Contraceptive Decision-Making Autonomy Among Married Women in Nigeria: Regional Disparities and Determinants Using the 2024 NDHS

Contraceptive Decision-Making Autonomy Among Married Women in Nigeria: Regional Disparities and Determinants Using the 2024 NDHS | 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 Contraceptive Decision-Making Autonomy Among Married Women in Nigeria: Regional Disparities and Determinants Using the 2024 NDHS Jamilu Sani, Abdullahi Abubakar Ambursa, Abubakar Yakubu Abbani, and 9 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8149264/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 15 You are reading this latest preprint version Abstract Background Women’s autonomy in contraceptive decision-making is a key component of reproductive rights and gender equality, yet remains low in many low- and middle-income countries, including Nigeria. Understanding the current patterns and determinants of contraceptive autonomy is essential for accelerating progress toward Sustainable Development Goal (SDG) 5. This study examined the prevalence, regional disparities, and sociodemographic predictors of contraceptive decision-making autonomy among married women in Nigeria using the 2024 Nigeria Demographic and Health Survey (NDHS). Methods This cross-sectional study analyzed data from 24,819 married women aged 15–49 years from the 2024 NDHS. Contraceptive autonomy was defined as women independently making decisions regarding contraceptive use. Descriptive statistics summarized respondents’ characteristics, and logistic regression models assessed crude and adjusted associations between predictors and autonomy. All analyses applied sampling weights to account for the NDHS complex survey design. Statistical significance was set at p < 0.05. Results Overall, 37% of married women reported autonomy in contraceptive decision-making. Autonomy was highest in the South West (51%) and lowest in the North West (31%). In the adjusted model, older age increased autonomy, including women aged 35–39 years (AOR = 1.25; 95% CI: 1.03–1.52; p = 0.025) and 40–44 years (AOR = 1.31; 95% CI: 1.07–1.60; p = 0.009). Higher household wealth was associated with autonomy—poorer (AOR = 1.26; p < 0.001) and richer households (AOR = 1.26; p < 0.001) compared with the poorest. Employed women had higher odds of autonomy (AOR = 1.49; 95% CI: 1.38–1.60; p < 0.001). Regional disparities persisted: autonomy was higher among women in the North East (AOR = 1.25; p < 0.001), South East (AOR = 1.41; p < 0.001), and South West (AOR = 1.70; p < 0.001), but lower in the North West (AOR = 0.88; p = 0.015) relative to North Central. Conclusion Contraceptive decision-making autonomy among married women in Nigeria remains low and varies substantially across demographic, socioeconomic, and regional contexts. Interventions aimed at enhancing women’s reproductive agency should prioritize education, economic empowerment, and culturally responsive strategies tailored to regions with persistent gender inequalities, particularly in the northern zones. Strengthening women’s autonomy is essential for improving reproductive health outcomes and advancing SDG 5 targets. Contraceptive autonomy Women Decision-making power Women’s empowerment Reproductive health Family planning Gender inequality Nigeria NDHS SDG 5 Figures Figure 1 Figure 2 Figure 3 BACKGROUND Women’s autonomy in reproductive decision-making is a central component of sexual and reproductive health rights and a critical indicator of gender equality ( 1 , 2 ). Contraceptive decision-making autonomy refers to a woman’s ability to independently choose whether and when to use contraception, free from coercion, pressure, or unequal power dynamics within relationships ( 3 , 4 ). This autonomy is essential for achieving desired fertility, preventing unintended pregnancies, and improving maternal and child health outcomes ( 5 ). Globally, enhancing women’s reproductive agency aligns with the Sustainable Development Goals (SDGs), particularly SDG 5, which emphasizes the elimination of gender inequalities and the promotion of women’s decision-making power in matters affecting their health and well-being ( 6 , 7 ). Despite global progress in expanding access to modern contraceptives, many women especially in low and middle-income countries still lack the power to make independent decisions regarding their reproductive choices ( 8 , 9 ). Evidence from sub-Saharan Africa shows that contraceptive decision-making is frequently influenced by patriarchal norms, relational power imbalances, and socio-cultural expectations that prioritize male authority in fertility-related matters ( 10 – 13 ). These constraints often limit women’s agency even when contraceptive services are available, underscoring the need to consider autonomy as distinct from mere access. In Nigeria, women’s empowerment and contraceptive autonomy remain major public health concerns. The country continues to record low contraceptive prevalence and high fertility rates relative to regional averages ( 11 , 14 , 15 ). Socio-cultural norms, gender power relations, and religious influences strongly shape reproductive behavior, often restricting women’s independence in making decisions about contraception ( 16 , 17 ). The northern regions, in particular, are characterized by early marriage, limited female education, and deeply entrenched gender norms, which contribute to lower levels of reproductive autonomy compared with the southern regions ( 16 ). These inequalities have been consistently highlighted in previous demographic analyses and underscore the heterogeneity of women’s reproductive experiences in Nigeria. Moreover, socioeconomic factors such as education, wealth, employment, and exposure to health information have been shown to influence women’s ability to participate in reproductive decision-making ( 18 – 21 ). Women with economic independence or higher educational attainment are often better positioned to negotiate contraceptive use and challenge restrictive gender norms. However, existing evidence remains mixed on how these factors interact with regional, cultural, and religious contexts in shaping women’s autonomy in Nigeria. While previous studies have examined determinants of maternal health services, contraceptive uptake, and women’s empowerment, limited recent research has focused specifically on contraceptive decision-making autonomy using the most updated nationally representative data. Understanding the current patterns and drivers of autonomy is critical for informing policy, strengthening gender-sensitive family planning programs, and accelerating national progress toward SDG 5. This study therefore assessed the prevalence, regional disparities, and sociodemographic determinants of contraceptive decision-making autonomy among married women in Nigeria using the 2024 Nigeria Demographic and Health Survey (NDHS). Findings from this analysis provide contemporary evidence on women’s reproductive agency and highlight priority areas for targeted interventions. METHODS Study Design and Data Source This study employed a cross-sectional analytical design using data from the 2024 Nigeria Demographic and Health Survey (NDHS). The NDHS is a nationally representative survey conducted periodically to collect comprehensive information on population, reproductive health, and sociodemographic indicators among women aged 15–49 years. The survey uses a stratified two-stage cluster sampling technique to ensure adequate representation across the six geopolitical zones and urban–rural strata ( 22 ). Data collection is implemented by the National Population Commission (NPC) in collaboration with ICF International using standardized DHS protocols to ensure comparability across countries and survey years. For this study, we extracted data from the Individual Recode (IR) file, which contains detailed information on women’s reproductive health behaviors, sociodemographic characteristics, and decision-making dynamics relevant to contraceptive autonomy. Study Population and Sample Selection The target population included married or in-union women aged 15–49 years who participated in the 2024 NDHS. From the IR dataset, we identified women who responded to the question on decision-making regarding contraceptive use. After excluding respondents with missing information on the outcome variable or key covariates, a total of 24,819 women formed the final analytical sample. Ethical Considerations Ethical approval for the 2024 NDHS was granted by the National Health Research Ethics Committee of Nigeria and the ICF Institutional Review Board. Informed consent was obtained from all participants prior to participation. This study involved secondary analysis of anonymized publicly available data and therefore required no additional ethical clearance. Study Variables Outcome Variable The primary outcome was contraceptive decision-making autonomy, derived from the DHS question on who usually makes decisions regarding contraceptive use. The original responses included: respondent, husband/partner, joint decision, someone else, and other. For analytical purposes, we created a binary outcome variable indicating women's autonomy. Women who reported making the decision themselves were coded as 1 (autonomous), while all other categories were coded as 0 (not autonomous). Explanatory Variables The independent variables were selected based on theoretical relevance and previous empirical evidence on women’s empowerment and reproductive decision-making. These variables included: Age group (5-year categories) Education level (no education, primary, secondary, higher) Religion (Christianity, Islam, others) Wealth index (poorest to richest) Employment status (working vs. not working) Number of living children (0, 1–2, 3–4, ≥ 5) Place of residence (urban/rural) Region (North Central, North East, North West, South East, South South, South West) These variables were treated as categorical and entered into both the bivariate and multivariable models. Statistical Analysis Descriptive statistics were used to summarize the sociodemographic characteristics of the study population, with results presented as frequencies and weighted percentages to account for the survey design. The overall and regional prevalence of contraceptive decision-making autonomy was examined and illustrated using bar charts and a geospatial map produced with Python’s GeoPandas library and Natural Earth administrative boundary data for Nigeria. All statistical analyses were performed using Stata version 17 (StataCorp LLC, College Station, TX, USA). Bivariate associations between each independent variable and contraceptive autonomy were assessed using logistic regression models, from which crude odds ratios (CORs) and corresponding 95% confidence intervals (CIs) were derived. Variables that demonstrated a statistically significant association at p < 0.05 in the bivariate analysis were subsequently included in the multivariable logistic regression model to identify independent predictors of autonomy. Adjusted odds ratios (AORs) with 95% CIs were reported for the multivariable model. All analyses incorporated sampling weights, clustering, and stratification to adjust for the complex survey design of the NDHS. Statistical significance was set at p < 0.05. RESULTS Sociodemographic Characteristics of Married Women Table 1 presents the sociodemographic characteristics of the study population. A total of 24,819 married women aged 15–49 years were included in the analysis. The largest proportion of respondents were aged 25–29 years (20%), followed by those aged 30–34 years (19%). Nearly half of the women (46%) had no formal education, 30% had secondary education, while only 12% attained higher education. Most respondents identified as Muslim (66%), while 33% were Christians. Regarding household wealth, 22% of women were from the poorest quintile, and 19% belonged to the richest quintile. Approximately 62% of the women were employed, and 32% had three to four living children. The majority resided in rural areas (59%), and the North West accounted for the highest regional representation (37%). Table 1 Sociodemographic