Unveiling Factors That Shape Contraceptive Use Among Adults in the US - Findings from the Add Health Study

Unveiling Factors That Shape Contraceptive Use Among Adults in the US - Findings from the Add Health Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Unveiling Factors That Shape Contraceptive Use Among Adults in the US - Findings from the Add Health Study Kajol Dahal, Achala Ghimire, Haleigh Ball, Ignacio Garcia, Sitasnu Dahal, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9260603/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 6 You are reading this latest preprint version Abstract Background: Most research has focused on adolescents, leaving a gap in understanding contraceptive behaviors among adults. This study aims to identify patterns and determinants of contraceptive use among adults aged 34–42. Methods: A cross-sectional analysis was conducted using Wave V of the Add Health dataset. The analytic sample included 3,552 sexually active individuals. Weighted descriptive, bivariate, and multivariable analyses were performed to explore associations between contraceptive use and demographic, socioeconomic, and relational factors. Results: Our study reveals lower odds of contraception use associated with older age (AOR: 0.92; 95% CI: 0.87–0.97), non-heterosexual identity (AOR: 0.64; 95% CI: 0.47–0.87), lower education (AOR: 0.49; 95% CI: 0.33–0.72), and cohabiting with a partner. Notably, experiencing partner violence significantly reduced the odds of contraception use (AOR: 0.64; 95% CI: 0.46–0.90). Conversely, those with no immediate pregnancy intentions had the highest odds of contraceptive use (p<0.001), while race and income were not significant predictors. Conclusions: Contraceptive use among adults is influenced by a complex interplay of individual, social, and relational factors. contraceptive use unintended pregnancy adult sexual and reproductive health Add health study 1. Introduction Unintended pregnancy, defined as pregnancies that are either mistimed or unwanted, remains a persistent public health concern in the United States. Although the overall rate of unintended pregnancies declined from 42.1 per 1,000 females aged 15–44 in 2010 to 35.7 in 2019, recent data show that this progress has not been uniform across all age groups [ 1 ]. The most notable reductions have occurred among adolescents and younger women, while rates among adults aged 35 years and older have remained stable or increased [ 1 ]. Despite this trend, much of the existing research and public health interventions continue to focus on adolescents, leaving a critical gap in understanding contraceptive behaviors among adults. Pregnancies occurring after age 35 carry elevated health risks, including higher rates of gestational diabetes, hypertension, preeclampsia, cesarean delivery, and chromosomal abnormalities [ 2 – 4 ]. These pregnancies also impose greater emotional, financial, and caregiving burdens on individuals who may have already completed their desired family size, particularly in environments with limited access to healthcare, childcare, and social support [ 5 ]. Furthermore, chronic health conditions such as obesity, hypertension, and diabetes are more prevalent in this age group, increasing the risk of maternal morbidity and mortality [ 6 ]. Addressing unintended pregnancy among adults is therefore essential not only to improve individual and family health but also to reduce healthcare costs and optimize the use of limited public health resources. Contraceptive behaviors among adults are shaped by a complex interplay of individual, social, and relational factors. Studies have shown that inconsistent, incorrect, or nonuse of contraception often described as risky contraceptive behaviors, increase the likelihood of unintended pregnancy [ 7 ]. These behaviors typically reflect barriers such as limited access to healthcare, financial constraints, dissatisfaction with contraceptive methods, report of past experiences with unwanted contraceptive side effects, or perceived low fertility risk, rather than intentional risk-taking [ 8 – 12 ]. Factors such as lower educational attainment, unstable relationships, lack of partner communication, and limited reproductive knowledge have been linked to inconsistent contraceptive use [ 7 , 9 – 11 , 13 ]. Conversely, individuals are more likely to use contraception when they perceive it as accessible, safe, and aligned with their reproductive goals [ 10 ]. Despite extensive research on adolescent reproductive health, relatively little is known about what drives contraceptive decision-making among adults. Understanding these determinants is essential for developing age-appropriate and context-sensitive interventions that promote consistent and informed contraceptive use. Therefore, this study aims to identify patterns and determinants of contraceptive use among adults aged 34–42 using nationally representative data from the Add Health Study. By examining the demographic, socioeconomic, and relational factors that shape contraceptive behavior, this study seeks to fill an important gap in the literature and inform strategies to reduce unintended pregnancies and improve reproductive health outcomes among U.S. adults. 2. Materials and Methods Data Source This study uses data from the National Longitudinal Study of Adolescent to Adult Health (Add Health), a longitudinal, nationally representative study designed to explore the social, behavioral, and biological determinants of health and well-being [ 14 ]. The Add Health cohort began in 1994–1995 (Wave I) with 20,745 students in grades 7–12. Subsequent follow-ups were conducted in 1996 (Wave II), 2001–2002 (Wave III), 2008 (Wave IV), and 2016–2018 (Wave V), when participants were aged 34–42 years. The Institutional Review Board of the University of North Carolina School of Public Health approved the data collection for Add Health. Study Design and Sample A cross-sectional analysis was conducted using the Wave V dataset. Participants aged 34–42 years who reported being sexually active and provided valid responses to the contraceptive use question were included. Respondents with legitimate skip patterns for contraceptive use were excluded. The final analytic sample included 3,552 individuals. All analyses were weighted using the Add Health survey weights to ensure national representativeness and account for the complex sampling design. Outcome Variable Contraceptive use was the dependent variable, based on the item: On average, how often do you or your partner use a contraceptive method of birth control or disease prevention? Responses were recoded into a binary variable: Yes = 1 (“always” or “sometimes”) No = 0 (“never”) Independent Variables The selection of variables in this study was guided by the Social Ecological Model (SEM), which conceptualizes health behavior as influenced by factors operating at multiple, interacting levels: individual, interpersonal, organizational, community, and societal. This framework is particularly relevant to contraceptive use, which is shaped not only by individual demographic and biological characteristics but also by relationship dynamics, healthcare access, and broader social structures. Accordingly, the variables in this study represent: (1) individual-level factors (age, sex, sexual identification, race/ethnicity, education, income, reproductive intentions/plan for a child); (2) interpersonal-level factors (living with partner, concurrent relationship, partner violence victim, partner violence perpetrator); and (3) organizational and societal-level factors (religion, insurance coverage, and perceived socioeconomic standing/socio-economic ladder). This multilevel framework enables a comprehensive understanding of personal and context. Statistical Analysis Weighted analyses were performed using Stata 17. Descriptive statistics summarized the sample distribution across key variables. Bivariate analyses (chi-square tests and t-tests) examined the associations between contraceptive use and independent variables. All variables identified in the bivariate analyses were included in the multivariable logistic regression model to assess adjusted associations with contraceptive use. The selection of these variables was guided by the theoretical framework underpinning the study, which justified retaining all independent variables in the multivariable analyses. Variance inflation factors (VIFs) were examined to assess multicollinearity, with all VIFs < 2.0, indicating no evidence of multicollinearity. Results were presented as adjusted odds ratios (AOR) with 95% confidence intervals (CIs). Ethical Considerations The Add Health data used in this study were accessed through a restricted-use data agreement with the University of North Carolina at Chapel Hill. This secondary analysis of de-identified data was deemed exempt from review by the East Tennessee State University Institutional Review Board. 