Modern Contraceptive Use Behavior among Young Married Women in Urban Settings of Ethiopia: A Multilevel Analysis

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This situation has had adverse consequences on the reproductive health outcomes of young women. Thus, this study was conducted to identify main determinants of young women’s contraceptive use in selected urban cities of Ethiopia. The findings of this study informed the design strategies to increase young women’s contraceptive use. Methods A dataset consisting of 680 young married women aged between 18 and 29 years was extracted from a secondary source and analyzed using STATA version 18 from a cross-sectional study, which was conducted from December 12, 2021 to January 21, 2022, in 13 selected urban cities. A multilevel logistic regression modeling techniques was used to identify the determinants of contraceptives (individual-level factors) and control for variations caused by differences between cities. Results Four hundred one (59% CI: 0.55–0.63) young women used contraceptives at the time of data collection. The most common contraceptive methods were injectables (42%) and implants (35%). High contraceptive use variability was observed across cities. About 16% variability of contraceptive use was observed at the intercept model analysis without factors and a 13% variability in contraceptive use across cities at the final model of multilevel analysis. The lowest contraceptive use was observed in Jigjiga (10%, CI = 0.03–0.24) and the highest was in Hawassa (81%, CI = 0.70–0.89). The analysis result indicated that individual-level variables such as young women who had more than two family members (AOR = 3.3, 95% CI = 2.04–5.27), who had knowledge of contraceptive methods (AOR = 2.6, 95% CI = 1.43–4.83) and who had radio exposure (AOR = 1.6, 95% CI = 1.13–2.32) were significantly associated with their contraceptive use behavior. Conclusion The study shows higher levels of contraceptive use among young women in the selected cities as compared with the national target of 50% for 2024/25. Increasing radio listenership about contraceptive use, supported by other interventions that enhance comprehensive knowledge can be an effective strategy to improve contraceptive use among young married women in cities. Contraceptive use exposure to media family size multilevel analysis young married women Figures Figure 1 Figure 2 Background The right to access Sexual and Reproductive Health (SRH) services and information can significantly reduce child marriage, teenage pregnancy, and the spread of sexually transmitted infections ( 1 ). The utilization of contraceptives among young women brings about substantial advantages for their health and society. It plays a crucial role in postponing pregnancies in young girls who are at risk for health complications arising from early childbearing. By reducing the occurrence of unintended pregnancies, we can significantly reduce the demand for unsafe abortions, curb the transmission of sexually transmitted infections, and avert pregnancy-related fatalities. This reduction can further support the pursuit of education for girls and empowers young women to actively participate in society, including through paid employment( 2 ) ( 3 ). In 2019, the estimated percentage of adolescent women who used modern contraceptive methods was 9.1% globally with 7.4 to 12.8 uncertainty interval ( 4 ). A study conducted in 29 countries within Sub-Saharan Africa (SSA) revealed that 24.7% of Adolescent Girls and Young Women (AGYW) in these countries utilize modern contraception. Among the countries included, Lesotho demonstrated the highest prevalence of modern contraceptive use among AGYW, with a rate of 59.2%. On the other hand, Chad exhibited the lowest prevalence, with only 5.1% of AGYW using modern contraceptives ( 5 ). In Ethiopia, young married women’s (age 15 to 24 years) use of modern contraceptives increased from 6% in 2000 to 16% in 2005 and to 36% in 2011 based on the three EDHS ( 6 ). However, it has since seemed to have declined as the 2019 EDHS data showed the prevalence of modern contraceptive use among young women at only 17% on average ( 7 ). Among young preparatory school students aged 15 to 22 years, the proportion of individuals who had undergone induced abortion at some point in their lifetime was high, 13.6% based on a study conducted in Southern Region of Ethiopia ( 8 ). Further, a systematic review illustrated that the prevalence of unintended pregnancy in Ethiopia was 28% in general, mainly occurring among women who do not use any form of contraception ( 9 ). Among the challenges in designing social behavior change interventions to improve contraceptive use behavior among young urban women in Ethiopia is insufficient evidence regarding determinants for contraceptive use behavior. This study is, therefore, conducted to examine contraceptive use among married young women aged 18 to 29 and identify associated factors in Ethiopia. The findings of this study are used by sexual health service implementers, partners and policymakers who are working to improve SRH among young women. Methods Study design and setting This study was conducted in major cities of Ethiopia identified as targets for Kefeta Integrate Youth Activities, namely: Adama, Addis Ababa, Assosa, Bahir Dar, Bishoftu, Dilla, Dire Dewa, Gambella, Harar, Jigjiga, Jimma, Hawassa, and Shashemenie. Youth, youth-serving organizations, and policy actors in these cities and higher education institutions found in the cities were targets for this study. According to data from the World Health Organization trendline, the number of women of reproductive age in Ethiopia amounts to 31,664 individuals (10). Data source This study utilized secondary data from the original formative assessment data set of the USAID-funded Integrative Youth Activities Project. The dataset consisted of 3,215 young people aged 18 to 29 years who were from community and HEI (Higher Education Institution) settings. Data collection took place from December 12, 2021, through January 21, 2022, across 13 cities. A total of 680 young married women data extracted and analyzed. Study variables The dependent variable in this study is the use of modern contraceptive methods at the time of data collection. The “Yes” category comprises individuals themselves or their husbands who are currently using a range of modern contraceptive methods, including pills, implants, injectables, intrauterine devices (IUDs), condoms, emergency contraceptives, standard days method (SDM), the lactational amenorrhea method, and female sterilization. The category referred to as “No” encompasses individuals who employ contraceptive methods such as the rhythm method, withdrawal, other traditional methods, and no contraceptive method at all. This study includes the following independent variables: respondent age (18 to 24 years, 25-29 years), exposure to radio media (yes, no), exposure to TV media (yes, no), knowledge about contraceptives (labeled as ‘yes’ if the respondents know at least two contraceptive methods and no if respondents know only one contraceptive method), family size (labeled as ‘yes’ if the respondents’ family size is less than three and ‘no’ if the respondents’ family size is greater than or equal to three). Additionally, the presence of partner communication norms was assessed using a composite of three variables: (1) a girl can suggest to her boyfriend that he can use a condom, (2) it wouldn’t be too embarrassing for someone like me to buy or obtain condoms, and (3) if a girl suggested using condoms to her partner, it wouldn’t mean that she didn’t trust him. Data analysis Descriptive statistics were used to summarize: the contraceptive use among young women in selected urban cities of Ethiopia, the distribution of contraceptive use across cities and individual-level factors, sources for obtaining contraceptives and contraceptive information sources. Data were analyzed using STATA Version 18 software. Data quality assurance and control procedures were applied throughout the data collection fieldwork. A multilevel binary logistic regression analysis was done to measure the association between contraceptive use and the variation across cities. Cities were considered as random effects to cater for the unexplained variability at the individual-level. The selection of variables for the multilevel models was based on their statistical significance at the bivariate analysis at a p < 0.05. Further, the statistical significance of the associations between each of the factors and current use of contraceptives was determined at a p-value of less than 0.05. Two models, comprising the null model (model 0) and model 1 were fitted. Model 0 showed the variance in modern contraceptive use attributed to the clustering of the primary sampling units without the explanatory variables. Model 1 is progressive containing the individual factors: age, media exposure through radio, media exposure through TV, knowledge on contraceptives, family size & partner communication norms. Model comparison was done using the log likelihood and Akaike’s Information Criterion (AIC) tests. The lowest AIC (818.3) and highest log likelihood (−401.2) were used to determine the best fit model. For model one, Odds ratio and associated 95% confidence intervals (CIs) were calculated. Using the variance inflation factor (VIF), a test for multicollinearity was done and there was no evidence of high collinearity. Operational definition In this study, the term “young women” refers to individuals aged 18 to 29. “Media exposure” refers to those young married women who had listened to radio or watched to television at least once a week. The study categorized modern contraceptive methods as pills, implants, injectables, intrauterine devices (IUDs), condoms, emergency contraceptives, the standard days method (SDM), the lactational amenorrhea method, and female sterilization. On the other hand, the rhythm method and withdrawal method were classified as traditional contraceptive methods (11). Respondents who demonstrated knowledge on at least two types of the contraceptive methods were considered to be knowldgeable. Ethics declarations Ethics approval and consent to