Characteristics Variable Category Frequency Percent (%) Age Group (5-year) 15–19 1,371 6% 20–24 3,789 15% 25–29 4,952 20% 30–34 4,691 19% 35–39 4,162 17% 40–44 3,409 14% 45–49 2,446 10% Education Level No Education 11,352 46% Primary 2,941 12% Secondary 7,473 30% Higher 3,053 12% Religion Christianity 8,255 33.3% Islam 16,459 66.3% Others 105 0.4% Wealth Index Poorest 5,370 22% Poorer 5,332 21% Middle 4,832 19% Richer 4,487 18% Richest 4,798 19% Work Status Not Working 9,472 38% Working 15,347 62% Number of Living Children 0% 0 2,065 8% 1–2 7,708 31% 3–4 7,941 32% 5+ 7,106 29% Residence Type Urban 10,111 41% Rural 14,708 59% Region North Central 4,653 19% North East 4,320 17% North West 9,255 37% South East 1,743 7% South South 1,794 7% South West 3,055 12% Prevalence of Contraceptive Decision-Making Autonomy Overall, 37% of married women reported having autonomy in contraceptive decision-making, while 63% indicated that contraceptive decisions were made by their partner or someone else. The national proportion is illustrated in Fig. 1 . Regional Disparities in Contraceptive Autonomy Marked regional disparities were observed (Fig. 2 ). Autonomy was highest in the South West (51%), followed by the South East (45%) and the North East (38%). The lowest autonomy levels were found in the North West (31%) and North Central (35%). These geographical variations are further visualized in the spatial map (Fig. 3 ), which highlights the concentration of low autonomy in northern regions. Bivariate Associations with Contraceptive Autonomy Table 2 presents the crude associations between explanatory variables and contraceptive autonomy. Autonomy increased steadily with age, rising from 29% among adolescents (15–19 years) to 42% among women aged 45–49 years. Compared with adolescents, older women showed significantly higher odds of autonomy, particularly those aged 35–39 years (COR = 1.67; p < 0.001) and 40–44 years (COR = 1.77; p < 0.001). Educational attainment also showed a strong positive association: women with secondary education (42%) had higher autonomy than those with no education (33%) (COR = 1.43; p < 0.001). Muslim women had lower autonomy compared with Christian women (35% vs. 41%; COR = 0.78; p < 0.001). A clear wealth gradient was observed, with autonomy increasing from 30% among the poorest women to 42% among the richest (COR for richest = 1.66; p < 0.001). Working women had significantly higher autonomy (42%) compared with non-working women (30%) (COR = 1.73; p < 0.001). Rural residence was associated with lower autonomy compared with urban residence (35% vs. 41%; COR = 0.75; p < 0.001). Regional variations were substantial. Compared with women in the North Central region, higher autonomy was observed in the South East (45%; COR = 1.51; p < 0.001) and South West (51%; COR = 1.89; p < 0.001). Conversely, women in the North West had significantly lower odds of autonomy (31%; COR = 0.84; p < 0.001). Table 2 Bivariate Associations Between Sociodemographic Factors and Contraceptive Decision-Making Autonomy Among Married Women Variable Contraceptive Autonomy COR [95% CI] P-value No Yes Age Group (5-year) 15–19 (ref.) 975 (71.1%) 396 (28.9%) 1 - 20–24 2,578 (68.0%) 1,211 (32.0%) 1.16 [0.98–1.37] 0.09 25–29 3,188 (64.4%) 1,764 (35.6%) 1.36 [1.16–1.61] < 0.001 30–34 2,962 (63.1%) 1,729 (36.9%) 1.44 [1.22–1.69] < 0.001 35–39 2,481 (59.6%) 1,681 (40.4%) 1.67 [1.42–1.97] < 0.001 40–44 1,985 (58.2%) 1,425 (41.8%) 1.77 [1.50–2.09] < 0.001 45–49 1,417 (57.9%) 1,028 (42.1%) 1.79 [1.50–2.13] < 0.001 Education Level No Education (ref.) 7,572 (66.7%) 3,780 (33.3%) 1 - Primary 1,769 (60.2%) 1,171 (39.8%) 1.33 [1.20–1.47] < 0.001 Secondary 4,356 (58.3%) 3,117 (41.7%) 1.43 [1.33–1.54] < 0.001 Higher 1,888 (61.8%) 1,165 (38.2%) 1.24 [1.12–1.36] < 0.001 Religion Christianity (ref.) 4,856 (58.8%) 3,398 (41.2%) 1 - Islam 10,657 (64.8%) 5,803 (35.2%) 0.78 [0.73–0.83] < 0.001 Others 72 (68.4%) 33 (31.6%) 0.66 [0.44–0.99] 0.046 Wealth Index Poorest (ref.) 3,733 (69.5%) 1,638 (30.5%) 1 - Poorer 3,389 (63.6%) 1,943 (36.4%) 1.31 [1.18–1.45] < 0.001 Middle 3,054 (63.2%) 1,778 (36.8%) 1.33 [1.20–1.47] < 0.001 Richer 2,634 (58.7%) 1,853 (41.3%) 1.60 [1.46–1.77] < 0.001 Richest 2,775 (57.9%) 2,022 (42.1%) 1.66 [1.51–1.83] < 0.001 Work Status Not Working (ref.) 6,678 (70.5%) 2,794 (29.5%) 1 - Working 8,907 (58.0%) 6,440 (41.9%) 1.73 [1.62–1.85] < 0.001 Number of Living Children 0 (ref.) 1,387 (67.2%) 677 (32.8%) 1 - 1–2 4,953 (64.3%) 2,755 (35.7%) 1.14 [1.00-1.29] 0.044 3–4 4,897 (61.7%) 3,044 (38.3%) 1.27 [1.12–1.44] < 0.001 5+ 4,348 (61.2%) 2,758 (38.8%) 1.30 [1.14–1.48] < 0.001 Residence Type Urban (ref.) 5,949 (58.8%) 4,162 (41.2%) 1 - Rural 9,636 (65.5%) 5,072 (34.5%) 0.75 [0.71–0.80] < 0.001 Region North Central (ref.) 3,007 (64.6%) 1,646 (35.4%) 1 - North East 2,658 (61.5%) 1,662 (38.5%) 1.14 [1.03–1.26] 0.009 North West 6,343 (68.5%) 2,911 (31.5%) 0.84 [0.77–0.92] < 0.001 South East 955 (54.8%) 788 (45.2%) 1.51 [1.36–1.68] < 0.001 South South 1,120 (62.4%) 674 (37.6%) 1.10 [0.98–1.23] 0.111 South West 1,502 (49.2%) 1,553 (50.8%) 1.89 [1.70–2.11] < 0.001 Multivariable Predictors of Contraceptive Autonomy The adjusted model (Table 3 ) identified several independent predictors of contraceptive autonomy. Age remained a significant predictor, with women aged 35–39 years having 25% higher odds of autonomy (AOR = 1.25; p = 0.025) compared with adolescents. Autonomy was also significantly higher among women aged 40–44 years (AOR = 1.31; p = 0.009) and 45–49 years (AOR = 1.30; p = 0.014). Higher education demonstrated a protective effect after adjustment: women with tertiary education were 14% less likely to report autonomy compared with those without education (AOR = 0.86; p = 0.036), although the direction suggests a context-specific pattern. Religion remained significant, with Muslim women showing slightly higher odds of autonomy than Christians (AOR = 1.14; p = 0.012). Wealth index continued to show a strong association in the adjusted model. Women in the poorer (AOR = 1.26; p < 0.001), middle (AOR = 1.17; p = 0.009), richer (AOR = 1.26; p < 0.001), and richest (AOR = 1.21; p = 0.012) households all had significantly higher odds of autonomy than those in the poorest households. Similarly, working women had substantially higher odds of autonomy than non-working women (AOR = 1.49; p < 0.001). Residence type was not associated with autonomy after adjustment (p = 0.958). Regional disparities persisted. Compared with the North Central region, women in the North East (AOR = 1.25; p < 0.001), South East (AOR = 1.41; p < 0.001), and South West (AOR = 1.70; p < 0.001) had significantly higher odds of autonomy, whereas those in the North West had reduced odds (AOR = 0.88; p = 0.015). Table 3 Multivariable Logistic Regression Analysis of Predictors of Contraceptive Decision-Making Autonomy Variable Contraceptive Autonomy AOR [95% CI] P-value No Yes Age Group (5-year) 15–19 (ref.) 975 (71.1%) 396 (28.9%) 1 - 20–24 2,578 (68.0%) 1,211 (32.0%) 1.02 [0.85–1.22] 0.813 25–29 3,188 (64.4%) 1,764 (35.6%) 1.13 [0.94–1.35] 0.184 30–34 2,962 (63.1%) 1,729 (36.9%) 1.11 [0.92–1.34] 0.262 35–39 2,481 (59.6%) 1,681 (40.4%) 1.25 [1.03–1.52] 0.025 40–44 1,985 (58.2%) 1,425 (41.8%) 1.31 [1.07–1.60] 0.009 45–49 1,417 (57.9%) 1,028 (42.1%) 1.30 [1.06–1.60] 0.014 Education Level No Education (ref.) 7,572 (66.7%) 3,780 (33.3%) 1 - Primary 1,769 (60.2%) 1,171 (39.8%) 1.09 [0.97–1.22] 0.137 Secondary 4,356 (58.3%) 3,117 (41.7%) 1.11 [1.00-1.23] 0.057 Higher 1,888 (61.8%) 1,165 (38.2%) 0.86 [0.75–0.99] 0.036 Religion Christianity (ref.) 4,856 (58.8%) 3,398 (41.2%) 1 - Islam 10,657 (64.8%) 5,803 (35.2%) 1.14 [1.03–1.25] 0.012 Others 72 (68.4%) 33 (31.6%) 0.85 [0.57–1.27] 0.429 Wealth Index Poorest (ref.) 3,733 (69.5%) 1,638 (30.5%) 1 - Poorer 3,389 (63.6%) 1,943 (36.4%) 1.26 [1.13–1.39] < 0.001 Middle 3,054 (63.2%) 1,778 (36.8%) 1.17 [1.04–1.31] 0.009 Richer 2,634 (58.7%) 1,853 (41.3%) 1.26 [1.11–1.44] < 0.001 Richest 2,775 (57.9%) 2,022 (42.1%) 1.21 [1.04–1.40] 0.012 Work Status Not Working (ref.) 6,678 (70.5%) 2,794 (29.5%) 1 - Working 8,907 (58.0%) 6,440 (41.9%) 1.49 [1.38–1.60] < 0.001 Number of Living Children 0 (ref.) 1,387 (67.2%) 677 (32.8%) 1 - 1–2 4,953 (64.3%) 2,755 (35.7%) 1.01 [0.89–1.16] 0.84 3–4 4,897 (61.7%) 3,044 (38.3%) 1.02 [0.88–1.17] 0.822 5+ 4,348 (61.2%) 2,758 (38.8%) 1.05 [0.90–1.22] 0.553 Residence Type Urban (ref.) 5,949 (58.8%) 4,162 (41.2%) 1 - Rural 9,636 (65.5%) 5,072 (34.5%) 1.00 [0.92–1.09] 0.958 Region North Central (ref.) 3,007 (64.6%) 1,646 (35.4%) 1 - North East 2,658 (61.5%) 1,662 (38.5%) 1.25 [1.12–1.39] < 0.001 North West 6,343 (68.5%) 2,911 (31.5%) 0.88 [0.79–0.98] 0.015 South East 955 (54.8%) 788 (45.2%) 1.41 [1.25–1.59] < 0.001 South South 1,120 (62.4%) 674 (37.6%) 1.05 [0.92–1.19] 0.489 South West 1,502 (49.2%) 1,553 (50.8%) 1.70 [1.51–1.91] < 0.001 DISCUSSION This study examined contraceptive decision-making autonomy among married women in Nigeria using nationally representative data, and the findings reveal important sociodemographic and regional inequalities. The overall prevalence of autonomy was relatively low, with only about one-third of women independently deciding on contraceptive use. This aligns with research from other sub-Saharan African settings, where patriarchal norms and gendered power relations remain major constraints to women’s reproductive agency ( 23 – 25 ). Limited autonomy has significant implications for women’s health, fertility preferences, and progress toward SDG 5, which emphasizes women’s bodily autonomy and decision-making rights ( 1 , 6 , 25 ). The study found substantial regional disparities, with women in the South West and South East demonstrating the highest autonomy, while those in the northern regions particularly the North West had the lowest levels. Similar patterns have been reported in previous Nigerian and regional studies, where differences in cultural norms, education, gender roles, and access to reproductive health information strongly influence women’s empowerment outcomes ( 17 , 26 – 30 ). The lower autonomy observed in northern Nigeria may be linked to early marriage, restrictive gender norms, limited educational attainment, and reduced exposure to family planning interventions, as documented in earlier analyses ( 31 – 34 ). These persistent regional inequalities underscore the need for tailored and culturally sensitive programming that addresses the underlying social structures limiting women’s decision-making power. Age was a significant predictor of autonomy, with older women having higher odds of independently deciding on contraceptive use compared with adolescents and younger women. This is consistent with previous studies showing that women’s bargaining power, confidence, and partner communication tend to increase with age and marital duration ( 35 – 38 ). Younger married women often face constraints related to limited negotiation power, societal expectations of deference, and pressure to prove fertility early in marriage ( 39 , 40 ). These findings highlight the need for age-specific interventions that support younger women, including newly married adolescents who are at heightened risk of low reproductive agency. Although education is commonly associated with greater reproductive autonomy, the pattern observed in this study, where tertiary education showed slightly reduced autonomy after adjustment, may reflect the complex dynamics of joint decision-making among educated couples. Recent evidence suggests that higher education can promote couple communication and shared reproductive choices, thereby reducing the likelihood of unilateral decision-making by women alone ( 41 – 43 ). This highlights the importance of interpreting autonomy not merely as an individual act but as part of relational dynamics between partners. Religion also demonstrated a significant association with autonomy. In contrast to assumptions that religious conservatism uniformly restricts women’s reproductive agency, Muslim women in this study exhibited slightly higher odds of autonomy after adjustment. Similar findings have been noted in emerging literature suggesting shifting attitudes toward