Examining the prevalence and determinants of Antenatal care utilization in Somalia: insights from the 2020 SOMALIA demographic and health survey

Examining the prevalence and determinants of Antenatal care utilization in Somalia: insights from the 2020 SOMALIA 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 Examining the prevalence and determinants of Antenatal care utilization in Somalia: insights from the 2020 SOMALIA demographic and health survey Hamda Jama Yousuf, Mohamed Hussien Egeh This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8669665/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 Globally, maternal mortality and morbidity pose the greatest challenge to human development. Almost all of maternal deaths occur in low- and middle-income countries. Maternal mortality rate declined by 45%from 380 to 210 deaths per 100,000 live births between 1990 and 2013 in the world. First, the finished Millennium Development Goal Agenda 5 targeted to reduce maternal deaths by 75%between 2000 and 2015. Next, Sustainable Development Goal 3.1 sets a specific target of MMR reduction below 70 by 2030 in the world. Most of these maternal deaths occur due to causes directly related to pregnancy. Fortunately, these maternal deaths can be prevented through the provision of antenatal care and institutional-based delivery services Method Secondary data was collected on SDHS2020.encompassing a sample of 5,235 women aged 15–49 years. Descriptive statistics and multivariate logistic regression were employed to identify significant predictors of ANC utilization. Adjusted odds ratio with 95%confidence interval was computed, and a p-value less than 0.05 was considered as a statistically significant level for identification of association. Result The findings indicate that 63.67%of women did not utilize ANC services, with key determinants including maternal age, educational level, wealth index, media exposure, and the place of delivery. Women with higher education and those from wealthier households demonstrated significantly higher rates of ANC utilization, while rural and nomadic populations faced substantial barriers due to cultural norms and limited access to healthcare facilities. Conclusion The study highlights the urgent need for targeted interventions to improve ANC utilization in Somalia, focusing on enhancing healthcare accessibility, strengthening health infrastructure, and promoting maternal education. Addressing these disparities is crucial for improving maternal and neonatal health outcomes in the region. Antenatal care DHS Sustainable Development Goals pregnant women Health service utilization public health Figures Figure 1 Background Globally, maternal mortality and morbidity encompass the greatest challenge to human development. Almost all of maternal deaths occur in low- and middle-income countries( 1 ). Maternal mortality rate declined by 45% from 380 to 210 deaths per 100,000 live births between 1990 and 2013 in the world( 2 ). One of the primary goals of the Millennium Development Goal agenda 5 was to achieve a 75% reduction in maternal deaths between 2000 and 2015( 3 ). Next, Sustainable Development Goal 3.1 sets a specific target of MMR reduction below 70 by 2030 in the world( 4 ). The majority of maternal deaths are a result of complications arising directly from pregnancy.( 5 ) Fortunately, these deaths are largely preventable through access to prenatal care and facility-based deliveries.( 6 ) Several studies have linked inadequate antenatal care (ANC) to increased maternal morbidity and mortality. Because insufficient ANC is associated with poorer pregnancy outcomes, health policymakers must gain a clearer understanding of the factors impacting the appropriate and timely use of ANC services. Utilizing ANC services during pregnancy can encourage further engagement with other crucial maternal services, such as facility-based deliveries and seeking assistance for complications during childbirth and the postpartum period. While individual research has identified numerous factors influencing ANC utilization in various settings, a comprehensive synthesis of these findings is lacking. Therefore, a literature review was necessary to consolidate the current understanding of factors affecting ANC utilization. This review aims to assess the factors that influence ANC use among pregnant women. The results of this study can be valuable in designing and implementing strategies to improve ANC utilization among pregnant women. ( 7 ) Antenatal care frequently serves as a woman's initial point of contact with the formal healthcare system, creating an opportunity for integrated care, promoting safe practices at home, improving health-seeking behaviors, and connecting women experiencing complications to more advanced medical facilities. ( 8 ) While the World Health Organization recommends four antenatal care visits for low-risk pregnancies, the ideal number of visits remains a subject of debate. ( 9 ) The optimal number of antenatal visits is influenced not only by their effectiveness but also by the practicality and various barriers to accessing and providing antenatal care, particularly in low-income countries. ( 10 ) In developing countries, many pregnant women delay starting antenatal care for a variety of reasons. ( 11 ) Maternal age and the husband's attitude towards antenatal care significantly impact a woman's use of these services. ( 12 , 13 ) Furthermore, various socio-demographic and reproductive health factors can lead to women missing opportunities for care. Limited or late-term antenatal care visits can put both mothers and their children at risk. ( 14 ) In Somalia, access to health care is severely constrained by socioeconomic challenges, cultural practices, and a fragmented health system, compounded by decades of conflict and instability. Despite global efforts to improve maternal health outcomes under the Sustainable Development Goals (SDG3), Somalia’s ANC coverage remains among the lowest worldwide. Evidence shows that 86% of pregnant women worldwide access skilled ANC at least once, and 65% have at least four visits. In sub-Saharan Africa, only 52% of pregnant mothers made at least four visits.( 15 ) The Somali Health and Demographic Survey (SHDS) 2020 revealed that only 31% of pregnant women received ANC from skilled personnel, highlighting significant gaps in service delivery and accessibility. Various factors influence ANC utilization in Somalia, including socioeconomic status, education, geographic location, and health infrastructure. Rural and nomadic populations face unique barriers, including long travel distances to healthcare facilities, high costs, and cultural norms that discourage formal healthcare use. Addressing these disparities is crucial to reducing maternal and neonatal mortality and achieving equitable healthcare access for all Somali women. This study aims to assess the prevalence of ANC utilization among pregnant women in Somalia and examine the socioeconomic, educational, and cultural factors influencing their use of ANC services, based on data from the 2020 Somalia Demographic and Health Survey. Method and material Study Setting Somalia is located in the Horn of Africa, with an estimated surface area of 637,657 km2 and a terrain consisting mainly of plateaus, plains, and highlands. It has the longest coastline in Africa, stretching over 3,333 km along the Gulf of Aden to the north and the Indian Ocean to the east and south. It borders Djibouti along the north-west, Ethiopia to the west, and Kenya to the south-west. Somalia still remains one of the poorest and least developed countries in Africa, with a Gross Domestic Product (GDP) of 4.7 million US dollars in 2018 (FGS 2020) and a per capita estimated at approximately $ 315 in 2018 (World Bank 2018). ( 16 ) Study Design The Somali Health and Demographic Survey (SHDS) was a cross-sectional, stratified cluster survey conducted from 2018 to 2019. It was the first nationally representative health and demographic survey in Somalia, designed to provide evidence-based data for monitoring and evaluating development plans, including the Sustainable Development Goals (SDGs). The survey was implemented by the Directorate of National Statistics, with technical support from UNFPA and other international partners. The survey used Geographic Information System (GIS) technology to digitize enumeration areas (EAs) and generate a sampling frame that included urban, rural, and nomadic settings. ( 16 ) Data source The 2020 SHDS datasets, which were collected between 2018 and 2020, were used in this investigation. The information was taken from ( https://microdata.nbs.gov.so/index.php/catalog/50 ), the SDHS website. Data management and analysis Data were analyzed using Stata software version 16. Data cleaning was performed missing variables were checked. Descriptive statistics, such as frequency, percentage, were computed by the use of pie charts and tables. Moreover, we have analyzed the plan file created in these three steps to identify factors associated with antenatal care utilization. A chi-square test was performed to observe any association between the dependent variable and the independent variables. First, we performed binary logistic regression analysis to identify variables associated with antenatal care utilization. In binary logistic regression analysis, we took variables with a p-value less than or equal to 0.005 into a multivariable logistic regression analysis to control for co-founders. Then, variables that had a significant association with antenatal care utilization were identified based on adjusted odds ratio (AOR) and p-value less than 0.005 in a multivariable logistic regression analysis model. Measurement of variables The study’s outcome variable was Antenatal care services utilization. it is a binary outcome variable. Those women who did not utilize antenatal care services were assigned as ‘0’, but those who utilized antenatal care services were assigned as ‘1’ during analysis. In this study, antenatal care utilization was defined as: women who visited a health facility at least once during their last pregnancy were considered as receiving antenatal care services; otherwise, not. Independent variables are categorized into two main groups, which include socioeconomic and reproductive health variables. Socio-demographic characteristics include age, region, place of residence, educational status, wealth index, marital status, family size, and Frequency of listening to the radio. Moreover, reproductive health characteristics consisted of the following variables: Age of respondent at 1st birth, Place of birth, Current pregnancy, Contraceptive use and intention, Person who usually decides on respondents’ health care, and Desire for more children (Table 1 ) Table 1 List of study variables Study variables Description and categorization Outcome variable Number of antenatal visits during pregnancy 0 = Non utilization of ANC | 1 = Utilization of ANC Independent variables Maternal age 1 = 15–19 2 = 20–24 3 = 25–29 4 = 30–34 5 = 35–39 6 = 40–44 7 = 45–49 Residence Type place of residence 1 = Rural 2 = Urban 3 = Nomadic Maternal education Highest educational level 0 = No Education 1 = Primary 2 = Secondary 3 = Higher Wealth index Wealth index combined 1 = Lowest 2 = Second 3 = Middle 4 = Fourth 5 = Highest marital status Current marital status 0 = Married 1 = Divorced 2 = Widowed Frequency of listening to the radio 1 = At least once a week 2 = Less than once a week Family size Number of household members (listed) 1 = Less than four members 2 = Four members or more Age of respondent at 1st birth 0 = < 20 1 = 20–24 2 = 25–30 3 = 30 and above Place of birth Place delivery 0 = Home 1 = Health institution Current pregnant 0 = Yes 1 = No Contraceptive use and intention 0 = Yes 1 = No Desire for more children 1 = Wants within 2 years 2 = Wants after 2 years 4 = Undecided 5 = Wants no more 6 = Declared Infecund Health care decision Person who usually decides on respondents’ health care 1 = Respondent 2 = Husband 3 = Respondent and Husband Jointly 4 = In Laws 5 = Someone else 6 = Other Region Awdal Woqooyi Galbeed Togdheer Sool Sanaag Bari Nugaal Mudug Galgaduud Hiraan Middle Shabelle Banadir Bay Bakool Gedo Lower Juba Results Table 2 summarizes the socio-demographic characteristics and their association with ANC utilization. The majority of respondents were married (91.7%) and had no formal education (83.5%). Most lived in rural areas (27.2%) or were nomadic residents (35.5%), while 37.3% resided in urban areas. Women aged 20–24 years had the highest ANC utilization (39.98%), while those aged 40–44 years exhibited the lowest (25.83%). The Gedo region had the lowest ANC utilization rate (10.89%), whereas Hiraan showed the highest (80.24%). Wealth and education were strong predictors; women in the highest wealth quintile (61.49%) and those with higher education (83.33%) were more likely to use ANC services. Conversely, the lowest wealth quintile (17.20%) and women with no formal education (30.89%) reported higher non-utilization rates. Media exposure, such as listening to the radio, also significantly influenced utilization, with regular listeners exhibiting higher rates (55.52%). These findings underscore the influence of socioeconomic, educational, and regional disparities on ANC utilization among women Table 2 demographic and socioeconomic characteristics of respondents (N = 5,235) Variables Categories Frequency (%) Anc utilization X2(p-value) Non utilization Utilization Age 15–19 312(5.96) 205(65.71) 107(34.29) 29.55(< 0.001) 20–24 1048(20.02) 629(60.02) 419(39.98) 