3. Results 3.1. Descriptive Statistics 3.1.1. Individual-level factors Table 1 displays the full descriptive data. We identified 3,552 individual records eligible for the study. Most of the study population were White (69.5%), with a mean age of 36.6 (± 0.47) years. More than half of the study population were female (51.0%), and majority were heterosexual (87.1%). The plurality of participants (39.6%) had some college education or an associate's degree. About two-thirds of the study population reported an annual income over $ 100,000 (37.4%), which was followed closely by those earning between $ 50,000 and $ 100,000 USD (36.0%). A majority of participants (69.9%) did not plan to have a child, 23% were uncertain, and 7.1% were planning to have one. 3.1.2 Organizational and societal-level factors Majority (89.8%) were insured. In terms of religious affiliation, 29.1% were Protestant, followed by other Christian denominations (not Protestant or Catholic) at 22.5%, and atheist at 21.5%. When asked about their self-perceived social status (based on money, education, and job) 49.5% placed themselves in the lower half of the socioeconomic ladder/spectrum. 3.1.3 Interpersonal-level factors Most respondents (87.5%) lived with a partner, Additionally, 10.2% reported being victims of partner violence, while 7.1% acknowledged perpetrating violence against their partner. One-fourth of participants indicated that either they or their partner had a concurrent partner during the study period. The use of contraception was reported by 38.7%, who indicated they always or sometimes used it, whereas 61.3% reported never using contraception. Table 1 Characteristics of the Sexually Active Participants Aged 34–42 years from Wave V of the Add Health Survey (2018) (N = 3,552) Variables Mean(± SD)/N (%) Variables Mean(± SD)/N (%) Age(yrs) 36.63 (± 0.47) Income Sex Below $ 25,000 297 (10.5%) Male 1,503 (49.0%) $ 25,000- $ 50,000 487 (16.1%) Female 2,049 (51.0%) $ 50,000 to $ 100,000 1,106 (36.0%) Sexual Identification More than $ 100,000 1,214 (37.4%) Heterosexual 3,076 (87.1%) Socio-economic ladder Bisexual 417 (11.4%) Less and equal to 5 1,684 (49.5%) Homosexual 46 (1.5%) More than 5 1,851 (50.5%) Race Insurance White, non-Hispanic 2,296 (69.5%) Yes 3,248 (89.8%) Black or African American, non-Hispanic 662 (13.3%) No 277 (10.2%) Other, non-Hispanic 235 (6.4%) Partner Violence Victim Hispanic 347 (10.7%) Yes 562 (16.8%) Education No 2,847 (83.2%) Less than high school graduate 142 (5.8%) Partner Violence Perpetrator High school graduate/GED 527 (16.1%) Yes 367 (10.2%) Some college or associate's degree 1,381 (39.6%) No 3,045 (89.8%) Bachelor's degree or higher 901 (23.7%) Plan for a child Graduate or professional degree 597 (14.7%) Yes 247 (7.1%) Living with partners Maybe 762 (23.0%) Yes 3,025 (87.5%) No 2,339 (69.9%) No 429 (12.5%) Concurrent relationship Religion Yes 896 (25.0%) Atheist 718 (21.5%) No 2,528 (75.0%) Protestant 1,085 (29.1%) Contraceptive Use Catholic 531 (16.9%) Always + Sometimes (Yes) 1,369 (38.7%) Other Christian 788 (22.5%) Never (No) 2,042 (61.3%) Other 327 (9.9%) 3.2. Bivariate Analysis Table 2 summarizes the bivariate associations between contraceptive use and selected characteristics among the participants. Contraceptive users were more likely to be younger than non-users (36.7 (± 1.98) vs 37.0 (± 1.96) years, p < 0.001). Use did not differ significantly by sex, but varied by sexual identification, with heterosexual participants reporting the highest use (39.5%), followed by bisexual (36.4%) and homosexual participants (6.2%; p < 0.001). Education was strongly associated with contraceptive use (p < 0.001); more than half of those with a graduate or professional degree used contraception compared with less than one-third of those with less than a high-school education. Participants not living with a partner were more likely to use contraception (53.9%) than those who were cohabiting with partner (36.5%; p < 0.001). Contraceptive use also differed by religion (p < 0.001) and was positively associated with higher self-perceived socioeconomic status (p < 0.001) and insurance coverage (p = 0.040). Individuals who had experienced partner violence were less likely to use contraception (p = 0.008), while fertility intention showed a strong inverse relationship, those not planning a child were the most likely users (p < 0.001). Table 2 Socio-Demographic Characteristics of participants by contraceptive use Variables Contraceptive Use p-value Yes No Age(yrs) 36.67 (± 1.98) 37.03 (± 1.96) < 0.001* Sex Male 556 (36.8%) 894 (63.2%) 0.080 Female 813 (40.6%) 1,148 (59.4%) Sexual identification Heterosexual 1,204 (39.5%) 1,744 (60.5%) < 0.001* Bisexual 157 (36.4%) 255 (63.6%) Homosexual 6 (6.2%) 36 (93.8%) Race White, non-Hispanic 919 (39.5%) 1,306 (60.5%) 0.239 Black or African American, non-Hispanic 238 (36.9%) 386 (63.1%) Other, non-Hispanic 98 (43.0%) 126 (57.0%) Hispanic 112 (33.4%) 216 (66.6%) Education Graduate or professional degree 311 (53.3%) 273 (46.7%) < 0.001* Bachelor's degree or higher 407 (44.4%) 467 (55.6%) Some college or associate's degree 454 (34.5%) 864 (65.5%) High school graduate/GED 162 (33.0%) 334 (67.0%) Less than high school graduate 35 (22.7%) 102 (77.3%) Living with partners Yes 1,127 (36.5%) 1,862 (63.5%) < 0.001* No 240 (53.9%) 180 (46.1%) Religion Atheist 333 (45.1%) 378 (54.9%) 0.001* Protestant 426 (38.9%) 643 (61.1%) Catholic 194 (34.8%) 325 (65.2%) Other Christian 276 (32.9%) 502 (67.1%) Other 134 (43.8%) 187 (56.2%) Income Below $ 25,000 103 (34.6%) 182 (65.4%) 0.098 $ 25,000- $ 50,000 161 (32.3%) 300 (67.7%) $ 50,000 to $ 100,000 406 (38.4%) 670 (61.6%) More than $ 100,000 509 (40.4%) 676 (59.6%) Socio-economic ladder Less and equal to 5 573 (34.8%) 1,052 (65.2%) < 0.001* More than 5 795 (42.7%) 979 (57.3%) Insurance Yes 1,266 (39.5%) 1,859 (60.5%) 0.040* No 96 (31.3%) 170 (68.7%) Partner Violence Victim Yes 184 (32.2%) 370 (67.8%) 0.008* No 1,169 (39.8%) 1,650 (60.2%) Partner Violence Perpetrator Yes 126 (33.5%) 237 (66.5%) 0.112 No 1,220 (39.0%) 1,790 (61.0%) Plan for a child Yes 31 (11.0%) 216 (89.0%) < 0.001* Maybe 411 (50.8%) 347 (49.2%) No 895 (37.7%) 1,431 (62.3%) Concurrent relationship Yes 339 (35.1%) 554 (64.9%) 0.053 No 1,022 (39.9%) 1,479 (60.1%) * p-values reported from chi-square and t-test, * p < 0.05 3.2. Multivariable Analysis Table 3 shows the multiple logistic regression results. With increase in age there was significantly lower odds of contraceptive use (AOR = 0.92, 95% CI: 0.87–0.97, p = 0.002). Females were more likely to use contraception than males (AOR = 1.28, 95% CI: 1.03–1.59, p = 0.024). Sexual identification remained significant, with homosexual or bisexual participants less likely to use contraception compared to heterosexuals (AOR = 0.64, 95% CI: 0.47–0.87, p = 0.005). Individuals with lower educational level were significantly less likely to use contraception than those with advanced degree. Not living with a partner doubled the odds of contraceptive use (AOR = 2.05, 95% CI: 1.38–3.06, p < 0.001) than living with partner. Participants who experienced partner violence were less likely to use contraception (AOR = 0.64, 95% CI: 0.46–0.90, p = 0.010) compared to their counterparts. Pregnancy intention of those who were uncertain or not planning a child had significantly higher odds of contraceptive use (p < 0.001) compared to those who were planning for a child. Race, religion, and income, were not significantly associated with contraceptive use. Table 3 Multivariable Logistic Regression Analysis of the Variables Variables Contraceptive Use Adjusted Odds Ratio (95% CI) p-value Age(yrs) 0.92 (0.87–0.97) 0.002* Sex Male Ref Ref Female 1.28(1.03–1.59) 0.024* Sexual identification Heterosexual Ref Ref Homo/Bi-sexual 0.64(0.47–0.87) 0.005* Race White, non-Hispanic Ref Ref Black or African American, non-Hispanic 0.88(0.64–1.21) 0.435 Other, non-Hispanic 1.37(7(0.89–2.12) 0.150 Hispanic 0.90(0.62–1.31) 0.592 Education Less than high school graduate 0.68(0.50–0.92) 0.011* High school graduate/GED 0.49(0.36–0.66) < 0.001* Some college or associate's degree 0.50(0.34–0.73) < 0.001* Bachelor's degree or higher 0.30(0.16–0.55) < 0.001* Graduate or professional degree Ref Ref Living with partners Yes Ref Ref No 2.05(1.38–3.06) < 0.001* Religion Protestant Ref Ref Catholic 0.91(0.66–1.26) 0.573 Other Christian 0.81(0.61–1.08) 0.153 Other 1.15(0.80–1.67) 0.448 Atheist 1.32(0.99–1.75) 0.058 Income Below $ 25,000 1.09(0.86–1.39) 0.478 $ 25,000- $ 50,000 0.83(0.59–1.18) 0.305 $ 50,000 to $ 100,000 1.09(0.70–1.70) 0.688 More than $ 100,000 Ref Ref Socio-economic ladder Less and equal to 5 0.83(0.66–1.05) 0.120 More than 5 Ref Ref Insurance Yes Ref Ref No 0.99(0.65–1.52) 0.972 Partner Violence Victims Yes 0.64(0.46–0.90) 0.010* No Ref Ref Partner Violence Perpetrators Yes 1.29(0.87–1.90) 0.201 No Ref Ref Plan for a child Yes Ref Ref Maybe 10.54(5.42–20.51) < 0.001* No 6.46(3.41–12.24) < 0.001* Concurrent relationship Yes 0.83(0.65–1.06) 0.129 No Ref Ref * p-values reported from chi-square and t-test, * p < 0.05 4. Discussion This study provides insights into the demographic, socioeconomic, and