contraceptive use within Muslim communities in West Africa ( 44 – 47 ). This may reflect increasing exposure to reproductive health education, evolving norms, or variations in religious interpretation at community level ( 48 ). Economic factors were among the most consistent predictors of autonomy. Women in wealthier households and those who were employed had significantly higher odds of autonomy, reflecting the well-documented link between economic empowerment and women’s agency ( 49 , 50 ). Employment increases women’s access to information, resources, and mobility, while also strengthening their bargaining position within households. These findings reinforce global evidence that financial stability and economic inclusion are critical pathways to enhancing women’s reproductive rights ( 51 ). Interestingly, urban–rural differences were not statistically significant in the adjusted model, suggesting that the initial disparities were explained by underlying socioeconomic characteristics such as wealth, education, and region. Similar observations have been reported by other authors, who argue that urban–rural gaps diminish when structural inequalities are accounted for ( 52 – 54 ). This highlights the importance of addressing root determinants rather than geography alone. The persistence of regional disparities in the fully adjusted model underscores the entrenched influence of socio-cultural norms and community-level gender ideologies. Women in the South East and South West retained significantly higher odds of autonomy, while those in the North West remained substantially disadvantaged which aligns with longstanding evidence on Nigeria’s gender and cultural heterogeneity ( 55 , 56 ). These results emphasize the need for region-specific strategies, particularly in northern Nigeria, to foster gender-equitable norms, engage community leaders, and enhance couple communication around reproductive choices. Overall, this study demonstrates that contraceptive decision-making autonomy among Nigerian women is shaped by a complex interaction of demographic factors, socioeconomic status, and regional context. Addressing these inequalities will require multisectoral interventions that simultaneously promote girls’ education, expand economic opportunities for women, strengthen reproductive health messaging, and engage communities in transforming restrictive gender norms. CONCLUSION This study provides important insights into the state of contraceptive decision-making autonomy among married women in Nigeria using recent nationally representative data. The overall prevalence of autonomy remains low, with substantial disparities across sociodemographic groups and geopolitical regions. Older age, higher household wealth, and employment were key enabling factors for women’s autonomy, while persistent structural and cultural constraints particularly in the northern regions, continue to limit independent decision-making for many women. These findings underscore the need for targeted, context-specific strategies that address gender norms, increase access to education and economic opportunities, and strengthen reproductive health programs aimed at enhancing women’s agency. Advancing contraceptive autonomy is essential not only for improving reproductive health outcomes but also for accelerating progress toward Sustainable Development Goal 5, which emphasizes women’s empowerment and the right to make informed decisions about sexual and reproductive health. Strengths and Limitations A major strength of this study is the use of data from the recent 2024 Nigeria Demographic and Health Survey, which provides a large, nationally representative sample of married women across all regions. The standardized DHS methodology enhances the validity and comparability of the findings. Additionally, the study employed robust analytical approaches, including weighted multivariable logistic regression, to identify independent predictors of contraceptive autonomy. The inclusion of geospatial visualization further strengthens the interpretation of regional patterns. Despite these strengths, the study has some limitations. First, the cross-sectional nature of the NDHS data limits the ability to establish causal relationships between the explanatory variables and contraceptive autonomy. Second, the outcome variable is based on self-reported measures of decision-making, which may be subject to social desirability or recall bias. Third, the dichotomization of decision-making categories, though necessary for analysis, may obscure nuances in joint decision-making dynamics. Finally, some potentially relevant contextual or cultural factors such as gender norms, partner attitudes, and community influence were not captured in the dataset and could not be explored. Declarations Ethics Approval and Consent to Participate The 2024 Nigeria Demographic and Health Survey (NDHS) obtained ethical approval from the National Health Research Ethics Committee of Nigeria (NHREC) and the ICF Institutional Review Board. All procedures were performed in accordance with the ethical standards of these committees and with the 1975 Declaration of Helsinki, as revised in 2013. Written informed consent was obtained from all participants at the time of data collection. This study involved secondary analysis of publicly available, de-identified DHS data and therefore required no additional ethical approval. Consent for Publication Not applicable. Competing Interests The authors declare that they have no competing interests. Disclaimer The views expressed in this manuscript are those of the authors and do not necessarily reflect the official policies or positions of the DHS Program, ICF, or the Government of Nigeria. Funding This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. Author Contribution JS conceptualized the study, designed the methodology, managed the data, conducted the statistical analysis, and drafted the initial manuscript. AAA, AYA, IGW, BH, MUG, IS, UIB, RAY, AMO, MAS and OA contributed to the interpretation of findings, critically reviewed the manuscript for important intellectual content, and provided substantial revisions. All authors read and approved the final version of the manuscript. Acknowledgement The authors are grateful to the DHS Program and the National Population Commission (NPC) of Nigeria for granting access to the 2024 NDHS dataset used in this analysis. Data Availability The datasets used in this study are publicly available from the DHS Program upon reasonable request and completion of the required authorization process ( [https://dhsprogram.com). References 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):e0000832. Idris IB, Hamis AA, Bukhori ABM, Hoong DCC, Yusop H, Shaharuddin MAA, et al. 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Sanni OF, Sanni AE, Onyeagwaibe CI, Ahamuefula T, Akeju OP. A comparative analysis of factors associated with modern contraceptive use among youth in Northern and Southern Nigeria: A cross-sectional population-based survey (2011–2021). PLOS Glob Public Health. 2025 June 2;5(6):e0004685. Saaka SA, Luginaah I. Do women’s autonomy lessen the brunt of unequal household responsibilities in the patriarchal context of semi-arid Northern Ghana? PLoS ONE. 2025;20(10):e0335142. Michael TO, Naidoo K. Education, economic autonomy and digitalization as factors associated with married women’s ability to make sexual and reproductive health decisions in sub-Saharan Africa: a multi-level analysis of 16 countries. BMC Women’s Health. 2025;25(1):407. Ogunrinde O, THE ROLE OF FINANCIAL. INCLUSION IN WOMEN’S ECONOMIC EMPOWERMENT: EVIDENCE FROM NIGERIA. 2024. Zhong S, Wang M, Zhu Y, Chen Z, Huang X. Urban expansion and the urban–rural income gap: Empirical evidence from China. Cities. 2022;129:103831. 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09:14:55","extension":"html","order_by":8,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":169269,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8149264/v1/fb67b8846b0021ebcab01cac.html"},{"id":97383611,"identity":"3386d218-66d6-4e87-b186-e53a42e911e1","added_by":"auto","created_at":"2025-12-03 19:01:09","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":45417,"visible":true,"origin":"","legend":"\u003cp\u003eNational Prevalence of Contraceptive Decision-Making Autonomy Among Married Women in Nigeria\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8149264/v1/b8dbe1adb3facb7d73cc170b.png"},{"id":97383610,"identity":"a162fe51-9086-4ad2-91f7-60c727a14298","added_by":"auto","created_at":"2025-12-03 19:01:09","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":43009,"visible":true,"origin":"","legend":"\u003cp\u003eRegional Distribution of Contraceptive Decision-Making Autonomy Across Nigeria’s Six Geopolitical Zones\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8149264/v1/695f58c6dc2c0e72110b32b9.png"},{"id":97383613,"identity":"6b03862b-a430-4242-8a55-9326e0e1258e","added_by":"auto","created_at":"2025-12-03 19:01:09","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":120754,"visible":true,"origin":"","legend":"\u003cp\u003eGeographic Map Showing Regional Variation in Contraceptive Decision-Making Autonomy Among Married Women in Nigeria\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8149264/v1/01de5adf2a6ac135c7d0cab4.png"},{"id":97677231,"identity":"62714beb-a888-415c-b9c1-af2daef48aa7","added_by":"auto","created_at":"2025-12-08 09:52:32","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1638399,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8149264/v1/782d8820-0154-4d5a-940e-f20897f44c34.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Contraceptive Decision-Making Autonomy Among Married Women in Nigeria: Regional Disparities and Determinants Using the 2024 NDHS","fulltext":[{"header":"BACKGROUND","content":"\u003cp\u003eWomen\u0026rsquo;s autonomy in reproductive decision-making is a central component of sexual and reproductive health rights and a critical indicator of gender equality (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Contraceptive decision-making autonomy refers to a woman\u0026rsquo;s ability to independently choose whether and when to use contraception, free from coercion, pressure, or unequal power dynamics within relationships (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). This autonomy is essential for achieving desired fertility, preventing unintended pregnancies, and improving maternal and child health outcomes (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Globally, enhancing women\u0026rsquo;s reproductive agency aligns with the Sustainable Development Goals (SDGs), particularly SDG 5, which emphasizes the elimination of gender inequalities and the promotion of women\u0026rsquo;s decision-making power in matters affecting their health and well-being (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eDespite global progress in expanding access to modern contraceptives, many women especially in low and middle-income countries still lack the power to make independent decisions regarding their reproductive choices (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). Evidence from sub-Saharan Africa shows that contraceptive decision-making is frequently influenced by patriarchal norms, relational power imbalances, and socio-cultural expectations that prioritize male authority in fertility-related matters (\u003cspan additionalcitationids=\"CR11 CR12\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). These constraints often limit women\u0026rsquo;s agency even when contraceptive services are available, underscoring the need to consider autonomy as distinct from mere access.