25–29 1453(27.76) 891(61.32) 562(38.68) 30–34 1053(20.11) 676(64.20) 377(35.80) 35–39 886(16.92) 583(65.80) 303(34.20) 40–44 360(6.88) 267(74.17) 93(25.83) 45–49 123(2.35) 82(66.67) 41(33.33) Region Awdal 276(5.27) 121(43.84) 155(56.16) 342.17(< 0.001) Woqooyi Galbeed 439(8.39) 276(62.87) 163(37.13) Togdheer 439(8.39) 215(48.97) 224(51.03) Sool 472((9.02) 225(47.67) 247(52.33) Sanaag 464(8.86) 243(52.37) 221(47.63) Bari 291(5.56) 208(71.48) 83(28.52) Nugaal 3095.90) 211(68.28) 98(31.72) Mudug 316(6.04) 234(74.05) 82(25.95) Galgaduud 259(4.95) 188(72.59) 71(27.41) Hiraan 253(4.83) 203(80.24) 50(19.76) Middle Shabelle 289(5.52) 173(59.86) 116(40.14) Banadir 453(8.65) 309(68.21) 144(31.79) Bay 104(1.99) 50(48.08) 54(51.92) Bakool 309(5.90) 221(71.52) 88(28.48) Gedo 257(4.91) 229(89.11) 28(10.89) Lower Juba 305(5.83) 227(74.43) 78(25.57) Residence Rural 1423(27.18) 935(65.71) 488(34.29) 10.35(0.0057) Urban 1954(37.33) 1268(64.89) 686(35.11) Nomadic 1858(35.49) 1130(60.82) 728(39.18) Education level No Education 4370(83.48) 3020(69.11) 1350(30.89) 354.37(< 0.001) Primary 634(12.11) 251(39.59) 383(60.41) Secondary 165(3.15) 51(30.91) 114(69.09) Higher 66(1.26) 11(16.67) 55(83.33) Wealth index Lowest 1157(22.10) 958(82.80) 199(17.20) 596.82(< 0.001) Second 1100(21.01) 859(78.09) 241(21.91) Middle 1043(19.92) 634(60.79) 409(39.21) Fourth 1021(19.50) 530(51.91) 491(48.09) Highest 914(17.46) 352(38.51) 562(61.49) Current marital status Married 4801(91.71) 3044(63.40) 1757(36.60) 4.44(0.1086) Divorced 310(5.92) 199(64.19) 111(35.81) Widowed 124(2.37) 90(72.58) 34(27.42) Frequency of listening to radio At least once a week 335(6.40) 149(44.48) 186(55.52) 74.39(< 0.001) Less than once a week 139(2.66) 67(48.20) 72(51.80) Not at all 4761(90.95) 3117(65.47) 1644(34.53) Family size Less than four members 1318(25.18) 837(63.51) 481(36.49) 0.02 (0.8874) Four members or more 3917(74.82) 2496(63.72) 1421(36.28) Regarding the reproductive health characteristics of the respondents, more than half, 2,842 (54.3%), gave birth for the first time before the age of 20, while only 81 (1.6%) had their first birth at 30 years or older. Among the total respondents, 1,309 (25.0%) were currently pregnant, and 3,926 (75.0%) were not pregnant at the time of the survey. A small proportion, 494 (9.4%), reported using contraceptives, while the majority, 4,741 (90.6%), did not. In terms of the desire for more children, 3,145 (60.1%) wanted to have more children within two years, whereas 939 (17.9%) wanted no more children, and 839 (16.0%) were undecided. Additionally, 1 (0.02%) respondent declared being infecund. Decision-making on healthcare varied, with 1,021 (19.5%) respondents deciding independently, 1,704 (32.6%) jointly with their husbands, and 2,481 (47.4%) relying on their husbands to make healthcare decisions. chi-square test was conducted to examine the association between various reproductive health characteristics and antenatal care (ANC) utilization among respondents. The findings revealed several significant relationships. The place of birth (X² = 817.70, p < 0.001) was significantly associated with ANC utilization, with a higher utilization rate among women who gave birth in health institutions compared to those who delivered at home. Current pregnancy status (X² = 5.21, p = 0.0224) also showed a significant relationship, with pregnant women more likely to utilize ANC services than non-pregnant women. Contraceptive use and intention (X² = 88.16, p < 0.001) were significantly associated with ANC utilization, with women using contraceptives demonstrating higher utilization rates. Desire for more children (X² = 166.37, p < 0.001) also had a significant association; women who wanted children within two years were more likely to utilize ANC services compared to those undecided or wanting no more children. Similarly, decision-making on healthcare (X² = 28.40, p < 0.001) was significantly linked to ANC utilization, with women who made decisions jointly with their husbands or independently showing higher rates of utilization. However, the age of respondents at first birth (X² = 2.41, p = 0.4924) did not show a significant association with ANC utilization. These results highlight the importance of institutional support, reproductive intentions, and autonomy in decision-making in improving ANC utilization rates ( Table 3 ) Table 3 Reproductive health characteristics of the respondents (N = 5,235) Variables Categories Frequency (%) Anc utilization X2(p-value) Non utilization Utilization Age of respondent at 1st birth < 20 2842(54.29) 1803(63.44) 1039(36.56) 2.41(0.4924) 20–24 1804(34.46) 1161(64.36) 643(35.64) 25–30 508(9.70) 313(61.61) 195(38.39) 30 and above 81(1.55) 56(69.14) 25(30.86) Place of birth Home 3908(74.65) 2921(74.74) 987(25.26) 817.70(< 0.001) Health institution 1327(25.35) 412(31.05) 915(68.95) Current pregnant Yes 1309(25.00) 799(61.04) 510(38.96) 5.21(0.0224) No 3926(75.00) 2534(64.54) 1392(35.46) Contraceptive use and intention No 4741(90.56) 3114(65.68) 1627(34.32) 88.16(< 0.001) Yes 494(9.44) 219(44.33) 275(55.67) Desire for more children Wants within 2 years 3145(60.08) 1827(58.09) 1318(41.91) 166.37(< 0.001) Wants after 2 years 311(5.94) 165(53.05) 146(46.95) Undecided 839(16.03) 643(76.64) 196(23.36) Wants no more 939(17.94) 698(74.33) 241(25.67) Declared Infecund 1(0.02) 0(0.00) 1(100.00) Health care decion Respondent 1021(19.50) 627(61.41) 394(38.59) 28.40(< 0.001) Husband 2481(47.39) 1669(67.27) 812(32.73) Respondent and Husband Jointly 1704(32.55) 1019(59.80) 685(40.20) In Laws 8(0.15) 5(62.50) 3(37.50) Someone else 11(0.21) 8(72.73) 3(27.27) Other 10(0.19) 5(50.00) 5(50.00) Table 4 shows the multivariate logistic regression analysis of antenatal care utilization in Somalia, based on the 2020 Somalia Demographic Health Survey data (N = 5,235), which identifies several key variables with significant associations. Higher age groups, increased education levels, wealthier economic statuses, frequent radio listening, institutional births, contraceptive use, and specific childbearing intentions are all positively correlated with the utilization of antenatal care services. Conversely, residing in regions other than Awdal is associated with lower antenatal care utilization. The analysis revealed that women in the age group of 20–24 were 39.5% more likely to utilize antenatal care (AOR = 1.395, 95%CI, 1.018–1.913). Women with primary education were nearly twice as likely (AOR = 1.966, 95%CI, 1.608–2.403), and those with higher education were over two and a half times more likely (AOR = 2.486, 95%CI, 1.209–5.112) to use antenatal care compared to those with no education. Women in higher wealth quintiles had higher odds of utilizing antenatal care, with those in the fourth wealth quintile having more than two and a half times the likelihood (AOR = 2.604, 95%CI, 2.079–3.262) compared to those in the lowest quintile. Frequency of radio listening also played a role, with those who listened at least once a week being more likely to use antenatal care (AOR = 3.124, 95%CI, 2.457–3.971). Furthermore, women who gave birth in a health institution were significantly more likely to use antenatal care (AOR = 3.821, 95%CI, 3.264–4.473). Conversely, women who desired no more children had a lower likelihood of using antenatal care. These findings emphasize the importance of educational status, wealth, media exposure, and healthcare access in influencing antenatal care utilization in Somalia. Table 4 multivariate logistic regression for antenatal care utilization in Somalia using Somalia demographic health survey 2020 (N = 5,235) Variables Categories Antenatal care utilization AOR (95%CI) COR (95%CI) Age 15–19 Ref - 20–24 1.395(1.018–1.913) ** 1.276(.98-1.663) * 25–29 1.468(1.074–2.006) ** 1.208(.935-1.562) 30–34 1.287(0.93–1.78) 1.068(.819-1.393) 35–39 1.507(1.074–2.114) ** .996(.759-1.307) ** 40–44 1.252(0.829–1.889) .667(.479-.93) 45–49 2.178(1.28–3.705) *** .958(.616 − 1.49)*** Region Awdal Ref - Woqooyi Galbeed .443(0.312–0.63) *** .461(.339-.626) *** Togdheer .59(0.418–0.834) *** .813(.601-1.101) Sool .691(0.49–0.976) ** .857(.636-1.155) Sanaag .587(0.416–0.827) *** .71(.526-.958) ** Bari .413(0.28–0.61) *** .312(.22-.441) *** Nugaal .458(0.313–0.669) *** .363(.259-.508) *** Mudug .415(0.281–0.611) *** .274(.194-.387) *** Galgaduud .396(0.264–0.594) *** .295(.205-.423) *** Hiraan .245(0.158–0.38) *** .192(.13-.284) *** Middle Shabelle .496(0.338–0.727) *** .523(.375-.731) *** Banadir .363(0.25-.529) *** .364(.267-.496) *** Bay 0.8(0.475–1.345) .843(.536-1.325) Bakool .318(0.217–0.466) *** .311(.221-.438) *** Gedo .155(0.095–0.254) *** .095(.06-.151) *** Lower Juba .293(0.198–0.435) *** .268(.189-.381) *** Education level No Education Ref - Primary 1.966(1.608–2.403) *** 3.413(2.875–4.053) *** Secondary 1.917(1.3-2.827) *** 5.000(3.572–6.999) *** Higher 2.486(1.209–5.112) ** 11.185(5.836–21.437) *** Wealth index Lowest Ref - Second 1.474(1.171–1.856) *** 1.351(1.096–1.665) *** Middle 2.493(1.995–3.115) *** 3.106(2.551–2.551) *** Fourth 2.604(2.079–3.262) *** 4.46(3.666–5.425) *** Frequency of listening to radio Highest 3.124(2.457–3.971) *** 7.686(6.276–9.413) *** At least once a week Ref - Less than once a week .93(0.587–1.472) .861(.579 − 1.28) Not at all .741(0.569–0.965) ** .423((.338-.528) *** Age of respondent at 1st birth < 20 Ref - 20–24 .894(.768 − 1.04) .961(.85-1.087) 25–30 1.091(.851-1.398) 1.081(.89-1.313) 30 and above .588(.318-1.088) * .775(.481-1.249) Home Ref - Place of birth Health institution 3.821(3.264–4.473) *** 6.573(5.732–7.537) *** Contraceptive use and intention No Ref - Yes 1.37(1.094–1.714) *** 2.403(1.993–2.899*** Desire for more children Wants within 2 years .993(.755-1.307) 1.227(.971-1.549) * Wants after 2 years .527(.431-.646) *** .423(.355-.503) *** Undecided .544(.447-.662) *** .479(.407-.563) *** Wants no more *** p<.01, ** p<.05, * p<.1 Ref, reference category; RRR, relative risk ratios; CI, confidence interval. Discussion This study assessed the prevalence and determinants of antenatal care (ANC) utilization among pregnant women in Somalia using data from the 2020 Somalia Demographic and Health Survey. The result showed that ANC utilization remains low, with only 31% pregnant women receiving ANC from skilled personnel. This rate is lower than a report from the study conducted in 11 East African Countries that showed the magnitude of optimal ANC utilization was the highest optimal ANC utilization in Zimbabwe (80.96%) and the lowest optimal ANC utilization in Rwanda (44.31%)( 17 ).also study conducted in 31 sub-Saharan African countries that showed non utilization of ANC in Chad (41.8%), Ethiopia (34.8%) and Nigeria (26.1%).( 18 ) the possible explanation for this inconsistency might be due to socio-demographic characteristic of the research participants, including their economic status, the restricted availability of maternal health care, and inadequate trained health personal in Somalia( 19 ).Key determinants of ANC utilization included maternal education, wealth status, geographic location, place of birth, contraceptive use, and media exposure. Women with higher education levels and those in the wealthier quintile were significantly more likely to utilize ANC services. Additionally, listening to the radio at least once a week was associated with higher ANC utilization. Conversely, women residing in rural and nomadic areas exhibited lower ANC utilization rates. Older age groups, particularly those aged 35–39 and 45–49, exhibited higher odds of ANC utilization. This finding is in line with reports of other previous studies. This finding is supported by a systematic review conducted in sub-Saharan Africa ( 20 ), Ethiopia ( 21 ), and Uganda ( 22 ). This trend suggests that the women age, they may become more aware of the important ANC services, possibly due to increased pregnancy experience and exposure to health education programs. However, the lower utilization among younger women indicates a potential gap in targeted maternal health programs for adolescent and young mothers. We found evidence suggesting that the higher education level of women improves their utilization of ANC services. This was supported by similar findings( 23 – 25 ), higher education level empowered women with knowledge about the benefits of maternal health care services. The positive impact of education underscores the importance of strengthening female education programs to enhance maternal health outcomes.( 26 , 27 ) Women who were the richest were more likely to utilize ANC than the poorest women. This finding is consistent with a study conducted in Ethiopia( 21 ) and elsewhere.