Social Determinants of Antenatal Care Utilization Among Reproductive Age Women: An Analysis of 2022 Ghana  Demographic and  Health Survey

Social Determinants of Antenatal Care Utilization Among Reproductive Age Women: An Analysis of 2022 Ghana 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 Social Determinants of Antenatal Care Utilization Among Reproductive Age Women: An Analysis of 2022 Ghana Demographic and Health Survey Ya Yang, Joseph Adu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5245471/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 12 Jan, 2026 Read the published version in BMC Pregnancy and Childbirth → Version 1 posted 13 You are reading this latest preprint version Abstract Background Antenatal care (ANC) is crucial for improving maternal health outcomes, yet full utilization remains an issue in some parts of Ghana. Using the Andersen Behavioral Model, this study examines the social determinants influencing ANC utilization among reproductive-age women in Ghana. Methods Data from the 2022 Ghana Demographic and Health Survey (GDHS) were analyzed, including 5,218 women aged 15–49. The Andersen Model guided the examination of predisposing (age, education, marital status, religion), enabling (wealth quintile, residence), and need factors (childbirth type, health status). Descriptive statistics and logistic regressions were employed to identify significant predictors of ANC utilization. Results Overall, 87.5% of women sought at least four ANC services. Factors significantly associated with increased likelihood of ANC use included higher education (AOR = 4.51, 95% CI: 1.89–10.78) and being in the highest wealth quintile (AOR = 5.98, 95% CI: 3.20–11.17). Additionally, women aged 25 to 34 (AOR = 1.35, 95% CI: 1.09–1.67) were more likely to use ANC compared to other age groups. In contrast, women in very poor health (AOR = 0.50, 95% CI: 0.18–1.36) and those adhering to traditional or other beliefs (AOR = 0.43, 95% CI: 0.32–0.57) were less likely to seek ANC. Marital status, religion, residence, and type of childbirth were not found to be statistically significant factors for ANC services utilization, with the exception of being married. Conclusions Education, marital status, and wealth were crucial determinants of ANC utilization, highlighting the importance of addressing socio-economic and cultural barriers to improve ANC coverage. Given the implementation of Ghana’s free maternal health services policy, future studies should explore the indirect costs and barriers that prevent women from using ANC. antenatal care maternal health predisposing factors enabling factors need factors Introduction Despite implementing Ghana's free maternal health services policy in 2008, maternal health outcomes remain a significant concern. In 2020, 263 women died per 100,000 live births due to pregnancy-related causes in Ghana [ 1 ]. One of the significant causes of the high maternal mortality rate is inadequate adherence to the recommended number of antenatal care (ANC) visits. Nearly a third of women in Ghana (24%) do not receive ANC services [ 2 , 3 ]. Antenatal care, as defined by the World Health Organization (2016), is the care provided by skilled healthcare professionals to pregnant women and adolescent girls to ensure optimal health conditions for both mother and baby during pregnancy [ 4 ]. Antenatal care services include measuring vital signs, urinalysis, and lab work. Providers also listen to the baby’s heartbeat, offer breastfeeding education, and assess issues such as vaginal bleeding [ 4 ]. This care is essential for detecting health issues related to maternal morbidity and mortality through regular physical examinations. Additionally, ANC improves neonatal outcomes by reducing the risk of stillbirth, preterm birth, and low birth weight [ 4 ]. At least four ANC visits are recommended to achieve optimal health for the mother and child [ 4 ]. The number of ANC visits attended by pregnant women is crucial in improving maternal health outcomes [ 2 , 3 ]. Understanding the utilization of ANC in Ghana provides deeper insights into the factors contributing to the country's high maternal mortality rate. These insights allow healthcare providers and policymakers to identify gaps and understand barriers, ultimately developing effective strategies to improve maternal health outcomes. Maternal deaths can occur at any stage of pregnancy— before, during birth delivery, or after birth. However, the majority of studies focus on deaths during childbirth rather than those occurring before [ 5 , 6 , 7 ]. This gap highlights the need for more research on ANC. Previous studies have identified various factors contributing to poor ANC utilization, including equality, wealth, age, education, and socio-demographic characteristics [ 8 , 9 , 10 ]. These factors are often linked to lower use of ANC services, highlighting a significant gap in understanding the determinants influencing ANC attendance among Ghanaian women. To address Ghana’s high maternal mortality ratio, it is essential to understand the barriers to ANC utilization. While past research has provided some insights [ 3 , 11 ], further exploration is needed to inform targeted policies and public health interventions. For instance, previous research did not consider the effect of “need factors” on the utilization of antenatal care during pregnancy [ 8 , 9 , 11 ]. Thus, a more inclusive analysis is essential to developing effective strategies to improve ANC utilization and reduce maternal mortality in Ghana. This study aims to fill the existing research gap by applying the Andersen Behavioral Model of Health Services to examine the social determinants associated with utilizing ANC services among a nationally representative sample of Ghanaian women of reproductive age. To expand the analysis on the need factors, we hypothesized that women in poor health would be more likely to seek ANC than women in good health. By identifying the factors influencing ANC utilization, this research seeks to provide valuable insights for policymakers and healthcare providers to develop and implement effective public health strategies. Understanding these determinants will help tailor interventions to improve ANC utilization and maternal health outcomes. The findings of this study hope to contribute to the ongoing efforts to reduce maternal mortality and ensure that more women receive the needed care during pregnancy to optimize the health and well-being of both mothers and their babies in the long run. METHODS Study data This study used data from the 2022 Ghana Demographic Health Survey (GDHS) after permission was given from the MEASURE DHS [ 12 ]. The Ghana Health Service, Ministry of Health, Ghana Statistical Service, and ICF International implemented and conducted the surveys. The 2022 Ghana DHS was designed to be representative at the national and regional levels. The survey employed a two-stage sampling design to select participants from households across all 16 regions in Ghana [ 12 ]. The survey interviewed 15,014 women aged 15 to 49, with a response rate of 98% [ 12 ]. The GDHS collected information on socio-demographic characteristics and reproductive health topics, such as family planning, fertility, maternal and child health, and many more [ 12 ]. Conceptual framework This research adopted and modified Andersen’s healthcare utilization model to study ANC use in Ghana [ 13 ]. Andersen’s (1968) conceptual framework examines the factors influencing the consumption of acute healthcare services [ 13 ]. The model aims to identify the determinants that lead to the use of health services. According to the model, health service utilization is shaped by societal, health system, and individual factors [ 13 ]. In this study, individual factors drive ANC use because they influence a person’s need, perception, and ability to seek and utilize healthcare services. These individual factors are categorized into three main components: predisposing, enabling, and need factors [ 13 , 14 ]. Predisposing characteristics refer to factors influencing an individual’s inclination to use health services [ 13 , 14 ]. Predisposing factors can include age, education, marital status, and religion. Enabling factors refer to the logistical and resource-related conditions that influence an individual's ability to access healthcare services [ 13 , 14 ]. These factors either facilitate or hinder health services use and include individual-level resources (such as household wealth) and community-level factors (such as place of residence) [ 13 , 14 ]. In this study, enabling factors include household wealth quintile and place of residence. Lastly, need factors refer to an individual’s perceived need or evaluated need for health services [ 13 , 14 ]. An individual’s perception of their current health status can prompt them to seek ANC, and the type of birth can pose risks that may necessitate ANC to prevent complications. The explanatory predictors in this study were categorized into predisposing factors (age, education, marital status, and religion), enabling factors (household wealth quintile and place of residence), and need factors (type of childbirth and health status). The type of childbirth refers to whether the most recent birth the mother had given was one child, twins, a second set of twins, or a third set of twins. Sample The study sample included 5,218 women of reproductive age (15 to 49 years) who responded to the question about whether or not they used ANC before child delivery. The inclusion criteria were that ANC be utilized at least four times before delivery. Any use of ANC less than four times is considered no use of ANC. Outcome variable ANC use was the percentage of women who had completed at least four antenatal care visits during pregnancy at any of the following settings: respondent's home, government hospital, government health facility, government community health practitioners, mobile clinics, public health settings, other public facilities, private hospital/clinic, Planned Parenthood of Association of Ghana, maternity home, private medical facilities, other private facilities, other homes, and other locations. The outcome variables were coded as follows: 0 = Did not use antenatal care and 1 = Used antenatal care. Exposure variables The independent variables were age, education, marital status, religion, household wealth quintile, residence, childbirth type, and perceived health status. See Table 1. Maternal age did not meet the linearity assumption due to a significant quadratic term (p-value = 0.001). Therefore, it was categorized as 15 to 24 years, 25–34 years, and 35–49 years. Education was organized as none: primary, secondary, and high. Marital status comprised never in union, married, living with a partner, widowed, divorced, and no longer living together or separated. In the GDHS data, the religion options were Catholic, Anglican, Methodist, Presbyterian, Pentecostal/charismatic, other Christian, Islam, Traditional/Spiritualist, no religion, and others. This study categorized Catholic, Anglican, Methodist, Presbyterian, Pentecostal/Charismatic, and other Christians as Christianity. Women without religion, Traditional/Spiritualist, or Other were grouped as Traditional and Other. The only group that remained the same was Islam. Christianity was chosen as the baseline group in this study because it represents the majority religion. This approach highlights potential disparities in care access that may arise due to religious affiliation, especially for Muslims and those practicing Traditional or other religions. The household wealth quintile was created from the Wealth index variable generated from the GDHS. Wealth information was calculated based on information on household assets using principal component analysis. The household wealth quintile was classified as poorest, poorer, middle, richer, and richest. The place of residence was separated