The Association Between Media Exposure and Health Facility Delivery in Ghana

The Association Between Media Exposure and Health Facility Delivery in Ghana | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article The Association Between Media Exposure and Health Facility Delivery in Ghana Ya Yang, Safa Uraizee, Mariam Hernandez Mendoza, Joseph Adu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6925215/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Despite a free maternal healthcare policy, many women in Ghana still give birth outside of health facilities. While prior research has examined how sociodemographic factors influence facility-based delivery, little is known about the role of various types of media exposure. This study examines the association between media exposure and the use of health facilities for delivery among women in Ghana. Methods: This study analyzed nationally representative data from the 2022 Ghana Demographic and Health Survey, focusing on 5,757 women aged 15–49. Descriptive statistics and logistic regressions were conducted to assess the association between media exposure and health facility delivery. Results: Among the respondents, 85.3% delivered at a health facility. Higher education, wealth, and urban residence were significantly associated with health facility delivery. Mobile phone ownership (AOR = 1.59, 95% CI: 1.35–1.87), television viewership (AOR = 1.30, 95% CI: 1.08–1.56), and Internet access (AOR = 1.83, 95% CI: 1.49–2.26) were all significantly associated with increased odds of facility-based delivery. Radio and newspaper exposure were not significant predictors in the adjusted analysis. Conclusions: Media exposure, particularly through mobile phones, television, and the Internet, significantly shapes maternal health behaviors and facility delivery in Ghana. Public health strategies to reduce maternal mortality should leverage these media channels to deliver targeted, culturally relevant health messages encouraging safe childbirth practices. media exposure health facility delivery maternal health digital health Introduction In Ghana, although maternal health services were offered free of charge through the National Health Insurance Scheme (NHIS), many women continued to give birth outside of health facilities [ 1 , 2 ]. To address financial barriers and access to skilled birth attendants, the Free Maternal Health Care Policy (FMHCP) was introduced in 2008 [ 3 – 5 ]. Prior to the policy, only 43% of births occurred in health facilities in 2003 [ 6 ]. After the implementation of FMHCP, the proportion of births occurring in health facilities increased to 73% in 2014 and 85% in 2022 [ 7 – 9 ]. Although this upward trend is promising, it still leaves many women without access to skilled birth attendants. Delivering in a health facility is essential for the mother and child because it ensures that trained healthcare professionals, such as midwives, nurses, and doctors, are present to manage childbirth and any related complications [ 10 – 12 ]. Research has shown that health facility delivery is associated with reductions in maternal mortality, neonatal deaths, and obstetric complications, especially in emergencies such as hemorrhage, sepsis, and obstructed labor [ 13 , 14 ]. Given that many women still deliver at home despite free access to maternal care, this raises concerns about structural barriers and behavioral determinants that limit the utilization of life-saving services. Addressing these gaps is essential to reducing global maternal and neonatal mortality in Ghana. Extensive literature has examined the role of sociodemographic factors in shaping health facility use in Ghana [ 10 , 13 , 15 ]. Factors such as maternal education, household wealth, urban residence, and parity have consistently been found to influence the likelihood of delivering at a health facility [ 13 , 16 ]. Women with higher education are more likely to be informed about the benefits of skilled care and are better equipped to navigate health systems [ 10 ]. Wealthier households can afford transportation and associated delivery costs, and urban residents benefit from closer proximity to health infrastructure [ 15 ]. However, existing literature often overlooks the rapidly evolving information ecosystem modern women can use to make reproductive decisions. In recent years, there has been a rapid increase in access to digital technology and mobile communication tools worldwide [ 17 , 18 ]. These tools are often referred to as mass media, encompassing various media, including radio, television, newspapers, magazines, phones, and posters, to promote health [ 19 – 21 ]. The mass media allows women to be exposed to information about appropriate health services [ 22 , 23 ]. It can assist mothers in understanding the importance of healthcare utilization by providing health information through visually appealing, audio messages, and written letters [ 24 – 26 ]. Research has shown that mass media exposure, particularly through television and radio, is positively associated with using health facilities [ 23 , 27 ]. While Aboagye et al. examined the association between mass media exposure and maternal health care service utilization among 28 countries in sub-Saharan Africa and included Ghana, their study focused specifically on skilled birth attendance rather than place of delivery [ 26 ]. This distinction is important, as a skilled birth attendant may be present outside formal health facilities, such as home settings [ 26 ]. Moreover, Aboagye et al. did not include mobile phone ownership as a form of media exposure [ 26 ]. Additionally, their data was from 2014, and media access has increased drastically over the last decade [ 26 ]. Similarly, Anaba et al. investigated the determinants of health facility delivery in Ghana using the 2014 Ghana Demographic and Health Survey (GDHS) data and found that media exposure was significantly associated with institutional delivery [ 28 ]. However, their analysis was limited to the frequency of exposure to traditional media sources, such as newspapers, radio, and television [ 28 ]. They did not examine access to or ownership of mobile phones or the Internet, two increasingly important sources of health information in today's digital era [ 28 ]. As media access and digital connectivity have grown substantially over the last decade, especially in sub-Saharan Africa, there is a need to expand the understanding of how newer forms of media influence maternal health behaviors [ 28 ]. This indicates a critical gap in maternal health research, especially as Internet use and mobile phone ownership continue to rise in Ghana. This study examines the association between media exposure and the use of health facilities for delivering among women in Ghana. By exploring these distinct forms of media, we contribute to a more nuanced understanding of how information dissemination in the digital age can influence maternal health behaviors. The findings from this study can inform future public health interventions and policy efforts aimed at increasing health facility delivery rates and reducing maternal mortality. Methods Study data This study utilized data from the 2022 Ghana Demographic and Health Survey (GDHS), with permission obtained from MEASURE DHS [ 7 ]. The Ghana Health Service, the Ministry of Health, the Ghana Statistical Service, and ICF International implemented and conducted the surveys. The 2022 Ghana DHS was designed to be representative at the national, regional, and district levels [ 7 ]. The survey employed a two-stage sampling design to select participants from households across all 16 regions in Ghana [ 7 ]. The survey interviewed 15,014 women aged 15 to 49, with a response rate of 98% [ 7 ]. The GDHS collected information on socio-demographic characteristics and reproductive health topics, such as family planning, fertility, maternal and child health, and many more [ 7 ]. Sample The study sample consisted of 5,757 women of reproductive age (15 to 49 years) who were asked whether they had delivered at a health facility. Outcome variable Health facility delivery refers to childbirth in a medical setting, such as a hospital, clinic, health center, or maternity home, attended by trained health professionals. In this study, births that occurred outside a health facility were classified as home deliveries. The outcome variable was coded: health facility delivery = ‘1’ and home delivery = ‘0’. Exposure variables The exposure variables in this study included a range of socio-demographic and media access factors that may influence health facility delivery. Age was categorized into 15–24, 25–34, and 35–49 years. Wealth status was categorized into three groups: poor, middle, and rich, while education level was classified into four categories: no education, primary, secondary, and higher education. Residence was defined as either rural or urban. Media exposure variables included radio, mobile phone, television, newspaper/magazine, and Internet access. Each media-related variable was coded as “Yes” or “No” based on whether the respondent reported using or accessing that medium. Statistical Analysis This study used sampling weights provided by GDHS. All analyses were conducted in Stata 18. Participants with missing data on health facility use for delivery or key exposure variables were excluded from the analysis. Frequency and percentage distribution were used to describe the characteristics of the respondents. Bivariate logistic regression was used to examine the associations between media exposure, sociodemographic factors, and place of delivery. Multiple logistic regression was used to examine the association between health facilities and key explanatory variables, adjusting for demographic factors. Adjusted odds ratios (AORs) and their corresponding 95% confidence intervals (CIs) were reported for all relevant predictors. Statistical significance was determined at p < .05. Multicollinearity was assessed and undetected. Results Descriptive results A total of 5,757 women aged 15–49 reported their place of delivery in the 2022 Ghana Demographic and Health Survey (GDHS). See Table 1. Among the participants, 85.26% reported having delivered at a health facility, while 14.74% did not. Nearly half (48.06%) of the women were between 25 and 34, followed by 26.21% aged 15 to 24, and 25.73% aged 35 to 49. In terms of household wealth, more than half of the women (57.14%) were in the poor wealth quintile, 18.03% were in the middle, and 24.83% were in the rich category. Most poor women delivered outside a health facility, compared to a much smaller proportion of wealthy women. Nearly half (46.51%) of the respondents had completed secondary education. Approximately 29.91% of the women had no formal education, 16.14% had completed primary education, and only 7.43% had attained higher education. The proportion of women delivering at a facility increased with higher levels of education. The study population was predominantly rural, with 59.16% of women residing in rural areas and 40.84% in urban areas. Women living in urban settings were more likely to deliver at a health facility compared to those in rural areas. Regarding media exposure and technology access, 55.18% of the women reported not listening to the radio, while 44.82% did. Ownership of mobile phones was high, with 74.46% of the women owning one. A little more than half (57.49%) of the respondents reported watching