TRENDS, DIFFERENTIALS AND DETERMINANTS OF MODERN CONTRACEPTIVE USE AMONG URBAN POOR WOMEN IN NIGERIA

TRENDS, DIFFERENTIALS AND DETERMINANTS OF MODERN CONTRACEPTIVE USE AMONG URBAN POOR WOMEN IN NIGERIA | 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 TRENDS, DIFFERENTIALS AND DETERMINANTS OF MODERN CONTRACEPTIVE USE AMONG URBAN POOR WOMEN IN NIGERIA Simon Osilama Izuagie, Olusina Samson Bamiwuye, Bola Lukman Solanke, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8679049/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract Background Understanding the trends and determinants of modern contraceptive use among urban-poor women is crucial for addressing disparities in family planning services. This study analyzed the prevalence of modern contraceptive use from 2011 to 2021, assessed socio-economic and demographic differentials, identified key drivers, and evaluated the interactive effects of these determinants. The aim was to provide evidence-based insights into the trends and determinants of contraceptive use among urban-poor women in Nigeria. Methods Using a cross-sectional design, secondary data from the Nigeria UNICEF Multiple Indicator Cluster Survey (MICS) for 2011, 2016-17, and 2021 were analyzed. The sample consisted of women in metropolitan areas within the poorest and poor wealth quintiles. Data analysis involved univariate, bivariate, and multivariate analyses. Results The prevalence of current contraceptive use declined from 14.6% in 2011 to 6.1% in 2016-17, then increased to 12.8% in 2021. Ever-use rose from 3.2% in 2016-17 to 7.1% in 2021. Age, marital status, childbirth history, and region significantly influenced ever-use, while age, education, and region of residence influenced current use across all survey periods. Ethnicity, media exposure significantly influences ever-use and current use, while spousal age difference influenced current use. The interactive effects of socio-demographic and intervening variables were strongly associated with contraceptive use, in 2016-17 and 2021 surveys. Conclusions The findings revealed dynamic trends and persistent socio-economic disparities in contraceptive use among urban-poor women. Despite some progress in recent years, the study highlights the need for targeted interventions addressing demographic and socio-economic determinants to improve access to family planning services. modern contraceptive urban poor trend differentials ever use of contraceptive current use Figures Figure 1 1. Introduction The global population continues to grow at a slower pace due to fertility declines, nevertheless, sub-Saharan African countries stand out with projected significant increases, influenced by population momentum and ongoing demographic transitions (Gu et al., 2021 ). Nigeria has the largest population in sub-Saharan Africa, with an annual growth rate of 2.6 percent, Nigeria’s population is expected to double in 26.9 years’ time. Contraceptive utilization is regarded as a key approach in managing population growth and prevention of maternal mortality. However, the weak health system in many developing countries is largely associated with rapid increase in the population of developing countries, leading to a steady high fertility rate which is a major hindrance to improvement in maternal and child health services (Requejo & Bhutta, 2015 ). It has been reported that contraceptive use effectively averts approximately 230 million annual global childbirths, thereby mitigating the occurrence of unintended pregnancies and subsequently leading to a decline in the overall fertility rate within a given nation (Ahmed et al., 2012 ). The 2018 Nigeria Demographic and Health Survey (NDHS) revealed a little disparity between the total fertility rate and the total intended fertility rate. The observed gap in question serves as a signal of the possible decrease in the number of births that may have been averted with the effective utilization of modern contraceptive techniques, as stated by the (National Population Commission (NPC) [Nigeria] and ICF, 2019 ). The findings also revealed that the high unwanted fertility and unmet contraceptive need expose women to life-threatening pregnancy risks and complications that could have been avoided using contraceptives. In 2019, Nigeria accounted for 20% of the global maternal mortality rate. Based on the report from the (World Health Organization, 2019 ), Nigeria witnessed a maternal mortality ratio that surpassed 800 maternal deaths per 100,000 live births (Olamijulo et al., 2022 ). Between the years 2005 and 2015, Nigeria reportedly saw a significant number of maternal deaths, with the total surpassing 600,000, alongside an estimated 900,000 instances of near-miss occurrences (World Health Organization, 2019 ). These near-miss incidences pertain to respondents who managed to survive problems arising from pregnancy or childbirth. The research conducted by (Girum & Wasie, 2017 ) has revealed a significant association between low contraceptive prevalence and increased maternal mortality ratio in a number of countries. The use of contraceptives has been shown to decrease maternal mortality rates, as well as the likelihood of conception and the subsequent risks and difficulties connected with pregnancy. According to the (World Health Organization, 2021 ), over 45% of all global abortions are categorized as unsafe, with a significant majority of 97% occurring in underdeveloped nations. Unsafe abortion is responsible for a range of maternal deaths, estimated to be between 4.7% and 13.2%. In Nigeria, as well as in numerous developing countries, abortion is generally prohibited with exceptions made in situations where it is deemed medically necessary to preserve the life of the mother. The recognition of the significance of family planning in achieving the Millennium Development Goals (MDGs) and the Sustainable Development Goals (SDGs) has been extensive. The primary reason for this is the substantial influence it exerts on maternal health and the consequent outcomes pertaining to pregnancy (Najafi-Sharjabad et al., 2013 ). A definition provided by the World Health Organisation (WHO), family planning is defined as a purposeful and premeditated decision undertaken by an respondent or a couple regarding the desired quantity of offspring and the optimal timing for their conception. ( Family Planning , n.d.) defined family planning as a comprehensive initiative aimed at managing the quantity and temporal distribution of offspring within a household, accomplished via the use of contraception or other forms of birth control. The implementation of family planning is a crucial measure used to mitigate the occurrence of unintended pregnancies and enhance favorable health consequences for women throughout their reproductive years, hence reducing the rates of mother and newborn mortality. Contraceptive use in the developing countries is grossly lower than that of the developed countries (Frank, 2023 ). The global satisfaction rate for family planning by modern technologies has remained relatively constant at approximately 77% between 2015 and 2020. However, it is noteworthy that the African region has had a modest increase of 3% in this regard. Based on the findings of the United Nations Department of Economic and Social Affairs Population Division (2019), it is evident that a significant proportion, specifically 58%, of women belonging to the reproductive age category across the globe need family planning services. In addition, within this group, almost 25% face the difficulty of an unmet demand for contraceptives. According to the survey conducted in 2013, about 15% of women in marital unions indicated that they use contraceptives. However, around 16% of married women reported a lack of access to contraception, indicating an unfulfilled need. In Nigeria, the rate of contraceptive use is approximately 12%, which shows that there is a relatively low adoption of contraceptive techniques. Furthermore, there exists a substantial unmet need for contraception, with unmarried sexually active women experiencing a 48% deficit and currently married women facing a 19% deficit (Fadeyibi et al., 2022 ; National Population Commission (NPC) [Nigeria] and ICF, 2014 , 2019 ). As a result, the fertility rates in Nigeria have remained consistently high due to the limited adoption of contraception methods inside the nation. At present, the fertility rate of the entire country is 5.3 children per woman (National Population Commission (NPC) [Nigeria] and ICF, 2019 ). The United Nations ( 2019 ) projects an estimated rise in the global population from 7.7 billion in 2019 to 9.7 billion by the year 2050. The planned expansion is projected to be largely powered by the African continent, with projections estimating that it will account for over 50% of the entire global population growth. In the meantime, there has been an apparent growth in the emigration of people from rural regions to urban centres, accompanied by a quick and significant modification of the physical environment inside urban areas. Urban population projections by the United Nations ( 2019 ) gave credence to the unbridled growth of urban population amidst a myriad of structural challenges, especially infrastructural decadence. Urban structural challenges are associated with mass exodus of people moving into the less-developed axis of urban settings. The reports, the population living in urban areas currently comprises over 50% of the global populace, amounting to over 4.2 billion respondents. Projections suggest that by the year 2041, this number would escalate to 6 billion people (United Nations, 2019 ). To increase the utilisation of contraceptives, marginalised women need access to modern contraceptives and good healthcare services. While reports from the 2018 NDHS revealed that improvements in contraceptive use are better among urban dwellers compared to the rural counterparts, the urban poor in Nigeria exhibit poor contraceptive use (6 per cent) compared to their urban counterparts (16 per cent) (National Population Commission (NPC) [Nigeria] and ICF, 2019 ). This imbalance results from the slum population's lack of access to affordable health services, misconceptions, and inadequate understanding of the available and accessible facilities for healthcare. Literature is replete with wide rural-urban gap in modern contraceptive use; however, disparities exist between modern contraceptive use and health indicators of women within the urban areas. This is attributable to the socio-economic differences between the women in urban areas. Therefore, it is important to analyze the underlying factors contributing to variations in modern contraceptive use, despite the implementation of many strategies and campaigns by governmental and international entities aimed at promoting the adoption of modern contraceptive methods. 2. Method and Materials The study used a cross-sectional research design. This study employed a cross-sectional design and collected data in three rounds. Secondary data from the Nigeria UNICEF Multiple Indicator Cluster Survey (UNICEF MICS) conducted in 2011, 2016-17, and 2021 were used. The sample included women living in metropolitan areas who fell into the lowest two wealth quintiles, specifically the poorest and poor categories. Study Area Nigeria, situated in Africa, stands as the nation with the highest population on the continent and ranks among the most densely populated nations globally. Current estimates indicate a population over 211 million respondents and a population growth rate of 2.6 percent (Population Reference Bureau, 2021). Furthermore, the total fertility rate for the country was recorded at 5.2 in the year 2020 (Population Reference Bureau, 2021). The distribution of population density exhibits spatial heterogeneity, with some regions characterized by high population concentrations and others characterized by low population concentrations (National Population Commission (NPC) [Nigeria] and ICF, 2019 ). The country exhibits suboptimal reproductive health outcomes, as shown by a maternal death ratio of 512 per 100,000 in 2018, a modern contraceptive prevalence rate of 12%, and an unmet demand for Family Planning estimated at 18.9 (National Population Commission (NPC) [Nigeria] and ICF, 2019 ). Data Source, Study Population, and Sample Size The research used secondary data. The primary data used in this study was obtained from the UNICEF Multiple Indicator Cluster Survey conducted in the years 2011, 2016-17, and 2021. The UNICEF Multiple Indicator Cluster Survey (MICS) offers standardized data on various indicators, such as reproductive and maternal health, child health, nutrition, development, protection from violence and exploitation, and living conditions. The main purpose of this survey is to evaluate key indicators that facilitate the collection of data by countries for the purposes of policymaking, programme execution, and national development objectives. Furthermore, it functions as a mechanism for monitoring advancements made towards the attainment of the SDGs and other internationally acknowledged commitments. The respondents responsible for collecting the data used a self-administered questionnaire as a means of obtaining information from the participants. The surveys include many thematic parts, such as maternity and child health, contraception, domestic violence, nutrition, malaria, HIV/AIDS, and women empowerment, among others. The researchers used a multi-stage, stratified cluster sampling technique to pick the sample. The main units of analysis consist of females aged 15 to 49 years residing in the 36 states of Nigeria, including the Federal Capital Territory (FCT), Abuja. The UNICEF Nigeria Multiple Indicator Cluster Surveys (MICS) included a total of 30,772, 32,237, and 38,806 women within the specified age bracket in the years 2011, 2016-17, and 2021 correspondingly. Following the application of inclusion and exclusion criteria, the weighted sample included 839, 769, and 967 women in the years 2011, 2016-17, and 2021, respectively. Consequently, the total weighted sample size consisted of 2,575 women classified as urban poor. Ethical Clearance The data used in this research was obtained from the UNICEF Nigeria Multiple Indicator Cluster Survey conducted in the years 2011, 2016-17, and 2021. In August 2021, the protocol for the UNICEF Nigeria Multiple Indicator Cluster Survey (MICS) was accepted by both the steering committee and a review committee composed of members from the Technical Committee. Each participant provided verbal consent and received comprehensive information regarding the voluntary nature of their participation, as well as the guarantee of confidentiality and anonymity regarding their personal information. The participants were provided with information regarding their entitlement to decline answering any or all of the questions, as well as to terminate the interview at any point. The UNICEF Nigeria MICS datasets may be accessed by the public via the official website https://mics.unicef.org/surveys . Additionally, I have been granted authorization to obtain and use these datasets. 3. Result Socio-Demographic Characteristics The analysis of respondents’ socio-demographic characteristics across three survey rounds (2011, 2016-17, and 2021) revealed significant trends. The mean age of respondents decreased from 29.3 years in 2011 to 28.5 years in subsequent rounds. Younger age groups (15–24 years) increased in proportion from 33.3% in 2011 to 39.9% in 2021, while older age groups (25–34 years) declined. Level of education further showed improvement, with the proportion of respondents without formal education decreasing from 54.8% in 2011 to 36.6% in 2021, while secondary education increased from 22.7% to 39.9%. However, higher education remained minimal, with less than 2% of respondents achieving this level. Also, marital status indicated a decline in marriage rates, with respondents married or cohabiting decreasing from 73.8% in 2011 to 57.5% in 2021, while those never married increased from 18.3% to 33.1%. Mean age at marriage rose from 16.5 years in 2011 to 17.1 years in 2021. Likewise, fertility patterns revealed a decline in childbirth rates, with 79.9% of respondents having given birth in 2011 compared to 66% in 2021. The average number of CEB decreased from 4.1 to 3.2 over the same period. Similarly, ethnicity shifted significantly, with the proportion of Hausa falling from 70% in 2016-17 to 48% in 2021, while percentage of Igbo and Yoruba respondents increased. Regional differences were also notable, with the Northern region’s share of respondents peaking at 92.7% in 2016-17 before declining to 66.4% in 2021, while the Southern region’s proportion rose to 33.6% in 2021. Table 1 Socio-Demographic Characteristics MICS 4 (2011) MICS 5 (2016-17) MICS 6 (2021) PERCENTAGE / MEAN (SD) Age 29.3 (± 9.4) 28.5 (± 9.8) 28.5 (± 9.8) Age group) 15–24 years 33.3 38.5 39.9 25–34 years 35.6 30.1 29.6 35–49 years 31.1 31.5 30.5 Level of education No formal education 54.8 61.4 36.6 Primary 21.0 15.1 22.2 Secondary 22.7 22.5 39.9 Higher 1.5 1.0 1.2 Marital Status Never married 18.3 26.8 33.1 Married/cohabiting 73.8 68.9 57.5 Formerly married 7.9 4.3 9.5 Age at marriage 16.5 (4.5) 16.6 (4.2) 17.1 (4.9) Ever given birth 79.9 71.2 66.4 Children ever born 4.1 (3.4) 3.8 (3.4) 3.2 (3.2) Husband’s age 43.0 (11.3) 45.6 (13.2) 44.1 (13.6) Ethnicity Hausa NA 69.8 47.7 Igbo NA 0.6 12.5 Yoruba NA 6.2 15.7 Other ethnic groups NA 23.4 24.1 Region North 75.7 92.7 66.4 South 24.3 7.3 33.6 N 845 774 974 Intervening variable Concerning the exposure to information from the media (newspaper, radio, and television), the data was unavailable in 2011, therefore, findings from 2016-17 and 2021 were only presented in this study. Regarding the exposure to newspapers, 16% of the respondents in 2016-17 were exposed to newspapers compared to 6% in 2021; 62% were exposed to radio in 2016-17 compared to 68% in 2021, and all the respondents in 2016-17 were exposed to television in 2016-17 compared to 21% in 2021. Likewise, findings showed that 21% were exposed to media in 2016-17 compared to 3% in 2021. In relation to the perception of domestic violence against wives, a composite variable was constructed by amalgamating five distinct views. The percentage who justify any form of wife beating slightly decreased from 12% in 2011 to 10% in 2021. In 2011, 35% of respondents believed that wife beating is justified when a woman goes out without informing her husband, decreasing to 20% in 2021. Additionally, 35% of respondents in 2011, 25% in 2016-17, and 23% of urban poor respondents in 2021 believed that wife beating is justified when a woman argues with her husband. Furthermore, the percentage of respondents justifying wife beating based on refusal to have sex with the spouse was approximately 37% in 2011 but declined to 27% in 2021. Lastly, from 19% in 2011, to 14% of urban poor respondents in 2021 justified wife beating if the woman burns food. Table 2 Percentage Distribution of Respondents by Intervening Variables MICS 4 (2011) MICS 5 (2016-17) MICS 6 (2021) PERCENTAGE / MEAN (SD) Exposed to newspaper N/A 15.5 5.6 Exposed to radio N/A 38.5 32.1 Exposed to television N/A 100.0 21.0 Exposure to all media N/A 21.0 3.3 Age difference between partners 11.8 (8.6) 13.1 (10.3) 11.4 (10.6) Wife beating justified. Not Justified Justified 88.5 11.5 90.6 9.4 90.4 9.6 Reasons for Wife-beating attitude justified : Goes out without telling her husband 34.9 27.0 19.8 Neglects children 33.7 28.5 22.5 Argues with husband 34.5 24.8 19.7 Refuse sex 36.8 30.6 27.0 Burns food 18.7 17.5 13.8 N 854 774 974 Level of Contraceptive Use (Current and Ever use) in Nigeria Results in Fig. 1 present the first part of objective 1 which was to examine the trends in the utilization of modern contraceptive from 2011–2021 among urban poor women residing in Nigeria. It can be deduced from Fig. 1 that 14.6 per cent of the respondents in 2011 were currently using contraceptives, compared to 6.1 per cent in 2016-17, and 12.8 per cent in 2021. This result shows a reduction in current contraceptive use from 2011–2021. Although there was a sharp decline between 2011 and 2016-17, the prevalence increased by 6.7 per cent by 2021. Furthermore, it can be deduced that the proportion of respondents who reported having used contraceptives as a means of pregnancy prevention was 3.2 percent in 2016, however this figure increased to 7.1 percent in 2021. The findings indicate an increase in the prevalence of contraceptive usage for the purpose of pregnancy prevention Socio-demographic Characteristics and Ever Use of Contraceptives among Urban Poor Respondents in Nigeria Table 3 displays the link between socio-demographic characteristics and the utilisation of contraceptives among participants belonging to Nigeria's urban poor population. Based on the results, it was seen that the mean age of the respondents included in the MICS 2016-17 survey was documented as 33.85 years, however in the MICS 2021 survey, a slight decrease to 33.10 years was noted. The statistical significance of the association between age and contraceptive usage was demonstrated by p-values of 0.01 and 0.001. Furthermore, a notable increase in the utilisation of contraceptives was found within the demographic of respondents aged 15–24 years. Specifically, the prevalence of contraceptive use rose from 0.67% in the MICS survey done during the period of 2016-17 to 1.84% in the subsequent MICS survey conducted in 2021. There was a significant increase observed in the utilisation of contraceptive methods among respondents who were married or cohabiting, as evidenced by the percentage rising from 4.76% during the MICS 2016-17 survey to 9.14% during the MICS 2021 study. Furthermore, a notable correlation has been observed between marital status and the utilisation of contraceptives, as evidenced by the data obtained from the Multiple Indicator Cluster Surveys (MICS) carried out during the periods of 2016-17 and 2021. There was a lack of substantial alteration observed in the mean age at marriage between the MICS 2016-17 survey and the subsequent MICS 2021 study. The time period encompassing MICS 2016–17 to MICS 2021 had a significant rise in contraceptive utilisation among those who had previously given birth, as indicated by the prevalence increasing from 4.34% to 9.95%. In contrast, a significant increase was observed in the percentage of participants who had never had delivery and were utilising contraceptive techniques, with the proportion rising from 0.62% to 2.07%. The examination of the p-value suggests a statistically significant association between the age at which respondents marry and their utilisation of contraceptives. Furthermore, the findings indicate a marginal increase in the mean number of children ever born (CEB) from 4.54 to 4.78 between the MICS surveys conducted in 2016-17 and 2021. This observed trend can be attributed to the significant proportion of respondents who reported taking contraceptives, suggesting a positive correlation between having more children and the likelihood of utilising contraceptive methods. Furthermore, it is noteworthy that the average age of the husbands of the participants exhibited a consistent level of stability throughout the duration spanning from the MICS survey conducted in 2016-17 to the most recent iteration of the survey in 2021. Nevertheless, there was no significant statistical correlation found between the age of the husband and the utilisation of contraceptive methods. There were notable variations in contraceptive usage across several ethnic groups.. The Igbo ethnic group had a decrease in contraceptive use from 30.46% to 16.65%. Hausa and Yoruba ethnic groups had a slight increase in contraceptive use, while other ethnic groups had a small increase as well. Likewise, ethnicity and ever use of contraceptives had statistical relationship. There were significant changes in contraceptive use based on the region between MICS 2016-17 and MICS 2021. In the Northern region, there was a decrease in contraceptive use from 68.35 per cent to 52.71 per cent while in the Southern region, there was an increase from 31.65 per cent to 47.29 per cent. Yet, northern region and ever use of contraceptives were associated. Table 3 Socio-demographic Characteristics and Ever Use of Contraceptives among Urban Poor Respondents in Nigeria MICS 2016-17 MICS 2021 NO Freq (per cent) YES Freq (per cent) NO Freq (per cent) YES Freq (per cent) Age Mean (SD) 28.44 (9.9) 33.85 (8.6) 27.35 (9.8) 33.10 (7.0) p = 0.01* p = 0.00* Age group χ 2 = 6.89 p = 0.03* χ 2 = 32.1 p < 0.01** 15–24 years 217 (99.33) 1 (0.67) 425 (98.16) 8 (1.84) 25–34 years 151 (93.50) 10 (6.50) 254 (90.48) 26 (9.52) 35–49 years 165 (96.61) 6 (3.39) 264 (87.54) 37 (12.46) Level of education χ 2 = 5.92 p = 0.12 χ 2 = 5.25 p = 0.15 No formal education 343 (98.51) 5 (1.49) 367 (95.00) 19 (5.00) Primary 69 (88.63) 9 (11.37) 206 (92.25) 17 (7.75) Secondary 117 (97.70) 3 (2.30) 358 (90.95) 36 (9.05) Higher 5 (82.97) 1 (17.03) 11 (100.00) 0 (0.00) Marital Status χ 2 = 11.38 p < 0.01** χ 2 = 19.00 p < 0.01** Never married 153 (100.00) 0 (0.00) 348 (97.89) 7 (2.11) Married/cohabiting 355 (95.24) 18 (4.76) 513 (90.86) 51 (9.14) Formerly married 25 (100.00) 0 (0.00) 81 (86.05) 13 (13.95) Age at marriage Mean (SD) 16.60 (4.49) 17.25 (3.70) 16.51 (4.54) 17.25 (4.33) p = 0.49 p = 0.23 Ever given birth χ 2 = 5.15 p = 0.02** χ 2 = 20.81 p < 0.01** No 165 (99.38) 1 (0.62) 356 (97.93) 8 (2.07) Yes 368 (95.66) 17 (4.34) 586 (90.05) 65 (9.95) Children ever born Mean (SD) 3.73 (3.45) 4.54 (2.93) 3.01 (3.19) 4.78 (2.89) p = 0.26 p < 0.01** Husband’s age Mean (SD) 45.74 (12.97) 43.39 (8.66) 44.02 (13.68) 43.33 (11.26) p = 0.39 p = 0.72 Ethnicity χ 2 = 23.81 p < 0.01** χ 2 = 16.36 p < 0.01** Hausa 384 (97.45) 10 (2.55) 485 (95.16) 25 (4.84) Igbo 2 (69.54) 1 (30.46) 92 (83.35) 18 (16.65) Yoruba 23 (82.73) 5 (17.27) 134 (88.06) 18 (11.94) Other ethnic groups 124 (98.34) 2 (1.66) 232 (95.40) 11 (4.60) Region χ 2 = 9.26 p < 0.01** χ 2 = 3.40 p = 0.06 North 