relational determinants of contraceptive use among U.S. adults aged 34–42, an age group often overlooked in reproductive health research. The use of contraception was reported by 38.7%, who indicated they always or sometimes used it. Younger age within the age group of 34–42, female sex, heterosexual identification, higher education, not living with partner, and clear reproductive intentions were associated with greater contraceptive use, whereas experiences of partner violence reduced the use of it. The finding that contraceptive use declines with increasing age aligns with prior studies showing that older adults perceive a lower risk of pregnancy or encounter barriers to accessing reproductive health services [ 7 , 15 ]. Midlife adults may deprioritize contraception due to perceived infertility or past experiences with unwanted side effects, underscoring the need for continued reproductive health counseling beyond the reproductive peak years [ 11 ]. Consistent with prior literature, education emerged as a strong predictor of contraceptive use. Individuals with higher educational attainment were significantly more likely to report contraceptive use, reflecting the established link between education, health literacy, and autonomy in reproductive decision-making [ 16 , 17 ]. Higher education may also correspond with increased access to healthcare resources and stronger communication with providers, facilitating more consistent contraceptive behaviors. In contrast, those with lower educational attainment may face greater misinformation, reduced access to healthcare, and limited economic means to obtain contraception [ 18 , 19 ]. The study also identified gender and sexual identification as important correlates of contraceptive use. Consistent with most of the literature, females were found to use contraceptive methods significantly more often than males [ 20 – 23 ]. However, in this study, the difference was not very large: 41% of females reported using contraception compared to 37% of males. This likely reflects women’s higher engagement with reproductive health services. Homosexual and bisexual participants were less likely to report using contraception compared to heterosexual participants. One reason is that many individuals in these groups may not have sex with opposite-sex partners, reducing their risk of unintended pregnancy. Still, we expected that bisexual and homosexual individuals might use contraception to protect themselves against sexually transmitted diseases. Our findings are consistent with earlier studies showing that sexual minority groups often make less use of gynecologic and family-planning services [ 24 ]. Another possible explanation is that many healthcare settings continue to assume patients are heterosexual, and sexual health counseling is often not fully inclusive of people with diverse sexual orientations. There are two differing assessments on the linkage between cohabitation and contraceptive use. Some literature claims married couple living together with more stable relation use contraception more and in a consistent way [ 25 ]. While others, similar to our study suggest that individuals not living/ non-cohabiting with their partners were more likely to use contraception as a preventive measure against unintended pregnancy and sexually transmitted infections [ 9 ]. This contrast highlights the importance of considering relationship dynamics when examining contraceptive behavior. However, victims of partner violence were significantly less likely to use contraception, a finding supported by literature linking intimate partner violence (IPV) to reproductive coercion and reduced contraceptive autonomy [ 26 , 27 ]. This underscores the importance of integrating reproductive health screening with IPV prevention programs and ensuring that healthcare settings provide trauma-informed contraceptive counseling [ 28 ]. Pregnancy intention was the strongest predictor of contraceptive use, consistent with research showing that individuals with clear reproductive goals are more proactive in using contraception [ 29 ]. However, the higher odds of contraceptive use among those who were uncertain or not planning a child highlight that reproductive intentions among adulthood are fluid and shaped by life course factors such as financial stability, relationship satisfaction, and prior parenting experience [ 30 ]. Collectively, these findings suggest that contraceptive behaviors among midlife adults are influenced by broader social and relational contexts. Addressing these determinants requires expanding family planning initiatives beyond younger populations to include counseling and resources for adults who may underestimate their fertility risk. Strengthening health planning and interventions inclusive of older individuals, promoting reproductive health education tailored to adults, and integrating IPV screening into reproductive care could significantly reduce unintended pregnancies in this population. 5. Conclusions This study highlights that contraceptive utilization among adults aged 34–42 in the United States is influenced by a multidimensional interplay of demographic, socioeconomic, and interpersonal factors. Younger age within the age group of 34–42, female sex, heterosexual identification, higher education, not living with partner, and clear reproductive intentions were associated with greater contraceptive use, whereas experiences of partner violence reduced use. These findings emphasize that interventions to reduce unintended pregnancy among adults should extend beyond access to contraceptive methods and focus on the social and relational environments in which reproductive choices occur. Public health programs should incorporate ongoing reproductive counseling for midlife adults, including discussions about fertility awareness, and method options suitable for older users. Additionally, integrating IPV screening and trauma-informed care into reproductive health services can protect contraceptive autonomy for vulnerable individuals. Future research should explore how evolving social norms, gender roles, and healthcare education influence contraceptive decision-making in adulthood. By centering this often-overlooked age group, public health practitioners can design inclusive, evidence-based interventions that support informed reproductive choices and further reduce unintended pregnancies across the lifespan. Declarations Author Contributions: Conceptualization, K.D., A.G., H.B., and I.G.; methodology, K.D., A.G., H.B., and I.G.; formal analysis, K.D.; writing—original draft preparation, K.D., A.G., H.B., and I.G.; writing—review and editing, K.D., M.A., S.D., A.M., E.F.A.A., H.N., and Su.D.; supervision, M.A. All authors have read and agreed to the published version of the manuscript. Funding: This research received no external funding. Institutional Review Board Statement: Ethical review and approval were waived for this study due to publicly available information and data with no identifying information. Data Availability Statement: The original data presented in the study are openly available in Add Health at https://addhealth.cpc.unc.edu/data/ Acknowledgments: We acknowledge Dr. Manik Ahuja for the supervision and technical expertise. Conflicts of Interest: The authors declare no conflicts of interest. Ethics approval and consent to participate This study involved secondary analysis of de‑identified data from the National Longitudinal Study of Adolescent to Adult Health (Add Health), originally collected by the University of North Carolina at Chapel Hill. The East Tennessee State University Institutional Review Board reviewed the project and determined that it is exempt from IRB oversight because it uses existing, fully de‑identified data. As no identifiable information was accessed and no direct contact with participants occurred, informed consent was not required. Clinical trial number Not applicable. Consent for publication This manuscript does not contain any individual person’s data in an identifiable form (including individual details, images, or videos); therefore, individual consent for publication is not applicable. All authors have reviewed the final version of the manuscript and give their full consent for its publication. Competing interests The authors declare no competing interests. References Center for Health Statistics N, Vital, Statistics H. Series 2, Number 201 n.d. https://doi.org/10.15620/cdc:124395 Gantt A, Metz TD, Kuller JA, Louis JM, Cahill AG, Turrentine MA. Pregnancy at Age 35 Years or Older: ACOG Obstetric Care Consensus 11. Obstet Gynecol. 2022;140:348–66. https://doi.org/10.1097/AOG.0000000000004873 . Cavazos-Rehg PA, Krauss MJ, Spitznagel EL, Bommarito K, Madden T, Olsen MA, et al. Maternal age and risk of labor and delivery complications HHS Public Access. Matern Child Health J. 2015;19:1202–11. https://doi.org/10.1007/s10995-014-1624-7 . 