\u003c/p\u003e\u003cp\u003eIn Nigeria, women\u0026rsquo;s empowerment and contraceptive autonomy remain major public health concerns. The country continues to record low contraceptive prevalence and high fertility rates relative to regional averages (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). Socio-cultural norms, gender power relations, and religious influences strongly shape reproductive behavior, often restricting women\u0026rsquo;s independence in making decisions about contraception (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). The northern regions, in particular, are characterized by early marriage, limited female education, and deeply entrenched gender norms, which contribute to lower levels of reproductive autonomy compared with the southern regions (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). These inequalities have been consistently highlighted in previous demographic analyses and underscore the heterogeneity of women\u0026rsquo;s reproductive experiences in Nigeria.\u003c/p\u003e\u003cp\u003eMoreover, socioeconomic factors such as education, wealth, employment, and exposure to health information have been shown to influence women\u0026rsquo;s ability to participate in reproductive decision-making (\u003cspan additionalcitationids=\"CR19 CR20\" citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). Women with economic independence or higher educational attainment are often better positioned to negotiate contraceptive use and challenge restrictive gender norms. However, existing evidence remains mixed on how these factors interact with regional, cultural, and religious contexts in shaping women\u0026rsquo;s autonomy in Nigeria.\u003c/p\u003e\u003cp\u003eWhile previous studies have examined determinants of maternal health services, contraceptive uptake, and women\u0026rsquo;s empowerment, limited recent research has focused specifically on contraceptive decision-making autonomy using the most updated nationally representative data. Understanding the current patterns and drivers of autonomy is critical for informing policy, strengthening gender-sensitive family planning programs, and accelerating national progress toward SDG 5.\u003c/p\u003e\u003cp\u003eThis study therefore assessed the prevalence, regional disparities, and sociodemographic determinants of contraceptive decision-making autonomy among married women in Nigeria using the 2024 Nigeria Demographic and Health Survey (NDHS). Findings from this analysis provide contemporary evidence on women\u0026rsquo;s reproductive agency and highlight priority areas for targeted interventions.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy Design and Data Source\u003c/h2\u003e\u003cp\u003eThis study employed a cross-sectional analytical design using data from the 2024 Nigeria Demographic and Health Survey (NDHS). The NDHS is a nationally representative survey conducted periodically to collect comprehensive information on population, reproductive health, and sociodemographic indicators among women aged 15\u0026ndash;49 years. The survey uses a stratified two-stage cluster sampling technique to ensure adequate representation across the six geopolitical zones and urban\u0026ndash;rural strata (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). Data collection is implemented by the National Population Commission (NPC) in collaboration with ICF International using standardized DHS protocols to ensure comparability across countries and survey years.\u003c/p\u003e\u003cp\u003eFor this study, we extracted data from the Individual Recode (IR) file, which contains detailed information on women\u0026rsquo;s reproductive health behaviors, sociodemographic characteristics, and decision-making dynamics relevant to contraceptive autonomy.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eStudy Population and Sample Selection\u003c/h3\u003e\n\u003cp\u003eThe target population included married or in-union women aged 15\u0026ndash;49 years who participated in the 2024 NDHS. From the IR dataset, we identified women who responded to the question on decision-making regarding contraceptive use. After excluding respondents with missing information on the outcome variable or key covariates, a total of 24,819 women formed the final analytical sample.\u003c/p\u003e\n\u003ch3\u003eEthical Considerations\u003c/h3\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval\u003c/strong\u003e\u003cp\u003e for the 2024 NDHS was granted by the National Health Research Ethics Committee of Nigeria and the ICF Institutional Review Board. Informed consent was obtained from all participants prior to participation. This study involved secondary analysis of anonymized publicly available data and therefore required no additional ethical clearance.\u003c/p\u003e\u003c/p\u003e\n\u003ch3\u003eStudy Variables\u003c/h3\u003e\n\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e\u003ch2\u003eOutcome Variable\u003c/h2\u003e\u003cp\u003eThe primary outcome was contraceptive decision-making autonomy, derived from the DHS question on who usually makes decisions regarding contraceptive use. The original responses included: respondent, husband/partner, joint decision, someone else, and other. For analytical purposes, we created a binary outcome variable indicating women's autonomy. Women who reported making the decision themselves were coded as 1 (autonomous), while all other categories were coded as 0 (not autonomous).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eExplanatory Variables\u003c/h2\u003e\u003cp\u003eThe independent variables were selected based on theoretical relevance and previous empirical evidence on women\u0026rsquo;s empowerment and reproductive decision-making. These variables included:\u003c/p\u003e\u003cp\u003e\u003cul\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eAge group\u003c/b\u003e (5-year categories)\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eEducation level\u003c/b\u003e (no education, primary, secondary, higher)\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eReligion\u003c/b\u003e (Christianity, Islam, others)\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eWealth index\u003c/b\u003e (poorest to richest)\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eEmployment status\u003c/b\u003e (working vs. not working)\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eNumber of living children\u003c/b\u003e (0, 1\u0026ndash;2, 3\u0026ndash;4, \u0026ge;\u0026thinsp;5)\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003ePlace of residence\u003c/b\u003e (urban/rural)\u003c/p\u003e\u003c/li\u003e\u003cli\u003e\u003cp\u003e\u003cb\u003eRegion\u003c/b\u003e (North Central, North East, North West, South East, South South, South West)\u003c/p\u003e\u003c/li\u003e\u003c/ul\u003e\u003c/p\u003e\u003cp\u003eThese variables were treated as categorical and entered into both the bivariate and multivariable models.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\u003cp\u003eDescriptive statistics were used to summarize the sociodemographic characteristics of the study population, with results presented as frequencies and weighted percentages to account for the survey design. The overall and regional prevalence of contraceptive decision-making autonomy was examined and illustrated using bar charts and a geospatial map produced with Python\u0026rsquo;s GeoPandas library and Natural Earth administrative boundary data for Nigeria. All statistical analyses were performed using Stata version 17 (StataCorp LLC, College Station, TX, USA).\u003c/p\u003e\u003cp\u003eBivariate associations between each independent variable and contraceptive autonomy were assessed using logistic regression models, from which crude odds ratios (CORs) and corresponding 95% confidence intervals (CIs) were derived. Variables that demonstrated a statistically significant association at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 in the bivariate analysis were subsequently included in the multivariable logistic regression model to identify independent predictors of autonomy. Adjusted odds ratios (AORs) with 95% CIs were reported for the multivariable model. All analyses incorporated sampling weights, clustering, and stratification to adjust for the complex survey design of the NDHS. Statistical significance was set at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e\u003c/div\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eSociodemographic Characteristics of Married Women\u003c/h2\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e presents the sociodemographic characteristics of the study population. A total of 24,819 married women aged 15\u0026ndash;49 years were included in the analysis. The largest proportion of respondents were aged 25\u0026ndash;29 years (20%), followed by those aged 30\u0026ndash;34 years (19%). Nearly half of the women (46%) had no formal education, 30% had secondary education, while only 12% attained higher education. Most respondents identified as Muslim (66%), while 33% were Christians. Regarding household wealth, 22% of women were from the poorest quintile, and 19% belonged to the richest quintile. Approximately 62% of the women were employed, and 32% had three to four living children. The majority resided in rural areas (59%), and the North West accounted for the highest regional representation (37%).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSociodemographic Characteristics\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\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=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\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\u003eCategory\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eFrequency\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePercent (%)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge Group (5-year)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e15\u0026ndash;19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1,371\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e20\u0026ndash;24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3,789\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e15%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e25\u0026ndash;29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4,952\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e20%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e30\u0026ndash;34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4,691\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e19%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e35\u0026ndash;39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4,162\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e17%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e40\u0026ndash;44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3,409\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e14%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e45\u0026ndash;49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2,446\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eEducation Level\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo Education\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e11,352\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e46%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePrimary\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2,941\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e12%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSecondary\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e7,473\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e30%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHigher\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3,053\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e12%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eReligion\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eChristianity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e8,255\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e33.3%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eIslam\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e16,459\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e66.3%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOthers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e105\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.4%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eWealth