Determinants of autonomy in sexual and reproductive health decision making among women: A mixed-effects multilevel analysis of the demographic and health survey in Ghana

Determinants of autonomy in sexual and reproductive health decision making among women: A mixed-effects multilevel analysis of the demographic and health survey 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 Determinants of autonomy in sexual and reproductive health decision making among women: A mixed-effects multilevel analysis of the demographic and health survey in Ghana John Lapah Niyi, Isaac Tetteh, Fidelis Zumah, Amanda Debuo Der This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6375599/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 14 You are reading this latest preprint version Abstract Background: Women’s autonomy in sexual and reproductive health (SRH) decision making is essential for achieving sustainable development goals (SDGs) 3 (ensuring healthy lives and promoting well-being) and 5 (achieving gender equality and empowering all women and girls). However, SRH decision-making autonomy remains limited with disparities in low- and middle-income countries (LMICs), including Ghana. Hence, this study examined the determinants of women’s autonomy in SRH decision making in Ghana. Methodology: We analyzed data from the 2022 Ghana Demographic and Health Survey (DHS), a nationally representative cross-sectional dataset. The sample included 8,811 married or cohabiting women aged 15-49 years. A mixed-effect multilevel binary logistic regression model was used to identify the determinants of SRH decision-making autonomy, with results presented as adjusted odds ratios (aORs) with 95% confidence intervals (CIs). Results: We found that 51.7% [CI=49.8,53.7] of Ghanaian women had autonomy in SRH decision-making. SRH decision-making autonomy was significantly high among women aged 35--39 years [aOR=2.06; CI=1.19,3.55], 45-49 years [aOR=2.76; CI=1.57,4.86], those with secondary education [aOR=1.65; CI=1.34,2.02], those with higher education [aOR=3.33; CI=2.31,4.80], those with media exposure [aOR=1.38; CI=1.11,1.70], those currently working [aOR=1.67; CI=1.33,2.09], and having a partner with secondary [aOR = 1.26; CI: 1.04,1.52] or higher education [aOR = 1.41; CI: 1.05,1.88], compared to their respective reference categories. Conversely, lower SRH decision-making autonomy was observed among Muslim women [aOR=0.72; CI=0.57,0.91] and rural residents [aOR=0.74; CI=0.59,0.91] compared to Christian women and urban resident women, respectively. Additionally, significant regional and ethnic disparities were evident, indicating important structural and sociocultural influences on women’s autonomy in SRH decisions. Conclusion: Nearly half of Ghanaian women lacked autonomy in SRH decision-making, significantly influenced by age, education, exposure to media, current work status, religion, ethnicity, and geographic region. Addressing these disparities requires targeted multilevel interventions that consider the unique cultural and socio-economic barriers faced by disadvantaged groups. Autonomy sexual and reproductive health decision-making demographic and health survey Ghana Introduction Women’s sexual and reproductive health (SRH) decision-making autonomy is fundamental to achieving gender equity and improving health outcomes globally. Autonomy in this domain reflects a woman’s ability to make informed choices regarding her SRH, including contraceptive use, family planning, and access to healthcare, free from coercion or external influence. 1 Additionally, the United Nations (UN) stipulates that autonomy in SRH decision-making among women is the ability to independently or jointly with their partners decide on health care for themselves, decide on contraceptive use, and to say no to sex with their husbands/partners if they do not want to. 2 This autonomy is not only a fundamental human right but also a cornerstone of global public health efforts, as underscored by the United Nations Sustainable Development Goals (SDGs), particularly SDG 3 on health and well-being and SDG 5 on gender equality and women’s empowerment. 3 Women’s SRH autonomy empowers them to choose whether to engage in a sexual relationship with their husband or partner, control over contraceptive use, and the right to decide to seek and utilize SRH services. 4 Empowering women in SRH decision-making autonomy has had a significant impact on health-related outcomes for women and their families. For example, studies have reported that women’s autonomy in SRH decision-making is positively correlated with increased antenatal and postnatal visits, reduced morbidity and mortality in women and children, increased family planning and improved child health and welfare. 5 – 7 In the 1994 International Conference on Population and Development (ICPD) held in Egypt, UN member states made a commitment to the empowerment of women with respect to sexual and reproductive health rights (SRHR). At the fifty-seventh World Health Assembly in 2004, the governments renewed their commitment to heighten the implementation of the 1994 ICPD action plan. Consequently, some progress has been achieved during the past few decades. However, this has since stagnated with increasing inequalities and sociocultural disparities. 8 – 11 Despite its recognized importance, SRH decision-making autonomy remains low in many low- and middle-income countries (LMICs), including Ghana. Studies have reported low levels of autonomy in SRH decision-making among women in LMICs. For instance, significant disparities were observed among regions, with approximately 80% reported in Europe, Southeastern Asia, and Latin America. However, Western and Middle Africa reported that fewer than 40% of women had decision-making autonomy. 6 , 12 In most developing countries, research has shown that cultural norms, religion, limited education, financial dependency, and inadequate healthcare infrastructure significantly affect women’s ability to exercise autonomy over their reproductive health. 6 , 13 – 16 Similarly, an earlier study in Ghana showed that women who are wealthier, live in urban areas, and are more educated have more control over their reproductive health. 17 Like many sub-Saharan African countries, Ghana faces persistent gender inequalities that are deeply rooted in traditional societal structures, influencing women’s decision-making capabilities. Rural women experience heightened vulnerability due to limited access to education and healthcare services, as well as increased exposure to patriarchal norms that prioritize male authority in household decisions. 13 Similarly, regarding the use of modern contraceptives for sexually transmitted infections (STIs) control and birth control, research has shown that women are less autonomous than men are, mainly because of male dominance and cultural influence at the household and community levels, respectively. 14 Although some studies have assessed autonomy in SRH decision making in Ghana, most of those studies relies on small, geographically limited samples, which are not nationally representative or outdated data. 18 – 20 Given the evolving socio-cultural nature and how vital women’s SRH decision-making autonomy is to achieve gender equality and good health and well-being, a comprehensive, nationally representative study is essential. Using the 2022 DHS, this study aims to assess the determinants of SRH decision-making autonomy among Ghanaian women. Methodology Study site description This study was conducted in Ghana, which is located in West Africa. The country has diverse ethnicities and cultural heritages. Based on the 2021 population and housing census, Ghana has a total population of approximately 30.8 million, with a population density of 129 persons per square kilometer. Ghana has 16 and 275 administrative regions and metropolitan/ municipal/ district assemblies respectively. 21 Study design and sampling method This is a cross-sectional study using data from the 2022 Ghana DHS. This nationally representative survey is conducted periodically in LMICs to provide updated estimates of fundamental demographic and health indicators. The DHS survey employed a stratified two-stage cluster sampling design. First, clusters representing the primary sampling units (PSUs) were selected from a sampling frame in both urban and rural areas in each of the 16 regions via systematic random sampling. In the second stage, systematic sampling was used to select households from a household sampling frame in each cluster where the participants were interviewed. 22 Detailed information about the survey design is available in the literature. 23 Study population The study involved 8,811 women in Ghana who were married or living with a partner (cohabiting). Variables Outcome variables The outcome variable for this study was autonomy in SRH decision-making among women. This outcome variable is defined as married or cohabiting women aged 15–49 years who (1) decide on health care for themselves, either alone or jointly with their husbands or partners; (2) decide on the use of contraception, either alone or jointly with their husbands or partners; and (3) can say no to sex with their husband or partner if they do not want to. 2 Exposure variables The exposure variables were grouped into individual and contextual-level variables. The individual-level variables included the age of the woman, number of children, educational level, exposure to media, current work status, husband/partner’s age, husband/partner’s educational level, ethnicity, and religion. The contextual-level variables included place of residence, wealth index, and region. Table 1 presents the exposure variables and their categories. Data analysis We first performed a descriptive univariate analysis to describe the characteristics of the study population with weighted frequencies and percentages. We also calculated the weighted prevalence of autonomy in SRH decision-making among women in Ghana along with the 95% confidence interval (CI) according to the original sampling weight provided by the DHS. We then performed bivariate cross-tabulation to describe the distribution of decision-making autonomy across the individual and contextual-level variables. The Pearson chi-square (χ²) test was used to determine the variables that had a statistically significant association with autonomy in SRH decision-making among women. Finally, we determined the individual- and contextual-level factors associated with the outcome, autonomy in SRH decision-making among women using a mixed-effect multilevel binary logistic regression model. Four models (Models I–IV) were fitted. Model I was a null model (without any predictor variable) that showed the variation in decision-making autonomy resulting from clustering at the PSU. Model II included only individual-level variables, whereas Model III included only contextual-level variables. Both the individual- and contextual-level variables were included in Model IV. The fixed-effect output showing the determinants of autonomy in SRH decision-making among women was presented using adjusted odds ratios (aORs) along with their 95% CIs. A p-value < 0.05 was considered to indicate statistical significance. We used Stata version 17 to perform the analysis. All analyses were weighted using svyset command to account for the complex nature of the DHS dataset due to the sampling technique used. Results Table 1 Demographic characteristics of the women in Ghana (n = 8811) Variable Weighted frequency (n) Weighted percentage (%) Age of women (years) 15–19 208 2.4 20–24 1,088 12.3 25–29 1,565 17.8 30–34 1,846 20.9 35–39 1,763 20 40–44 1,331 15.1 45–49 1,010 11.5 Number of children None 637 7.2 1 1,554 17.6 2 1,687 19.1 3 1,613 18.3 4+ 3,320 37.7 Educational level No education 2,164 24.6 Primary 1,324 15 Secondary 4,482 50.9 Higher 841 9.5 Exposure to media No 1,300 14.8 Yes 7,511 85.2 Current work status No 1,358 15.4 Yes 7,453 84.6 Currently residing with husband/partner Living with husband/partner 6,681 75.8 Staying elsewhere 2,130 24.2 Husband/Partner's age (years) 15–19 12 0.1 20–29 1,193 13.5 30–39 3,115 35.4 40–49 2,905 33 50–59 1,169 13.3 60 and above 416 4.7 Husband/Partner’s educational level No education 1,986 22.5 Primary 776 8.8 Secondary 4,689 53.2 Higher 1,361 15.4 Ethnicity Akan 3,593 40.8 Ga/Dangme 550 6.2 Ewe 942 10.7 Guan 268 3.0 Mole-Dagbani 1,964 22.3 Grusi 334 3.8 Gurma 763 8.7 Mande 315 3.6 Other 81 0.9 Religion Christian 6,311 71.6 Islam 2,065 23.4 Traditionalist 235 2.7 Others 200 2.3 Place of residence Urban 4,562 51.8 Rural 4,249 48.2 Wealth index of household Poor 3,410 38.7 Middle 1,659 18.8 Rich 3,742 42.5 Region Western 523 5.9 Central 876 9.9 Greater Accra 1,229 13.9 Volta 403 4.6 Eastern 679 7.7 Ashanti 1,532 17.4 Western North 248 2.8 Ahafo 196 2.2 Bono 305 3.5 Bono East 404 4.6 Oti 266 3 Northern 935 10.6 Savannah 234 2.7 North East 246 2.8 Upper East 457 5.2 Upper West 277 3.1 Source: Authors’ analysis 2024 The background characteristics of the women are presented in Table 1 . Our analysis included a total of 8,811 women aged 15–49 years from Ghana who were currently married or in a union. Most of the women were within 30–34 years (20.9%) and had at least 4 children. More than half of the women had secondary education (50.9%), were exposed to media (85.2%), were working (84.6%), and were living with their husband/partner (75.8%). Most of the women’s husbands/partners were aged 30–39 years (35.4%) and had attained secondary education (53.2%). Approximately 41% belong to the Akan ethnic group. With respect to contextual (community and household) characteristics, 51.8% and 17.4% resided in urban areas and the Ashanti region respectively, whereas 42.5% lived in rich wealth index households. Table 2 Bivariate analysis of sociodemographic variables and autonomy in sexual and reproductive health decision-making among women in Ghana Variable Autonomy in sexual and reproductive health decision making % [95% CI] P value Prevalence 51.7 [49.8,53.7] Age of women (years) < 0.001 15–19 32.4 [24.7,41.2] 20–24 43.7 [40.0,47.4] 25–29 48.1 [44.6,51.6] 30–34 55.2 [52.0,58.3] 35–39 55.5 [52.0,59.0] 