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Policy Forum Intimate Partner Violence and Reproductive Coercion: Global Barriers to Women’s Reproductive Control 2014. https://doi.org/10.1371/journal.pmed.1001723 Mccauley HL, Silverman JG, Jones KA, Tancredi DJ, Decker MR, Mccormick MC et al. Psychometric properties and refinement of the Reproductive Coercion Scale ☆,☆☆,★ 2017. https://doi.org/10.1016/j.contraception.2016.09.010 Samari G, Foster DG, Ralph LJ, Rocca CH. Pregnancy Preferences and Contraceptive Use among US Women HHS Public Access. Contraception. 2020;101:79–85. https://doi.org/10.1016/j.contraception.2019.10.007 . Yeatman S, Sennott C. Fertility Desires and Contraceptive Transition. Popul Dev Rev. 2024;50:511. https://doi.org/10.1111/PADR.12669 . Additional Declarations No competing interests reported. Supplementary Files AppendixA.docx Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 06 May, 2026 Reviewers invited by journal 01 May, 2026 Editor invited by journal 20 Apr, 2026 Editor assigned by journal 02 Apr, 2026 Submission checks completed at journal 02 Apr, 2026 First submitted to journal 29 Mar, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-9260603","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":635730556,"identity":"4552dbbc-0a96-4dbc-a6c7-3235bb8b478a","order_by":0,"name":"Kajol Dahal","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAuElEQVRIiWNgGAWjYDCCAzwMDA8O2EB5bMRqSTiQxsBDqpbDJGjhO3724IeEM+fl7PnPGDB8KDtMWIvkmbxkiYQbt415JHIMGGecI0KLwYEcA4mED7cTeyR4DJh524jRcv6N8Y+ED+fqe4AOY/5LlJYbOWZAhx1I4GHIMWBmJEaL5I03ZhYJZ5INe26kFRzsOZdOWAvf+RzjGx+O2cmz9x/e+OBHmTVhLSjgAInqR8EoGAWjYBTgAgDjO0A9NmOddgAAAABJRU5ErkJggg==","orcid":"","institution":"East Tennessee State University","correspondingAuthor":true,"prefix":"","firstName":"Kajol","middleName":"","lastName":"Dahal","suffix":""},{"id":635730557,"identity":"66e091ec-5f07-4d4e-92a6-5ba1c592315f","order_by":1,"name":"Achala Ghimire","email":"","orcid":"","institution":"East Tennessee State University","correspondingAuthor":false,"prefix":"","firstName":"Achala","middleName":"","lastName":"Ghimire","suffix":""},{"id":635730558,"identity":"8ae52b83-296d-4ad0-9422-53b4a184b083","order_by":2,"name":"Haleigh Ball","email":"","orcid":"","institution":"East Tennessee State University","correspondingAuthor":false,"prefix":"","firstName":"Haleigh","middleName":"","lastName":"Ball","suffix":""},{"id":635730559,"identity":"5ba0edc3-d1b8-412c-8f3f-366e580152f7","order_by":3,"name":"Ignacio Garcia","email":"","orcid":"","institution":"East Tennessee State University","correspondingAuthor":false,"prefix":"","firstName":"Ignacio","middleName":"","lastName":"Garcia","suffix":""},{"id":635730560,"identity":"42932941-5228-4e2f-aefd-4ba2372882ee","order_by":4,"name":"Sitasnu Dahal","email":"","orcid":"","institution":"Pennsylvania State University","correspondingAuthor":false,"prefix":"","firstName":"Sitasnu","middleName":"","lastName":"Dahal","suffix":""},{"id":635730561,"identity":"af2e9936-6449-4dad-a544-18c0a29c99c9","order_by":5,"name":"Anita Mahotra","email":"","orcid":"","institution":"University of Iowa","correspondingAuthor":false,"prefix":"","firstName":"Anita","middleName":"","lastName":"Mahotra","suffix":""},{"id":635730562,"identity":"f3522730-16bd-46a4-8d07-7e572119d25e","order_by":6,"name":"Esther Fadekemi Adebayo Abikoye","email":"","orcid":"","institution":"East Tennessee State University","correspondingAuthor":false,"prefix":"","firstName":"Esther","middleName":"Fadekemi Adebayo","lastName":"Abikoye","suffix":""},{"id":635730563,"identity":"1780b95a-4045-4540-87a1-4ada8f638575","order_by":7,"name":"Hemanta Neupane","email":"","orcid":"","institution":"East Tennessee State University","correspondingAuthor":false,"prefix":"","firstName":"Hemanta","middleName":"","lastName":"Neupane","suffix":""},{"id":635730564,"identity":"1681edd0-89ff-43c4-8c04-5aa55db6be30","order_by":8,"name":"Subecha Dahal","email":"","orcid":"","institution":"Drexel University","correspondingAuthor":false,"prefix":"","firstName":"Subecha","middleName":"","lastName":"Dahal","suffix":""},{"id":635730566,"identity":"4d21f537-b995-4b6c-aac2-51c02bc2b047","order_by":9,"name":"Manik Ahuja","email":"","orcid":"","institution":"East Tennessee State University","correspondingAuthor":false,"prefix":"","firstName":"Manik","middleName":"","lastName":"Ahuja","suffix":""}],"badges":[],"createdAt":"2026-03-29 18:53:50","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9260603/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9260603/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":108984400,"identity":"7e51f29f-5158-4466-b80f-8ad04024cc6b","added_by":"auto","created_at":"2026-05-11 12:40:13","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":463296,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9260603/v1/393da58d-bbe7-411c-9d2f-39ab9fa985c4.pdf"},{"id":108982372,"identity":"e33e69c1-b7f2-470f-9e92-6b2bda16cbd5","added_by":"auto","created_at":"2026-05-11 12:24:54","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":19422,"visible":true,"origin":"","legend":"","description":"","filename":"AppendixA.docx","url":"https://assets-eu.researchsquare.com/files/rs-9260603/v1/e6108c1bc3336c630852ba80.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Unveiling Factors That Shape Contraceptive Use Among Adults in the US - Findings from the Add Health Study","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eUnintended pregnancy, defined as pregnancies that are either mistimed or unwanted, remains a persistent public health concern in the United States. Although the overall rate of unintended pregnancies declined from 42.1 per 1,000 females aged 15\u0026ndash;44 in 2010 to 35.7 in 2019, recent data show that this progress has not been uniform across all age groups [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. The most notable reductions have occurred among adolescents and younger women, while rates among adults aged 35 years and older have remained stable or increased [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Despite this trend, much of the existing research and public health interventions continue to focus on adolescents, leaving a critical gap in understanding contraceptive behaviors among adults.\u003c/p\u003e \u003cp\u003ePregnancies occurring after age 35 carry elevated health risks, including higher rates of gestational diabetes, hypertension, preeclampsia, cesarean delivery, and chromosomal abnormalities [\u003cspan additionalcitationids=\"CR3\" citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. These pregnancies also impose greater emotional, financial, and caregiving burdens on individuals who may have already completed their desired family size, particularly in environments with limited access to healthcare, childcare, and social support [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Furthermore, chronic health conditions such as obesity, hypertension, and diabetes are more prevalent in this age group, increasing the risk of maternal morbidity and mortality [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Addressing unintended pregnancy among adults is therefore essential not only to improve individual and family health but also to reduce healthcare costs and optimize the use of limited public health resources.\u003c/p\u003e \u003cp\u003eContraceptive behaviors among adults are shaped by a complex interplay of individual, social, and relational factors. Studies have shown that inconsistent, incorrect, or nonuse of contraception often described as risky contraceptive behaviors, increase the likelihood of unintended pregnancy [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. These behaviors typically reflect barriers such as limited access to healthcare, financial constraints, dissatisfaction with contraceptive methods, report of past experiences with unwanted contraceptive side effects, or perceived low fertility risk, rather than intentional risk-taking [\u003cspan additionalcitationids=\"CR9 CR10 CR11\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Factors such as lower educational attainment, unstable relationships, lack of partner communication, and limited reproductive knowledge have been linked to inconsistent contraceptive use [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Conversely, individuals are more likely to use contraception when they perceive it as accessible, safe, and aligned with their reproductive goals [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDespite extensive research on adolescent reproductive health, relatively little is known about what drives contraceptive decision-making among adults. Understanding these determinants is essential for developing age-appropriate and context-sensitive interventions that promote consistent and informed contraceptive use. Therefore, this study aims to identify patterns and determinants of contraceptive use among adults aged 34\u0026ndash;42 using nationally representative data from the Add Health Study. By examining the demographic, socioeconomic, and relational factors that shape contraceptive behavior, this study seeks to fill an important gap in the literature and inform strategies to reduce unintended pregnancies and improve reproductive health outcomes among U.S. adults.