television, while 42.51% did not. Only 3.13% of the women reported reading newspapers or magazines. About 29.99% of women had access to the Internet, while the remaining 70.01% did not. Bivariate logistic regression results Age was not significantly associated with the use of health facilities for delivery. See Table 2. Compared to women aged 15 to 24, those aged 25 to 34 had slightly higher odds of facility delivery (OR = 1.09, 95% CI: 0.91–1.30), while women aged 35 to 49 had slightly lower odds (OR = 0.86, 95% CI: 0.71–1.06). However, neither association was statistically significant. Household wealth was found to have a strong positive association with facility-based delivery. Compared to women from poor households, those in the middle wealth category had over three times the odds of delivering at a health facility (OR = 3.12, 95% CI: 2.46–3.95), and women in the rich category had nearly eight times the odds (OR = 7.83, 95% CI: 5.82–10.54). Both were statistically significant at p < 0.0001. Education was also significantly associated with facility delivery. Women with primary education had higher odds of facility delivery compared to those with no education (OR = 1.48, 95% CI: 1.21–1.80), and those with secondary education had over three times the odds (OR = 3.24, 95% CI: 2.73–3.84). The strongest association was observed among women with higher education, who had over 17 times the odds of delivering at a facility (OR = 17.26, 95% CI: 8.50–35.03), all p < 0.0001. Compared to rural residence, urban residence was significantly associated with increased odds of delivering at a health facility (OR = 4.15, 95% CI: 3.44–5.03, p < 0.0001). Regarding media exposure, women who listened to the radio had higher odds of delivering at a health facility (OR = 1.20, 95% CI: 1.04–1.40, p = 0.014). Mobile phone ownership was associated with significantly higher odds of facility delivery (OR = 2.85, 95% CI: 2.45–3.31, p < 0.0001). Similarly, watching television (OR = 2.98, 95% CI: 2.56–3.47), reading newspapers or magazines (OR = 5.17, 95% CI: 2.28–11.71), and having Internet access (OR = 4.12, 95% CI: 3.29–5.15) were all significantly associated with increased odds of delivering at a health facility (p < 0.0001). Multiple logistic regression After adjusting for all other variables in the model, age was not significantly associated with facility delivery. Women aged 25 to 34 had a slightly lower but non-significant likelihood of delivering at a health facility compared to those aged 15 to 24 (AOR = 0.96, 95% CI: 0.79–1.17, p = 0.736). Similarly, women aged 35 to 49 also had no significant difference in odds (AOR = 0.93, 95% CI: 0.74–1.15, p = 0.531). Wealth remained a strong predictor of health facility delivery. Compared to women in the poor wealth category, those in the middle category had 1.43 times the odds of delivering at a facility (AOR = 1.43, 95% CI: 1.08–1.88, p = 0.01), while those in the rich category had more than twice the odds (AOR = 2.22, 95% CI: 1.54–3.19, p < 0.0001). Education level was found to be associated with facility delivery. Women with secondary education had 1.77 times the odds (AOR = 1.77, 95% CI: 1.45–2.15), and those with higher education had three times the odds (AOR = 3.06, 95% CI: 1.42–6.60) of delivering at a health facility compared to those with no education. The association for primary education was not statistically significant (AOR = 1.15, 95% CI: 0.93–1.42). Urban residence was significantly associated with increased odds of health facility delivery. Women living in urban areas had nearly twice the odds of delivering at a facility compared to rural women (AOR = 1.98, 95% CI: 1.59–2.47, p < 0.0001). Regarding media and technology exposure, mobile phone ownership remained a strong predictor after adjustment for other factors. Women who owned a mobile phone had 1.59 times the odds of delivering at a health facility (AOR = 1.59, 95% CI: 1.35–1.87, p < 0.0001). Watching television was also associated with increased odds (AOR = 1.30, 95% CI: 1.08–1.56). Internet access was positively associated with facility delivery (AOR = 1.83, 95% CI: 1.49–2.26, p = 0.0007). However, exposure to radio (AOR = 1.00, 95% CI: 0.85–1.17) and reading newspapers or magazines (AOR = 1.70, 95% CI: 0.73–3.97) were not significantly associated with the outcome in the adjusted model. Discussion This study examined the relationship between media exposure and the utilization of healthcare facilities for childbirth among women in Ghana. The findings indicated that higher wealth status, higher educational attainment, and residing in urban areas were significantly associated with increased use of health facilities for delivery. In contrast, age was not found to be a significant factor. Among media exposure variables, owning a mobile phone, watching television, and having Internet access were positively associated with using health facilities for delivery. However, no significant association was observed between listening to the radio or reading newspapers/magazines and delivering in a health facility. For the different types of media exposures, mobile phone ownership and Internet access showed the strongest associations with facility delivery. Women with access to the Internet were 83% more likely to deliver at a health facility, and mobile phone ownership increased the odds by 59%. While watching television was also associated with increased facility use, the effect was not as strong. This may be due to the nature of content accessible through phones and Internet platforms, which often provide more interactive and globally sourced health information, potentially including maternal health, compared to traditional television programming. This finding suggests that newer forms of mass technology may be shaping maternal health behaviors. These results highlight the importance of considering evolving digital behaviors when assessing health service utilization patterns in Ghana. Our findings align with a growing body of literature that recognizes the role of media exposure in improving maternal health outcomes. Previous studies have consistently shown that exposure to mass media is associated with increased awareness and use of maternal health services [ 23 , 24 , 27 ]. For example, Fatema and Lariscy assessed the association between mass media exposure and maternal health utilization in four South Asian countries (India, Bangladesh, Nepal, and Pakistan) [ 27 ]. They found that mass media exposure was associated with maternal utilization among all four countries [ 27 ]. However, one limitation of their study was that it only included watching TV, listening to the radio, and reading the newspaper as forms of media consumption [ 27 ]. This limited the scope of their conclusions in today’s rapidly evolving digital landscape, particularly with the widespread adoption of mobile phones and Internet access [ 27 ]. Similarly, Musizvingoza & Wekwete explored the associations between exposure to mass media and maternal healthcare utilization among women in Zimbabwe [ 29 ]. They found that women exposed to mass media were positively associated with making at least four ANC and PNC visits in two days [ 29 ]. Additionally, their findings revealed that women who listened to the radio at least once a week had higher odds of four or more ANC visits (AOR 1.26, 95% CI: (1.07–1.49), and receiving PNC in 48 hours (AOR 1.26, 95% CI: (1.01–1.57) than women who did not [ 29 ]. Furthermore, Igbinoba et al. conducted a descriptive survey in Ota, Nigeria, to examine whether media exposure increases maternal health awareness among women aged 15–49 [ 23 ]. The researchers employed haphazard sampling and administered a 29-item questionnaire to 100 women [ 23 ]. Their findings showed that 88.3% of the variation in maternal health awareness could be explained by exposure to media sources such as the Internet, television, newspapers, and radio (R² = 0.883) [ 23 ]. This study provides invaluable insights into current research on media exposure and maternal healthcare utilization in Ghana. To our knowledge, this is the first study to examine the various types of media exposure and their association with health facility delivery in Ghana. The inclusion of newer media forms such as mobile phones and Internet access reflects the changing nature of information access and health communication in low- and middle-income countries. By identifying the specific types of media that influence health facility use for delivery, this study offers a more detailed understanding of where public health messaging may be most effectively targeted. Moreover, this study uses nationally representative, population-based data, enhancing the findings' generalizability. The GDHS is known for its rigorous methodology, high response rates, and comprehensive coverage of reproductive health indicators. Mass media exposure, maternal healthcare utilization, and sociodemographic factors are commonly measured in comparable ways across countries, enabling meaningful cross-country comparisons. Finally, our findings that mass media is associated with health facility delivery suggest its potential as a tool for health promotion, especially in developing countries like Ghana, where it is predominantly rural. Public health efforts to reduce maternal and neonatal mortality can leverage mass media to raise awareness about other critical issues, including the importance of antenatal care, health facility delivery, and postnatal care. While our research offered new findings, there are important limitations that we must note. First, the cross-sectional study limits our ability to establish causal relationships between media exposure and health facility delivery. While we observed strong associations, we cannot determine the directionality of these relationships. Furthermore, we did not explore potential interaction effects between variables. For instance, the influence of media exposure on facility delivery is moderated by education level or rural-urban residence, which could provide more detailed insights into population subgroups. Additionally, while we accounted for access to different media types, we did not examine the content, frequency, or quality of the messages delivered through these platforms. For example, having access to a mobile phone or the Internet does not guarantee exposure to maternal health information. Moreover, one-time use of a mobile phone may not allow an individual to be exposed to health information compared to someone who has had several or more exposures. Future studies should consider how often and in what ways women engage with health-related content across these platforms. Lastly, our study did not control for cultural beliefs, partner influence, or previous birth experiences, which can also shape delivery decisions. These contextual factors may interact with media exposure and warrant further exploration. Future research should employ longitudinal designs to better assess the causal pathways between media exposure and maternal health service utilization. Studies incorporating qualitative components could offer deeper insights into how and why women engage with different media platforms and how this shapes their perceptions and decisions regarding childbirth. Moreover, future investigations should consider analyzing the interaction between media exposure, education, location, and social norms to understand better how information access translates into behavioral