participate The study proposal was reviewed and approved by the Institutional Review Board (IRB) of the Ethiopian Public Health Association (EPHA) before any data collection activities commenced. Permission was obtained from the administrations of participating cities. Before interviews were conducted, all interviewees were provided with adequate information about the purpose of the study, contents of interviews, and contact details of the principal investigator (PI) and IRB chairperson. Verbal consent was obtained from each informant before they were interviewed. Results Sociodemographic characteristics of respondents Among the 680 young married women selected for this study, 653 (96%) were those selected from a community setting and 27 (4%) were from HEIs. Eleven (2%) were young women with physical disabilities. The median age was 25 years with an interquartile range of 5 years. More than 60% (415) of the respondents were between ages of 25-29 years while the remaining (267) were in the age group of 18-24 years. Respondents from Addis Ababa were 81 (12%), Adama 78 (12%), Assosa 26 (4%), Bahir Dar 63 (9%), Bishoftu 36 (5%), Dilla 33 (5%), Dire Dewa 68 (10%), Gambella 56 (8%), Harar 24 (4%), Hawassa 74 (11%), Jigjiga 39 (6%), Jimma 55 (8%) and Shashemenie 47 (7%) were interviewed. The following table provides a summary of the sociodemographic characteristics of the respondents ( Table 1 ). Table 1 Background characteristics of respondents Characteristics % Age group 18 to 24 39.3 25 to 29 60.7 Education status No formal education 7.1 Primary school students 37.2 Secondary school students 28.1 TVET attendant or graduate 14.0 University attendant or graduate 13.7 Disability status No disability 98.4 Youth with disability 1.6 Media exposure (radio) No 57.7 Yes 42.3 Media exposure (TV) No 16.0 Yes 84.0 Knowledge on contraceptives No (knows only one contraceptive method) 14.9 Yes (knows at least two contraceptive methods) 85.2 Existence of partner communication norm with couples No 35.7 Yes 64.3 Family size Less than 3 family size 17.5 Greater than or equal to 3 family size 82.5 Currently attending school No 94.0 Yes 6.0 Working mostly in the past 12 months No 70.9 Yes 29.1 Contraceptive use The result of this study illustrated those young women’s contraceptive use was 401 (59%) and the most used contraceptive methods were injectables (n=171, 42%), followed by implants (n=143, 35%) and pills (n=55, 14%) as shown in the figure below. Contraceptive use slightly differed by age group; 246 (60%) young women within the age group of 25 to 29 years and 155 (58%) young women within the age group of 18 to 24 years were currently using contraceptives ( Fig. 1 ). Fig. 1 High contraceptive use variability was observed across cities. The prevalence of contraceptive use among young married women in Jigjiga and Harar was found to be low in the range of 10% and 29%. The highest uptake of contraceptives was observed among the target population in Adama and Hawassa in the range of 65% to 81% ( Fig. 2 ). Fig. 2 Knowledge of contraceptives Most of the youth respondents (643, 94.6%) have heard about family planning methods. Five hundred seventy nine (85%) young married women knew at least two types of contraceptive methods. The most known methods were injectables (575, 85%), followed by pills (531, 78%) and implants (516, 76%). The least known methods were withdrawal 62 (9.1%) and male sterilization 64 (9.4%). Sexual and reproductive health information Exposure to messages related to SRH was assessed among youth and almost half of the young married women (334, 49%) had received SRH-related information from any source in the preceding three months. The most common SRH message sources for the young married women were TV (199, 29%), followed by health facilities (171, 25%) and social media (59, 9%). Sources of contraceptive Health centers were the most common sources of SRH services (181, 27%) for young married women, followed by government hospitals (61, 9%) and private health facilities (47, 7%). Association between individual factors and youth’s contraceptive use among young married women in Ethiopia The multilevel logistic regression analysis illustrated that individual-level factors, such as young married women who had more than two family members, knowledge about family planning, and listened to the radio at least once a week, were significantly associated with contraceptive use ( Table 2 ). Table 2 Mixed effect multilevel logistic regression analysis of factors associated with contraceptive use Covariates Contraceptive use COR (95% CI) Model-I AOR (95% CI) Yes No Age group 18 to 24 years 155 (58.1%) 112 (42.0%) Ref Ref 25 to 29 years 246 (60.0%) 167 (40.4%) 1.1 (0.78, 1.46) 0.9 (0.64, 1.37) Media exposure (radio) No 207 (52.8%) 185 (47.2%) Ref Ref Yes 194 (67.4%) 94 (32.6%) 1.8 (1.34, 2.53) 1.6 (1.13, 2.32) * Media exposure (TV) No 58 (53.2%) 51 (46.8%) Ref Ref Yes 343 (60.1%) 228 (39.9%) 1.3 (0.88, 2.00) 1.1 (0.69, 1.81) Knowledge on contraceptives No 41 (40.6%) 60 (59.4%) Ref Ref Yes 360 (62.2%) 219 (37.8%) 2.4 (1.56, 3.70) 2.6 (1.43, 4.83) * Communication norm with partners No 23 (56.1%) 18 (43.9%) Ref Ref Yes 378 (59.2%) 261 (40.9%) 1.1 (0.60, 2.14) 0.8 (0.39, 1.79) Family size Less than 3 family size 44 (38.6%) 70 (61.4%) Ref Ref Family size of atleast 3 341 (63.3%) 198 (36.7%) 2.7 (1.81, 4.15) 3.3 (2.04, 5.27) * *P-value<0.05. Model fitness Log likelihood ratios and Akaike’s Information Criterion (AIC) were used to check model fitness for the multilevel models. Controlling more predictor variables (age, media exposure through radio, media exposure through TV, knowledge on contraceptives, family size & partner communication norms), the final mixed effect model resulted in significantly reduced contraceptive use variability across cities as compared to the intercept only model ( Table 3 ). Table 3 Multilevel analysis model building, and contraceptive use variability across cities in Ethiopia. Models process ICC AIC LLR Contraceptive use variability across cities- without predictors -Fixed effect model 0.155 883.2 -439.6 Contraceptive use variability across cities – with adding age 0.158 884.3 -439.1 Contraceptive use variability across cities - with adding media exposure through radio 0.142* 878.8 -435.4 Contraceptive use variability across cities- with adding media exposure through TV 0.140 880.3 -435.1 Contraceptive use variability across cities – with adding knowledge on contraceptives 0.123* 874.5 -431.3 Contraceptive use variability across cities- with adding partner communication norm 0.123 876.5 -431.3 Contraceptive use variability across cities- with adding family size (all predictors)- Mixed effect model 0.125* 818.3 -401.2 ICC in the random intercept model is 0.155, AIC value is 883.2 and LLR is -439.6, The acronym ICC- intraclass correlation coefficient, AIC-Akaike's Information Criteria, LLR- log likelihood ratio. Discussion This study found that 401 (59%) of young married women in the selected cities used contraceptive. Having more than two family members, knowledge on contraceptive and exposure to radio were identified as individual-level predictors of contraceptive use among young married women. This study discovered that the utilization of contraceptives among young married women surpassed the targeted national contraceptive rate of 50% set for the years 2024-2025 (12). This could be due to higher listenership of SRH-related messages among young married women residing in urban cities. The 2019 Ethiopian Mini Demographic and Health Survey data indicated that the prevalence of modern contraceptive use among young married women aged 15 to 24 was only 17% on average (7). Another study conducted in Malawi indicated that 31% of young women used contraceptive (13). The study illustrated that young women who had more than two members in their family were more likely to use contraceptives. Consistent to this finding, analysis of 2000 to 2016 Ethiopian Demographic and Health Surveys indicated that having two children has increased the likely of modern contraceptive use (14). A study conducted on married women of reproductive age in rural Zambia indicated that compared to women with no children, women with one or two, three or four and five or more children were more likely to use contraceptives (15). Compared with previous studies, there is an improvement in the number of young married women using contraceptive methods in this study which could be due to relatively higher exposure to contraceptive use related messages. The result of this study also showed that young married women who had comprehensive knowledge of family planning were more likely to use contraceptives than those who did not. Similarly, a multilevel analysis of the household survey in Ethiopia indicated having knowledge of contraceptive methods increased young women’ use of contraception by more than twofold (16). A community based cross-sectional study conducted in rural Ethiopia indicated that exposure to family planning information and having knowledge of contraceptive were significantly associated with young married women aged contraceptive use (17). This means that access to SRH related information plays a significant role in increasing the use of contraception as it can raise an individual’s awareness on family planning and use of contraceptives. Young married women who listened to the radio at least once a week were more likely to use contraceptives than those who did not. This is consistent with existing literature, which indicates access to family planning information via different sources increases the use of contraceptive methods. According to a study conducted by Adu-Bonsaaoh K, et al. (2022), women in Sub-Saharan Africa who had media exposure were found to be more likely to make informed choices regarding contraceptive methods compared to women who had no media exposure (18). According to High Impact Practices (HIPs), experts worldwide have identified mass media programming as having high impact in Family Planning (19). A multilevel analysis of the DHS data indicated that women who had no exposure to radio had lower odds of using modern contraceptives, across 29 countries in Sub Saharan Africa (5). Furthermore, women who recalled only