as urban and rural. In contrast to previous studies, we are using urban as the baseline for residence type because many health interventions are designed to address challenges faced by rural populations. By using urban as a baseline, it allows the study to evaluate how living in a resource-rich environment has an effect on the use of ANC compared to rural areas. The childbirth type comprised a single birth, first twins of multiple, second twins of multiple, and third twins of multiple. Health status was identified as very good, good, moderate, bad, and very bad. Statistical Analysis This study used sampling weights provided by GDHS. All analysis was conducted in Stata BE 18. Participants with missing data on the outcome variable (ANC utilization) or key exposure variables were excluded from the analysis. Descriptive statistics, chi-squared test, and frequency and percentage distribution were used to describe the characteristics of the respondents. The chi-squared test explored the statistical significance of the differences in ANC use across exposure variables. Bivariate logistic regression examined the associations between social factors and the use of ANC. A multiple logistic regression method explored the link between ANC utilization and explanatory factors. The multiple regression model adjusted the demographic characteristics. The odds ratios and corresponding 95% confidence intervals were computed for all significant variables. An association was considered statistically significant when p < .05. The multicollinearity was investigated and not observed. Multicollinearity was assessed using Variance Inflation Factors (VIF), and no significant multicollinearity was detected, as all VIFs were below 2. RESULTS Descriptive Results Five thousand two hundred and eighteen women between the ages of 15 and 49 responded to the question on using ANC in the 2022 GDHS. As shown on Table 2, the average age for the study population was 29.6 years old (SD=6.92). About 87.5% of women reported completing at least four ANC visits during pregnancy, while 12.5% did not use ANC during pregnancy. Almost half (47.72%) of the women fell between the ages of 25 to 34 years. About one-fourth (25.68%) of the women were between 35 to 49 years old, while slightly over one-fourth (26.60%) were between 15 to 24 years. The ANC utilization rates were comparable among the age groups, with 83.7% for those aged 15-24, 89.8% for those aged 25-34, and 87.1% for those aged 35-49. Almost half (47.07%) of the women had attained at least secondary education. The second largest group of respondents did not have a formal education (29.28%), and approximately one-sixth (15.98%) of women received primary education. The lowest number of women (7.67%) received higher education. Across all educational levels, women with higher education reported the highest ANC utilization rate (98.5%). Following this, women with secondary education reported an ANC use rate of 90.7%, while those with primary education had a rate of 84.3%. Women with no education reported the lowest ANC utilization rate of 81.2%. The higher the education level, the greater the utilization rate of ANC services. The majority (67.86%) of women in this study were married. There were 18.05% of women who reported living with their partner but did not identify as married. The third largest group (9.85%) of women was never in union. Women who were widowed (0.92%), divorced (0.57%), or no longer living together with their partner (2.74%) accounted for the smallest groups of respondents. ANC utilization rates were similar across all marital statuses: never in union (83.7%), married (88.9%), living with a partner (85.1%), widowed (87.5%), divorced (80.0%), and no longer living together or separated (83.2%). Most of the women (62.50%) were Christians. The second largest religious group was Muslims (33.23%), followed by traditional and other beliefs (5.27%). ANC utilization rates were similar among Christian and Muslim women, but there was a difference among women with traditional and other beliefs. ANC use rates were 88.7% among Christian women and 88.4% among Muslim women. The ANC utilization rate was significantly lower among women with traditional or other beliefs at 67.3%. Women from the poorest wealth quintile comprised about 31.79% of the respondents, while the poorer group included almost one-fourth (24.80%) of the respondents, and the middle-class group was 18.15%. The richer (18.15%) and richest (14.33%) included the least respondents in this study. Among all classes of wealth, women from the middle (90.4%), richer (94.7%), and richest (97.7%) categories were reported to have the highest ANC utilization rates. Women from the poorer group had an 87.7% ANC utilization rate. In contrast, women from the poorest group reported a significantly lower ANC use rate (78.9%) than all other groups. More than half (58.59%) of the women lived in rural areas. Among these urban respondents, about 84.7% used at least four ANC during pregnancy. On the other hand, 41.41% of the women lived in urban areas. Compared to rural dwellers, women from urban areas had a higher ANC utilization rate (91.5%). Most women (97.32%) reported having a history of only one birth. A smaller proportion, 2.61%, reported having two sets of twins in addition to their other single children, while 0.08% of women had three sets of twins in addition to their other single children. No woman reported having only one set of twins. Among all groups of childbirth type, women with three sets of twins in addition to their other single child had the highest ANC use rate (100%). Similar ANC utilization rates were observed among women with a single birth (87.5%) and two sets of twins in addition to their other single children (86.8%). Among all health statuses, women with “good” health (48.75%) accounted for most of the respondents, followed by women with “very good” health (32.60%). A smaller portion (15.25%) of the respondents reported having “moderate health,” while very few (2.99% and 0.40%) of the women had “bad” and “very bad” health, respectively. All health statuses, except "very bad," showed similar ANC utilization rates, each exceeding 80%: very good (88.5%), good (87.7%), moderate (86.6%), and bad (80.1%). In contrast, the "very bad" health status had a notably lower ANC utilization rate of 71.4%. Bivariate logistic regression results The bivariable analysis produced point estimates of a little over one for women aged 25-34 years (Unadjusted OR =1.72; 95% CI = 1.42-2.08) and those aged 35-49 years (Unadjusted OR = 1.31; 95% CI = 1.06-1.63%) when compared to women aged 15-24 years (Table 3). For education, the association between primary education and the use of ANC is not statistically significant at the 5% level. This indicates that the OR=1.25; CI = 0.99-1.56 may be due to random chance rather than a true effect. Relative to women without education, women with secondary education were 2.27 (95% CI = 1.88-2.74) times to use ANC, and higher education was 15.25 (95% CI = 6.74-34.50%) times to use ANC. The OR = 0.97; CI = 0.81-1.17 for Muslim women indicates a slight decrease in the likelihood of using antenatal care compared to Christianity, but the p-value of 0.746 suggests no statistically significant association. Women who identify as traditional or other religions are 0.26 (95% CI = 0.20-0.34) times as likely as Christians to seek ANC care, indicating a slightly lower likelihood. The odds of seeking ANC care among the richest and richer women were about 11.46 (95% CI = 6.53-20.10) and 4.73 (95% CI = 3.37-6.65) times when compared to the poor, respectively. Furthermore, middle-class women were 2.52 (95% CI = 2.03 – 3.59) times more likely to utilize ANC services than the poorest women. Similarly, women from the poorest group were 1.91 (95% CI = 1.56 – 2.34) times more likely to use ANC when compared to the poorest group. Women living in rural areas were 0.51 (95% CI = 0.43 – 0.62) times as likely as women from urban areas to seek ANC services. Women with a history of two sets of twins in addition to other children were 0.94 (95% CI = 0.57 – 1.55) times as likely as women with only single births to use ANC but without statistically significant evidence to confirm this difference. Compared to women who give birth to only a single child, women with three sets of twins and other single children were 7.00 times (95% CI = 6.44 – 7.60) more likely to utilize ANC. Individuals with "Good" health (OR = 0.92, 95% CI: 0.76-1.11) or "Moderate" health (OR = 0.83, 95% CI: 0.65-1.07) have slightly lower odds of using antenatal care compared to those with "Very good" health, though these differences are not statistically significant. In contrast, those with "Bad" health (OR = 0.52, 95% CI: 0.34 – 0.80) or "Very bad" health (OR = 0.32, 95% CI: 0.12-0.84) have significantly lower odds of using antenatal care, indicating a strong association with reduced likelihood of antenatal care use. Multiple logistic regression results Similar trends were observed among women of different ages who used ANC during pregnancy. After adjusting for confounders, women aged 25-34 years (AOR = 1.35, 95% CI: 1.09 – 1.67) had higher odds of using ANC services than women aged between 15 and 24 (Table 4). Women aged 35-49 had 1.19 (95% CI: 0.93 – 1.53) higher odds of seeking ANC than women aged 15 to 24 but without statistical significance. Women with primary education have odds of using ANC that are 1.23 times those without education (95% CI: 0.96-1.58), though this is not statistically significant. In contrast, those with secondary education (AOR = 1.80, 95% CI: 1.43-2.27) and higher education (AOR = 4.51, 95% CI: 1.89-10.78) have significantly higher odds of using antenatal care than uneducated women. In comparison to women who were never in a union, those who are married have substantially higher odds of using antenatal care (AOR = 1.97, 95% CI: 1.46-2.66). However, women who identify as living with a partner (AOR = 1.19, 95% CI: 0.87-1.63), widowed (AOR = 1.73, 95% CI: 0.68-4.45), divorced (AOR = 0.84, 95% CI: 0.32-2.21), and no longer living together/separated (AOR = 0.98, 95% CI: 0.58-1.64) do not show statistically significant differences in ANC usage. Compared to Christians, those who practice Islam have similar odds of using ANC (AOR = 1.05, 95% CI: 0.85-1.30), with no significant difference. However, individuals practicing Traditional or other religions have significantly lower odds of using ANC (AOR = 0.43, 95% CI: 0.32-0.57). When compared to the poorest group of women, individuals in higher household wealth quintiles have progressively higher odds of using antenatal care, with poorer (AOR = 1.81, 95% CI: 1.45-2.26), middle (AOR = 2.23, 95% CI: 1.66-3.00), richer (AOR = 3.61, 95% CI: 2.44-5.35), and richest (AOR = 5.98, 95% CI: 3.20-11.17) quintiles showing significantly higher odds of ANC utilization. Relative to those in urban areas, individuals in rural areas have slightly higher odds of using ANC (AOR = 1.15, 95% CI: 0.92-1.45), but this difference is not statistically significant. Compared to single births, the odds of using ANC among women with two sets of twins and multiple children are similar (AOR = 0.98, 95% CI: 0.58-1.65), with no significant difference. Similarly, the odds among women with three sets of twins and multiple children were not applicable or assessed in this dataset because there were too few observations. Individuals in "good" health (AOR = 1.05, 95% CI: 0.86-1.28), "moderate" health (AOR = 0.94, 95% CI: 0.72-1.22), "bad" health (AOR = 0.82, 95% CI: 0.53-1.27), and "very bad" health (AOR = 0.50, 95% CI: 0.18-1.36) have similar odds of using antenatal care as those in "very good" health, with none showing statistically significant differences. DISCUSSION This study examined the associations between predisposing, enabling, and need factors and the use of ANC among women surveyed in the 2022 GDHS, using the Andersen