55 Educational Level No Education (ref.) 4,156 (76.10) 1,305 (23.90) 1 Primary 1,397 (52.27) 1,277 (47.73) 1.31 (1.14–1.50) 0.000 Secondary 1,944 (31.63) 4,203 (68.37) 2.04 (1.79–2.32) 0.000 Higher 217 (11.93) 1,601 (88.07) 5.14 (4.12–6.41) 0.000 Religion Christianity (ref.) 1,982 (27.85) 5,133 (72.15) 1 Islam 5,688 (63.83) 3,222 (36.17) 0.60 (0.53–0.69) 0.000 Others 45 (59.93) 30 (40.07) 0.68 (0.41–1.11) 0.119 Wealth Index Poorest (ref.) 1,961 (80.56) 473 (19.44) 1 Poorer 2,088 (67.31) 1,014 (32.69) 1.63 (1.41–1.89) 0.000 Middle 1,777 (50.55) 1,738 (49.45) 2.32 (1.99–2.69) 0.000 Richer 1,231 (34.56) 2,332 (65.44) 3.14 (2.66–3.71) 0.000 Richest 657 (18.84) 2,828 (81.16) 4.65 (3.80–5.69) 0.000 Distance to Health Facility Big problem (Ref) 1,975 (5.45) 1,720 (46.55) 1 Not a big problem 5,739 (4.27) 6,666 (53.73) 1.16 (1.05–1.29) 0.004 Working Status No (ref.) 2,569 (57.83) 1,873 (42.17) 1 Yes 5,146 (44.14) 6,513 (55.86) 1.05 (0.95–1.16) 0.376 Residence Urban (ref.) 2,433 (32.40) 5,075 (67.60) 1 Rural 5,282 (61.47) 3,311 (38.53) 0.88 (0.80–0.98) 0.015 Region North West (ref.) 3,663 (75.93) 1,161 (24.07) 1 North Central 756 (35.07) 1,400 (64.93) 3.83 (3.31–4.43) 0.000 North East 1,747 (63.81) 991 (36.19) 2.04 (1.80–2.33) 0.000 South East 343 (17.07) 1,666 (82.93) 5.22 (4.30–6.33) 0.000 South South 622 (39.98) 934 (60.02) 1.33 (1.09–1.62) 0.004 South West 583 (20.69) 2,233 (79.31) 4.17 (3.44–5.06) 0.000 DISCUSSION This study investigated the prevalence and determinants of institutional delivery dropout (IDD) among women of reproductive age in Nigeria using nationally representative data from the 2018 NDHS. The findings reveal a substantial level of dropout from institutional delivery despite antenatal care (ANC) attendance, with nearly half (48%) of the women delivering outside health facilities. This pattern underscores a critical discontinuity in the maternal healthcare continuum, suggesting that ANC attendance does not necessarily translate into health facility delivery. The regional disparities in IDD were pronounced. The North West and North East regions recorded the highest dropout rates, whereas the South East and South West had the lowest. These differences likely reflect variations in sociocultural norms, healthcare infrastructure, security, and accessibility ( 21 ). The lower IDD rates in the southern regions may be attributed to better maternal health infrastructure and higher female educational attainment ( 22 – 24 ). In contrast, the northern regions are often characterized by deeply rooted cultural practices favoring home births, limited autonomy for women in healthcare decision-making, and high poverty levels, which may hinder access to facility-based care ( 25 , 26 ). Educational attainment emerged as one of the most significant predictors of institutional delivery. Women with higher education were over five times more likely to deliver in health facilities compared to those with no formal education. This finding is consistent with previous studies in Nigeria and other low- and middle-income countries, where maternal education is strongly associated with increased health literacy, financial autonomy, and favorable attitudes toward skilled birth attendance ( 27 – 30 ). Education also facilitates better communication with health workers and greater confidence in navigating the healthcare system ( 31 ). Economic status was another important determinant. A strong wealth gradient was observed, with women in the richest quintile having nearly five times the odds of institutional delivery compared to the poorest group. This is aligned with evidence that financial constraints, including transportation costs and informal payments, remain significant barriers to accessing skilled birth services ( 32 – 34 ). Despite Nigeria’s free maternal health policies in some states, out-of-pocket expenses and indirect costs often deter facility use, especially among the poor ( 35 ). Religious affiliation was also associated with IDD. Muslim women had significantly lower odds of institutional delivery than their Christian counterparts. This may reflect both regional concentrations, given that Muslims predominantly reside in northern Nigeria where IDD rates are highest, and also specific cultural or gender norms that influence care-seeking behaviors ( 26 , 36 ). Targeted community engagement and culturally appropriate health promotion strategies are essential to address such disparities ( 37 ). Contrary to expectations, employment status did not show a significant association with institutional delivery in the multivariable model. While employment may enhance women's financial capacity, it does not automatically translate to healthcare utilization if systemic or sociocultural barriers persist. Moreover, informal employment, which is prevalent among women in Nigeria, may not provide sufficient income or time flexibility to support facility-based delivery ( 38 ). Residence remained an independent predictor, with rural women less likely to deliver in health facilities than urban women. Rural areas often face infrastructural deficits, including long distances to health facilities, poor transportation networks, and inadequate availability of skilled personnel ( 39 , 40 ). Although women who did not perceive distance as a problem were more likely to deliver in a facility, geographic access alone does not guarantee utilization if other barriers, such as cost or provider attitudes, are present ( 41 ). The persistence of regional variation even after adjusting for sociodemographic factors suggests that contextual and health system-level influences play a significant role in shaping maternal health behaviors. These may include differences in state-level policies, health workforce density, quality of care, and availability of emergency obstetric services ( 42 , 43 ). CONCLUSION This study highlights a substantial burden of institutional delivery dropout in Nigeria, with nearly half of women who attend antenatal care failing to deliver in health facilities. Sociodemographic inequalities, including education, wealth, religion, and rural residence, as well as marked regional disparities, significantly influence this gap in the maternal health continuum. The persistence of dropout, especially in northern regions, reflects structural, cultural, and health system barriers to facility-based childbirth. Addressing these challenges requires more than improving ANC coverage; targeted, context-specific interventions that promote equitable access to quality delivery services are essential. Strengthening community engagement, enhancing health infrastructure, and implementing financial and geographic access strategies are critical steps toward achieving improved maternal health outcomes and reducing preventable maternal mortality in Nigeria. Strengths and Limitations This study's major strength lies in the use of a large, nationally representative dataset with rigorous sampling methods and standardized measurement protocols, allowing for generalizable findings across Nigeria. Furthermore, the analytical approach accounted for complex survey design and adjusted for multiple covariates, enhancing the validity of the associations observed. However, some limitations must be acknowledged. First, the cross-sectional nature of the data limits causal inference. Second, the reliance on self-reported data may introduce recall or social desirability bias, especially concerning ANC visits and delivery location. Third, certain potentially important factors such as quality of ANC, availability of transportation, or spousal influence were not captured in the dataset and thus could not be assessed. Implications for Policy and Practice The findings highlight the urgent need to strengthen the linkage between ANC attendance and facility-based delivery. This requires a multi-faceted strategy including health education during ANC visits, improved transportation and referral systems, financial protection mechanisms, and respectful maternity care. Special attention should be paid to northern regions and underserved rural communities where IDD is highest. Community-based interventions that engage traditional and religious leaders may be particularly effective in shifting norms and promoting institutional delivery. Declarations Ethics approval and consent to participate This study analyzed data from the 2018 Nigeria Demographic and Health Survey (NDHS), which adhered to the ethical principles outlined in the Helsinki Declaration. Approval for the survey was granted by both the National Health Research Ethics Committee of Nigeria (NHREC) and the ICF Institutional Review Board. Prior to data collection, informed consent was obtained from all participants. As this research involved secondary data analysis, confidentiality and anonymity were strictly maintained in accordance with established ethical standards. Consent for publication The study relies exclusively on secondary data from the DHS Program, specifically the 2018 NDHS dataset. No primary data collection was conducted for this research. Therefore, traditional consent for publication does not apply as no direct involvement of individual participants occurred. Competing interests The authors declare no competing interests. Clinical trial number Not applicable Funding No funding was received for this study. Author Contribution JS led the study design, data analysis, visualization, resource acquisition, data management, and manuscript drafting. AYA, MAS, YAA, and ROY supervised and critically reviewed the manuscript. AFU, UIB, MUG, RAY, and LB contributed to manuscript review and editing. Acknowledgement We thank the National Population Commission and ICF International for the 2018 NDHS data, and we appreciate the research team and participating women whose contributions were vital to this study. Data Availability The data utilized in this study are publicly available through the DHS Program and can be accessed via their official website: https://dhsprogram.com. References Tarik YD, Nigussie AA, Balcha WF, Getu AA. Factors associated with institutional delivery among mothers who gave birth within 1 year prior to the study at Gilgelbelles town, Northwest Ethiopia: a mixed-methods study. BMJ open. 2022;12(11):e061218. Wayessa ZJ, Dukale UG. Factors associated with institutional delivery among women in Bule Hora Town, Southern Ethiopia. Midwifery. 2021;97:102968. Maternal and reproductive health [Internet]. [cited 2025 Apr 15]. Available from: https://www.who.int/data/gho/data/themes/topics/sdg-target-3-1-maternal-mortality Sustainable Development Goal 3: Good Health and Well-being | United Nations in Nigeria [Internet]. [cited 2024 Nov 20]. Available from: https://nigeria.un.org/en/sdgs/3 UNICEF DATA [Internet]. [cited 2024 Nov 19]. Maternal mortality rates and statistics. Available from: https://data.unicef.org/topic/maternal-health/maternal-mortality/ Npc NPC, ICF. Nigeria Demographic and Health Survey 2018 - Final Report. 2019 Oct 1 [cited 2024 Aug 9]; Available from: https://dhsprogram.com/publications/publication-fr359-dhs-final-reports.cfm Kitila SB, Feyissa GT, Wordofa MA. Completion of the Maternal Health Care Continuum—Barriers and Facilitators Among Pregnant Women in Jimma Zone, Southwest Ethiopia: A Prospective Study. Health Serv Insights. 