506 (94.93) 12 (68.35) 660 (69.96) 38 (52.71) South 27 (5.07) 6 (31.65) 283 (30.04) 34 (47.29) ** indicates p < 0.01 * indicates p < 0.05 OR – Odds Ratio Socio-demographic Characteristics and the Current Use of Contraceptives among Urban Poor Respondents in Nigeria Table 4 below focuses on the socio-demographic characteristics and the current use of contraceptives among urban poor women in Nigeria. The table presents data from three different time periods: MICS 2011, MICS 2016-17, and MICS 2021. The table revealed a significant relationship between age, age group and the current use of contraceptives. In MICS 2011, the highest proportion of contraceptive use was observed among women aged 35–49 years (19.09%). In MICS 2016-17, the highest proportion shifted to women aged 25–34 years (9.83%). In MICS 2021, the highest proportion was again observed among women aged 25–34 years (20.60%). The increasing proportion of contraceptive use among women aged 25–34 years in MICS 2016-17 and MICS 2021 suggests that this age group may be more proactive in using contraceptives. This could be attributed to increased awareness and access to family planning services among this demographic. Concerning the level of education, the highest proportion of contraceptive use in the MICS 2011, was among women with higher education (45.51%). In MICS 2016-17, it shifted to women with secondary education (9.43%). In MICS 2021, the highest proportion was again observed among women with secondary education (15.30%). The p-values for education level indicate a statistical association with use of contraceptive, except for MICS 2021 where p = 0.22, indicating a weaker association, highlighting the value of education in encouraging contraceptive use. It implies that educated women are more likely to be familiar with and have access to contraceptive methods. Regarding marital status, the highest proportion of contraceptive use in MICS 2011 was among formerly married women (23.54%). In MICS 2016-17, it shifted to married/cohabiting women (8.48%). In MICS 2021, the highest proportion was again observed among married/cohabiting women (17.20%). The decreasing p-values across the years (0.58, 0.01, 0.00) suggest a significant change in contraceptive use across different marital statuses over time. The increasing proportion of contraceptive use among married/cohabiting women in MICS 2016-17 and MICS 2021 indicates a positive shift towards family planning among this group. This could be due to efforts in promoting spousal communication, joint decision-making, and the availability of diverse contraceptive options There was a significant relationship between age at marriage and the current use of contraceptives in MICS 2011 and 2021. Concerning childbearing status, the highest proportion of contraceptive use in MICS 2011 was among women who had given birth (15.14%). In MICS 2016-17, it shifted to women who had not given birth (8.43%). In MICS 2021, the highest proportion was again observed among women who had given birth (16.85%). The p-values for ever giving birth indicate a significant association with contraceptive use, except for MICS 2011 where p = 0.72, indicating no significant association. The higher proportion of contraceptive use among women who have given birth in MICS 2011 and MICS 2021 highlights the importance of postpartum contraception. It suggests that efforts to promote and provide contraceptives to women immediately after childbirth are gaining recognition and leading to increased usage. Regarding ethnicity and region, the p-values indicate the statistical influence on contraceptive use. Ethnicity data is missing for MICS 2011, but in MICS 2016-17 and 2021, certain ethnic groups (Hausa, Igbo, Yoruba, and other ethnic groups) show significant associations with contraceptive use. Similarly, the two regions (North and South) also show significant associations with contraceptive use across the years. Table 4 Socio-demographic Characteristics and the Current Use of Contraceptives among Urban Poor Respondents in Nigeria MICS 2011 MICS 2016-17 MICS 2021 NO Freq (%) YES Freq (%) NO Freq (%) YES Freq (%) NO Freq (%) YES Freq (%) Age [mean (SD)] 29.28 (9.77) 31.58 (9.01) 28.46 (10.27) 32.42 (7.85) 27.48 (9.97) 32.28 (7.79) p = 0.03* p = 0.01** p < 0.01** Age group χ 2 = 6.22 p = 0.04* χ 2 = 11.30 p < 0.01** χ 2 = 38.34 p < 0.01** 15–24 years 230 (88.88) 29 (11.12) 204 (97.41) 5 (2.59) 400 (94.11) 25 (5.89) 25–34 years 224 (86.15) 36 (13.85) 131 (90.17) 14 (9.83) 222 (79.40) 58 (20.60) 35–49 years 198 (80.91) 47 (19.09) 160 (92.73) 12 (7.27) 259 (84.66) 47 (15.34) Level of education χ 2 = 39.19 p < 0.01** χ 2 = 21.55 p < 0.01** χ 2 = 4.37 p = 0.22 No education 373 (91.34) 35 (8.66) 305 (96.83) 10 (3.17) 332 (90.88) 33 (9.12) Primary 131 (84.43) 24 (15.57) 73 (87.43) 10 (12.57) 191 (86.11) 31 (13.89) Secondary 141 (75.32) 46 (24.68) 113 (90.57) 12 (9.43) 348 (84.70) 63 (15.30) Higher 7 (54.49) 6 (45.51) 4 (100.00) 0 (0.00) 11 (80..17) 3 (19.83) Marital Status χ 2 = 1.11 p = 0.58 χ 2 = 8.50 p = 0.01** χ 2 = 33.04 p < 0.01** Never married 131 (85.07) 23 (14.93) 157 (98.17) 3 (1.83) 343 (93.63) 23 (6.37) Married/cohabiting 471 (86.55) 73 (13.45) 314 (91.52) 29 (8.48) 447 (82.80) 93 (17.20) Formerly married 49 (76.46) 15 (23.54) 25 (98.98) 1 (1.02) 91 (87.20) 13 (12.80) Age at marriage (mean) 16.38 (4.44) 18.44 (4.56) 16.79 (4.67) 17.38 (4.24) 16.49 (4.47) 18.40 (4.93) p < 0.01** p = 0.44 p < 0.01** Ever given birth χ 2 = 0.13 p = 0.72 χ 2 = 11.58 p < 0.01** χ 2 = 39.71 p < 0.01** No 138 (87.46) 20 (12.54) 166 (98.87) 2 (1.13) 346 (94.25) 21 (5.75) Yes 514 (84.86) 91 (15.14) 330 (91.57) 30 (8.43) 535 (83.15) 108 (16.85) Children ever born (mean) 4.05 (3.41) 4.09 (3.17) 3.69 (3.50) 4.58 (2.63) 3.01 (3.26) 4.43 (2.82) p = 0.92 p = 0.08 p < 0.01** Husband’s age (mean) 43.17 (12.42) 45.10 (11.09) 46.22 (12.69) 43.25 (11.85) 44.65 (13.69) 44.53 (11.78) p = 0.23 p = 0.16 p = 0.94 Ethnicity NA NA χ 2 = 45.02 p < 0.01** χ 2 = 23.32 p < 0.01** Hausa NA NA 359 (96.46) 13 (3.54) 433 (92.17) 37 (7.83) Igbo NA NA 2 (65.76) 1 (34.24) 100 (75.33) 33 (24.67) Yoruba NA NA 26 (76.41) 8 (23.59) 138 (83.26) 28 (16.74) Other ethnic groups NA NA 108 (91.72) 10 (8.28) 210 (86.66) 32 (13.34) Region χ 2 = 40.04 p < 0.01** χ 2 = 26.98 p = 0.00* χ 2 = 13.71 p < 0.01** North 514 (78.85) 51 (46.31) 465 (93.90) 22 (69.39) 594 (67.39) 63 (48.72) South 138 (21.15) 60 (53.69) 30 (6.10) 10 (30.61) 287 (32.61) 66 (51.28) N 652 111 496 32 881 130 ** indicates p < 0.01 * indicates p < 0.05 OR – Odds Ratio Model 1: Binary Logistic Regression Model of Respondents’ Ever Use and Current Use of Contraceptives by Socio-Demographic Factors Table 5 shows that age significantly predict ever use of contraceptives. In MICS 2016-17, a one-year increase in age was associated with a 19% higher likelihood of ever using contraceptives (OR = 1.19, p < 0.04, 95% CI: 1.01–1.39). However, in MICS 2021, this trend reversed, showing a slight decrease in the odds (OR = 0.88, p < 0.04, 95% CI: 0.79–0.99). This suggests that younger respondents in 2021 may have faced different access or attitudinal barriers compared to the earlier period. However, for current use, age was not a significant predictor in either dataset (MICS 2016-17: OR = 0.96, p = 0.55; MICS 2021: OR = 0.96, p = 0.43), indicating that factors beyond age may be influencing recent contraceptive use patterns. In same vein, Education played a crucial role in predicting both ever use and current use of contraceptives. In MICS 2016-17, respondents with higher education were significantly more likely to have ever used contraceptives (OR = 9.35, p = 0.05, 95% CI: 0.98–89.29), while those with primary education had significantly lower odds of ever use (OR = 2.36, p = .35). By 2021, the impact of education remained strong, with those having secondary (OR = 3.88, p = 0.01) and primary education (OR = 3.06, p = 0.01) showing increased odds of ever use. For current contraceptive use, MICS 2016-17 showed that respondents with secondary and higher education were significantly more likely to use contraceptives (Secondary: OR = 8.12, p = 0.01, 95% CI: 2.86–23.04). However, in MICS 2021, this effect reduced, with no statistically significant increase in odds among higher-educated groups. Ethnicity also influenced contraceptive use patterns. In MICS 2016-17, Igbo respondents were over four times more likely to have ever used contraceptives compared to Hausa respondents (OR = 4.56, p = 0.06, 95% CI: 0.93–22.21), while Yoruba respondents had lower odds (OR = 0.56, p = 0.45). By 2021, these differences remained but were no longer significant, suggesting possible convergence in contraceptive uses across ethnic groups. While for current use, Igbo respondents had higher odds in MICS 2021 (OR = 8.38, p = .01, 95% CI: 2.68–26.17), indicating a sustained ethnic disparity in access or preferences for contraception. Table 5 Binary Logistic Regression Model of Respondents’ Ever Use and Current Use by the Interactive Effect of Socio-Demographic and Intervening Variables Age Group # Wife Beating Ever Use (MICS 2016-17) Ever Use (MICS 2021) Current Use (MICS 2016-17) Current Use (MICS 2021) OR p-value 95% CI OR p-value 95% CI OR p-value 95% CI OR p-value 95% CI Age 1.19 0.04 1.01–1.39 0.88 0.04 0.79–0.99 0.96 0.55 0.85–1.09 0.96 0.43 0.88–1.06 Age Group 15–24 years (Ref) - - - - - - - - - - - - 25–34 years 1.07 0.95 0.13–8.63 29.77 0.01 2.02–439.16 4.79 0.06 0.96–23.94 1.23 0.72 0.40–3.79 35–49 years 0.11 0.23 0.00–4.12 158.36 0 6.09–4119.28 5.22 0.23 0.36–76.31 1.19 0.85 0.20–7.21 Education No education (Ref) - - - - - - - - - - - - Primary 8.18 0.01 2.63–25.48 3.06 0.01 1.25–7.46 3.68 0.01 1.41–9.64 1.51 0.23 0.77–2.98 Secondary 2.36 0.35 0.40–14.01 3.88 0.01 1.45–10.41 8.12 0.01 2.86–23.04 1.79 0.14 0.83–3.85 Higher 9.35 0.05 0.98–89.29 1.00 - - 1.00 - - 2.10 0.48 0.27–16.34 Age at First Marriage 0.97 0.64 0.85–1.10 1.02 0.65 0.93–1.11 1.00 0.94 0.91–1.11 1.08 0.01 1.02–1.15 Children Ever Born 0.96 0.75 0.75–1.23 1.11 0.23 0.93–1.34 1.00 0.99 0.82–1.22 1.14 0.07 0.99–1.31 Husband’s Age 0.96 0.1 0.92–1.01 0.98 0.24 0.95–1.01 0.98 0.31 0.95–1.02 1.01 0.42 0.98–1.04 Ethnic Group Hausa (Ref) - - - - - - - - - - - - Igbo 23.32 0.1 0.58–939.45 2.18 0.33 0.46–10.41 0.98 0.99 0.03–34.29 8.38 0.01 2.68–26.17 Yoruba 4.56 0.06 0.93–22.21 1.61 0.34 0.59–4.37 4.89 0.02 1.36–17.58 2.26 0.05 0.99–5.20 Other Group 0.56 0.45 0.13–2.51 0.78 0.6 0.32–1.94 1.90 0.18 0.74–4.85 1.87 0.05 0.99–3.54 Notes: OR : Odds Ratio p < 0.01 ( ), p < 0.05 (*) RC : Reference Category Model 2: Binary Logistic Regression Model of Respondents’ Ever and Current Use of Contraceptives by the Combination of Socio-Demographic and Intervening Variables Table 6 reveal maternal age’s association with ever use of contraceptives in both MICS 2016-17 and MICS 2021 though with different trends. In MICS 2016-17, a one-year increase in age increased the likelihood of ever using contraceptives by 21% (OR = 1.21, p < 0.05). However, in MICS 2021, older age was associated with reduced odds of ever using contraceptives (OR = 0.88, p < 0.05). For current use, age was not related in either survey, indicating that age alone does not determine continued contraceptive use. Education consistently influenced both ever and current use. Respondents with higher education had significantly higher odds of ever using contraceptives in MICS 2016-17 (OR = 9.00, p < 0.01), though this effect was slightly weaker in 2021 (OR = 3.12, p < 0.05). For current use, education remained important in MICS 2016-17, with respondents having secondary (OR = 9.00, p < 0.01) or primary education (OR = 3.96, p 0.05). Neither age at first marriage nor children ever born significantly influenced ever use in either dataset (p > 0.05). However, for current use, age at first marriage became significant in MICS 2021, with a one-year increase associated with a 9% higher likelihood of contraceptive use (OR = 1.09, p < 0.05). By ethnicity. in MICS 2016-17, Igbo respondents were significantly more likely to have ever used contraceptives (OR = 24.30, p = 0.08) compared to the Hausa. However, this effect was not significant in MICS 2021, indicating a influence on contraceptive uses across ethnic groups over time. For current use, Igbo and Yoruba respondents had significantly higher odds in MICS 2021 (Igbo: OR = 9.00, p < 0.01; Yoruba: OR = 2.40, p 0.05). However, for current use, MICS 2021 showed a strong positive association (OR = 3.42), though it was not significant. Attitudes toward wife beating were not consistently significant for either ever or current use, though the odds ratios suggest that respondents who justified wife beating were more likely to use contraception, especially in MICS 2021 (OR = 2.05, p = 0.12). This finding may indicate that attitudes toward gender roles interact with contraceptive uses in complex ways. Table 6 Binary Logistic Regression Model of Respondents’ Ever Use and Current Use of Contraceptives by Socio-Demographic and Intervening Variables Variable Ever Use (MICS 2016-17) Ever Use (MICS 2021) Current Use (MICS 2016-17) Current Use (MICS 2021) OR p-value 95% CI OR p-value 95% CI OR p-value 95% CI OR p-value 95% CI Age 1.21 0.03* 1.02–1.43 0.88 0.03* 0.78–0.99 0.95 0.39 0.83–1.08 0.96 0.37 0.87–1.05 Age Group 15–24 years (R) 25–34 years 0.83 0.87 0.10–7.07 29.82 0.01* 2.02–441.23 5.52 0.04* 1.08–28.23 1.28 0.67 0.41–3.96 35–49 years 0.05 0.13 0.00–2.38 165.76 0.01** 6.26–4388.31 7.62 0.14 0.50–116.34 1.21 0.84 0.19–7.58 Education No education (R) Primary 9.00 0.00** 2.78–29.15 3.12 0.01* 1.27–7.67 3.96 0.01* 1.49–10.54 1.54 0.21 0.78–3.05 Secondary 2.74 0.28 0.44–16.99 3.92 0.01* 1.45–10.63 9.00 0.01** 3.01–26.93 1.88 0.11 0.86–4.08 Higher 7.66 0.09 0.70–83.51 1.00 1.00 1.36 0.81 0.12–15.14 Ethnic Group Hausa (R) Igbo 24.30 0.08 0.66–897.58 2.31 0.29 0.48–11.12 0.98 0.99 0.03–33.77 9.00 0.01** 2.86–28.36 Yoruba 4.10 0.09 0.81–20.93 1.72 0.29 0.62–4.75 4.83 0.02* 1.31–17.85 2.40 0.04* 1.03–5.61 Other Ethnic Group 0.64 0.56 0.14–2.88 0.77 0.57 0.31–1.93 2.06 0.14 0.79–5.33 2.01 0.03* 1.06–3.83 Exposed to Media Not exposed (R) Exposed 1.78 0.31 0.58–5.43 1.00 1.91 0.18 0.74–4.89 3.42 0.34 0.27–43.74 Wife Beating Attitude Not Justified (R) Justified 3.11 0.11 0.78–12.46 1.82 0.24 0.67–4.94 0.33 0.21 0.06–1.88 2.05 0.12 0.84–5.01 Notes: OR : Odds Ratio p < 0.01 ( ), p < 0.05 (*) R : Reference Category Model 3: Binary Logistic Regression Model of Respondents’ Ever Use and Current Use by the Interactive Effect of Socio-Demographic and Intervening Variables The findings from Table 7 reveal the binary logistic regression models indicate a significant interaction effect between respondents' age group and their attitudes toward wife beating on both ever use and current use of the examined service. It was obvious that, among respondents aged 15–24 years who justified wife beating, the odds of ever use were significantly higher in both MICS 2016-17 (OR = 7.05, p < .01, 95% CI: 1.69–29.30) and MICS 2021 (OR = 8.65, p < .01, 95% CI: 3.56–21.02). This suggests that younger respondents who support wife beating may have different behavioural patterns compared to their counterpart who do not justify such attitudes. Similarly, for current use, respondents aged 25–34 years who justified wife beating had notably higher odds in MICS 2016-17 (OR = 162.16, p < .02, 95% CI: 2.32–11329.9), highlighting a stark contrast to other age groups. However, in MICS 2021, the effect size decreased (OR = 7.04, p < .17, 95% CI: 0.42–117.38), indicating shifts in behavioural tendencies. Level of education also played a critical role in shaping both ever use and current use. Respondents with no formal education who justified wife beating had lower odds of ever use in MICS 2016-17 (OR = 1.00, p = .20, 95% CI: 0.66–7.14) but significantly higher odds in MICS 2021 (OR = 2.71, p = .38, 95% CI: 0.29–25.53). For current use, respondents with primary education who justified wife beating had significantly higher odds in MICS 2016-17 (OR = 5.73, p = .01, 95% CI: 2.53–12.97) but saw a relative decrease in MICS 2021 (OR = 2.13, p = .01, 95% CI: 1.16–3.89). Conclusively, these findings reveal the association between socio-demographic factors in shaping behavioural outcomes. Table 7 Binary Logistic Regression Model of Respondents’ Ever Use and Current Use by the Interactive Effect of Socio-Demographic and Intervening Variables Age Group # Wife Beating Ever Use (MICS 2016-17) Ever Use (MICS 2021) Current Use (MICS 2016-17) Current Use (MICS 2021) OR p-value 95% CI OR p-value 95% CI OR p-value 95% CI OR p-value 95% CI 15–24 years # justified 7.05 0.01** 1.69–29.30 8.65 0.00** 3.56–21.02 39.49 0.01* 2.67–584.90 5.09 0.16 0.53–48.53 25–34 years # not justified 75.34 0.01** 4.57–1240.7 23.95 0.01** 2.39–239.73 9.56 0.01** 3.57–25.56 8.04 0.01** 4.21–15.33 25–34 years # justified 7.06 0.01** 1.61–31.01 13.76 0.00** 5.58–33.92 162.16 0.02* 2.32–11329.9 7.04 0.17 0.42–117.38 35–49 years # not justified 50.22 0.00** 3.43–736.00 12.28 0.06 0.94–159.89 8.81 0.00** 3.14–24.75 6.26 0.01** 3.11–12.60 35–49 years # justified - - - - - - 65.77 0.02* 2.12–2041.14 21.89 0.01* 1.68–284.35 Education # Wife Beating No education # justified 1 0.20 0.66–7.14 2.71 0.38 0.29–25.53 1 0.01** 2.53–12.97 1.45 0.76 0.13–16.12 Primary # not justified 2.17 0.04* 1.06–10.58 2.67 0.01** 1.29–5.54 5.73 0.61 0.01–11.84 2.13 0.01* 1.16–3.89 Primary # justified 1 0.20 0.46–40.08 1 0.01** 2.60–10.15 0.42 0.01** 3.29–18.23 0.47 0.63 0.02–10.55 Secondary # not justified 3.35 0.04* 1.06–10.58 5.14 0.01** 2.60–10.15 7.75 0.01** 3.29–18.23 3.54 0.01** 2.02–6.18 Secondary # justified 1 - - 1 - - 1 - - 1.68 0.52 0.35–7.99 Higher # not justified 4.27 - - 1 - - 1 - - 1 - - Higher # justified 1 - - 1 - - 1 - - 1 - - Notes: OR: Odds Ratio p < 0.01 (), p < 0.05 (*) Discussion of findings This study examined trends and determinants of ever and current use of modern contraceptives among the urban poor women in Nigeria. The study extracted data from three series of data collection points to tease out information on the changes in use of modern contraception over the course of two decades, as well as the drivers of these changes. Salient findings were derived from this study. The low prevalence of contraceptive use among the urban poor women indicated a slight decrease of current use of contraceptives between 2011 and 2017, however, there was an increase in 2021. Although was a decline in current use of contraceptive use between 2011 and 2017, however, there was a surge in contraceptive prevalence in 2021 which is almost similar to the contraceptive prevalence rate report in the 2018 Nigeria Demographic and Health Survey. (National Population Commission (NPC) [Nigeria] and ICF, 2019 ). The plausible explanation for the decline and further resurgence could be a lag in family planning intervention period across the time frame. Results of previous studies align with this (Alirol et al., 2011 ; Fadeyibi et al., 2022 ). Policies on promoting family planning should be strengthened, especially among the urban poor women in Nigeria. Similarly, the results showed that ever use of contraceptives among urban poor women recorded a significant in increase. This is an indication of increase in those who ever used modern contraceptive among the urban poon in Niger. Women who reported to have ever used modern contraceptive were expected to have higher prevalent because the population of urban poor women would increase over time. However, the prevalence of ever use of modern contraceptives among urban poor women is surprising as it is lower than current use. Previous studies have reported higher prevalence of modern contraceptives, though in the general urban population (Dambo et al., 2017 ). This finding is in contrast with previous studies, although ever use of modern contraceptives is expected to be lower than current use if family planning programmes and interventions are effective. Policies should be made to promote the use of contraceptives, especially in urban poor contexts. At the bivariate analysis, the study showed age of women was significantly related to ever use of modern contraceptives. The use of modern contraceptives increases as age increases. In addition, age was also significantly related to current use of modern contraception throughout the three rounds of data points. At multivariable analysis, age of women was also significantly related to ever of contraceptives with older women more likely to use, even when intervening variables were controlled for. This is reasonable because age depicts lifetime exposure to using contraception. Previous studies have established that who have almost completed their childbearing adopt family planning to prevent unwanted pregnancy (Dambo et al., 2017 ; Tekelab et al., 2015 ). Policies should target younger women more to reduce unwanted pregnancies. The result also showed that education was significantly related to ever use of modern contraceptives. In like manner, level of education was significantly related to current use of modern contraception in 2016 and 2021 rounds of data sets. At multivariate level, women with primary and secondary education had higher odds of ever use of modern contraceptives even when other control variables were factored into the model. This result is in agreement with prior studies (Ba et al., 2019 ; Taingson et al., 2017 ). The plausible reason for this is that advancement in education brings forth knowledge of family planning and opportunities cost of having many children decreases. Educated women, even the urban poor plan their childbearing. Policies should target both the educated and uneducated women to increase family planning demand generation. Marital status was also associated with ever and current use of modern contraceptives. Married women were more likely to ever use and currently using modern contraceptives. These results are in consonance with prior research which argued that married women planned their childbearing with a view to achieving their desired family size (Andreoli et al., 2021 ; Najimudeen, 2020 ). The plausible reasons are: marriage exposes women to frequent coitus interruptus and family planning awareness during antenatal or postnatal health visit. Policies should target married women for family planning demand generation during maternal and child healthcare programmes. Ethnicity was significantly related to ever and current use of modern contraceptives. The Yoruba were more likely to use modern contraceptive compared to other ethnic groups. This result echoes what was reported in the 2018 Nigeria Demographic and Health Survey. In the survey, the Yoruba ethnic group had higher modern contraceptive prevalence rate. Other ethnic groups, especially the Hausa/ Fulani should be targeted for family planning demand generation. Similarly, the Northern region had lower ever use of modern contraceptives compared to the South while all the regions had influence on current use of modern contraceptives. Previous studies have reported regional variations in modern contraception, with the Northern part having lower rate (National Population Commission (NPC) [Nigeria] and ICF, 2019 ; Obasohan, 2015 ). The plausible reasons find meaning in the culture of early childbearing and polygynous marriage. Interventions should aim at promoting family planning in the Northern region. Having ever given birth was significantly related to current use of modern contraceptives. The result is in tandem with prior studies which established that women who had given birth were more informed about the use of modern contraceptives compared to those who have not (Apanga & Adam, 2015; Hanley et al., 2017 ). Exposure to radio was significantly related to ever and current use of modern contraception. Previous studies have shown that radio had wider reach than other mass sources, especially among the urban poor who may lack access to television and other sophisticated mass media (Dambo et al., 2017 ; Ezire et al., 2014 ). More radio jingles should be promoted to increase family planning among the urban poor women. Moreover, the results showed the interactive effect of age of women and attitude toward wife beating were significantly related to ever and current use of modern contraceptive. This result is in contrast with previous studies (Abate & Tareke, 2019 ; Bamiwuye, 2013 ; Ridlo et al., 2020 ). Women who encourage wife beating are less more likely to adopt contraception regardless of age. This is unexpected because such women who approve of wife beating lack empowerment and independent decision-making in the household. It might also be that women who approve of wife beating lacked safe sex negotiation and as such, use contraception to prevent unwanted pregnancy. The result also revealed interactive effect of education and wife beating on ever and current use of contraceptives. The result findings showed that women who approved of wife beating are more likely to adopt modern contraception is contrary to previous studies which emphasized that wife beating is a manifestation of lack of women empowerment and more prominent among less-educated women (Danaan, 2018 ; Fasina & Oduaran, 2019 ). However, contraceptives were more utilised among women who approved of wife beating regardless of level of education. The possible reason could be that some women are dominated in marital union and lack respondent agency regardless of their level of education. The implication of this is that wife beating, and the level of education did not limit the use of contraceptives. Conclusion This study examines the trends and determinants of modern contraceptive use among urban poor women in Nigeria, highlighting disparities in access to family planning services. Using data from the Nigeria Multiple Indicator Cluster Surveys (MICS) for 2011, 2016-17, and 2021, the study analysed changes in contraceptive prevalence and identified key socio-economic and demographic factors influencing use. Findings revealed a decline in contraceptive use between 2011 and 2016-17, followed by a rise in 2021. Ever-use of contraceptives also increased over time. Age, education, ethnicity, geographic location, and media exposure played significant roles in shaping contraceptive behaviours. The study underscores the interactive effects of these determinants, emphasizing the need for targeted interventions to address persistent inequalities and improve family planning access among urban poor women. Declarations Institutional Review Board Statement The study was based on the analysis of openly available data. Thus, ethical approval was not necessary. Clinical Trial Not Applicable. Conflicts of Interest: The authors declare no conflict of interest. Ethical Approval: The data used in this research was obtained from the UNICEF Nigeria Multiple Indicator Cluster Survey conducted in the years 2011, 2016-17, and 2021. In August 2021, the protocol for the UNICEF Nigeria Multiple Indicator Cluster Survey (MICS) was accepted by both the steering committee and a review committee composed of members from the Technical Committee. Consent to Participate: Each participant provided verbal consent and received comprehensive information regarding the voluntary nature of their participation, as well as the guarantee of confidentiality and anonymity regarding their personal information. The participants were provided with information regarding their entitlement to decline answering any or all of the questions, as well as to terminate the interview at any point. The UNICEF Nigeria MICS datasets may be accessed by the public via the official website https://mics.unicef.org/surveys . Additionally, authorization was obtained to use these datasets. Consent for publication: Since this analysis relies solely on secondary anonymised MICS datasets, no further consent to publish was necessary. Funding: This research received no external funding. Author Contribution S. O. I., O. S. B and B.L.S conceptualized and designed the study, developed the methodology and models. S. O. I. implemented the formal analysis and interpreted with support from T. E. O. Also, O. S. B, B.L.S. and T. E. O. reviewed the analysis and interpretation of the results while S. O. I and T. E. O. drafted, reviewed and edited the manuscript. All authors have read and agreed to publish this version of the manuscript. Acknowledgement The authors are grateful to NBS and UNICEF, Nigeria for granting the authors the request to use the Multiple Indicator Cluster Survey (MICS) Data. Data Availability The data can be accessed here: [https://mics.unicef.org/](https:/mics.unicef.org)Access via UNICEF is granted through a simple sign-in process, where users provide basic identification, professional details, and a summary of their intended research activities. Additionally, I have been granted authorization to obtain and use these datasets. References Abate MG, Tareke AA. (2019). Individual and community level associates of contraceptive use in Ethiopia: a multilevel mixed effects analysis . 