40–44 51.5 [47.4,55.7] 45–49 57.3 [53.0,61.5] Number of children 0.016 None 49.2 [44.0,54.4] 1 52.6 [49.0,56.1] 2 56.0 [52.6,59.4] 3 52.4 [48.6,56.2] 4+ 49.3 [46.6,52.0] Educational level < 0.001 No education 35.7 [32.4,39.2] Primary 50.3 [46.6,54.0] Secondary 55.6 [53.4,57.8] Higher 74.5 [70.0,78.5] Exposure to media < 0.001 No 33.6 [29.9,37.5] Yes 54.9 [52.8,56.9] Current work status < 0.001 No 39.5 [35.5,43.7] Yes 54.0 [51.9,56.0] Currently residing with husband/partner 0.126 Living with husband/partner 51.1 [48.8,53.3] Staying elsewhere 53.9 [50.7,57.0] Husband/Partner's age (years) < 0.001 15–19 13.2 [3.8,37.0] 20–29 45.2 [41.7,48.7] 30–39 52.3 [49.6,54.8] 40–49 55.1 [52.2,58.1] 50–59 51.0 [47.1,54.9] 60 and above 46.0 [39.8,52.4] Husband/Partner educational level < 0.001 No education 36.4 [33.1,39.7] Primary 46.4 [41.8,51.0] Secondary 54.9 [52.6,57.1] Higher 66.4 [62.8,69.8] Ethnicity < 0.001 Akan 58.9 [55.9,61.8] Ga/Dangme 56.7 [47.9,65.2] Ewe 56.3 [51.3,61.1] Guan 56.3 [48.1,64.1] Mole-Dagbani 41.9 [37.9,45.9] Grusi 46.3 [39.6,53.0] Gurma 41.9 [36.6,47.3] Mande 34.2 [25.9,43.6] Other 56.5 [40.3,71.3] Religion < 0.001 Christian 56.9 [54.7,59.0] Islam 37.8 [33.8,41.9] Traditionalist 40.6 [32.0,49.8] Others 46.8 [37.6,56.3] Place of residence < 0.001 Urban 59.3 [56.4,62.1] Rural 43.6 [41.2,46.1] Wealth index < 0.001 Poor 40.7 [38.2,43.3] Middle 51.2 [47.7,54.8] Rich 62.0 [59.2,64.7] Region < 0.001 Western 69.0 [62.3,75.0] Central 59.4 [54.5,64.2] Greater Accra 69.0 [62.5,74.8] Volta 54.5 [48.5,60.3] Eastern 42.1 [35.7,48.7] Ashanti 47.8 [42.2,53.4] Western North 40.5 [33.6,47.8] Ahafo 37.4 [28.6,47.2] Bono 61.7 [55.2,67.9] Bono East 50.9 [44.0,57.7] Oti 50.5 [43.5,57.4] Northern 40.1 [32.7,47.9] Savannah 39.1 [31.9,46.8] North East 28.5 [22.0,36.2] Upper East 52.5 [48.1,56.8] Upper West 40.8 [33.4,48.5] Source: Author analysis, 2024. P values generated from the chi-square test As shown in Table 2 , approximately half of the women (52% [49.8, 53.7%]) had autonomy in SRH decision-making. Women aged 45–49 years had the highest prevalence of SRH decision-making autonomy, whereas those aged 15–19 years had the lowest prevalence. Women who had no education as well as husbands/partners with no education had the lowest (35.7% [32.4, 39.2]) and (36.4% [33.1, 39.7]) autonomy in SRH decision-making respectively. SRH decision-making autonomy was high among women who were exposed to media (54.9% [52.8, 56.9%], were workers (54.0% [51.9, 56.0%], belonged to the Akan ethnic group (58.9% [55.9, 61.8]), and were Christians (56.9% [54.7, 59.0]). Conversely, the lowest prevalence of autonomy in SRH decision-making was reported among those who resided in rural areas (43.6% [41.2,46.1]), households with poor wealth indices (40.7% [38.2,43.3]) and those who also resided in North East region (28.5% [22.0,36.2]). All the exposure variables except for currently residing with a husband/partner were significantly associated with autonomy in SRH decision making (p < 0.005). Table 3 Determinants of autonomy in sexual and reproductive health decision-making among women in Ghana Variables Model I empty model Model II aOR [95% CI] Model III aOR [95% CI] Model IV aOR [95% CI] Fixed effect results Age of women (years) 15–19 Ref Ref 20–24 1.39 [0.82,2.35] 1.39 [0.82,2.35] 25–29 1.59 [0.94,2.69] 1.59 [0.94,2.69] 30–34 1.96 * [1.16,3.31] 1.96 * [1.16,3.31] 35–39 2.06 ** [1.20,3.56] 2.06 ** [1.19,3.55] 40–44 1.92 * [1.08,3.42] 1.93 * [1.09,3.43] 45–49 2.76 *** [1.57,4.86] 2.76 *** [1.57,4.86] Number of children None Ref Ref 1 1.02 [0.76,1.37] 1.02 [0.76,1.37] 2 1.05 [0.75,1.46] 1.04 [0.75,1.46] 3 0.85 [0.60,1.19] 0.84 [0.60,1.19] 4+ 0.93 [0.66,1.30] 0.92 [0.66,1.30] Educational level No education Ref Ref Primary 1.47 ** [1.16,1.86] 1.47 ** [1.16,1.86] Secondary 1.64 *** [1.34,2.02] 1.65 *** [1.34,2.02] Higher 3.31 *** [2.31,4.76] 3.33 *** [2.31,4.80] Exposure to media No Ref Ref Yes 1.38 ** [1.12,1.71] 1.38 ** [1.11,1.70] Current work status No Ref Ref Yes 1.65 *** [1.32,2.07] 1.67 *** [1.33,2.09] Husband/Partner's age (years) 15–19 Ref Ref 20–29 3.22 [0.86,12.04] 3.21 [0.86,12.00] 30–39 3.22 [0.85,12.23] 3.22 [0.85,12.21] 40–49 3.55 [0.92,13.66] 3.55 [0.92,13.63] 50–59 3.12 [0.81,11.96] 3.11 [0.81,11.93] 60 and above 3.08 [0.78,12.17] 3.08 [0.78,12.15] Husband/Partner ’s educational level No education Ref Ref Primary 1.17 [0.90,1.51] 1.17 [0.90,1.52] Secondary 1.26 * [1.04,1.52] 1.26 * [1.04,1.52] Higher 1.40 * [1.05,1.87] 1.41 * [1.05,1.88] Ethnicity Akan Ref Ref Ga/Dangme 0.91 [0.52,1.59] 0.89 [0.50,1.57] Ewe 0.92 [0.68,1.25] 0.91 [0.66,1.26] Guan 1.18 [0.79,1.75] 1.17 [0.78,1.75] Mole-Dagbani 0.70 * [0.53,0.93] 0.69 * [0.52,0.92] Grusi 0.90 [0.58,1.39] 0.88 [0.57,1.37] Gurma 0.63 * [0.44,0.90] 0.63 * [0.43,0.90] Mande 0.51 * [0.30,0.88] 0.51 * [0.29,0.87] Other 0.89 [0.41,1.95] 0.89 [0.41,1.95] Religion Christian Ref Ref Islam 0.73 ** [0.57,0.92] 0.72 ** [0.57,0.91] Traditionalist 0.90 [0.56,1.42] 0.90 [0.57,1.43] Others 0.86 [0.58,1.28] 0.86 [0.58,1.28] Place of residence Urban Ref Ref Rural 0.72 ** [0.58,0.89] 0.74 ** [0.59,0.91] Wealth index Poor Ref Ref Middle 1.25 * [1.02,1.53] 1.04 [0.84,1.29] Rich 1.56 *** [1.25,1.95] 0.97 [0.77,1.22] Region Western Ref Ref Central 0.54 ** [0.34,0.86] 0.50 ** [0.32,0.79] Greater Accra 0.78 [0.45,1.36] 0.81 [0.45,1.45] Volta 0.41 *** [0.25,0.68] 0.37 *** [0.22,0.64] Eastern 0.25 *** [0.15,0.41] 0.22 *** [0.13,0.38] Ashanti 0.34 *** [0.22,0.54] 0.33 *** [0.21,0.52] Western North 0.26 *** [0.16,0.42] 0.24 *** [0.15,0.40] Ahafo 0.21 *** [0.12,0.37] 0.22 *** [0.13,0.40] Bono 0.61 [0.37,1.00] 0.61 [0.37,1.02] Bono East 0.48 ** [0.29,0.79] 0.65 [0.40,1.07] Oti 0.44 ** [0.27,0.73] 0.54 * [0.32,0.91] Northern 0.24 *** [0.13,0.43] 0.54 * [0.30,1.00] Savannah 0.31 *** [0.18,0.54] 0.54 * [0.30,0.96] North East 0.19 *** [0.11,0.33] 0.40 ** [0.23,0.71] Upper East 0.57 * [0.36,0.90] 0.78 [0.47,1.28] Upper West 0.31 *** [0.18,0.55] 0.53 * [0.29,0.95] Random effect model PSU variance (95% CI) 1.38 [1.16,1.65] 1.17 [0.97,1.41] 0.96 [0.80,1.16] 0.93 [0.77,1.12] ICC 0.29 [0.26,0.33] 0.26 [0.23,0.30] 0.22 [0.20,0.26] 0.22 [0.19,0.25] Sample size 8811 8811 8811 8811 Number of clusters 618 618 618 618 Source: Author analysis, 2024 Model II adjusted for individual level factors Model III adjusted for community level factors Model IV adjusted for both individual and community level determinants aOR = adjusted odds ratio; CI = confidence interval; PSU = primary sampling unit; ICC = intraclass correlation coefficient * p < 0.05 ** p < 0.01 *** p < 0.001 Ref = Reference Category The odds of autonomy in SRH decision-making were greater among women aged 30–34 years [aOR = 1.96; CI = 1.16, 3.31], 35–39 years [aOR = 2.06; CI = 1.19, 3.55], 40–44 years [aOR = 1.93; CI = 1.09, 3.43], and 45–49 years [aOR = 2.76; CI = 1.57, 4.86] than among teenage women (15–19 years). Women who attained primary [aOR = 1.47; CI = 1.16, 1.86], secondary [aOR = 1.65; CI = 1.34, 2.02], or higher [aOR = 3.33; CI = 2.31, 4.80] educational levels had a higher odds of autonomy in SRH decision making compared to women who had no education. Women who had media exposure were 38% [aOR = 1.38; CI = 1.11, 1.70] more likely to have decision-making autonomy compared to those who were not exposed to media. Working women were 1.67 times [aOR = 1.67; 1.33, 2.09] more likely to have autonomy in SRH decision making than non-working women. The odds of decision-making autonomy were higher among women whose husbands/partners had secondary [aOR = 1.26; CI = 1.04, 1.52] and higher [aOR = 1.41; CI = 1.05, 1.88] educational levels compared to those whose husbands/partners were not educated. Compared with the Akan ethnic group, belonging to the Mole-Dagbani [aOR = 0.69; CI = 0.52, 0.92], Gurma [aOR = 0.63; CI = 0.43, 0.90], and Mande [aOR = 0.51; CI = 0.29, 0.87] ethnic groups was associated with lower odds of SRH decision-making autonomy. Compared with Christians, Islamic women were 28% [aOR = 0.72; CI = 0.57, 0.91] less likely to have autonomy in SRH decision making. The odds of autonomy in SRH decision-making were 26% lower among women who resided in rural areas [aOR = 0.74; CI = 0.59, 0.91] compared with urban resident women. Compared with women from the Western region, women who resided in Central, Volta, Eastern, Ashanti, Western North, Ahafo, Oti, Northern, Savannah, Northeast, and Upper West regions had lower odds of having SRH decision-making autonomy (Table 3 ). The random effects model is also presented in Table 3 . Discussion This study examined the determinants of autonomy in SRH decision-making among women in Ghana. First, we observed that approximately half of Ghanaian women lacked autonomy in SRH decision-making. Second, the individual-level determinants associated with autonomy in decision-making were being older, having a high educational level, being exposed to media, currently working, having a husband/partner with at least secondary educational, ethnicity (Mole-Dagbani, Gruma, Mande), and religion. Finally, the contextual factors associated with autonomy in SRH decision-making included place of residence, higher household wealth index, and region of residence. The finding that approximately half of Ghanaian women lack autonomy in decision making corroborates the findings of previous studies in some LMICs. 24 – 26 Conversely, much lower levels of SRH decision-making autonomy have been reported in other studies. 4 , 14 , 27 In Ghana, several nongovernmental organizations (NGOs) are championing women’s empowerment initiatives and interventions. For example, Norsaac and WomensTrust, are one of the leading NGOs promoting SRH rights among women in Ghana. This has notably led to an increased level of decision-making autonomy compared with that of some LMICs. 4 Despite these efforts, approximately half of these women still lack autonomy in SRH decision-making. This calls for urgent and effective population-focused interventions to empower women on SRH decision-making. Empowering women in SRH decision making is pivotal in enhancing women’s and child health outcomes and bridging the gender inequality gap. However, significant disparities and inequalities continue to limit this autonomy. We observed that older (30–49 years) women were more likely to have decision-making autonomy than teenage women were, which is in line with previous research findings in LMICs. 4 , 6 , 24 For instance, studies in Ethiopia and Nepal reported that women aged 30–49 years were approximately 2 times more likely to have autonomy in decision making compared with teenage women. 4 , 24 The higher odds of decision-making autonomy observed among older women may be attributed to the respect and recognition accorded to them in society. In addition, their lived experiences and societal role as mothers empowered them to make independent decisions on their health needs. In contrast, younger women may still be under the control of their in-laws and husbands/partners in terms of making decisions. Hence, they have little to no autonomy in making sexual and healthcare decisions. 4 , 24 Moreover, we found that higher education is associated with increased autonomy in sexual reproductive decision-making among women. In particular, women who attained at least primary and secondary education were 40–60% more likely to have decision-making autonomy compared with uneducated women, whereas higher education increased decision-making autonomy by 3 times. Similarly, previous studies have shown that higher education is positively correlated with autonomy in SRH decision-making. 6 , 14 , 27 Higher education enlightens women on their SRHR and enhances their self-confidence and ability to make informed decisions. In addition, higher education has been reported to be associated with high health literacy levels. 28 , 29 Notably, women whose husbands/partners had attained at least secondary education were more likely to have decision-making autonomy compared with the reference group, which is consistent with the findings of previous studies. 6 , 14 , 27 This observation implies that well-educated men may be more inclined toward gender equality and depart from the societal norm of male dominance in household decision making 30 , hence empowering their wives/partners to make decisions by themselves or jointly with their husbands/partners. Consistent with previous studies 4 , 14 , 26 we found that women exposed to media were 38% more likely to have decision-making autonomy compared with those without media exposure. For example, studies in Ethiopia and Nigeria reported that decision-making autonomy increased by more than twofold among media-exposed women compared with those not exposed to media. 14 , 26 This implies that women’s exposure to television, radio, newspapers and other media sources enhances their access to information and informed decision-making behaviors. Consequently, they are empowered to exercise SRH decision-making autonomy. Hence, the media should be properly utilized to educate the public on SRHR. With respect to religion, this study revealed that Muslim women were 28% less likely to have decision-making autonomy compared with Christian women. Previous studies reported comparable findings where lower odds of decision-making autonomy were observed among Muslim women. 13 , 14 In contrast, findings reported by Adweeti Nepal et al. 4 did not find religion to be a significant determinant of decision-making autonomy in the context of Nepal. This was attributed to a high proportion (86%) of women belonging to the Hindu religion, whereas other religions constituted a minimal percentage. 4 In northern Ghana, where Islam is the dominant religion, traditional and cultural gender norms are highly prevalent in Islamic homes. where men are mostly regarded as the sole decision makers with absolute marital control over women. Consequently, women are denied any form of decision-making autonomy. Accordingly, our results indicate that women who reside in rural areas are 26% less likely to have decision-making autonomy compared with urban residents. Our findings resonate with those of previous studies conducted in LMICs. 