Index\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePoorest\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5,370\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e22%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePoorer\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5,332\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e21%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMiddle\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4,832\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e19%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRicher\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4,487\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e18%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRichest\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4,798\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e19%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eWork Status\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNot Working\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e9,472\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e38%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eWorking\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e15,347\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e62%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eNumber of Living Children\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2,065\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1\u0026ndash;2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e7,708\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e31%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e3\u0026ndash;4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e7,941\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e32%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e7,106\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e29%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eResidence Type\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUrban\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e10,111\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e41%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRural\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e14,708\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e59%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eRegion\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNorth Central\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4,653\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e19%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNorth East\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4,320\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e17%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNorth West\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e9,255\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e37%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSouth East\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1,743\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSouth South\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1,794\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSouth West\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3,055\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e12%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003ePrevalence of Contraceptive Decision-Making Autonomy\u003c/h2\u003e\u003cp\u003eOverall, 37% of married women reported having autonomy in contraceptive decision-making, while 63% indicated that contraceptive decisions were made by their partner or someone else. The national proportion is illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\u003ch2\u003eRegional Disparities in Contraceptive Autonomy\u003c/h2\u003e\u003cp\u003eMarked regional disparities were observed (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Autonomy was highest in the South West (51%), followed by the South East (45%) and the North East (38%). The lowest autonomy levels were found in the North West (31%) and North Central (35%). These geographical variations are further visualized in the spatial map (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), which highlights the concentration of low autonomy in northern regions.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003eBivariate Associations with Contraceptive Autonomy\u003c/h2\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e presents the crude associations between explanatory variables and contraceptive autonomy. Autonomy increased steadily with age, rising from 29% among adolescents (15\u0026ndash;19 years) to 42% among women aged 45\u0026ndash;49 years. Compared with adolescents, older women showed significantly higher odds of autonomy, particularly those aged 35\u0026ndash;39 years (COR\u0026thinsp;=\u0026thinsp;1.67; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and 40\u0026ndash;44 years (COR\u0026thinsp;=\u0026thinsp;1.77; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Educational attainment also showed a strong positive association: women with secondary education (42%) had higher autonomy than those with no education (33%) (COR\u0026thinsp;=\u0026thinsp;1.43; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Muslim women had lower autonomy compared with Christian women (35% vs. 41%; COR\u0026thinsp;=\u0026thinsp;0.78; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). A clear wealth gradient was observed, with autonomy increasing from 30% among the poorest women to 42% among the richest (COR for richest\u0026thinsp;=\u0026thinsp;1.66; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Working women had significantly higher autonomy (42%) compared with non-working women (30%) (COR\u0026thinsp;=\u0026thinsp;1.73; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Rural residence was associated with lower autonomy compared with urban residence (35% vs. 41%; COR\u0026thinsp;=\u0026thinsp;0.75; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Regional variations were substantial. Compared with women in the North Central region, higher autonomy was observed in the South East (45%; COR\u0026thinsp;=\u0026thinsp;1.51; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and South West (51%; COR\u0026thinsp;=\u0026thinsp;1.89; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Conversely, women in the North West had significantly lower odds of autonomy (31%; COR\u0026thinsp;=\u0026thinsp;0.84; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eBivariate Associations Between Sociodemographic Factors and Contraceptive Decision-Making Autonomy Among Married Women\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eContraceptive Autonomy\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eCOR [95% CI]\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eP-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge Group (5-year)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e15\u0026ndash;19 (ref.)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e975 (71.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e396 (28.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e20\u0026ndash;24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2,578 (68.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1,211 (32.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.16 [0.98\u0026ndash;1.37]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.09\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e25\u0026ndash;29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3,188 (64.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1,764 (35.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.36 [1.16\u0026ndash;1.61]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\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\u003e30\u0026ndash;34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2,962 (63.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1,729 (36.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.44 [1.22\u0026ndash;1.69]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\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\u003e35\u0026ndash;39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2,481 (59.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1,681 (40.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.67 [1.42\u0026ndash;1.97]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\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\u003e40\u0026ndash;44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1,985 (58.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1,425 (41.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.77 [1.50\u0026ndash;2.09]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\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\u003e45\u0026ndash;49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1,417 (57.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1,028 (42.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.79 [1.50\u0026ndash;2.13]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\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\u003e\u003cb\u003eEducation Level\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo Education (ref.)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e7,572 (66.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3,780 (33.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePrimary\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1,769 (60.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1,171 (39.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.33 [1.20\u0026ndash;1.47]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\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\u003eSecondary\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e4,356 (58.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3,117 (41.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.43 [1.33\u0026ndash;1.54]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\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\u003eHigher\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1,888 (61.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1,165 (38.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.24 [1.12\u0026ndash;1.36]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\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\u003e\u003cb\u003eReligion\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eChristianity (ref.)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e4,856 (58.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3,398 (41.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIslam\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e10,657 (64.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5,803 (35.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.78 [0.73\u0026ndash;0.83]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\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\u003eOthers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e72 (68.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e33 (31.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.66 [0.44\u0026ndash;0.99]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.046\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eWealth Index\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePoorest (ref.)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3,733 (69.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1,638 (30.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePoorer\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3,389 (63.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1,943 (36.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.31 [1.18\u0026ndash;1.45]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\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\u003eMiddle\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3,054 (63.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1,778 (36.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.33 [1.20\u0026ndash;1.47]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\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\u003eRicher\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2,634 (58.