one media source with a family planning message were even high likely to use a modern contraceptive method than women who recalled no media source (20). Further, the findings of a mixed methods study conducted in four regions of Ethiopia indicated that a weekly exposure to the radio is a primary influencing factor for contraceptive use (21). This could be due to exposure to radio content can contribute to knowledge and attitudes about contraception influencing an individual's decision to use contraceptives. Limitation of the study This study solely relied on a quantitative research methodology to evaluate the contraceptive use behavior of young women in urban cities of Ethiopia. Employing a combination of qualitative and quantitative research methods would have identified some of the socio-cultural factors that influence modern contraceptive use yielding valuable insights into the contraceptive use behavior of young women in urban cities of Ethiopia. Conclusion The finding of this study indicate that young married women have a relatively higher rate of contraceptive use. It has been observed that their contraceptive usage is significantly influenced by factors such as family size, knowledge of contraceptive methods, and their listening behavior in relation to radio programs. Given that radio listenership is a strong predictor to contraceptive use among young married women, SRH interventions and strategies should aim for integration of strong radio programming that promote contraceptives. Such programs should also aim to enhance knowledge on family planning, which has also been identified as a significant predictor. Radio programs can be used to educate women about the various types of modern contraceptives available, their benefits, potential risks, and how to access them. Apart from radio, SRH programs should use a comprehensive approach that employs multichannel strategy that includes mass, mid and social media as well as interpersonal communication. Furthermore, in order to cater to the needs of young women, SRH programs ought to also offer comprehensive education programs, counseling services, and community outreach initiatives focusing on the utilization of modern contraceptives. This educational component should cover the full range of contraceptive options, as well as the importance of postponing childbirth and planning the spacing of pregnancies. Abbreviations AOR: Adjusted Odds Ratio CI: Confidence Interval COR: Crude Odds Ratio EDHS: Ethiopia Demographic and Health Survey HEI: Higher Education Institution IUDs: Intrauterine devices LMIC: Low- and Middle-Income Countries SRH: Sexual and Reproductive Health STATA: Statistical software for data science TV: Television USAID: United States Agency for International Development Declarations Human Ethics and Consent to Participate declarations Not applicable Consent for publication No data from any individual person were presented in this manuscript, thus consent for publication is not applicable. Competing interests The authors declare that they have no conflict of interest. Availability of data and materials Data will be made available from corresponding author upon a reasonable request and based on the data sharing policy of the organization. Funding Not applicable Authors contributions Data analysis was conducted by TH, HT and YL, while YL took charge of figure preparation. The tables were jointly prepared by TH and YL. The manuscript underwent a thorough review and revision process, with contributions from all authors (TH, HT, YL, TU, BM, TB, BA, SH, CT, WA, DH, IL, and YS). The final manuscript was read and approved by all authors. References UNITED NATIONS HUMAN RIGHTS. SEXUAL AND REPRODUCTIVE HEALTH [Internet]. 2021 [cited 2023 Dec 12]. https://www.ohchr.org/en/women/sexual-and-reproductive-health-and-rights . WHO. World Health Organization Adolescent and young adult health [Internet]. 2023 [cited 2023 Dec 12]. https://www.who.int/news-room/fact-sheets/detail/adolescents-health-risks-and-solutions . WHO. 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Cite Share Download PDF Status: Published Journal Publication published 05 Nov, 2025 Read the published version in BMC Public Health → Version 1 posted Editorial decision: Revision requested 07 Jul, 2025 Reviews received at journal 07 May, 2025 Reviewers agreed at journal 01 May, 2025 Reviews received at journal 31 Mar, 2025 Reviewers agreed at journal 29 Mar, 2025 Reviews received at journal 12 Mar, 2025 Reviewers agreed at journal 28 Feb, 2025 Reviewers agreed at journal 07 Jan, 2025 Reviewers invited by journal 25 Apr, 2024 Editor invited by journal 22 Apr, 2024 Editor assigned by journal 18 Apr, 2024 Submission checks completed at journal 01 Apr, 2024 First submitted to journal 29 Mar, 2024 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. 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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-4186777","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":286360180,"identity":"de078f66-a937-4b79-aa4f-31790b7ae220","order_by":0,"name":"Tsion Habtu 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Programs","correspondingAuthor":false,"prefix":"","firstName":"Habtamu","middleName":"Tamene","lastName":"Temesgen","suffix":""},{"id":286360182,"identity":"949b7a86-9ace-4417-bbca-a5ba456a7e3b","order_by":2,"name":"Yihunie Lakew Tarekegn","email":"","orcid":"","institution":"Johns Hopkins University Center for Communication Programs","correspondingAuthor":false,"prefix":"","firstName":"Yihunie","middleName":"Lakew","lastName":"Tarekegn","suffix":""},{"id":286360183,"identity":"5b8113c1-e945-486f-bbe9-76f62ee48248","order_by":3,"name":"Tigist Urgessa Wakene","email":"","orcid":"","institution":"Johns Hopkins University Center for Communication Programs","correspondingAuthor":false,"prefix":"","firstName":"Tigist","middleName":"Urgessa","lastName":"Wakene","suffix":""},{"id":286360184,"identity":"9b26f630-7956-49a8-adf8-56bff0e56c9d","order_by":4,"name":"Biruk Melaku Ayalew","email":"","orcid":"","institution":"Johns Hopkins University Center for Communication Programs","correspondingAuthor":false,"prefix":"","firstName":"Biruk","middleName":"Melaku","lastName":"Ayalew","suffix":""},{"id":286360185,"identity":"e0c14692-cd56-4015-8dd0-09aaed43453c","order_by":5,"name":"Tsega Berhanu Zerihun","email":"","orcid":"","institution":"Johns Hopkins University Center for Communication Programs","correspondingAuthor":false,"prefix":"","firstName":"Tsega","middleName":"Berhanu","lastName":"Zerihun","suffix":""},{"id":286360186,"identity":"b74e1bbf-4491-49b6-bd23-c2bcafa63192","order_by":6,"name":"Betemariam Alemu Tiruneh","email":"","orcid":"","institution":"Johns Hopkins University Center for Communication Programs","correspondingAuthor":false,"prefix":"","firstName":"Betemariam","middleName":"Alemu","lastName":"Tiruneh","suffix":""},{"id":286360187,"identity":"683d51af-64f0-4864-93c0-c0220bd618a2","order_by":7,"name":"Simon Heliso Kuka","email":"","orcid":"","institution":"Johns Hopkins University Center for Communication Programs","correspondingAuthor":false,"prefix":"","firstName":"Simon","middleName":"Heliso","lastName":"Kuka","suffix":""},{"id":286360188,"identity":"199e5f72-42bc-4524-bfe7-24763ecc9a4e","order_by":8,"name":"Chalachew Tiruneh Alemu","email":"","orcid":"","institution":"Amref Health Africa","correspondingAuthor":false,"prefix":"","firstName":"Chalachew","middleName":"Tiruneh","lastName":"Alemu","suffix":""},{"id":286360189,"identity":"59882329-69cb-40a4-9203-7300c004d500","order_by":9,"name":"Wasihun Andualem Gobeze","email":"","orcid":"","institution":"Amref Health Africa","correspondingAuthor":false,"prefix":"","firstName":"Wasihun","middleName":"Andualem","lastName":"Gobeze","suffix":""},{"id":286360190,"identity":"071f1760-6317-45fd-9bc4-544852d65045","order_by":10,"name":"Dereje Haddis Engida","email":"","orcid":"","institution":"Amref Health Africa","correspondingAuthor":false,"prefix":"","firstName":"Dereje","middleName":"Haddis","lastName":"Engida","suffix":""},{"id":286360191,"identity":"9b9dbfed-2c50-495f-9a36-c0888225e220","order_by":11,"name":"Israel Lemma Hailu","email":"","orcid":"","institution":"Amref Health Africa","correspondingAuthor":false,"prefix":"","firstName":"Israel","middleName":"Lemma","lastName":"Hailu","suffix":""},{"id":286360192,"identity":"c616b19a-94f5-4b54-959b-d522322ad939","order_by":12,"name":"Yimer Seid Adem","email":"","orcid":"","institution":"Amref Health Africa","correspondingAuthor":false,"prefix":"","firstName":"Yimer","middleName":"Seid","lastName":"Adem","suffix":""}],"badges":[],"createdAt":"2024-03-29 08:50:10","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4186777/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4186777/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12889-025-25219-1","type":"published","date":"2025-11-05T15:56:57+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":54184798,"identity":"bc80fedd-bf8f-4160-af2c-fb96ad70d8f4","added_by":"auto","created_at":"2024-04-05 17:23:52","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":9683,"visible":true,"origin":"","legend":"\u003cp\u003eFigure legend not available with this version.\u003c/p\u003e","description":"","filename":"Onlinedrawingimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-4186777/v1/209e5abe315b0f65343aff9c.png"},{"id":54184796,"identity":"54009e5b-311a-405c-8325-4cb6832a97c7","added_by":"auto","created_at":"2024-04-05 17:23:51","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":25794,"visible":true,"origin":"","legend":"\u003cp\u003eFigure legend not available with this version.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-4186777/v1/0a623ff5374ecd347c996b05.png"},{"id":95564098,"identity":"1a634eff-43a9-425b-9787-313b56ef9a1f","added_by":"auto","created_at":"2025-11-10 16:07:50","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":978306,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4186777/v1/b00b1722-1a91-4d87-b26a-d91d5dca00b5.