( 28 – 30 ) Access to maternal health services may be significantly hampered by household poverty. Women from low-income families could not have the necessary funds. should either pay for the services provided throughout the prenatal period or register at clinics. This may lead to a situation where such women would partially attend the clinics or not attend at all. Compared to their counterparts, media-exposed women were more likely to use ANC. This result is consistent with a population-based research that used DHS data in Nepal( 24 ), a systematic review that was carried out in developing nations( 31 ), and a systematic review and meta-analysis study that was carried out in Ethiopia( 32 ). Media like radio may encourage positive changes in behavior by regularly airing public service announcements and programs backed by the government or non-state entities that outline the advantages of using ANC and other maternal healthcare treatments on time( 33 ). There may be a connection between maternal healthcare-seeking behavior and family planning awareness, since women who used contraceptives were much more likely to utilize ANC services. Women who wanted no more children, on the other hand, had a lower likelihood of using ANC, which could be a result of less pregnancy-related worries or a lack of desire to get maternity care. ANC education should be incorporated into family planning programs to promote consistent utilization of maternal health services, irrespective of fertility goals( 34 , 35 ). Significant regional variation in ANC utilization was observed, with women residing in regions such as Gedo, Hiraan, and Mudug having significantly lower odds of using ANC compared to those in Awdal.The unequal distribution of medical facilities, restricted access to maternal health care, and potential cultural variations impacting ANC-seeking behaviors are all highlighted by these inequalities. Targeted initiatives are needed to address these gaps, such as better healthcare facilities, mobile clinics, and culturally aware health promotion tactics in underprivileged areas( 35 , 36 ). Compared to women who gave birth at home, those who gave birth in medical facilities were almost four times more likely to have used ANC services. According to this research, women who are currently interacting with healthcare systems are more likely to seek out ongoing maternity care. Increased use of ANC may be encouraged by bolstering institutional delivery services and encouraging facility-based deliveries( 37 ). Conclusion This study provides valuable insight into the prevalence and determinants of antenatal care utilization (ANC) in Somalia, using nationally representative data from the 2020 Somalia Demographic and Health Survey. The findings reveal that ANC utilization remains significantly low, with more than half of women (63.67%) not utilizing ANC services, whereas the rest (36.33%) did. Various socioeconomic, educational, and cultural factors influenced ANC utilization. Women with higher education, increased wealth status, and frequent media exposure demonstrated higher ANC utilization, whereas rural residence, nomadic lifestyles, and cultural barriers posed significant challenges. Addressing these disparities is crucial to improving maternal and neonatal health outcomes. Policymakers should prioritize interventions aimed at increasing healthcare accessibility, strengthening health infrastructure in underserved areas, and promoting maternal education. Additionally, raising awareness through mass media and community-based programs could enhance positive health-seeking behavior among pregnant women. The utilization gap might also be closed by expanding the capacity of the healthcare personnel, incorporating traditional birth attendants into official healthcare systems, and putting in place incentive-based programs for ANC visits. Expanding outreach initiatives, especially for rural and nomadic groups, can be facilitated by fortifying alliances between governmental and non-governmental organizations. Future studies should examine how digital health interventions, healthcare professional attitudes, and partner support might enhance ANC adoption. To guarantee long-lasting gains in ANC use and, eventually, lower mother and newborn morbidity and death in Somalia, a multi-sector strategy combining health, education, and social development strategies is necessary. Strengths and Limitations A key strength of this study is the use of a nationally representative dataset, ensuring generalizability to the Somali population. The study also uses statistical methods to identify key determinants of ANC care utilization. However, certain limitations must be acknowledged. The reliance on self-reported data may introduce recall bias, and the cross-sectional nature of the study limits causal inference. Additionally, culture and qualitative factors influencing ANC utilization were not extensively explored. Abbreviations ANC Antenatal Care AOR Adjusted Odds Ratio CI Confidence Interval COR Crude Odds Ratio DHS Demographic and Health Survey FGS Federal Government of Somalia GDP Gross Domestic Product GIS Geographic Information System MDG Millennium Development Goal MMR Maternal Mortality Ratio Declarations Ethical approval and consent to participate Ethical approval wasn't required for this study because we used publicly available, anonymized data from the Demographic and Health Survey (DHS). We obtained permission to download the DHS dataset from the Central Statistical Agency (CSA) through a request at https://microdata.nbs.gov.so/index.php/catalog/50 Consent for publication Not applicable Competing interests The authors declare no competing interests. Funding This research received no external funding Author Contribution All authors contributed to the research, writing, and final approval of the manuscript and are accountable for its content. All authors were involved in the study's design, data analysis, and manuscript preparation. Acknowledgements Not applicable Data Availability The Somalia Demographic and Health Survey (SDHS) 2020 datasets used in this study are publicly accessible and can be obtained through an online request at [https://microdata.nbs.gov.so/index.php/catalog/50](https:/microdata.nbs.gov.so/index.php/catalog/50) , specifying the purpose of the research. The datasets analyzed during the current study are also available from the corresponding author upon reasonable request. References Tsegaye B, Ayalew M. Prevalence and factors associated with antenatal care utilization in Ethiopia: an evidence from demographic health survey 2016. BMC Pregnancy Childbirth. 2020;20:1–9. Lawson GW, Keirse MJ. Reflections on the maternal mortality millennium goal. Birth. 2013;40(2):96–102. Afework MF. Achieving the maternal health Millennium Development Goals in ethiopia: where are we and what needs to be done? 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Factors influencing antenatal care service utilization in hadiya zone. Ethiop J health Sci. 2010;20(2). Mesganaw F, Olwit G, Shamebo D. Determinants of ANC attendance and preference of site or delivery in Addis Ababa. Ethiopia J Health Dev. 1990;6(2):17–21. Chege J, Askew I, Mosery N, Ndube-Nxumalo M, Kunene B, Beksinska M et al. Feasibility of introducing a comprehensive package of antenatal care services in rural public clinics in South Africa. 2005. Central Statistics Department MoP, National Development SG. The Somaliland Health and Demographic Survey 2020. Federal Government of Somalia and UNFPA; 2020. 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 women's health. 2022:67–77. Adedokun ST, Yaya S. 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Focused antenatal care utilization and associated factors in Debre Tabor Town, northwest Ethiopia, 2017. BMC Res Notes. 2018;11:1–6. Simkhada B, Teijlingen ERv, Porter M, Simkhada P. Factors affecting the utilization of antenatal care in developing countries: systematic review of the literature. J Adv Nurs. 2008;61(3):244–60. Yeneneh A, Alemu K, Dadi AF, Alamirrew A. Spatial distribution of antenatal care utilization and associated factors in Ethiopia: evidence from Ethiopian demographic health surveys. BMC Pregnancy Childbirth. 2018;18:1–12. Corroon M, Speizer IS, Fotso J-C, Akiode A, Saad A, Calhoun L, et al. The role of gender empowerment on reproductive health outcomes in urban Nigeria. Matern Child Health J. 2014;18:307–15. Dankwah E, Zeng W, Feng C, Kirychuk S, Farag M. The social determinants of health facility delivery in Ghana. Reproductive health. 2019;16:1–10. Fagbamigbe AF, Idemudia ES. Wealth and antenatal care utilization in Nigeria: policy implications. Health Care Women Int. 2017;38(1):17–37. Adedokun ST, Uthman OA. Women who have not utilized health Service for Delivery in Nigeria: who are they and where do they live? BMC Pregnancy Childbirth. 2019;19:1–14. Joshi C, Torvaldsen S, Hodgson R, Hayen A. Factors associated with the use and quality of antenatal care in Nepal: a population-based study using the demographic and health survey data. BMC Pregnancy Childbirth. 2014;14:1–11. Adewuyi EO, Auta A, Khanal V, Bamidele OD, Akuoko CP, Adefemi K, et al. Prevalence and factors associated with underutilization of antenatal care services in Nigeria: A comparative study of rural and urban residences based on the 2013 Nigeria demographic and health survey. PLoS ONE. 2018;13(5):e0197324. Fatema K, Lariscy JT. Mass media exposure and maternal healthcare utilization in South Asia. SSM-population Health. 2020;11:100614. Ahinkorah BO, Budu E, Aboagye RG, Agbaglo E, Arthur-Holmes F, Adu C, et al. Factors associated with modern contraceptive use among women with no fertility intention in sub-Saharan Africa: evidence from cross-sectional surveys of 29 countries. Contracept reproductive Med. 2021;6:1–13. Chikandiwa A, Burgess E, Otwombe K, Chimoyi L. Use of contraceptives, high risk births and under-five mortality in Sub Saharan Africa: evidence from Kenyan (2014) and Zimbabwean (2011) demographic health surveys. BMC Womens Health. 2018;18:1–13. Tsegay Y, Gebrehiwot T, Goicolea I, Edin K, Lemma H, Sebastian MS. Determinants of antenatal and delivery care utilization in Tigray region, Ethiopia: a cross-sectional study. Int J Equity Health. 2013;12:1–10. Yesuf EA, Calderon-Margalit R. Disparities in the use of antenatal care service in Ethiopia over a period of fifteen years. BMC Pregnancy Childbirth. 2013;13:1–10. 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. 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Almost all of maternal deaths occur in low- and middle-income countries(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). Maternal mortality rate declined by 45% from 380 to 210 deaths per 100,000 live births between 1990 and 2013 in the world(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). One of the primary goals of the Millennium Development Goal agenda 5 was to achieve a 75% reduction in maternal deaths between 2000 and 2015(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Next, Sustainable Development Goal 3.1 sets a specific target of MMR reduction below 70 by 2030 in the world(\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). The majority of maternal deaths are a result of complications arising directly from pregnancy.(\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e) Fortunately, these deaths are largely preventable through access to prenatal care and facility-based deliveries.(\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eSeveral studies have linked inadequate antenatal care (ANC) to increased maternal morbidity and mortality. Because insufficient ANC is associated with poorer pregnancy outcomes, health policymakers must gain a clearer understanding of the factors impacting the appropriate and timely use of ANC services. Utilizing ANC services during pregnancy can encourage further engagement with other crucial maternal services, such as facility-based deliveries and seeking assistance for complications during childbirth and the postpartum period. While individual research has identified numerous factors influencing ANC utilization in various settings, a comprehensive synthesis of these findings is lacking. Therefore, a literature review was necessary to consolidate the current understanding of factors affecting ANC utilization. This review aims to assess the factors that influence ANC use among pregnant women. The results of this study can be valuable in designing and implementing strategies to improve ANC utilization among pregnant women. (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eAntenatal care frequently serves as a woman's initial point of contact with the formal healthcare system, creating an opportunity for integrated care, promoting safe practices at home, improving health-seeking behaviors, and connecting women experiencing complications to more advanced medical facilities. (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e) While the World Health Organization recommends four antenatal care visits for low-risk pregnancies, the ideal number of visits remains a subject of debate. (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e) The optimal number of antenatal visits is influenced not only by their effectiveness but also by the practicality and various barriers to accessing and providing antenatal care, particularly in low-income countries. (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e) In developing countries, many pregnant women delay starting antenatal care for a variety of reasons. (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e) Maternal age and the husband's attitude towards antenatal care significantly impact a woman's use of these services. (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e) Furthermore, various socio-demographic and reproductive health factors can lead to women missing opportunities for care. Limited or late-term antenatal care visits can put both mothers and their children at risk. (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eIn Somalia, access to health care is severely constrained by socioeconomic challenges, cultural practices, and a fragmented health system, compounded by decades of conflict and instability. Despite global efforts to improve maternal health outcomes under the Sustainable Development Goals (SDG3), Somalia\u0026rsquo;s ANC coverage remains among the lowest worldwide. Evidence shows that 86% of pregnant women worldwide access skilled ANC at least once, and 65% have at least four visits. In sub-Saharan Africa, only 52% of pregnant mothers made at least four visits.