change. There is also a need for intervention-based studies that assess the effectiveness of mobile and Internet-based maternal health campaigns, particularly in rural and low-resource settings where there are structural and systemic inequalities. Conclusion In conclusion, this study contributes to the growing literature on maternal health service utilization by highlighting the important role that various forms of media exposure influence health facility delivery in Ghana. Our findings suggest that mobile phones, Internet access, and television are associated with health facility delivery. As the digital landscape expands worldwide, maternal health interventions should increase and incorporate digital communication strategies to enhance their effectiveness, especially in a low-income country like Ghana. By understanding the types of media women access, public health practitioners and policymakers can design more effective outreach campaigns to ensure that more women deliver in safe, equipped, and supportive health facilities. These efforts are essential for reducing preventable maternal and neonatal deaths and achieving global health equity. Abbreviations AOR: Adjusted Odds Ratio CI: Confidence Interval GDHS: Ghana Demographic and Health Survey Declarations Ethics 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 All authors have reviewed and approved the final version of this manuscript. Each author gives full consent for publication in Reproductive Health. Availability of data and materials The data used in this study are freely available from The DHS Program website (https://www.dhsprogram.com/data/available-datasets.cfm). The study was carried out specifically using 2022 Ghana Demographic and Health Survey dataset. Competing interests The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Funding There was no funding was received for this study. Authors' contributions Ya Yang: Conceptualization, Formal analysis, Investigation, Methodology, Supervision, Writing – original draft, Writing – review & editing. Safa Uraizee: Data entry, validation, writing – original draft. Mariam Hernandez Mendoza: Data entry, validation, writing – original draft. Joseph Adu: Conceptualization, Writing – reviewing & editing Acknowledgements There is no one to acknowledge at this time. References Sarkodie AO. Effect of the National Health Insurance Scheme on Healthcare Utilization and Out-of-Pocket Payment: Evidence from GLSS 7. Humanit Soc Sci Commun. 2021 Nov 23;8(1):293. Blanchet NJ, Fink G, Osei-Akoto I. The effect of ghana’s national health insurance scheme on health care utilisation. Ghana Medical Journal. 2012;46(2). Azaare J, Akweongo P, Aryeetey GC, Dwomoh D. Impact of free maternal health care policy on maternal health care utilization and perinatal mortality in Ghana: protocol design for historical cohort study. Reprod Health. 2020 Dec;17(1):169. Adawudu EA, Aidam K, Oduro E, Miezah D, Vorderstrasse A. 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Association between frequency of mass media exposure and maternal health care service utilization among women in sub-Saharan Africa: Implications for tailored health communication and education. Todd CS, editor. PLoS ONE. 2022 Sep 29;17(9):e0275202. Fatema K, Lariscy JT. Mass media exposure and maternal healthcare utilization in South Asia. SSM - Population Health. 2020 Aug;11:100614. Anaba EA, Alangea DO, Addo-Lartey A, Modey EJ, Manu A, Alor SK, et al. Determinants of health facility delivery among young mothers in Ghana; insights from the 2014 Ghana Demographic and Health Survey. BMC Pregnancy Childbirth. 2022 Aug 20;22(1):656. Musizvingoza R, Wekwete NN. Exposure to Mass Media and Maternal Healthcare Utilization in Zimbabwe. Ethiop J Health Dev. Tables Table 1. Study variable description Variable name Description Level of measurement Health Facility Delivery Respondents use of health facility for delivery 0 = Did not use health facility 1 = Used health facility Age Maternal age (years) 1 = 15 to 24 2 = 25 to 34 3 = 35 to 49 Wealth Financial status of the respondent 1 = Poor 2 = Middle 3 = Rich Education Highest educational level 1 = None 2 = Primary 3 = Secondary 4 = High Religion Religious affiliation of the respondent 1 = Christianity 2 = Islam 3 = Traditional/Other Residence Place of residence 1 = Urban 2 = Rural Radio Household has radio 1 = No 2 = Yes Mobile Phone Owns a mobile telephone 1 = No 2 = Yes TV Household has a television 1 = No 2 = Yes Newspaper/Magazine Heard family planning in newspaper/magazine in last few months 1 = No 2 = Yes Internet access Household has internet access 1 = No 2 = Yes Table 2. Distribution of health facility use ( N =5,757) Predictors Sample size Did not deliver at a health facility Delivered at a health facility P-Value Total Sample Size Women 850 [14.76%] 4,907 [85.4%] Age 5,757 [100.00%] 15 to 24 1509 [26.21%] 223 [14.78%] 1286 [85.22%] 0.036 25 to 34 2767 [48.06%] 380 [13.74%] 2387 [86.26%] 35 to 49 1481 [25.73%] 247 [16.68%] 1234 [83.32%] Wealth Poor 3290 [57.14%] 716 [21.77%] 2574 [78.23%] <0.0001* Middle 1038 [18.03%] 85 [8.19%] 953 [91.81%] Rich 1429 [24.83%] 49 [3.43%] 1380 [96.57%] Education None 1722 [29.91%] 426 [24.74%] 1296 [75.26%] <0.0001* Primary 929 [16.14%] 169 [18.19%] 760 [81.81%] Secondary 2678 [46.51%] 247 [9.22%] 2431 [90.78%] Higher 428 [7.43%] 8 [1.87%] 420 [98.13%] Residence Urban 2351 [40.84%] 140 [5.96%] 2111 [94.04%] <0.0001* Rural 3406 [59.16%] 710 [20.85%] 2696 [79.15%] Radio No 3177 [55.18%] 502 [15.80%] 2675 [84.20%] 0.014 Yes 2580 [44.82%] 348 [13.49%] 2232 [86.51%] Mobile Phone No 1470 [25.54%] 381 [25.92%] 1089 [74.08%] <0.0001* Yes 4287 [74.46%] 469 [10.95%] 3818 [89.05%] TV No 2447 [42.51%] 554 [22.64%] 1893 [77.36%] <0.0001* Yes 3310 [57.49%] 296 [8.94%] 3014 [91.06%] Newspaper/Magazine No 5577 [96.87%] 844 [15.13%] 4733 [84.87%] <0.0001* Yes 180 [3.13%] 6 [3.33%] 174 [96.67%] Internet Access No 4030 [70.01%] 758 [18.81%] 3272 [81.19%] <0.0001* Yes 1727 [29.99%] 92 [5.33%] 1635 [94.67%] Table 3. Unadjusted odds ratio and 95% confidence interval of using health facility for delivery by demographic and mass media factors in the bivariable logistic regression analyses. Predictors Unadjusted Odds Ratio (95% Confidence Interval) P-Value Age 15 to 24 Ref. Ref. 25 to 34 1.09 [0.91, 1.30] 0.348 35 to 49 0.86 [0.71, 1.06] 0.154 Wealth Poor Ref. Ref. Middle 3.12 [2.46, 3.95] <0.0001 Rich 7.83 [5.82, 10.54] <0.0001 Education No education Ref. Ref. Primary 1.48 [1.21, 1.80] <0.0001 Secondary 3.24 [2.73, 3.84] <0.0001 Higher 17.26 [8.50, 35.03] <0.0001 Residence Rural Ref. Ref. Urban 4.15 [3.44, 5.03] <0.0001 Radio No Ref. Ref. Yes 1.20 [1.04, 1.40] 0.014 Mobile Phone No Ref. Ref. Yes 2.85 [2.45, 3.31] <0.0001 TV No Ref. Ref. Yes 2.98 [2.56, 3.47] <0.0001 Newspaper/Magazine No Ref. Ref. Yes 5.17 [2.28, 11.71] <0.0001 Internet Access No Ref. Ref. Yes 4.12 [3.29, 5.15] <0.0001 Table 4. Adjusted odds ratio and 95% confidence interval of using health facility for delivery by demographic and mass media factors in the multiple logistic regression analyses. Predictors Adjusted Odds Ratio (95% CI) P-Value Age 15 to 24 Ref. Ref. 25 to 34 0.96 [0.79, 1.17] 0.736 35 to 49 0.93 [0.74, 1.15] 0.531 Wealth Poor Ref. Ref. Middle 1.43 [1.08, 1.88] 0.01 Rich 2.22 [1.54, 3.19] <0.0001 Education No education Ref. Ref. Primary 1.15 [0.93, 1.42] 0.178 Secondary 1.77 [1.45, 2.15] 0.000 Higher 3.06 [1.42, 6.60] 0.004 Residence Rural Ref. Ref. Urban 1.98 [1.59, 2.47] 0.000 Radio No Ref. Ref. Yes 1.00 [0.85, 1.17] 0.959 Mobile Phone No Ref. Ref. Yes 1.59 [1.35, 1.87] <0.0001 TV No Ref. Ref. Yes 1.30 [1.08, 1.56 ] 0.004 Newspaper/Magazine No Ref. Ref. Yes 1.70 [0.73, 3. 97] 0.215 Internet Access No Ref. Ref. Yes 1.83 [1.49, 2.26] 0.007 Additional Declarations No competing interests reported. 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To address financial barriers and access to skilled birth attendants, the Free Maternal Health Care Policy (FMHCP) was introduced in 2008 [\u003cspan additionalcitationids=\"CR4\" citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Prior to the policy, only 43% of births occurred in health facilities in 2003 [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. After the implementation of FMHCP, the proportion of births occurring in health facilities increased to 73% in 2014 and 85% in 2022 [\u003cspan additionalcitationids=\"CR8\" citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Although this upward trend is promising, it still leaves many women without access to skilled birth attendants. Delivering in a health facility is essential for the mother and child because it ensures that trained healthcare professionals, such as midwives, nurses, and doctors, are present to manage childbirth and any related complications [\u003cspan additionalcitationids=\"CR11\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Research has shown that health facility delivery is associated with reductions in maternal mortality, neonatal deaths, and obstetric complications, especially in emergencies such as hemorrhage, sepsis, and obstructed labor [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Given that many women still deliver at home despite free access to maternal care, this raises concerns about structural barriers and behavioral determinants that limit the utilization of life-saving services. Addressing these gaps is essential to reducing global maternal and neonatal mortality in Ghana.\u003c/p\u003e \u003cp\u003eExtensive literature has examined the role of sociodemographic factors in shaping health facility use in Ghana [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Factors such as maternal education, household wealth, urban residence, and parity have consistently been found to influence the likelihood of delivering at a health facility [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Women with higher education are more likely to be informed about the benefits of skilled care and are better equipped to navigate health systems [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Wealthier households can afford transportation and associated delivery costs, and urban residents benefit from closer proximity to health infrastructure [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. However, existing literature often overlooks the rapidly evolving information ecosystem modern women can use to make reproductive decisions. In recent years, there has been a rapid increase in access to digital technology and mobile communication tools worldwide [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. These tools are often referred to as mass media, encompassing various media, including radio, television, newspapers, magazines, phones, and posters, to promote health [\u003cspan additionalcitationids=\"CR20\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. The mass media allows women to be exposed to information about appropriate health services [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. It can assist mothers in understanding the importance of healthcare utilization by providing health information through visually appealing, audio messages, and written letters [\u003cspan additionalcitationids=\"CR25\" citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Research has shown that mass media exposure, particularly through television and radio, is positively associated with using health facilities [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. While