2023 Nov 30;16:11786329231214607. Merid MW, Chilot D, Yigzaw ZA, Melesse AW, Ferede MG, Aragaw FM, et al. Women in low- and middle-income countries receive antenatal care at health institutions, yet not delivered there: a multilevel analysis of 2016–2021 DHS data. Trop Med Health. 2024 Jan 2;52(1):1. Muluneh AG, Kassa GM, Alemayehu GA, Merid MW. High dropout rate from maternity continuum of care after antenatal care booking and its associated factors among reproductive age women in Ethiopia, Evidence from Demographic and Health Survey 2016. PloS one. 2020;15(6):e0234741. Akinyemi JO, Afolabi RF, Awolude OA. Patterns and determinants of dropout from maternity care continuum in Nigeria. BMC Pregnancy Childbirth. 2016 Dec;16(1):282. Cheng H, Luo W, Si S, Xin X, Peng Z, Zhou H, et al. Global trends in total fertility rate and its relation to national wealth, life expectancy and female education. BMC Public Health. 2022 Dec;22(1):1346. Grenier L, Suhowatsky S, Kabue MM, Noguchi LM, Mohan D, Karnad SR, et al. Impact of group antenatal care (G-ANC) versus individual antenatal care (ANC) on quality of care, ANC attendance and facility-based delivery: a pragmatic cluster-randomized controlled trial in Kenya and Nigeria. PLoS One. 2019;14(10):e0222177. Imo CK. Influence of women’s decision-making autonomy on antenatal care utilisation and institutional delivery services in Nigeria: evidence from the Nigeria Demographic and Health Survey 2018. BMC Pregnancy Childbirth. 2022 Dec;22(1):141. Kebede AS, Wana GW, Tirore LL, Boltena MT. Determinants of dropout from the maternal continuum of care in Ethiopia, multilevel analysis of the 2016 demographic and health survey. PLOS Global Public Health. 2024;4(9):e0003641. Oyedele OK. Disparities and barriers of health facility delivery following optimal and suboptimal pregnancy care in Nigeria: evidence of home births from cross-sectional surveys. BMC Womens Health. 2023 Apr 25;23:194. Shah R, Rehfuess EA, Paudel D, Maskey MK, Delius M. Barriers and facilitators to institutional delivery in rural areas of Chitwan district, Nepal: a qualitative study. Reprod Health. 2018 Jun 20;15:110. Yihune Teshale M, Bante A, Gedefaw Belete A, Crutzen R, Spigt M, Stutterheim SE. Barriers and facilitators to maternal healthcare in East Africa: a systematic review and qualitative synthesis of perspectives from women, their families, healthcare providers, and key stakeholders. BMC Pregnancy Childbirth. 2025 Feb 3;25:111. Adde KS, Dickson KS, Amu H. Prevalence and determinants of the place of delivery among reproductive age women in sub–Saharan Africa. Plos one. 2020;15(12):e0244875. Bolarinwa OA, Fortune E, Aboagye RG, Seidu AA, Olagunju OS, Nwagbara UI, et al. Health facility delivery among women of reproductive age in Nigeria: Does age at first birth matter? PLoS One. 2021 Nov 4;16(11):e0259250. Umar N, Wickremasinghe D, Hill Z, Usman UA, Marchant T. Understanding mistreatment during institutional delivery in Northeast Nigeria: a mixed-method study. Reprod Health. 2019 Dec;16(1):174. Abubakar I, Dalglish SL, Angell B, Sanuade O, Abimbola S, Adamu AL, et al. The Lancet Nigeria Commission: investing in health and the future of the nation. The Lancet. 2022;399(10330):1155–200. Adejoorin MV, Salman KK, Adenegan KO, Obi-Egbedi O, Dairo MD, Omotayo AO. Utilization of maternal health facilities and rural women’s well-being: towards the attainment of sustainable development goals. Health Econ Rev. 2024 Jun 13;14:40. Omam LA, O’Laughlin K, Tendongfor N, Wudiri Z, Hassan MN, Metuge A, et al. Exploring factors influencing the selection of primary health care delivery models in conflict-affected settings of North West and South West regions of Cameroon and North-East Nigeria: A study protocol. Plos one. 2023;18(5):e0284957. Ramadan M, Tappis H, Uribe MV, Brieger W. Access to primary healthcare Services in Conflict-Affected Fragile States: a subnational descriptive analysis of educational and wealth disparities in Cameroon, Democratic Republic of Congo, Mali, and Nigeria. Int J Equity Health. 2021 Dec;20(1):253. Adewuyi EO, Auta A, Adewuyi MI, Phili AA, Olutuase V, Zhao Y, et al. Antenatal care utilisation in Nigeria: assessing disparities between rural and urban areas—analysis of the 2018 Nigeria demographic and health survey [Internet]. medRxiv; 2024 [cited 2025 Apr 15]. p. 2024.01.24.24301729. Available from: https://www.medrxiv.org/content/10.1101/2024.01.24.24301729v1 Opara UC, Iheanacho PN, Petrucka P. Cultural and religious structures influencing the use of maternal health services in Nigeria: a focused ethnographic research. Reprod Health. 2024 Dec 18;21(1):188. Amwonya D, Kigosa N, Kizza J. Female education and maternal health care utilization: evidence from Uganda. Reprod Health. 2022 Dec;19(1):142. Bintabara D, Mwampagatwa I. Socioeconomic inequalities in maternal healthcare utilization: An analysis of the interaction between wealth status and education, a population-based surveys in Tanzania. PLOS Global Public Health. 2023;3(6):e0002006. Olorunsaiye CZ, Degge HM, Lengmang SJ. Age-specific factors related to institutional delivery in Nigeria: Insights from the 2011 Multiple Indicator Cluster Survey. Women & Health. 2018 Oct 21;58(9):1001–16. Raru TB, Ayana GM, Zakaria HF, Merga BT. Association of Higher Educational Attainment on Antenatal Care Utilization Among Pregnant Women in East Africa Using Demographic and Health Surveys (DHS) from 2010 to 2018: A Multilevel Analysis. Int J Womens Health. 2022 Feb 1;14:67–77. Hassan MM, Ali AN, Ali I, Mohamed ZO, Abdullahi HM, Ahmed MM, et al. Regulation of health professions education and the growth of schools in Somalia. BMC Med Educ. 2024 Oct 19;24(1):1178. Aikpitanyi J, Okonofua F, Ntoimo LF, Tubeuf S. Demand-side barriers to access and utilization of skilled birth care in low and lower-middle-income countries: A scoping review of evidence. African Journal of Reproductive Health. 2022;26(9):31–47. Chowdhury SSA, Kundu S, Sharif AB. Socioeconomic and geographical inequalities in using skilled birth attendants during delivery in Bangladesh over two decades. BMC Pregnancy Childbirth. 2023 Jun 9;23(1):430. Kpodotsi A, Baku EA, Adams JH, Alaba O. Socioeconomic inequalities in access and use of skilled birth attendants during childbirth in Ghana: a decomposition analysis. BMC Pregnancy Childbirth. 2021 Dec 31;21(1):850. Ogbuabor DC, Onwujekwe OE. Implementation of free maternal and child healthcare policies: assessment of influence of context and institutional capacity of health facilities in South-east Nigeria. Global Health Action. 2018 Jan;11(1):1535031. Maiwada AM, Mamat NM, Rahman NAA, Rahman SA, Baba TM. Islamic Perspectives of Reproductive and Maternal Health: What Role Can Nigerian Muslim Religious Leaders Play in the Prevention of Maternal Mortality?–With Particular Reference to Zamfara State NorthWest Nigeria. IIUM Medical Journal Malaysia [Internet]. 2018 [cited 2024 Jul 27];17(1). Available from: https://journals.iium.edu.my/kom-o/index.php/imjm/article/view/1026 Okonofua FE, Ntoimo LFC, Adejumo OA, Imongan W, Ogu RN, Anjorin SO. Assessment of Interventions in Primary Health Care for Improved Maternal, New-born and Child Health in Sub-Saharan Africa: A Systematic Review. Sage Open. 2022 Oct;12(4):21582440221134222. Arum I, Eze NS. Women and the Informal Sector of Nigerian Economy. Redeemer’s University Journal of Management and Social Sciences [Internet]. 2022 [cited 2025 Apr 15];5(1). Available from: https://runjmss.com/index.php/runojs/article/view/43 EZEUDU TS, FADEYI TJ. Examining the influence of infrastructure deficit on economic activities, education, and healthcare in rural areas of Nigeria. Nnamdi Azikiwe Journal of Political Science. 2024;9(1):155–76. Tanou M, Kishida T, Kamiya Y. The effects of geographical accessibility to health facilities on antenatal care and delivery services utilization in Benin: a cross-sectional study. Reproductive Health. 2021 Oct 14;18:205. Mseke EP, Jessup B, Barnett T. Impact of distance and/or travel time on healthcare service access in rural and remote areas: A scoping review. Journal of Transport & Health. 2024 Jul 1;37:101819. Aderoba AK, Adu-Bonsaffoh K. Antenatal and postnatal care. Obstetrics and Gynecology Clinics. 2022;49(4):665–92. Banke-Thomas A, Olubodun T, Olaniran AA, Wong KL, Shah Y, Achugo DC, et al. Optimising availability and geographical accessibility to emergency obstetric care within a sub-national social health insurance scheme in Nigeria. Frontiers in Health Services. 2024;4:1460580. Additional Declarations No competing interests reported. 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. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6455632","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":456437424,"identity":"ee1e5d37-4d0b-4c7b-9eb0-b9baa9079b7e","order_by":0,"name":"Jamilu Sani","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+0lEQVRIiWNgGAWjYBACxgYGhgMPIMzGBxUMBwyALAPCWhIgzGaDM8RoAQOIFgY2CaK0MLefTjyQ2MZgzz+7ua3iYNsdYwb25m0SjDtqcTusJ3cDSEvijDsH224cbHtmxsBzrEyC8cxxPH6BaElguJHYdvtj22EbBokcMwnGtmO4tfS/BWuxlwdqKTgI0iL/hoCWGRBbGDcAtTAAtZgxSPCAtNTg0QK0JeGcROLGG4nNEgfOPTNm40krtkhsO4BTi2F/7uYPH8ps7OVupD/8cKDsjmE/++GNNz621eHW0gCmJBAibCAigeEwTi3yuCRw2zIKRsEoGAUjDgAAbZhgzBnC9HUAAAAASUVORK5CYII=","orcid":"","institution":"Federal University Birnin Kebbi","correspondingAuthor":true,"prefix":"","firstName":"Jamilu","middleName":"","lastName":"Sani","suffix":""},{"id":456437425,"identity":"83e6351e-803c-4573-8ee2-0ff588ad39bb","order_by":1,"name":"Abubakar Yakubu Abbani","email":"","orcid":"","institution":"Federal University Birnin Kebbi","correspondingAuthor":false,"prefix":"","firstName":"Abubakar","middleName":"Yakubu","lastName":"Abbani","suffix":""},{"id":456437426,"identity":"d5d81419-9e78-42e5-93ad-7af64d89b1eb","order_by":2,"name":"Muazu Alhaji Shamaki","email":"","orcid":"","institution":"Usmanu Danfodiyo University","correspondingAuthor":false,"prefix":"","firstName":"Muazu","middleName":"Alhaji","lastName":"Shamaki","suffix":""},{"id":456437427,"identity":"ba4453ac-6ea0-43cd-8309-cd037d40735a","order_by":3,"name":"Umar Idris Boku","email":"","orcid":"","institution":"Federal University Birnin Kebbi","correspondingAuthor":false,"prefix":"","firstName":"Umar","middleName":"Idris","lastName":"Boku","suffix":""},{"id":456437428,"identity":"85ff652f-af06-443e-99bb-60d2a9b5b3ee","order_by":4,"name":"Mustapha Usman Giro","email":"","orcid":"","institution":"Federal University Birnin Kebbi","correspondingAuthor":false,"prefix":"","firstName":"Mustapha","middleName":"Usman","lastName":"Giro","suffix":""},{"id":456437429,"identity":"08b1aabf-5811-4712-a4c6-aedb6e3b8b51","order_by":5,"name":"Rasheed Adebayo Yinusa","email":"","orcid":"","institution":"Federal University Birnin Kebbi","correspondingAuthor":false,"prefix":"","firstName":"Rasheed","middleName":"Adebayo","lastName":"Yinusa","suffix":""},{"id":456437430,"identity":"e15b591f-d4b6-4fa7-9ab0-de17c53477a5","order_by":6,"name":"Yetunde A. Arigbede","email":"","orcid":"","institution":"Ahmadu Bello University","correspondingAuthor":false,"prefix":"","firstName":"Yetunde","middleName":"A.","lastName":"Arigbede","suffix":""},{"id":456437431,"identity":"d96fd1f2-3938-401b-a193-61a6ae69b33b","order_by":7,"name":"Anas Fagge Usman","email":"","orcid":"","institution":"Sa'adatu Rimi College of