Behavioral Health Model of Health Services Use. Among the predisposing factors, only education was significantly associated with ANC utilization, while age, marital status, and religion were not significantly associated. However, within age groups, women aged 25 to 34 years were more likely to utilize ANC services compared to younger and older women. For the enabling factors, household wealth emerged as a strong predictor of ANC use, whereas place of residence did not show a significant association. Women in the poorest wealth quintile and those adhering to traditional or religious beliefs were less likely to utilize ANC compared to their counterparts. Regarding the need factors, neither health status nor type of childbirth demonstrated a significant association with ANC utilization. Additionally, women aged 25 to 34 were more likely to receive ANC compared to younger and older age groups. On the other hand, women who are very poor and those adhering to traditional or other beliefs were less likely to seek ANC compared to their counterparts. Marital status, religion, and type of childbirth were not found to be statistically significant factors for ANC services utilization, with the exception of being married. This study provides valuable insights into the current research on maternal health in Ghana. In 2014, 87.3% of women received at least four antenatal care [ 15 ]. According to our current analysis, this shows only a slight increase to 87.5 in 2022 [ 12 ]. Overall, education and wealth were critical predictors of ANC use. In this study, Christianity and urban areas were used as the baselines for religion and residency type. Our findings revealed that women practicing Traditional and other religions were less likely to use antenatal care (ANC) services. Although Muslim women were slightly more likely than Christian women to utilize ANC services, the difference was not statistically significant. To our knowledge, our research is among the few studies considering the women’s perception of their health status as a need factor for ANC utilization [ 16 , 17 ]. Initially, we hypothesized that women in poor health would be more likely to seek ANC, as they might perceive a greater need for care due to their health issues, while women in good health might perceive themselves as healthy and not feel the need for ANC services. However, contrary to our expectations, we found that women with poorer health were less likely to seek ANC. Qualitative studies suggest this may stem from economic constraints, physical limitations, stigma, or lack of transportation. Additionally, women may normalize their symptoms or prioritize other household needs over ANC utilization despite their health condition. Understanding and addressing these barriers is pivotal for creating targeted interventions to improve ANC utilization. To address the lower ANC utilization among women in poor health, policymakers should invest in mobile health clinics and home-based ANC services that bring care directly to women facing transportation challenges. Moreover, strengthening social support programs, such as community health worker visits and financial incentives, may also reduce barriers. For women adhering to traditional beliefs, engaging community leaders and traditional healers in health promotion campaigns can help build trust and bridge cultural divides. Furthermore, it would benefit the communities by designing culturally sensitive ANC education programs that respect traditional practices while emphasizing the benefits of skilled care, which could improve service uptake among these groups. Our findings are consistent with existing studies emphasizing the importance of education, wealth, and residence type in maternal health service utilization. For instance, Dimbuene et al. [ 18 ] examined the effects of women’s education within different socioeconomic strata in Africa. Their findings revealed that women’s education positively correlates with ANC use [ 18 ]. Similarly, they found that the partner's education among pregnant women was also associated with using ANC services [ 18 ]. In addition, several studies emphasized that wealthy women were more likely to utilize ANC, as women from lower-income backgrounds often face barriers such as distance, travel, cost, and medical expenses when seeking maternal care [ 3 , 19 , 20 ]. Furthermore, several studies also identified residence as a maternal health service use predictor [ 21 , 22 , 23 , 24 ]. Women from urban areas have been consistently found to use more maternal health services than rural women [ 2 , 25 , 26 ]. In line with this, our study found that women from rural areas in Ghana are less likely to receive ANC than those in urban areas. This may be due to travel times. A study supports this by showing that women in urban areas experienced shorter travel times to healthcare services than their rural counterparts [ 27 ]. This indicates the need to build more hospitals that are accessible to women in rural regions. While age was not identified as a critical determinant of ANC utilization, our finding was similar to other studies that have found a weak association between age and ANC use [ 6 , 28 , 29 , 30 ]. In our study, the association between age and ANC utilization was moderately strong and statistically significant for women between 25 and 34 years old. However, for women between 35 and 49, there was no significance. Possible reasons why the oldest group of women may not be seeking maternal health services compared to the middle-aged group include their previous experience, which may lead them to feel more capable and less in need of regular medical supervision, potentially receiving different treatment from healthcare providers who might be less inclined to recommend pregnancy-related care for older women, and differences in support systems at their stage of life. This brings to light the need to explore why the oldest group of women is not using maternal health services compared to the middle-aged group. Despite existing literature citing marital status as a key determinant of ANC utilization [ 31 , 32 ], our findings indicate that marital status was not a determinant of ANC use. In our study, married and widowed women were more likely to seek ANC compared to those who had never been married. There were inconsistencies among women who identified as living with a partner, divorced, and separated. Another analysis that our study revealed was the association between childbirth type and ANC use. Most of the women reported having single birth, so there needed to be more data to analyze and draw conclusions from our analysis. Additionally, our research did not find religion a significant predisposing factor to using ANC. In contrast to previous studies that found Muslim women to be less likely to seek maternal health services [ 33 , 34 ], our findings did not show a statistically significant difference in ANC utilization between Muslim and Christian women in Ghana. Given this, it may be beneficial to analyze where the Muslim women in our study live, as a previous study in India found that Muslim women from urban areas were more likely to use maternal care than those from rural areas [ 35 ]. Limitations This study was subject to several significant limitations. First, the cross-sectional nature of the DHS data means our results can only show associations, not establish causality. Second, the Andersen model used in this study does not account for socio-cultural beliefs that may act as barriers to care-seeking, as it does not capture these contextual factors. To address these limitations, future research should consider using longitudinal data and incorporating qualitative or mixed-methods approaches to explore socio-cultural barriers comprehensively. Qualitative research would allow researchers to explore why there is still a disparity in ANC use even after implementing free universal maternal health in Ghana. Existing barriers, such as spouse’s approval, stigma, social support, or cultural beliefs, could not be studied through quantitative data collection. Additionally, although we adjusted for several key sociodemographic and health-related variables, the potential for residual confounding by unmeasured factors remains possible. For example, some variables did not exist and could be potential confounders, such as distance to healthcare facilities, number of living children, or healthcare provider attitudes. These factors could influence ANC utilization. Moreover, self-reported data for both health status and ANC use could introduce the possibility of misclassification bias. Participants may underreport their health condition or ANC use, which could bias the observed associations. Despite these limitations, the representative nature of the DHS data ensures that our findings are robust and reflective of the broader population. Potential interaction effects between predictors, such as between wealth and education or rural residence and health status, were not analyzed and should be explored in future research. A formal sensitivity analysis was not performed. Future studies should conduct sensitivity analyses to assess the robustness of findings under different model assumptions. Conclusion Our study points to several important directions for future research. Longitudinal studies are needed to establish causality between the identified factors and ANC utilization. Moreover, incorporating qualitative or mixed-methods approaches can help explore socio-cultural barriers to care-seeking that the DHS data does not capture. Given the study's findings, it is recommended that researchers focus on exploring why women with poor health do not seek ANC, given the implementation of the 2008 free maternal health services policy. Researchers should use a model focusing on socio-cultural factors to understand maternal health services utilization. Future studies should assess the social determinants at individual, household, and community levels to understand how they affect ANC services in Ghana. Abbreviations AOR Adjusted Odds Ratio ANC Antenatal Care CI Confidence Interval DHS Demographic and Health Survey GDHS Ghana Demographic and Health Survey OR Odds Ratio SD Standard Deviation WHO World Health Organization Declarations Availability of data and materials. The data supporting this study are available from the corresponding authors upon reasonable request. Funding declaration There is no funding for this study. Ethics declarations Ethical approval and consent to participate The Demographic Health Survey (DHS) collects nationally representative data on health and population, and it has started since 1984. The DHS is funded by the United States Agency for International Development (USAID) and implemented by ICF International. The DHS is also affiliated with the United Children’s Fund, the United Nations Population Fund, the World Health Organization, and the Joint United Nations Programme on HIV/AIDS. The data used in this study were obtained from the 2022 Ghana Demographic and Health Survey (GDHS), which was approved by the Ghana Health Service Ethical Review Committee and the Institutional Review Board (IRB) of ICF International. According to Ghana Statistical Service (GSS),” Ghana Statistics Service submitted the survey protocol to the Ethical Review Committee (ERC) of the Ghana Health Service to assure that the survey procedures were in accordance with Ghana’s ethical research standards. The ERC approved ethical clearance for the survey. ICF submitted the GDHS survey protocol to the ICF Institutional Review Board (IRB) to obtain ethical clearance assuring that the survey procedures are in accordance with US and international ethical research standards. The IRB approved ethical clearance for the survey.” Informed consent was obtained from all participants, and their confidentiality was safeguarded. For participants younger than 16, informed consent was obtained from their parents or legal guardians as part of the Ghana Demographic and Health Survey protocol. As the analysis was based on de-identified, publicly available data, no further ethical review was required. Consent for publication Not applicable. Competing interests The authors declare no competing interests. References Trends in maternal mortality 2000 to 2020: estimates by WHO, UNICEF, UNFPA, World Bank Group and UNDESA/Population Division. Geneva: World Health Organization; 2023. Babalola BI. Determinants of rural-urban differentials of antenatal care utilization in Nigeria. Afr Popul Stud. 2014;28(3):1263-1273. Adu J, Tenkorang E, Banchani E, Allison J, Mulay S. The effects of individual and community-level factors on maternal health outcomes in Ghana. PLoS ONE. 2018;13(11). WHO Reproductive Health Library. WHO recommendation on group antenatal care. Geneva: World Health Organization; 2016. Available from: https://www.who.int/publications/i/item/9789241549912. Doctor HV, Nkhana-Salimu S, Abdulsalam-Anibilowo M. Health facility delivery in sub-Saharan Africa: successes, challenges, and implications for the 2030 development agenda. BMC Public Health. 