Aboagye et al. examined the association between mass media exposure and maternal health care service utilization among 28 countries in sub-Saharan Africa and included Ghana, their study focused specifically on skilled birth attendance rather than place of delivery [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. This distinction is important, as a skilled birth attendant may be present outside formal health facilities, such as home settings [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Moreover, Aboagye et al. did not include mobile phone ownership as a form of media exposure [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. Additionally, their data was from 2014, and media access has increased drastically over the last decade [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSimilarly, Anaba et al. investigated the determinants of health facility delivery in Ghana using the 2014 Ghana Demographic and Health Survey (GDHS) data and found that media exposure was significantly associated with institutional delivery [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. However, their analysis was limited to the frequency of exposure to traditional media sources, such as newspapers, radio, and television [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. They did not examine access to or ownership of mobile phones or the Internet, two increasingly important sources of health information in today's digital era [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. As media access and digital connectivity have grown substantially over the last decade, especially in sub-Saharan Africa, there is a need to expand the understanding of how newer forms of media influence maternal health behaviors [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. This indicates a critical gap in maternal health research, especially as Internet use and mobile phone ownership continue to rise in Ghana.\u003c/p\u003e \u003cp\u003eThis study examines the association between media exposure and the use of health facilities for delivering among women in Ghana. By exploring these distinct forms of media, we contribute to a more nuanced understanding of how information dissemination in the digital age can influence maternal health behaviors. The findings from this study can inform future public health interventions and policy efforts aimed at increasing health facility delivery rates and reducing maternal mortality.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy data\u003c/h2\u003e \u003cp\u003eThis study utilized data from the 2022 Ghana Demographic and Health Survey (GDHS), with permission obtained from MEASURE DHS [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. The Ghana Health Service, the Ministry of Health, the Ghana Statistical Service, and ICF International implemented and conducted the surveys. The 2022 Ghana DHS was designed to be representative at the national, regional, and district levels [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. The survey employed a two-stage sampling design to select participants from households across all 16 regions in Ghana [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. The survey interviewed 15,014 women aged 15 to 49, with a response rate of 98% [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\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=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eSample\u003c/h3\u003e\n\u003cp\u003eThe study sample consisted of 5,757 women of reproductive age (15 to 49 years) who were asked whether they had delivered at a health facility.\u003c/p\u003e\n\u003ch3\u003eOutcome variable\u003c/h3\u003e\n\u003cp\u003eHealth facility delivery refers to childbirth in a medical setting, such as a hospital, clinic, health center, or maternity home, attended by trained health professionals. In this study, births that occurred outside a health facility were classified as home deliveries. The outcome variable was coded: health facility delivery = \u0026lsquo;1\u0026rsquo; and home delivery = \u0026lsquo;0\u0026rsquo;.\u003c/p\u003e\n\u003ch3\u003eExposure variables\u003c/h3\u003e\n\u003cp\u003eThe exposure variables in this study included a range of socio-demographic and media access factors that may influence health facility delivery. Age was categorized into 15\u0026ndash;24, 25\u0026ndash;34, and 35\u0026ndash;49 years. Wealth status was categorized into three groups: poor, middle, and rich, while education level was classified into four categories: no education, primary, secondary, and higher education. Residence was defined as either rural or urban. Media exposure variables included radio, mobile phone, television, newspaper/magazine, and Internet access. Each media-related variable was coded as \u0026ldquo;Yes\u0026rdquo; or \u0026ldquo;No\u0026rdquo; based on whether the respondent reported using or accessing that medium.\u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eThis study used sampling weights provided by GDHS. All analyses were conducted in Stata 18. Participants with missing data on health facility use for delivery or key exposure variables were excluded from the analysis. Frequency and percentage distribution were used to describe the characteristics of the respondents. Bivariate logistic regression was used to examine the associations between media exposure, sociodemographic factors, and place of delivery. Multiple logistic regression was used to examine the association between health facilities and key explanatory variables, adjusting for demographic factors. Adjusted odds ratios (AORs) and their corresponding 95% confidence intervals (CIs) were reported for all relevant predictors. Statistical significance was determined at p\u0026thinsp;\u0026lt;\u0026thinsp;.05. Multicollinearity was assessed and undetected.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eDescriptive results\u003c/h2\u003e \u003cp\u003eA total of 5,757 women aged 15\u0026ndash;49 reported their place of delivery in the 2022 Ghana Demographic and Health Survey (GDHS). See Table\u0026nbsp;1. Among the participants, 85.26% reported having delivered at a health facility, while 14.74% did not. Nearly half (48.06%) of the women were between 25 and 34, followed by 26.21% aged 15 to 24, and 25.73% aged 35 to 49. In terms of household wealth, more than half of the women (57.14%) were in the poor wealth quintile, 18.03% were in the middle, and 24.83% were in the rich category. Most poor women delivered outside a health facility, compared to a much smaller proportion of wealthy women. Nearly half (46.51%) of the respondents had completed secondary education. Approximately 29.91% of the women had no formal education, 16.14% had completed primary education, and only 7.43% had attained higher education. The proportion of women delivering at a facility increased with higher levels of education.\u003c/p\u003e \u003cp\u003eThe study population was predominantly rural, with 59.16% of women residing in rural areas and 40.84% in urban areas. Women living in urban settings were more likely to deliver at a health facility compared to those in rural areas. Regarding media exposure and technology access, 55.18% of the women reported not listening to the radio, while 44.82% did. Ownership of mobile phones was high, with 74.46% of the women owning one. A little more than half (57.49%) of the respondents reported watching television, while 42.51% did not. Only 3.13% of the women reported reading newspapers or magazines. About 29.99% of women had access to the Internet, while the remaining 70.01% did not.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eBivariate logistic regression results\u003c/h3\u003e\n\u003cp\u003eAge was not significantly associated with the use of health facilities for delivery. See Table\u0026nbsp;2. Compared to women aged 15 to 24, those aged 25 to 34 had slightly higher odds of facility delivery (OR\u0026thinsp;=\u0026thinsp;1.09, 95% CI: 0.91\u0026ndash;1.30), while women aged 35 to 49 had slightly lower odds (OR\u0026thinsp;=\u0026thinsp;0.86, 95% CI: 0.71\u0026ndash;1.06). However, neither association was statistically significant. Household wealth was found to have a strong positive association with facility-based delivery. Compared to women from poor households, those in the middle wealth category had over three times the odds of delivering at a health facility (OR\u0026thinsp;=\u0026thinsp;3.12, 95% CI: 2.46\u0026ndash;3.95), and women in the rich category had nearly eight times the odds (OR\u0026thinsp;=\u0026thinsp;7.83, 95% CI: 5.82\u0026ndash;10.54). Both were statistically significant at p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001.\u003c/p\u003e \u003cp\u003eEducation was also significantly associated with facility delivery. Women with primary education had higher odds of facility delivery compared to those with no education (OR\u0026thinsp;=\u0026thinsp;1.48, 95% CI: 1.21\u0026ndash;1.80), and those with secondary education had over three times the odds (OR\u0026thinsp;=\u0026thinsp;3.24, 95% CI: 2.73\u0026ndash;3.84). The strongest association was observed among women with higher education, who had over 17 times the odds of delivering at a facility (OR\u0026thinsp;=\u0026thinsp;17.26, 95% CI: 8.50\u0026ndash;35.03), all p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001. Compared to rural residence, urban residence was significantly associated with increased odds of delivering at a health facility (OR\u0026thinsp;=\u0026thinsp;4.15, 95% CI: 3.44\u0026ndash;5.03, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001).\u003c/p\u003e \u003cp\u003eRegarding media exposure, women who listened to the radio had higher odds of delivering at a health facility (OR\u0026thinsp;=\u0026thinsp;1.20, 95% CI: 1.04\u0026ndash;1.40, p\u0026thinsp;=\u0026thinsp;0.014). Mobile phone ownership was associated with significantly higher odds of facility delivery (OR\u0026thinsp;=\u0026thinsp;2.85, 95% CI: 2.45\u0026ndash;3.31, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). Similarly, watching television (OR\u0026thinsp;=\u0026thinsp;2.98, 95% CI: 2.56\u0026ndash;3.47), reading newspapers or magazines (OR\u0026thinsp;=\u0026thinsp;5.17, 95% CI: 2.28\u0026ndash;11.71), and having Internet access (OR\u0026thinsp;=\u0026thinsp;4.12, 95% CI: 3.29\u0026ndash;5.15) were all significantly associated with increased odds of delivering at a health facility (p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001).\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eMultiple logistic regression\u003c/h2\u003e \u003cp\u003eAfter adjusting for all other variables in the model, age was not significantly associated with facility delivery. Women aged 25 to 34 had a slightly lower but non-significant likelihood of delivering at a health facility compared to those aged 15 to 24 (AOR\u0026thinsp;=\u0026thinsp;0.96, 95% CI: 0.79\u0026ndash;1.17, p\u0026thinsp;=\u0026thinsp;0.736). Similarly, women aged 35 to 49 also had no significant difference in odds (AOR\u0026thinsp;=\u0026thinsp;0.93, 95% CI: 0.74\u0026ndash;1.15, p\u0026thinsp;=\u0026thinsp;0.531). Wealth remained a strong predictor of health facility delivery. Compared to women in the poor wealth category, those in the middle category had 1.43 times the odds of delivering at a facility (AOR\u0026thinsp;=\u0026thinsp;1.43, 95% CI: 1.08\u0026ndash;1.88, p\u0026thinsp;=\u0026thinsp;0.01), while those in the rich category had more than twice the odds (AOR\u0026thinsp;=\u0026thinsp;2.22, 95% CI: 1.54\u0026ndash;3.19, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001).