1–12. Ahmed S, Li Q, Liu L, Tsui AO, Bill F, Foundation MG. Maternal deaths averted by contraceptive use: an analysis of 172 countries. Lancet. 2012;380(9837):111–25. https://doi.org/10.1016/S0140-6736(12)60478-4 . Alirol E, Getaz L, Stoll B, Chappuis F, Loutan L. Urbanisation and infectious diseases in a globalised world. Lancet Infect Dis. 2011;11(2):131–41. https://doi.org/10.1016/S1473-3099(10)70223-1 . Andreoli F, Mussini M, Prete V, Zoli C. Urban poverty: Measurement theory and evidence from American cities. The Journal of Economic Inequality; 2021. Apanga & Adam. (2015). Factors influencing the uptake of family planning services in the Talensi District, Ghana . 8688 , 1–9. https://doi.org/10.11604/pamj.2015.20.10.5301 Ba DM, Ssentongo P, Agbese E, Kjerulff KH. Prevalence and predictors of contraceptive use among women of reproductive age in 17 sub-Saharan African countries: A large population-based study. Sexual & Reproductive Healthcare; 2019. Bamiwuye SO. (2013). Linkages between autonomy, poverty and contraceptive use in two sub-Saharan African countries . 2 , 64–73. Dambo ND, Jeremiah I, Wallymahmed A. (2017). Determinants of contraceptive use by women in the Central Senatorial Zone of Bayelsa State, Nigeria : A cross – sectional survey . 26–31. https://doi.org/10.4103/0300-1652.218409 Danaan VV. (2018). Analysing Poverty in Nigeria through Theoretical Lenses . 11 (1), 20–31. https://doi.org/10.5539/jsd.v11n1p20 Ezire O, Idogho O, Theophilus A, Ikani S, Oluigbo O. (2014). Study on the patterns and trend in contraceptive use in South-South and North-Western zones of Nigeria: 2003–2011 . 65–72. Fadeyibi O, Alade M, Adebayo S, Erinfolami T. (2022). Household Structure and Contraceptive Use in Nigeria . 3 (May), 1–9. https://doi.org/10.3389/fgwh.2022.821178 family planning . (n.d.). Fasina F, Oduaran A. (2019). The effect of women ’ s status on desired family size with implications for community based participatory action. Frank TC. (2023). ASSESSMENT OF MODERN CONTRACEPTIVE UTILIZATION IN HEALTH FACILITIES REPORTING ON DISTRICT HEALTH INFORMATION SYSTEM PLATFORM IN RIVERS STATE . 9 (7), 80–103. Girum T, Wasie A. (2017). Correlates of maternal mortality in developing countries: an ecological study in 82 countries . 1–6. https://doi.org/10.1186/s40748-017-0059-8 Gu D, Andreev K, Dupre ME. (2021). Major Trends in Population Growth Around the World Continuing Gowth of the World Population at a Slowing Pace . 3 (28). Hanley GE, Hutcheon JA, Kinniburgh BA, Lee L. Interpregnancy interval and adverse pregnancy outcomes an analysis of successive pregnancies. Obstet Gynecol. 2017;129(3):408–15. https://doi.org/10.1097/AOG.0000000000001891 . Khan K, Su C-W, Tao R, Hao L-N. Urbanization and carbon emission: causality evidence from the new industrialized economies. Environ Dev Sustain. 2020;22(8):7193–213. https://doi.org/10.1007/s10668-019-00479-1 . Najafi-Sharjabad F, Zainiyah Syed Yahya S, Abdul Rahman H, Hanafiah Juni M, Manaf A, R. Barriers of modern contraceptive practices among Asian women: a mini literature review. Global J Health Sci. 2013;5(5):181–92. https://doi.org/10.5539/gjhs.v5n5p181 . Najimudeen M. (2020). Islamic Perspective on Family Planning . 8235 , 90–93. https://doi.org/10.36348/sijog.2020.v03i03.006 National Population Commission (NPC) [Nigeria] and ICF. (2014). NIGERIA DEMOGRAPHIC AND HEALTH SURVEY . National Population Commission (NPC) [Nigeria] and ICF. (2019). National Population Commission (NPC) [Nigeria] and ICF . Obasohan PE. (2015). Religion, Ethnicity and Contraceptive Use among Reproductive age Women in Nigeria . 3 (1), 63–73. Olamijulo JA, Olorunfemi G, Okunola H. Trends and causes of maternal death at the Lagos University teaching hospital, Lagos, Nigeria (2007–2019). BMC Pregnancy Childbirth. 2022;1–12. https://doi.org/10.1186/s12884-022-04649-4 . Population R, Bureau P. (2021). 2021 World Population Data Sheet: Special focus on Global fertility . Requejo JH, Bhutta A. (2015). The post-2015 agenda: staying the course in maternal and child survival . 100 (Suppl 1), 1–6. https://doi.org/10.1136/archdischild-2013-305737 Ridlo MA, Soetomo S, Kistanto NH. (2020). Theoretical Study Of Poverty In Urban Slum Settlements . 9 (03), 4825–4829. Taingson MC, Adze JA, Bature SB, Durosinlorun AM, Caleb M, Amina A, Kana MA, Lydia A. (2017). Trend of modern contraceptive uptake and its predictors among women accessing family planning service in a tertiary hospital in Northwestern Nigeria, 2000–2014 . https://doi.org/10.4103/TJOG.TJOG Tekelab T, Melka AS, Wirtu D. Predictors of modern contraceptive methods use among married women of reproductive age groups in Western Ethiopia: a community based cross-sectional study. BMC Women’s Health. 2015;1–8. https://doi.org/10.1186/s12905-015-0208-z . United Nations. Growing at a slower pace. World Population Prospects. Department of Economic and Social Affairs; 2019. World Health Organization. (2019). Maternal health in Nigeria: generating information for action. In Sexual and reproductive health (Issue June, pp. 1–3). World Health Organization. (2021). Abortion . Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 25 Mar, 2026 Reviews received at journal 19 Mar, 2026 Reviews received at journal 11 Mar, 2026 Reviewers agreed at journal 01 Mar, 2026 Reviewers agreed at journal 20 Feb, 2026 Reviewers invited by journal 07 Feb, 2026 Editor assigned by journal 07 Feb, 2026 Editor invited by journal 29 Jan, 2026 Submission checks completed at journal 29 Jan, 2026 First submitted to journal 29 Jan, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8679049","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":589184356,"identity":"6855f7e9-15b5-43a9-b156-c8c4116ce1c6","order_by":0,"name":"Simon Osilama Izuagie","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA6UlEQVRIiWNgGAWjYBACNjBpAGV8AImwk6KFcQZIhJkUK5l5wCQBVXz8Zww/fimwsecTO3zssc2vbfJ8zAyMHz7m4HPYGWNpGYO0xDbptHTj3L7bhm3MDMySM7fh0cLYYyAtYXA4gU06x0w6t+c2I1ALGzMvPi3MPMa/JQz+24O1WPbctieshY3HTPKDwQHGNpAWhh+3Ewlr4WErs2YwSAb5JU2yt+F2chszYzNev8j3H95888cfO3v52cnHJH78uW07v7354IePeLSAACQ6QICxDUw24FcPUvIDzvxDUPEoGAWjYBSMQAAAIUZDvUAnT4YAAAAASUVORK5CYII=","orcid":"","institution":"Obafemi Awolowo University","correspondingAuthor":true,"prefix":"","firstName":"Simon","middleName":"Osilama","lastName":"Izuagie","suffix":""},{"id":589184362,"identity":"24b618a8-1d4c-48f8-9e6f-59f1447d39e1","order_by":1,"name":"Olusina Samson Bamiwuye","email":"","orcid":"","institution":"Obafemi Awolowo University","correspondingAuthor":false,"prefix":"","firstName":"Olusina","middleName":"Samson","lastName":"Bamiwuye","suffix":""},{"id":589184367,"identity":"92348427-91d9-48da-8018-24b3bf2a3118","order_by":2,"name":"Bola Lukman Solanke","email":"","orcid":"","institution":"Obafemi Awolowo University","correspondingAuthor":false,"prefix":"","firstName":"Bola","middleName":"Lukman","lastName":"Solanke","suffix":""},{"id":589184377,"identity":"5ad09cb1-dc56-4d7f-a1e9-edf144e95787","order_by":3,"name":"Temisola Emmanuel OYELAKIN","email":"","orcid":"","institution":"Obafemi Awolowo University","correspondingAuthor":false,"prefix":"","firstName":"Temisola","middleName":"Emmanuel","lastName":"OYELAKIN","suffix":""}],"badges":[],"createdAt":"2026-01-23 12:09:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8679049/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8679049/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":102617340,"identity":"6d692868-5310-4383-b6ac-1799cdeb5d85","added_by":"auto","created_at":"2026-02-13 15:58:36","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":33676,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003ePrevalence of Contraceptive Use in Nigeria\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8679049/v1/9be46c972edc05501422e1b7.png"},{"id":103056317,"identity":"6c6edefb-4b16-4c2e-9afb-4bce6509d303","added_by":"auto","created_at":"2026-02-20 09:06:23","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2678165,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8679049/v1/b23e31bf-2236-4aab-bdfd-0008ad80e792.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"TRENDS, DIFFERENTIALS AND DETERMINANTS OF MODERN CONTRACEPTIVE USE AMONG URBAN POOR WOMEN IN NIGERIA","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eThe global population continues to grow at a slower pace due to fertility declines, nevertheless, sub-Saharan African countries stand out with projected significant increases, influenced by population momentum and ongoing demographic transitions (Gu et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Nigeria has the largest population in sub-Saharan Africa, with an annual growth rate of 2.6 percent, Nigeria\u0026rsquo;s population is expected to double in 26.9 years\u0026rsquo; time. Contraceptive utilization is regarded as a key approach in managing population growth and prevention of maternal mortality. However, the weak health system in many developing countries is largely associated with rapid increase in the population of developing countries, leading to a steady high fertility rate which is a major hindrance to improvement in maternal and child health services (Requejo \u0026amp; Bhutta, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). It has been reported that contraceptive use effectively averts approximately 230\u0026nbsp;million annual global childbirths, thereby mitigating the occurrence of unintended pregnancies and subsequently leading to a decline in the overall fertility rate within a given nation (Ahmed et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2012\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe 2018 Nigeria Demographic and Health Survey (NDHS) revealed a little disparity between the total fertility rate and the total intended fertility rate. The observed gap in question serves as a signal of the possible decrease in the number of births that may have been averted with the effective utilization of modern contraceptive techniques, as stated by the (National Population Commission (NPC) [Nigeria] and ICF, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The findings also revealed that the high unwanted fertility and unmet contraceptive need expose women to life-threatening pregnancy risks and complications that could have been avoided using contraceptives.\u003c/p\u003e \u003cp\u003eIn 2019, Nigeria accounted for 20% of the global maternal mortality rate. Based on the report from the (World Health Organization, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), Nigeria witnessed a maternal mortality ratio that surpassed 800 maternal deaths per 100,000 live births (Olamijulo et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Between the years 2005 and 2015, Nigeria reportedly saw a significant number of maternal deaths, with the total surpassing 600,000, alongside an estimated 900,000 instances of near-miss occurrences (World Health Organization, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). These near-miss incidences pertain to respondents who managed to survive problems arising from pregnancy or childbirth. The research conducted by (Girum \u0026amp; Wasie, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) has revealed a significant association between low contraceptive prevalence and increased maternal mortality ratio in a number of countries. The use of contraceptives has been shown to decrease maternal mortality rates, as well as the likelihood of conception and the subsequent risks and difficulties connected with pregnancy. According to the (World Health Organization, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), over 45% of all global abortions are categorized as unsafe, with a significant majority of 97% occurring in underdeveloped nations. Unsafe abortion is responsible for a range of maternal deaths, estimated to be between 4.7% and 13.2%. In Nigeria, as well as in numerous developing countries, abortion is generally prohibited with exceptions made in situations where it is deemed medically necessary to preserve the life of the mother.\u003c/p\u003e \u003cp\u003eThe recognition of the significance of family planning in achieving the Millennium Development Goals (MDGs) and the Sustainable Development Goals (SDGs) has been extensive. The primary reason for this is the substantial influence it exerts on maternal health and the consequent outcomes pertaining to pregnancy (Najafi-Sharjabad et al., \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). A definition provided by the World Health Organisation (WHO), family planning is defined as a purposeful and premeditated decision undertaken by an respondent or a couple regarding the desired quantity of offspring and the optimal timing for their conception. (\u003cem\u003eFamily Planning\u003c/em\u003e, n.d.) defined family planning as a comprehensive initiative aimed at managing the quantity and temporal distribution of offspring within a household, accomplished via the use of contraception or other forms of birth control. The implementation of family planning is a crucial measure used to mitigate the occurrence of unintended pregnancies and enhance favorable health consequences for women throughout their reproductive years, hence reducing the rates of mother and newborn mortality. Contraceptive use in the developing countries is grossly lower than that of the developed countries (Frank, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). The global satisfaction rate for family planning by modern technologies has remained relatively constant at approximately 77% between 2015 and 2020. However, it is noteworthy that the African region has had a modest increase of 3% in this regard. Based on the findings of the United Nations Department of Economic and Social Affairs Population Division (2019), it is evident that a significant proportion, specifically 58%, of women belonging to the reproductive age category across the globe need family planning services. In addition, within this group, almost 25% face the difficulty of an unmet demand for contraceptives. According to the survey conducted in 2013, about 15% of women in marital unions indicated that they use contraceptives. However, around 16% of married women reported a lack of access to contraception, indicating an unfulfilled need. In Nigeria, the rate of contraceptive use is approximately 12%, which shows that there is a relatively low adoption of contraceptive techniques. Furthermore, there exists a substantial unmet need for contraception, with unmarried sexually active women experiencing a 48% deficit and currently married women facing a 19% deficit (Fadeyibi et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; National Population Commission (NPC) [Nigeria] and ICF, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2014\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). As a result, the fertility rates in Nigeria have remained consistently high due to the limited adoption of contraception methods inside the nation. At present, the fertility rate of the entire country is 5.3 children per woman (National Population Commission (NPC) [Nigeria] and ICF, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe United Nations (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) projects an estimated rise in the global population from 7.7\u0026nbsp;billion in 2019 to 9.7\u0026nbsp;billion by the year 2050. The planned expansion is projected to be largely powered by the African continent, with projections estimating that it will account for over 50% of the entire global population growth. In the meantime, there has been an apparent growth in the emigration of people from rural regions to urban centres, accompanied by a quick and significant modification of the physical environment inside urban areas. Urban population projections by the United Nations (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) gave credence to the unbridled growth of urban population amidst a myriad of structural challenges, especially infrastructural decadence. Urban structural challenges are associated with mass exodus of people moving into the less-developed axis of urban settings. The reports, the population living in urban areas currently comprises over 50% of the global populace, amounting to over 4.2\u0026nbsp;billion respondents. Projections suggest that by the year 2041, this number would escalate to 6\u0026nbsp;billion people (United Nations, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTo increase the utilisation of contraceptives, marginalised women need access to modern contraceptives and good healthcare services. While reports from the 2018 NDHS revealed that improvements in contraceptive use are better among urban dwellers compared to the rural counterparts, the urban poor in Nigeria exhibit poor contraceptive use (6 per cent) compared to their urban counterparts (16 per cent) (National Population Commission (NPC) [Nigeria] and ICF, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). This imbalance results from the slum population's lack of access to affordable health services, misconceptions, and inadequate understanding of the available and accessible facilities for healthcare.\u003c/p\u003e \u003cp\u003eLiterature is replete with wide rural-urban gap in modern contraceptive use; however, disparities exist between modern contraceptive use and health indicators of women within the urban areas. This is attributable to the socio-economic differences between the women in urban areas. Therefore, it is important to analyze the underlying factors contributing to variations in modern contraceptive use, despite the implementation of many strategies and campaigns by governmental and international entities aimed at promoting the adoption of modern contraceptive methods.\u003c/p\u003e"},{"header":"2. Method and Materials","content":"\u003cp\u003eThe study used a cross-sectional research design. This study employed a cross-sectional design and collected data in three rounds. Secondary data from the Nigeria UNICEF Multiple Indicator Cluster Survey (UNICEF MICS) conducted in 2011, 2016-17, and 2021 were used. The sample included women living in metropolitan areas who fell into the lowest two wealth quintiles, specifically the poorest and poor categories.\u003c/p\u003e \u003cp\u003e \u003cb\u003eStudy Area\u003c/b\u003e \u003c/p\u003e \u003cp\u003eNigeria, situated in Africa, stands as the nation with the highest population on the continent and ranks among the most densely populated nations globally. Current estimates indicate a population over 211\u0026nbsp;million respondents and a population growth rate of 2.6 percent (Population Reference Bureau, 2021). Furthermore, the total fertility rate for the country was recorded at 5.2 in the year 2020 (Population Reference Bureau, 2021). The distribution of population density exhibits spatial heterogeneity, with some regions characterized by high population concentrations and others characterized by low population concentrations (National Population Commission (NPC) [Nigeria] and ICF, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The country exhibits suboptimal reproductive health outcomes, as shown by a maternal death ratio of 512 per 100,000 in 2018, a modern contraceptive prevalence rate of 12%, and an unmet demand for Family Planning estimated at 18.9 (National Population Commission (NPC) [Nigeria] and ICF, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cb\u003eData Source, Study Population, and Sample Size\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe research used secondary data. The primary data used in this study was obtained from the UNICEF Multiple Indicator Cluster Survey conducted in the years 2011, 2016-17, and 2021. The UNICEF Multiple Indicator Cluster Survey (MICS) offers standardized data on various indicators, such as reproductive and maternal health, child health, nutrition, development, protection from violence and exploitation, and living conditions. The main purpose of this survey is to evaluate key indicators that facilitate the collection of data by countries for the purposes of policymaking, programme execution, and national development objectives. Furthermore, it functions as a mechanism for monitoring advancements made towards the attainment of the SDGs and other internationally acknowledged commitments.\u003c/p\u003e \u003cp\u003eThe respondents responsible for collecting the data used a self-administered questionnaire as a means of obtaining information from the participants. The surveys include many thematic parts, such as maternity and child health, contraception, domestic violence, nutrition, malaria, HIV/AIDS, and women empowerment, among others. The researchers used a multi-stage, stratified cluster sampling technique to pick the sample. The main units of analysis consist of females aged 15 to 49 years residing in the 36 states of Nigeria, including the Federal Capital Territory (FCT), Abuja. The UNICEF Nigeria Multiple Indicator Cluster Surveys (MICS) included a total of 30,772, 32,237, and 38,806 women within the specified age bracket in the years 2011, 2016-17, and 2021 correspondingly. Following the application of inclusion and exclusion criteria, the weighted sample included 839, 769, and 967 women in the years 2011, 2016-17, and 2021, respectively. Consequently, the total weighted sample size consisted of 2,575 women classified as urban poor.\u003c/p\u003e \u003cp\u003e \u003cb\u003eEthical Clearance\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe data used in this research was obtained from the UNICEF Nigeria Multiple Indicator Cluster Survey conducted in the years 2011, 2016-17, and 2021. In August 2021, the protocol for the UNICEF Nigeria Multiple Indicator Cluster Survey (MICS) was accepted by both the steering committee and a review committee composed of members from the Technical Committee. Each participant provided verbal consent and received comprehensive information regarding the voluntary nature of their participation, as well as the guarantee of confidentiality and anonymity regarding their personal information. The participants were provided with information regarding their entitlement to decline answering any or all of the questions, as well as to terminate the interview at any point. The UNICEF Nigeria MICS datasets may be accessed by the public via the official website \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://mics.unicef.org/surveys\u003c/span\u003e\u003cspan address=\"https://mics.unicef.org/surveys\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Additionally, I have been granted authorization to obtain and use these datasets.\u003c/p\u003e"},{"header":"3. Result","content":"\u003cp\u003e \u003cb\u003eSocio-Demographic Characteristics\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe analysis of respondents’ socio-demographic characteristics across three survey rounds (2011, 2016-17, and 2021) revealed significant trends. The mean age of respondents decreased from 29.3 years in 2011 to 28.5 years in subsequent rounds. Younger age groups (15–24 years) increased in proportion from 33.3% in 2011 to 39.9% in 2021, while older age groups (25–34 years) declined.