2018;18:765. Dankwah E, Zeng W, Feng C, et al. The social determinants of health facility delivery in Ghana. Reprod Health. 2019;16:101. Boah M, Adampah T, Jin B, Wan S, Mahama AB, et al. “I couldn’t buy the items so I didn’t go to deliver at the health facility” Home delivery among rural women in northern Ghana: A mixed-method analysis. PLOS ONE. 2020;15(3) Rurangirwa AA, Mogren I, Nyirazinyoye L, et al. Determinants of poor utilization of antenatal care services among recently delivered women in Rwanda; a population-based study. BMC Pregnancy Childbirth. 2017;17:142. Duodu PA, Bayuo J, Mensah JA, et al. Trends in antenatal care visits and associated factors in Ghana from 2006 to 2018. BMC Pregnancy Childbirth. 2022;22:59. Adu J, Owusu MF, Martin-Yeboah E, Ahenkan A, Gyamfi S. Maternal health care in Ghana: Challenges facing the uptake of services in the Shai Osudoku District. Women’s Reprod Health. 2021;9(4):274–290. Afaya A, Azongo TB, Dzomeku VM, Afaya RA, Salia SM, et al. Women’s knowledge and its associated factors regarding optimum utilisation of antenatal care in rural Ghana: A cross-sectional study. PLOS ONE. 2020;15(7). Ghana Statistical Service (GSS) and ICF. Ghana Demographic and Health Survey 2022: Key Indicators Report. Accra, Ghana, and Rockville, Maryland, USA: GSS and ICF; 2023. Azfredrick C. Using Anderson’s model of health service utilization to examine the use of services by adolescent girls in southeastern Nigeria. Int J Adolesc Youth. 2016;24:523-529. Kabir MR. Adopting Andersen's behavior model to identify factors influencing maternal healthcare service utilization in Bangladesh. PLOS ONE. 2021;16(11) Ghana Statistical Service (GSS), Ghana Health Service (GHS), and ICF International. Ghana Demographic and Health Survey 2014. Rockville, Maryland, USA: GSS, GHS, and ICF International; 2015. Banchani E, Tenkorang EY. Occupational types and antenatal care attendance among women in Ghana. Health Care Women Int. 2014;35(7–9):1040–64. Kim ET, Ali M, Adam H, et al. The effects of antenatal depression and women’s perception of having poor health on maternal health service utilization in Northern Ghana. Matern Child Health J. 2021;25:1697–706. doi:10.1007/s10995-021-03216-1. Tsala Dimbuene Z, Amo-Adjei J, Amugsi D, Mumah J, Izugbara CO, Beguy D. Women's education and utilization of maternal health services in Africa: a multi-country and socioeconomic status analysis. J Biosoc Sci. 2018;50(6):725–48. doi:10.1017/S0021932017000505. Omollo JV. Factors and challenges influencing mother's choice of birth attendance in Bunyala Sub-County, Kenya. Int J Sci Technol Res. 2016;5(7):101–5. Dickson KS, Darteh EK, Kumi-Kyereme A, et al. Determinants of choice of skilled antenatal care service providers in Ghana: analysis of demographic and health survey. Matern Health Neonatol Perinatol. 2018;4:4. doi:10.1186/s40748-018-0082-4. Afulani PA. Rural/urban and socioeconomic differentials in quality of antenatal care in Ghana. PLoS One. 2015;10(2). doi:10.1371/journal.pone.0117996. Amporfu E, Grépin KA. Measuring and explaining changing patterns of inequality in institutional deliveries between urban and rural women in Ghana: a decomposition analysis. Int J Equity Health. 2019;18:123. doi:10.1186/s12939-019-1025-z. Ameyaw EK, Dickson KS, Adde KS. Are Ghanaian women meeting the WHO recommended maternal healthcare (MCH) utilisation? Evidence from a national survey. BMC Pregnancy Childbirth. 2021;21:161. Appiah F, Salihu T, Fenteng JOD, Darteh AO, Kannor P, Ayerakwah PA, et al. Postnatal care utilisation among women in rural Ghana: analysis of 2014 Ghana demographic and health survey. BMC Pregnancy Childbirth. 2021;21:26. Ahinkorah BO, Kang M, Perry L, Brooks F, Hayen A. Prevalence of first adolescent pregnancy and its associated factors in sub-Saharan Africa: a multi-country analysis. PLoS One. 2021;16(2). Yang Y, Patterson A, Yimer BE. Cost-effectiveness comparison of the ReMiND program and the Newhints program for reducing neonatal mortality rates in the Muchinga Province of Zambia. Public Health Rev. 2021. Dotse-Gborgbortsi W, Nilsen K, Ofosu A, et al. Distance is “a big problem”: a geographic analysis of reported and modelled proximity to maternal health services in Ghana. BMC Pregnancy Childbirth. 2022;22:672. doi:10.1186/s12884-022-04998-0. Boah M, Mahama AB, Ayamga EA. They receive antenatal care in health facilities, yet do not deliver there: predictors of health facility delivery by women in rural Ghana. BMC Pregnancy Childbirth. 2018;18:125. doi:10.1186/s12884-018-1749-6. Amoro VA, Abiiro GA, Alatinga KA. Bypassing primary healthcare facilities for maternal healthcare in North West Ghana: socio-economic correlates and financial implications. BMC Health Serv Res. 2021;21:545. doi:10.1186/s12913-021-06573-3. Ehiawey JT-B, Manu A, Modey E, Ogum D, Atuhaire E, Torpey K. Utilisation of reproductive health services among adolescents in Ghana: analysis of the 2007 and 2017 Ghana maternal health surveys. Int J Environ Res Public Health. 2024;21:526. doi:10.3390/ijerph21050526. Sakeah E, Okawa S, Rexford Oduro A, Shibanuma A, Ansah E, Kikuchi K, Gyapong M, Owusu-Agyei S, Williams J, Debpuur C, Yeji F, Kukula VA, Enuameh Y, Asare GQ, Agyekum EO, Addai S, Sarpong D, Adjei K, Tawiah C, Yasuoka J, Nanishi K, Jimba M, Hodgson A. The Ghana Embrace Team. Determinants of attending antenatal care at least four times in rural Ghana: analysis of a cross-sectional survey. Glob Health Action. 2017;10(1):1291879. doi:10.1080/16549716.2017.1291879. Nuamah GB, Agyei-Baffour P, Mensah KA, et al. Access and utilization of maternal healthcare in a rural district in the forest belt of Ghana. BMC Pregnancy Childbirth. 2019;19:6. doi:10.1186/s12884-018-2159-5. Ganle JK. Why Muslim women in Northern Ghana do not use skilled maternal healthcare services at health facilities: a qualitative study. BMC Int Health Hum Rights. 2015;15:10. doi:10.1186/s12914-015-0048-9. Dahab R, Sakellariou D. Barriers to accessing maternal care in low income countries in Africa: a systematic review. Int J Environ Res Public Health. 2020;17(12):4292. doi:10.3390/ijerph17124292. Sk MIK, Ali B, Biswas MM, Saha MK. Disparities in three critical maternal health indicators amongst Muslims: vis-à-vis the results reflected on National Health Mission. BMC Public Health. 2022;22(1):266. doi:10.1186/s12889-022-12662-7. Tables Tables 1 to 4 are available in the Supplementary Files section Additional Declarations No competing interests reported. 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In 2020, 263 women died per 100,000 live births due to pregnancy-related causes in Ghana [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. One of the significant causes of the high maternal mortality rate is inadequate adherence to the recommended number of antenatal care (ANC) visits. Nearly a third of women in Ghana (24%) do not receive ANC services [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Antenatal care, as defined by the World Health Organization (2016), is the care provided by skilled healthcare professionals to pregnant women and adolescent girls to ensure optimal health conditions for both mother and baby during pregnancy [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Antenatal care services include measuring vital signs, urinalysis, and lab work. Providers also listen to the baby\u0026rsquo;s heartbeat, offer breastfeeding education, and assess issues such as vaginal bleeding [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. This care is essential for detecting health issues related to maternal morbidity and mortality through regular physical examinations. Additionally, ANC improves neonatal outcomes by reducing the risk of stillbirth, preterm birth, and low birth weight [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. At least four ANC visits are recommended to achieve optimal health for the mother and child [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. The number of ANC visits attended by pregnant women is crucial in improving maternal health outcomes [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Understanding the utilization of ANC in Ghana provides deeper insights into the factors contributing to the country's high maternal mortality rate. These insights allow healthcare providers and policymakers to identify gaps and understand barriers, ultimately developing effective strategies to improve maternal health outcomes.\u003c/p\u003e\u003cp\u003eMaternal deaths can occur at any stage of pregnancy\u0026mdash; before, during birth delivery, or after birth. However, the majority of studies focus on deaths during childbirth rather than those occurring before [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. This gap highlights the need for more research on ANC. Previous studies have identified various factors contributing to poor ANC utilization, including equality, wealth, age, education, and socio-demographic characteristics [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. These factors are often linked to lower use of ANC services, highlighting a significant gap in understanding the determinants influencing ANC attendance among Ghanaian women. To address Ghana\u0026rsquo;s high maternal mortality ratio, it is essential to understand the barriers to ANC utilization. While past research has provided some insights [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e], further exploration is needed to inform targeted policies and public health interventions. For instance, previous research did not consider the effect of \u0026ldquo;need factors\u0026rdquo; on the utilization of antenatal care during pregnancy [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Thus, a more inclusive analysis is essential to developing effective strategies to improve ANC utilization and reduce maternal mortality in Ghana.\u003c/p\u003e\u003cp\u003eThis study aims to fill the existing research gap by applying the Andersen Behavioral Model of Health Services to examine the social determinants associated with utilizing ANC services among a nationally representative sample of Ghanaian women of reproductive age. To expand the analysis on the need factors, we hypothesized that women in poor health would be more likely to seek ANC than women in good health. By identifying the factors influencing ANC utilization, this research seeks to provide valuable insights for policymakers and healthcare providers to develop and implement effective public health strategies. Understanding these determinants will help tailor interventions to improve ANC utilization and maternal health outcomes. The findings of this study hope to contribute to the ongoing efforts to reduce maternal mortality and ensure that more women receive the needed care during pregnancy to optimize the health and well-being of both mothers and their babies in the long run.