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003e \u003cem\u003eData Source\u003c/em\u003e \u003c/p\u003e \u003cp\u003eThis study uses data from the National Longitudinal Study of Adolescent to Adult Health (Add Health), a longitudinal, nationally representative study designed to explore the social, behavioral, and biological determinants of health and well-being [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. The Add Health cohort began in 1994\u0026ndash;1995 (Wave I) with 20,745 students in grades 7\u0026ndash;12. Subsequent follow-ups were conducted in 1996 (Wave II), 2001\u0026ndash;2002 (Wave III), 2008 (Wave IV), and 2016\u0026ndash;2018 (Wave V), when participants were aged 34\u0026ndash;42 years. The Institutional Review Board of the University of North Carolina School of Public Health approved the data collection for Add Health.\u003c/p\u003e \u003cp\u003e \u003cem\u003eStudy Design and Sample\u003c/em\u003e \u003c/p\u003e \u003cp\u003eA cross-sectional analysis was conducted using the Wave V dataset. Participants aged 34\u0026ndash;42 years who reported being sexually active and provided valid responses to the contraceptive use question were included. Respondents with legitimate skip patterns for contraceptive use were excluded. The final analytic sample included 3,552 individuals. All analyses were weighted using the Add Health survey weights to ensure national representativeness and account for the complex sampling design.\u003c/p\u003e \u003cp\u003e \u003cem\u003eOutcome Variable\u003c/em\u003e \u003c/p\u003e \u003cp\u003eContraceptive use was the dependent variable, based on the item:\u003c/p\u003e \u003cp\u003eOn average, how often do you or your partner use a contraceptive method of birth control or disease prevention?\u003c/p\u003e \u003cp\u003eResponses were recoded into a binary variable:\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cul\u003e \u003cli\u003e \u003cp\u003eYes\u0026thinsp;=\u0026thinsp;1 (\u0026ldquo;always\u0026rdquo; or \u0026ldquo;sometimes\u0026rdquo;)\u003c/p\u003e \u003c/li\u003e \u003cli\u003e \u003cp\u003eNo\u0026thinsp;=\u0026thinsp;0 (\u0026ldquo;never\u0026rdquo;)\u003c/p\u003e \u003c/li\u003e \u003c/ul\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003e \u003cem\u003eIndependent Variables\u003c/em\u003e \u003c/p\u003e \u003cp\u003eThe selection of variables in this study was guided by the Social Ecological Model (SEM), which conceptualizes health behavior as influenced by factors operating at multiple, interacting levels: individual, interpersonal, organizational, community, and societal. This framework is particularly relevant to contraceptive use, which is shaped not only by individual demographic and biological characteristics but also by relationship dynamics, healthcare access, and broader social structures. Accordingly, the variables in this study represent: (1) individual-level factors (age, sex, sexual identification, race/ethnicity, education, income, reproductive intentions/plan for a child); (2) interpersonal-level factors (living with partner, concurrent relationship, partner violence victim, partner violence perpetrator); and (3) organizational and societal-level factors (religion, insurance coverage, and perceived socioeconomic standing/socio-economic ladder). This multilevel framework enables a comprehensive understanding of personal and context.\u003c/p\u003e \u003cp\u003e \u003cem\u003eStatistical Analysis\u003c/em\u003e \u003c/p\u003e \u003cp\u003eWeighted analyses were performed using Stata 17. Descriptive statistics summarized the sample distribution across key variables. Bivariate analyses (chi-square tests and t-tests) examined the associations between contraceptive use and independent variables. All variables identified in the bivariate analyses were included in the multivariable logistic regression model to assess adjusted associations with contraceptive use. The selection of these variables was guided by the theoretical framework underpinning the study, which justified retaining all independent variables in the multivariable analyses. Variance inflation factors (VIFs) were examined to assess multicollinearity, with all VIFs\u0026thinsp;\u0026lt;\u0026thinsp;2.0, indicating no evidence of multicollinearity. Results were presented as adjusted odds ratios (AOR) with 95% confidence intervals (CIs).\u003c/p\u003e \u003cp\u003e \u003cem\u003eEthical Considerations\u003c/em\u003e \u003c/p\u003e \u003cp\u003eThe Add Health data used in this study were accessed through a restricted-use data agreement with the University of North Carolina at Chapel Hill. This secondary analysis of de-identified data was deemed exempt from review by the East Tennessee State University Institutional Review Board.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Descriptive Statistics\u003c/h2\u003e \u003cdiv id=\"Sec5\" class=\"Section3\"\u003e \u003ch2\u003e3.1.1. Individual-level factors\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e displays the full descriptive data. We identified 3,552 individual records eligible for the study. Most of the study population were White (69.5%), with a mean age of 36.6 (\u0026plusmn;\u0026thinsp;0.47) years. More than half of the study population were female (51.0%), and majority were heterosexual (87.1%). The plurality of participants (39.6%) had some college education or an associate's degree. About two-thirds of the study population reported an annual income over \u003cspan\u003e$\u003c/span\u003e100,000 (37.4%), which was followed closely by those earning between \u003cspan\u003e$\u003c/span\u003e50,000 and \u003cspan\u003e$\u003c/span\u003e100,000 USD (36.0%). A majority of participants (69.9%) did not plan to have a child, 23% were uncertain, and 7.1% were planning to have one.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section3\"\u003e \u003ch2\u003e3.1.2 Organizational and societal-level factors\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eMajority (89.8%) were insured. In terms of religious affiliation, 29.1% were Protestant, followed by other Christian denominations (not Protestant or Catholic) at 22.5%, and atheist at 21.5%. When asked about their self-perceived social status (based on money, education, and job) 49.5% placed themselves in the lower half of the socioeconomic ladder/spectrum.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section3\"\u003e \u003ch2\u003e3.1.3 Interpersonal-level factors\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eMost respondents (87.5%) lived with a partner, Additionally, 10.2% reported being victims of partner violence, while 7.1% acknowledged perpetrating violence against their partner. One-fourth of participants indicated that either they or their partner had a concurrent partner during the study period. The use of contraception was reported by 38.7%, who indicated they always or sometimes used it, whereas 61.3% reported never using contraception.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eCharacteristics of the Sexually Active Participants Aged 34\u0026ndash;42 years from Wave V of the Add Health Survey (2018) (N\u0026thinsp;=\u0026thinsp;3,552)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMean(\u0026plusmn;\u0026thinsp;SD)/N (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMean(\u0026plusmn;\u0026thinsp;SD)/N (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge(yrs)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36.63 (\u0026plusmn;\u0026thinsp;0.47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eIncome\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBelow \u003cspan\u003e$\u003c/span\u003e25,000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e297 (10.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,503 (49.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cspan\u003e$\u003c/span\u003e25,000-\u003cspan\u003e$\u003c/span\u003e50,000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e487 (16.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,049 (51.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cspan\u003e$\u003c/span\u003e50,000 to \u003cspan\u003e$\u003c/span\u003e100,000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1,106 (36.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSexual Identification\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMore than \u003cspan\u003e$\u003c/span\u003e100,000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1,214 (37.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeterosexual\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,076 (87.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eSocio-economic ladder\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBisexual\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e417 (11.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLess and equal to 5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1,684 (49.