\u003c/p\u003e \u003cp\u003eLevel of education further showed improvement, with the proportion of respondents without formal education decreasing from 54.8% in 2011 to 36.6% in 2021, while secondary education increased from 22.7% to 39.9%. However, higher education remained minimal, with less than 2% of respondents achieving this level. Also, marital status indicated a decline in marriage rates, with respondents married or cohabiting decreasing from 73.8% in 2011 to 57.5% in 2021, while those never married increased from 18.3% to 33.1%. Mean age at marriage rose from 16.5 years in 2011 to 17.1 years in 2021.\u003c/p\u003e \u003cp\u003eLikewise, fertility patterns revealed a decline in childbirth rates, with 79.9% of respondents having given birth in 2011 compared to 66% in 2021. The average number of CEB decreased from 4.1 to 3.2 over the same period. Similarly, ethnicity shifted significantly, with the proportion of Hausa falling from 70% in 2016-17 to 48% in 2021, while percentage of Igbo and Yoruba respondents increased. Regional differences were also notable, with the Northern region’s share of respondents peaking at 92.7% in 2016-17 before declining to 66.4% in 2021, while the Southern region’s proportion rose to 33.6% in 2021.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSocio-Demographic Characteristics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e \u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth colname=\"c1\" morerows=\"1\" rowspan=\"2\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003eMICS 4 (2011)\u003c/p\u003e \u003c/th\u003e\u003cth colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003eMICS 5 (2016-17)\u003c/p\u003e \u003c/th\u003e\u003cth colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003eMICS 6 (2021)\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth colspan=\"3\" nameend=\"c4\" namest=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003ePERCENTAGE / MEAN (SD)\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eAge\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e29.3 (± 9.4)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e28.5 (± 9.8)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e28.5 (± 9.8)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eAge group)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003e15–24 years\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e33.3\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e38.5\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e39.9\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003e25–34 years\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e35.6\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e30.1\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e29.6\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003e35–49 years\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e31.1\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e31.5\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e30.5\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eLevel of education\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eNo formal education\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e54.8\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e61.4\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e36.6\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003ePrimary\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e21.0\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e15.1\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e22.2\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eSecondary\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e22.7\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e22.5\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e39.9\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eHigher\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e1.5\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e1.0\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e1.2\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eMarital Status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eNever married\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e18.3\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e26.8\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e33.1\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eMarried/cohabiting\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e73.8\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e68.9\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e57.5\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eFormerly married\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e7.9\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e4.3\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e9.5\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eAge at marriage\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e16.5 (4.5)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e16.6 (4.2)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e17.1 (4.9)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eEver given birth\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e79.9\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e71.2\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e66.4\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eChildren ever born\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e4.1 (3.4)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e3.8 (3.4)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e3.2 (3.2)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eHusband’s age\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e43.0 (11.3)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e45.6 (13.2)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e44.1 (13.6)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eEthnicity\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eHausa\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e69.8\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e47.7\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eIgbo\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e12.5\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eYoruba\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e6.2\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e15.7\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eOther ethnic groups\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e23.4\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e24.1\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eRegion\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eNorth\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e75.7\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e92.7\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e66.4\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eSouth\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e24.3\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e7.3\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e33.6\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eN\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003e845\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003e774\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003e974\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e \u003cp\u003e\u003c/p\u003e \u003cp\u003e \u003cb\u003eIntervening variable\u003c/b\u003e \u003c/p\u003e \u003cp\u003eConcerning the exposure to information from the media (newspaper, radio, and television), the data was unavailable in 2011, therefore, findings from 2016-17 and 2021 were only presented in this study. Regarding the exposure to newspapers, 16% of the respondents in 2016-17 were exposed to newspapers compared to 6% in 2021; 62% were exposed to radio in 2016-17 compared to 68% in 2021, and all the respondents in 2016-17 were exposed to television in 2016-17 compared to 21% in 2021. Likewise, findings showed that 21% were exposed to media in 2016-17 compared to 3% in 2021.\u003c/p\u003e \u003cp\u003eIn relation to the perception of domestic violence against wives, a composite variable was constructed by amalgamating five distinct views. The percentage who justify any form of wife beating slightly decreased from 12% in 2011 to 10% in 2021. In 2011, 35% of respondents believed that wife beating is justified when a woman goes out without informing her husband, decreasing to 20% in 2021. Additionally, 35% of respondents in 2011, 25% in 2016-17, and 23% of urban poor respondents in 2021 believed that wife beating is justified when a woman argues with her husband. Furthermore, the percentage of respondents justifying wife beating based on refusal to have sex with the spouse was approximately 37% in 2011 but declined to 27% in 2021. Lastly, from 19% in 2011, to 14% of urban poor respondents in 2021 justified wife beating if the woman burns food.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePercentage Distribution of Respondents by Intervening Variables\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e \u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth colname=\"c1\" morerows=\"1\" rowspan=\"2\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003eMICS 4 (2011)\u003c/p\u003e \u003c/th\u003e\u003cth colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003eMICS 5 (2016-17)\u003c/p\u003e \u003c/th\u003e\u003cth colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003eMICS 6 (2021)\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth colspan=\"3\" nameend=\"c4\" namest=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003ePERCENTAGE / MEAN (SD)\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eExposed to newspaper\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e15.5\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e5.6\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eExposed to radio\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e38.5\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e32.1\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eExposed to television\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e100.0\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e21.0\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eExposure to all media\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003eN/A\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e21.0\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e3.3\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eAge difference between partners\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e11.8 (8.6)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e13.1 (10.3)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e11.4 (10.6)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eWife beating justified.\u003c/b\u003e\u003c/p\u003e \u003cp\u003eNot Justified\u003c/p\u003e \u003cp\u003eJustified\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e88.5\u003c/p\u003e \u003cp\u003e11.5\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e90.6\u003c/p\u003e \u003cp\u003e9.4\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e90.4\u003c/p\u003e \u003cp\u003e9.6\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eReasons for Wife-beating attitude justified\u003c/b\u003e:\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eGoes out without telling her husband\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e34.9\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e27.0\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e19.8\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eNeglects children\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e33.7\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e28.5\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e22.5\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eArgues with husband\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e34.5\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e24.8\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e19.7\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eRefuse sex\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e36.8\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e30.6\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e27.0\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eBurns food\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e18.7\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e17.5\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e13.8\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eN\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003e854\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003e774\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003e974\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e \u003cp\u003e\u003c/p\u003e \u003cp\u003e \u003cb\u003eLevel of Contraceptive Use (Current and Ever use) in Nigeria\u003c/b\u003e \u003c/p\u003e \u003cp\u003eResults in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e present the first part of objective 1 which was to examine the trends in the utilization of modern contraceptive from 2011–2021 among urban poor women residing in Nigeria. It can be deduced from Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e that 14.6 per cent of the respondents in 2011 were currently using contraceptives, compared to 6.1 per cent in 2016-17, and 12.8 per cent in 2021. This result shows a reduction in current contraceptive use from 2011–2021. Although there was a sharp decline between 2011 and 2016-17, the prevalence increased by 6.7 per cent by 2021. Furthermore, it can be deduced that the proportion of respondents who reported having used contraceptives as a means of pregnancy prevention was 3.2 percent in 2016, however this figure increased to 7.1 percent in 2021. The findings indicate an increase in the prevalence of contraceptive usage for the purpose of pregnancy prevention\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eSocio-demographic Characteristics and Ever Use of Contraceptives among Urban Poor Respondents in Nigeria\u003c/b\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e displays the link between socio-demographic characteristics and the utilisation of contraceptives among participants belonging to Nigeria's urban poor population. Based on the results, it was seen that the mean age of the respondents included in the MICS 2016-17 survey was documented as 33.85 years, however in the MICS 2021 survey, a slight decrease to 33.10 years was noted. The statistical significance of the association between age and contraceptive usage was demonstrated by p-values of 0.01 and 0.001. Furthermore, a notable increase in the utilisation of contraceptives was found within the demographic of respondents aged 15–24 years. Specifically, the prevalence of contraceptive use rose from 0.67% in the MICS survey done during the period of 2016-17 to 1.84% in the subsequent MICS survey conducted in 2021.\u003c/p\u003e \u003cp\u003eThere was a significant increase observed in the utilisation of contraceptive methods among respondents who were married or cohabiting, as evidenced by the percentage rising from 4.76% during the MICS 2016-17 survey to 9.14% during the MICS 2021 study. Furthermore, a notable correlation has been observed between marital status and the utilisation of contraceptives, as evidenced by the data obtained from the Multiple Indicator Cluster Surveys (MICS) carried out during the periods of 2016-17 and 2021. There was a lack of substantial alteration observed in the mean age at marriage between the MICS 2016-17 survey and the subsequent MICS 2021 study. The time period encompassing MICS 2016–17 to MICS 2021 had a significant rise in contraceptive utilisation among those who had previously given birth, as indicated by the prevalence increasing from 4.34% to 9.95%. In contrast, a significant increase was observed in the percentage of participants who had never had delivery and were utilising contraceptive techniques, with the proportion rising from 0.62% to 2.07%. The examination of the p-value suggests a statistically significant association between the age at which respondents marry and their utilisation of contraceptives.\u003c/p\u003e \u003cp\u003eFurthermore, the findings indicate a marginal increase in the mean number of children ever born (CEB) from 4.54 to 4.78 between the MICS surveys conducted in 2016-17 and 2021. This observed trend can be attributed to the significant proportion of respondents who reported taking contraceptives, suggesting a positive correlation between having more children and the likelihood of utilising contraceptive methods. Furthermore, it is noteworthy that the average age of the husbands of the participants exhibited a consistent level of stability throughout the duration spanning from the MICS survey conducted in 2016-17 to the most recent iteration of the survey in 2021. Nevertheless, there was no significant statistical correlation found between the age of the husband and the utilisation of contraceptive methods. There were notable variations in contraceptive usage across several ethnic groups.. The Igbo ethnic group had a decrease in contraceptive use from 30.46% to 16.65%. Hausa and Yoruba ethnic groups had a slight increase in contraceptive use, while other ethnic groups had a small increase as well. Likewise, ethnicity and ever use of contraceptives had statistical relationship. There were significant changes in contraceptive use based on the region between MICS 2016-17 and MICS 2021. In the Northern region, there was a decrease in contraceptive use from 68.35 per cent to 52.71 per cent while in the Southern region, there was an increase from 31.65 per cent to 47.29 per cent. Yet, northern region and ever use of contraceptives were associated.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\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\u003eSocio-demographic Characteristics and Ever Use of Contraceptives among Urban Poor Respondents in Nigeria\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e \u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth colname=\"c1\" morerows=\"1\" rowspan=\"2\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth colspan=\"2\" nameend=\"c3\" namest=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003eMICS 2016-17\u003c/p\u003e \u003c/th\u003e\u003cth colspan=\"2\" nameend=\"c5\" namest=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003eMICS 2021\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003eNO\u003c/p\u003e \u003cp\u003eFreq (per cent)\u003c/p\u003e \u003c/th\u003e\u003cth colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003eYES\u003c/p\u003e \u003cp\u003eFreq (per cent)\u003c/p\u003e \u003c/th\u003e\u003cth colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003eNO\u003c/p\u003e \u003cp\u003eFreq (per cent)\u003c/p\u003e \u003c/th\u003e\u003cth colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003eYES\u003c/p\u003e \u003cp\u003eFreq (per cent)\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd colname=\"c1\" morerows=\"1\" rowspan=\"2\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eAge\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003eMean (SD)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e28.44 (9.9)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e33.85 (8.6)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e27.35 (9.8)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003e33.10 (7.0)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"2\" nameend=\"c3\" namest=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003ep = 0.01*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colspan=\"2\" nameend=\"c5\" namest=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003ep = 0.00*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eAge group\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eχ\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e \u003cb\u003e= 6.89\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003ep = 0.03*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eχ\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e \u003cb\u003e= 32.1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003ep \u0026lt; 0.01**\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003e15–24 years\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e217 (99.33)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e1 (0.67)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e425 (98.16)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003e8 (1.84)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003e25–34 years\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e151 (93.50)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e10 (6.50)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e254 (90.48)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003e26 (9.52)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003e35–49 years\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e165 (96.61)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e6 (3.39)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e264 (87.54)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003e37 (12.46)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eLevel of education\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eχ\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e \u003cb\u003e= 5.92\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003ep = 0.12\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eχ\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e \u003cb\u003e= 5.25\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003ep = 0.15\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eNo formal education\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e343 (98.51)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e5 (1.49)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e367 (95.00)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003e19 (5.00)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003ePrimary\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e69 (88.63)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e9 (11.37)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e206 (92.25)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003e17 (7.75)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eSecondary\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e117 (97.70)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e3 (2.30)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e358 (90.95)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003e36 (9.05)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eHigher\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e5 (82.97)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e1 (17.03)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e11 (100.00)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003e0 (0.00)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eMarital Status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eχ\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e \u003cb\u003e= 11.38\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003ep \u0026lt; 0.01**\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eχ\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e \u003cb\u003e= 19.00\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003ep \u0026lt; 0.01**\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eNever married\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e153 (100.00)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e0 (0.00)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e348 (97.89)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003e7 (2.11)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eMarried/cohabiting\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e355 (95.24)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e18 (4.76)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e513 (90.86)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003e51 (9.14)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eFormerly married\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e25 (100.00)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e0 (0.00)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e81 (86.05)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003e13 (13.95)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" morerows=\"1\" rowspan=\"2\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eAge at marriage\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003eMean (SD)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e16.60 (4.49)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e17.25 (3.70)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e16.51 (4.54)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003e17.25 (4.33)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003ep = 0.49\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003ep = 0.23\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eEver given birth\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eχ\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e \u003cb\u003e= 5.15\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003ep = 0.02**\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eχ\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e \u003cb\u003e= 20.81\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003ep \u0026lt; 0.01**\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e165 (99.38)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e1 (0.62)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e356 (97.93)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003e8 (2.07)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e368 (95.66)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e17 (4.34)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e586 (90.05)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003e65 (9.95)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" morerows=\"1\" rowspan=\"2\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eChildren