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy data\u003c/h2\u003e\u003cp\u003eThis study used data from the 2022 Ghana Demographic Health Survey (GDHS) after permission was given from the MEASURE DHS [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. The Ghana Health Service, Ministry of Health, Ghana Statistical Service, and ICF International implemented and conducted the surveys. The 2022 Ghana DHS was designed to be representative at the national and regional levels. The survey employed a two-stage sampling design to select participants from households across all 16 regions in Ghana [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. The survey interviewed 15,014 women aged 15 to 49, with a response rate of 98% [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. The GDHS collected information on socio-demographic characteristics and reproductive health topics, such as family planning, fertility, maternal and child health, and many more [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eConceptual framework\u003c/h3\u003e\n\u003cp\u003eThis research adopted and modified Andersen\u0026rsquo;s healthcare utilization model to study ANC use in Ghana [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Andersen\u0026rsquo;s (1968) conceptual framework examines the factors influencing the consumption of acute healthcare services [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. The model aims to identify the determinants that lead to the use of health services. According to the model, health service utilization is shaped by societal, health system, and individual factors [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. In this study, individual factors drive ANC use because they influence a person\u0026rsquo;s need, perception, and ability to seek and utilize healthcare services. These individual factors are categorized into three main components: predisposing, enabling, and need factors [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Predisposing characteristics refer to factors influencing an individual\u0026rsquo;s inclination to use health services [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Predisposing factors can include age, education, marital status, and religion. Enabling factors refer to the logistical and resource-related conditions that influence an individual's ability to access healthcare services [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. These factors either facilitate or hinder health services use and include individual-level resources (such as household wealth) and community-level factors (such as place of residence) [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. In this study, enabling factors include household wealth quintile and place of residence. Lastly, need factors refer to an individual\u0026rsquo;s perceived need or evaluated need for health services [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. An individual\u0026rsquo;s perception of their current health status can prompt them to seek ANC, and the type of birth can pose risks that may necessitate ANC to prevent complications. The explanatory predictors in this study were categorized into predisposing factors (age, education, marital status, and religion), enabling factors (household wealth quintile and place of residence), and need factors (type of childbirth and health status). The type of childbirth refers to whether the most recent birth the mother had given was one child, twins, a second set of twins, or a third set of twins.\u003c/p\u003e\n\u003ch3\u003eSample\u003c/h3\u003e\n\u003cp\u003eThe study sample included 5,218 women of reproductive age (15 to 49 years) who responded to the question about whether or not they used ANC before child delivery. The inclusion criteria were that ANC be utilized at least four times before delivery. Any use of ANC less than four times is considered no use of ANC.\u003c/p\u003e\n\u003ch3\u003eOutcome variable\u003c/h3\u003e\n\u003cp\u003eANC use was the percentage of women who had completed at least four antenatal care visits during pregnancy at any of the following settings: respondent's home, government hospital, government health facility, government community health practitioners, mobile clinics, public health settings, other public facilities, private hospital/clinic, Planned Parenthood of Association of Ghana, maternity home, private medical facilities, other private facilities, other homes, and other locations. The outcome variables were coded as follows: 0\u0026thinsp;=\u0026thinsp;Did not use antenatal care and 1\u0026thinsp;=\u0026thinsp;Used antenatal care.\u003c/p\u003e\n\u003ch3\u003eExposure variables\u003c/h3\u003e\n\u003cp\u003eThe independent variables were age, education, marital status, religion, household wealth quintile, residence, childbirth type, and perceived health status. See Table\u0026nbsp;1. Maternal age did not meet the linearity assumption due to a significant quadratic term (p-value\u0026thinsp;=\u0026thinsp;0.001). Therefore, it was categorized as 15 to 24 years, 25\u0026ndash;34 years, and 35\u0026ndash;49 years. Education was organized as none: primary, secondary, and high. Marital status comprised never in union, married, living with a partner, widowed, divorced, and no longer living together or separated. In the GDHS data, the religion options were Catholic, Anglican, Methodist, Presbyterian, Pentecostal/charismatic, other Christian, Islam, Traditional/Spiritualist, no religion, and others. This study categorized Catholic, Anglican, Methodist, Presbyterian, Pentecostal/Charismatic, and other Christians as Christianity. Women without religion, Traditional/Spiritualist, or Other were grouped as Traditional and Other. The only group that remained the same was Islam. Christianity was chosen as the baseline group in this study because it represents the majority religion. This approach highlights potential disparities in care access that may arise due to religious affiliation, especially for Muslims and those practicing Traditional or other religions. The household wealth quintile was created from the Wealth index variable generated from the GDHS. Wealth information was calculated based on information on household assets using principal component analysis. The household wealth quintile was classified as poorest, poorer, middle, richer, and richest. The place of residence was separated as urban and rural. In contrast to previous studies, we are using urban as the baseline for residence type because many health interventions are designed to address challenges faced by rural populations. By using urban as a baseline, it allows the study to evaluate how living in a resource-rich environment has an effect on the use of ANC compared to rural areas. The childbirth type comprised a single birth, first twins of multiple, second twins of multiple, and third twins of multiple. Health status was identified as very good, good, moderate, bad, and very bad.\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\u003cp\u003eThis study used sampling weights provided by GDHS. All analysis was conducted in Stata BE 18. Participants with missing data on the outcome variable (ANC utilization) or key exposure variables were excluded from the analysis. Descriptive statistics, chi-squared test, and frequency and percentage distribution were used to describe the characteristics of the respondents. The chi-squared test explored the statistical significance of the differences in ANC use across exposure variables. Bivariate logistic regression examined the associations between social factors and the use of ANC. A multiple logistic regression method explored the link between ANC utilization and explanatory factors. The multiple regression model adjusted the demographic characteristics. The odds ratios and corresponding 95% confidence intervals were computed for all significant variables. An association was considered statistically significant when p\u0026thinsp;\u0026lt;\u0026thinsp;.05. The multicollinearity was investigated and not observed. Multicollinearity was assessed using Variance Inflation Factors (VIF), and no significant multicollinearity was detected, as all VIFs were below 2.\u003c/p\u003e\u003c/div\u003e"},{"header":"RESULTS","content":"\u003cp\u003e\u003cem\u003eDescriptive Results\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eFive thousand two hundred and eighteen women between the ages of 15 and 49 responded to the question on using ANC in the 2022 GDHS. As shown on Table 2, the average age for the study population was 29.6 years old (SD=6.92). About 87.5% of women reported completing at least four ANC visits during pregnancy, while 12.5% did not use ANC during pregnancy. Almost half (47.72%) of the women fell between the ages of 25 to 34 years. About one-fourth (25.68%) of the women were between 35 to 49 years old, while slightly over one-fourth (26.60%) were between 15 to 24 years. The ANC utilization rates were comparable among the age groups, with 83.7% for those aged 15-24, 89.8% for those aged 25-34, and 87.1% for those aged 35-49.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Almost half (47.07%) of the women had attained at least secondary education. The second largest group of respondents did not have a formal education (29.28%), and approximately one-sixth (15.98%) of women received primary education. The lowest number of women (7.67%) received higher education. Across all educational levels, women with higher education reported the highest ANC utilization rate (98.5%). Following this, women with secondary education reported an ANC use rate of 90.7%, while those with primary education had a rate of 84.3%. Women with no education reported the lowest ANC utilization rate of 81.2%. The higher the education level, the greater the utilization rate of ANC services.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;The majority (67.86%) of women in this study were married. There were 18.05% of women who reported living with their partner but did not identify as married. The third largest group (9.85%) of women was never in union. Women who were widowed (0.92%), divorced (0.57%), or no longer living together with their partner (2.74%) accounted for the smallest groups of respondents. ANC utilization rates were similar across all marital statuses: never in union (83.7%), married (88.9%), living with a partner (85.1%), widowed (87.5%), divorced (80.0%), and no longer living together or separated (83.2%).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Most of the women (62.50%) were Christians. The second largest religious group was Muslims (33.23%), followed by traditional and other beliefs (5.27%). ANC utilization rates were similar among Christian and Muslim women, but there was a difference among women with traditional and other beliefs. ANC use rates were 88.7% among Christian women and 88.4% among Muslim women. The ANC utilization rate was significantly lower among women with traditional or other beliefs at 67.3%.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Women from the poorest wealth quintile comprised about 31.79% of the respondents, while the poorer group included almost one-fourth (24.80%) of the respondents, and the middle-class group was 18.15%. The richer (18.15%) and richest (14.33%) included the least respondents in this study. Among all classes of wealth, women from the middle (90.4%), richer (94.7%), and richest (97.7%) categories were reported to have the highest ANC utilization rates. Women from the poorer group had an 87.7% ANC utilization rate. In contrast, women from the poorest group reported a significantly lower ANC use rate (78.9%) than all other groups. \u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;More than half (58.59%) of the women lived in rural areas. Among these urban respondents, about 84.7% used at least four ANC during pregnancy. On the other hand, 41.41% of the women lived in urban areas. Compared to rural dwellers, women from urban areas had a higher ANC utilization rate (91.5%).