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Modern Contraceptive Use Behavior among Young Married Women in Urban Settings of Ethiopia: A Multilevel Analysis","fulltext":[{"header":"Background","content":"\u003cp\u003eThe right to access Sexual and Reproductive Health (SRH) services and information can significantly reduce child marriage, teenage pregnancy, and the spread of sexually transmitted infections (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). The utilization of contraceptives among young women brings about substantial advantages for their health and society. It plays a crucial role in postponing pregnancies in young girls who are at risk for health complications arising from early childbearing. By reducing the occurrence of unintended pregnancies, we can significantly reduce the demand for unsafe abortions, curb the transmission of sexually transmitted infections, and avert pregnancy-related fatalities. This reduction can further support the pursuit of education for girls and empowers young women to actively participate in society, including through paid employment(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn 2019, the estimated percentage of adolescent women who used modern contraceptive methods was 9.1% globally with 7.4 to 12.8 uncertainty interval (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). A study conducted in 29 countries within Sub-Saharan Africa (SSA) revealed that 24.7% of Adolescent Girls and Young Women (AGYW) in these countries utilize modern contraception. Among the countries included, Lesotho demonstrated the highest prevalence of modern contraceptive use among AGYW, with a rate of 59.2%. On the other hand, Chad exhibited the lowest prevalence, with only 5.1% of AGYW using modern contraceptives (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). In Ethiopia, young married women\u0026rsquo;s (age 15 to 24 years) use of modern contraceptives increased from 6% in 2000 to 16% in 2005 and to 36% in 2011 based on the three EDHS (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). However, it has since seemed to have declined as the 2019 EDHS data showed the prevalence of modern contraceptive use among young women at only 17% on average (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). Among young preparatory school students aged 15 to 22 years, the proportion of individuals who had undergone induced abortion at some point in their lifetime was high, 13.6% based on a study conducted in Southern Region of Ethiopia (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). Further, a systematic review illustrated that the prevalence of unintended pregnancy in Ethiopia was 28% in general, mainly occurring among women who do not use any form of contraception (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAmong the challenges in designing social behavior change interventions to improve contraceptive use behavior among young urban women in Ethiopia is insufficient evidence regarding determinants for contraceptive use behavior. This study is, therefore, conducted to examine contraceptive use among married young women aged 18 to 29 and identify associated factors in Ethiopia. The findings of this study are used by sexual health service implementers, partners and policymakers who are working to improve SRH among young women.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eStudy design and setting\u003c/p\u003e\n\u003cp\u003eThis study was conducted in major cities of Ethiopia identified as targets for Kefeta Integrate Youth Activities,\u0026nbsp;namely:\u0026nbsp;Adama, Addis Ababa, Assosa, Bahir Dar, Bishoftu, Dilla, Dire Dewa, Gambella, Harar, Jigjiga, Jimma, Hawassa, and Shashemenie. Youth, youth-serving organizations, and policy actors in these cities and higher education institutions found in the cities were targets for this study. According to data from the World Health Organization trendline, the number of women of reproductive age in Ethiopia amounts to 31,664 individuals\u0026nbsp;(10).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData\u003c/strong\u003e\u003cstrong\u003esource\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study utilized secondary data from the original formative assessment data set of the USAID-funded Integrative Youth Activities Project. The dataset consisted of 3,215 young people\u0026nbsp;aged 18 to 29 years\u0026nbsp;who were from community and HEI (Higher Education Institution) settings. Data collection took place from\u0026nbsp;December 12, 2021, through January 21, 2022, across 13 cities.\u0026nbsp;A total of 680 young married women data extracted and analyzed.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eStudy\u0026nbsp;variables\u003c/p\u003e\n\u003cp\u003eThe dependent variable in this study is the use of modern contraceptive methods at the time of data collection. The \u0026ldquo;Yes\u0026rdquo; category comprises individuals themselves or their husbands who are currently using a range of modern contraceptive methods, including pills, implants, injectables, intrauterine devices (IUDs), condoms, emergency contraceptives, standard days method (SDM), the lactational amenorrhea method, and female sterilization. The category referred to as \u0026ldquo;No\u0026rdquo; encompasses individuals who employ contraceptive methods such as the rhythm method, withdrawal, other traditional methods, and no contraceptive method at all.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis study includes the following independent variables: respondent age (18 to 24 years, 25-29 years), exposure to radio media (yes, no), exposure to TV media (yes, no), knowledge about contraceptives (labeled as \u0026lsquo;yes\u0026rsquo; if the respondents know at least two contraceptive methods and no if respondents know only one contraceptive method), family size (labeled as \u0026lsquo;yes\u0026rsquo; if the respondents\u0026rsquo; family size is less than three and \u0026lsquo;no\u0026rsquo; if the respondents\u0026rsquo; family size is greater than or equal to three). Additionally, the presence of partner communication norms was assessed using a composite of three variables: (1) a girl can suggest to her boyfriend that he can use a condom, (2) it wouldn\u0026rsquo;t be too embarrassing for someone like me to buy or obtain condoms, and (3) if a girl suggested using condoms to her partner, it wouldn\u0026rsquo;t mean that she didn\u0026rsquo;t trust him.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDescriptive statistics were used to summarize: the contraceptive use among young women in selected urban cities of Ethiopia, the distribution of contraceptive use across cities and individual-level factors, sources for obtaining contraceptives and contraceptive information sources. Data were analyzed using STATA Version 18 software.\u0026nbsp;Data quality assurance and control procedures were applied throughout the data collection fieldwork.\u003c/p\u003e\n\u003cp\u003eA multilevel binary logistic regression analysis was done to measure the association between contraceptive use and the\u0026nbsp;variation across cities. Cities were considered as random effects to cater for the unexplained variability at the individual-level. The selection of variables for the multilevel models was based on their statistical significance at the bivariate analysis at a p \u0026lt; 0.05. Further, the statistical significance of the associations between each of the factors and current use of contraceptives was determined at a p-value of less than 0.05.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTwo models, comprising the null model (model 0) and model 1 were fitted. Model 0 showed the variance in modern contraceptive use attributed to the clustering of the primary sampling units without the explanatory variables. Model 1 is progressive containing the individual factors:\u0026nbsp;age, media exposure through radio, media exposure through TV, knowledge on contraceptives, family size \u0026amp; partner communication norms. Model comparison was done using the log likelihood and Akaike\u0026rsquo;s Information Criterion (AIC) tests. The lowest AIC (818.3) and highest log likelihood (\u0026minus;401.2) were used to determine the best fit model. For model one, Odds ratio and associated 95% confidence intervals (CIs) were calculated. Using the variance inflation factor (VIF), a test for multicollinearity was done and there was no evidence of high collinearity.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOperational definition\u003c/p\u003e\n\u003cp\u003eIn this study, the term \u0026ldquo;young women\u0026rdquo; refers to individuals aged 18 to 29. \u0026ldquo;Media exposure\u0026rdquo; refers to those young married women who had listened to radio or watched to television at least once a week. The study categorized modern contraceptive methods as pills, implants, injectables, intrauterine devices (IUDs), condoms, emergency contraceptives, the standard days method (SDM), the lactational amenorrhea method, and female sterilization. On the other hand, the rhythm method and withdrawal method were classified as traditional contraceptive methods\u0026nbsp;(11). Respondents who demonstrated knowledge on at least two types of the contraceptive methods were considered to be knowldgeable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eEthics declarations\u003c/p\u003e\n\u003cp\u003eEthics approval and consent to participate\u003c/p\u003e\n\u003cp\u003eThe study proposal was reviewed and approved by the Institutional Review Board (IRB) of the Ethiopian Public Health Association (EPHA) before any data collection activities commenced. Permission was obtained from the administrations of participating cities. Before interviews were conducted, all interviewees were provided with adequate information about the purpose of the study, contents of interviews, and contact details of the principal investigator (PI) and IRB chairperson. Verbal consent was obtained from each informant before they were interviewed.