(\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e) The Somali Health and Demographic Survey (SHDS) 2020 revealed that only 31% of pregnant women received ANC from skilled personnel, highlighting significant gaps in service delivery and accessibility. Various factors influence ANC utilization in Somalia, including socioeconomic status, education, geographic location, and health infrastructure. Rural and nomadic populations face unique barriers, including long travel distances to healthcare facilities, high costs, and cultural norms that discourage formal healthcare use.\u003c/p\u003e \u003cp\u003eAddressing these disparities is crucial to reducing maternal and neonatal mortality and achieving equitable healthcare access for all Somali women. This study aims to assess the prevalence of ANC utilization among pregnant women in Somalia and examine the socioeconomic, educational, and cultural factors influencing their use of ANC services, based on data from the 2020 Somalia Demographic and Health Survey.\u003c/p\u003e"},{"header":"Method and material","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Setting\u003c/h2\u003e \u003cp\u003eSomalia is located in the Horn of Africa, with an estimated surface area of 637,657 km2 and a terrain consisting mainly of plateaus, plains, and highlands. It has the longest coastline in Africa, stretching over 3,333 km along the Gulf of Aden to the north and the Indian Ocean to the east and south. It borders Djibouti along the north-west, Ethiopia to the west, and Kenya to the south-west. Somalia still remains one of the poorest and least developed countries in Africa, with a Gross Domestic Product (GDP) of 4.7\u0026nbsp;million US dollars in 2018 (FGS 2020) and a per capita estimated at approximately \u003cspan\u003e$\u003c/span\u003e315 in 2018 (World Bank 2018). (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e)\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eStudy Design\u003c/h3\u003e\n\u003cp\u003eThe Somali Health and Demographic Survey (SHDS) was a cross-sectional, stratified cluster survey conducted from 2018 to 2019. It was the first nationally representative health and demographic survey in Somalia, designed to provide evidence-based data for monitoring and evaluating development plans, including the Sustainable Development Goals (SDGs). The survey was implemented by the Directorate of National Statistics, with technical support from UNFPA and other international partners. The survey used Geographic Information System (GIS) technology to digitize enumeration areas (EAs) and generate a sampling frame that included urban, rural, and nomadic settings. (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e)\u003c/p\u003e\n\u003ch3\u003eData source\u003c/h3\u003e\n\u003cp\u003eThe 2020 SHDS datasets, which were collected between 2018 and 2020, were used in this investigation. The information was taken from (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://microdata.nbs.gov.so/index.php/catalog/50\u003c/span\u003e\u003cspan address=\"https://microdata.nbs.gov.so/index.php/catalog/50\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), the SDHS website.\u003c/p\u003e\n\u003ch3\u003eData management and analysis\u003c/h3\u003e\n\u003cp\u003eData were analyzed using Stata software version 16. Data cleaning was performed missing variables were checked. Descriptive statistics, such as frequency, percentage, were computed by the use of pie charts and tables. Moreover, we have analyzed the plan file created in these three steps to identify factors associated with antenatal care utilization. A chi-square test was performed to observe any association between the dependent variable and the independent variables. First, we performed binary logistic regression analysis to identify variables associated with antenatal care utilization. In binary logistic regression analysis, we took variables with a p-value less than or equal to 0.005 into a multivariable logistic regression analysis to control for co-founders. Then, variables that had a significant association with antenatal care utilization were identified based on adjusted odds ratio (AOR) and p-value less than 0.005 in a multivariable logistic regression analysis model.\u003c/p\u003e\n\u003ch3\u003eMeasurement of variables\u003c/h3\u003e\n\u003cp\u003eThe study’s outcome variable was Antenatal care services utilization. it is a binary outcome variable. Those women who did not utilize antenatal care services were assigned as ‘0’, but those who utilized antenatal care services were assigned as ‘1’ during analysis. In this study, antenatal care utilization was defined as: women who visited a health facility at least once during their last pregnancy were considered as receiving antenatal care services; otherwise, not. Independent variables are categorized into two main groups, which include socioeconomic and reproductive health variables. Socio-demographic characteristics include age, region, place of residence, educational status, wealth index, marital status, family size, and Frequency of listening to the radio. Moreover, reproductive health characteristics consisted of the following variables: Age of respondent at 1st birth, Place of birth, Current pregnancy, Contraceptive use and intention, Person who usually decides on respondents’ health care, and Desire for more children (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\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\u003eList of study variables\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"2\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStudy variables\u003c/p\u003e \u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDescription and categorization\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOutcome variable\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNumber of antenatal visits during pregnancy\u003c/p\u003e \u003cp\u003e0 = Non utilization of ANC |\u003c/p\u003e \u003cp\u003e1 = Utilization of ANC\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eIndependent variables\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaternal age\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 = 15–19\u003c/p\u003e \u003cp\u003e2 = 20–24\u003c/p\u003e \u003cp\u003e3 = 25–29\u003c/p\u003e \u003cp\u003e4 = 30–34\u003c/p\u003e \u003cp\u003e5 = 35–39\u003c/p\u003e \u003cp\u003e6 = 40–44\u003c/p\u003e \u003cp\u003e7 = 45–49\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResidence\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eType place of residence\u003c/p\u003e \u003cp\u003e1 = Rural\u003c/p\u003e \u003cp\u003e2 = Urban\u003c/p\u003e \u003cp\u003e3 = Nomadic\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaternal education\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHighest educational level\u003c/p\u003e \u003cp\u003e0 = No Education\u003c/p\u003e \u003cp\u003e1 = Primary\u003c/p\u003e \u003cp\u003e2 = Secondary\u003c/p\u003e \u003cp\u003e3 = Higher\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWealth index\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWealth index combined\u003c/p\u003e \u003cp\u003e1 = Lowest\u003c/p\u003e \u003cp\u003e2 = Second\u003c/p\u003e \u003cp\u003e3 = Middle\u003c/p\u003e \u003cp\u003e4 = Fourth\u003c/p\u003e \u003cp\u003e5 = Highest\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003emarital status\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCurrent marital status\u003c/p\u003e \u003cp\u003e0 = Married\u003c/p\u003e \u003cp\u003e1 = Divorced\u003c/p\u003e \u003cp\u003e2 = Widowed\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFrequency of listening to the radio\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 = At least once a week\u003c/p\u003e \u003cp\u003e2 = Less than once a week\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFamily size\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNumber of household members (listed)\u003c/p\u003e \u003cp\u003e1 = Less than four members\u003c/p\u003e \u003cp\u003e2 = Four members or more\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge of respondent at 1st birth\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 = \u0026lt; 20\u003c/p\u003e \u003cp\u003e1 = 20–24\u003c/p\u003e \u003cp\u003e2 = 25–30\u003c/p\u003e \u003cp\u003e3 = 30 and above\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlace of birth\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePlace delivery\u003c/p\u003e \u003cp\u003e0 = Home\u003c/p\u003e \u003cp\u003e1 = Health institution\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCurrent pregnant\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 = Yes\u003c/p\u003e \u003cp\u003e1 = No\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eContraceptive use and intention\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 = Yes\u003c/p\u003e \u003cp\u003e1 = No\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDesire for more children\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 = Wants within 2 years\u003c/p\u003e \u003cp\u003e2 = Wants after 2 years\u003c/p\u003e \u003cp\u003e4 = Undecided\u003c/p\u003e \u003cp\u003e5 = Wants no more\u003c/p\u003e \u003cp\u003e6 = Declared Infecund\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHealth care decision\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePerson who usually decides on respondents’ health care\u003c/p\u003e \u003cp\u003e1 = Respondent\u003c/p\u003e \u003cp\u003e2 = Husband\u003c/p\u003e \u003cp\u003e3 = Respondent and Husband Jointly\u003c/p\u003e \u003cp\u003e4 = In Laws\u003c/p\u003e \u003cp\u003e5 = Someone else\u003c/p\u003e \u003cp\u003e6 = Other\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRegion\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAwdal\u003c/p\u003e \u003cp\u003eWoqooyi Galbeed\u003c/p\u003e \u003cp\u003eTogdheer\u003c/p\u003e \u003cp\u003eSool\u003c/p\u003e \u003cp\u003eSanaag\u003c/p\u003e \u003cp\u003eBari\u003c/p\u003e \u003cp\u003eNugaal\u003c/p\u003e \u003cp\u003eMudug\u003c/p\u003e \u003cp\u003eGalgaduud\u003c/p\u003e \u003cp\u003eHiraan\u003c/p\u003e \u003cp\u003eMiddle Shabelle\u003c/p\u003e \u003cp\u003eBanadir\u003c/p\u003e \u003cp\u003eBay\u003c/p\u003e \u003cp\u003eBakool\u003c/p\u003e \u003cp\u003eGedo\u003c/p\u003e \u003cp\u003eLower Juba\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e \u003cp\u003e\u003c/p\u003e "},{"header":"Results","content":"\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e summarizes the socio-demographic characteristics and their association with ANC utilization. The majority of respondents were married (91.7%) and had no formal education (83.5%). Most lived in rural areas (27.2%) or were nomadic residents (35.5%), while 37.3% resided in urban areas. Women aged 20–24 years had the highest ANC utilization (39.98%), while those aged 40–44 years exhibited the lowest (25.83%). The Gedo region had the lowest ANC utilization rate (10.89%), whereas Hiraan showed the highest (80.24%). Wealth and education were strong predictors; women in the highest wealth quintile (61.49%) and those with higher education (83.33%) were more likely to use ANC services. Conversely, the lowest wealth quintile (17.20%) and women with no formal education (30.89%) reported higher non-utilization rates. Media exposure, such as listening to the radio, also significantly influenced utilization, with regular listeners exhibiting higher rates (55.52%). These findings underscore the influence of socioeconomic, educational, and regional disparities on ANC utilization among women\u003c/p\u003e\u003cp\u003e \u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\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\u003edemographic and socioeconomic characteristics of respondents (N = 5,235)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003c/colgroup\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCategories\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFrequency (%)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eAnc utilization\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eX2(p-value)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNon utilization\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eUtilization\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"6\" rowspan=\"7\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15–19\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e312(5.96)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e205(65.71)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e107(34.29)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"6\" rowspan=\"7\"\u003e \u003cp\u003e29.55(\u0026lt; 0.001)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20–24\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1048(20.02)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e629(60.02)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e419(39.98)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25–29\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1453(27.76)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e891(61.32)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e562(38.68)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30–34\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1053(20.11)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e676(64.20)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e377(35.80)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35–39\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e886(16.92)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e583(65.80)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e303(34.20)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40–44\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e360(6.88)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e267(74.17)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e93(25.83)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45–49\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e123(2.35)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e82(66.67)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e41(33.33)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"15\" rowspan=\"16\"\u003e \u003cp\u003eRegion\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAwdal\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e276(5.27)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e121(43.84)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e155(56.16)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"15\" rowspan=\"16\"\u003e \u003cp\u003e342.17(\u0026lt; 0.001)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWoqooyi Galbeed\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e439(8.39)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e276(62.87)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e163(37.13)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTogdheer\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e439(8.39)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e215(48.97)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e224(51.03)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSool\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e472((9.02)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e225(47.67)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e247(52.33)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSanaag\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e464(8.86)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e243(52.37)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e221(47.63)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBari\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e291(5.56)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e208(71.48)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e83(28.52)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNugaal\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3095.90)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e211(68.28)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e98(31.72)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMudug\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e316(6.04)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e234(74.05)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e82(25.95)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGalgaduud\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e259(4.95)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e188(72.59)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e71(27.41)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHiraan\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e253(4.83)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e203(80.24)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e50(19.76)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMiddle Shabelle\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e289(5.52)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e173(59.86)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e116(40.14)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBanadir\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e453(8.65)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e309(68.21)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e144(31.79)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBay\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e104(1.99)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e50(48.08)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e54(51.92)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBakool\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e309(5.90)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e221(71.52)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e88(28.48)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGedo\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e257(4.91)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e229(89.11)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e28(10.89)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLower Juba\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e305(5.83)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e227(74.43)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e78(25.57)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eResidence\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRural\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1423(27.18)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e935(65.71)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e488(34.29)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e10.35(0.0057)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUrban\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1954(37.33)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1268(64.89)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e686(35.11)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNomadic\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1858(35.49)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1130(60.82)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e728(39.18)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eEducation level\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo Education\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4370(83.48)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3020(69.11)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1350(30.89)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e354.37(\u0026lt; 0.001)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrimary\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e634(12.11)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e251(39.59)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e383(60.41)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSecondary\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e165(3.15)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e51(30.91)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e114(69.09)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigher\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e66(1.26)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11(16.67)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e55(83.33)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eWealth index\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLowest\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1157(22.10)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e958(82.80)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e199(17.20)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e596.82(\u0026lt; 0.001)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSecond\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1100(21.01)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e859(78.09)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e241(21.91)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMiddle\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1043(19.92)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e634(60.79)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e409(39.21)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFourth\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1021(19.50)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e530(51.91)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e491(48.09)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHighest\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e914(17.46)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e352(38.51)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e562(61.49)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eCurrent marital status\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4801(91.71)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3044(63.40)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1757(36.60)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e4.44(0.1086)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDivorced\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e310(5.92)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e199(64.19)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e111(35.81)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWidowed\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e124(2.37)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e90(72.58)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e34(27.42)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eFrequency of listening to radio\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAt least once a week\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e335(6.40)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e149(44.48)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e186(55.52)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e74.39(\u0026lt; 0.001)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLess than once a week\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e139(2.66)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e67(48.20)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e72(51.80)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNot at all\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4761(90.95)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3117(65.47)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1644(34.53)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eFamily size\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLess than four members\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1318(25.18)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e837(63.51)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e481(36.49)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.02 (0.8874)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFour members or more\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3917(74.82)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2496(63.72)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1421(36.28)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eRegarding the reproductive health characteristics of the respondents, more than half, 2,842 (54.3%), gave birth for the first time before the age of 20, while only 81 (1.6%) had their first birth at 30 years or older. Among the total respondents, 1,309 (25.0%) were currently pregnant, and 3,926 (75.0%) were not pregnant at the time of the survey. A small proportion, 494 (9.4%), reported using contraceptives, while the majority, 4,741 (90.6%), did not. In terms of the desire for more children, 3,145 (60.1%) wanted to have more children within two years, whereas 939 (17.9%) wanted no more children, and 839 (16.0%) were undecided. Additionally, 1 (0.02%) respondent declared being infecund. Decision-making on healthcare varied, with 1,021 (19.5%) respondents deciding independently, 1,704 (32.6%) jointly with their husbands, and 2,481 (47.4%) relying on their husbands to make healthcare decisions. chi-square test was conducted to examine the association between various reproductive health characteristics and antenatal care (ANC) utilization among respondents. The findings revealed several significant relationships. The place of birth (X² = 817.70, p \u0026lt; 0.001) was significantly associated with ANC utilization, with a higher utilization rate among women who gave birth in health institutions compared to those who delivered at home. Current pregnancy status (X² = 5.21, p = 0.0224) also showed a significant relationship, with pregnant women more likely to utilize ANC services than non-pregnant women. Contraceptive use and intention (X² = 88.16, p \u0026lt; 0.001) were significantly associated with ANC utilization, with women using contraceptives demonstrating higher utilization rates. Desire for more children (X² = 166.37, p \u0026lt; 0.001) also had a significant association; women who wanted children within two years were more likely to utilize ANC services compared to those undecided or wanting no more children. Similarly, decision-making on healthcare (X² = 28.40, p \u0026lt; 0.001) was significantly linked to ANC utilization, with women who made decisions jointly with their husbands or independently showing higher rates of utilization. However, the age of respondents at first birth (X² = 2.41, p = 0.4924) did not show a significant association with ANC utilization. These results highlight the importance of institutional support, reproductive intentions, and autonomy in decision-making in improving ANC utilization rates \u003cb\u003e(\u003c/b\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e\u003c/p\u003e\u003cp\u003e \u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\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\u003eReproductive health characteristics of the respondents (N = 5,235)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003c/colgroup\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCategories\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eFrequency (%)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eAnc