Education","correspondingAuthor":false,"prefix":"","firstName":"Anas","middleName":"Fagge","lastName":"Usman","suffix":""},{"id":456437432,"identity":"43b6da77-9b93-48ef-a7eb-3353564511e0","order_by":8,"name":"Lawal Badru","email":"","orcid":"","institution":"Federal Teaching Hospital Birnin-Kebbi","correspondingAuthor":false,"prefix":"","firstName":"Lawal","middleName":"","lastName":"Badru","suffix":""},{"id":456437433,"identity":"d4bf186b-782b-4a86-a23b-967c76931bd5","order_by":9,"name":"Rafiu Olalekan Yusuf","email":"","orcid":"","institution":"Ahmadu Bello University","correspondingAuthor":false,"prefix":"","firstName":"Rafiu","middleName":"Olalekan","lastName":"Yusuf","suffix":""}],"badges":[],"createdAt":"2025-04-15 14:08:19","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6455632/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6455632/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":82900701,"identity":"553c33da-e5be-4d37-b329-c834e0d00f69","added_by":"auto","created_at":"2025-05-16 13:23:51","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":22304,"visible":true,"origin":"","legend":"\u003cp\u003ePrevalence of Institutional Deliveries\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6455632/v1/7eadad4946f1db73b357d9ce.jpg"},{"id":82900697,"identity":"03562e5b-bc23-4719-a092-b056e143e936","added_by":"auto","created_at":"2025-05-16 13:23:50","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":38727,"visible":true,"origin":"","legend":"\u003cp\u003eRegional Distribution of Institutional Deliveries (Yes/No)\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6455632/v1/b9c5b1f9e7a581bfe50f6d42.jpg"},{"id":82900700,"identity":"11927aff-f164-433c-84a2-a9d862aedc69","added_by":"auto","created_at":"2025-05-16 13:23:51","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":63720,"visible":true,"origin":"","legend":"\u003cp\u003eRegional Disparities of IDD across Regions of Nigeria\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6455632/v1/4cd3c13d2c43b4eed19fea2f.jpg"},{"id":101388614,"identity":"e07d58a1-24eb-42d8-86d6-894a84e2adcd","added_by":"auto","created_at":"2026-01-29 07:53:21","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1491749,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6455632/v1/78a9c1a8-55a5-4dcf-9413-d1e551078b42.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Regional Disparities and Sociodemographic Determinants of Institutional Delivery Dropout (IDD) among Women in Nigeria: Analysis of the 2018 Demographic and Health Survey","fulltext":[{"header":"Background","content":"\u003cp\u003eInstitutional delivery, defined as childbirth assisted by skilled health professionals within a health facility, is a critical intervention for reducing maternal and neonatal morbidity and mortality (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Globally, it has been recognized as an essential component of the continuum of care for maternal health, and its importance is underscored in efforts to achieve Sustainable Development Goal (SDG) 3, which aims to reduce the global maternal mortality ratio to less than 70 per 100,000 live births by 2030 (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDespite global progress, sub-Saharan Africa continues to bear a disproportionate burden of maternal deaths, accounting for approximately 70% of all maternal deaths worldwide (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Nigeria alone contributes nearly 20% of the global maternal mortality burden, with an estimated maternal mortality ratio of 512 per 100,000 live births as of the 2018 Nigeria Demographic and Health Survey (NDHS) (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). One of the major contributing factors to this high mortality is the low utilization of institutional delivery services, even among women who attend antenatal care (ANC) services. This phenomenon, which is commonly referred to as institutional delivery dropout (IDD), represents a critical gap in the maternal health service continuum and undermines the effectiveness of ANC in preventing adverse pregnancy outcomes (\u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIDD reflects a missed opportunity for skilled attendance at birth, despite initial contact with the healthcare system through ANC. Numerous studies have shown that while ANC coverage is relatively high in Nigeria, a significant proportion of women who attend ANC ultimately deliver at home or in other non-institutional settings (\u003cspan additionalcitationids=\"CR11 CR12\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). This dropout pattern is concerning, as it suggests that barriers persist between ANC and delivery care. These barriers may include sociocultural norms, cost of delivery services, transportation challenges, perceived or experienced poor quality of care, and lack of autonomy in decision-making (\u003cspan additionalcitationids=\"CR15 CR16\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eEvidence indicates that IDD is not evenly distributed across populations and regions. Sociodemographic factors such as maternal education, age, parity, household wealth, religious beliefs, and geographic location are known to influence the likelihood of delivering in a health facility (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). In Nigeria, significant regional disparities exist in maternal health service utilization, reflecting differences in socioeconomic development, cultural practices, and health system infrastructure (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). Understanding the extent and drivers of institutional delivery dropout within the Nigerian context is essential for designing effective interventions aimed at improving maternal and neonatal outcomes (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThis study, therefore, seeks to examine the prevalence and regional disparities of institutional delivery dropout in Nigeria and to identify the sociodemographic factors associated with this phenomenon. By using nationally representative data from the 2018 NDHS, this study provides empirical insights into gaps in maternal healthcare utilization and offers evidence to guide policy and programmatic strategies for improving institutional delivery rates across the country.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Design and Setting\u003c/h2\u003e \u003cp\u003eThis study employed a cross-sectional design based on secondary data from the 2018 Nigeria Demographic and Health Survey (NDHS). The NDHS is a nationally representative survey conducted by the National Population Commission (NPC) in collaboration with ICF, covering all six geopolitical zones of Nigeria: North Central, North East, North West, South East, South South, and South West. These regions vary significantly in terms of socioeconomic development, cultural practices, and health infrastructure, which can influence maternal healthcare utilization, including place of delivery.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eData Source and Sample\u003c/h3\u003e\n\u003cp\u003eData were drawn from the Individual Recode (IR) file of the 2018 NDHS, which includes comprehensive information on women's reproductive health, demographic characteristics, and healthcare utilization. The analysis focused on women aged 15\u0026ndash;49 years who reported at least one antenatal care (ANC) visit and provided information on the place of delivery for their most recent live birth within the five years preceding the survey. After applying the inclusion criteria, a weighted sample of 16,100 women was included in the analysis.\u003c/p\u003e\n\u003ch3\u003eOutcome Variable\u003c/h3\u003e\n\u003cp\u003eThe primary outcome variable in this study was \u003cem\u003einstitutional delivery dropout\u003c/em\u003e (IDD), defined as the failure to deliver in a health facility despite attending at least one antenatal care (ANC) visit. This variable was operationalized as a binary outcome to capture whether or not a woman utilized institutional delivery services following ANC attendance. Women who received at least one ANC visit but delivered outside a recognized health facility, such as at home or in other non-medical settings, were considered to have experienced institutional delivery dropout. In contrast, those who delivered in a health facility, including government hospitals, health centres, health posts, or private medical facilities, were classified as having completed the institutional delivery pathway. For analysis, institutional delivery dropout was coded as \u0026ldquo;1,\u0026rdquo; while institutional delivery was coded as \u0026ldquo;0.\u0026rdquo;\u003c/p\u003e\n\u003ch3\u003eIndependent Variables\u003c/h3\u003e\n\u003cp\u003eThe independent variables included sociodemographic and contextual factors based on previous literature and data availability. These were:\u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eAge group\u003c/b\u003e (15\u0026ndash;19, 20\u0026ndash;24, 25\u0026ndash;29, 30\u0026ndash;34, 35\u0026ndash;39, 40\u0026ndash;44, 45\u0026ndash;49 years)\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eEducational attainment\u003c/b\u003e (no education, primary, secondary, higher)\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eMarital status\u003c/b\u003e (never in union, married, living with partner, widowed, divorced/separated)\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eReligion\u003c/b\u003e (Christianity, Islam, others)\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eWealth index\u003c/b\u003e (poorest, poorer, middle, richer, richest)\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eWorking status\u003c/b\u003e (employed, not employed)\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003ePlace of residence\u003c/b\u003e (urban, rural)\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003ePerceived distance to health facility\u003c/b\u003e (a big problem, not a big problem)\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003e \u003cb\u003eRegion of residence\u003c/b\u003e (North Central, North East, North West, South East, South South, South West)\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eDescriptive statistics were used to summarize the characteristics of the study population. Categorical variables were presented as weighted frequencies and percentages. Bivariate logistic regression was performed to assess the unadjusted associations between each independent variable and institutional delivery, with crude odds ratios (CORs) and 95% confidence intervals (CIs) reported. To identify independent predictors of institutional delivery, multivariable logistic regression was conducted, adjusting for all covariates. Adjusted odds ratios (AORs) with corresponding 95% CIs were reported. A p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e \u003cp\u003eAll analyses were conducted with consideration for the complex sampling design of the NDHS. This involved applying appropriate sampling weights, clustering, and stratification using the svy command in Stata version 17. To facilitate clear data interpretation, various visualizations were employed, including pie charts and bar plots. Furthermore, a regional map was generated using Python and GeoPandas, incorporating GADM shapefiles for Nigeria. This map effectively illustrated the spatial distribution and highlighted regional disparities in institutional delivery across the country.