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Most women (97.32%) reported having a history of only one birth. A smaller proportion, 2.61%, reported having two sets of twins in addition to their other single children, while 0.08% of women had three sets of twins in addition to their other single children. No woman reported having only one set of twins. Among all groups of childbirth type, women with three sets of twins in addition to their other single child had the highest ANC use rate (100%). Similar ANC utilization rates were observed among women with a single birth (87.5%) and two sets of twins in addition to their other single children (86.8%).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Among all health statuses, women with “good” health (48.75%) accounted for most of the respondents, followed by women with “very good” health (32.60%). A smaller portion (15.25%) of the respondents reported having “moderate health,” while very few (2.99% and 0.40%) of the women had “bad” and “very bad” health, respectively. All health statuses, except \"very bad,\" showed similar ANC utilization rates, each exceeding 80%: very good (88.5%), good (87.7%), moderate (86.6%), and bad (80.1%). In contrast, the \"very bad\" health status had a notably lower ANC utilization rate of 71.4%.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eBivariate logistic regression results\u0026nbsp; \u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;The bivariable analysis produced point estimates of a little over one for women aged 25-34 years (Unadjusted OR =1.72; 95% CI = 1.42-2.08) and those aged 35-49 years (Unadjusted OR = 1.31; 95% CI = 1.06-1.63%) when compared to women aged 15-24 years (Table 3). For education, the association between primary education and the use of ANC is not statistically significant at the 5% level. This indicates that the OR=1.25; CI = 0.99-1.56 may be due to random chance rather than a true effect. Relative to women without education, women with secondary education were 2.27 (95% CI = 1.88-2.74) times to use ANC, and higher education was 15.25 (95% CI = 6.74-34.50%) times to use ANC. The OR = 0.97; CI = 0.81-1.17 for Muslim women indicates a slight decrease in the likelihood of using antenatal care compared to Christianity, but the p-value of 0.746 suggests no statistically significant association. Women who identify as traditional or other religions are 0.26 (95% CI = 0.20-0.34) times as likely as Christians to seek ANC care, indicating a slightly lower likelihood.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe odds of seeking ANC care among the richest and richer women were about 11.46 (95% CI = 6.53-20.10) and 4.73 (95% CI = 3.37-6.65) times when compared to the poor, respectively. Furthermore, middle-class women were 2.52 (95% CI = 2.03 – 3.59) times more likely to utilize ANC services than the poorest women. Similarly, women from the poorest group were 1.91 (95% CI = 1.56 – 2.34) times more likely to use ANC when compared to the poorest group. Women living in rural areas were 0.51 (95% CI = 0.43 – 0.62) times as likely as women from urban areas to seek ANC services.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWomen with a history of two sets of twins in addition to other children were 0.94 (95% CI = 0.57 – 1.55) times as likely as women with only single births to use ANC but without statistically significant evidence to confirm this difference. Compared to women who give birth to only a single child, women with three sets of twins and other single children were 7.00 times (95% CI = 6.44 – 7.60) more likely to utilize ANC. Individuals with \"Good\" health (OR = 0.92, 95% CI: 0.76-1.11) or \"Moderate\" health (OR = 0.83, 95% CI: 0.65-1.07) have slightly lower odds of using antenatal care compared to those with \"Very good\" health, though these differences are not statistically significant. In contrast, those with \"Bad\" health (OR = 0.52, 95% CI: 0.34 – 0.80) or \"Very bad\" health (OR = 0.32, 95% CI: 0.12-0.84) have significantly lower odds of using antenatal care, indicating a strong association with reduced likelihood of antenatal care use.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eMultiple logistic regression results\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Similar trends were observed among women of different ages who used ANC during pregnancy. After adjusting for confounders, women aged 25-34 years (AOR = 1.35, 95% CI: 1.09 – 1.67) had higher odds of using ANC services than women aged between 15 and 24 (Table 4). Women aged 35-49 had 1.19 (95% CI: 0.93 – 1.53) higher odds of seeking ANC than women aged 15 to 24 but without statistical significance. Women with primary education have odds of using ANC that are 1.23 times those without education (95% CI: 0.96-1.58), though this is not statistically significant. In contrast, those with secondary education (AOR = 1.80, 95% CI: 1.43-2.27) and higher education (AOR = 4.51, 95% CI: 1.89-10.78) have significantly higher odds of using antenatal care than uneducated women. In comparison to women who were never in a union, those who are married have substantially higher odds of using antenatal care (AOR = 1.97, 95% CI: 1.46-2.66). However, women who identify as living with a partner (AOR = 1.19, 95% CI: 0.87-1.63), widowed (AOR = 1.73, 95% CI: 0.68-4.45), divorced (AOR = 0.84, 95% CI: 0.32-2.21), and no longer living together/separated (AOR = 0.98, 95% CI: 0.58-1.64) do not show statistically significant differences in ANC usage. Compared to Christians, those who practice Islam have similar odds of using ANC (AOR = 1.05, 95% CI: 0.85-1.30), with no significant difference. However, individuals practicing Traditional or other religions have significantly lower odds of using ANC (AOR = 0.43, 95% CI: 0.32-0.57).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWhen compared to the poorest group of women, individuals in higher household wealth quintiles have progressively higher odds of using antenatal care, with poorer (AOR = 1.81, 95% CI: 1.45-2.26), middle (AOR = 2.23, 95% CI: 1.66-3.00), richer (AOR = 3.61, 95% CI: 2.44-5.35), and richest (AOR = 5.98, 95% CI: 3.20-11.17) quintiles showing significantly higher odds of ANC utilization. Relative to those in urban areas, individuals in rural areas have slightly higher odds of using ANC (AOR = 1.15, 95% CI: 0.92-1.45), but this difference is not statistically significant.\u003c/p\u003e\n\u003cp\u003eCompared to single births, the odds of using ANC among women with two sets of twins and multiple children are similar (AOR = 0.98, 95% CI: 0.58-1.65), with no significant difference. Similarly, the odds among women with three sets of twins and multiple children were not applicable or assessed in this dataset because there were too few observations. Individuals in \"good\" health (AOR = 1.05, 95% CI: 0.86-1.28), \"moderate\" health (AOR = 0.94, 95% CI: 0.72-1.22), \"bad\" health (AOR = 0.82, 95% CI: 0.53-1.27), and \"very bad\" health (AOR = 0.50, 95% CI: 0.18-1.36) have similar odds of using antenatal care as those in \"very good\" health, with none showing statistically significant differences.\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThis study examined the associations between predisposing, enabling, and need factors and the use of ANC among women surveyed in the 2022 GDHS, using the Andersen Behavioral Health Model of Health Services Use. Among the predisposing factors, only education was significantly associated with ANC utilization, while age, marital status, and religion were not significantly associated. However, within age groups, women aged 25 to 34 years were more likely to utilize ANC services compared to younger and older women. For the enabling factors, household wealth emerged as a strong predictor of ANC use, whereas place of residence did not show a significant association. Women in the poorest wealth quintile and those adhering to traditional or religious beliefs were less likely to utilize ANC compared to their counterparts. Regarding the need factors, neither health status nor type of childbirth demonstrated a significant association with ANC utilization.\u003c/p\u003e\u003cp\u003eAdditionally, women aged 25 to 34 were more likely to receive ANC compared to younger and older age groups. On the other hand, women who are very poor and those adhering to traditional or other beliefs were less likely to seek ANC compared to their counterparts. Marital status, religion, and type of childbirth were not found to be statistically significant factors for ANC services utilization, with the exception of being married.\u003c/p\u003e\u003cp\u003eThis study provides valuable insights into the current research on maternal health in Ghana. In 2014, 87.3% of women received at least four antenatal care [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. According to our current analysis, this shows only a slight increase to 87.5 in 2022 [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Overall, education and wealth were critical predictors of ANC use. In this study, Christianity and urban areas were used as the baselines for religion and residency type. Our findings revealed that women practicing Traditional and other religions were less likely to use antenatal care (ANC) services. Although Muslim women were slightly more likely than Christian women to utilize ANC services, the difference was not statistically significant. To our knowledge, our research is among the few studies considering the women\u0026rsquo;s perception of their health status as a need factor for ANC utilization [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Initially, we hypothesized that women in poor health would be more likely to seek ANC, as they might perceive a greater need for care due to their health issues, while women in good health might perceive themselves as healthy and not feel the need for ANC services. However, contrary to our expectations, we found that women with poorer health were less likely to seek ANC. Qualitative studies suggest this may stem from economic constraints, physical limitations, stigma, or lack of transportation. Additionally, women may normalize their symptoms or prioritize other household needs over ANC utilization despite their health condition. Understanding and addressing these barriers is pivotal for creating targeted interventions to improve ANC utilization. To address the lower ANC utilization among women in poor health, policymakers should invest in mobile health clinics and home-based ANC services that bring care directly to women facing transportation challenges. Moreover, strengthening social support programs, such as community health worker visits and financial incentives, may also reduce barriers. For women adhering to traditional beliefs, engaging community leaders and traditional healers in health promotion campaigns can help build trust and bridge cultural divides. Furthermore, it would benefit the communities by designing culturally sensitive ANC education programs that respect traditional practices while emphasizing the benefits of skilled care, which could improve service uptake among these groups.