11 , 13 , 14 This may be because women residing in rural areas have limited educational opportunities, media exposure, and access to health facilities. This study further revealed ethnic and regional disparities in the autonomy of SRH decision-making among women. For example, women belonging to the Mole-Dagbani, Gurma, and Mande ethnic groups were less likely to have decision-making autonomy compared with Akan women. In response to these disparities and the low level of autonomy in SRH decision making among women in Ghana, targeted interventions for disadvantaged population groups should be adopted rather than wholesale interventions for general population groups. In particular, these tailored interventions should focus on rural populations, adolescent women, Muslim populations, and people with limited education to help bridge the decision-making autonomy gaps and disparities identified in this study. Limitations This study had some limitations. The sensitive nature of this research topic, coupled with self-reports of women’s SRH decision-making autonomy might lead to misestimation of the level of women’s decision-making autonomy. The Ghana DHS 2022 data used in this study included only three SRH dimensions and indicators. However, the SRH autonomy includes more than three dimensions. Moreover, a cross-sectional study design was used in this study, hence limiting the ability of the study to draw causal inferences. Nonetheless, this study used nationally representative data based on indicators by the SDGs of the SRHR, which makes it an ideal reference study for designing policies and interventions for the SRH decision-making autonomy in the context of Ghana. Policy implications This study reveals substantial geographic, socio-demographic, and cultural disparities in women’s autonomy over SRH decisions in Ghana. While approximately 51.7% of women reported SRH decision-making autonomy, this figure conceals important inequalities that demand tailored, regionally responsive policies and programs to achieve national and global commitments under SDG 3 (health) and SDG 5 (gender equality). The need for multisectoral and intersectional approaches and collaborations are of the essence in this regard. First and foremost, investments in female education should be central in improving SRH decision-making autonomy. The strong positive association between education and SRH autonomy suggests that increasing access to quality education especially beyond the primary level can empower women to make informed health decisions. Education should also be extended males to foster equitable gender norms and promote supportive partnerships in SRH matters. Also, economic empowerment initiatives should be prioritized, particularly in rural areas, where women face multiple layers of disadvantage. Programs that promote women’s employment and financial independence can increase their decision-making power, as evidenced by the higher autonomy among working women in this study. Further, mass media and information dissemination should be leveraged more systematically in public health programming. Media exposure was significantly associated with increased autonomy, indicating its potential to raise awareness about SRHR, address cultural norms regarding SRH decision-making autonomy, and promote gender-equitable behaviors. This can transcend across the different regions in the country. In addition, religious and cultural engagement is essential. Lower autonomy among Muslim women and women from certain ethnic groups (for instance Mole-Dagbani, Gurma, Mande) points to the need for culturally tailored interventions. Partnering with community and religious leaders can facilitate normative change in ways that are respectful, context-sensitive, and sustainable. Moreso, national policies should be revised to explicitly incorporate SRH decision-making autonomy as a measurable and actionable indicator of women’s empowerment. This includes strengthening monitoring and evaluation frameworks within the Ghana Health Service and Ministry of Gender, Children, and Social Protection to track progress and inform data-driven interventions. Conclusion The findings of this study indicate that approximately 1 in 2 women lack autonomy in SRH decision making in Ghana. The significant determinants of decision-making autonomy were age, educational level, religion, media exposure, and ethnicity. We further observed rural–urban and regional disparities in autonomy in decision-making. To address these gaps and disparities, SRHR interventions should be tailored to disadvantaged population groups and based on a sound understanding of the cultural and social norms of these populations. We recommend research assessing how the intersectionality of low educational attainment, rural residence and current work status influence the decision-making autonomy of women in Ghana. Abbreviations aOR Adjusted odds ratio CI Confidence interval DHS Demographic health survey ICPD Internation conference for population and development LMICs Low- and middle-income countries NGOs Nongovernmental organizations PSU Primary sampling unit SDG Sustainable development goal SRH Sexual and reproductive health SRHR Sexual and reproductive health right STIs Sexual transmitted infections UN United Nations Declarations Ethics approval and consent to participate Ethical clearance was not sought for the study since the secondary dataset is freely available in the public domain. A detailed description of the ethical issues regarding the DHS and its dataset usage can be assessed at http://goo.gl/ny8T6X. Consent for publication Note applicable Availability of data and materials The data used for this study is freely available at https://dhsprogram.com/data/dataset/Ghana_Standard-DHS_2022.cfm?flag=1 Competing interest The authors declare that they have no competing interests Funding The study received no funding Author contribution J.L.N. conceptualized and designed the study and led in data analysis and interpretation. J.L.N. and I.T. wrote the initial manuscript. F.Z., A.D.D., and I.T. contributed to the data analysis, interpretation of the results, and manuscript writing. All authors contributed to the critical revision of the manuscript. All authors approved the final submission of the manuscript. Acknowledgement Not applicable References Gebeyehu NA, Gelaw KA, Lake EA, Adela GA, Tegegne KD, Shewangashaw NE. Women decision-making autonomy on maternal health service and associated factors in low- and middle-income countries: Systematic review and meta-analysis. Volume 18. Women’s Health; 2022. United Nations Population Fund. SDG indicator metadata [Internet]. 2024 [cited 2025 Feb 22]. Available from: https://www.unfpa.org/sites/default/files/pub-pdf/programme_of_action_Web%20ENGLISH.pdf United Nations. The Sustainable Development Goals Report 2022 [Internet]. 2022 [cited 2025 Feb 23]. Available from: https://unstats.un.org/sdgs/report/2022/ Nepal A, Dangol SK, Karki S, Shrestha N. Factors that determine women’s autonomy to make decisions about sexual and reproductive health and rights in Nepal: A cross-sectional study. PLOS Global Public Health. 2023;3(1). Sano Y, Antabe R, Atuoye KN, Braimah JA, Galaa SZ, Luginaah I. Married women’s autonomy and post-delivery modern contraceptive use in the Democratic Republic of Congo. BMC Womens Health. 2018;18(1):4–10. Idris IB, Hamis AA, Bukhori ABM, Hoong DCC, Yusop H, Shaharuddin MAA et al. Women’s autonomy in healthcare decision making: a systematic review. BMC Womens Health. 2023;23(1). Tayal C, Sharma R, Lata K. Association between women’s autonomy and reproductive health outcomes in India. Journal of Medicine, Surgery, and Public Health [Internet]. 2024;4:100156. Available from: https://linkinghub.elsevier.com/retrieve/pii/S2949916X24001099 United Nations. Joint UN statement calling for sexual and reproductive health and rights for all [Internet]. 2024 Jul. Available from: https://www.un.org/development/desa/pd/content/regional-reviews-icpd-programme-action World Health Organization. Extending sexual and reproductive health and rights to future generations through science and evidence. Geneva; 2024. World Health Organization. Sexual and reproductive health for all: 20 years of the Global Strategy [Internet]. 2024 [cited 2025 Feb 23]. Available from: https://www.who.int/news/item/16-05-2024-sexual-and-reproductive-health-for-all-20-years-of-the-global-strategy Liang M, Katz L, Filmer-Wilson E, Idele P. Accelerating Progress in Women’s Sexual and Reproductive Health and Rights Decision-Making: Trends in 32 Low-and Middle-Income Countries and Future Perspectives [Internet]. Available from: United Nations Population Fund. Ensure universal access to sexual and reproductive health and reproductive rights. New York; 2020 Feb. Darteh EKM, Dickson KS, Doku DT. Women’s reproductive health decision making: A multi-country analysis of demographic and health surveys in sub-Saharan Africa. PLoS ONE. 2019;14(1). Mare KU, Aychiluhm SB, Tadesse AW, Abdu M. Married women’s decision-making autonomy on contraceptive use and its associated factors in Ethiopia: A multilevel analysis of 2016 demographic and health survey. SAGE Open Med. 2022;10. UNFPA. Research on factors that determine women’s ability to make decisions about sexual and reproductive health and rights. United Nations Popul Fund. 2019;I(October):9–11. Ramtohul R. Women’s sexual and reproductive rights in contemporary Africa. Expanding Perspectives on Human Rights in Africa. Taylor and Francis; 2019. pp. 251–67. Ameyaw EK, Tanle A, Kissah-Korsah K, Amo-Adjei J. Women’s Health Decision-Making Autonomy and Skilled Birth Attendance in Ghana. Int J Reprod Med. 2016;2016. Loll D, Fleming PJ, Stephenson R, King EJ, Morhe E, Manu A et al. Factors associated with reproductive autonomy in Ghana. Cult Health Sex [Internet]. 2021 [cited 2025 Mar 27];23(3):349–66. Available from: https://www.tandfonline.com/doi/abs/ 10.1080/13691058.2019.1710567 Darteh EKM, Doku DT, Esia-Donkoh K. Reproductive health decision making among Ghanaian women. Reprod Health [Internet]. 2014 Mar 15 [cited 2025 Mar 27];11(1):1–8. Available from: https://link.springer.com/articles/ 10.1186/1742-4755-11-23 Khalid AA, Irahola DLA, Salifu A. Women’s Autonomy in Maternal Healthcare Decision-Making in Urban Ghana. https://doi.org/103138/jcfs54402 [Internet]. 2024 Jul 26 [cited 2025 Mar 27];54(4):306–33. Available from: https://utppublishing.com/doi/10.3138/jcfs.54.4.02 Ghana Statistical Serivce. Ghana 2021 Population and Housing Census: General Report Volume 3A [Internet]. Accra. 2021. Available from: https://www.statsghana.gov.gh/gssmain/fileUpload/pressrelease/2021 PHC General Report Vol 3A_Population of Regions and Districts_181121.pdf. Ghana Statistical Serivce. Ghana Demographic and Health Survey. 2022. ICF International. Demographic and Health Survey Sampling and Household Listing Manual. Maryland, U.S.A: ICF International;: MEASURE DHS. Calverton; 2012. Kassahun A, Zewdie A. Decision-making autonomy in maternal health service use and associated factors among women in Mettu District, Southwest Ethiopia: A community-based cross-sectional study. BMJ Open. 2022;12(5). Saaka M. Women s decision-making autonomy and its relationship with child feeding practices and postnatal growth. J Nutr Sci. 2020;9. Solanke BL, Adetutu OM, Sunmola KA, Opadere AA, Adeyemi NK, Soladoye DA. Multi-level predictors of sexual autonomy among married women in Nigeria. BMC Womens Health. 2022;22(1). Asabu MD, Altaseb DK. The trends of women’s autonomy in health care decision making and associated factors in Ethiopia: evidence from 2005, 2011 and 2016 DHS data. BMC Womens Health. 2021;21(1). Jiregna B, Amare M, Dinku M, Nigatu D, Desalegn D. Women Health Literacy and Associated Factors on Women and Child Health Care in Ilu Ababor Public Health Facilities, Ethiopia. Int J Womens Health. 2024;16:143–52. Meldgaard M, Gamborg M, Terkildsen Maindal H. Health literacy levels among women in the prenatal period: A systematic review. Sexual and Reproductive Healthcare. Volume 34. Elsevier B.V.; 2022. Alemayehu M, Meskele M. Health care decision making autonomy of women from rural districts of Southern Ethiopia: A community based cross-sectional study. Int J Womens Health. 2017;9:213–21. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 15 Dec, 2025 Reviews received at journal 24 Nov, 2025 Reviewers agreed at journal 03 Nov, 2025 Reviewers agreed at journal 19 Sep, 2025 Reviewers agreed at journal 10 Jul, 2025 Reviewers agreed at journal 08 Jun, 2025 Reviews received at journal 31 May, 2025 Reviewers agreed at journal 16 May, 2025 Reviewers agreed at journal 29 Apr, 2025 Reviewers invited by journal 28 Apr, 2025 Editor invited by journal 09 Apr, 2025 Editor assigned by journal 08 Apr, 2025 Submission checks completed at journal 08 Apr, 2025 First submitted to journal 04 Apr, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6375599","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":449869024,"identity":"cb36a2d8-10fb-406d-a8ca-7b873e177a56","order_by":0,"name":"John Lapah Niyi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA1ElEQVRIiWNgGAWjYDACZgaGAxIMBxj42RuAPAMLErRI9hwAaZEg2q4DDAY3EkAMIrSYs/MYHrCouJNncPP51Q0/CiQY+Nu7E/BqsWzmMTggceZZseTtnLKbPUCHSZw5uwGvFoPDQC2SbYcT+27npN3gAWoxkMglUkvDzTNpN/+QpGXCDfZjt4m0ha0A6JfDiTN7cthuyxhI8BD2y/nDmz9LVBxO7Gc//uzmmz82cvztvfi1MDBwGDBDIoPHAEwSUA4C7A8YP0AZRKgeBaNgFIyCkQgAttlPeWgPJUIAAAAASUVORK5CYII=","orcid":"","institution":"Ghana Health Service, Gushegu Municipal Health Directorate","correspondingAuthor":true,"prefix":"","firstName":"John","middleName":"Lapah","lastName":"Niyi","suffix":""},{"id":449869025,"identity":"1f8e5c87-21a1-4cc1-928a-12de56eb082c","order_by":1,"name":"Isaac Tetteh","email":"","orcid":"","institution":"University of Health and Allied Sciences","correspondingAuthor":false,"prefix":"","firstName":"Isaac","middleName":"","lastName":"Tetteh","suffix":""},{"id":449869026,"identity":"350f2cc2-aeb0-4492-b85f-fa735bb75c53","order_by":2,"name":"Fidelis Zumah","email":"","orcid":"","institution":"George Mason University","correspondingAuthor":false,"prefix":"","firstName":"Fidelis","middleName":"","lastName":"Zumah","suffix":""},{"id":449869027,"identity":"5c26f4a4-d030-4bec-b007-d4cdb86a7318","order_by":3,"name":"Amanda Debuo Der","email":"","orcid":"","institution":"University of Washington","correspondingAuthor":false,"prefix":"","firstName":"Amanda","middleName":"Debuo","lastName":"Der","suffix":""}],"badges":[],"createdAt":"2025-04-04 11:08:09","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6375599/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6375599/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":82004462,"identity":"8ad1bc73-8c52-48fe-bbbf-41849544499d","added_by":"auto","created_at":"2025-05-05 21:08:56","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1576758,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6375599/v1/9d38f33b-f5cb-49f2-b725-fa4144fdcdc1.