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHomosexual\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e46 (1.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMore than 5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1,851 (50.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRace\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eInsurance\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWhite, non-Hispanic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2,296 (69.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3,248 (89.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlack or African American, non-Hispanic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e662 (13.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e277 (10.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther, non-Hispanic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e235 (6.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003ePartner Violence Victim\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHispanic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e347 (10.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e562 (16.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2,847 (83.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLess than high school graduate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e142 (5.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003ePartner Violence Perpetrator\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh school graduate/GED\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e527 (16.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e367 (10.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSome college or associate's degree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,381 (39.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e3,045 (89.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBachelor's degree or higher\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e901 (23.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003ePlan for a child\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGraduate or professional degree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e597 (14.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e247 (7.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLiving with partners\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMaybe\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e762 (23.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3,025 (87.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2,339 (69.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e429 (12.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eConcurrent relationship\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eReligion\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e896 (25.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAtheist\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e718 (21.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2,528 (75.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProtestant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,085 (29.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eContraceptive Use\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCatholic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e531 (16.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAlways\u0026thinsp;+\u0026thinsp;Sometimes (Yes)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1,369 (38.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther Christian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e788 (22.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNever (No)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e2,042 (61.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e327 (9.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Bivariate Analysis\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e summarizes the bivariate associations between contraceptive use and selected characteristics among the participants. Contraceptive users were more likely to be younger than non-users (36.7 (\u0026plusmn;\u0026thinsp;1.98) vs 37.0 (\u0026plusmn;\u0026thinsp;1.96) years, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Use did not differ significantly by sex, but varied by sexual identification, with heterosexual participants reporting the highest use (39.5%), followed by bisexual (36.4%) and homosexual participants (6.2%; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Education was strongly associated with contraceptive use (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001); more than half of those with a graduate or professional degree used contraception compared with less than one-third of those with less than a high-school education. Participants not living with a partner were more likely to use contraception (53.9%) than those who were cohabiting with partner (36.5%; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Contraceptive use also differed by religion (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and was positively associated with higher self-perceived socioeconomic status (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and insurance coverage (p\u0026thinsp;=\u0026thinsp;0.040). Individuals who had experienced partner violence were less likely to use contraception (p\u0026thinsp;=\u0026thinsp;0.008), while fertility intention showed a strong inverse relationship, those not planning a child were the most likely users (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSocio-Demographic Characteristics of participants by contraceptive use\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eContraceptive Use\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eYes\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003eNo\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge(yrs)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36.67 (\u0026plusmn;\u0026thinsp;1.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37.03 (\u0026plusmn;\u0026thinsp;1.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e556 (36.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e894 (63.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.080\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e813 (40.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,148 (59.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSexual identification\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeterosexual\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,204 (39.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,744 (60.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBisexual\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e157 (36.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e255 (63.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHomosexual\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (6.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36 (93.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRace\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWhite, non-Hispanic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e919 (39.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,306 (60.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.239\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlack or African American, non-Hispanic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e238 (36.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e386 (63.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther, non-Hispanic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e98 (43.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e126 (57.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHispanic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e112 (33.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e216 (66.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGraduate or professional degree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e311 (53.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e273 (46.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBachelor's degree or higher\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e407 (44.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e467 (55.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSome college or associate's degree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e454 (34.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e864 (65.5%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh school graduate/GED\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e162 (33.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e334 (67.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLess than high school graduate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35 (22.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e102 (77.