utilization\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eX2(p-value)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eNon utilization\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e\u003cb\u003eUtilization\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eAge of respondent at 1st birth\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt; 20\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2842(54.29)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1803(63.44)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1039(36.56)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e2.41(0.4924)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20–24\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1804(34.46)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1161(64.36)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e643(35.64)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25–30\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e508(9.70)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e313(61.61)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e195(38.39)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30 and above\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e81(1.55)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e56(69.14)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e25(30.86)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePlace of birth\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHome\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3908(74.65)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2921(74.74)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e987(25.26)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e817.70(\u0026lt; 0.001)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHealth institution\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1327(25.35)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e412(31.05)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e915(68.95)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCurrent pregnant\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1309(25.00)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e799(61.04)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e510(38.96)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e5.21(0.0224)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3926(75.00)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2534(64.54)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1392(35.46)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eContraceptive use and intention\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4741(90.56)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3114(65.68)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1627(34.32)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e88.16(\u0026lt; 0.001)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e494(9.44)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e219(44.33)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e275(55.67)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eDesire for more children\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWants within 2 years\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3145(60.08)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1827(58.09)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1318(41.91)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e166.37(\u0026lt; 0.001)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWants after 2 years\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e311(5.94)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e165(53.05)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e146(46.95)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUndecided\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e839(16.03)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e643(76.64)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e196(23.36)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWants no more\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e939(17.94)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e698(74.33)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e241(25.67)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDeclared Infecund\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1(0.02)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0(0.00)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1(100.00)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003eHealth care decion\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRespondent\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1021(19.50)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e627(61.41)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e394(38.59)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003e28.40(\u0026lt; 0.001)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHusband\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2481(47.39)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1669(67.27)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e812(32.73)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRespondent and Husband Jointly\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1704(32.55)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1019(59.80)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e685(40.20)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIn Laws\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8(0.15)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5(62.50)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3(37.50)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSomeone else\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11(0.21)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8(72.73)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3(27.27)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10(0.19)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5(50.00)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5(50.00)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e \u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e shows the multivariate logistic regression analysis of antenatal care utilization in Somalia, based on the 2020 Somalia Demographic Health Survey data (N = 5,235), which identifies several key variables with significant associations. Higher age groups, increased education levels, wealthier economic statuses, frequent radio listening, institutional births, contraceptive use, and specific childbearing intentions are all positively correlated with the utilization of antenatal care services. Conversely, residing in regions other than Awdal is associated with lower antenatal care utilization. The analysis revealed that women in the age group of 20–24 were 39.5% more likely to utilize antenatal care (AOR = 1.395, 95%CI, 1.018–1.913). Women with primary education were nearly twice as likely (AOR = 1.966, 95%CI, 1.608–2.403), and those with higher education were over two and a half times more likely (AOR = 2.486, 95%CI, 1.209–5.112) to use antenatal care compared to those with no education. Women in higher wealth quintiles had higher odds of utilizing antenatal care, with those in the fourth wealth quintile having more than two and a half times the likelihood (AOR = 2.604, 95%CI, 2.079–3.262) compared to those in the lowest quintile. Frequency of radio listening also played a role, with those who listened at least once a week being more likely to use antenatal care (AOR = 3.124, 95%CI, 2.457–3.971). Furthermore, women who gave birth in a health institution were significantly more likely to use antenatal care (AOR = 3.821, 95%CI, 3.264–4.473). Conversely, women who desired no more children had a lower likelihood of using antenatal care. These findings emphasize the importance of educational status, wealth, media exposure, and healthcare access in influencing antenatal care utilization in Somalia.\u003c/p\u003e\u003cp\u003e \u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003emultivariate logistic regression for antenatal care utilization in Somalia using Somalia demographic health survey 2020 (N = 5,235)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003c/colgroup\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCategories\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eAntenatal care utilization\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eAOR (95%CI)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eCOR (95%CI)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"6\" rowspan=\"7\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15–19\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20–24\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.395(1.018–1.913) **\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.276(.98-1.663) *\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25–29\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.468(1.074–2.006) **\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.208(.935-1.562)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30–34\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.287(0.93–1.78)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.068(.819-1.393)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35–39\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.507(1.074–2.114) **\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.996(.759-1.307) **\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40–44\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.252(0.829–1.889)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.667(.479-.93)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e45–49\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.178(1.28–3.705) ***\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.958(.616 − 1.49)***\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"15\" rowspan=\"16\"\u003e \u003cp\u003eRegion\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAwdal\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWoqooyi Galbeed\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.443(0.312–0.63) ***\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.461(.339-.626) ***\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTogdheer\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.59(0.418–0.834) ***\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.813(.601-1.101)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSool\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.691(0.49–0.976) **\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.857(.636-1.155)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSanaag\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.587(0.416–0.827) ***\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.71(.526-.958) **\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBari\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.413(0.28–0.61) ***\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.312(.22-.441) ***\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNugaal\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.458(0.313–0.669) ***\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.363(.259-.508) ***\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMudug\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.415(0.281–0.611) ***\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.274(.194-.387) ***\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGalgaduud\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.396(0.264–0.594) ***\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.295(.205-.423) ***\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHiraan\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.245(0.158–0.38) ***\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.192(.13-.284) ***\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMiddle Shabelle\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.496(0.338–0.727) ***\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.523(.375-.731) ***\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBanadir\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.363(0.25-.529) ***\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.364(.267-.496) ***\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBay\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.8(0.475–1.345)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.843(.536-1.325)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBakool\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.318(0.217–0.466) ***\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.311(.221-.438) ***\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eGedo\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.155(0.095–0.254) ***\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.095(.06-.151) ***\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLower Juba\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.293(0.198–0.435) ***\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.268(.189-.381) ***\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eEducation level\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo Education\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrimary\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.966(1.608–2.403) ***\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.413(2.875–4.053) ***\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSecondary\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.917(1.3-2.827) ***\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.000(3.572–6.999) ***\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigher\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.486(1.209–5.112) **\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.185(5.836–21.437) ***\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eWealth index\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLowest\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSecond\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.474(1.171–1.856) ***\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.351(1.096–1.665) ***\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMiddle\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.493(1.995–3.115) ***\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.106(2.551–2.551) ***\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFourth\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.604(2.079–3.262) ***\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.46(3.666–5.425) ***\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eFrequency of listening to radio\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHighest\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.124(2.457–3.971) ***\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.686(6.276–9.413) ***\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAt least once a week\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLess than once a week\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.93(0.587–1.472)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.861(.579 − 1.28)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNot at all\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.741(0.569–0.965) **\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.423((.338-.528) ***\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eAge of respondent at 1st birth\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026lt; 20\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20–24\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.894(.768 − 1.04)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.961(.85-1.087)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25–30\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.091(.851-1.398)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.081(.89-1.313)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e30 and above\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.588(.318-1.088) *\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.775(.481-1.249)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHome\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlace of birth\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHealth institution\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.821(3.264–4.473) ***\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.573(5.732–7.537) ***\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eContraceptive use and intention\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.37(1.094–1.714) ***\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.403(1.993–2.899***\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eDesire for more children\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWants within 2 years\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.993(.755-1.307)\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.227(.971-1.549) *\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWants after 2 years\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.527(.431-.646) ***\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.423(.355-.503) ***\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUndecided\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e.544(.447-.662) ***\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.479(.407-.563) ***\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWants no more\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\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e \u003cb\u003e*** p\u0026lt;.01, ** p\u0026lt;.05, * p\u0026lt;.1 Ref, reference category; RRR, relative risk ratios; CI, confidence interval.\u003c/b\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study assessed the prevalence and determinants of antenatal care (ANC) utilization among pregnant women in Somalia using data from the 2020 Somalia Demographic and Health Survey. The result showed that ANC utilization remains low, with only 31% pregnant women receiving ANC from skilled personnel. This rate is lower than a report from the study conducted in 11 East African Countries that showed the magnitude of optimal ANC utilization was the highest optimal ANC utilization in Zimbabwe (80.96%) and the lowest optimal ANC utilization in Rwanda (44.31%)(\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e).also study conducted in 31 sub-Saharan African countries that showed non utilization of ANC in Chad (41.8%), Ethiopia (34.8%) and Nigeria (26.1%).(\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e) the possible explanation for this inconsistency might be due to socio-demographic characteristic of the research participants, including their economic status, the restricted availability of maternal health care, and inadequate trained health personal in Somalia(\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e).Key determinants of ANC utilization included maternal education, wealth status, geographic location, place of birth, contraceptive use, and media exposure. Women with higher education levels and those in the wealthier quintile were significantly more likely to utilize ANC services. Additionally, listening to the radio at least once a week was associated with higher ANC utilization. Conversely, women residing in rural and nomadic areas exhibited lower ANC utilization rates. Older age groups, particularly those aged 35\u0026ndash;39 and 45\u0026ndash;49, exhibited higher odds of ANC utilization. This finding is in line with reports of other previous studies. This finding is supported by a systematic review conducted in sub-Saharan Africa (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e), Ethiopia (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e), and Uganda (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). This trend suggests that the women age, they may become more aware of the important ANC services, possibly due to increased pregnancy experience and exposure to health education programs. However, the lower utilization among younger women indicates a potential gap in targeted maternal health programs for adolescent and young mothers. We found evidence suggesting that the higher education level of women improves their utilization of ANC services. This was supported by similar findings(\u003cspan additionalcitationids=\"CR24\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e), higher education level empowered women with knowledge about the benefits of maternal health care services. The positive impact of education underscores the importance of strengthening female education programs to enhance maternal health outcomes.(\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e) Women who were the richest were more likely to utilize ANC than the poorest women. This finding is consistent with a study conducted in Ethiopia(\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e) and elsewhere.(\u003cspan additionalcitationids=\"CR29\" citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e) Access to maternal health services may be significantly hampered by household poverty. Women from low-income families could not have the necessary funds. should either pay for the services provided throughout the prenatal period or register at clinics. This may lead to a situation where such women would partially attend the clinics or not attend at all. Compared to their counterparts, media-exposed women were more likely to use ANC. This result is consistent with a population-based research that used DHS data in Nepal(\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e), a systematic review that was carried out in developing nations(\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e), and a systematic review and meta-analysis study that was carried out in Ethiopia(\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e). Media like radio may encourage positive changes in behavior by regularly airing public service announcements and programs backed by the government or non-state entities that outline the advantages of using ANC and other maternal healthcare treatments on time(\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e). There may be a connection between maternal healthcare-seeking behavior and family planning awareness, since women who used contraceptives were much more likely to utilize ANC services. Women who wanted no more children, on the other hand, had a lower likelihood of using ANC, which could be a result of less pregnancy-related worries or a lack of desire to get maternity care. ANC education should be incorporated into family planning programs to promote consistent utilization of maternal health services, irrespective of fertility goals(\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e). Significant regional variation in ANC utilization was observed, with women residing in regions such as Gedo, Hiraan, and Mudug having significantly lower odds of using ANC compared to those in Awdal.The unequal distribution of medical facilities, restricted access to maternal health care, and potential cultural variations impacting ANC-seeking behaviors are all highlighted by these inequalities. Targeted initiatives are needed to address these gaps, such as better healthcare facilities, mobile clinics, and culturally aware health promotion tactics in underprivileged areas(\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e). Compared to women who gave birth at home, those who gave birth in medical facilities were almost four times more likely to have used ANC services. According to this research, women who are currently interacting with healthcare systems are more likely to seek out ongoing maternity care. Increased use of ANC may be encouraged by bolstering institutional delivery services and encouraging facility-based deliveries(\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e).\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study provides valuable insight into the prevalence and determinants of antenatal care utilization (ANC) in Somalia, using nationally representative data from the 2020 Somalia Demographic and Health Survey. The findings reveal that ANC utilization remains significantly low, with more than half of women (63.67%) not utilizing ANC services, whereas the rest (36.33%) did. Various socioeconomic, educational, and cultural factors influenced ANC utilization. Women with higher education, increased wealth status, and frequent media exposure demonstrated higher ANC utilization, whereas rural residence, nomadic lifestyles, and cultural barriers posed significant challenges. Addressing these disparities is crucial to improving maternal and neonatal health outcomes. Policymakers should prioritize interventions aimed at increasing healthcare accessibility, strengthening health infrastructure in underserved areas, and promoting maternal education. Additionally, raising awareness through mass media and community-based programs could enhance positive health-seeking behavior among pregnant women. The utilization gap might also be closed by expanding the capacity of the healthcare personnel, incorporating traditional birth attendants into official healthcare systems, and putting in place incentive-based programs for ANC visits. Expanding outreach initiatives, especially for rural and nomadic groups, can be facilitated by fortifying alliances between governmental and non-governmental organizations. Future studies should examine how digital health interventions, healthcare professional attitudes, and partner support might enhance ANC adoption. To guarantee long-lasting gains in ANC use and, eventually, lower mother and newborn morbidity and death in Somalia, a multi-sector strategy combining health, education, and social development strategies is necessary.\u003c/p\u003e\n\u003ch3\u003eStrengths and Limitations\u003c/h3\u003e\n\u003cp\u003eA key strength of this study is the use of a nationally representative dataset, ensuring generalizability to the Somali population. The study also uses statistical methods to identify key determinants of ANC care utilization. However, certain limitations must be acknowledged. The reliance on self-reported data may introduce recall bias, and the cross-sectional nature of the study limits causal inference. Additionally, culture and qualitative factors influencing ANC utilization were not extensively explored.