ever born Mean (SD)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e3.73 (3.45)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e4.54 (2.93)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e3.01 (3.19)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003e4.78 (2.89)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003ep = 0.26\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003ep \u0026lt; 0.01**\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" morerows=\"1\" rowspan=\"2\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eHusband’s age\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u003cb\u003eMean (SD)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e45.74 (12.97)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e43.39 (8.66)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e44.02 (13.68)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003e43.33 (11.26)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003ep = 0.39\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003ep = 0.72\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eEthnicity\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eχ\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e \u003cb\u003e= 23.81\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003ep \u0026lt; 0.01**\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eχ\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e \u003cb\u003e= 16.36\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003ep \u0026lt; 0.01**\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eHausa\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e384 (97.45)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e10 (2.55)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e485 (95.16)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003e25 (4.84)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eIgbo\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e2 (69.54)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e1 (30.46)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e92 (83.35)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003e18 (16.65)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eYoruba\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e23 (82.73)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e5 (17.27)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e134 (88.06)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003e18 (11.94)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eOther ethnic groups\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e124 (98.34)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e2 (1.66)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e232 (95.40)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003e11 (4.60)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eRegion\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eχ\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e \u003cb\u003e= 9.26\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003ep \u0026lt; 0.01**\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eχ\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e \u003cb\u003e= 3.40\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003ep = 0.06\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eNorth\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e506 (94.93)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e12 (68.35)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e660 (69.96)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003e38 (52.71)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eSouth\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e27 (5.07)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e6 (31.65)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e283 (30.04)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003e34 (47.29)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"5\"\u003e** indicates p \u0026lt; 0.01 * indicates p \u0026lt; 0.05 OR – Odds Ratio\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e \u003cp\u003e\u003c/p\u003e \u003cp\u003e \u003cb\u003eSocio-demographic Characteristics and the Current Use of Contraceptives among Urban Poor Respondents in Nigeria\u003c/b\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e below focuses on the socio-demographic characteristics and the current use of contraceptives among urban poor women in Nigeria. The table presents data from three different time periods: MICS 2011, MICS 2016-17, and MICS 2021. The table revealed a significant relationship between age, age group and the current use of contraceptives. In MICS 2011, the highest proportion of contraceptive use was observed among women aged 35–49 years (19.09%). In MICS 2016-17, the highest proportion shifted to women aged 25–34 years (9.83%). In MICS 2021, the highest proportion was again observed among women aged 25–34 years (20.60%). The increasing proportion of contraceptive use among women aged 25–34 years in MICS 2016-17 and MICS 2021 suggests that this age group may be more proactive in using contraceptives. This could be attributed to increased awareness and access to family planning services among this demographic.\u003c/p\u003e \u003cp\u003eConcerning the level of education, the highest proportion of contraceptive use in the MICS 2011, was among women with higher education (45.51%). In MICS 2016-17, it shifted to women with secondary education (9.43%). In MICS 2021, the highest proportion was again observed among women with secondary education (15.30%). The p-values for education level indicate a statistical association with use of contraceptive, except for MICS 2021 where p = 0.22, indicating a weaker association, highlighting the value of education in encouraging contraceptive use. It implies that educated women are more likely to be familiar with and have access to contraceptive methods. Regarding marital status, the highest proportion of contraceptive use in MICS 2011 was among formerly married women (23.54%). In MICS 2016-17, it shifted to married/cohabiting women (8.48%). In MICS 2021, the highest proportion was again observed among married/cohabiting women (17.20%). The decreasing p-values across the years (0.58, 0.01, 0.00) suggest a significant change in contraceptive use across different marital statuses over time. The increasing proportion of contraceptive use among married/cohabiting women in MICS 2016-17 and MICS 2021 indicates a positive shift towards family planning among this group. This could be due to efforts in promoting spousal communication, joint decision-making, and the availability of diverse contraceptive options\u003c/p\u003e \u003cp\u003eThere was a significant relationship between age at marriage and the current use of contraceptives in MICS 2011 and 2021. Concerning childbearing status, the highest proportion of contraceptive use in MICS 2011 was among women who had given birth (15.14%). In MICS 2016-17, it shifted to women who had not given birth (8.43%). In MICS 2021, the highest proportion was again observed among women who had given birth (16.85%). The p-values for ever giving birth indicate a significant association with contraceptive use, except for MICS 2011 where p = 0.72, indicating no significant association. The higher proportion of contraceptive use among women who have given birth in MICS 2011 and MICS 2021 highlights the importance of postpartum contraception. It suggests that efforts to promote and provide contraceptives to women immediately after childbirth are gaining recognition and leading to increased usage. Regarding ethnicity and region, the p-values indicate the statistical influence on contraceptive use. Ethnicity data is missing for MICS 2011, but in MICS 2016-17 and 2021, certain ethnic groups (Hausa, Igbo, Yoruba, and other ethnic groups) show significant associations with contraceptive use. Similarly, the two regions (North and South) also show significant associations with contraceptive use across the years.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSocio-demographic Characteristics and the Current Use of Contraceptives among Urban Poor Respondents in Nigeria\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"9\"\u003e \u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth colname=\"c1\" morerows=\"1\" rowspan=\"2\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth colspan=\"3\" nameend=\"c4\" namest=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003eMICS 2011\u003c/p\u003e \u003c/th\u003e\u003cth colspan=\"3\" nameend=\"c7\" namest=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003eMICS 2016-17\u003c/p\u003e \u003c/th\u003e\u003cth colspan=\"2\" nameend=\"c9\" namest=\"c8\" style=\"text-align: left;\"\u003e \u003cp\u003eMICS 2021\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003eNO\u003c/p\u003e \u003cp\u003eFreq (%)\u003c/p\u003e \u003c/th\u003e\u003cth colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003eYES\u003c/p\u003e \u003cp\u003eFreq (%)\u003c/p\u003e \u003c/th\u003e\u003cth colspan=\"2\" nameend=\"c5\" namest=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003eNO\u003c/p\u003e \u003cp\u003eFreq (%)\u003c/p\u003e \u003c/th\u003e\u003cth colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003eYES\u003c/p\u003e \u003cp\u003eFreq (%)\u003c/p\u003e \u003c/th\u003e\u003cth colspan=\"2\" nameend=\"c8\" namest=\"c7\" style=\"text-align: left;\"\u003e \u003cp\u003eNO\u003c/p\u003e \u003cp\u003eFreq (%)\u003c/p\u003e \u003c/th\u003e\u003cth colname=\"c9\" style=\"text-align: left;\"\u003e \u003cp\u003eYES\u003c/p\u003e \u003cp\u003eFreq (%)\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd colname=\"c1\" morerows=\"1\" rowspan=\"2\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eAge [mean (SD)]\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e29.28 (9.77)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e31.58 (9.01)\u003c/p\u003e \u003c/td\u003e\u003ctd colspan=\"2\" nameend=\"c5\" namest=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e28.46 (10.27)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003e32.42 (7.85)\u003c/p\u003e \u003c/td\u003e\u003ctd colspan=\"2\" nameend=\"c8\" namest=\"c7\" style=\"text-align: left;\"\u003e \u003cp\u003e27.48 (9.97)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e \u003cp\u003e32.28 (7.79)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"3\" nameend=\"c4\" namest=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003ep = 0.03*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colspan=\"3\" nameend=\"c7\" namest=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003ep = 0.01**\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colspan=\"2\" nameend=\"c9\" namest=\"c8\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003ep \u0026lt; 0.01**\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eAge group\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e \u003cb\u003e= 6.22\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003ep = 0.04*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colspan=\"2\" nameend=\"c5\" namest=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e \u003cb\u003e= 11.30\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003ep \u0026lt; 0.01**\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colspan=\"2\" nameend=\"c8\" namest=\"c7\" style=\"text-align: left;\"\u003e \u003cp\u003eχ\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e \u003cb\u003e= 38.34\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003ep \u0026lt; 0.01**\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003e15–24 years\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e230 (88.88)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e29 (11.12)\u003c/p\u003e \u003c/td\u003e\u003ctd colspan=\"2\" nameend=\"c5\" namest=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e204 (97.41)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003e5 (2.59)\u003c/p\u003e \u003c/td\u003e\u003ctd colspan=\"2\" nameend=\"c8\" namest=\"c7\" style=\"text-align: left;\"\u003e \u003cp\u003e400 (94.11)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e \u003cp\u003e25 (5.89)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003e25–34 years\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e224 (86.15)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e36 (13.85)\u003c/p\u003e \u003c/td\u003e\u003ctd colspan=\"2\" nameend=\"c5\" namest=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e131 (90.17)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003e14 (9.83)\u003c/p\u003e \u003c/td\u003e\u003ctd colspan=\"2\" nameend=\"c8\" namest=\"c7\" style=\"text-align: left;\"\u003e \u003cp\u003e222 (79.40)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e \u003cp\u003e58 (20.60)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003e35–49 years\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e198 (80.91)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e47 (19.09)\u003c/p\u003e \u003c/td\u003e\u003ctd colspan=\"2\" nameend=\"c5\" namest=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e160 (92.73)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003e12 (7.27)\u003c/p\u003e \u003c/td\u003e\u003ctd colspan=\"2\" nameend=\"c8\" namest=\"c7\" style=\"text-align: left;\"\u003e \u003cp\u003e259 (84.66)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e \u003cp\u003e47 (15.34)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eLevel of education\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eχ\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e \u003cb\u003e= 39.19\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003ep \u0026lt; 0.01**\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colspan=\"2\" nameend=\"c5\" namest=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eχ\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e \u003cb\u003e= 21.55\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003ep \u0026lt; 0.01**\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colspan=\"2\" nameend=\"c8\" namest=\"c7\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eχ\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e \u003cb\u003e= 4.37\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003ep = 0.22\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eNo education\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e373 (91.34)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e35 (8.66)\u003c/p\u003e \u003c/td\u003e\u003ctd colspan=\"2\" nameend=\"c5\" namest=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e305 (96.83)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003e10 (3.17)\u003c/p\u003e \u003c/td\u003e\u003ctd colspan=\"2\" nameend=\"c8\" namest=\"c7\" style=\"text-align: left;\"\u003e \u003cp\u003e332 (90.88)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e \u003cp\u003e33 (9.12)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003ePrimary\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e131 (84.43)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e24 (15.57)\u003c/p\u003e \u003c/td\u003e\u003ctd colspan=\"2\" nameend=\"c5\" namest=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e73 (87.43)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003e10 (12.57)\u003c/p\u003e \u003c/td\u003e\u003ctd colspan=\"2\" nameend=\"c8\" namest=\"c7\" style=\"text-align: left;\"\u003e \u003cp\u003e191 (86.11)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e \u003cp\u003e31 (13.89)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eSecondary\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e141 (75.32)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e46 (24.68)\u003c/p\u003e \u003c/td\u003e\u003ctd colspan=\"2\" nameend=\"c5\" namest=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e113 (90.57)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003e12 (9.43)\u003c/p\u003e \u003c/td\u003e\u003ctd colspan=\"2\" nameend=\"c8\" namest=\"c7\" style=\"text-align: left;\"\u003e \u003cp\u003e348 (84.70)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e \u003cp\u003e63 (15.30)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eHigher\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e7 (54.49)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e6 (45.51)\u003c/p\u003e \u003c/td\u003e\u003ctd colspan=\"2\" nameend=\"c5\" namest=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e4 (100.00)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003e0 (0.00)\u003c/p\u003e \u003c/td\u003e\u003ctd colspan=\"2\" nameend=\"c8\" namest=\"c7\" style=\"text-align: left;\"\u003e \u003cp\u003e11 (80..17)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e \u003cp\u003e3 (19.83)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eMarital Status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eχ\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e \u003cb\u003e= 1.11\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003ep = 0.58\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colspan=\"2\" nameend=\"c5\" namest=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eχ\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e \u003cb\u003e= 8.50\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003ep = 0.01**\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colspan=\"2\" nameend=\"c8\" namest=\"c7\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eχ\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e \u003cb\u003e= 33.04\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003ep \u0026lt; 0.01**\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eNever married\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e131 (85.07)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e23 (14.93)\u003c/p\u003e \u003c/td\u003e\u003ctd colspan=\"2\" nameend=\"c5\" namest=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e157 (98.17)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003e3 (1.83)\u003c/p\u003e \u003c/td\u003e\u003ctd colspan=\"2\" nameend=\"c8\" namest=\"c7\" style=\"text-align: left;\"\u003e \u003cp\u003e343 (93.63)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e \u003cp\u003e23 (6.37)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eMarried/cohabiting\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e471 (86.55)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e73 (13.45)\u003c/p\u003e \u003c/td\u003e\u003ctd colspan=\"2\" nameend=\"c5\" namest=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e314 (91.52)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003e29 (8.48)\u003c/p\u003e \u003c/td\u003e\u003ctd colspan=\"2\" nameend=\"c8\" namest=\"c7\" style=\"text-align: left;\"\u003e \u003cp\u003e447 (82.80)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e \u003cp\u003e93 (17.20)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eFormerly married\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e49 (76.46)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e15 (23.54)\u003c/p\u003e \u003c/td\u003e\u003ctd colspan=\"2\" nameend=\"c5\" namest=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e25 (98.98)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003e1 (1.02)\u003c/p\u003e \u003c/td\u003e\u003ctd colspan=\"2\" nameend=\"c8\" namest=\"c7\" style=\"text-align: left;\"\u003e \u003cp\u003e91 (87.20)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e \u003cp\u003e13 (12.80)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" morerows=\"1\" rowspan=\"2\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eAge at marriage (mean)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e16.38 (4.44)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e18.44 (4.56)\u003c/p\u003e \u003c/td\u003e\u003ctd colspan=\"2\" nameend=\"c5\" namest=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e16.79 (4.67)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003e17.38 (4.24)\u003c/p\u003e \u003c/td\u003e\u003ctd colspan=\"2\" nameend=\"c8\" namest=\"c7\" style=\"text-align: left;\"\u003e \u003cp\u003e16.49 (4.47)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e \u003cp\u003e18.40 (4.93)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003ep \u0026lt; 0.01**\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colspan=\"2\" nameend=\"c5\" namest=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003ep = 0.44\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colspan=\"2\" nameend=\"c8\" namest=\"c7\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003ep \u0026lt; 0.01**\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eEver given birth\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eχ\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e \u003cb\u003e= 0.13\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003ep = 0.72\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colspan=\"2\" nameend=\"c5\" namest=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eχ\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e \u003cb\u003e= 11.58\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003ep \u0026lt; 0.01**\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colspan=\"2\" nameend=\"c8\" namest=\"c7\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eχ\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e \u003cb\u003e= 39.71\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003ep \u0026lt; 0.01**\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e138 (87.46)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e20 (12.54)\u003c/p\u003e \u003c/td\u003e\u003ctd colspan=\"2\" nameend=\"c5\" namest=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e166 (98.87)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003e2 (1.13)\u003c/p\u003e \u003c/td\u003e\u003ctd colspan=\"2\" nameend=\"c8\" namest=\"c7\" style=\"text-align: left;\"\u003e \u003cp\u003e346 (94.25)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e \u003cp\u003e21 (5.75)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e514 (84.86)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e91 (15.14)\u003c/p\u003e \u003c/td\u003e\u003ctd colspan=\"2\" nameend=\"c5\" namest=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e330 (91.57)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003e30 (8.43)\u003c/p\u003e \u003c/td\u003e\u003ctd colspan=\"2\" nameend=\"c8\" namest=\"c7\" style=\"text-align: left;\"\u003e \u003cp\u003e535 (83.15)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e \u003cp\u003e108 (16.85)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" morerows=\"1\" rowspan=\"2\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eChildren ever born (mean)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e4.05 (3.41)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e4.09 (3.17)\u003c/p\u003e \u003c/td\u003e\u003ctd colspan=\"2\" nameend=\"c5\" namest=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e3.69 (3.50)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003e4.58 (2.63)\u003c/p\u003e \u003c/td\u003e\u003ctd colspan=\"2\" nameend=\"c8\" namest=\"c7\" style=\"text-align: left;\"\u003e \u003cp\u003e3.01 (3.26)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e \u003cp\u003e4.43 (2.82)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003ep = 0.92\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colspan=\"2\" nameend=\"c5\" namest=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003ep = 0.08\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colspan=\"2\" nameend=\"c8\" namest=\"c7\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003ep \u0026lt; 0.01**\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" morerows=\"1\" rowspan=\"2\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eHusband’s age (mean)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e43.17 (12.42)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e45.10 (11.09)\u003c/p\u003e \u003c/td\u003e\u003ctd colspan=\"2\" nameend=\"c5\" namest=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e46.22 (12.69)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003e43.25 (11.85)\u003c/p\u003e \u003c/td\u003e\u003ctd colspan=\"2\" nameend=\"c8\" namest=\"c7\" style=\"text-align: left;\"\u003e \u003cp\u003e44.65 (13.69)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e \u003cp\u003e44.53 (11.78)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003ep = 0.23\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colspan=\"2\" nameend=\"c5\" namest=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003ep = 0.16\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colspan=\"2\" nameend=\"c8\" namest=\"c7\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003ep = 0.94\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eEthnicity\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eNA\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eNA\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colspan=\"2\" nameend=\"c5\" namest=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eχ\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e \u003cb\u003e= 45.02\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003ep \u0026lt; 0.01**\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colspan=\"2\" nameend=\"c8\" namest=\"c7\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eχ\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e \u003cb\u003e= 23.32\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003ep \u0026lt; 0.01**\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eHausa\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e\u003ctd colspan=\"2\" nameend=\"c5\" namest=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e359 (96.46)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003e13 (3.54)\u003c/p\u003e \u003c/td\u003e\u003ctd colspan=\"2\" nameend=\"c8\" namest=\"c7\" style=\"text-align: left;\"\u003e \u003cp\u003e433 (92.17)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e \u003cp\u003e37 (7.83)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eIgbo\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e\u003ctd