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLiving with partners\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,127 (36.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,862 (63.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e240 (53.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e180 (46.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eReligion\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAtheist\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e333 (45.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e378 (54.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e\u003cb\u003e0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProtestant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e426 (38.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e643 (61.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCatholic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e194 (34.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e325 (65.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther Christian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e276 (32.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e502 (67.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e134 (43.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e187 (56.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIncome\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBelow \u003cspan\u003e$\u003c/span\u003e25,000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e103 (34.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e182 (65.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.098\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cspan\u003e$\u003c/span\u003e25,000-\u003cspan\u003e$\u003c/span\u003e50,000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e161 (32.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e300 (67.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cspan\u003e$\u003c/span\u003e50,000 to \u003cspan\u003e$\u003c/span\u003e100,000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e406 (38.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e670 (61.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMore than \u003cspan\u003e$\u003c/span\u003e100,000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e509 (40.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e676 (59.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSocio-economic ladder\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLess and equal to 5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e573 (34.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,052 (65.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMore than 5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e795 (42.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e979 (57.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eInsurance\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,266 (39.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,859 (60.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e0.040*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e96 (31.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e170 (68.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePartner Violence Victim\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e184 (32.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e370 (67.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e0.008*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,169 (39.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,650 (60.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePartner Violence Perpetrator\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e126 (33.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e237 (66.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.112\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,220 (39.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,790 (61.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePlan for a child\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31 (11.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e216 (89.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaybe\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e411 (50.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e347 (49.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e895 (37.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,431 (62.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eConcurrent relationship\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e339 (35.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e554 (64.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.053\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1,022 (39.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,479 (60.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e* p-values reported from chi-square and t-test, * p\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.2. Multivariable Analysis\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e shows the multiple logistic regression results. With increase in age there was significantly lower odds of contraceptive use (AOR\u0026thinsp;=\u0026thinsp;0.92, 95% CI: 0.87\u0026ndash;0.97, p\u0026thinsp;=\u0026thinsp;0.002). Females were more likely to use contraception than males (AOR\u0026thinsp;=\u0026thinsp;1.28, 95% CI: 1.03\u0026ndash;1.59, p\u0026thinsp;=\u0026thinsp;0.024). Sexual identification remained significant, with homosexual or bisexual participants less likely to use contraception compared to heterosexuals (AOR\u0026thinsp;=\u0026thinsp;0.64, 95% CI: 0.47\u0026ndash;0.87, p\u0026thinsp;=\u0026thinsp;0.005). Individuals with lower educational level were significantly less likely to use contraception than those with advanced degree. Not living with a partner doubled the odds of contraceptive use (AOR\u0026thinsp;=\u0026thinsp;2.05, 95% CI: 1.38\u0026ndash;3.06, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) than living with partner. Participants who experienced partner violence were less likely to use contraception (AOR\u0026thinsp;=\u0026thinsp;0.64, 95% CI: 0.46\u0026ndash;0.90, p\u0026thinsp;=\u0026thinsp;0.010) compared to their counterparts. Pregnancy intention of those who were uncertain or not planning a child had significantly higher odds of contraceptive use (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) compared to those who were planning for a child. Race, religion, and income, were not significantly associated with contraceptive use.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eMultivariable Logistic Regression Analysis of the Variables\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eContraceptive Use\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eAdjusted Odds Ratio (95% CI)\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003ep-value\u003c/b\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge(yrs)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.92 (0.87\u0026ndash;0.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.002*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSex\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.28(1.03\u0026ndash;1.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.024*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSexual identification\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeterosexual\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHomo/Bi-sexual\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.64(0.47\u0026ndash;0.87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.005*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRace\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWhite, non-Hispanic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBlack or African American, non-Hispanic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.88(0.64\u0026ndash;1.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.435\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther, non-Hispanic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.37(7(0.89\u0026ndash;2.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.150\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHispanic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.90(0.62\u0026ndash;1.31)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.592\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEducation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLess than high school graduate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.68(0.50\u0026ndash;0.92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.011*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh school graduate/GED\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.49(0.36\u0026ndash;0.66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSome college or associate's degree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.50(0.34\u0026ndash;0.73)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBachelor's degree or higher\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.30(0.16\u0026ndash;0.