\u003c/p\u003e \u003cp\u003eEducation level was found to be associated with facility delivery. Women with secondary education had 1.77 times the odds (AOR\u0026thinsp;=\u0026thinsp;1.77, 95% CI: 1.45\u0026ndash;2.15), and those with higher education had three times the odds (AOR\u0026thinsp;=\u0026thinsp;3.06, 95% CI: 1.42\u0026ndash;6.60) of delivering at a health facility compared to those with no education. The association for primary education was not statistically significant (AOR\u0026thinsp;=\u0026thinsp;1.15, 95% CI: 0.93\u0026ndash;1.42). Urban residence was significantly associated with increased odds of health facility delivery. Women living in urban areas had nearly twice the odds of delivering at a facility compared to rural women (AOR\u0026thinsp;=\u0026thinsp;1.98, 95% CI: 1.59\u0026ndash;2.47, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001).\u003c/p\u003e \u003cp\u003eRegarding media and technology exposure, mobile phone ownership remained a strong predictor after adjustment for other factors. Women who owned a mobile phone had 1.59 times the odds of delivering at a health facility (AOR\u0026thinsp;=\u0026thinsp;1.59, 95% CI: 1.35\u0026ndash;1.87, p\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). Watching television was also associated with increased odds (AOR\u0026thinsp;=\u0026thinsp;1.30, 95% CI: 1.08\u0026ndash;1.56). Internet access was positively associated with facility delivery (AOR\u0026thinsp;=\u0026thinsp;1.83, 95% CI: 1.49\u0026ndash;2.26, p\u0026thinsp;=\u0026thinsp;0.0007). However, exposure to radio (AOR\u0026thinsp;=\u0026thinsp;1.00, 95% CI: 0.85\u0026ndash;1.17) and reading newspapers or magazines (AOR\u0026thinsp;=\u0026thinsp;1.70, 95% CI: 0.73\u0026ndash;3.97) were not significantly associated with the outcome in the adjusted model.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study examined the relationship between media exposure and the utilization of healthcare facilities for childbirth among women in Ghana. The findings indicated that higher wealth status, higher educational attainment, and residing in urban areas were significantly associated with increased use of health facilities for delivery. In contrast, age was not found to be a significant factor. Among media exposure variables, owning a mobile phone, watching television, and having Internet access were positively associated with using health facilities for delivery. However, no significant association was observed between listening to the radio or reading newspapers/magazines and delivering in a health facility. For the different types of media exposures, mobile phone ownership and Internet access showed the strongest associations with facility delivery. Women with access to the Internet were 83% more likely to deliver at a health facility, and mobile phone ownership increased the odds by 59%. While watching television was also associated with increased facility use, the effect was not as strong. This may be due to the nature of content accessible through phones and Internet platforms, which often provide more interactive and globally sourced health information, potentially including maternal health, compared to traditional television programming. This finding suggests that newer forms of mass technology may be shaping maternal health behaviors. These results highlight the importance of considering evolving digital behaviors when assessing health service utilization patterns in Ghana.\u003c/p\u003e \u003cp\u003eOur findings align with a growing body of literature that recognizes the role of media exposure in improving maternal health outcomes. Previous studies have consistently shown that exposure to mass media is associated with increased awareness and use of maternal health services [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. For example, Fatema and Lariscy assessed the association between mass media exposure and maternal health utilization in four South Asian countries (India, Bangladesh, Nepal, and Pakistan) [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. They found that mass media exposure was associated with maternal utilization among all four countries [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. However, one limitation of their study was that it only included watching TV, listening to the radio, and reading the newspaper as forms of media consumption [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. This limited the scope of their conclusions in today\u0026rsquo;s rapidly evolving digital landscape, particularly with the widespread adoption of mobile phones and Internet access [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSimilarly, Musizvingoza \u0026amp; Wekwete explored the associations between exposure to mass media and maternal healthcare utilization among women in Zimbabwe [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. They found that women exposed to mass media were positively associated with making at least four ANC and PNC visits in two days [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Additionally, their findings revealed that women who listened to the radio at least once a week had higher odds of four or more ANC visits (AOR 1.26, 95% CI: (1.07\u0026ndash;1.49), and receiving PNC in 48 hours (AOR 1.26, 95% CI: (1.01\u0026ndash;1.57) than women who did not [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Furthermore, Igbinoba et al. conducted a descriptive survey in Ota, Nigeria, to examine whether media exposure increases maternal health awareness among women aged 15\u0026ndash;49 [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. The researchers employed haphazard sampling and administered a 29-item questionnaire to 100 women [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Their findings showed that 88.3% of the variation in maternal health awareness could be explained by exposure to media sources such as the Internet, television, newspapers, and radio (R\u0026sup2; = 0.883) [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThis study provides invaluable insights into current research on media exposure and maternal healthcare utilization in Ghana. To our knowledge, this is the first study to examine the various types of media exposure and their association with health facility delivery in Ghana. The inclusion of newer media forms such as mobile phones and Internet access reflects the changing nature of information access and health communication in low- and middle-income countries. By identifying the specific types of media that influence health facility use for delivery, this study offers a more detailed understanding of where public health messaging may be most effectively targeted. Moreover, this study uses nationally representative, population-based data, enhancing the findings' generalizability. The GDHS is known for its rigorous methodology, high response rates, and comprehensive coverage of reproductive health indicators. Mass media exposure, maternal healthcare utilization, and sociodemographic factors are commonly measured in comparable ways across countries, enabling meaningful cross-country comparisons. Finally, our findings that mass media is associated with health facility delivery suggest its potential as a tool for health promotion, especially in developing countries like Ghana, where it is predominantly rural. Public health efforts to reduce maternal and neonatal mortality can leverage mass media to raise awareness about other critical issues, including the importance of antenatal care, health facility delivery, and postnatal care.\u003c/p\u003e \u003cp\u003eWhile our research offered new findings, there are important limitations that we must note. First, the cross-sectional study limits our ability to establish causal relationships between media exposure and health facility delivery. While we observed strong associations, we cannot determine the directionality of these relationships. Furthermore, we did not explore potential interaction effects between variables. For instance, the influence of media exposure on facility delivery is moderated by education level or rural-urban residence, which could provide more detailed insights into population subgroups. Additionally, while we accounted for access to different media types, we did not examine the content, frequency, or quality of the messages delivered through these platforms. For example, having access to a mobile phone or the Internet does not guarantee exposure to maternal health information. Moreover, one-time use of a mobile phone may not allow an individual to be exposed to health information compared to someone who has had several or more exposures. Future studies should consider how often and in what ways women engage with health-related content across these platforms. Lastly, our study did not control for cultural beliefs, partner influence, or previous birth experiences, which can also shape delivery decisions. These contextual factors may interact with media exposure and warrant further exploration.\u003c/p\u003e \u003cp\u003eFuture research should employ longitudinal designs to better assess the causal pathways between media exposure and maternal health service utilization. Studies incorporating qualitative components could offer deeper insights into how and why women engage with different media platforms and how this shapes their perceptions and decisions regarding childbirth. Moreover, future investigations should consider analyzing the interaction between media exposure, education, location, and social norms to understand better how information access translates into behavioral change. There is also a need for intervention-based studies that assess the effectiveness of mobile and Internet-based maternal health campaigns, particularly in rural and low-resource settings where there are structural and systemic inequalities.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn conclusion, this study contributes to the growing literature on maternal health service utilization by highlighting the important role that various forms of media exposure influence health facility delivery in Ghana. Our findings suggest that mobile phones, Internet access, and television are associated with health facility delivery. As the digital landscape expands worldwide, maternal health interventions should increase and incorporate digital communication strategies to enhance their effectiveness, especially in a low-income country like Ghana. By understanding the types of media women access, public health practitioners and policymakers can design more effective outreach campaigns to ensure that more women deliver in safe, equipped, and supportive health facilities. These efforts are essential for reducing preventable maternal and neonatal deaths and achieving global health equity.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAOR:\u003c/em\u003e\u003c/strong\u003e Adjusted Odds Ratio\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eCI:\u003c/em\u003e\u003c/strong\u003e Confidence Interval\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eGDHS:\u003c/em\u003e\u003c/strong\u003e Ghana Demographic and Health Survey\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\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\u0026rsquo;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),\u0026rdquo; 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\u0026rsquo;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.