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eEthical Considerations\u003c/h2\u003e \u003cp\u003eEthical approval for the 2018 NDHS was obtained from the National Health Research Ethics Committee of Nigeria and the Institutional Review Board of ICF. Informed consent was obtained from all participants at the time of data collection. As this study involved secondary analysis of anonymized, publicly available data, no additional ethical clearance was required.\u003c/p\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eSociodemographic Characteristics\u003c/h3\u003e\n\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e presents the sociodemographic characteristics of the 16,100 women included in the analysis. The most common age group was 25\u0026ndash;29 years (26.4%), followed by 30\u0026ndash;34 years (22.9%) and 20\u0026ndash;24 years (18.8%). Approximately 33.9% of respondents had no formal education, while 38.2% attained secondary education and 11.3% completed higher education. A large majority were currently married (90.8%) and over half (55.3%) identified as Muslim. Employment was reported by 72.4% of the women. Slightly more respondents lived in rural areas (53.4%) compared to urban areas (46.6%). The North West region contributed the largest proportion of the sample (30.0%), followed by the South West (17.5%) and North East (17.0%).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSociodemographic Characteristics (N\u0026thinsp;=\u0026thinsp;16,100)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWeighted Frequency\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePercent\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge Group\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u0026ndash;19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e802\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.98\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20\u0026ndash;24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3,019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e18.76\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25\u0026ndash;29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4,247\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26.38\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e30\u0026ndash;34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3,684\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e22.88\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e35\u0026ndash;39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,683\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16.67\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e40\u0026ndash;44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,193\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7.41\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e45\u0026ndash;49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e471\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.92\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducational Level\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo Education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5,461\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e33.92\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,674\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16.61\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecondary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6,147\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e38.18\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigher\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,818\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11.29\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMarital Status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNever in Union\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e380\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.36\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e14,615\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e90.78\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiving with Partner\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e512\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.18\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWidowed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e209\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1.30\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDivorced/Separated\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e384\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.39\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eReligion\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChristianity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7,115\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e44.19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIslam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8,910\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e55.34\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e75\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.47\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWealth Index\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoorest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,434\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e15.12\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoorer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3,102\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19.27\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMiddle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3,516\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e21.84\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRicher\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3,563\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e22.13\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRichest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3,485\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e21.65\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWorking Status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4,442\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e27.59\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e11,658\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e72.41\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eResidence\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7,507\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e46.63\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e8,593\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e53.37\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRegion\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNorth Central\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,156\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13.39\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNorth East\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,738\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNorth West\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4,825\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29.97\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSouth East\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12.48\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSouth South\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,557\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9.67\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSouth West\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,816\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17.49\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e\n\u003ch3\u003ePrevalence and Regional Disparities of Institutional Delivery Dropout\u003c/h3\u003e\n\u003cp\u003eThe overall prevalence of institutional delivery dropout (IDD), defined as not delivering in a health facility despite attending at least one ANC visit, was found to be 48% (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Notably, there was a considerable regional variation in IDD (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The North West recorded the highest proportion of women with IDD (75.9%), followed by the North East (63.8%). In contrast, the South East had the lowest dropout rate (17.1%), followed by the South West (20.7%) and North Central (35.1%) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eBivariate Associations with Institutional Delivery Dropout\u003c/h2\u003e \u003cp\u003eBivariate logistic regression results are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Increasing maternal age was associated with lower odds of IDD compared to adolescents aged 15\u0026ndash;19 years. For instance, women aged 30\u0026ndash;34 had 2.03 times the odds of institutional delivery compared to the reference group (COR\u0026thinsp;=\u0026thinsp;2.03; 95% CI: 1.69\u0026ndash;2.44), and those aged 35\u0026ndash;39 had an even higher likelihood (COR\u0026thinsp;=\u0026thinsp;2.22; 95% CI: 1.83\u0026ndash;2.68). Educational attainment was strongly associated with lower IDD. Compared to women with no education, those with primary education had nearly three times the odds of delivering in a facility (COR\u0026thinsp;=\u0026thinsp;2.91; 95% CI: 2.58\u0026ndash;3.27), while those with secondary and higher education had markedly higher odds (COR\u0026thinsp;=\u0026thinsp;6.88; 95% CI: 6.25\u0026ndash;7.58 and COR\u0026thinsp;=\u0026thinsp;23.50; 95% CI: 19.52\u0026ndash;28.28, respectively). Religion also showed significant differences; Muslim women had substantially lower odds of delivering in a health facility compared to Christians (COR\u0026thinsp;=\u0026thinsp;0.22; 95% CI: 0.20\u0026ndash;0.24). Wealth index was positively associated with institutional delivery. Compared to the poorest group, women in the richest quintile had nearly 18 times the odds of delivering in a health facility (COR\u0026thinsp;=\u0026thinsp;17.85; 95% CI: 15.24\u0026ndash;20.91).\u003c/p\u003e \u003cp\u003eResidence and distance to health facility were significant predictors. Rural women had significantly lower odds of institutional delivery than urban women (COR\u0026thinsp;=\u0026thinsp;0.30; 95% CI: 0.28\u0026ndash;0.33), and women who did not perceive distance as a major barrier had higher odds of institutional delivery (COR\u0026thinsp;=\u0026thinsp;1.33; 95% CI: 1.22\u0026ndash;1.45). Regional differences were striking. Compared to the North West, all other regions had significantly higher odds of institutional delivery. Women in the South East had the highest odds (COR\u0026thinsp;=\u0026thinsp;15.33; 95% CI: 13.28\u0026ndash;17.69), followed by those in the South West (COR\u0026thinsp;=\u0026thinsp;12.09; 95% CI: 10.28\u0026ndash;14.23), North Central (COR\u0026thinsp;=\u0026thinsp;5.84; 95% CI: 5.18\u0026ndash;6.59), and South South (COR\u0026thinsp;=\u0026thinsp;4.74; 95% CI: 4.11\u0026ndash;5.45).