colspan=\"2\" nameend=\"c5\" namest=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e2 (65.76)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003e1 (34.24)\u003c/p\u003e \u003c/td\u003e\u003ctd colspan=\"2\" nameend=\"c8\" namest=\"c7\" style=\"text-align: left;\"\u003e \u003cp\u003e100 (75.33)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e \u003cp\u003e33 (24.67)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eYoruba\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e\u003ctd colspan=\"2\" nameend=\"c5\" namest=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e26 (76.41)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003e8 (23.59)\u003c/p\u003e \u003c/td\u003e\u003ctd colspan=\"2\" nameend=\"c8\" namest=\"c7\" style=\"text-align: left;\"\u003e \u003cp\u003e138 (83.26)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e \u003cp\u003e28 (16.74)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eOther ethnic groups\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e\u003ctd colspan=\"2\" nameend=\"c5\" namest=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e108 (91.72)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003e10 (8.28)\u003c/p\u003e \u003c/td\u003e\u003ctd colspan=\"2\" nameend=\"c8\" namest=\"c7\" style=\"text-align: left;\"\u003e \u003cp\u003e210 (86.66)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e \u003cp\u003e32 (13.34)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eRegion\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eχ\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e \u003cb\u003e= 40.04\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003ep \u0026lt; 0.01**\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colspan=\"2\" nameend=\"c5\" namest=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eχ\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e \u003cb\u003e= 26.98\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003ep = 0.00*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colspan=\"2\" nameend=\"c8\" namest=\"c7\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eχ\u003c/b\u003e\u003csup\u003e\u003cb\u003e2\u003c/b\u003e\u003c/sup\u003e \u003cb\u003e= 13.71\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003ep \u0026lt; 0.01**\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eNorth\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e514 (78.85)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e51 (46.31)\u003c/p\u003e \u003c/td\u003e\u003ctd colspan=\"2\" nameend=\"c5\" namest=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e465 (93.90)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003e22 (69.39)\u003c/p\u003e \u003c/td\u003e\u003ctd colspan=\"2\" nameend=\"c8\" namest=\"c7\" style=\"text-align: left;\"\u003e \u003cp\u003e594 (67.39)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e \u003cp\u003e63 (48.72)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eSouth\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e138 (21.15)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e60 (53.69)\u003c/p\u003e \u003c/td\u003e\u003ctd colspan=\"2\" nameend=\"c5\" namest=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e30 (6.10)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003e10 (30.61)\u003c/p\u003e \u003c/td\u003e\u003ctd colspan=\"2\" nameend=\"c8\" namest=\"c7\" style=\"text-align: left;\"\u003e \u003cp\u003e287 (32.61)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e \u003cp\u003e66 (51.28)\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eN\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003e652\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003e111\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colspan=\"2\" nameend=\"c5\" namest=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003e496\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003e32\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colspan=\"2\" nameend=\"c8\" namest=\"c7\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003e881\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003e130\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"9\"\u003e** indicates p \u0026lt; 0.01 * indicates p \u0026lt; 0.05 OR – Odds Ratio\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e \u003cp\u003e\u003c/p\u003e \u003cp\u003e \u003cb\u003eModel 1: Binary Logistic Regression Model of Respondents’ Ever Use and Current Use of Contraceptives by Socio-Demographic Factors\u003c/b\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e shows that age significantly predict ever use of contraceptives. In MICS 2016-17, a one-year increase in age was associated with a 19% higher likelihood of ever using contraceptives (OR = 1.19, p \u0026lt; 0.04, 95% CI: 1.01–1.39). However, in MICS 2021, this trend reversed, showing a slight decrease in the odds (OR = 0.88, p \u0026lt; 0.04, 95% CI: 0.79–0.99). This suggests that younger respondents in 2021 may have faced different access or attitudinal barriers compared to the earlier period. However, for current use, age was not a significant predictor in either dataset (MICS 2016-17: OR = 0.96, p = 0.55; MICS 2021: OR = 0.96, p = 0.43), indicating that factors beyond age may be influencing recent contraceptive use patterns.\u003c/p\u003e \u003cp\u003eIn same vein, Education played a crucial role in predicting both ever use and current use of contraceptives. In MICS 2016-17, respondents with higher education were significantly more likely to have ever used contraceptives (OR = 9.35, p = 0.05, 95% CI: 0.98–89.29), while those with primary education had significantly lower odds of ever use (OR = 2.36, p = .35). By 2021, the impact of education remained strong, with those having secondary (OR = 3.88, p = 0.01) and primary education (OR = 3.06, p = 0.01) showing increased odds of ever use.\u003c/p\u003e \u003cp\u003eFor current contraceptive use, MICS 2016-17 showed that respondents with secondary and higher education were significantly more likely to use contraceptives (Secondary: OR = 8.12, p = 0.01, 95% CI: 2.86–23.04). However, in MICS 2021, this effect reduced, with no statistically significant increase in odds among higher-educated groups.\u003c/p\u003e \u003cp\u003eEthnicity also influenced contraceptive use patterns. In MICS 2016-17, Igbo respondents were over four times more likely to have ever used contraceptives compared to Hausa respondents (OR = 4.56, p = 0.06, 95% CI: 0.93–22.21), while Yoruba respondents had lower odds (OR = 0.56, p = 0.45). By 2021, these differences remained but were no longer significant, suggesting possible convergence in contraceptive uses across ethnic groups. While for current use, Igbo respondents had higher odds in MICS 2021 (OR = 8.38, p = .01, 95% CI: 2.68–26.17), indicating a sustained ethnic disparity in access or preferences for contraception.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBinary Logistic Regression Model of Respondents’ Ever Use and Current Use by the Interactive Effect of Socio-Demographic and Intervening Variables\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"13\"\u003e \u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eAge Group # Wife Beating\u003c/p\u003e \u003c/th\u003e\u003cth colspan=\"3\" nameend=\"c4\" namest=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003eEver Use (MICS 2016-17)\u003c/p\u003e \u003c/th\u003e\u003cth colspan=\"3\" nameend=\"c7\" namest=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003eEver Use (MICS 2021)\u003c/p\u003e \u003c/th\u003e\u003cth colspan=\"3\" nameend=\"c10\" namest=\"c8\" style=\"text-align: left;\"\u003e \u003cp\u003eCurrent Use (MICS 2016-17)\u003c/p\u003e \u003c/th\u003e\u003cth colspan=\"3\" nameend=\"c13\" namest=\"c11\" style=\"text-align: left;\"\u003e \u003cp\u003eCurrent Use (MICS 2021)\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth colname=\"c1\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003c/th\u003e\u003cth colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e\u003cth colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e\u003cth colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003c/th\u003e\u003cth colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e\u003cth colname=\"c7\" style=\"text-align: left;\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e\u003cth colname=\"c8\" style=\"text-align: left;\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003c/th\u003e\u003cth colname=\"c9\" style=\"text-align: left;\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e\u003cth colname=\"c10\" style=\"text-align: left;\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e\u003cth colname=\"c11\" style=\"text-align: left;\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003c/th\u003e\u003cth colname=\"c12\" style=\"text-align: left;\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e\u003cth colname=\"c13\" style=\"text-align: left;\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e1.19\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e1.01–1.39\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003e0.88\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003e0.04\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c7\" style=\"text-align: left;\"\u003e \u003cp\u003e0.79–0.99\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c8\" style=\"text-align: left;\"\u003e \u003cp\u003e0.96\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e \u003cp\u003e0.55\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c10\" style=\"text-align: left;\"\u003e \u003cp\u003e0.85–1.09\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c11\" style=\"text-align: left;\"\u003e \u003cp\u003e0.96\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c12\" style=\"text-align: left;\"\u003e \u003cp\u003e0.43\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c13\" style=\"text-align: left;\"\u003e \u003cp\u003e0.88–1.06\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eAge Group\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c7\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c8\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c10\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c11\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c12\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c13\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003e15–24 years (Ref)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c7\" style=\"text-align: left;\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c8\" style=\"text-align: left;\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c10\" style=\"text-align: left;\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c11\" style=\"text-align: left;\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c12\" style=\"text-align: left;\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c13\" style=\"text-align: left;\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003e25–34 years\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e1.07\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e0.13–8.63\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003e29.77\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c7\" style=\"text-align: left;\"\u003e \u003cp\u003e2.02–439.16\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c8\" style=\"text-align: left;\"\u003e \u003cp\u003e4.79\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c10\" style=\"text-align: left;\"\u003e \u003cp\u003e0.96–23.94\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c11\" style=\"text-align: left;\"\u003e \u003cp\u003e1.23\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c12\" style=\"text-align: left;\"\u003e \u003cp\u003e0.72\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c13\" style=\"text-align: left;\"\u003e \u003cp\u003e0.40–3.79\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003e35–49 years\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e0.00–4.12\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003e158.36\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c7\" style=\"text-align: left;\"\u003e \u003cp\u003e6.09–4119.28\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c8\" style=\"text-align: left;\"\u003e \u003cp\u003e5.22\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c10\" style=\"text-align: left;\"\u003e \u003cp\u003e0.36–76.31\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c11\" style=\"text-align: left;\"\u003e \u003cp\u003e1.19\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c12\" style=\"text-align: left;\"\u003e \u003cp\u003e0.85\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c13\" style=\"text-align: left;\"\u003e \u003cp\u003e0.20–7.21\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eEducation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c7\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c8\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c10\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c11\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c12\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c13\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eNo education (Ref)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c7\" style=\"text-align: left;\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c8\" style=\"text-align: left;\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c10\" style=\"text-align: left;\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c11\" style=\"text-align: left;\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c12\" style=\"text-align: left;\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c13\" style=\"text-align: left;\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003ePrimary\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e8.18\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e2.63–25.48\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003e3.06\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c7\" style=\"text-align: left;\"\u003e \u003cp\u003e1.25–7.46\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c8\" style=\"text-align: left;\"\u003e \u003cp\u003e3.68\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c10\" style=\"text-align: left;\"\u003e \u003cp\u003e1.41–9.64\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c11\" style=\"text-align: left;\"\u003e \u003cp\u003e1.51\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c12\" style=\"text-align: left;\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c13\" style=\"text-align: left;\"\u003e \u003cp\u003e0.77–2.98\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eSecondary\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e2.36\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e0.35\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e0.40–14.01\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003e3.88\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c7\" style=\"text-align: left;\"\u003e \u003cp\u003e1.45–10.41\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c8\" style=\"text-align: left;\"\u003e \u003cp\u003e8.12\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c10\" style=\"text-align: left;\"\u003e \u003cp\u003e2.86–23.04\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c11\" style=\"text-align: left;\"\u003e \u003cp\u003e1.79\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c12\" style=\"text-align: left;\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c13\" style=\"text-align: left;\"\u003e \u003cp\u003e0.83–3.85\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eHigher\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e9.35\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e0.98–89.29\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c7\" style=\"text-align: left;\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c8\" style=\"text-align: left;\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c10\" style=\"text-align: left;\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c11\" style=\"text-align: left;\"\u003e \u003cp\u003e2.10\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c12\" style=\"text-align: left;\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c13\" style=\"text-align: left;\"\u003e \u003cp\u003e0.27–16.34\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eAge at First Marriage\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e0.97\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e0.64\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e0.85–1.10\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003e1.02\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003e0.65\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c7\" style=\"text-align: left;\"\u003e \u003cp\u003e0.93–1.11\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c8\" style=\"text-align: left;\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e \u003cp\u003e0.94\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c10\" style=\"text-align: left;\"\u003e \u003cp\u003e0.91–1.11\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c11\" style=\"text-align: left;\"\u003e \u003cp\u003e1.08\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c12\" style=\"text-align: left;\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c13\" style=\"text-align: left;\"\u003e \u003cp\u003e1.02–1.15\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eChildren Ever Born\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e0.96\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e0.75\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e0.75–1.23\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003e1.11\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c7\" style=\"text-align: left;\"\u003e \u003cp\u003e0.93–1.34\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c8\" style=\"text-align: left;\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c10\" style=\"text-align: left;\"\u003e \u003cp\u003e0.82–1.22\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c11\" style=\"text-align: left;\"\u003e \u003cp\u003e1.14\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c12\" style=\"text-align: left;\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c13\" style=\"text-align: left;\"\u003e \u003cp\u003e0.99–1.31\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eHusband’s Age\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e0.96\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e0.92–1.01\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003e0.24\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c7\" style=\"text-align: left;\"\u003e \u003cp\u003e0.95–1.01\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c8\" style=\"text-align: left;\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e \u003cp\u003e0.31\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c10\" style=\"text-align: left;\"\u003e \u003cp\u003e0.95–1.02\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c11\" style=\"text-align: left;\"\u003e \u003cp\u003e1.01\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c12\" style=\"text-align: left;\"\u003e \u003cp\u003e0.42\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c13\" style=\"text-align: left;\"\u003e \u003cp\u003e0.98–1.04\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eEthnic Group\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c7\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c8\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c10\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c11\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c12\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c13\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eHausa (Ref)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c7\" style=\"text-align: left;\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c8\" style=\"text-align: left;\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c10\" style=\"text-align: left;\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c11\" style=\"text-align: left;\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c12\" style=\"text-align: left;\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c13\" style=\"text-align: left;\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eIgbo\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e23.32\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e0.1\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e0.58–939.45\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003e2.18\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003e0.33\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c7\" style=\"text-align: left;\"\u003e \u003cp\u003e0.46–10.41\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c8\" style=\"text-align: left;\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c10\" style=\"text-align: left;\"\u003e \u003cp\u003e0.03–34.29\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c11\" style=\"text-align: left;\"\u003e \u003cp\u003e8.38\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c12\" style=\"text-align: left;\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c13\" style=\"text-align: left;\"\u003e \u003cp\u003e2.68–26.17\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eYoruba\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e4.56\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e0.93–22.21\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003e1.61\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003e0.34\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c7\" style=\"text-align: left;\"\u003e \u003cp\u003e0.59–4.37\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c8\" style=\"text-align: left;\"\u003e \u003cp\u003e4.89\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c10\" style=\"text-align: left;\"\u003e \u003cp\u003e1.36–17.58\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c11\" style=\"text-align: left;\"\u003e \u003cp\u003e2.26\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c12\" style=\"text-align: left;\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c13\" style=\"text-align: left;\"\u003e \u003cp\u003e0.99–5.20\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eOther Group\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e0.56\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e0.45\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e0.13–2.51\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003e0.6\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c7\" style=\"text-align: left;\"\u003e \u003cp\u003e0.32–1.94\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c8\" style=\"text-align: left;\"\u003e \u003cp\u003e1.90\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c10\" style=\"text-align: left;\"\u003e \u003cp\u003e0.74–4.85\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c11\" style=\"text-align: left;\"\u003e \u003cp\u003e1.87\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c12\" style=\"text-align: left;\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c13\" style=\"text-align: left;\"\u003e \u003cp\u003e0.99–3.54\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"13\"\u003e\u003cb\u003eNotes: OR\u003c/b\u003e: Odds Ratio \u003cb\u003ep \u0026lt; 0.01 (\u003c/b\u003e), \u003cb\u003ep \u0026lt; 0.05 (*) RC\u003c/b\u003e: Reference Category\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e \u003cp\u003e\u003c/p\u003e \u003cp\u003e \u003cb\u003eModel 2: Binary Logistic Regression Model of Respondents’ Ever and Current Use of Contraceptives by the Combination of Socio-Demographic and Intervening Variables\u003c/b\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab6\" class=\"InternalRef\"\u003e6\u003c/span\u003e reveal maternal age’s association with ever use of contraceptives in both MICS 2016-17 and MICS 2021 though with different trends. In MICS 2016-17, a one-year increase in age increased the likelihood of ever using contraceptives by 21% (OR = 1.21, p \u0026lt; 0.05). However, in MICS 2021, older age was associated with reduced odds of ever using contraceptives (OR = 0.88, p \u0026lt; 0.05). For current use, age was not related in either survey, indicating that age alone does not determine continued contraceptive use.\u003c/p\u003e \u003cp\u003eEducation consistently influenced both ever and current use. Respondents with higher education had significantly higher odds of ever using contraceptives in MICS 2016-17 (OR = 9.00, p \u0026lt; 0.01), though this effect was slightly weaker in 2021 (OR = 3.12, p \u0026lt; 0.05). For current use, education remained important in MICS 2016-17, with respondents having secondary (OR = 9.00, p \u0026lt; 0.01) or primary education (OR = 3.96, p \u0026lt; 0.05) being significantly more likely to use contraceptives. However, in MICS 2021, the association was not statistically significant for all education levels (p \u0026gt; 0.05).\u003c/p\u003e \u003cp\u003eNeither age at first marriage nor children ever born significantly influenced ever use in either dataset (p \u0026gt; 0.05). However, for current use, age at first marriage became significant in MICS 2021, with a one-year increase associated with a 9% higher likelihood of contraceptive use (OR = 1.09, p \u0026lt; 0.05).\u003c/p\u003e \u003cp\u003eBy ethnicity. in MICS 2016-17, Igbo respondents were significantly more likely to have ever used contraceptives (OR = 24.30, p = 0.08) compared to the Hausa. However, this effect was not significant in MICS 2021, indicating a influence on contraceptive uses across ethnic groups over time. For current use, Igbo and Yoruba respondents had significantly higher odds in MICS 2021 (Igbo: OR = 9.00, p \u0026lt; 0.01; Yoruba: OR = 2.40, p \u0026lt; 0.05).\u003c/p\u003e \u003cp\u003eExposure to media did not significantly influence ever use in either dataset (p \u0026gt; 0.05). However, for current use, MICS 2021 showed a strong positive association (OR = 3.42), though it was not significant. Attitudes toward wife beating were not consistently significant for either ever or current use, though the odds ratios suggest that respondents who justified wife beating were more likely to use contraception, especially in MICS 2021 (OR = 2.05, p = 0.12). This finding may indicate that attitudes toward gender roles interact with contraceptive uses in complex ways.