\u0026rdquo; 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.\\\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors have reviewed and approved the final version of this manuscript. Each author gives full consent for publication in Reproductive Health.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data used in this study are freely available from The DHS Program website (https://www.dhsprogram.com/data/available-datasets.cfm). The study was carried out specifically using 2022 Ghana Demographic and Health Survey dataset.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThere was no funding was received for this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eYa Yang:\u003c/strong\u003e Conceptualization, Formal analysis, Investigation, Methodology, Supervision, Writing \u0026ndash; original draft, Writing \u0026ndash; review \u0026amp; editing. \u003cstrong\u003eSafa Uraizee:\u003c/strong\u003e Data entry, validation, writing \u0026ndash; original draft. Mariam Hernandez Mendoza: Data entry, validation, writing \u0026ndash; original draft. \u003cstrong\u003eJoseph Adu:\u003c/strong\u003e Conceptualization, Writing \u0026ndash; reviewing \u0026amp; editing\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThere is no one to acknowledge at this time.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSarkodie AO. Effect of the National Health Insurance Scheme on Healthcare Utilization and Out-of-Pocket Payment: Evidence from GLSS 7. Humanit Soc Sci Commun. 2021 Nov 23;8(1):293.\u003c/li\u003e\n\u003cli\u003eBlanchet NJ, Fink G, Osei-Akoto I. The effect of ghana\u0026rsquo;s national health insurance scheme on health care utilisation. Ghana Medical Journal. 2012;46(2).\u003c/li\u003e\n\u003cli\u003eAzaare J, Akweongo P, Aryeetey GC, Dwomoh D. 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Mass Media and Maternal Healthcare: A Critical Discourse. 2015;\u003c/li\u003e\n\u003cli\u003eIgbinoba AO, Soola EO, Omojola O, Odukoya J, Adekeye O, Salau OP. Women\u0026rsquo;s mass media exposure and maternal health awareness in Ota, Nigeria. Amoo EO, editor. Cogent Social Sciences. 2020 Jan;6(1):1766260.\u003c/li\u003e\n\u003cli\u003eOhaja M, Senkyire EK, Ewetan O, Asiedua E, Azuh D. A narrative literature review on media and maternal health in Africa. World Med \u0026amp;amp; Health Policy. 2023 Jun;15(2):123\u0026ndash;47.\u003c/li\u003e\n\u003cli\u003eIacoella F, Gassmann F, Tirivayi N. Which communication technology is effective for promoting reproductive health? Television, radio, and mobile phones in sub-Saharan Africa. Olapeju BB, editor. PLoS ONE. 2022 Aug 17;17(8):e0272501.\u003c/li\u003e\n\u003cli\u003eAboagye RG, Seidu AA, Ahinkorah BO, Cadri A, Frimpong JB, Hagan JE, et al. Association between frequency of mass media exposure and maternal health care service utilization among women in sub-Saharan Africa: Implications for tailored health communication and education. Todd CS, editor. PLoS ONE. 2022 Sep 29;17(9):e0275202.\u003c/li\u003e\n\u003cli\u003eFatema K, Lariscy JT. Mass media exposure and maternal healthcare utilization in South Asia. SSM - Population Health. 2020 Aug;11:100614.\u003c/li\u003e\n\u003cli\u003eAnaba EA, Alangea DO, Addo-Lartey A, Modey EJ, Manu A, Alor SK, et al. Determinants of health facility delivery among young mothers in Ghana; insights from the 2014 Ghana Demographic and Health Survey. BMC Pregnancy Childbirth. 2022 Aug 20;22(1):656.\u003c/li\u003e\n\u003cli\u003eMusizvingoza R, Wekwete NN. Exposure to Mass Media and Maternal Healthcare Utilization in Zimbabwe. Ethiop J Health Dev.\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"671\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"3\" valign=\"bottom\" style=\"width: 671px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 1.\u0026nbsp;\u003c/strong\u003eStudy variable description\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eVariable name\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eDescription\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eLevel of measurement\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eHealth Facility Delivery\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eRespondents use of health facility for delivery\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e0 = Did not use health facility\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1 = Used health facility\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eAge\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eMaternal age (years)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1 = 15 to 24\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e2 = 25 to 34\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e3 = 35 to 49\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eWealth\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eFinancial status of the respondent\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1 = Poor\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e2 = Middle\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e3 = Rich\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eEducation\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eHighest educational level\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1 = None\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e2 = Primary\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e3 = Secondary\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e4 = High\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eReligion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eReligious affiliation of the respondent\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1 = Christianity\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e2 = Islam\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e3 = Traditional/Other\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eResidence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003ePlace of residence\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1 = Urban\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e2 = Rural\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eRadio\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eHousehold has radio\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1 = No\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e2 = Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eMobile Phone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eOwns a mobile telephone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1 = No\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e2 = Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eTV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eHousehold has a television\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1 = No\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e2 = Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eNewspaper/Magazine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eHeard family planning in newspaper/magazine in last few months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1 = No\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e2 = Yes\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eInternet access\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003eHousehold has internet access\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e1 = No\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"bottom\"\u003e\n \u003cp\u003e2 = Yes\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"899\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" valign=\"top\" style=\"width: 899px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 2.\u003c/strong\u003e Distribution of health facility use (\u003cem\u003eN\u003c/em\u003e=5,757)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 179px;\"\u003e\n \u003cp\u003ePredictors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003eSample size\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003eDid not deliver at a health facility\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003eDelivered at a health facility\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003eP-Value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 179px;\"\u003e\n \u003cp\u003eTotal Sample Size\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 179px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003eWomen\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003e850 [14.76%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003e4,907 [85.4%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 179px;\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e5,757 [100.00%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 179px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e15 to 24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e1509 [26.21%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003e223 [14.78%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003e1286 [85.22%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003e0.036\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 179px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e25 to 34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e2767 [48.06%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003e380 [13.74%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003e2387 [86.26%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 179px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003e35 to 49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e1481 [25.73%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003e247 [16.68%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003e1234 [83.32%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 179px;\"\u003e\n \u003cp\u003eWealth\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 179px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003ePoor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e3290 [57.14%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003e716 [21.77%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003e2574 [78.23%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003e\u0026lt;0.0001*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 179px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003eMiddle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e1038 [18.03%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003e85 [8.19%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003e953 [91.81%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 179px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003eRich\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e1429 [24.83%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003e49 [3.43%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003e1380 [96.57%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 179px;\"\u003e\n \u003cp\u003eEducation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 179px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003eNone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e1722 [29.91%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003e426 [24.74%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003e1296 [75.26%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003e\u0026lt;0.0001*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 