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBivariate analysis of factors associated with IDD\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eInstitutional Delivery\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCOR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNO - IDD (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYES (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge Group\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u0026ndash;19 (ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e494 (61.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e308 (38.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20\u0026ndash;24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,649 (54.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1,371 (45.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.33 (1.11, 1.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.003\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25\u0026ndash;29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,007 (47.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2,240 (52.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.79 (1.49, 2.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e30\u0026ndash;34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,626 (44.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2,058 (55.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.03 (1.69, 2.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e35\u0026ndash;39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,127 (41.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1,557 (58.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.22 (1.83, 2.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e40\u0026ndash;44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e572 (47.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e621 (52.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.74 (1.41, 2.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e45\u0026ndash;49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e239 (50.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e232 (49.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.55 (1.19, 2.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducational Level\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo Education (ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4,156 (76.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1,305 (23.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,397 (52.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1,277 (47.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.91 (2.58, 3.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecondary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,944 (31.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4,203 (68.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.88 (6.25, 7.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigher\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e217 (11.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1,601 (88.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23.50 (19.52, 28.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eMarital Status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNever in Union (ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e137 (35.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e243 (64.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7,159 (48.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7,457 (51.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.59 (0.47, 0.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiving with Partner\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e183 (35.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e329 (64.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.01 (0.75, 1.35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.946\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWidowed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e74 (35.69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e134 (64.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.01 (0.69, 1.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.947\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDivorced/Separated\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e162 (42.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e223 (57.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.78 (0.56, 1.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.122\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eReligion\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChristianity (ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,982 (27.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5,133 (72.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIslam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5,688 (63.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3,222 (36.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.22 (0.20, 0.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e45 (59.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30 (40.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.26 (0.16, 0.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWealth Index\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoorest (ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,961 (80.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e473 (19.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoorer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,088 (67.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1,014 (32.69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.01 (1.76, 2.30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMiddle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,777 (50.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1,738 (49.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.05 (3.56, 4.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRicher\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,231 (34.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2,332 (65.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.85 (6.84, 9.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRichest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e657 (18.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2,828 (81.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17.85 (15.24, 20.91)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDistance to Health Facility\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBig problem (Ref)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,975 (5.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1,720 (46.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot a big problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5,739 (4.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6,666 (53.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.33 (1.22\u0026ndash;1.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWorking Status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo (ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,569 (57.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1,873 (42.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5,146 (44.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6,513 (55.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.74 (1.60, 1.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eResidence\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrban (ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,433 (32.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5,075 (67.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5,282 (61.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3,311 (38.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.30 (0.28, 0.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRegion\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNorth West (ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3,663 (75.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1,161 (24.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNorth Central\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e756 (35.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1,400 (64.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.84 (5.18, 6.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNorth East\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,747 (63.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e991 (36.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.79 (1.59, 2.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSouth East\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e343 (17.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1,666 (82.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.33 (13.28, 17.69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSouth South\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e622 (39.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e934 (60.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.74 (4.11, 5.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSouth West\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e583 (20.69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2,233 (79.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.09 (10.28, 14.23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eMultivariable Predictors of Institutional Delivery Dropout\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e presents the results from multivariable logistic regression analysis. After adjusting for covariates, educational attainment remained a strong predictor of institutional delivery. Women with higher education were over five times more likely to deliver in a health facility compared to those with no education (AOR\u0026thinsp;=\u0026thinsp;5.14; 95% CI: 4.12\u0026ndash;6.41). Those with secondary (AOR\u0026thinsp;=\u0026thinsp;2.04; 95% CI: 1.79\u0026ndash;2.32) and primary education (AOR\u0026thinsp;=\u0026thinsp;1.31; 95% CI: 1.14\u0026ndash;1.50) also had significantly increased odds.\u003c/p\u003e \u003cp\u003eWealth status continued to be positively associated with institutional delivery. The odds of delivering in a health facility increased progressively across wealth quintiles, reaching an AOR of 4.65 (95% CI: 3.80\u0026ndash;5.69) among the richest.\u003c/p\u003e \u003cp\u003eMuslim women remained significantly less likely than Christians to use health facilities for delivery (AOR\u0026thinsp;=\u0026thinsp;0.60; 95% CI: 0.53\u0026ndash;0.69). Women residing in rural areas had lower odds of institutional delivery compared to those in urban areas (AOR\u0026thinsp;=\u0026thinsp;0.88; 95% CI: 0.80\u0026ndash;0.98). Reporting distance to health facility as not being a major problem was associated with increased institutional delivery (AOR\u0026thinsp;=\u0026thinsp;1.16; 95% CI: 1.05\u0026ndash;1.29).\u003c/p\u003e \u003cp\u003eRegional disparities persisted after adjustment. Compared to the North West, women in the South East had significantly higher odds of institutional delivery (AOR\u0026thinsp;=\u0026thinsp;5.22; 95% CI: 4.30\u0026ndash;6.33), followed by the South West (AOR\u0026thinsp;=\u0026thinsp;4.17; 95% CI: 3.44\u0026ndash;5.06), North Central (AOR\u0026thinsp;=\u0026thinsp;3.83; 95% CI: 3.31\u0026ndash;4.43), North East (AOR\u0026thinsp;=\u0026thinsp;2.04; 95% CI: 1.80\u0026ndash;2.33), and South South (AOR\u0026thinsp;=\u0026thinsp;1.33; 95% CI: 1.09\u0026ndash;1.62).