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1,853 (41.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.60 [1.46\u0026ndash;1.77]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\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\u003eRichest\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2,775 (57.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2,022 (42.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.66 [1.51\u0026ndash;1.83]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\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\u003e\u003cb\u003eWork Status\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNot Working (ref.)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6,678 (70.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2,794 (29.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWorking\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e8,907 (58.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e6,440 (41.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.73 [1.62\u0026ndash;1.85]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\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\u003e\u003cb\u003eNumber of Living Children\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e0 (ref.)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1,387 (67.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e677 (32.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u0026ndash;2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e4,953 (64.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2,755 (35.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.14 [1.00-1.29]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.044\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3\u0026ndash;4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e4,897 (61.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3,044 (38.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.27 [1.12\u0026ndash;1.44]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\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\u003e5+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e4,348 (61.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2,758 (38.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.30 [1.14\u0026ndash;1.48]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\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\u003e\u003cb\u003eResidence Type\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUrban (ref.)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e5,949 (58.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4,162 (41.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRural\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e9,636 (65.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5,072 (34.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.75 [0.71\u0026ndash;0.80]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\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\u003e\u003cb\u003eRegion\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNorth Central (ref.)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3,007 (64.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1,646 (35.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNorth East\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2,658 (61.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1,662 (38.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.14 [1.03\u0026ndash;1.26]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.009\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNorth West\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6,343 (68.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2,911 (31.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.84 [0.77\u0026ndash;0.92]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\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\u003eSouth East\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e955 (54.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e788 (45.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.51 [1.36\u0026ndash;1.68]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\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\u003eSouth South\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1,120 (62.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e674 (37.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.10 [0.98\u0026ndash;1.23]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.111\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSouth West\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1,502 (49.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1,553 (50.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.89 [1.70\u0026ndash;2.11]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003eMultivariable Predictors of Contraceptive Autonomy\u003c/h2\u003e\u003cp\u003eThe adjusted model (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) identified several independent predictors of contraceptive autonomy. Age remained a significant predictor, with women aged 35\u0026ndash;39 years having 25% higher odds of autonomy (AOR\u0026thinsp;=\u0026thinsp;1.25; p\u0026thinsp;=\u0026thinsp;0.025) compared with adolescents. Autonomy was also significantly higher among women aged 40\u0026ndash;44 years (AOR\u0026thinsp;=\u0026thinsp;1.31; p\u0026thinsp;=\u0026thinsp;0.009) and 45\u0026ndash;49 years (AOR\u0026thinsp;=\u0026thinsp;1.30; p\u0026thinsp;=\u0026thinsp;0.014). Higher education demonstrated a protective effect after adjustment: women with tertiary education were 14% less likely to report autonomy compared with those without education (AOR\u0026thinsp;=\u0026thinsp;0.86; p\u0026thinsp;=\u0026thinsp;0.036), although the direction suggests a context-specific pattern. Religion remained significant, with Muslim women showing slightly higher odds of autonomy than Christians (AOR\u0026thinsp;=\u0026thinsp;1.14; p\u0026thinsp;=\u0026thinsp;0.012).\u003c/p\u003e\u003cp\u003eWealth index continued to show a strong association in the adjusted model. Women in the poorer (AOR\u0026thinsp;=\u0026thinsp;1.26; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), middle (AOR\u0026thinsp;=\u0026thinsp;1.17; p\u0026thinsp;=\u0026thinsp;0.009), richer (AOR\u0026thinsp;=\u0026thinsp;1.26; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and richest (AOR\u0026thinsp;=\u0026thinsp;1.21; p\u0026thinsp;=\u0026thinsp;0.012) households all had significantly higher odds of autonomy than those in the poorest households. Similarly, working women had substantially higher odds of autonomy than non-working women (AOR\u0026thinsp;=\u0026thinsp;1.49; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\u003cp\u003eResidence type was not associated with autonomy after adjustment (p\u0026thinsp;=\u0026thinsp;0.958). Regional disparities persisted. Compared with the North Central region, women in the North East (AOR\u0026thinsp;=\u0026thinsp;1.25; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), South East (AOR\u0026thinsp;=\u0026thinsp;1.41; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and South West (AOR\u0026thinsp;=\u0026thinsp;1.70; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) had significantly higher odds of autonomy, whereas those in the North West had reduced odds (AOR\u0026thinsp;=\u0026thinsp;0.88; p\u0026thinsp;=\u0026thinsp;0.015).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eMultivariable Logistic Regression Analysis of Predictors of Contraceptive Decision-Making Autonomy\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eContraceptive Autonomy\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eAOR [95% CI]\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eP-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge Group (5-year)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e15\u0026ndash;19 (ref.)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e975 (71.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e396 (28.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e20\u0026ndash;24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2,578 (68.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1,211 (32.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.02 [0.85\u0026ndash;1.22]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.813\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e25\u0026ndash;29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3,188 (64.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1,764 (35.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.13 [0.94\u0026ndash;1.35]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.184\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e30\u0026ndash;34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2,962 (63.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1,729 (36.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.11 [0.92\u0026ndash;1.34]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.262\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e35\u0026ndash;39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2,481 (59.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1,681 (40.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.25 [1.03\u0026ndash;1.52]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.025\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e40\u0026ndash;44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1,985 (58.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1,425 (41.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.31 [1.07\u0026ndash;1.60]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.009\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e45\u0026ndash;49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1,417 (57.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1,028 (42.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.30 [1.06\u0026ndash;1.60]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.014\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eEducation Level\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo Education (ref.)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e7,572 (66.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3,780 (33.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePrimary\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1,769 (60.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1,171 (39.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.09 [0.97\u0026ndash;1.22]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.137\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSecondary\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e4,356 (58.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3,117 (41.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.11 [1.00-1.23]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.057\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHigher\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1,888 (61.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1,165 (38.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.86 [0.75\u0026ndash;0.99]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.036\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eReligion\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eChristianity (ref.)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e4,856 (58.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3,398 (41.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIslam\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e10,657 (64.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5,803 (35.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.14 [1.03\u0026ndash;1.25]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.012\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOthers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e72 (68.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e33 (31.