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Determinants of autonomy in sexual and reproductive health decision making among women: A mixed-effects multilevel analysis of the demographic and health survey in Ghana","fulltext":[{"header":"Introduction","content":"\u003cp\u003eWomen\u0026rsquo;s sexual and reproductive health (SRH) decision-making autonomy is fundamental to achieving gender equity and improving health outcomes globally. Autonomy in this domain reflects a woman\u0026rsquo;s ability to make informed choices regarding her SRH, including contraceptive use, family planning, and access to healthcare, free from coercion or external influence.\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e Additionally, the United Nations (UN) stipulates that autonomy in SRH decision-making among women is the ability to independently or jointly with their partners decide on health care for themselves, decide on contraceptive use, and to say no to sex with their husbands/partners if they do not want to.\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e This autonomy is not only a fundamental human right but also a cornerstone of global public health efforts, as underscored by the United Nations Sustainable Development Goals (SDGs), particularly SDG 3 on health and well-being and SDG 5 on gender equality and women\u0026rsquo;s empowerment.\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e Women\u0026rsquo;s SRH autonomy empowers them to choose whether to engage in a sexual relationship with their husband or partner, control over contraceptive use, and the right to decide to seek and utilize SRH services.\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e Empowering women in SRH decision-making autonomy has had a significant impact on health-related outcomes for women and their families. For example, studies have reported that women\u0026rsquo;s autonomy in SRH decision-making is positively correlated with increased antenatal and postnatal visits, reduced morbidity and mortality in women and children, increased family planning and improved child health and welfare.\u003csup\u003e\u003cspan additionalcitationids=\"CR6\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eIn the 1994 International Conference on Population and Development (ICPD) held in Egypt, UN member states made a commitment to the empowerment of women with respect to sexual and reproductive health rights (SRHR). At the fifty-seventh World Health Assembly in 2004, the governments renewed their commitment to heighten the implementation of the 1994 ICPD action plan. Consequently, some progress has been achieved during the past few decades. However, this has since stagnated with increasing inequalities and sociocultural disparities.\u003csup\u003e\u003cspan additionalcitationids=\"CR9 CR10\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e Despite its recognized importance, SRH decision-making autonomy remains low in many low- and middle-income countries (LMICs), including Ghana.\u003c/p\u003e \u003cp\u003eStudies have reported low levels of autonomy in SRH decision-making among women in LMICs. For instance, significant disparities were observed among regions, with approximately 80% reported in Europe, Southeastern Asia, and Latin America. However, Western and Middle Africa reported that fewer than 40% of women had decision-making autonomy.\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e In most developing countries, research has shown that cultural norms, religion, limited education, financial dependency, and inadequate healthcare infrastructure significantly affect women\u0026rsquo;s ability to exercise autonomy over their reproductive health.\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan additionalcitationids=\"CR14 CR15\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e Similarly, an earlier study in Ghana showed that women who are wealthier, live in urban areas, and are more educated have more control over their reproductive health.\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e Like many sub-Saharan African countries, Ghana faces persistent gender inequalities that are deeply rooted in traditional societal structures, influencing women\u0026rsquo;s decision-making capabilities. Rural women experience heightened vulnerability due to limited access to education and healthcare services, as well as increased exposure to patriarchal norms that prioritize male authority in household decisions.\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e Similarly, regarding the use of modern contraceptives for sexually transmitted infections (STIs) control and birth control, research has shown that women are less autonomous than men are, mainly because of male dominance and cultural influence at the household and community levels, respectively.\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eAlthough some studies have assessed autonomy in SRH decision making in Ghana, most of those studies relies on small, geographically limited samples, which are not nationally representative or outdated data.\u003csup\u003e\u003cspan additionalcitationids=\"CR19\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e Given the evolving socio-cultural nature and how vital women\u0026rsquo;s SRH decision-making autonomy is to achieve gender equality and good health and well-being, a comprehensive, nationally representative study is essential. Using the 2022 DHS, this study aims to assess the determinants of SRH decision-making autonomy among Ghanaian women.\u003c/p\u003e"},{"header":"Methodology","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy site description\u003c/h2\u003e \u003cp\u003eThis study was conducted in Ghana, which is located in West Africa. The country has diverse ethnicities and cultural heritages. Based on the 2021 population and housing census, Ghana has a total population of approximately 30.8\u0026nbsp;million, with a population density of 129 persons per square kilometer. Ghana has 16 and 275 administrative regions and metropolitan/ municipal/ district assemblies respectively.\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eStudy design and sampling method\u003c/h3\u003e\n\u003cp\u003eThis is a cross-sectional study using data from the 2022 Ghana DHS. This nationally representative survey is conducted periodically in LMICs to provide updated estimates of fundamental demographic and health indicators. The DHS survey employed a stratified two-stage cluster sampling design. First, clusters representing the primary sampling units (PSUs) were selected from a sampling frame in both urban and rural areas in each of the 16 regions via systematic random sampling. In the second stage, systematic sampling was used to select households from a household sampling frame in each cluster where the participants were interviewed.\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e Detailed information about the survey design is available in the literature.\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e\n\u003ch3\u003eStudy population\u003c/h3\u003e\n\u003cp\u003eThe study involved 8,811 women in Ghana who were married or living with a partner (cohabiting).\u003c/p\u003e\n\u003ch3\u003eVariables\u003c/h3\u003e\n\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eOutcome variables\u003c/h2\u003e \u003cp\u003eThe outcome variable for this study was autonomy in SRH decision-making among women. This outcome variable is defined as married or cohabiting women aged 15\u0026ndash;49 years who (1) decide on health care for themselves, either alone or jointly with their husbands or partners; (2) decide on the use of contraception, either alone or jointly with their husbands or partners; and (3) can say no to sex with their husband or partner if they do not want to.\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eExposure variables\u003c/h2\u003e \u003cp\u003eThe exposure variables were grouped into individual and contextual-level variables. The individual-level variables included the age of the woman, number of children, educational level, exposure to media, current work status, husband/partner\u0026rsquo;s age, husband/partner\u0026rsquo;s educational level, ethnicity, and religion. The contextual-level variables included place of residence, wealth index, and region. Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e presents the exposure variables and their categories.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eData analysis\u003c/h2\u003e \u003cp\u003eWe first performed a descriptive univariate analysis to describe the characteristics of the study population with weighted frequencies and percentages. We also calculated the weighted prevalence of autonomy in SRH decision-making among women in Ghana along with the 95% confidence interval (CI) according to the original sampling weight provided by the DHS. We then performed bivariate cross-tabulation to describe the distribution of decision-making autonomy across the individual and contextual-level variables. The Pearson chi-square (χ\u0026sup2;) test was used to determine the variables that had a statistically significant association with autonomy in SRH decision-making among women. Finally, we determined the individual- and contextual-level factors associated with the outcome, autonomy in SRH decision-making among women using a mixed-effect multilevel binary logistic regression model. Four models (Models I\u0026ndash;IV) were fitted. Model I was a null model (without any predictor variable) that showed the variation in decision-making autonomy resulting from clustering at the PSU. Model II included only individual-level variables, whereas Model III included only contextual-level variables. Both the individual- and contextual-level variables were included in Model IV. The fixed-effect output showing the determinants of autonomy in SRH decision-making among women was presented using adjusted odds ratios (aORs) along with their 95% CIs. A p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered to indicate statistical significance. We used Stata version 17 to perform the analysis. All analyses were weighted using svyset command to account for the complex nature of the DHS dataset due to the sampling technique used.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDemographic characteristics of the women in Ghana (n\u0026thinsp;=\u0026thinsp;8811)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWeighted frequency (n)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eWeighted percentage (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eAge of women (years)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u0026ndash;19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e208\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20\u0026ndash;24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,088\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25\u0026ndash;29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,565\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e30\u0026ndash;34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,846\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e35\u0026ndash;39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,763\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e40\u0026ndash;44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,331\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e45\u0026ndash;49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,010\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eNumber of children\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e637\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,554\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,687\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,613\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,320\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eEducational level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,164\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,324\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecondary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4,482\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e50.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigher\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e841\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eExposure to media\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,300\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7,511\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e85.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eCurrent work status\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,358\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7,453\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e84.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eCurrently residing with husband/partner\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiving with husband/partner\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6,681\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e75.