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMultivariable analysis of factors associated with IDD\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCategory\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eInstitutional Delivery\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAOR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNO - IDD (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYES (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge Group\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u0026ndash;19 (ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e494 (61.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e308 (38.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20\u0026ndash;24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,649 (54.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1,371 (45.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.85 (0.67\u0026ndash;1.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25\u0026ndash;29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,007 (47.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2,240 (52.74)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.80 (0.64\u0026ndash;0.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.044\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e30\u0026ndash;34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,626 (44.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2,058 (55.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.82 (0.66\u0026ndash;1.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.092\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e35\u0026ndash;39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,127 (41.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1,557 (58.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.92 (0.73\u0026ndash;1.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.491\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e40\u0026ndash;44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e572 (47.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e621 (52.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.89 (0.68\u0026ndash;1.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.421\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e45\u0026ndash;49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e239 (50.82)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e232 (49.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.10 (0.81\u0026ndash;1.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducational Level\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo Education (ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e4,156 (76.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1,305 (23.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,397 (52.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1,277 (47.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.31 (1.14\u0026ndash;1.50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecondary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,944 (31.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4,203 (68.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.04 (1.79\u0026ndash;2.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigher\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e217 (11.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1,601 (88.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.14 (4.12\u0026ndash;6.41)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eReligion\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChristianity (ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,982 (27.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5,133 (72.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIslam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5,688 (63.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3,222 (36.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.60 (0.53\u0026ndash;0.69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e45 (59.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30 (40.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.68 (0.41\u0026ndash;1.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.119\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWealth Index\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoorest (ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,961 (80.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e473 (19.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoorer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,088 (67.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1,014 (32.69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.63 (1.41\u0026ndash;1.89)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMiddle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,777 (50.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1,738 (49.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.32 (1.99\u0026ndash;2.69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRicher\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,231 (34.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2,332 (65.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.14 (2.66\u0026ndash;3.71)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRichest\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e657 (18.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2,828 (81.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.65 (3.80\u0026ndash;5.69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDistance to Health Facility\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBig problem (Ref)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,975 (5.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1,720 (46.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNot a big problem\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5,739 (4.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6,666 (53.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.16 (1.05\u0026ndash;1.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWorking Status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo (ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,569 (57.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1,873 (42.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5,146 (44.14)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6,513 (55.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.05 (0.95\u0026ndash;1.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.376\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eResidence\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrban (ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e2,433 (32.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5,075 (67.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5,282 (61.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3,311 (38.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.88 (0.80\u0026ndash;0.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.015\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRegion\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNorth West (ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e3,663 (75.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1,161 (24.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNorth Central\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e756 (35.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1,400 (64.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.83 (3.31\u0026ndash;4.43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNorth East\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1,747 (63.81)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e991 (36.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.04 (1.80\u0026ndash;2.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSouth East\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e343 (17.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1,666 (82.93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.22 (4.30\u0026ndash;6.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSouth South\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e622 (39.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e934 (60.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.33 (1.09\u0026ndash;1.62)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSouth West\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e583 (20.69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2,233 (79.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.17 (3.44\u0026ndash;5.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.000\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThis study investigated the prevalence and determinants of institutional delivery dropout (IDD) among women of reproductive age in Nigeria using nationally representative data from the 2018 NDHS. The findings reveal a substantial level of dropout from institutional delivery despite antenatal care (ANC) attendance, with nearly half (48%) of the women delivering outside health facilities. This pattern underscores a critical discontinuity in the maternal healthcare continuum, suggesting that ANC attendance does not necessarily translate into health facility delivery.\u003c/p\u003e \u003cp\u003eThe regional disparities in IDD were pronounced. The North West and North East regions recorded the highest dropout rates, whereas the South East and South West had the lowest. These differences likely reflect variations in sociocultural norms, healthcare infrastructure, security, and accessibility (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). The lower IDD rates in the southern regions may be attributed to better maternal health infrastructure and higher female educational attainment (\u003cspan additionalcitationids=\"CR23\" citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). In contrast, the northern regions are often characterized by deeply rooted cultural practices favoring home births, limited autonomy for women in healthcare decision-making, and high poverty levels, which may hinder access to facility-based care (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eEducational attainment emerged as one of the most significant predictors of institutional delivery. Women with higher education were over five times more likely to deliver in health facilities compared to those with no formal education. This finding is consistent with previous studies in Nigeria and other low- and middle-income countries, where maternal education is strongly associated with increased health literacy, financial autonomy, and favorable attitudes toward skilled birth attendance (\u003cspan additionalcitationids=\"CR28 CR29\" citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). Education also facilitates better communication with health workers and greater confidence in navigating the healthcare system (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eEconomic status was another important determinant. A strong wealth gradient was observed, with women in the richest quintile having nearly five times the