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.85 [0.57\u0026ndash;1.27]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.429\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eWealth Index\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePoorest (ref.)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3,733 (69.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1,638 (30.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePoorer\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3,389 (63.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1,943 (36.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.26 [1.13\u0026ndash;1.39]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\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\u003eMiddle\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3,054 (63.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1,778 (36.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.17 [1.04\u0026ndash;1.31]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.009\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRicher\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2,634 (58.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1,853 (41.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.26 [1.11\u0026ndash;1.44]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\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\u003eRichest\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2,775 (57.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2,022 (42.1%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.21 [1.04\u0026ndash;1.40]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.012\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eWork Status\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNot Working (ref.)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6,678 (70.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2,794 (29.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWorking\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e8,907 (58.0%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e6,440 (41.9%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.49 [1.38\u0026ndash;1.60]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\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\u003e\u003cb\u003eNumber of Living Children\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e0 (ref.)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1,387 (67.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e677 (32.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u0026ndash;2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e4,953 (64.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2,755 (35.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.01 [0.89\u0026ndash;1.16]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.84\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3\u0026ndash;4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e4,897 (61.7%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e3,044 (38.3%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.02 [0.88\u0026ndash;1.17]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.822\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e5+\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e4,348 (61.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2,758 (38.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.05 [0.90\u0026ndash;1.22]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.553\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eResidence Type\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUrban (ref.)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e5,949 (58.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e4,162 (41.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRural\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e9,636 (65.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5,072 (34.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.00 [0.92\u0026ndash;1.09]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.958\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eRegion\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNorth Central (ref.)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e3,007 (64.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1,646 (35.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e-\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNorth East\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e2,658 (61.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1,662 (38.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.25 [1.12\u0026ndash;1.39]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\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\u003eNorth West\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e6,343 (68.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e2,911 (31.5%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.88 [0.79\u0026ndash;0.98]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.015\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSouth East\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e955 (54.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e788 (45.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.41 [1.25\u0026ndash;1.59]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\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\u003eSouth South\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1,120 (62.4%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e674 (37.6%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.05 [0.92\u0026ndash;1.19]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.489\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSouth West\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e1,502 (49.2%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1,553 (50.8%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.70 [1.51\u0026ndash;1.91]\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eThis study examined contraceptive decision-making autonomy among married women in Nigeria using nationally representative data, and the findings reveal important sociodemographic and regional inequalities. The overall prevalence of autonomy was relatively low, with only about one-third of women independently deciding on contraceptive use. This aligns with research from other sub-Saharan African settings, where patriarchal norms and gendered power relations remain major constraints to women\u0026rsquo;s reproductive agency (\u003cspan additionalcitationids=\"CR24\" citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). Limited autonomy has significant implications for women\u0026rsquo;s health, fertility preferences, and progress toward SDG 5, which emphasizes women\u0026rsquo;s bodily autonomy and decision-making rights (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe study found substantial regional disparities, with women in the South West and South East demonstrating the highest autonomy, while those in the northern regions particularly the North West had the lowest levels. Similar patterns have been reported in previous Nigerian and regional studies, where differences in cultural norms, education, gender roles, and access to reproductive health information strongly influence women\u0026rsquo;s empowerment outcomes (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan additionalcitationids=\"CR27 CR28 CR29\" citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). The lower autonomy observed in northern Nigeria may be linked to early marriage, restrictive gender norms, limited educational attainment, and reduced exposure to family planning interventions, as documented in earlier analyses (\u003cspan additionalcitationids=\"CR32 CR33\" citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e). These persistent regional inequalities underscore the need for tailored and culturally sensitive programming that addresses the underlying social structures limiting women\u0026rsquo;s decision-making power.\u003c/p\u003e\u003cp\u003eAge was a significant predictor of autonomy, with older women having higher odds of independently deciding on contraceptive use compared with adolescents and younger women. This is consistent with previous studies showing that women\u0026rsquo;s bargaining power, confidence, and partner communication tend to increase with age and marital duration (\u003cspan additionalcitationids=\"CR36 CR37\" citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e). Younger married women often face constraints related to limited negotiation power, societal expectations of deference, and pressure to prove fertility early in marriage (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e). These findings highlight the need for age-specific interventions that support younger women, including newly married adolescents who are at heightened risk of low reproductive agency.\u003c/p\u003e\u003cp\u003eAlthough education is commonly associated with greater reproductive autonomy, the pattern observed in this study, where tertiary education showed slightly reduced autonomy after adjustment, may reflect the complex dynamics of joint decision-making among educated couples. Recent evidence suggests that higher education can promote couple communication and shared reproductive choices, thereby reducing the likelihood of unilateral decision-making by women alone (\u003cspan additionalcitationids=\"CR42\" citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e). This highlights the importance of interpreting autonomy not merely as an individual act but as part of relational dynamics between partners.\u003c/p\u003e\u003cp\u003eReligion also demonstrated a significant association with autonomy. In contrast to assumptions that religious conservatism uniformly restricts women\u0026rsquo;s reproductive agency, Muslim women in this study exhibited slightly higher odds of autonomy after adjustment. Similar findings have been noted in emerging literature suggesting shifting attitudes toward contraceptive use within Muslim communities in West Africa (\u003cspan additionalcitationids=\"CR45 CR46\" citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e). This may reflect increasing exposure to reproductive health education, evolving norms, or variations in religious interpretation at community level (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eEconomic factors were among the most consistent predictors of autonomy. Women in wealthier households and those who were employed had significantly higher odds of autonomy, reflecting the well-documented link between economic empowerment and women\u0026rsquo;s agency (\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e). Employment increases women\u0026rsquo;s access to information, resources, and mobility, while also strengthening their bargaining position within households. These findings reinforce global evidence that financial stability and economic inclusion are critical pathways to enhancing women\u0026rsquo;s reproductive rights (\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eInterestingly, urban\u0026ndash;rural differences were not statistically significant in the adjusted model, suggesting that the initial disparities were explained by underlying socioeconomic characteristics such as wealth, education, and region. Similar observations have been reported by other authors, who argue that urban\u0026ndash;rural gaps diminish when structural inequalities are accounted for (\u003cspan additionalcitationids=\"CR53\" citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e). This highlights the importance of addressing root determinants rather than geography alone.\u003c/p\u003e\u003cp\u003e The persistence of regional disparities in the fully adjusted model underscores the entrenched influence of socio-cultural norms and community-level gender ideologies. Women in the South East and South West retained significantly higher odds of autonomy, while those in the North West remained substantially disadvantaged which aligns with longstanding evidence on Nigeria\u0026rsquo;s gender and cultural heterogeneity (\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e, \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e). These results emphasize the need for region-specific strategies, particularly in northern Nigeria, to foster gender-equitable norms, engage community leaders, and enhance couple communication around reproductive choices.