\u003c/p\u003e"},{"header":"Results","content":"\u003ch2\u003eSociodemographic characteristics of respondents\u003c/h2\u003e\n\u003cp\u003eAmong the 680 young married women selected for this study, 653 (96%) were those selected from a community setting and 27 (4%) were from HEIs. Eleven (2%) were young women with physical disabilities. The median age was 25 years with an interquartile range of 5 years. More than 60% (415) of the respondents were between ages of 25-29 years while the remaining (267) were in the age group of 18-24 years. Respondents from Addis Ababa were 81 (12%), Adama 78 (12%), Assosa 26 (4%), Bahir Dar 63 (9%), Bishoftu 36 (5%), Dilla 33 (5%), Dire Dewa 68 (10%), Gambella 56 (8%), Harar 24 (4%), Hawassa 74 (11%), Jigjiga 39 (6%), Jimma 55 (8%) and Shashemenie 47 (7%) were interviewed. \u0026nbsp;The following table provides a summary of the sociodemographic characteristics of the respondents (\u003cstrong\u003eTable 1\u003c/strong\u003e).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eBackground characteristics of respondents\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"59.770114942528735%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharacteristics\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.229885057471265%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e%\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"59.770114942528735%\" valign=\"top\"\u003e\n \u003cp\u003eAge group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.229885057471265%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"59.770114942528735%\" valign=\"top\"\u003e\n \u003cp\u003e18 to 24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.229885057471265%\" valign=\"top\"\u003e\n \u003cp\u003e39.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"59.770114942528735%\" valign=\"top\"\u003e\n \u003cp\u003e25 to 29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.229885057471265%\" valign=\"top\"\u003e\n \u003cp\u003e60.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"59.770114942528735%\" valign=\"top\"\u003e\n \u003cp\u003eEducation status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.229885057471265%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"59.770114942528735%\" valign=\"top\"\u003e\n \u003cp\u003eNo formal education\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.229885057471265%\" valign=\"top\"\u003e\n \u003cp\u003e7.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"59.770114942528735%\" valign=\"top\"\u003e\n \u003cp\u003ePrimary school students\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.229885057471265%\" valign=\"top\"\u003e\n \u003cp\u003e37.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"59.770114942528735%\" valign=\"top\"\u003e\n \u003cp\u003eSecondary school students\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.229885057471265%\" valign=\"top\"\u003e\n \u003cp\u003e28.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"59.770114942528735%\" valign=\"top\"\u003e\n \u003cp\u003eTVET attendant or graduate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.229885057471265%\" valign=\"top\"\u003e\n \u003cp\u003e14.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"59.770114942528735%\" valign=\"top\"\u003e\n \u003cp\u003eUniversity attendant or graduate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.229885057471265%\" valign=\"top\"\u003e\n \u003cp\u003e13.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"59.770114942528735%\" valign=\"top\"\u003e\n \u003cp\u003eDisability status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.229885057471265%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"59.770114942528735%\" valign=\"top\"\u003e\n \u003cp\u003eNo disability\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.229885057471265%\" valign=\"top\"\u003e\n \u003cp\u003e98.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"59.770114942528735%\" valign=\"top\"\u003e\n \u003cp\u003eYouth with disability\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.229885057471265%\" valign=\"top\"\u003e\n \u003cp\u003e1.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"59.770114942528735%\" valign=\"top\"\u003e\n \u003cp\u003eMedia exposure (radio)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.229885057471265%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"59.770114942528735%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.229885057471265%\" valign=\"top\"\u003e\n \u003cp\u003e57.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"59.770114942528735%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.229885057471265%\" valign=\"top\"\u003e\n \u003cp\u003e42.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"59.770114942528735%\" valign=\"top\"\u003e\n \u003cp\u003eMedia exposure (TV)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.229885057471265%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"59.770114942528735%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.229885057471265%\" valign=\"top\"\u003e\n \u003cp\u003e16.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"59.770114942528735%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.229885057471265%\" valign=\"top\"\u003e\n \u003cp\u003e84.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"59.770114942528735%\" valign=\"top\"\u003e\n \u003cp\u003eKnowledge on contraceptives\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.229885057471265%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"59.770114942528735%\" valign=\"top\"\u003e\n \u003cp\u003eNo (knows only one contraceptive method)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.229885057471265%\" valign=\"top\"\u003e\n \u003cp\u003e14.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"59.770114942528735%\" valign=\"top\"\u003e\n \u003cp\u003eYes (knows at least two contraceptive methods)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.229885057471265%\" valign=\"top\"\u003e\n \u003cp\u003e85.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"59.770114942528735%\" valign=\"top\"\u003e\n \u003cp\u003eExistence of partner communication norm with couples\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.229885057471265%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"59.770114942528735%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.229885057471265%\" valign=\"top\"\u003e\n \u003cp\u003e35.7\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"59.770114942528735%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.229885057471265%\" valign=\"top\"\u003e\n \u003cp\u003e64.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"59.770114942528735%\" valign=\"top\"\u003e\n \u003cp\u003eFamily size\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.229885057471265%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"59.770114942528735%\" valign=\"top\"\u003e\n \u003cp\u003eLess than 3 family size\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.229885057471265%\" valign=\"top\"\u003e\n \u003cp\u003e17.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"59.770114942528735%\" valign=\"top\"\u003e\n \u003cp\u003eGreater than or equal to 3 family size\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.229885057471265%\" valign=\"top\"\u003e\n \u003cp\u003e82.5\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"59.770114942528735%\" valign=\"top\"\u003e\n \u003cp\u003eCurrently attending school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.229885057471265%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"59.770114942528735%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.229885057471265%\" valign=\"top\"\u003e\n \u003cp\u003e94.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"59.770114942528735%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.229885057471265%\" valign=\"top\"\u003e\n \u003cp\u003e6.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"59.770114942528735%\" valign=\"top\"\u003e\n \u003cp\u003eWorking mostly in the past 12 months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.229885057471265%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"59.770114942528735%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.229885057471265%\" valign=\"top\"\u003e\n \u003cp\u003e70.9\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"59.770114942528735%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"40.229885057471265%\" valign=\"top\"\u003e\n \u003cp\u003e29.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003ch2\u003eContraceptive use\u003c/h2\u003e\n\u003cp\u003eThe result of this study illustrated those young women\u0026rsquo;s contraceptive use was 401 (59%) and the most used contraceptive methods were injectables (n=171, 42%), followed by implants (n=143, 35%) and pills (n=55, 14%) as shown in the figure below. Contraceptive use slightly differed by age group; 246 (60%) young women within the age group of 25 to 29 years and 155 (58%) young women within the age group of 18 to 24 years were currently using contraceptives (\u003cstrong\u003eFig. 1\u003c/strong\u003e).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFig. 1\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHigh contraceptive use variability was observed across cities. The prevalence of contraceptive use among young married women in Jigjiga and Harar was found to be low in the range of 10% and 29%. The highest uptake of contraceptives was observed among the target population in Adama and Hawassa \u0026nbsp;in the range of 65% to 81% (\u003cstrong\u003eFig. 2\u003c/strong\u003e).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFig. 2\u003c/strong\u003e\u003c/p\u003e\n\u003ch2\u003eKnowledge of\u0026nbsp;contraceptives\u003c/h2\u003e\n\u003cp\u003eMost of the youth respondents (643, 94.6%) have heard about family planning methods. Five hundred seventy nine (85%) young married women knew at least two types of contraceptive methods. The most known methods were injectables (575, 85%), followed by pills (531, 78%) and implants (516, 76%). The least known methods were withdrawal 62 (9.1%) and male sterilization 64 (9.4%).\u003c/p\u003e\n\u003ch2\u003eSexual and reproductive health information\u003c/h2\u003e\n\u003cp\u003eExposure to messages related to SRH was assessed among youth and almost half of the young married women (334, 49%) had received SRH-related information from any source in the preceding three months. The most common SRH message sources for the young married women were TV (199, 29%), followed by health facilities (171, 25%) and social media (59, 9%).\u003c/p\u003e\n\u003ch2\u003eSources of contraceptive\u003c/h2\u003e\n\u003cp\u003eHealth centers were the most common sources of SRH services (181, 27%) for young married women, followed by government hospitals (61, 9%) and private health facilities (47, 7%).