odds of institutional delivery compared to the poorest group. This is aligned with evidence that financial constraints, including transportation costs and informal payments, remain significant barriers to accessing skilled birth services (\u003cspan additionalcitationids=\"CR33\" citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e). Despite Nigeria\u0026rsquo;s free maternal health policies in some states, out-of-pocket expenses and indirect costs often deter facility use, especially among the poor (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eReligious affiliation was also associated with IDD. Muslim women had significantly lower odds of institutional delivery than their Christian counterparts. This may reflect both regional concentrations, given that Muslims predominantly reside in northern Nigeria where IDD rates are highest, and also specific cultural or gender norms that influence care-seeking behaviors (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e). Targeted community engagement and culturally appropriate health promotion strategies are essential to address such disparities (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eContrary to expectations, employment status did not show a significant association with institutional delivery in the multivariable model. While employment may enhance women's financial capacity, it does not automatically translate to healthcare utilization if systemic or sociocultural barriers persist. Moreover, informal employment, which is prevalent among women in Nigeria, may not provide sufficient income or time flexibility to support facility-based delivery (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eResidence remained an independent predictor, with rural women less likely to deliver in health facilities than urban women. Rural areas often face infrastructural deficits, including long distances to health facilities, poor transportation networks, and inadequate availability of skilled personnel (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e). Although women who did not perceive distance as a problem were more likely to deliver in a facility, geographic access alone does not guarantee utilization if other barriers, such as cost or provider attitudes, are present (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe persistence of regional variation even after adjusting for sociodemographic factors suggests that contextual and health system-level influences play a significant role in shaping maternal health behaviors. These may include differences in state-level policies, health workforce density, quality of care, and availability of emergency obstetric services (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e).\u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eThis study highlights a substantial burden of institutional delivery dropout in Nigeria, with nearly half of women who attend antenatal care failing to deliver in health facilities. Sociodemographic inequalities, including education, wealth, religion, and rural residence, as well as marked regional disparities, significantly influence this gap in the maternal health continuum. The persistence of dropout, especially in northern regions, reflects structural, cultural, and health system barriers to facility-based childbirth. Addressing these challenges requires more than improving ANC coverage; targeted, context-specific interventions that promote equitable access to quality delivery services are essential. Strengthening community engagement, enhancing health infrastructure, and implementing financial and geographic access strategies are critical steps toward achieving improved maternal health outcomes and reducing preventable maternal mortality in Nigeria.\u003c/p\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eStrengths and Limitations\u003c/h2\u003e \u003cp\u003eThis study's major strength lies in the use of a large, nationally representative dataset with rigorous sampling methods and standardized measurement protocols, allowing for generalizable findings across Nigeria. Furthermore, the analytical approach accounted for complex survey design and adjusted for multiple covariates, enhancing the validity of the associations observed.\u003c/p\u003e \u003cp\u003eHowever, some limitations must be acknowledged. First, the cross-sectional nature of the data limits causal inference. Second, the reliance on self-reported data may introduce recall or social desirability bias, especially concerning ANC visits and delivery location. Third, certain potentially important factors such as quality of ANC, availability of transportation, or spousal influence were not captured in the dataset and thus could not be assessed.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eImplications for Policy and Practice\u003c/h2\u003e \u003cp\u003eThe findings highlight the urgent need to strengthen the linkage between ANC attendance and facility-based delivery. This requires a multi-faceted strategy including health education during ANC visits, improved transportation and referral systems, financial protection mechanisms, and respectful maternity care. Special attention should be paid to northern regions and underserved rural communities where IDD is highest. Community-based interventions that engage traditional and religious leaders may be particularly effective in shifting norms and promoting institutional delivery.\u003c/p\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eEthics approval and consent to participate\u003c/h2\u003e \u003cp\u003eThis study analyzed data from the 2018 Nigeria Demographic and Health Survey (NDHS), which adhered to the ethical principles outlined in the Helsinki Declaration. Approval for the survey was granted by both the National Health Research Ethics Committee of Nigeria (NHREC) and the ICF Institutional Review Board. Prior to data collection, informed consent was obtained from all participants. As this research involved secondary data analysis, confidentiality and anonymity were strictly maintained in accordance with established ethical standards.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent for publication\u003c/strong\u003e \u003cp\u003eThe study relies exclusively on secondary data from the DHS Program, specifically the 2018 NDHS dataset. No primary data collection was conducted for this research. Therefore, traditional consent for publication does not apply as no direct involvement of individual participants occurred.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eCompeting interests\u003c/strong\u003e \u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eClinical trial number\u003c/h2\u003e \u003cp\u003eNot applicable\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eNo funding was received for this study.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eJS led the study design, data analysis, visualization, resource acquisition, data management, and manuscript drafting. AYA, MAS, YAA, and ROY supervised and critically reviewed the manuscript. AFU, UIB, MUG, RAY, and LB contributed to manuscript review and editing.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eWe thank the National Population Commission and ICF International for the 2018 NDHS data, and we appreciate the research team and participating women whose contributions were vital to this study.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe data utilized in this study are publicly available through the DHS Program and can be accessed via their official website: https://dhsprogram.com.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eTarik YD, Nigussie AA, Balcha WF, Getu AA. Factors associated with institutional delivery among mothers who gave birth within 1 year prior to the study at Gilgelbelles town, Northwest Ethiopia: a mixed-methods study. BMJ open. 2022;12(11):e061218. \u003c/li\u003e\n\u003cli\u003eWayessa ZJ, Dukale UG. Factors associated with institutional delivery among women in Bule Hora Town, Southern Ethiopia. Midwifery. 2021;97:102968. \u003c/li\u003e\n\u003cli\u003eMaternal and reproductive health [Internet]. [cited 2025 Apr 15]. Available from: https://www.who.int/data/gho/data/themes/topics/sdg-target-3-1-maternal-mortality\u003c/li\u003e\n\u003cli\u003eSustainable Development Goal 3: Good Health and Well-being | United Nations in Nigeria [Internet]. [cited 2024 Nov 20]. Available from: https://nigeria.un.org/en/sdgs/3\u003c/li\u003e\n\u003cli\u003eUNICEF DATA [Internet]. [cited 2024 Nov 19]. Maternal mortality rates and statistics. Available from: https://data.unicef.org/topic/maternal-health/maternal-mortality/\u003c/li\u003e\n\u003cli\u003eNpc NPC, ICF. Nigeria Demographic and Health Survey 2018 - Final Report. 2019 Oct 1 [cited 2024 Aug 9]; Available from: https://dhsprogram.com/publications/publication-fr359-dhs-final-reports.cfm\u003c/li\u003e\n\u003cli\u003eKitila SB, Feyissa GT, Wordofa MA. Completion of the Maternal Health Care Continuum\u0026mdash;Barriers and Facilitators Among Pregnant Women in Jimma Zone, Southwest Ethiopia: A Prospective Study. Health Serv Insights. 2023 Nov 30;16:11786329231214607. \u003c/li\u003e\n\u003cli\u003eMerid MW, Chilot D, Yigzaw ZA, Melesse AW, Ferede MG, Aragaw FM, et al. Women in low- and middle-income countries receive antenatal care at health institutions, yet not delivered there: a multilevel analysis of 2016\u0026ndash;2021 DHS data. Trop Med Health. 2024 Jan 2;52(1):1. \u003c/li\u003e\n\u003cli\u003eMuluneh AG, Kassa GM, Alemayehu GA, Merid MW. High dropout rate from maternity continuum of care after antenatal care booking and its associated factors among reproductive age women in Ethiopia, Evidence from Demographic and Health Survey 2016. PloS one. 2020;15(6):e0234741. \u003c/li\u003e\n\u003cli\u003eAkinyemi JO, Afolabi RF, Awolude OA. Patterns and determinants of dropout from maternity care continuum in Nigeria. BMC Pregnancy Childbirth. 2016 Dec;16(1):282. \u003c/li\u003e\n\u003cli\u003eCheng H, Luo W, Si S, Xin X, Peng Z, Zhou H, et al. Global trends in total fertility rate and its relation to national wealth, life expectancy and female education. BMC Public Health. 2022 Dec;22(1):1346. \u003c/li\u003e\n\u003cli\u003eGrenier L, Suhowatsky S, Kabue MM, Noguchi LM, Mohan D, Karnad SR, et al. Impact of group antenatal care (G-ANC) versus individual antenatal care (ANC) on quality of care, ANC attendance and facility-based delivery: a pragmatic cluster-randomized controlled trial in Kenya and Nigeria. PLoS One. 2019;14(10):e0222177. \u003c/li\u003e\n\u003cli\u003eImo CK. Influence of women\u0026rsquo;s decision-making autonomy on antenatal care utilisation and institutional delivery services in Nigeria: evidence from the Nigeria Demographic and Health Survey 2018. BMC Pregnancy Childbirth. 2022 Dec;22(1):141. \u003c/li\u003e\n\u003cli\u003eKebede AS, Wana GW, Tirore LL, Boltena MT. Determinants of dropout from the maternal continuum of care in Ethiopia, multilevel analysis of the 2016 demographic and health survey. PLOS Global Public Health. 2024;4(9):e0003641. \u003c/li\u003e\n\u003cli\u003eOyedele OK. Disparities and barriers of health facility delivery following optimal and suboptimal pregnancy care in Nigeria: evidence of home births from cross-sectional surveys. BMC Womens Health. 