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStaying elsewhere\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,130\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eHusband/Partner's age (years)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u0026ndash;19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20\u0026ndash;29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,193\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e30\u0026ndash;39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,115\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e40\u0026ndash;49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,905\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e50\u0026ndash;59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,169\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e60 and above\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e416\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003eHusband/Partner\u0026rsquo;s educational level\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,986\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e776\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecondary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4,689\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e53.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigher\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,361\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEthnicity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAkan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,593\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGa/Dangme\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e550\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEwe\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e942\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGuan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e268\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMole-Dagbani\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,964\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGrusi\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e334\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGurma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e763\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMande\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e315\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eReligion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChristian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6,311\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e71.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIslam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,065\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTraditionalist\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e235\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e200\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003ePlace of residence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4,562\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e51.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4,249\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eWealth index of household\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,410\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMiddle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,659\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRich\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,742\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRegion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWestern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e523\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCentral\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e876\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGreater Accra\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,229\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVolta\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e403\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEastern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e679\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAshanti\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,532\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWestern North\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e248\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAhafo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e196\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBono\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e305\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBono East\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e404\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e4.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOti\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e266\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNorthern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e935\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSavannah\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e234\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNorth East\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e246\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUpper East\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e457\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUpper West\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e277\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eSource: Authors\u0026rsquo; analysis 2024\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe background characteristics of the women are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Our analysis included a total of 8,811 women aged 15\u0026ndash;49 years from Ghana who were currently married or in a union. Most of the women were within 30\u0026ndash;34 years (20.9%) and had at least 4 children. More than half of the women had secondary education (50.9%), were exposed to media (85.2%), were working (84.6%), and were living with their husband/partner (75.8%). Most of the women\u0026rsquo;s husbands/partners were aged 30\u0026ndash;39 years (35.4%) and had attained secondary education (53.2%). Approximately 41% belong to the Akan ethnic group. With respect to contextual (community and household) characteristics, 51.8% and 17.4% resided in urban areas and the Ashanti region respectively, whereas 42.5% lived in rich wealth index households.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cb\u003eBivariate analysis of sociodemographic variables and autonomy in sexual and reproductive health decision-making among women in Ghana\u003c/b\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAutonomy in sexual and reproductive health decision making\u003c/p\u003e \u003cp\u003e% [95% CI]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eP value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrevalence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e51.7 [49.8,53.7]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge of women (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u0026ndash;19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e32.4 [24.7,41.2]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20\u0026ndash;24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e43.7 [40.0,47.4]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25\u0026ndash;29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e48.1 [44.6,51.6]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e30\u0026ndash;34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e55.2 [52.0,58.3]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e35\u0026ndash;39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e55.5 [52.0,59.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e40\u0026ndash;44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e51.5 [47.4,55.7]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e45\u0026ndash;49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e57.3 [53.0,61.5]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNumber of children\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.016\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e49.2 [44.0,54.4]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e52.6 [49.0,56.1]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e56.0 [52.6,59.4]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e52.4 [48.6,56.2]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e49.3 [46.6,52.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducational level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e35.7 [32.4,39.2]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e50.3 [46.6,54.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecondary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e55.6 [53.4,57.8]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigher\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e74.5 [70.0,78.5]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eExposure to media\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e33.6 [29.9,37.5]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e54.9 [52.8,56.9]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCurrent work status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e39.5 [35.5,43.7]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e54.0 [51.9,56.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCurrently residing with husband/partner\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e0.126\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLiving with husband/partner\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e51.1 [48.8,53.3]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStaying elsewhere\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e53.9 [50.7,57.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHusband/Partner's age (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u0026ndash;19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e13.2 [3.8,37.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20\u0026ndash;29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e45.2 [41.7,48.7]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e30\u0026ndash;39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e52.3 [49.6,54.8]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e40\u0026ndash;49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e55.1 [52.2,58.1]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e50\u0026ndash;59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e51.0 [47.1,54.9]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e60 and above\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e46.0 [39.8,52.4]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHusband/Partner educational level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e36.4 [33.1,39.7]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e46.4 [41.8,51.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecondary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e54.9 [52.6,57.1]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigher\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e66.4 [62.8,69.8]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEthnicity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAkan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e58.9 [55.9,61.8]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGa/Dangme\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e56.7 [47.9,65.2]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEwe\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e56.3 [51.3,61.1]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGuan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e56.3 [48.1,64.1]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMole-Dagbani\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e41.9 [37.9,45.9]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGrusi\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e46.3 [39.6,53.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGurma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e41.9 [36.6,47.3]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMande\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e34.2 [25.9,43.6]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e56.5 [40.3,71.3]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eReligion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChristian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e56.9 [54.7,59.