\u003c/p\u003e\u003cp\u003eOur findings are consistent with existing studies emphasizing the importance of education, wealth, and residence type in maternal health service utilization. For instance, Dimbuene et al. [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] examined the effects of women\u0026rsquo;s education within different socioeconomic strata in Africa. Their findings revealed that women\u0026rsquo;s education positively correlates with ANC use [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Similarly, they found that the partner's education among pregnant women was also associated with using ANC services [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. In addition, several studies emphasized that wealthy women were more likely to utilize ANC, as women from lower-income backgrounds often face barriers such as distance, travel, cost, and medical expenses when seeking maternal care [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Furthermore, several studies also identified residence as a maternal health service use predictor [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Women from urban areas have been consistently found to use more maternal health services than rural women [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. In line with this, our study found that women from rural areas in Ghana are less likely to receive ANC than those in urban areas. This may be due to travel times. A study supports this by showing that women in urban areas experienced shorter travel times to healthcare services than their rural counterparts [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. This indicates the need to build more hospitals that are accessible to women in rural regions. While age was not identified as a critical determinant of ANC utilization, our finding was similar to other studies that have found a weak association between age and ANC use [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. In our study, the association between age and ANC utilization was moderately strong and statistically significant for women between 25 and 34 years old. However, for women between 35 and 49, there was no significance. Possible reasons why the oldest group of women may not be seeking maternal health services compared to the middle-aged group include their previous experience, which may lead them to feel more capable and less in need of regular medical supervision, potentially receiving different treatment from healthcare providers who might be less inclined to recommend pregnancy-related care for older women, and differences in support systems at their stage of life. This brings to light the need to explore why the oldest group of women is not using maternal health services compared to the middle-aged group.\u003c/p\u003e\u003cp\u003eDespite existing literature citing marital status as a key determinant of ANC utilization [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e], our findings indicate that marital status was not a determinant of ANC use. In our study, married and widowed women were more likely to seek ANC compared to those who had never been married. There were inconsistencies among women who identified as living with a partner, divorced, and separated. Another analysis that our study revealed was the association between childbirth type and ANC use. Most of the women reported having single birth, so there needed to be more data to analyze and draw conclusions from our analysis. Additionally, our research did not find religion a significant predisposing factor to using ANC. In contrast to previous studies that found Muslim women to be less likely to seek maternal health services [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e], our findings did not show a statistically significant difference in ANC utilization between Muslim and Christian women in Ghana. Given this, it may be beneficial to analyze where the Muslim women in our study live, as a previous study in India found that Muslim women from urban areas were more likely to use maternal care than those from rural areas [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e].\u003c/p\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003eLimitations\u003c/h2\u003e\u003cp\u003eThis study was subject to several significant limitations. First, the cross-sectional nature of the DHS data means our results can only show associations, not establish causality. Second, the Andersen model used in this study does not account for socio-cultural beliefs that may act as barriers to care-seeking, as it does not capture these contextual factors. To address these limitations, future research should consider using longitudinal data and incorporating qualitative or mixed-methods approaches to explore socio-cultural barriers comprehensively. Qualitative research would allow researchers to explore why there is still a disparity in ANC use even after implementing free universal maternal health in Ghana. Existing barriers, such as spouse\u0026rsquo;s approval, stigma, social support, or cultural beliefs, could not be studied through quantitative data collection.\u003c/p\u003e\u003cp\u003eAdditionally, although we adjusted for several key sociodemographic and health-related variables, the potential for residual confounding by unmeasured factors remains possible. For example, some variables did not exist and could be potential confounders, such as distance to healthcare facilities, number of living children, or healthcare provider attitudes. These factors could influence ANC utilization. Moreover, self-reported data for both health status and ANC use could introduce the possibility of misclassification bias. Participants may underreport their health condition or ANC use, which could bias the observed associations.\u003c/p\u003e\u003cp\u003eDespite these limitations, the representative nature of the DHS data ensures that our findings are robust and reflective of the broader population. Potential interaction effects between predictors, such as between wealth and education or rural residence and health status, were not analyzed and should be explored in future research. A formal sensitivity analysis was not performed. Future studies should conduct sensitivity analyses to assess the robustness of findings under different model assumptions.\u003c/p\u003e\u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eOur study points to several important directions for future research. Longitudinal studies are needed to establish causality between the identified factors and ANC utilization. Moreover, incorporating qualitative or mixed-methods approaches can help explore socio-cultural barriers to care-seeking that the DHS data does not capture. Given the study's findings, it is recommended that researchers focus on exploring why women with poor health do not seek ANC, given the implementation of the 2008 free maternal health services policy. Researchers should use a model focusing on socio-cultural factors to understand maternal health services utilization. Future studies should assess the social determinants at individual, household, and community levels to understand how they affect ANC services in Ghana.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eAOR\u003c/b\u003e\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\"\u003e\u003cb\u003eANC\u003c/b\u003e\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\"\u003e\u003cb\u003eCI\u003c/b\u003e\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\"\u003e\u003cb\u003eDHS\u003c/b\u003e\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\"\u003e\u003cb\u003eGDHS\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eGhana Demographic and Health Survey\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eOR\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eOdds Ratio\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eSD\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eStandard Deviation\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eWHO\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eWorld Health Organization\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAvailability of data and materials.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data supporting this study are available from the corresponding authors upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding declaration\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThere is no funding for this study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics declarations\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical approval and consent to participate\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe Demographic Health Survey (DHS) collects nationally representative data on health and population, and it has started since 1984. The DHS is funded by the United States Agency for International Development (USAID) and implemented by ICF International. The DHS is also affiliated with the United Children’s Fund, the United Nations Population Fund, the World Health Organization, and the Joint United Nations Programme on HIV/AIDS. The data used in this study were obtained from the 2022 Ghana Demographic and Health Survey (GDHS), which was approved by the Ghana Health Service Ethical Review Committee and the Institutional Review Board (IRB) of ICF International. According to Ghana Statistical Service (GSS),” Ghana Statistics Service submitted the survey protocol to the Ethical Review Committee (ERC) of the Ghana Health Service to assure that the survey procedures were in accordance with Ghana’s ethical research standards. The ERC approved ethical clearance for the survey. ICF submitted the GDHS survey protocol to the ICF Institutional Review Board (IRB) to obtain ethical clearance assuring that the survey procedures are in accordance with US and international ethical research standards. The IRB approved ethical clearance for the survey.” Informed consent was obtained from all participants, and their confidentiality was safeguarded. For participants younger than 16, informed consent was obtained from their parents or legal guardians as part of the Ghana Demographic and Health Survey protocol. As the analysis was based on de-identified, publicly available data, no further ethical review was required.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eConsent for publication\u003c/p\u003e\n\u003cp\u003eNot applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCompeting interests\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eTrends in maternal mortality 2000 to 2020: estimates by WHO, UNICEF, UNFPA, World Bank Group and UNDESA/Population Division. Geneva: World Health Organization; 2023.\u003c/li\u003e\n\u003cli\u003eBabalola BI. Determinants of rural-urban differentials of antenatal care utilization in Nigeria. Afr Popul Stud. 2014;28(3):1263-1273.\u003c/li\u003e\n\u003cli\u003eAdu J, Tenkorang E, Banchani E, Allison J, Mulay S. The effects of individual and community-level factors on maternal health outcomes in Ghana. PLoS ONE. 2018;13(11). \u003c/li\u003e\n\u003cli\u003eWHO Reproductive Health Library. WHO recommendation on group antenatal care. Geneva: World Health Organization; 2016. Available from: https://www.who.int/publications/i/item/9789241549912.\u003c/li\u003e\n\u003cli\u003eDoctor HV, Nkhana-Salimu S, Abdulsalam-Anibilowo M. Health facility delivery in sub-Saharan Africa: successes, challenges, and implications for the 2030 development agenda. BMC Public Health. 2018;18:765.\u003c/li\u003e\n\u003cli\u003eDankwah E, Zeng W, Feng C, et al. The social determinants of health facility delivery in Ghana. Reprod Health. 2019;16:101.\u003c/li\u003e\n\u003cli\u003eBoah M, Adampah T, Jin B, Wan S, Mahama AB, et al. \u0026ldquo;I couldn\u0026rsquo;t buy the items so I didn\u0026rsquo;t go to deliver at the health facility\u0026rdquo; Home delivery among rural women in northern Ghana: A mixed-method analysis. PLOS ONE. 2020;15(3)\u003c/li\u003e\n\u003cli\u003eRurangirwa AA, Mogren I, Nyirazinyoye L, et al. Determinants of poor utilization of antenatal care services among recently delivered women in Rwanda; a population-based study. BMC Pregnancy Childbirth. 2017;17:142.\u003c/li\u003e\n\u003cli\u003eDuodu PA, Bayuo J, Mensah JA, et al. Trends in antenatal care visits and associated factors in Ghana from 2006 to 2018. BMC Pregnancy Childbirth. 2022;22:59.\u003c/li\u003e\n\u003cli\u003eAdu J, Owusu MF, Martin-Yeboah E, Ahenkan A, Gyamfi S. Maternal health care in Ghana: Challenges facing the uptake of services in the Shai Osudoku District. Women\u0026rsquo;s Reprod Health. 