\u003c/p\u003e\u003cp\u003eOverall, this study demonstrates that contraceptive decision-making autonomy among Nigerian women is shaped by a complex interaction of demographic factors, socioeconomic status, and regional context. Addressing these inequalities will require multisectoral interventions that simultaneously promote girls\u0026rsquo; education, expand economic opportunities for women, strengthen reproductive health messaging, and engage communities in transforming restrictive gender norms.\u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eThis study provides important insights into the state of contraceptive decision-making autonomy among married women in Nigeria using recent nationally representative data. The overall prevalence of autonomy remains low, with substantial disparities across sociodemographic groups and geopolitical regions. Older age, higher household wealth, and employment were key enabling factors for women\u0026rsquo;s autonomy, while persistent structural and cultural constraints particularly in the northern regions, continue to limit independent decision-making for many women. These findings underscore the need for targeted, context-specific strategies that address gender norms, increase access to education and economic opportunities, and strengthen reproductive health programs aimed at enhancing women\u0026rsquo;s agency. Advancing contraceptive autonomy is essential not only for improving reproductive health outcomes but also for accelerating progress toward Sustainable Development Goal 5, which emphasizes women\u0026rsquo;s empowerment and the right to make informed decisions about sexual and reproductive health.\u003c/p\u003e\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003eStrengths and Limitations\u003c/h2\u003e\u003cp\u003eA major strength of this study is the use of data from the recent 2024 Nigeria Demographic and Health Survey, which provides a large, nationally representative sample of married women across all regions. The standardized DHS methodology enhances the validity and comparability of the findings. Additionally, the study employed robust analytical approaches, including weighted multivariable logistic regression, to identify independent predictors of contraceptive autonomy. The inclusion of geospatial visualization further strengthens the interpretation of regional patterns.\u003c/p\u003e\u003cp\u003eDespite these strengths, the study has some limitations. First, the cross-sectional nature of the NDHS data limits the ability to establish causal relationships between the explanatory variables and contraceptive autonomy. Second, the outcome variable is based on self-reported measures of decision-making, which may be subject to social desirability or recall bias. Third, the dichotomization of decision-making categories, though necessary for analysis, may obscure nuances in joint decision-making dynamics. Finally, some potentially relevant contextual or cultural factors such as gender norms, partner attitudes, and community influence were not captured in the dataset and could not be explored.\u003c/p\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics Approval and Consent to Participate\u003c/strong\u003e\u003cp\u003e The 2024 Nigeria Demographic and Health Survey (NDHS) obtained ethical approval from the National Health Research Ethics Committee of Nigeria (NHREC) and the ICF Institutional Review Board. All procedures were performed in accordance with the ethical standards of these committees and with the 1975 Declaration of Helsinki, as revised in 2013. Written informed consent was obtained from all participants at the time of data collection. This study involved secondary analysis of publicly available, de-identified DHS data and therefore required no additional ethical approval.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConsent for Publication\u003c/strong\u003e\u003cp\u003eNot applicable.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003ch2\u003eCompeting Interests\u003c/h2\u003e\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\u003c/p\u003e\u003cp\u003e\u003ch2\u003eDisclaimer\u003c/h2\u003e\u003cp\u003eThe views expressed in this manuscript are those of the authors and do not necessarily reflect the official policies or positions of the DHS Program, ICF, or the Government of Nigeria.\u003c/p\u003e\u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e\u003cp\u003eThis research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eJS conceptualized the study, designed the methodology, managed the data, conducted the statistical analysis, and drafted the initial manuscript. AAA, AYA, IGW, BH, MUG, IS, UIB, RAY, AMO, MAS and OA contributed to the interpretation of findings, critically reviewed the manuscript for important intellectual content, and provided substantial revisions. All authors read and approved the final version of the manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThe authors are grateful to the DHS Program and the National Population Commission (NPC) of Nigeria for granting access to the 2024 NDHS dataset used in this analysis.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe datasets used in this study are publicly available from the DHS Program upon reasonable request and completion of the required authorization process ( [https://dhsprogram.com).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eNepal A, Dangol SK, Karki S, Shrestha N. 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Integr J Arts Humanit. 2023;4(4):62\u0026ndash;70.\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-womens-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmwh","sideBox":"Learn more about [BMC Women's Health](http://bmcwomenshealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bmwh/default.aspx","title":"BMC Women's Health","twitterHandle":"","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Contraceptive autonomy, Women Decision-making power, Women’s empowerment, Reproductive health, Family planning, Gender inequality, Nigeria, NDHS, SDG 5","lastPublishedDoi":"10.21203/rs.3.rs-8149264/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8149264/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eWomen\u0026rsquo;s autonomy in contraceptive decision-making is a key component of reproductive rights and gender equality, yet remains low in many low- and middle-income countries, including Nigeria. Understanding the current patterns and determinants of contraceptive autonomy is essential for accelerating progress toward Sustainable Development Goal (SDG) 5. This study examined the prevalence, regional disparities, and sociodemographic predictors of contraceptive decision-making autonomy among married women in Nigeria using the 2024 Nigeria Demographic and Health Survey (NDHS).\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eThis cross-sectional study analyzed data from 24,819 married women aged 15\u0026ndash;49 years from the 2024 NDHS. Contraceptive autonomy was defined as women independently making decisions regarding contraceptive use. Descriptive statistics summarized respondents\u0026rsquo; characteristics, and logistic regression models assessed crude and adjusted associations between predictors and autonomy. All analyses applied sampling weights to account for the NDHS complex survey design. Statistical significance was set at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eOverall, 37% of married women reported autonomy in contraceptive decision-making. Autonomy was highest in the South West (51%) and lowest in the North West (31%). In the adjusted model, older age increased autonomy, including women aged 35\u0026ndash;39 years (AOR\u0026thinsp;=\u0026thinsp;1.25; 95% CI: 1.03\u0026ndash;1.52; p\u0026thinsp;=\u0026thinsp;0.025) and 40\u0026ndash;44 years (AOR\u0026thinsp;=\u0026thinsp;1.31; 95% CI: 1.07\u0026ndash;1.60; p\u0026thinsp;=\u0026thinsp;0.009). Higher household wealth was associated with autonomy\u0026mdash;poorer (AOR\u0026thinsp;=\u0026thinsp;1.26; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and richer households (AOR\u0026thinsp;=\u0026thinsp;1.26; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) compared with the poorest. Employed women had higher odds of autonomy (AOR\u0026thinsp;=\u0026thinsp;1.49; 95% CI: 1.38\u0026ndash;1.60; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Regional disparities persisted: autonomy was higher among women in the North East (AOR\u0026thinsp;=\u0026thinsp;1.25; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), South East (AOR\u0026thinsp;=\u0026thinsp;1.41; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and South West (AOR\u0026thinsp;=\u0026thinsp;1.70; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), but lower in the North West (AOR\u0026thinsp;=\u0026thinsp;0.88; p\u0026thinsp;=\u0026thinsp;0.015) relative to North Central.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eContraceptive decision-making autonomy among married women in Nigeria remains low and varies substantially across demographic, socioeconomic, and regional contexts. Interventions aimed at enhancing women\u0026rsquo;s reproductive agency should prioritize education, economic empowerment, and culturally responsive strategies tailored to regions with persistent gender inequalities, particularly in the northern zones. Strengthening women\u0026rsquo;s autonomy is essential for improving reproductive health outcomes and advancing SDG 5 targets.\u003c/p\u003e","manuscriptTitle":"Contraceptive Decision-Making Autonomy Among Married Women in Nigeria: Regional Disparities and Determinants Using the 2024 NDHS","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-03 19:01:05","doi":"10.21203/rs.3.rs-8149264/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-02-19T23:42:50+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-30T23:33:46+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"80876661846542178156313561456290082542","date":"2026-01-27T09:56:00+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-26T23:03:15+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"22777029595031238932186420829922770139","date":"2026-01-26T22:58:25+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-19T14:50:02+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"94241091220825381670310920245398164952","date":"2025-12-17T08:10:49+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"291637612135835934725117561959647020926","date":"2025-12-15T07:28:25+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"26328596160796643479053013491488717267","date":"2025-12-15T00:44:05+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"93495432666014692527794330356176106515","date":"2025-12-08T07:43:32+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-12-02T03:03:13+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-11-21T06:45:23+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-11-20T07:00:57+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-11-20T06:58:59+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Women's Health","date":"2025-11-18T22:24:14+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-womens-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmwh","sideBox":"Learn more about [BMC Women's Health](http://bmcwomenshealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bmwh/default.aspx","title":"BMC Women's Health","twitterHandle":"","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"d529ff80-4d8b-4b53-b268-0b4448ae403f","owner":[],"postedDate":"December 3rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-22T02:28:58+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-03 19:01:05","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8149264","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8149264","identity":"rs-8149264","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}