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIslam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e37.8 [33.8,41.9]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTraditionalist\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e40.6 [32.0,49.8]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e46.8 [37.6,56.3]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePlace of residence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e59.3 [56.4,62.1]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e43.6 [41.2,46.1]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWealth index\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e40.7 [38.2,43.3]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMiddle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e51.2 [47.7,54.8]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRich\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e62.0 [59.2,64.7]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRegion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWestern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e69.0 [62.3,75.0]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCentral\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e59.4 [54.5,64.2]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGreater Accra\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e69.0 [62.5,74.8]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVolta\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e54.5 [48.5,60.3]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEastern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e42.1 [35.7,48.7]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAshanti\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e47.8 [42.2,53.4]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWestern North\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e40.5 [33.6,47.8]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAhafo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e37.4 [28.6,47.2]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBono\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e61.7 [55.2,67.9]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBono East\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e50.9 [44.0,57.7]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOti\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e50.5 [43.5,57.4]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNorthern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e40.1 [32.7,47.9]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSavannah\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e39.1 [31.9,46.8]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNorth East\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e28.5 [22.0,36.2]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUpper East\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e52.5 [48.1,56.8]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUpper West\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e40.8 [33.4,48.5]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eSource: Author analysis, 2024. P values generated from the chi-square test\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAs shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, approximately half of the women (52% [49.8, 53.7%]) had autonomy in SRH decision-making. Women aged 45\u0026ndash;49 years had the highest prevalence of SRH decision-making autonomy, whereas those aged 15\u0026ndash;19 years had the lowest prevalence. Women who had no education as well as husbands/partners with no education had the lowest (35.7% [32.4, 39.2]) and (36.4% [33.1, 39.7]) autonomy in SRH decision-making respectively. SRH decision-making autonomy was high among women who were exposed to media (54.9% [52.8, 56.9%], were workers (54.0% [51.9, 56.0%], belonged to the Akan ethnic group (58.9% [55.9, 61.8]), and were Christians (56.9% [54.7, 59.0]). Conversely, the lowest prevalence of autonomy in SRH decision-making was reported among those who resided in rural areas (43.6% [41.2,46.1]), households with poor wealth indices (40.7% [38.2,43.3]) and those who also resided in North East region (28.5% [22.0,36.2]). All the exposure variables except for currently residing with a husband/partner were significantly associated with autonomy in SRH decision making (p\u0026thinsp;\u0026lt;\u0026thinsp;0.005).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDeterminants of autonomy in sexual and reproductive health decision-making among women in Ghana\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eModel I empty model\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eModel II aOR [95% CI]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eModel III aOR [95% CI]\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eModel IV aOR [95% CI]\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003eFixed effect results\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge of women (years)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u0026ndash;19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20\u0026ndash;24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e1.39 [0.82,2.35]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.39 [0.82,2.35]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25\u0026ndash;29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e1.59 [0.94,2.69]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.59 [0.94,2.69]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e30\u0026ndash;34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e1.96\u003csup\u003e*\u003c/sup\u003e [1.16,3.31]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.96\u003csup\u003e*\u003c/sup\u003e [1.16,3.31]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e35\u0026ndash;39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e2.06\u003csup\u003e**\u003c/sup\u003e [1.20,3.56]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.06\u003csup\u003e**\u003c/sup\u003e [1.19,3.55]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e40\u0026ndash;44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e1.92\u003csup\u003e*\u003c/sup\u003e [1.08,3.42]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.93\u003csup\u003e*\u003c/sup\u003e [1.09,3.43]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e45\u0026ndash;49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e2.76\u003csup\u003e***\u003c/sup\u003e [1.57,4.86]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.76\u003csup\u003e***\u003c/sup\u003e [1.57,4.86]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNumber of children\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNone\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e1.02 [0.76,1.37]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.02 [0.76,1.37]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e1.05 [0.75,1.46]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.04 [0.75,1.46]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e0.85 [0.60,1.19]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.84 [0.60,1.19]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e4+\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e0.93 [0.66,1.30]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.92 [0.66,1.30]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducational level\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e1.47\u003csup\u003e**\u003c/sup\u003e [1.16,1.86]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.47\u003csup\u003e**\u003c/sup\u003e [1.16,1.86]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecondary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e1.64\u003csup\u003e***\u003c/sup\u003e [1.34,2.02]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.65\u003csup\u003e***\u003c/sup\u003e [1.34,2.02]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigher\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e3.31\u003csup\u003e***\u003c/sup\u003e [2.31,4.76]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.33\u003csup\u003e***\u003c/sup\u003e [2.31,4.80]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eExposure to media\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e1.38\u003csup\u003e**\u003c/sup\u003e [1.12,1.71]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.38\u003csup\u003e**\u003c/sup\u003e [1.11,1.70]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCurrent work status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e1.65\u003csup\u003e***\u003c/sup\u003e [1.32,2.07]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.67\u003csup\u003e***\u003c/sup\u003e [1.33,2.09]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHusband/Partner's age (years)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15\u0026ndash;19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e20\u0026ndash;29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e3.22 [0.86,12.04]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.21 [0.86,12.00]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e30\u0026ndash;39\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e3.22 [0.85,12.23]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.22 [0.85,12.21]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e40\u0026ndash;49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e3.55 [0.92,13.66]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.55 [0.92,13.63]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e50\u0026ndash;59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e3.12 [0.81,11.96]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.11 [0.81,11.93]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e60 and above\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e3.08 [0.78,12.17]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.08 [0.78,12.15]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHusband/Partner\u003c/b\u003e\u0026rsquo;s \u003cb\u003eeducational level\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo education\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e1.17 [0.90,1.51]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.17 [0.90,1.52]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecondary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e1.26\u003csup\u003e*\u003c/sup\u003e [1.04,1.52]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.26\u003csup\u003e*\u003c/sup\u003e [1.04,1.52]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigher\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e1.40\u003csup\u003e*\u003c/sup\u003e [1.05,1.87]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.41\u003csup\u003e*\u003c/sup\u003e [1.05,1.88]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEthnicity\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAkan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGa/Dangme\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e0.91 [0.52,1.59]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.89 [0.50,1.57]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEwe\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e0.92 [0.68,1.25]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.91 [0.66,1.26]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGuan\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e1.18 [0.79,1.75]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.17 [0.78,1.75]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMole-Dagbani\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e0.70\u003csup\u003e*\u003c/sup\u003e [0.53,0.93]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.69\u003csup\u003e*\u003c/sup\u003e [0.52,0.92]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGrusi\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e0.90 [0.58,1.39]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.88 [0.57,1.37]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGurma\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e0.63\u003csup\u003e*\u003c/sup\u003e [0.44,0.90]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.63\u003csup\u003e*\u003c/sup\u003e [0.43,0.90]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMande\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e0.51\u003csup\u003e*\u003c/sup\u003e [0.30,0.88]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.51\u003csup\u003e*\u003c/sup\u003e [0.29,0.87]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e0.89 [0.41,1.95]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.89 [0.41,1.95]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eReligion\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChristian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIslam\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e0.73\u003csup\u003e**\u003c/sup\u003e [0.57,0.92]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.72\u003csup\u003e**\u003c/sup\u003e [0.57,0.91]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTraditionalist\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e0.90 [0.56,1.42]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.90 [0.57,1.43]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e \u003cp\u003e0.86 [0.58,1.28]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.86 [0.58,1.28]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePlace of residence\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.72\u003csup\u003e**\u003c/sup\u003e [0.58,0.89]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.74\u003csup\u003e**\u003c/sup\u003e [0.59,0.91]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eWealth index\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePoor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMiddle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.25\u003csup\u003e*\u003c/sup\u003e [1.02,1.53]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.04 [0.84,1.29]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRich\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.56\u003csup\u003e***\u003c/sup\u003e [1.25,1.95]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.97 [0.77,1.22]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRegion\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWestern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCentral\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.54\u003csup\u003e**\u003c/sup\u003e [0.34,0.86]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.50\u003csup\u003e**\u003c/sup\u003e [0.32,0.79]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGreater Accra\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.78 [0.45,1.36]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.81 [0.45,1.45]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVolta\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.41\u003csup\u003e***\u003c/sup\u003e [0.25,0.68]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.37\u003csup\u003e***\u003c/sup\u003e [0.22,0.64]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEastern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.25\u003csup\u003e***\u003c/sup\u003e [0.15,0.41]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.22\u003csup\u003e***\u003c/sup\u003e [0.13,0.38]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAshanti\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.34\u003csup\u003e***\u003c/sup\u003e [0.22,0.54]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.33\u003csup\u003e***\u003c/sup\u003e [0.21,0.52]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWestern North\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.26\u003csup\u003e***\u003c/sup\u003e [0.16,0.42]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.24\u003csup\u003e***\u003c/sup\u003e [0.15,0.40]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAhafo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.21\u003csup\u003e***\u003c/sup\u003e [0.12,0.37]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.22\u003csup\u003e***\u003c/sup\u003e [0.13,0.40]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBono\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.61 [0.37,1.00]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.61 [0.37,1.02]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBono East\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.48\u003csup\u003e**\u003c/sup\u003e [0.29,0.79]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.65 [0.40,1.07]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOti\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.44\u003csup\u003e**\u003c/sup\u003e [0.27,0.73]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.54\u003csup\u003e*\u003c/sup\u003e [0.32,0.91]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNorthern\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.24\u003csup\u003e***\u003c/sup\u003e [0.13,0.43]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.54\u003csup\u003e*\u003c/sup\u003e [0.30,1.00]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSavannah\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.31\u003csup\u003e***\u003c/sup\u003e [0.18,0.54]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.54\u003csup\u003e*\u003c/sup\u003e [0.30,0.96]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNorth East\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.19\u003csup\u003e***\u003c/sup\u003e [0.11,0.33]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.40\u003csup\u003e**\u003c/sup\u003e [0.23,0.71]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUpper East\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.57\u003csup\u003e*\u003c/sup\u003e [0.36,0.90]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.78 [0.47,1.28]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUpper West\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.31\u003csup\u003e***\u003c/sup\u003e [0.18,0.55]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.53\u003csup\u003e*\u003c/sup\u003e [0.29,0.95]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"7\" nameend=\"c7\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRandom effect model\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003ePSU variance (95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e1.38 [1.16,1.65]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.17 [0.97,1.41]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.96 [0.80,1.16]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.93 [0.77,1.12]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eICC\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e0.29 [0.26,0.33]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.26 [0.23,0.30]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.22 [0.20,0.26]\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.22 [0.19,0.25]\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eSample size\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e8811\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8811\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8811\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e8811\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eNumber of clusters\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e618\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e618\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e618\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e618\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eSource: Author analysis, 2024\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eModel II adjusted for individual level factors\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"7\"\u003eModel III adjusted for community level factors\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eModel IV adjusted for both individual and community level determinants\u003c/p\u003e \u003cp\u003eaOR\u0026thinsp;=\u0026thinsp;adjusted odds ratio; CI\u0026thinsp;=\u0026thinsp;confidence interval; PSU\u0026thinsp;=\u0026thinsp;primary sampling unit; ICC\u0026thinsp;=\u0026thinsp;intraclass correlation coefficient\u003c/p\u003e \u003cp\u003e \u003csup\u003e*\u003c/sup\u003e p\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/p\u003e \u003cp\u003e \u003csup\u003e**\u003c/sup\u003e p\u0026thinsp;\u0026lt;\u0026thinsp;0.01\u003c/p\u003e \u003cp\u003e \u003csup\u003e***\u003c/sup\u003e p\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003cp\u003eRef\u0026thinsp;=\u0026thinsp;Reference Category\u003c/p\u003e \u003cp\u003eThe odds of autonomy in SRH decision-making were greater among women aged 30\u0026ndash;34 years [aOR\u0026thinsp;=\u0026thinsp;1.96; CI\u0026thinsp;=\u0026thinsp;1.16, 3.31], 35\u0026ndash;39 years [aOR\u0026thinsp;=\u0026thinsp;2.06; CI\u0026thinsp;=\u0026thinsp;1.19, 3.55], 40\u0026ndash;44 years [aOR\u0026thinsp;=\u0026thinsp;1.93; CI\u0026thinsp;=\u0026thinsp;1.09, 3.43], and 45\u0026ndash;49 years [aOR\u0026thinsp;=\u0026thinsp;2.76; CI\u0026thinsp;=\u0026thinsp;1.57, 4.86] than among teenage women (15\u0026ndash;19 years). Women who attained primary [aOR\u0026thinsp;=\u0026thinsp;1.47; CI\u0026thinsp;=\u0026thinsp;1.16, 1.86], secondary [aOR\u0026thinsp;=\u0026thinsp;1.65; CI\u0026thinsp;=\u0026thinsp;1.34, 2.02], or higher [aOR\u0026thinsp;=\u0026thinsp;3.33; CI\u0026thinsp;=\u0026thinsp;2.31, 4.80] educational levels had a higher odds of autonomy in SRH decision making compared to women who had no education. Women who had media exposure were 38% [aOR\u0026thinsp;=\u0026thinsp;1.38; CI\u0026thinsp;=\u0026thinsp;1.11, 1.70] more likely to have decision-making autonomy compared to those who were not exposed to media. Working women were 1.67 times [aOR\u0026thinsp;=\u0026thinsp;1.67; 1.33, 2.09] more likely to have autonomy in SRH decision making than non-working women. The odds of decision-making autonomy were higher among women whose husbands/partners had secondary [aOR\u0026thinsp;=\u0026thinsp;1.26; CI\u0026thinsp;=\u0026thinsp;1.04, 1.52] and higher [aOR\u0026thinsp;=\u0026thinsp;1.41; CI\u0026thinsp;=\u0026thinsp;1.05, 1.88] educational levels compared to those whose husbands/partners were not educated. Compared with the Akan ethnic group, belonging to the Mole-Dagbani [aOR\u0026thinsp;=\u0026thinsp;0.69; CI\u0026thinsp;=\u0026thinsp;0.52, 0.92], Gurma [aOR\u0026thinsp;=\u0026thinsp;0.63; CI\u0026thinsp;=\u0026thinsp;0.43, 0.90], and Mande [aOR\u0026thinsp;=\u0026thinsp;0.51; CI\u0026thinsp;=\u0026thinsp;0.29, 0.87] ethnic groups was associated with lower odds of SRH decision-making autonomy. Compared with Christians, Islamic women were 28% [aOR\u0026thinsp;=\u0026thinsp;0.72; CI\u0026thinsp;=\u0026thinsp;0.57, 0.91] less likely to have autonomy in SRH decision making. The odds of autonomy in SRH decision-making were 26% lower among women who resided in rural areas [aOR\u0026thinsp;=\u0026thinsp;0.74; CI\u0026thinsp;=\u0026thinsp;0.59, 0.91] compared with urban resident women. Compared with women from the Western region, women who resided in Central, Volta, Eastern, Ashanti, Western North, Ahafo, Oti, Northern, Savannah, Northeast, and Upper West regions had lower odds of having SRH decision-making autonomy (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The random effects model is also presented in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study examined the determinants of autonomy in SRH decision-making among women in Ghana. First, we observed that approximately half of Ghanaian women lacked autonomy in SRH decision-making. Second, the individual-level determinants associated with autonomy in decision-making were being older, having a high educational level, being exposed to media, currently working, having a husband/partner with at least secondary educational, ethnicity (Mole-Dagbani, Gruma, Mande), and religion. Finally, the contextual factors associated with autonomy in SRH decision-making included place of residence, higher household wealth index, and region of residence.\u003c/p\u003e \u003cp\u003eThe finding that approximately half of Ghanaian women lack autonomy in decision making corroborates the findings of previous studies in some LMICs.\u003csup\u003e\u003cspan additionalcitationids=\"CR25\" citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e Conversely, much lower levels of SRH decision-making autonomy have been reported in other studies.\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e In Ghana, several nongovernmental organizations (NGOs) are championing women\u0026rsquo;s empowerment initiatives and interventions. For example, Norsaac and WomensTrust, are one of the leading NGOs promoting SRH rights among women in Ghana. This has notably led to an increased level of decision-making autonomy compared with that of some LMICs.\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e Despite these efforts, approximately half of these women still lack autonomy in SRH decision-making. This calls for urgent and effective population-focused interventions to empower women on SRH decision-making.\u003c/p\u003e \u003cp\u003eEmpowering women in SRH decision making is pivotal in enhancing women\u0026rsquo;s and child health outcomes and bridging the gender inequality gap. However, significant disparities and inequalities continue to limit this autonomy. We observed that older (30\u0026ndash;49 years) women were more likely to have decision-making autonomy than teenage women were, which is in line with previous research findings in LMICs.\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e For instance, studies in Ethiopia and Nepal reported that women aged 30\u0026ndash;49 years were approximately 2 times more likely to have autonomy in decision making compared with teenage women.\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e The higher odds of decision-making autonomy observed among older women may be attributed to the respect and recognition accorded to them in society. In addition, their lived experiences and societal role as mothers empowered them to make independent decisions on their health needs. In contrast, younger women may still be under the control of their in-laws and husbands/partners in terms of making decisions. Hence, they have little to no autonomy in making sexual and healthcare decisions.\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eMoreover, we found that higher education is associated with increased autonomy in sexual reproductive decision-making among women. In particular, women who attained at least primary and secondary education were 40\u0026ndash;60% more likely to have decision-making autonomy compared with uneducated women, whereas higher education increased decision-making autonomy by 3 times. Similarly, previous studies have shown that higher education is positively correlated with autonomy in SRH decision-making.\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e Higher education enlightens women on their SRHR and enhances their self-confidence and ability to make informed decisions. In addition, higher education has been reported to be associated with high health literacy levels.\u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e,\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e Notably, women whose husbands/partners had attained at least secondary education were more likely to have decision-making autonomy compared with the reference group, which is consistent with the findings of previous studies.\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e This observation implies that well-educated men may be more inclined toward gender equality and depart from the societal norm of male dominance in household decision making\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e, hence empowering their wives/partners to make decisions by themselves or jointly with their husbands/partners.\u003c/p\u003e \u003cp\u003eConsistent with previous studies\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e we found that women exposed to media were 38% more likely to have decision-making autonomy compared with those without media exposure. For example, studies in Ethiopia and Nigeria reported that decision-making autonomy increased by more than twofold among media-exposed women compared with those not exposed to media.\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e,\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e This implies that women\u0026rsquo;s exposure to television, radio, newspapers and other media sources enhances their access to information and informed decision-making behaviors. Consequently, they are empowered to exercise SRH decision-making autonomy. Hence, the media should be properly utilized to educate the public on SRHR.\u003c/p\u003e \u003cp\u003eWith respect to religion, this study revealed that Muslim women were 28% less likely to have decision-making autonomy compared with Christian women. Previous studies reported comparable findings where lower odds of decision-making autonomy were observed among Muslim women.\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e In contrast, findings reported by Adweeti Nepal et al.\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e did not find religion to be a significant determinant of decision-making autonomy in the context of Nepal. This was attributed to a high proportion (86%) of women belonging to the Hindu religion, whereas other religions constituted a minimal percentage.\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e In northern Ghana, where Islam is the dominant religion, traditional and cultural gender norms are highly prevalent in Islamic homes. where men are mostly regarded as the sole decision makers with absolute marital control over women. Consequently, women are denied any form of decision-making autonomy.\u003c/p\u003e \u003cp\u003eAccordingly, our results indicate that women who reside in rural areas are 26% less likely to have decision-making autonomy compared with urban residents. Our findings resonate with those of previous studies conducted in LMICs.\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e,\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e This may be because women residing in rural areas have limited educational opportunities, media exposure, and access to health facilities.