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eANC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAntenatal Care\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAOR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAdjusted Odds Ratio\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eConfidence Interval\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCOR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCrude Odds Ratio\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eDHS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eDemographic and Health Survey\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eFGS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eFederal Government of Somalia\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eGDP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eGross Domestic Product\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eGIS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eGeographic Information System\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMDG\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMillennium Development Goal\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMMR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eMaternal Mortality Ratio\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003cstrong\u003eEthical approval and consent to participate\u003c/strong\u003e \u003cp\u003eEthical approval wasn't required for this study because we used publicly available, anonymized data from the Demographic and Health Survey (DHS). We obtained permission to download the DHS dataset from the Central Statistical Agency (CSA) through a request at \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://microdata.nbs.gov.so/index.php/catalog/50\u003c/span\u003e\u003cspan address=\"https://microdata.nbs.gov.so/index.php/catalog/50\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent for publication\u003c/strong\u003e \u003cp\u003eNot applicable\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eCompeting interests\u003c/h2\u003e \u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis research received no external funding\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eAll authors contributed to the research, writing, and final approval of the manuscript and are accountable for its content. All authors were involved in the study's design, data analysis, and manuscript preparation.\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e \u003cp\u003eNot applicable\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe Somalia Demographic and Health Survey (SDHS) 2020 datasets used in this study are publicly accessible and can be obtained through an online request at [https://microdata.nbs.gov.so/index.php/catalog/50](https:/microdata.nbs.gov.so/index.php/catalog/50) , specifying the purpose of the research. The datasets analyzed during the current study are also available from the corresponding author upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eTsegaye B, Ayalew M. Prevalence and factors associated with antenatal care utilization in Ethiopia: an evidence from demographic health survey 2016. BMC Pregnancy Childbirth. 2020;20:1\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLawson GW, Keirse MJ. Reflections on the maternal mortality millennium goal. Birth. 2013;40(2):96\u0026ndash;102.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAfework MF. Achieving the maternal health Millennium Development Goals in ethiopia: where are we and what needs to be done? SOC LATINOAMER ESPECIALISTAS MAM\u0026Iacute;FEROS ACU\u0026Aacute;TICOS C/O SALVATORE SICILIANO \u0026hellip; pp. 87\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYamin AE, Boulanger VM. Embedding sexual and reproductive health and rights in a transformational development framework: lessons learned from the MDG targets and indicators. Reprod Health Matters. 2013;21(42):74\u0026ndash;85.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKv\u0026aring;le G, Olsen BE, Hinderaker SG, Ulstein M, Bergsj\u0026oslash; P. Maternal deaths in developing countries: A preventable tragedy. Norsk Epidemiologi. 2005;15(2).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMcCaw-Binns A, La Grenade J, Ashley D. Under-users of antenatal care: a comparison of non-attenders and late attenders for antenatal care, with early attenders. Soc Sci Med. 1995;40(7):1003\u0026ndash;12.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTekelab T, Chojenta C, Smith R, Loxton D. Factors affecting utilization of antenatal care in Ethiopia: a systematic review and meta-analysis. PLoS ONE. 2019;14(4):e0214848.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKassebaum N, Barber R, Dandona L, Hay S, Larson H, Lim S, et al. Erratum: Global, regional, and national levels of maternal mortality, 1990\u0026ndash;2015: a systematic analysis for the Global Burden of Disease Study 2015 (The Lancet (2016) 388 (10053)(1775\u0026ndash;1812)(S0140673616314702)(10.1016/S0140-6736. Lancet. 2017;389(16):31470\u0026ndash;2.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCarroli G, Villar J, Piaggio G, Khan-Neelofur D, G\u0026uuml;lmezoglu M, Mugford M, et al. WHO systematic review of randomised controlled trials of routine antenatal care. Lancet. 2001;357(9268):1565\u0026ndash;70.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLincetto O, Mothebesoane-Anoh S, Gomez P, Munjanja S. Antenatal care. Opportunities for Africa's newborns: Practical data, policy and programmatic support for newborn care in Africa. 2006:55\u0026ndash;62.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVan Eijk AM, Lindblade KA, Odhiambo F, Peterson E, Sikuku E, Ayisi JG, et al. Reproductive health issues in rural Western Kenya. Reproductive health. 2008;5:1\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePaul BK. Health service resources as determinants of infant death in rural Bangladesh: an empirical study. 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Federal Government of Somalia and UNFPA; 2020.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\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 women's health. 2022:67\u0026ndash;77.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAdedokun ST, Yaya S. Correlates of antenatal care utilization among women of reproductive age in sub-Saharan Africa: evidence from multinomial analysis of demographic and health surveys (2010\u0026ndash;2018) from 31 countries. Archives Public Health. 2020;78:1\u0026ndash;10.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUmer A, Zinsstag J, Schelling E, Tschopp R, Hattendof J, Osman K, et al. Antenatal care and skilled delivery service utilisation in Somali pastoral communities of Eastern Ethiopia. Tropical Med Int Health. 2020;25(3):328\u0026ndash;37.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOkedo-Alex IN, Akamike IC, Ezeanosike OB, Uneke CJ. Determinants of antenatal care utilisation in sub-Saharan Africa: a systematic review. BMJ open. 2019;9(10):e031890.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOusman SK, Mdala I, Thorsen VC, Sundby J, Magnus JH. Social determinants of antenatal care service use in Ethiopia: changes over a 15-year span. Front public health. 2019;7:161.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAtuhaire S, Mugisha J. Determinants of antenatal care visits and their impact on the choice of birthplace among mothers in Uganda. 2020.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAyalew TW, Nigatu AM. Focused antenatal care utilization and associated factors in Debre Tabor Town, northwest Ethiopia, 2017. BMC Res Notes. 2018;11:1\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSimkhada B, Teijlingen ERv, Porter M, Simkhada P. Factors affecting the utilization of antenatal care in developing countries: systematic review of the literature. J Adv Nurs. 2008;61(3):244\u0026ndash;60.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYeneneh A, Alemu K, Dadi AF, Alamirrew A. Spatial distribution of antenatal care utilization and associated factors in Ethiopia: evidence from Ethiopian demographic health surveys. BMC Pregnancy Childbirth. 2018;18:1\u0026ndash;12.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCorroon M, Speizer IS, Fotso J-C, Akiode A, Saad A, Calhoun L, et al. The role of gender empowerment on reproductive health outcomes in urban Nigeria. Matern Child Health J. 2014;18:307\u0026ndash;15.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDankwah E, Zeng W, Feng C, Kirychuk S, Farag M. The social determinants of health facility delivery in Ghana. Reproductive health. 2019;16:1\u0026ndash;10.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFagbamigbe AF, Idemudia ES. Wealth and antenatal care utilization in Nigeria: policy implications. Health Care Women Int. 2017;38(1):17\u0026ndash;37.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAdedokun ST, Uthman OA. Women who have not utilized health Service for Delivery in Nigeria: who are they and where do they live? BMC Pregnancy Childbirth. 2019;19:1\u0026ndash;14.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJoshi C, Torvaldsen S, Hodgson R, Hayen A. Factors associated with the use and quality of antenatal care in Nepal: a population-based study using the demographic and health survey data. BMC Pregnancy Childbirth. 2014;14:1\u0026ndash;11.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAdewuyi EO, Auta A, Khanal V, Bamidele OD, Akuoko CP, Adefemi K, et al. Prevalence and factors associated with underutilization of antenatal care services in Nigeria: A comparative study of rural and urban residences based on the 2013 Nigeria demographic and health survey. PLoS ONE. 2018;13(5):e0197324.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFatema K, Lariscy JT. Mass media exposure and maternal healthcare utilization in South Asia. SSM-population Health. 2020;11:100614.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAhinkorah BO, Budu E, Aboagye RG, Agbaglo E, Arthur-Holmes F, Adu C, et al. Factors associated with modern contraceptive use among women with no fertility intention in sub-Saharan Africa: evidence from cross-sectional surveys of 29 countries. Contracept reproductive Med. 2021;6:1\u0026ndash;13.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChikandiwa A, Burgess E, Otwombe K, Chimoyi L. Use of contraceptives, high risk births and under-five mortality in Sub Saharan Africa: evidence from Kenyan (2014) and Zimbabwean (2011) demographic health surveys. BMC Womens Health. 2018;18:1\u0026ndash;13.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTsegay Y, Gebrehiwot T, Goicolea I, Edin K, Lemma H, Sebastian MS. Determinants of antenatal and delivery care utilization in Tigray region, Ethiopia: a cross-sectional study. Int J Equity Health. 2013;12:1\u0026ndash;10.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eYesuf EA, Calderon-Margalit R. Disparities in the use of antenatal care service in Ethiopia over a period of fifteen years. BMC Pregnancy Childbirth. 2013;13:1\u0026ndash;10.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\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/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Antenatal care, DHS, Sustainable Development Goals, pregnant women, Health service utilization, public health","lastPublishedDoi":"10.21203/rs.3.rs-8669665/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8669665/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eGlobally, maternal mortality and morbidity pose the greatest challenge to human development. Almost all of maternal deaths occur in low- and middle-income countries. Maternal mortality rate declined by 45%from 380 to 210 deaths per 100,000 live births between 1990 and 2013 in the world. First, the finished Millennium Development Goal Agenda 5 targeted to reduce maternal deaths by 75%between 2000 and 2015. Next, Sustainable Development Goal 3.1 sets a specific target of MMR reduction below 70 by 2030 in the world. Most of these maternal deaths occur due to causes directly related to pregnancy. Fortunately, these maternal deaths can be prevented through the provision of antenatal care and institutional-based delivery services\u003c/p\u003e\u003ch2\u003eMethod\u003c/h2\u003e \u003cp\u003eSecondary data was collected on SDHS2020.encompassing a sample of 5,235 women aged 15\u0026ndash;49 years. Descriptive statistics and multivariate logistic regression were employed to identify significant predictors of ANC utilization. Adjusted odds ratio with 95%confidence interval was computed, and a p-value less than 0.05 was considered as a statistically significant level for identification of association.\u003c/p\u003e\u003ch2\u003eResult\u003c/h2\u003e \u003cp\u003eThe findings indicate that 63.67%of women did not utilize ANC services, with key determinants including maternal age, educational level, wealth index, media exposure, and the place of delivery. Women with higher education and those from wealthier households demonstrated significantly higher rates of ANC utilization, while rural and nomadic populations faced substantial barriers due to cultural norms and limited access to healthcare facilities.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThe study highlights the urgent need for targeted interventions to improve ANC utilization in Somalia, focusing on enhancing healthcare accessibility, strengthening health infrastructure, and promoting maternal education. Addressing these disparities is crucial for improving maternal and neonatal health outcomes in the region.\u003c/p\u003e","manuscriptTitle":"Examining the prevalence and determinants of Antenatal care utilization in Somalia: insights from the 2020 SOMALIA demographic and health survey","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-29 00:54:03","doi":"10.21203/rs.3.rs-8669665/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":"79edc2b0-4dd6-46f5-ae6f-4f876456c430","owner":[],"postedDate":"January 29th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-01-29T00:54:14+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-29 00:54:03","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8669665","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8669665","identity":"rs-8669665","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}