179px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003ePrimary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e929 [16.14%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003e169 [18.19%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003e760 [81.81%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 179px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003eSecondary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e2678 [46.51%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003e247 [9.22%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003e2431 [90.78%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 179px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003eHigher\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e428 [7.43%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003e8 [1.87%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003e420 [98.13%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 179px;\"\u003e\n \u003cp\u003eResidence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 179px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003eUrban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e2351 [40.84%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003e140 [5.96%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003e2111 [94.04%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003e\u0026lt;0.0001*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 179px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003eRural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e3406 [59.16%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003e710 [20.85%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003e2696 [79.15%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 179px;\"\u003e\n \u003cp\u003eRadio\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 179px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e3177 [55.18%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003e502 [15.80%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003e2675 [84.20%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003e0.014\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 179px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e2580 [44.82%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003e348 [13.49%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003e2232 [86.51%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 179px;\"\u003e\n \u003cp\u003eMobile Phone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 179px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e1470 [25.54%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003e381 [25.92%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003e1089 [74.08%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003e\u0026lt;0.0001*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 179px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e4287 [74.46%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003e469 [10.95%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003e3818 [89.05%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 179px;\"\u003e\n \u003cp\u003eTV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 179px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e2447 [42.51%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003e554 [22.64%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003e1893 [77.36%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003e\u0026lt;0.0001*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 179px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e3310 [57.49%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003e296 [8.94%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003e3014 [91.06%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 179px;\"\u003e\n \u003cp\u003eNewspaper/Magazine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 179px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e5577 [96.87%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003e844 [15.13%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003e4733 [84.87%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003e\u0026lt;0.0001*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 179px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e180 [3.13%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003e6 [3.33%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003e174 [96.67%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 179px;\"\u003e\n \u003cp\u003eInternet Access\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 179px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e4030 [70.01%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003e758 [18.81%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003e3272 [81.19%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\n \u003cp\u003e\u0026lt;0.0001*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 179px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 90px;\"\u003e\n \u003cp\u003eYes\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 132px;\"\u003e\n \u003cp\u003e1727 [29.99%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 168px;\"\u003e\n \u003cp\u003e92 [5.33%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 164px;\"\u003e\n \u003cp\u003e1635 [94.67%]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 166px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"863\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 863px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 3.\u0026nbsp;\u003c/strong\u003eUnadjusted odds ratio and 95% confidence interval of using health facility for delivery by demographic and mass media factors in the bivariable logistic regression analyses.\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 276px;\"\u003e\n \u003cp\u003ePredictors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003eUnadjusted Odds Ratio (95% Confidence Interval)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 221px;\"\u003e\n \u003cp\u003eP-Value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 276px;\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 221px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 276px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e15 to 24\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 221px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 276px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e25 to 34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e1.09 [0.91, 1.30]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 221px;\"\u003e\n \u003cp\u003e0.348\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 276px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003e35 to 49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e0.86 [0.71, 1.06]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 221px;\"\u003e\n \u003cp\u003e0.154\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 276px;\"\u003e\n \u003cp\u003eWealth\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 221px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 276px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003ePoor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 221px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 276px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003eMiddle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e3.12 [2.46, 3.95]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 221px;\"\u003e\n \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 276px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003eRich\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e7.83 [5.82, 10.54]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 221px;\"\u003e\n \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 276px;\"\u003e\n \u003cp\u003eEducation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 221px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 276px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003eNo education\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 221px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 276px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003ePrimary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e1.48 [1.21, 1.80]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 221px;\"\u003e\n \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 276px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003eSecondary\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e3.24 [2.73, 3.84]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 221px;\"\u003e\n \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 276px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003eHigher\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e17.26 [8.50, 35.03]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 221px;\"\u003e\n \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 276px;\"\u003e\n \u003cp\u003eResidence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 221px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 276px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003eRural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 221px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 276px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003eUrban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e4.15 [3.44, 5.03]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 221px;\"\u003e\n \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 276px;\"\u003e\n \u003cp\u003eRadio\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 221px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 276px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 221px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 276px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e1.20 [1.04, 1.40]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 221px;\"\u003e\n \u003cp\u003e0.014\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 276px;\"\u003e\n \u003cp\u003eMobile Phone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 221px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 276px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 221px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 276px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e2.85 [2.45, 3.31]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 221px;\"\u003e\n \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 276px;\"\u003e\n \u003cp\u003eTV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 221px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 276px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 221px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 276px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e2.98 [2.56, 3.47]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 221px;\"\u003e\n \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 276px;\"\u003e\n \u003cp\u003eNewspaper/Magazine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 221px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 276px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 221px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 276px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e5.17 [2.28, 11.71]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 221px;\"\u003e\n \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 276px;\"\u003e\n \u003cp\u003eInternet Access\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 221px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 276px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 221px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 276px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 161px;\"\u003e\n \u003cp\u003eYes\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 205px;\"\u003e\n \u003cp\u003e4.12 [3.29, 5.15]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 221px;\"\u003e\n \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"863\" class=\"fr-table-selection-hover\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"4\" valign=\"top\" style=\"width: 863px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 4.