\u003c/p\u003e \u003cp\u003eThis study further revealed ethnic and regional disparities in the autonomy of SRH decision-making among women. For example, women belonging to the Mole-Dagbani, Gurma, and Mande ethnic groups were less likely to have decision-making autonomy compared with Akan women.\u003c/p\u003e \u003cp\u003eIn response to these disparities and the low level of autonomy in SRH decision making among women in Ghana, targeted interventions for disadvantaged population groups should be adopted rather than wholesale interventions for general population groups. In particular, these tailored interventions should focus on rural populations, adolescent women, Muslim populations, and people with limited education to help bridge the decision-making autonomy gaps and disparities identified in this study.\u003c/p\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eLimitations\u003c/h2\u003e \u003cp\u003eThis study had some limitations. The sensitive nature of this research topic, coupled with self-reports of women\u0026rsquo;s SRH decision-making autonomy might lead to misestimation of the level of women\u0026rsquo;s decision-making autonomy. The Ghana DHS 2022 data used in this study included only three SRH dimensions and indicators. However, the SRH autonomy includes more than three dimensions. Moreover, a cross-sectional study design was used in this study, hence limiting the ability of the study to draw causal inferences. Nonetheless, this study used nationally representative data based on indicators by the SDGs of the SRHR, which makes it an ideal reference study for designing policies and interventions for the SRH decision-making autonomy in the context of Ghana.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003ePolicy implications\u003c/h2\u003e \u003cp\u003eThis study reveals substantial geographic, socio-demographic, and cultural disparities in women\u0026rsquo;s autonomy over SRH decisions in Ghana. While approximately 51.7% of women reported SRH decision-making autonomy, this figure conceals important inequalities that demand tailored, regionally responsive policies and programs to achieve national and global commitments under SDG 3 (health) and SDG 5 (gender equality). The need for multisectoral and intersectional approaches and collaborations are of the essence in this regard.\u003c/p\u003e \u003cp\u003eFirst and foremost, investments in female education should be central in improving SRH decision-making autonomy. The strong positive association between education and SRH autonomy suggests that increasing access to quality education especially beyond the primary level can empower women to make informed health decisions. Education should also be extended males to foster equitable gender norms and promote supportive partnerships in SRH matters. Also, economic empowerment initiatives should be prioritized, particularly in rural areas, where women face multiple layers of disadvantage. Programs that promote women\u0026rsquo;s employment and financial independence can increase their decision-making power, as evidenced by the higher autonomy among working women in this study.\u003c/p\u003e \u003cp\u003eFurther, mass media and information dissemination should be leveraged more systematically in public health programming. Media exposure was significantly associated with increased autonomy, indicating its potential to raise awareness about SRHR, address cultural norms regarding SRH decision-making autonomy, and promote gender-equitable behaviors. This can transcend across the different regions in the country. In addition, religious and cultural engagement is essential. Lower autonomy among Muslim women and women from certain ethnic groups (for instance Mole-Dagbani, Gurma, Mande) points to the need for culturally tailored interventions. Partnering with community and religious leaders can facilitate normative change in ways that are respectful, context-sensitive, and sustainable. Moreso, national policies should be revised to explicitly incorporate SRH decision-making autonomy as a measurable and actionable indicator of women\u0026rsquo;s empowerment. This includes strengthening monitoring and evaluation frameworks within the Ghana Health Service and Ministry of Gender, Children, and Social Protection to track progress and inform data-driven interventions.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe findings of this study indicate that approximately 1 in 2 women lack autonomy in SRH decision making in Ghana. The significant determinants of decision-making autonomy were age, educational level, religion, media exposure, and ethnicity. We further observed rural\u0026ndash;urban and regional disparities in autonomy in decision-making. To address these gaps and disparities, SRHR interventions should be tailored to disadvantaged population groups and based on a sound understanding of the cultural and social norms of these populations. We recommend research assessing how the intersectionality of low educational attainment, rural residence and current work status influence the decision-making autonomy of women in Ghana.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eaOR \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Adjusted odds ratio\u003c/p\u003e\n\u003cp\u003eCI \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Confidence interval\u003c/p\u003e\n\u003cp\u003eDHS \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Demographic health survey\u003c/p\u003e\n\u003cp\u003eICPD \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Internation conference for population and development\u003c/p\u003e\n\u003cp\u003eLMICs \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Low- and middle-income countries\u003c/p\u003e\n\u003cp\u003eNGOs \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Nongovernmental organizations\u003c/p\u003e\n\u003cp\u003ePSU \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Primary sampling unit\u003c/p\u003e\n\u003cp\u003eSDG \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Sustainable development goal\u003c/p\u003e\n\u003cp\u003eSRH \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Sexual and reproductive health\u003c/p\u003e\n\u003cp\u003eSRHR \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Sexual and reproductive health right\u003c/p\u003e\n\u003cp\u003eSTIs \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Sexual transmitted infections\u003c/p\u003e\n\u003cp\u003eUN \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;United Nations\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical clearance was not sought for the study since the secondary dataset is freely available in the public domain. A detailed description of the ethical issues regarding the DHS and its dataset usage can be assessed at http://goo.gl/ny8T6X.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNote applicable\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data used for this study is freely available at https://dhsprogram.com/data/dataset/Ghana_Standard-DHS_2022.cfm?flag=1\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interest\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study received no funding\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eJ.L.N. conceptualized and designed the study and led in data analysis and interpretation. J.L.N. and I.T. wrote the initial manuscript. F.Z., A.D.D., and I.T. contributed to the data analysis, interpretation of the results, and manuscript writing. All authors contributed to the critical revision of the manuscript. All authors approved the final submission of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgement\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eGebeyehu NA, Gelaw KA, Lake EA, Adela GA, Tegegne KD, Shewangashaw NE. Women decision-making autonomy on maternal health service and associated factors in low- and middle-income countries: Systematic review and meta-analysis. Volume 18. Women\u0026rsquo;s Health; 2022.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUnited Nations Population Fund. SDG indicator metadata [Internet]. 2024 [cited 2025 Feb 22]. 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BMC Womens Health. 2022;22(1).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAsabu MD, Altaseb DK. The trends of women\u0026rsquo;s autonomy in health care decision making and associated factors in Ethiopia: evidence from 2005, 2011 and 2016 DHS data. BMC Womens Health. 2021;21(1).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJiregna B, Amare M, Dinku M, Nigatu D, Desalegn D. Women Health Literacy and Associated Factors on Women and Child Health Care in Ilu Ababor Public Health Facilities, Ethiopia. Int J Womens Health. 2024;16:143\u0026ndash;52.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMeldgaard M, Gamborg M, Terkildsen Maindal H. Health literacy levels among women in the prenatal period: A systematic review. Sexual and Reproductive Healthcare. Volume 34. Elsevier B.V.; 2022.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAlemayehu M, Meskele M. 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Int J Womens Health. 2017;9:213\u0026ndash;21.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"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":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Autonomy, sexual and reproductive health, decision-making, demographic and health survey, Ghana","lastPublishedDoi":"10.21203/rs.3.rs-6375599/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6375599/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003eWomen’s autonomy in sexual and reproductive health (SRH) decision making is essential for achieving sustainable development goals (SDGs) 3 (ensuring healthy lives and promoting well-being) and 5 (achieving gender equality and empowering all women and girls). However, SRH decision-making autonomy remains limited with disparities in low- and middle-income countries (LMICs), including Ghana. Hence, this study examined the determinants of women’s autonomy in SRH decision making in Ghana.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethodology:\u003c/strong\u003eWe analyzed data from the 2022 Ghana Demographic and Health Survey (DHS), a nationally representative cross-sectional dataset. The sample included 8,811 married or cohabiting women aged 15-49 years. A mixed-effect multilevel binary logistic regression model was used to identify the determinants of SRH decision-making autonomy, with results presented as adjusted odds ratios (aORs) with 95% confidence intervals (CIs).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eWe found that\u003cstrong\u003e \u003c/strong\u003e51.7% [CI=49.8,53.7] of Ghanaian women had autonomy in SRH decision-making. SRH decision-making autonomy was significantly high among women aged 35--39 years [aOR=2.06; CI=1.19,3.55], 45-49 years [aOR=2.76; CI=1.57,4.86], those with secondary education [aOR=1.65; CI=1.34,2.02], those with higher education [aOR=3.33; CI=2.31,4.80], those with media exposure [aOR=1.38; CI=1.11,1.70], those currently working [aOR=1.67; CI=1.33,2.09], and having a partner with secondary [aOR = 1.26; CI: 1.04,1.52] or higher education [aOR = 1.41; CI: 1.05,1.88], compared to their respective reference categories. Conversely, lower SRH decision-making autonomy was observed among Muslim women [aOR=0.72; CI=0.57,0.91] and rural residents [aOR=0.74; CI=0.59,0.91] compared to Christian women and urban resident women, respectively. Additionally, significant regional and ethnic disparities were evident, indicating important structural and sociocultural influences on women’s autonomy in SRH decisions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003eNearly half of Ghanaian women lacked autonomy in SRH decision-making, significantly influenced by age, education, exposure to media, current work status, religion, ethnicity, and geographic region. Addressing these disparities requires targeted multilevel interventions that consider the unique cultural and socio-economic barriers faced by disadvantaged groups.\u003c/p\u003e","manuscriptTitle":"Determinants of autonomy in sexual and reproductive health decision making among women: A mixed-effects multilevel analysis of the demographic and health survey in Ghana","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-05-05 20:52:51","doi":"10.21203/rs.3.rs-6375599/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-12-15T07:13:26+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-11-24T15:51:04+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"327433993537553950199087383264816648731","date":"2025-11-03T20:55:01+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"110174828158172093697330471252395352994","date":"2025-09-19T15:22:01+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"74946861493702982839071641660853855786","date":"2025-07-11T01:31:50+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"218374429874503524302769897693639182354","date":"2025-06-08T06:44:56+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-31T07:30:12+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"172242362087526595928318256031918147500","date":"2025-05-16T13:03:06+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"291800711663716599148368523495247040707","date":"2025-04-29T19:50:10+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-04-29T01:40:37+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-04-09T09:25:31+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-04-08T23:37:14+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-04-08T23:35:40+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Public Health","date":"2025-04-04T10:54:05+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"c2be04f6-b86d-40a1-bcb3-29334680865d","owner":[],"postedDate":"May 5th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-03-31T09:10:27+00:00","versionOfRecord":[],"versionCreatedAt":"2025-05-05 20:52:51","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6375599","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6375599","identity":"rs-6375599","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}