\u003c/p\u003e\n\u003ch2\u003eAssociation between individual factors and youth\u0026rsquo;s contraceptive use among young married women in Ethiopia\u003c/h2\u003e\n\u003cp\u003eThe multilevel logistic regression analysis illustrated that individual-level factors, such as young married women who had more than two family members, knowledge about family planning, and listened to the radio at least once a week, were significantly associated with contraceptive use (\u003cstrong\u003eTable 2\u003c/strong\u003e).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2 Mixed effect multilevel logistic regression analysis of factors associated with contraceptive use\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"630\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.476190476190474%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCovariates\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.428571428571427%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eContraceptive use\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.095238095238095%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCOR (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eModel-I\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eAOR (95% CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"51.515151515151516%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eYes\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"48.484848484848484%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eNo\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.476190476190474%\" valign=\"top\"\u003e\n \u003cp\u003eAge group\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.19047619047619%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.238095238095237%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.095238095238095%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.476190476190474%\" valign=\"top\"\u003e\n \u003cp\u003e18 to 24 years\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.19047619047619%\" valign=\"top\"\u003e\n \u003cp\u003e155 (58.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.238095238095237%\" valign=\"top\"\u003e\n \u003cp\u003e112 (42.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.095238095238095%\" valign=\"top\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.476190476190474%\" valign=\"top\"\u003e\n \u003cp\u003e25 to 29 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.19047619047619%\" valign=\"top\"\u003e\n \u003cp\u003e246 (60.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.238095238095237%\" valign=\"top\"\u003e\n \u003cp\u003e167 (40.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.095238095238095%\" valign=\"top\"\u003e\n \u003cp\u003e1.1 (0.78, 1.46)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e0.9 (0.64, 1.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.476190476190474%\" valign=\"top\"\u003e\n \u003cp\u003eMedia exposure (radio)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.19047619047619%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.238095238095237%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.095238095238095%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.476190476190474%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.19047619047619%\" valign=\"top\"\u003e\n \u003cp\u003e207 (52.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.238095238095237%\" valign=\"top\"\u003e\n \u003cp\u003e185 (47.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.095238095238095%\" valign=\"top\"\u003e\n \u003cp\u003eRef\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003eRef \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.476190476190474%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.19047619047619%\" valign=\"top\"\u003e\n \u003cp\u003e194 (67.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.238095238095237%\" valign=\"top\"\u003e\n \u003cp\u003e94 (32.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.095238095238095%\" valign=\"top\"\u003e\n \u003cp\u003e1.8 (1.34, 2.53)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e1.6 (1.13, 2.32) *\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.476190476190474%\" valign=\"top\"\u003e\n \u003cp\u003eMedia exposure (TV)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.19047619047619%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.238095238095237%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.095238095238095%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.476190476190474%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.19047619047619%\" valign=\"top\"\u003e\n \u003cp\u003e58 (53.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.238095238095237%\" valign=\"top\"\u003e\n \u003cp\u003e51 (46.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.095238095238095%\" valign=\"top\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.476190476190474%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.19047619047619%\" valign=\"top\"\u003e\n \u003cp\u003e343 (60.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.238095238095237%\" valign=\"top\"\u003e\n \u003cp\u003e228 (39.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.095238095238095%\" valign=\"top\"\u003e\n \u003cp\u003e1.3 (0.88, 2.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e1.1 (0.69, 1.81)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.476190476190474%\" valign=\"top\"\u003e\n \u003cp\u003eKnowledge on contraceptives\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.19047619047619%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.238095238095237%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.095238095238095%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.476190476190474%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.19047619047619%\" valign=\"top\"\u003e\n \u003cp\u003e41 (40.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.238095238095237%\" valign=\"top\"\u003e\n \u003cp\u003e60 (59.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.095238095238095%\" valign=\"top\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.476190476190474%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.19047619047619%\" valign=\"top\"\u003e\n \u003cp\u003e360 (62.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.238095238095237%\" valign=\"top\"\u003e\n \u003cp\u003e219 (37.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.095238095238095%\" valign=\"top\"\u003e\n \u003cp\u003e2.4 (1.56, 3.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e2.6 (1.43, 4.83) *\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.476190476190474%\" valign=\"top\"\u003e\n \u003cp\u003eCommunication norm with partners\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.19047619047619%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.238095238095237%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.095238095238095%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.476190476190474%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.19047619047619%\" valign=\"top\"\u003e\n \u003cp\u003e23 (56.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.238095238095237%\" valign=\"top\"\u003e\n \u003cp\u003e18 (43.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.095238095238095%\" valign=\"top\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.476190476190474%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.19047619047619%\" valign=\"top\"\u003e\n \u003cp\u003e378 (59.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.238095238095237%\" valign=\"top\"\u003e\n \u003cp\u003e261 (40.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.095238095238095%\" valign=\"top\"\u003e\n \u003cp\u003e1.1 (0.60, 2.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e0.8 (0.39, 1.79)\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.476190476190474%\" valign=\"top\"\u003e\n \u003cp\u003eFamily size\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.19047619047619%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.238095238095237%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.095238095238095%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.476190476190474%\" valign=\"top\"\u003e\n \u003cp\u003eLess than 3 family size\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.19047619047619%\" valign=\"top\"\u003e\n \u003cp\u003e44 (38.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.238095238095237%\" valign=\"top\"\u003e\n \u003cp\u003e70 (61.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.095238095238095%\" valign=\"top\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003eRef\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.476190476190474%\" valign=\"top\"\u003e\n \u003cp\u003eFamily size of atleast 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.19047619047619%\" valign=\"top\"\u003e\n \u003cp\u003e341 (63.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.238095238095237%\" valign=\"top\"\u003e\n \u003cp\u003e198 (36.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.095238095238095%\" valign=\"top\"\u003e\n \u003cp\u003e2.7 (1.81, 4.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20%\" valign=\"top\"\u003e\n \u003cp\u003e3.3 (2.04, 5.27) *\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e*P-value\u0026lt;0.05.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eModel fitness\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eLog likelihood ratios and Akaike\u0026rsquo;s Information Criterion (AIC) were used to check model fitness for the multilevel models.\u0026nbsp;Controlling more predictor variables (age, media exposure through radio, media exposure through TV, knowledge on contraceptives, family size \u0026amp; partner communication norms), the final mixed effect model resulted in significantly reduced contraceptive use variability across cities as compared to the intercept only model (\u003cstrong\u003eTable 3\u003c/strong\u003e).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3 Multilevel analysis model building, and contraceptive use variability across cities in Ethiopia.