2023 Apr 25;23:194. \u003c/li\u003e\n\u003cli\u003eShah R, Rehfuess EA, Paudel D, Maskey MK, Delius M. Barriers and facilitators to institutional delivery in rural areas of Chitwan district, Nepal: a qualitative study. Reprod Health. 2018 Jun 20;15:110. \u003c/li\u003e\n\u003cli\u003eYihune Teshale M, Bante A, Gedefaw Belete A, Crutzen R, Spigt M, Stutterheim SE. Barriers and facilitators to maternal healthcare in East Africa: a systematic review and qualitative synthesis of perspectives from women, their families, healthcare providers, and key stakeholders. BMC Pregnancy Childbirth. 2025 Feb 3;25:111. \u003c/li\u003e\n\u003cli\u003eAdde KS, Dickson KS, Amu H. Prevalence and determinants of the place of delivery among reproductive age women in sub\u0026ndash;Saharan Africa. Plos one. 2020;15(12):e0244875. \u003c/li\u003e\n\u003cli\u003eBolarinwa OA, Fortune E, Aboagye RG, Seidu AA, Olagunju OS, Nwagbara UI, et al. Health facility delivery among women of reproductive age in Nigeria: Does age at first birth matter? PLoS One. 2021 Nov 4;16(11):e0259250. \u003c/li\u003e\n\u003cli\u003eUmar N, Wickremasinghe D, Hill Z, Usman UA, Marchant T. Understanding mistreatment during institutional delivery in Northeast Nigeria: a mixed-method study. Reprod Health. 2019 Dec;16(1):174. \u003c/li\u003e\n\u003cli\u003eAbubakar I, Dalglish SL, Angell B, Sanuade O, Abimbola S, Adamu AL, et al. The Lancet Nigeria Commission: investing in health and the future of the nation. The Lancet. 2022;399(10330):1155\u0026ndash;200. \u003c/li\u003e\n\u003cli\u003eAdejoorin MV, Salman KK, Adenegan KO, Obi-Egbedi O, Dairo MD, Omotayo AO. Utilization of maternal health facilities and rural women\u0026rsquo;s well-being: towards the attainment of sustainable development goals. Health Econ Rev. 2024 Jun 13;14:40. \u003c/li\u003e\n\u003cli\u003eOmam LA, O\u0026rsquo;Laughlin K, Tendongfor N, Wudiri Z, Hassan MN, Metuge A, et al. Exploring factors influencing the selection of primary health care delivery models in conflict-affected settings of North West and South West regions of Cameroon and North-East Nigeria: A study protocol. Plos one. 2023;18(5):e0284957. \u003c/li\u003e\n\u003cli\u003eRamadan M, Tappis H, Uribe MV, Brieger W. Access to primary healthcare Services in Conflict-Affected Fragile States: a subnational descriptive analysis of educational and wealth disparities in Cameroon, Democratic Republic of Congo, Mali, and Nigeria. Int J Equity Health. 2021 Dec;20(1):253. \u003c/li\u003e\n\u003cli\u003eAdewuyi EO, Auta A, Adewuyi MI, Phili AA, Olutuase V, Zhao Y, et al. Antenatal care utilisation in Nigeria: assessing disparities between rural and urban areas\u0026mdash;analysis of the 2018 Nigeria demographic and health survey [Internet]. medRxiv; 2024 [cited 2025 Apr 15]. p. 2024.01.24.24301729. Available from: https://www.medrxiv.org/content/10.1101/2024.01.24.24301729v1\u003c/li\u003e\n\u003cli\u003eOpara UC, Iheanacho PN, Petrucka P. Cultural and religious structures influencing the use of maternal health services in Nigeria: a focused ethnographic research. Reprod Health. 2024 Dec 18;21(1):188. \u003c/li\u003e\n\u003cli\u003eAmwonya D, Kigosa N, Kizza J. Female education and maternal health care utilization: evidence from Uganda. Reprod Health. 2022 Dec;19(1):142. \u003c/li\u003e\n\u003cli\u003eBintabara D, Mwampagatwa I. Socioeconomic inequalities in maternal healthcare utilization: An analysis of the interaction between wealth status and education, a population-based surveys in Tanzania. PLOS Global Public Health. 2023;3(6):e0002006. \u003c/li\u003e\n\u003cli\u003eOlorunsaiye CZ, Degge HM, Lengmang SJ. Age-specific factors related to institutional delivery in Nigeria: Insights from the 2011 Multiple Indicator Cluster Survey. Women \u0026amp; Health. 2018 Oct 21;58(9):1001\u0026ndash;16. \u003c/li\u003e\n\u003cli\u003eRaru TB, Ayana GM, Zakaria HF, Merga BT. Association of Higher Educational Attainment on Antenatal Care Utilization Among Pregnant Women in East Africa Using Demographic and Health Surveys (DHS) from 2010 to 2018: A Multilevel Analysis. Int J Womens Health. 2022 Feb 1;14:67\u0026ndash;77. \u003c/li\u003e\n\u003cli\u003eHassan MM, Ali AN, Ali I, Mohamed ZO, Abdullahi HM, Ahmed MM, et al. Regulation of health professions education and the growth of schools in Somalia. BMC Med Educ. 2024 Oct 19;24(1):1178. \u003c/li\u003e\n\u003cli\u003eAikpitanyi J, Okonofua F, Ntoimo LF, Tubeuf S. Demand-side barriers to access and utilization of skilled birth care in low and lower-middle-income countries: A scoping review of evidence. African Journal of Reproductive Health. 2022;26(9):31\u0026ndash;47. \u003c/li\u003e\n\u003cli\u003eChowdhury SSA, Kundu S, Sharif AB. Socioeconomic and geographical inequalities in using skilled birth attendants during delivery in Bangladesh over two decades. BMC Pregnancy Childbirth. 2023 Jun 9;23(1):430. \u003c/li\u003e\n\u003cli\u003eKpodotsi A, Baku EA, Adams JH, Alaba O. Socioeconomic inequalities in access and use of skilled birth attendants during childbirth in Ghana: a decomposition analysis. BMC Pregnancy Childbirth. 2021 Dec 31;21(1):850. \u003c/li\u003e\n\u003cli\u003eOgbuabor DC, Onwujekwe OE. Implementation of free maternal and child healthcare policies: assessment of influence of context and institutional capacity of health facilities in South-east Nigeria. Global Health Action. 2018 Jan;11(1):1535031. \u003c/li\u003e\n\u003cli\u003eMaiwada AM, Mamat NM, Rahman NAA, Rahman SA, Baba TM. Islamic Perspectives of Reproductive and Maternal Health: What Role Can Nigerian Muslim Religious Leaders Play in the Prevention of Maternal Mortality?\u0026ndash;With Particular Reference to Zamfara State NorthWest Nigeria. IIUM Medical Journal Malaysia [Internet]. 2018 [cited 2024 Jul 27];17(1). Available from: https://journals.iium.edu.my/kom-o/index.php/imjm/article/view/1026\u003c/li\u003e\n\u003cli\u003eOkonofua FE, Ntoimo LFC, Adejumo OA, Imongan W, Ogu RN, Anjorin SO. Assessment of Interventions in Primary Health Care for Improved Maternal, New-born and Child Health in Sub-Saharan Africa: A Systematic Review. Sage Open. 2022 Oct;12(4):21582440221134222. \u003c/li\u003e\n\u003cli\u003eArum I, Eze NS. Women and the Informal Sector of Nigerian Economy. Redeemer\u0026rsquo;s University Journal of Management and Social Sciences [Internet]. 2022 [cited 2025 Apr 15];5(1). Available from: https://runjmss.com/index.php/runojs/article/view/43\u003c/li\u003e\n\u003cli\u003eEZEUDU TS, FADEYI TJ. Examining the influence of infrastructure deficit on economic activities, education, and healthcare in rural areas of Nigeria. Nnamdi Azikiwe Journal of Political Science. 2024;9(1):155\u0026ndash;76. \u003c/li\u003e\n\u003cli\u003eTanou M, Kishida T, Kamiya Y. The effects of geographical accessibility to health facilities on antenatal care and delivery services utilization in Benin: a cross-sectional study. Reproductive Health. 2021 Oct 14;18:205. \u003c/li\u003e\n\u003cli\u003eMseke EP, Jessup B, Barnett T. Impact of distance and/or travel time on healthcare service access in rural and remote areas: A scoping review. Journal of Transport \u0026amp; Health. 2024 Jul 1;37:101819. \u003c/li\u003e\n\u003cli\u003eAderoba AK, Adu-Bonsaffoh K. Antenatal and postnatal care. Obstetrics and Gynecology Clinics. 2022;49(4):665\u0026ndash;92. \u003c/li\u003e\n\u003cli\u003eBanke-Thomas A, Olubodun T, Olaniran AA, Wong KL, Shah Y, Achugo DC, et al. Optimising availability and geographical accessibility to emergency obstetric care within a sub-national social health insurance scheme in Nigeria. Frontiers in Health Services. 2024;4:1460580. \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Institutional delivery dropout (IDD), Antenatal care (ANC), Maternal health, Health facility delivery, Nigeria, NDHS, Regional disparities, Sociodemographic factors, Healthcare utilization","lastPublishedDoi":"10.21203/rs.3.rs-6455632/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6455632/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eInstitutional delivery is a critical component of maternal healthcare that reduces the risk of maternal and neonatal morbidity and mortality. While antenatal care (ANC) coverage has improved in Nigeria, a significant number of women who attend ANC still deliver outside health facilities\u0026mdash;a phenomenon referred to as institutional delivery dropout (IDD). This study examined the prevalence, regional disparities, and sociodemographic determinants of IDD among women of reproductive age in Nigeria.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis cross-sectional study utilized data from the 2018 Nigeria Demographic and Health Survey (NDHS). The analysis included 16,100 women aged 15\u0026ndash;49 years who reported at least one ANC visit and provided information on the place of delivery for their most recent birth. Descriptive statistics, bivariate analysis using crude odds ratios (COR), and multivariable logistic regression were conducted to assess predictors of institutional delivery. All analyses accounted for the complex survey design and applied sampling weights.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe prevalence of IDD in Nigeria was 48%. Marked regional disparities were observed, with the highest dropout in the North West (75.9%) and the lowest in the South East (17.1%). In bivariate analysis, maternal education, wealth index, religion, residence, and region were significantly associated with institutional delivery. Multivariable analysis confirmed that higher education (AOR\u0026thinsp;=\u0026thinsp;5.14; 95% CI: 4.12\u0026ndash;6.41), higher wealth (AOR\u0026thinsp;=\u0026thinsp;4.65; 95% CI: 3.80\u0026ndash;5.69), Christian religion (AOR\u0026thinsp;=\u0026thinsp;0.60; 95% CI: 0.53\u0026ndash;0.69), urban residence (AOR\u0026thinsp;=\u0026thinsp;1.14; 95% CI: 1.02\u0026ndash;1.25), and southern regional residence were associated with increased likelihood of institutional delivery.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eNearly half of Nigerian women who attend ANC still deliver outside health facilities, reflecting a serious breakdown in the maternal healthcare continuum. Sociodemographic inequalities and regional disparities play a substantial role in institutional delivery decisions. Addressing IDD requires targeted interventions that improve health facility access, enhance service quality, and challenge sociocultural norms\u0026mdash;especially in underserved regions. These findings underscore the need for regionally targeted interventions to improve maternal health outcomes and reduce preventable maternal deaths in Nigeria.\u003c/p\u003e","manuscriptTitle":"Regional Disparities and Sociodemographic Determinants of Institutional Delivery Dropout (IDD) among Women in Nigeria: Analysis of the 2018 Demographic and Health Survey","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-16 13:23:36","doi":"10.21203/rs.3.rs-6455632/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":"d529ff80-4d8b-4b53-b268-0b4448ae403f","owner":[],"postedDate":"May 16th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-01-29T07:53:07+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-16 13:23:36","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6455632","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6455632","identity":"rs-6455632","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}