2021;9(4):274\u0026ndash;290.\u003c/li\u003e\n\u003cli\u003eAfaya A, Azongo TB, Dzomeku VM, Afaya RA, Salia SM, et al. Women\u0026rsquo;s knowledge and its associated factors regarding optimum utilisation of antenatal care in rural Ghana: A cross-sectional study. PLOS ONE. 2020;15(7).\u003c/li\u003e\n\u003cli\u003eGhana Statistical Service (GSS) and ICF. Ghana Demographic and Health Survey 2022: Key Indicators Report. Accra, Ghana, and Rockville, Maryland, USA: GSS and ICF; 2023.\u003c/li\u003e\n\u003cli\u003eAzfredrick C. Using Anderson\u0026rsquo;s model of health service utilization to examine the use of services by adolescent girls in southeastern Nigeria. Int J Adolesc Youth. 2016;24:523-529.\u003c/li\u003e\n\u003cli\u003eKabir MR. Adopting Andersen\u0026apos;s behavior model to identify factors influencing maternal healthcare service utilization in Bangladesh. PLOS ONE. 2021;16(11)\u003c/li\u003e\n\u003cli\u003eGhana Statistical Service (GSS), Ghana Health Service (GHS), and ICF International. Ghana Demographic and Health Survey 2014. Rockville, Maryland, USA: GSS, GHS, and ICF International; 2015.\u003c/li\u003e\n\u003cli\u003eBanchani E, Tenkorang EY. Occupational types and antenatal care attendance among women in Ghana. Health Care Women Int. 2014;35(7\u0026ndash;9):1040\u0026ndash;64.\u003c/li\u003e\n\u003cli\u003eKim ET, Ali M, Adam H, et al. The effects of antenatal depression and women\u0026rsquo;s perception of having poor health on maternal health service utilization in Northern Ghana. Matern Child Health J. 2021;25:1697\u0026ndash;706. doi:10.1007/s10995-021-03216-1.\u003c/li\u003e\n\u003cli\u003eTsala Dimbuene Z, Amo-Adjei J, Amugsi D, Mumah J, Izugbara CO, Beguy D. Women\u0026apos;s education and utilization of maternal health services in Africa: a multi-country and socioeconomic status analysis. J Biosoc Sci. 2018;50(6):725\u0026ndash;48. doi:10.1017/S0021932017000505.\u003c/li\u003e\n\u003cli\u003eOmollo JV. Factors and challenges influencing mother\u0026apos;s choice of birth attendance in Bunyala Sub-County, Kenya. Int J Sci Technol Res. 2016;5(7):101\u0026ndash;5.\u003c/li\u003e\n\u003cli\u003eDickson KS, Darteh EK, Kumi-Kyereme A, et al. Determinants of choice of skilled antenatal care service providers in Ghana: analysis of demographic and health survey. Matern Health Neonatol Perinatol. 2018;4:4. doi:10.1186/s40748-018-0082-4.\u003c/li\u003e\n\u003cli\u003eAfulani PA. Rural/urban and socioeconomic differentials in quality of antenatal care in Ghana. PLoS One. 2015;10(2). doi:10.1371/journal.pone.0117996.\u003c/li\u003e\n\u003cli\u003eAmporfu E, Gr\u0026eacute;pin KA. Measuring and explaining changing patterns of inequality in institutional deliveries between urban and rural women in Ghana: a decomposition analysis. Int J Equity Health. 2019;18:123. doi:10.1186/s12939-019-1025-z.\u003c/li\u003e\n\u003cli\u003eAmeyaw EK, Dickson KS, Adde KS. Are Ghanaian women meeting the WHO recommended maternal healthcare (MCH) utilisation? Evidence from a national survey. BMC Pregnancy Childbirth. 2021;21:161.\u003c/li\u003e\n\u003cli\u003eAppiah F, Salihu T, Fenteng JOD, Darteh AO, Kannor P, Ayerakwah PA, et al. Postnatal care utilisation among women in rural Ghana: analysis of 2014 Ghana demographic and health survey. BMC Pregnancy Childbirth. 2021;21:26.\u003c/li\u003e\n\u003cli\u003eAhinkorah BO, Kang M, Perry L, Brooks F, Hayen A. Prevalence of first adolescent pregnancy and its associated factors in sub-Saharan Africa: a multi-country analysis. PLoS One. 2021;16(2).\u003c/li\u003e\n\u003cli\u003eYang Y, Patterson A, Yimer BE. Cost-effectiveness comparison of the ReMiND program and the Newhints program for reducing neonatal mortality rates in the Muchinga Province of Zambia. Public Health Rev. 2021.\u003c/li\u003e\n\u003cli\u003eDotse-Gborgbortsi W, Nilsen K, Ofosu A, et al. Distance is \u0026ldquo;a big problem\u0026rdquo;: a geographic analysis of reported and modelled proximity to maternal health services in Ghana. BMC Pregnancy Childbirth. 2022;22:672. doi:10.1186/s12884-022-04998-0.\u003c/li\u003e\n\u003cli\u003eBoah M, Mahama AB, Ayamga EA. They receive antenatal care in health facilities, yet do not deliver there: predictors of health facility delivery by women in rural Ghana. BMC Pregnancy Childbirth. 2018;18:125. doi:10.1186/s12884-018-1749-6.\u003c/li\u003e\n\u003cli\u003eAmoro VA, Abiiro GA, Alatinga KA. Bypassing primary healthcare facilities for maternal healthcare in North West Ghana: socio-economic correlates and financial implications. BMC Health Serv Res. 2021;21:545. doi:10.1186/s12913-021-06573-3.\u003c/li\u003e\n\u003cli\u003eEhiawey JT-B, Manu A, Modey E, Ogum D, Atuhaire E, Torpey K. Utilisation of reproductive health services among adolescents in Ghana: analysis of the 2007 and 2017 Ghana maternal health surveys. Int J Environ Res Public Health. 2024;21:526. doi:10.3390/ijerph21050526.\u003c/li\u003e\n\u003cli\u003eSakeah E, Okawa S, Rexford Oduro A, Shibanuma A, Ansah E, Kikuchi K, Gyapong M, Owusu-Agyei S, Williams J, Debpuur C, Yeji F, Kukula VA, Enuameh Y, Asare GQ, Agyekum EO, Addai S, Sarpong D, Adjei K, Tawiah C, Yasuoka J, Nanishi K, Jimba M, Hodgson A. The Ghana Embrace Team. Determinants of attending antenatal care at least four times in rural Ghana: analysis of a cross-sectional survey. Glob Health Action. 2017;10(1):1291879. doi:10.1080/16549716.2017.1291879.\u003c/li\u003e\n\u003cli\u003eNuamah GB, Agyei-Baffour P, Mensah KA, et al. Access and utilization of maternal healthcare in a rural district in the forest belt of Ghana. BMC Pregnancy Childbirth. 2019;19:6. doi:10.1186/s12884-018-2159-5.\u003c/li\u003e\n\u003cli\u003eGanle JK. Why Muslim women in Northern Ghana do not use skilled maternal healthcare services at health facilities: a qualitative study. BMC Int Health Hum Rights. 2015;15:10. doi:10.1186/s12914-015-0048-9.\u003c/li\u003e\n\u003cli\u003eDahab R, Sakellariou D. Barriers to accessing maternal care in low income countries in Africa: a systematic review. Int J Environ Res Public Health. 2020;17(12):4292. doi:10.3390/ijerph17124292.\u003c/li\u003e\n\u003cli\u003eSk MIK, Ali B, Biswas MM, Saha MK. Disparities in three critical maternal health indicators amongst Muslims: vis-\u0026agrave;-vis the results reflected on National Health Mission. BMC Public Health. 2022;22(1):266. doi:10.1186/s12889-022-12662-7.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTables 1 to 4 are available in the Supplementary Files section\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-pregnancy-and-childbirth","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"prch","sideBox":"Learn more about [BMC Pregnancy and Childbirth](http://bmcpregnancychildbirth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/prch/default.aspx","title":"BMC Pregnancy and Childbirth","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"antenatal care, maternal health, predisposing factors, enabling factors, need factors","lastPublishedDoi":"10.21203/rs.3.rs-5245471/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5245471/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eAntenatal care (ANC) is crucial for improving maternal health outcomes, yet full utilization remains an issue in some parts of Ghana. Using the Andersen Behavioral Model, this study examines the social determinants influencing ANC utilization among reproductive-age women in Ghana.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eData from the 2022 Ghana Demographic and Health Survey (GDHS) were analyzed, including 5,218 women aged 15\u0026ndash;49. The Andersen Model guided the examination of predisposing (age, education, marital status, religion), enabling (wealth quintile, residence), and need factors (childbirth type, health status). Descriptive statistics and logistic regressions were employed to identify significant predictors of ANC utilization.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eOverall, 87.5% of women sought at least four ANC services. Factors significantly associated with increased likelihood of ANC use included higher education (AOR\u0026thinsp;=\u0026thinsp;4.51, 95% CI: 1.89\u0026ndash;10.78) and being in the highest wealth quintile (AOR\u0026thinsp;=\u0026thinsp;5.98, 95% CI: 3.20\u0026ndash;11.17). Additionally, women aged 25 to 34 (AOR\u0026thinsp;=\u0026thinsp;1.35, 95% CI: 1.09\u0026ndash;1.67) were more likely to use ANC compared to other age groups. In contrast, women in very poor health (AOR\u0026thinsp;=\u0026thinsp;0.50, 95% CI: 0.18\u0026ndash;1.36) and those adhering to traditional or other beliefs (AOR\u0026thinsp;=\u0026thinsp;0.43, 95% CI: 0.32\u0026ndash;0.57) were less likely to seek ANC. Marital status, religion, residence, and type of childbirth were not found to be statistically significant factors for ANC services utilization, with the exception of being married.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eEducation, marital status, and wealth were crucial determinants of ANC utilization, highlighting the importance of addressing socio-economic and cultural barriers to improve ANC coverage. Given the implementation of Ghana\u0026rsquo;s free maternal health services policy, future studies should explore the indirect costs and barriers that prevent women from using ANC.\u003c/p\u003e","manuscriptTitle":"Social Determinants of Antenatal Care Utilization Among Reproductive Age Women: An Analysis of 2022 Ghana Demographic and Health Survey","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-24 18:36:17","doi":"10.21203/rs.3.rs-5245471/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-11-12T17:59:03+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-09T03:06:30+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-08T03:29:58+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-10-23T17:43:23+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"53190542107848511482908589896556573908","date":"2025-10-20T15:53:17+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"332887009163807373156923182672754898645","date":"2025-10-17T23:26:48+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"313875160560298884486015015344624347635","date":"2025-10-17T08:52:20+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"67628090527996350628938382466442649355","date":"2025-10-16T09:58:10+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"235470765653370964929906873713526718122","date":"2025-10-10T15:05:14+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-10-10T13:55:07+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-10-10T13:54:35+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-05-10T07:58:38+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Pregnancy and Childbirth","date":"2025-05-01T05:05:56+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-pregnancy-and-childbirth","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"prch","sideBox":"Learn more about [BMC Pregnancy and Childbirth](http://bmcpregnancychildbirth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/prch/default.aspx","title":"BMC Pregnancy and Childbirth","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"c31ba04f-0306-4989-9af8-fc86f704de6a","owner":[],"postedDate":"October 24th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2026-01-19T16:48:54+00:00","versionOfRecord":{"articleIdentity":"rs-5245471","link":"https://doi.org/10.1186/s12884-025-08632-7","journal":{"identity":"bmc-pregnancy-and-childbirth","isVorOnly":false,"title":"BMC Pregnancy and Childbirth"},"publishedOn":"2026-01-12 16:30:46","publishedOnDateReadable":"January 12th, 2026"},"versionCreatedAt":"2025-10-24 18:36:17","video":"","vorDoi":"10.1186/s12884-025-08632-7","vorDoiUrl":"https://doi.org/10.1186/s12884-025-08632-7","workflowStages":[]},"version":"v1","identity":"rs-5245471","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5245471","identity":"rs-5245471","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}