\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"62.62626262626262%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eModels process\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.131313131313131%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eICC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eAIC\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.131313131313131%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eLLR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"62.62626262626262%\" valign=\"top\"\u003e\n \u003cp\u003eContraceptive use variability across cities- without predictors -Fixed effect model\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.131313131313131%\" valign=\"top\"\u003e\n \u003cp\u003e0.155\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003e883.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.131313131313131%\" valign=\"top\"\u003e\n \u003cp\u003e-439.6\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"62.62626262626262%\" valign=\"top\"\u003e\n \u003cp\u003eContraceptive use variability across cities \u0026ndash; with adding age\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.131313131313131%\" valign=\"top\"\u003e\n \u003cp\u003e0.158\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003e884.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.131313131313131%\" valign=\"top\"\u003e\n \u003cp\u003e-439.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"62.62626262626262%\" valign=\"top\"\u003e\n \u003cp\u003eContraceptive use variability across cities - with adding media exposure through radio\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.131313131313131%\" valign=\"top\"\u003e\n \u003cp\u003e0.142*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003e878.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.131313131313131%\" valign=\"top\"\u003e\n \u003cp\u003e-435.4\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"62.62626262626262%\" valign=\"top\"\u003e\n \u003cp\u003eContraceptive use variability across cities- with adding media exposure through TV\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.131313131313131%\" valign=\"top\"\u003e\n \u003cp\u003e0.140\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003e880.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.131313131313131%\" valign=\"top\"\u003e\n \u003cp\u003e-435.1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"62.62626262626262%\" valign=\"top\"\u003e\n \u003cp\u003eContraceptive use variability across cities \u0026ndash; with adding knowledge on contraceptives\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.131313131313131%\" valign=\"top\"\u003e\n \u003cp\u003e0.123*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003e874.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.131313131313131%\" valign=\"top\"\u003e\n \u003cp\u003e-431.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"62.62626262626262%\" valign=\"top\"\u003e\n \u003cp\u003eContraceptive use variability across cities- with adding partner communication norm\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.131313131313131%\" valign=\"top\"\u003e\n \u003cp\u003e0.123\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003e876.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.131313131313131%\" valign=\"top\"\u003e\n \u003cp\u003e-431.3\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"62.62626262626262%\" valign=\"top\"\u003e\n \u003cp\u003eContraceptive use variability across cities- with adding family size (all predictors)- Mixed effect model\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.131313131313131%\" valign=\"top\"\u003e\n \u003cp\u003e0.125*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"11.11111111111111%\" valign=\"top\"\u003e\n \u003cp\u003e818.3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.131313131313131%\" valign=\"top\"\u003e\n \u003cp\u003e-401.2\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eICC in the random intercept model is 0.155, AIC value is 883.2 and LLR is -439.6, The acronym ICC- intraclass correlation coefficient, AIC-Akaike\u0026apos;s Information Criteria, LLR- log likelihood ratio.\u0026nbsp;\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study found that 401 (59%) of young married women in the selected cities used contraceptive.\u0026nbsp;Having more than two family members, knowledge on contraceptive and exposure to radio were identified as individual-level predictors of contraceptive use among young married women.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis study discovered that\u0026nbsp;the utilization of contraceptives among young married women surpassed the targeted national contraceptive rate of 50% set for the years 2024-2025\u0026nbsp;(12). This could be due to higher listenership of SRH-related messages among young married women residing in urban cities. The\u0026nbsp;2019 Ethiopian Mini Demographic and Health Survey data\u0026nbsp;indicated that the prevalence of modern contraceptive use among young married women aged 15 to 24 was only 17% on average\u0026nbsp;(7).\u0026nbsp;Another study conducted in Malawi indicated that 31% of young women used contraceptive\u0026nbsp;(13).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe study illustrated that young women who had more than two members in their family were more likely to use contraceptives. Consistent to this finding, analysis of 2000 to 2016 Ethiopian Demographic and Health Surveys indicated that having two children has increased the likely of modern contraceptive use\u0026nbsp;(14).\u0026nbsp;A study conducted on married women of reproductive age in rural Zambia indicated that compared to women with no children, women with one or two, three or four and five or more children were more likely to use contraceptives\u0026nbsp;(15).\u0026nbsp;Compared with previous studies,\u0026nbsp;there is an improvement in the number of young married women using contraceptive methods in this study which could be due to relatively higher exposure to contraceptive use related messages.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe result of this study also showed that young married women who had comprehensive\u0026nbsp;knowledge of family planning were more likely to use contraceptives than those who did not.\u0026nbsp;Similarly, a multilevel analysis of the household survey in Ethiopia indicated having knowledge of contraceptive methods increased young women\u0026rsquo; use of contraception by more than twofold\u0026nbsp;(16). A community based cross-sectional study conducted in rural Ethiopia indicated that exposure to family planning information and having knowledge of contraceptive were significantly associated with young married women aged contraceptive use\u0026nbsp;(17). This means that access to SRH related information plays a significant role in increasing the use of contraception as it can raise an individual\u0026rsquo;s awareness on family planning and use of contraceptives.\u003c/p\u003e\n\u003cp\u003eYoung married women who listened to the radio at least once a week were more likely to use contraceptives than those who did not. This is consistent with\u0026nbsp;existing literature, which indicates access to family planning information via different sources increases the use of contraceptive methods. According to a study conducted by\u0026nbsp;Adu-Bonsaaoh K, et al.\u0026nbsp;(2022), women in Sub-Saharan Africa who had media exposure were found to be more likely to make informed choices regarding contraceptive methods compared to women who had no media exposure\u0026nbsp;(18).\u0026nbsp;According to High Impact Practices (HIPs), experts worldwide have identified mass media programming as having high impact in Family Planning\u0026nbsp;(19). \u0026nbsp;A multilevel analysis of the DHS data indicated that women who had no exposure to radio had lower odds of using modern contraceptives, across 29 countries in Sub Saharan Africa\u0026nbsp;(5). Furthermore, women who recalled only one media source with a family planning message were even high likely to use a modern contraceptive method than women who recalled no media source\u0026nbsp;(20). Further, the findings of a mixed methods study conducted in four regions of Ethiopia indicated that a weekly exposure to the radio is a primary influencing factor for contraceptive use\u0026nbsp;(21). This could be due to exposure to radio content can contribute to knowledge and attitudes about contraception influencing an individual\u0026apos;s decision to use contraceptives.\u003c/p\u003e\n\u003cp\u003eLimitation of the study\u003c/p\u003e\n\u003cp\u003eThis study solely relied on a quantitative research methodology to evaluate the contraceptive use behavior of young women in urban cities of Ethiopia. Employing a combination of qualitative and quantitative research methods would have identified some of the socio-cultural factors that influence modern contraceptive use yielding valuable insights into the contraceptive use behavior of young women in urban cities of Ethiopia.\u0026nbsp;\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe finding of this study indicate that young married women have a relatively higher rate of contraceptive use. It has been observed that their contraceptive usage is significantly influenced by factors such as family size, knowledge of contraceptive methods, and their listening behavior in relation to radio programs. Given that radio listenership is a strong predictor to contraceptive use among young married women, SRH interventions and strategies should aim for integration of strong radio programming that promote contraceptives. Such programs should also aim to enhance knowledge on family planning, which has also been identified as a significant predictor. Radio programs can be used to educate women about the various types of modern contraceptives available, their benefits, potential risks, and how to access them.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eApart from radio, SRH programs should use a comprehensive approach that employs multichannel strategy that includes mass, mid and social media as well as interpersonal communication. Furthermore, in order to cater to the needs of young women, SRH programs ought to also offer comprehensive education programs, counseling services, and community outreach initiatives focusing on the utilization of modern contraceptives. This educational component should cover the full range of contraceptive options, as well as the importance of postponing childbirth and planning the spacing of pregnancies.