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBinary Logistic Regression Model of Respondents’ Ever Use and Current Use of Contraceptives by Socio-Demographic and Intervening Variables\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"13\"\u003e \u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e\u003cth colspan=\"3\" nameend=\"c4\" namest=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003eEver Use (MICS 2016-17)\u003c/p\u003e \u003c/th\u003e\u003cth colspan=\"3\" nameend=\"c7\" namest=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003eEver Use (MICS 2021)\u003c/p\u003e \u003c/th\u003e\u003cth colspan=\"3\" nameend=\"c10\" namest=\"c8\" style=\"text-align: left;\"\u003e \u003cp\u003eCurrent Use (MICS 2016-17)\u003c/p\u003e \u003c/th\u003e\u003cth colspan=\"3\" nameend=\"c13\" namest=\"c11\" style=\"text-align: left;\"\u003e \u003cp\u003eCurrent Use (MICS 2021)\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth colname=\"c1\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003c/th\u003e\u003cth colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e\u003cth colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e\u003cth colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003c/th\u003e\u003cth colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e\u003cth colname=\"c7\" style=\"text-align: left;\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e\u003cth colname=\"c8\" style=\"text-align: left;\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003c/th\u003e\u003cth colname=\"c9\" style=\"text-align: left;\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e\u003cth colname=\"c10\" style=\"text-align: left;\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e\u003cth colname=\"c11\" style=\"text-align: left;\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003c/th\u003e\u003cth colname=\"c12\" style=\"text-align: left;\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e\u003cth colname=\"c13\" style=\"text-align: left;\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e1.21\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e0.03*\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e1.02–1.43\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003e0.88\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003e0.03*\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c7\" style=\"text-align: left;\"\u003e \u003cp\u003e0.78–0.99\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c8\" style=\"text-align: left;\"\u003e \u003cp\u003e0.95\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e \u003cp\u003e0.39\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c10\" style=\"text-align: left;\"\u003e \u003cp\u003e0.83–1.08\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c11\" style=\"text-align: left;\"\u003e \u003cp\u003e0.96\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c12\" style=\"text-align: left;\"\u003e \u003cp\u003e0.37\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c13\" style=\"text-align: left;\"\u003e \u003cp\u003e0.87–1.05\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eAge Group\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c7\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c8\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c10\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c11\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c12\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c13\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003e15–24 years (R)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c7\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c8\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c10\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c11\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c12\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c13\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003e25–34 years\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e0.83\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e0.87\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e0.10–7.07\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003e29.82\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003e0.01*\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c7\" style=\"text-align: left;\"\u003e \u003cp\u003e2.02–441.23\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c8\" style=\"text-align: left;\"\u003e \u003cp\u003e5.52\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e \u003cp\u003e0.04*\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c10\" style=\"text-align: left;\"\u003e \u003cp\u003e1.08–28.23\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c11\" style=\"text-align: left;\"\u003e \u003cp\u003e1.28\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c12\" style=\"text-align: left;\"\u003e \u003cp\u003e0.67\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c13\" style=\"text-align: left;\"\u003e \u003cp\u003e0.41–3.96\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003e35–49 years\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e0.00–2.38\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003e165.76\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003e0.01**\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c7\" style=\"text-align: left;\"\u003e \u003cp\u003e6.26–4388.31\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c8\" style=\"text-align: left;\"\u003e \u003cp\u003e7.62\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c10\" style=\"text-align: left;\"\u003e \u003cp\u003e0.50–116.34\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c11\" style=\"text-align: left;\"\u003e \u003cp\u003e1.21\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c12\" style=\"text-align: left;\"\u003e \u003cp\u003e0.84\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c13\" style=\"text-align: left;\"\u003e \u003cp\u003e0.19–7.58\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eEducation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c7\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c8\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c10\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c11\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c12\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c13\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eNo education (R)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c7\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c8\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c10\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c11\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c12\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c13\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003ePrimary\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e9.00\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e0.00**\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e2.78–29.15\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003e3.12\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003e0.01*\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c7\" style=\"text-align: left;\"\u003e \u003cp\u003e1.27–7.67\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c8\" style=\"text-align: left;\"\u003e \u003cp\u003e3.96\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e \u003cp\u003e0.01*\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c10\" style=\"text-align: left;\"\u003e \u003cp\u003e1.49–10.54\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c11\" style=\"text-align: left;\"\u003e \u003cp\u003e1.54\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c12\" style=\"text-align: left;\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c13\" style=\"text-align: left;\"\u003e \u003cp\u003e0.78–3.05\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eSecondary\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e2.74\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e0.28\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e0.44–16.99\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003e3.92\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003e0.01*\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c7\" style=\"text-align: left;\"\u003e \u003cp\u003e1.45–10.63\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c8\" style=\"text-align: left;\"\u003e \u003cp\u003e9.00\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e \u003cp\u003e0.01**\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c10\" style=\"text-align: left;\"\u003e \u003cp\u003e3.01–26.93\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c11\" style=\"text-align: left;\"\u003e \u003cp\u003e1.88\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c12\" style=\"text-align: left;\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c13\" style=\"text-align: left;\"\u003e \u003cp\u003e0.86–4.08\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eHigher\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e7.66\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e0.70–83.51\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c7\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c8\" style=\"text-align: left;\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c10\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c11\" style=\"text-align: left;\"\u003e \u003cp\u003e1.36\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c12\" style=\"text-align: left;\"\u003e \u003cp\u003e0.81\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c13\" style=\"text-align: left;\"\u003e \u003cp\u003e0.12–15.14\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eEthnic Group\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c7\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c8\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c10\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c11\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c12\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c13\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eHausa (R)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c7\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c8\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c10\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c11\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c12\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c13\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eIgbo\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e24.30\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e0.08\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e0.66–897.58\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003e2.31\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c7\" style=\"text-align: left;\"\u003e \u003cp\u003e0.48–11.12\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c8\" style=\"text-align: left;\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c10\" style=\"text-align: left;\"\u003e \u003cp\u003e0.03–33.77\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c11\" style=\"text-align: left;\"\u003e \u003cp\u003e9.00\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c12\" style=\"text-align: left;\"\u003e \u003cp\u003e0.01**\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c13\" style=\"text-align: left;\"\u003e \u003cp\u003e2.86–28.36\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eYoruba\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e4.10\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e0.81–20.93\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003e1.72\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003e0.29\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c7\" style=\"text-align: left;\"\u003e \u003cp\u003e0.62–4.75\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c8\" style=\"text-align: left;\"\u003e \u003cp\u003e4.83\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e \u003cp\u003e0.02*\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c10\" style=\"text-align: left;\"\u003e \u003cp\u003e1.31–17.85\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c11\" style=\"text-align: left;\"\u003e \u003cp\u003e2.40\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c12\" style=\"text-align: left;\"\u003e \u003cp\u003e0.04*\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c13\" style=\"text-align: left;\"\u003e \u003cp\u003e1.03–5.61\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eOther Ethnic Group\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e0.64\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e0.56\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e0.14–2.88\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c7\" style=\"text-align: left;\"\u003e \u003cp\u003e0.31–1.93\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c8\" style=\"text-align: left;\"\u003e \u003cp\u003e2.06\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c10\" style=\"text-align: left;\"\u003e \u003cp\u003e0.79–5.33\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c11\" style=\"text-align: left;\"\u003e \u003cp\u003e2.01\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c12\" style=\"text-align: left;\"\u003e \u003cp\u003e0.03*\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c13\" style=\"text-align: left;\"\u003e \u003cp\u003e1.06–3.83\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eExposed to Media\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c7\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c8\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c10\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c11\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c12\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c13\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eNot exposed (R)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c7\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c8\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c10\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c11\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c12\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c13\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eExposed\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e1.78\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e0.31\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e0.58–5.43\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c7\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c8\" style=\"text-align: left;\"\u003e \u003cp\u003e1.91\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c10\" style=\"text-align: left;\"\u003e \u003cp\u003e0.74–4.89\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c11\" style=\"text-align: left;\"\u003e \u003cp\u003e3.42\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c12\" style=\"text-align: left;\"\u003e \u003cp\u003e0.34\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c13\" style=\"text-align: left;\"\u003e \u003cp\u003e0.27–43.74\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eWife Beating Attitude\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c7\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c8\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c10\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c11\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c12\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c13\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eNot Justified (R)\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c7\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c8\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c10\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c11\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c12\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c13\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eJustified\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e3.11\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e0.78–12.46\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003e1.82\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003e0.24\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c7\" style=\"text-align: left;\"\u003e \u003cp\u003e0.67–4.94\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c8\" style=\"text-align: left;\"\u003e \u003cp\u003e0.33\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c10\" style=\"text-align: left;\"\u003e \u003cp\u003e0.06–1.88\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c11\" style=\"text-align: left;\"\u003e \u003cp\u003e2.05\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c12\" style=\"text-align: left;\"\u003e \u003cp\u003e0.12\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c13\" style=\"text-align: left;\"\u003e \u003cp\u003e0.84–5.01\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"13\"\u003e\u003cb\u003eNotes: OR\u003c/b\u003e: Odds Ratio \u003cb\u003ep \u0026lt; 0.01 (\u003c/b\u003e), \u003cb\u003ep \u0026lt; 0.05 (*) R\u003c/b\u003e: Reference Category\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e \u003cp\u003e\u003c/p\u003e \u003cp\u003e \u003cb\u003eModel 3: Binary Logistic Regression Model of Respondents’ Ever Use and Current Use by the Interactive Effect of Socio-Demographic and Intervening Variables\u003c/b\u003e \u003c/p\u003e \u003cp\u003eThe findings from Table\u0026nbsp;\u003cspan refid=\"Tab7\" class=\"InternalRef\"\u003e7\u003c/span\u003e reveal the binary logistic regression models indicate a significant interaction effect between respondents' age group and their attitudes toward wife beating on both ever use and current use of the examined service. It was obvious that, among respondents aged 15–24 years who justified wife beating, the odds of ever use were significantly higher in both MICS 2016-17 (OR = 7.05, p \u0026lt; .01, 95% CI: 1.69–29.30) and MICS 2021 (OR = 8.65, p \u0026lt; .01, 95% CI: 3.56–21.02). This suggests that younger respondents who support wife beating may have different behavioural patterns compared to their counterpart who do not justify such attitudes.\u003c/p\u003e \u003cp\u003eSimilarly, for current use, respondents aged 25–34 years who justified wife beating had notably higher odds in MICS 2016-17 (OR = 162.16, p \u0026lt; .02, 95% CI: 2.32–11329.9), highlighting a stark contrast to other age groups. However, in MICS 2021, the effect size decreased (OR = 7.04, p \u0026lt; .17, 95% CI: 0.42–117.38), indicating shifts in behavioural tendencies.\u003c/p\u003e \u003cp\u003eLevel of education also played a critical role in shaping both ever use and current use. Respondents with no formal education who justified wife beating had lower odds of ever use in MICS 2016-17 (OR = 1.00, p = .20, 95% CI: 0.66–7.14) but significantly higher odds in MICS 2021 (OR = 2.71, p = .38, 95% CI: 0.29–25.53). For current use, respondents with primary education who justified wife beating had significantly higher odds in MICS 2016-17 (OR = 5.73, p = .01, 95% CI: 2.53–12.97) but saw a relative decrease in MICS 2021 (OR = 2.13, p = .01, 95% CI: 1.16–3.89). Conclusively, these findings reveal the association between socio-demographic factors in shaping behavioural outcomes.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c12\" colnum=\"12\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c13\" colnum=\"13\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBinary Logistic Regression Model of Respondents’ Ever Use and Current Use by the Interactive Effect of Socio-Demographic and Intervening Variables\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e\u003ccolgroup cols=\"13\"\u003e \u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eAge Group # Wife Beating\u003c/p\u003e \u003c/th\u003e\u003cth colspan=\"3\" nameend=\"c4\" namest=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003eEver Use (MICS 2016-17)\u003c/p\u003e \u003c/th\u003e\u003cth colspan=\"3\" nameend=\"c7\" namest=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003eEver Use (MICS 2021)\u003c/p\u003e \u003c/th\u003e\u003cth colspan=\"3\" nameend=\"c10\" namest=\"c8\" style=\"text-align: left;\"\u003e \u003cp\u003eCurrent Use (MICS 2016-17)\u003c/p\u003e \u003c/th\u003e\u003cth colspan=\"3\" nameend=\"c13\" namest=\"c11\" style=\"text-align: left;\"\u003e \u003cp\u003eCurrent Use (MICS 2021)\u003c/p\u003e \u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c7\" style=\"text-align: left;\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c8\" style=\"text-align: left;\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c10\" style=\"text-align: left;\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c11\" style=\"text-align: left;\"\u003e \u003cp\u003eOR\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c12\" style=\"text-align: left;\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c13\" style=\"text-align: left;\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003e15–24 years # justified\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e7.05\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e0.01**\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e1.69–29.30\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003e8.65\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003e0.00**\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c7\" style=\"text-align: left;\"\u003e \u003cp\u003e3.56–21.02\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c8\" style=\"text-align: left;\"\u003e \u003cp\u003e39.49\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e \u003cp\u003e0.01*\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c10\" style=\"text-align: left;\"\u003e \u003cp\u003e2.67–584.90\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c11\" style=\"text-align: left;\"\u003e \u003cp\u003e5.09\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c12\" style=\"text-align: left;\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c13\" style=\"text-align: left;\"\u003e \u003cp\u003e0.53–48.53\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003e25–34 years # not justified\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e75.34\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e0.01**\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e4.57–1240.7\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003e23.95\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003e0.01**\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c7\" style=\"text-align: left;\"\u003e \u003cp\u003e2.39–239.73\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c8\" style=\"text-align: left;\"\u003e \u003cp\u003e9.56\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e \u003cp\u003e0.01**\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c10\" style=\"text-align: left;\"\u003e \u003cp\u003e3.57–25.56\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c11\" style=\"text-align: left;\"\u003e \u003cp\u003e8.04\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c12\" style=\"text-align: left;\"\u003e \u003cp\u003e0.01**\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c13\" style=\"text-align: left;\"\u003e \u003cp\u003e4.21–15.33\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003e25–34 years # justified\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e7.06\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e0.01**\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e1.61–31.01\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003e13.76\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003e0.00**\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c7\" style=\"text-align: left;\"\u003e \u003cp\u003e5.58–33.92\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c8\" style=\"text-align: left;\"\u003e \u003cp\u003e162.16\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e \u003cp\u003e0.02*\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c10\" style=\"text-align: left;\"\u003e \u003cp\u003e2.32–11329.9\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c11\" style=\"text-align: left;\"\u003e \u003cp\u003e7.04\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c12\" style=\"text-align: left;\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c13\" style=\"text-align: left;\"\u003e \u003cp\u003e0.42–117.38\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003e35–49 years # not justified\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e50.22\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e0.00**\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e3.43–736.00\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003e12.28\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c7\" style=\"text-align: left;\"\u003e \u003cp\u003e0.94–159.89\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c8\" style=\"text-align: left;\"\u003e \u003cp\u003e8.81\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e \u003cp\u003e0.00**\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c10\" style=\"text-align: left;\"\u003e \u003cp\u003e3.14–24.75\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c11\" style=\"text-align: left;\"\u003e \u003cp\u003e6.26\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c12\" style=\"text-align: left;\"\u003e \u003cp\u003e0.01**\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c13\" style=\"text-align: left;\"\u003e \u003cp\u003e3.11–12.60\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003e35–49 years # justified\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c7\" style=\"text-align: left;\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c8\" style=\"text-align: left;\"\u003e \u003cp\u003e65.77\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e \u003cp\u003e0.02*\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c10\" style=\"text-align: left;\"\u003e \u003cp\u003e2.12–2041.14\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c11\" style=\"text-align: left;\"\u003e \u003cp\u003e21.89\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c12\" style=\"text-align: left;\"\u003e \u003cp\u003e0.01*\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c13\" style=\"text-align: left;\"\u003e \u003cp\u003e1.68–284.35\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003e\u003cb\u003eEducation # Wife Beating\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c7\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c8\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c10\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c11\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c12\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd colname=\"c13\" style=\"text-align: left;\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eNo education # justified\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e0.66–7.14\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003e2.71\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003e0.38\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c7\" style=\"text-align: left;\"\u003e \u003cp\u003e0.29–25.53\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c8\" style=\"text-align: left;\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e \u003cp\u003e0.01**\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c10\" style=\"text-align: left;\"\u003e \u003cp\u003e2.53–12.97\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c11\" style=\"text-align: left;\"\u003e \u003cp\u003e1.45\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c12\" style=\"text-align: left;\"\u003e \u003cp\u003e0.76\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c13\" style=\"text-align: left;\"\u003e \u003cp\u003e0.13–16.12\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003ePrimary # not justified\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e2.17\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e0.04*\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e1.06–10.58\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003e2.67\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003e0.01**\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c7\" style=\"text-align: left;\"\u003e \u003cp\u003e1.29–5.54\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c8\" style=\"text-align: left;\"\u003e \u003cp\u003e5.73\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e \u003cp\u003e0.61\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c10\" style=\"text-align: left;\"\u003e \u003cp\u003e0.01–11.84\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c11\" style=\"text-align: left;\"\u003e \u003cp\u003e2.13\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c12\" style=\"text-align: left;\"\u003e \u003cp\u003e0.01*\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c13\" style=\"text-align: left;\"\u003e \u003cp\u003e1.16–3.89\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003ePrimary # justified\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e0.46–40.08\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003e0.01**\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c7\" style=\"text-align: left;\"\u003e \u003cp\u003e2.60–10.15\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c8\" style=\"text-align: left;\"\u003e \u003cp\u003e0.42\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e \u003cp\u003e0.01**\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c10\" style=\"text-align: left;\"\u003e \u003cp\u003e3.29–18.23\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c11\" style=\"text-align: left;\"\u003e \u003cp\u003e0.47\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c12\" style=\"text-align: left;\"\u003e \u003cp\u003e0.63\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c13\" style=\"text-align: left;\"\u003e \u003cp\u003e0.02–10.55\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eSecondary # not justified\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e3.35\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e0.04*\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e1.06–10.58\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003e5.14\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003e0.01**\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c7\" style=\"text-align: left;\"\u003e \u003cp\u003e2.60–10.15\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c8\" style=\"text-align: left;\"\u003e \u003cp\u003e7.75\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e \u003cp\u003e0.01**\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c10\" style=\"text-align: left;\"\u003e \u003cp\u003e3.29–18.23\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c11\" style=\"text-align: left;\"\u003e \u003cp\u003e3.54\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c12\" style=\"text-align: left;\"\u003e \u003cp\u003e0.01**\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c13\" style=\"text-align: left;\"\u003e \u003cp\u003e2.02–6.18\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eSecondary # justified\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c7\" style=\"text-align: left;\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c8\" style=\"text-align: left;\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c10\" style=\"text-align: left;\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c11\" style=\"text-align: left;\"\u003e \u003cp\u003e1.68\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c12\" style=\"text-align: left;\"\u003e \u003cp\u003e0.52\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c13\" style=\"text-align: left;\"\u003e \u003cp\u003e0.35–7.99\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eHigher # not justified\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e4.27\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c7\" style=\"text-align: left;\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c8\" style=\"text-align: left;\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c10\" style=\"text-align: left;\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c11\" style=\"text-align: left;\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c12\" style=\"text-align: left;\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c13\" style=\"text-align: left;\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colname=\"c1\" style=\"text-align: left;\"\u003e \u003cp\u003eHigher # justified\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c2\" style=\"text-align: left;\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c3\" style=\"text-align: left;\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c4\" style=\"text-align: left;\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c5\" style=\"text-align: left;\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c6\" style=\"text-align: left;\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c7\" style=\"text-align: left;\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c8\" style=\"text-align: left;\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c9\" style=\"text-align: left;\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c10\" style=\"text-align: left;\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c11\" style=\"text-align: left;\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c12\" style=\"text-align: left;\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003ctd colname=\"c13\" style=\"text-align: left;\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003ctfoot\u003e\u003ctr\u003e\u003ctd colspan=\"13\"\u003eNotes: OR: Odds Ratio p \u0026lt; 0.01 (), p \u0026lt; 0.05 (*)\u003c/td\u003e\u003c/tr\u003e\u003c/tfoot\u003e\u003c/table\u003e\u003c/div\u003e \u003cp\u003e\u003c/p\u003e "},{"header":"Discussion of findings","content":"\u003cp\u003eThis study examined trends and determinants of ever and current use of modern contraceptives among the urban poor women in Nigeria. The study extracted data from three series of data collection points to tease out information on the changes in use of modern contraception over the course of two decades, as well as the drivers of these changes. Salient findings were derived from this study. The low prevalence of contraceptive use among the urban poor women indicated a slight decrease of current use of contraceptives between 2011 and 2017, however, there was an increase in 2021. Although was a decline in current use of contraceptive use between 2011 and 2017, however, there was a surge in contraceptive prevalence in 2021 which is almost similar to the contraceptive prevalence rate report in the 2018 Nigeria Demographic and Health Survey. (National Population Commission (NPC) [Nigeria] and ICF, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). The plausible explanation for the decline and further resurgence could be a lag in family planning intervention period across the time frame. Results of previous studies align with this (Alirol et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Fadeyibi et al., \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Policies on promoting family planning should be strengthened, especially among the urban poor women in Nigeria. Similarly, the results showed that ever use of contraceptives among urban poor women recorded a significant in increase. This is an indication of increase in those who ever used modern contraceptive among the urban poon in Niger. Women who reported to have ever used modern contraceptive were expected to have higher prevalent because the population of urban poor women would increase over time. However, the prevalence of ever use of modern contraceptives among urban poor women is surprising as it is lower than current use. Previous studies have reported higher prevalence of modern contraceptives, though in the general urban population (Dambo et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). This finding is in contrast with previous studies, although ever use of modern contraceptives is expected to be lower than current use if family planning programmes and interventions are effective. Policies should be made to promote the use of contraceptives, especially in urban poor contexts.\u003c/p\u003e\u003cp\u003eAt the bivariate analysis, the study showed age of women was significantly related to ever use of modern contraceptives. The use of modern contraceptives increases as age increases. In addition, age was also significantly related to current use of modern contraception throughout the three rounds of data points. At multivariable analysis, age of women was also significantly related to ever of contraceptives with older women more likely to use, even when intervening variables were controlled for. This is reasonable because age depicts lifetime exposure to using contraception. Previous studies have established that who have almost completed their childbearing adopt family planning to prevent unwanted pregnancy (Dambo et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Tekelab et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Policies should target younger women more to reduce unwanted pregnancies. The result also showed that education was significantly related to ever use of modern contraceptives. In like manner, level of education was significantly related to current use of modern contraception in 2016 and 2021 rounds of data sets. At multivariate level, women with primary and secondary education had higher odds of ever use of modern contraceptives even when other control variables were factored into the model. This result is in agreement with prior studies (Ba et al., \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Taingson et al., \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). The plausible reason for this is that advancement in education brings forth knowledge of family planning and opportunities cost of having many children decreases. Educated women, even the urban poor plan their childbearing. Policies should target both the educated and uneducated women to increase family planning demand generation.\u003c/p\u003e\u003cp\u003eMarital status was also associated with ever and current use of modern contraceptives. Married women were more likely to ever use and currently using modern contraceptives. These results are in consonance with prior research which argued that married women planned their childbearing with a view to achieving their desired family size (Andreoli et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Najimudeen, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The plausible reasons are: marriage exposes women to frequent coitus interruptus and family planning awareness during antenatal or postnatal health visit. Policies should target married women for family planning demand generation during maternal and child healthcare programmes.\u003c/p\u003e\u003cp\u003eEthnicity was significantly related to ever and current use of modern contraceptives. The Yoruba were more likely to use modern contraceptive compared to other ethnic groups. This result echoes what was reported in the 2018 Nigeria Demographic and Health Survey. In the survey, the Yoruba ethnic group had higher modern contraceptive prevalence rate. Other ethnic groups, especially the Hausa/ Fulani should be targeted for family planning demand generation. Similarly, the Northern region had lower ever use of modern contraceptives compared to the South while all the regions had influence on current use of modern contraceptives. Previous studies have reported regional variations in modern contraception, with the Northern part having lower rate (National Population Commission (NPC) [Nigeria] and ICF, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Obasohan, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). The plausible reasons find meaning in the culture of early childbearing and polygynous marriage. Interventions should aim at promoting family planning in the Northern region.\u003c/p\u003e\u003cp\u003eHaving ever given birth was significantly related to current use of modern contraceptives. The result is in tandem with prior studies which established that women who had given birth were more informed about the use of modern contraceptives compared to those who have not (Apanga \u0026amp; Adam, 2015; Hanley et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Exposure to radio was significantly related to ever and current use of modern contraception. Previous studies have shown that radio had wider reach than other mass sources, especially among the urban poor who may lack access to television and other sophisticated mass media (Dambo et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Ezire et al., \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). More radio jingles should be promoted to increase family planning among the urban poor women.\u003c/p\u003e\u003cp\u003eMoreover, the results showed the interactive effect of age of women and attitude toward wife beating were significantly related to ever and current use of modern contraceptive. This result is in contrast with previous studies (Abate \u0026amp; Tareke, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Bamiwuye, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Ridlo et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Women who encourage wife beating are less more likely to adopt contraception regardless of age. This is unexpected because such women who approve of wife beating lack empowerment and independent decision-making in the household. It might also be that women who approve of wife beating lacked safe sex negotiation and as such, use contraception to prevent unwanted pregnancy.\u003c/p\u003e\u003cp\u003eThe result also revealed interactive effect of education and wife beating on ever and current use of contraceptives. The result findings showed that women who approved of wife beating are more likely to adopt modern contraception is contrary to previous studies which emphasized that wife beating is a manifestation of lack of women empowerment and more prominent among less-educated women (Danaan, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Fasina \u0026amp; Oduaran, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). However, contraceptives were more utilised among women who approved of wife beating regardless of level of education. The possible reason could be that some women are dominated in marital union and lack respondent agency regardless of their level of education. The implication of this is that wife beating, and the level of education did not limit the use of contraceptives.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study examines the trends and determinants of modern contraceptive use among urban poor women in Nigeria, highlighting disparities in access to family planning services. Using data from the Nigeria Multiple Indicator Cluster Surveys (MICS) for 2011, 2016-17, and 2021, the study analysed changes in contraceptive prevalence and identified key socio-economic and demographic factors influencing use. Findings revealed a decline in contraceptive use between 2011 and 2016-17, followed by a rise in 2021. Ever-use of contraceptives also increased over time. Age, education, ethnicity, geographic location, and media exposure played significant roles in shaping contraceptive behaviours. The study underscores the interactive effects of these determinants, emphasizing the need for targeted interventions to address persistent inequalities and improve family planning access among urban poor women.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eInstitutional Review Board Statement\u003c/h2\u003e \u003cp\u003eThe study was based on the analysis of openly available data. Thus, ethical approval was not necessary.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eClinical Trial\u003c/strong\u003e \u003cp\u003eNot Applicable.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eConflicts of Interest:\u003c/h2\u003e \u003cp\u003eThe authors declare no conflict of interest.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eEthical Approval:\u003c/strong\u003e \u003cp\u003eThe data used in this research was obtained from the UNICEF Nigeria Multiple Indicator Cluster Survey conducted in the years 2011, 2016-17, and 2021. In August 2021, the protocol for the UNICEF Nigeria Multiple Indicator Cluster Survey (MICS) was accepted by both the steering committee and a review committee composed of members from the Technical Committee.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent to Participate:\u003c/strong\u003e \u003cp\u003eEach participant provided verbal consent and received comprehensive information regarding the voluntary nature of their participation, as well as the guarantee of confidentiality and anonymity regarding their personal information. The participants were provided with information regarding their entitlement to decline answering any or all of the questions, as well as to terminate the interview at any point. The UNICEF Nigeria MICS datasets may be accessed by the public via the official website \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://mics.unicef.org/surveys\u003c/span\u003e\u003cspan address=\"https://mics.unicef.org/surveys\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Additionally, authorization was obtained to use these datasets.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent for publication:\u003c/strong\u003e \u003cp\u003eSince this analysis relies solely on secondary anonymised MICS datasets, no further consent to publish was necessary.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding:\u003c/h2\u003e \u003cp\u003eThis research received no external funding.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eS. O. I., O. S. B and B.L.S conceptualized and designed the study, developed the methodology and models. S. O. I. implemented the formal analysis and interpreted with support from T. E. O. Also, O. S. B, B.L.S. and T. E. O. reviewed the analysis and interpretation of the results while S. O. I and T. E. O. drafted, reviewed and edited the manuscript. All authors have read and agreed to publish this version of the manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgement\u003c/h2\u003e\u003cp\u003eThe authors are grateful to NBS and UNICEF, Nigeria for granting the authors the request to use the Multiple Indicator Cluster Survey (MICS) Data.\u003c/p\u003e\u003ch2\u003eData Availability\u003c/h2\u003e\u003cp\u003eThe data can be accessed here: [https://mics.unicef.org/](https:/mics.unicef.org)Access via UNICEF is granted through a simple sign-in process, where users provide basic identification, professional details, and a summary of their intended research activities. Additionally, I have been granted authorization to obtain and use these datasets.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAbate MG, Tareke AA. (2019). \u003cem\u003eIndividual and community level associates of contraceptive use in Ethiopia: a multilevel mixed effects analysis\u003c/em\u003e. 1\u0026ndash;12.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAhmed S, Li Q, Liu L, Tsui AO, Bill F, Foundation MG. Maternal deaths averted by contraceptive use: an analysis of 172 countries. Lancet. 2012;380(9837):111\u0026ndash;25. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1016/S0140-6736(12)60478-4\u003c/span\u003e\u003cspan address=\"10.1016/S0140-6736(12)60478-4\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAlirol E, Getaz L, Stoll B, Chappuis F, Loutan L. 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(2021). \u003cem\u003eAbortion\u003c/em\u003e.\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":"discover-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Discover Public Health](https://link.springer.com/journal/12982)","snPcode":"12982","submissionUrl":"https://submission.springernature.com/new-submission/12982/3","title":"Discover Public Health","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"modern contraceptive, urban poor, trend, differentials, ever use of contraceptive, current use","lastPublishedDoi":"10.21203/rs.3.rs-8679049/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8679049/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eUnderstanding the trends and determinants of modern contraceptive use among urban-poor women is crucial for addressing disparities in family planning services. This study analyzed the prevalence of modern contraceptive use from 2011 to 2021, assessed socio-economic and demographic differentials, identified key drivers, and evaluated the interactive effects of these determinants. The aim was to provide evidence-based insights into the trends and determinants of contraceptive use among urban-poor women in Nigeria.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eUsing a cross-sectional design, secondary data from the Nigeria UNICEF Multiple Indicator Cluster Survey (MICS) for 2011, 2016-17, and 2021 were analyzed. The sample consisted of women in metropolitan areas within the poorest and poor wealth quintiles. Data analysis involved univariate, bivariate, and multivariate analyses.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe prevalence of current contraceptive use declined from 14.6% in 2011 to 6.1% in 2016-17, then increased to 12.8% in 2021. Ever-use rose from 3.2% in 2016-17 to 7.1% in 2021. Age, marital status, childbirth history, and region significantly influenced ever-use, while age, education, and region of residence influenced current use across all survey periods. Ethnicity, media exposure significantly influences ever-use and current use, while spousal age difference influenced current use. The interactive effects of socio-demographic and intervening variables were strongly associated with contraceptive use, in 2016-17 and 2021 surveys.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eThe findings revealed dynamic trends and persistent socio-economic disparities in contraceptive use among urban-poor women. Despite some progress in recent years, the study highlights the need for targeted interventions addressing demographic and socio-economic determinants to improve access to family planning services.\u003c/p\u003e","manuscriptTitle":"TRENDS, DIFFERENTIALS AND DETERMINANTS OF MODERN CONTRACEPTIVE USE AMONG URBAN POOR WOMEN IN NIGERIA","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-13 15:58:27","doi":"10.21203/rs.3.rs-8679049/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-03-25T05:21:23+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-19T08:52:11+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-11T13:46:25+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"320462484811182635888953393908170023782","date":"2026-03-01T06:48:39+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"139250397187652680463938837685832127902","date":"2026-02-20T07:05:59+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-02-07T21:42:04+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-02-07T20:53:20+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-01-30T03:19:20+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-01-29T09:46:39+00:00","index":"","fulltext":""},{"type":"submitted","content":"Discover Public Health","date":"2026-01-29T09:03:10+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"discover-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Discover Public Health](https://link.springer.com/journal/12982)","snPcode":"12982","submissionUrl":"https://submission.springernature.com/new-submission/12982/3","title":"Discover Public Health","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"53ae4e56-85f8-4aee-9516-c86ee0e3e714","owner":[],"postedDate":"February 13th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-19T10:54:43+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-13 15:58:27","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8679049","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8679049","identity":"rs-8679049","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}