\u0026nbsp;\u003c/strong\u003eAdjusted odds ratio and 95% confidence interval of using health facility for delivery by demographic and mass media factors in the multiple logistic regression analyses.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 307px;\"\u003e\n \u003cp\u003ePredictors\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 228px;\"\u003e\n \u003cp\u003eAdjusted Odds Ratio (95% CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 185px;\"\u003e\n \u003cp\u003eP-Value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 307px;\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 228px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 185px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 307px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e15 to 24\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 228px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 185px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 307px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e25 to 34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 228px;\"\u003e\n \u003cp\u003e0.96 [0.79, 1.17]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 185px;\"\u003e\n \u003cp\u003e0.736\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 307px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003e35 to 49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 228px;\"\u003e\n \u003cp\u003e0.93 [0.74, 1.15]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 185px;\"\u003e\n \u003cp\u003e0.531\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 307px;\"\u003e\n \u003cp\u003eWealth\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 228px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 185px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 307px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003ePoor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 228px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 185px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 307px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eMiddle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 228px;\"\u003e\n \u003cp\u003e1.43 [1.08, 1.88]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 185px;\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 307px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eRich\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 228px;\"\u003e\n \u003cp\u003e2.22 [1.54, 3.19]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 185px;\"\u003e\n \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 307px;\"\u003e\n \u003cp\u003eEducation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 228px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 185px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 307px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eNo education\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 228px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 185px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 307px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003ePrimary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 228px;\"\u003e\n \u003cp\u003e1.15 [0.93, 1.42]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 185px;\"\u003e\n \u003cp\u003e0.178\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 307px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eSecondary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 228px;\"\u003e\n \u003cp\u003e1.77 [1.45, 2.15]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 185px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 307px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eHigher\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 228px;\"\u003e\n \u003cp\u003e3.06 [1.42, 6.60]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 185px;\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 307px;\"\u003e\n \u003cp\u003eResidence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 228px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 185px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 307px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eRural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 228px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 185px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 307px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eUrban\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 228px;\"\u003e\n \u003cp\u003e1.98 [1.59, 2.47]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 185px;\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 307px;\"\u003e\n \u003cp\u003eRadio\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 228px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 185px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 307px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 228px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 185px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 307px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 228px;\"\u003e\n \u003cp\u003e1.00 [0.85, 1.17]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 185px;\"\u003e\n \u003cp\u003e0.959\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 307px;\"\u003e\n \u003cp\u003eMobile Phone\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 228px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 185px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 307px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 228px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 185px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 307px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 228px;\"\u003e\n \u003cp\u003e1.59 [1.35, 1.87]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 185px;\"\u003e\n \u003cp\u003e\u0026lt;0.0001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 307px;\"\u003e\n \u003cp\u003eTV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 228px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 185px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 307px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 228px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 185px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 307px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 228px;\"\u003e\n \u003cp\u003e1.30 [1.08, 1.56 ]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 185px;\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 307px;\"\u003e\n \u003cp\u003eNewspaper/Magazine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 228px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 185px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 307px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 228px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 185px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 307px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 228px;\"\u003e\n \u003cp\u003e1.70 [0.73, 3. 97]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 185px;\"\u003e\n \u003cp\u003e0.215\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 307px;\"\u003e\n \u003cp\u003eInternet Access\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 228px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 185px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 307px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 228px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 185px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 307px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eYes\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 228px;\"\u003e\n \u003cp\u003e1.83 [1.49, 2.26]\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 185px;\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"media exposure, health facility delivery, maternal health, digital health","lastPublishedDoi":"10.21203/rs.3.rs-6925215/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6925215/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground:\u003c/h2\u003e \u003cp\u003eDespite a free maternal healthcare policy, many women in Ghana still give birth outside of health facilities. While prior research has examined how sociodemographic factors influence facility-based delivery, little is known about the role of various types of media exposure. This study examines the association between media exposure and the use of health facilities for delivery among women in Ghana.\u003c/p\u003e\u003ch2\u003eMethods:\u003c/h2\u003e \u003cp\u003eThis study analyzed nationally representative data from the 2022 Ghana Demographic and Health Survey, focusing on 5,757 women aged 15\u0026ndash;49. Descriptive statistics and logistic regressions were conducted to assess the association between media exposure and health facility delivery.\u003c/p\u003e\u003ch2\u003eResults:\u003c/h2\u003e \u003cp\u003eAmong the respondents, 85.3% delivered at a health facility. Higher education, wealth, and urban residence were significantly associated with health facility delivery. Mobile phone ownership (AOR\u0026thinsp;=\u0026thinsp;1.59, 95% CI: 1.35\u0026ndash;1.87), television viewership (AOR\u0026thinsp;=\u0026thinsp;1.30, 95% CI: 1.08\u0026ndash;1.56), and Internet access (AOR\u0026thinsp;=\u0026thinsp;1.83, 95% CI: 1.49\u0026ndash;2.26) were all significantly associated with increased odds of facility-based delivery. Radio and newspaper exposure were not significant predictors in the adjusted analysis.\u003c/p\u003e\u003ch2\u003eConclusions:\u003c/h2\u003e \u003cp\u003eMedia exposure, particularly through mobile phones, television, and the Internet, significantly shapes maternal health behaviors and facility delivery in Ghana. Public health strategies to reduce maternal mortality should leverage these media channels to deliver targeted, culturally relevant health messages encouraging safe childbirth practices.\u003c/p\u003e","manuscriptTitle":"The Association Between Media Exposure and Health Facility Delivery in Ghana","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-06-19 10:47:02","doi":"10.21203/rs.3.rs-6925215/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"c31ba04f-0306-4989-9af8-fc86f704de6a","owner":[],"postedDate":"June 19th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-07-02T04:53:37+00:00","versionOfRecord":[],"versionCreatedAt":"2025-06-19 10:47:02","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6925215","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6925215","identity":"rs-6925215","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}