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eAOR: Adjusted Odds Ratio\u003c/p\u003e\n\u003cp\u003eCI: Confidence Interval\u003c/p\u003e\n\u003cp\u003eCOR: Crude Odds Ratio\u003c/p\u003e\n\u003cp\u003eEDHS: Ethiopia Demographic and Health Survey\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHEI: Higher Education Institution\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIUDs: Intrauterine devices\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eLMIC: Low- and Middle-Income Countries\u003c/p\u003e\n\u003cp\u003eSRH: Sexual and Reproductive Health\u003c/p\u003e\n\u003cp\u003eSTATA: Statistical software for data science\u003c/p\u003e\n\u003cp\u003eTV: Television\u003c/p\u003e\n\u003cp\u003eUSAID: United States Agency for International Development\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eHuman Ethics and Consent to Participate declarations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNo data from any individual person were presented in this manuscript, thus consent for publication is not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData will be made available from corresponding author upon a reasonable request and based on the data sharing policy of the organization.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData analysis was conducted by TH, HT and YL, while YL took charge of figure preparation. The tables were jointly prepared by TH and YL. The manuscript underwent a thorough review and revision process, with contributions from all authors (TH, HT, YL, TU, BM, TB, BA, SH, CT, WA, DH, IL, and YS). The final manuscript was read and approved by all authors.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eUNITED NATIONS HUMAN RIGHTS. SEXUAL AND REPRODUCTIVE HEALTH [Internet]. 2021 [cited 2023 Dec 12]. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ohchr.org/en/women/sexual-and-reproductive-health-and-rights\u003c/span\u003e\u003cspan address=\"https://www.ohchr.org/en/women/sexual-and-reproductive-health-and-rights\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWHO. 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BMJ Open [Internet]. 2020;10(3):e030980. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://bmjopen.bmj.com/content/10/3/e030980.abstract\u003c/span\u003e\u003cspan address=\"http://bmjopen.bmj.com/content/10/3/e030980.abstract\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDebelew GT, Habte MB. Contraceptive Method Utilization and Determinant Factors among Young Women (15\u0026ndash;24) in Ethiopia: A Mixed-Effects Multilevel Logistic Regression Analysis of the Performance Monitoring for Action 2018 Household Survey. Char A, editor. Biomed Res Int [Internet]. 2021;2021:6642852. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1155/2021/6642852\u003c/span\u003e\u003cspan address=\"10.1155/2021/6642852\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTariku Dingeta LOAWYB. Young Married Women Contraceptive Use and Associated Factors in Rural Ethiopia: Community Based Cross-Sectional Study. popconf.org. 2019.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAdu-Bonsaaoh K, Adhikari C, Mamuye M, Tsega NT. Pooled prevalence and determinants of informed choice of contraceptive methods among reproductive age women in Sub-Saharan Africa: A multilevel analysis.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHIP: FAMILY PLANNING HIGH IMPACT PRACTICES [Internet]. [cited 2023 Dec 12]. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.fphighimpactpractices.org/briefs/family-planning-high-impact-practices-list/\u003c/span\u003e\u003cspan address=\"https://www.fphighimpactpractices.org/briefs/family-planning-high-impact-practices-list/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMiriam NJ. SCMTJNADNBKCNE. The Impact of Multimedia Family Planning Promotion on the Contraceptive Behavior of Women in Tanzania. International Family Planning Perspectives, 1999, 25 (2): 60\u0026ndash;67. 1990.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKapadia-Kundu N, Tamene H, Ayele M, Dana F, Heliso S, Velu S et al. Applying a gender lens to social norms, couple communication and decision making to increase modern contraceptive use in Ethiopia, a mixed methods study. Reprod Health [Internet]. 2022;19(1):138. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s12978-022-01440-8\u003c/span\u003e\u003cspan address=\"10.1186/s12978-022-01440-8\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\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":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Contraceptive use, exposure to media, family size, multilevel analysis, young married women","lastPublishedDoi":"10.21203/rs.3.rs-4186777/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4186777/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eBased on the Ethiopia Demographic and Health Survey, there has been low contraceptive utilization among young married women in Ethiopia, as well as unmet needs. This situation has had adverse consequences on the reproductive health outcomes of young women. Thus, this study was conducted to identify main determinants of young women\u0026rsquo;s contraceptive use in selected urban cities of Ethiopia. The findings of this study informed the design strategies to increase young women\u0026rsquo;s contraceptive use.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA dataset consisting of 680 young married women aged between 18 and 29 years was extracted from a secondary source and analyzed using STATA version 18 from a cross-sectional study, which was conducted from December 12, 2021 to January 21, 2022, in 13 selected urban cities. A multilevel logistic regression modeling techniques was used to identify the determinants of contraceptives (individual-level factors) and control for variations caused by differences between cities.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eFour hundred one (59% CI: 0.55\u0026ndash;0.63) young women used contraceptives at the time of data collection. The most common contraceptive methods were injectables (42%) and implants (35%). High contraceptive use variability was observed across cities. About 16% variability of contraceptive use was observed at the intercept model analysis without factors and a 13% variability in contraceptive use across cities at the final model of multilevel analysis. The lowest contraceptive use was observed in Jigjiga (10%, CI\u0026thinsp;=\u0026thinsp;0.03\u0026ndash;0.24) and the highest was in Hawassa (81%, CI\u0026thinsp;=\u0026thinsp;0.70\u0026ndash;0.89). The analysis result indicated that individual-level variables such as young women who had more than two family members (AOR\u0026thinsp;=\u0026thinsp;3.3, 95% CI\u0026thinsp;=\u0026thinsp;2.04\u0026ndash;5.27), who had knowledge of contraceptive methods (AOR\u0026thinsp;=\u0026thinsp;2.6, 95% CI\u0026thinsp;=\u0026thinsp;1.43\u0026ndash;4.83) and who had radio exposure (AOR\u0026thinsp;=\u0026thinsp;1.6, 95% CI\u0026thinsp;=\u0026thinsp;1.13\u0026ndash;2.32) were significantly associated with their contraceptive use behavior.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThe study shows higher levels of contraceptive use among young women in the selected cities as compared with the national target of 50% for 2024/25. Increasing radio listenership about contraceptive use, supported by other interventions that enhance comprehensive knowledge can be an effective strategy to improve contraceptive use among young married women in cities.\u003c/p\u003e","manuscriptTitle":"Modern Contraceptive Use Behavior among Young Married Women in Urban Settings of Ethiopia: A Multilevel Analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-04-05 17:23:47","doi":"10.21203/rs.3.rs-4186777/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-07-07T10:37:07+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-05-07T04:03:38+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"180587170332839588641944006782516036976","date":"2025-05-01T16:03:10+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-03-31T08:57:28+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"280879989919890028383901644340995387087","date":"2025-03-29T09:38:35+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-03-12T11:48:04+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"251842961846752980992035995600040759148","date":"2025-02-28T08:28:06+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"119516191274443089418493525788354969771","date":"2025-01-07T05:23:29+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-04-26T03:35:49+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-04-22T19:52:42+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-04-18T09:43:51+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-04-02T01:00:57+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Public Health","date":"2024-03-29T08:48:29+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"pubh","sideBox":"Learn more about [BMC Public Health](http://bmcpublichealth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/pubh/default.aspx","title":"BMC Public Health","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"3825a609-2a3a-42a1-be04-91463ca1ee78","owner":[],"postedDate":"April 5th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-11-10T16:03:26+00:00","versionOfRecord":{"articleIdentity":"rs-4186777","link":"https://doi.org/10.1186/s12889-025-25219-1","journal":{"identity":"bmc-public-health","isVorOnly":false,"title":"BMC Public Health"},"publishedOn":"2025-11-05 15:56:57","publishedOnDateReadable":"November 5th, 2025"},"versionCreatedAt":"2024-04-05 17:23:47","video":"","vorDoi":"10.1186/s12889-025-25219-1","vorDoiUrl":"https://doi.org/10.1186/s12889-025-25219-1","workflowStages":[]},"version":"v1","identity":"rs-4186777","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4186777","identity":"rs-4186777","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}