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGraduate or professional degree\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eLiving with partners\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2.05(1.38\u0026ndash;3.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eReligion\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProtestant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCatholic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.91(0.66\u0026ndash;1.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.573\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther Christian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.81(0.61\u0026ndash;1.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.153\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.15(0.80\u0026ndash;1.67)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.448\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAtheist\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.32(0.99\u0026ndash;1.75)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.058\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIncome\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBelow \u003cspan\u003e$\u003c/span\u003e25,000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.09(0.86\u0026ndash;1.39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.478\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cspan\u003e$\u003c/span\u003e25,000-\u003cspan\u003e$\u003c/span\u003e50,000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.83(0.59\u0026ndash;1.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.305\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cspan\u003e$\u003c/span\u003e50,000 to \u003cspan\u003e$\u003c/span\u003e100,000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.09(0.70\u0026ndash;1.70)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.688\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMore than \u003cspan\u003e$\u003c/span\u003e100,000\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eSocio-economic ladder\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLess and equal to 5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.83(0.66\u0026ndash;1.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.120\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMore than 5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eInsurance\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.99(0.65\u0026ndash;1.52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.972\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePartner Violence Victims\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.64(0.46\u0026ndash;0.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e0.010*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePartner Violence Perpetrators\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.29(0.87\u0026ndash;1.90)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.201\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePlan for a child\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMaybe\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10.54(5.42\u0026ndash;20.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6.46(3.41\u0026ndash;12.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e\u0026lt;\u0026thinsp;0.001*\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eConcurrent relationship\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.83(0.65\u0026ndash;1.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.129\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eRef\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003e* p-values reported from chi-square and t-test, * p\u0026thinsp;\u0026lt;\u0026thinsp;0.05\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThis study provides insights into the demographic, socioeconomic, and relational determinants of contraceptive use among U.S. adults aged 34\u0026ndash;42, an age group often overlooked in reproductive health research. The use of contraception was reported by 38.7%, who indicated they always or sometimes used it. Younger age within the age group of 34\u0026ndash;42, female sex, heterosexual identification, higher education, not living with partner, and clear reproductive intentions were associated with greater contraceptive use, whereas experiences of partner violence reduced the use of it.\u003c/p\u003e \u003cp\u003eThe finding that contraceptive use declines with increasing age aligns with prior studies showing that older adults perceive a lower risk of pregnancy or encounter barriers to accessing reproductive health services [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Midlife adults may deprioritize contraception due to perceived infertility or past experiences with unwanted side effects, underscoring the need for continued reproductive health counseling beyond the reproductive peak years [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eConsistent with prior literature, education emerged as a strong predictor of contraceptive use. Individuals with higher educational attainment were significantly more likely to report contraceptive use, reflecting the established link between education, health literacy, and autonomy in reproductive decision-making [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Higher education may also correspond with increased access to healthcare resources and stronger communication with providers, facilitating more consistent contraceptive behaviors. In contrast, those with lower educational attainment may face greater misinformation, reduced access to healthcare, and limited economic means to obtain contraception [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe study also identified gender and sexual identification as important correlates of contraceptive use. Consistent with most of the literature, females were found to use contraceptive methods significantly more often than males [\u003cspan additionalcitationids=\"CR21 CR22\" citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. However, in this study, the difference was not very large: 41% of females reported using contraception compared to 37% of males. This likely reflects women\u0026rsquo;s higher engagement with reproductive health services. Homosexual and bisexual participants were less likely to report using contraception compared to heterosexual participants. One reason is that many individuals in these groups may not have sex with opposite-sex partners, reducing their risk of unintended pregnancy. Still, we expected that bisexual and homosexual individuals might use contraception to protect themselves against sexually transmitted diseases. Our findings are consistent with earlier studies showing that sexual minority groups often make less use of gynecologic and family-planning services [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Another possible explanation is that many healthcare settings continue to assume patients are heterosexual, and sexual health counseling is often not fully inclusive of people with diverse sexual orientations.\u003c/p\u003e \u003cp\u003eThere are two differing assessments on the linkage between cohabitation and contraceptive use. Some literature claims married couple living together with more stable relation use contraception more and in a consistent way [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. While others, similar to our study suggest that individuals not living/ non-cohabiting with their partners were more likely to use contraception as a preventive measure against unintended pregnancy and sexually transmitted infections [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. This contrast highlights the importance of considering relationship dynamics when examining contraceptive behavior. However, victims of partner violence were significantly less likely to use contraception, a finding supported by literature linking intimate partner violence (IPV) to reproductive coercion and reduced contraceptive autonomy [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. This underscores the importance of integrating reproductive health screening with IPV prevention programs and ensuring that healthcare settings provide trauma-informed contraceptive counseling [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePregnancy intention was the strongest predictor of contraceptive use, consistent with research showing that individuals with clear reproductive goals are more proactive in using contraception [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. However, the higher odds of contraceptive use among those who were uncertain or not planning a child highlight that reproductive intentions among adulthood are fluid and shaped by life course factors such as financial stability, relationship satisfaction, and prior parenting experience [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eCollectively, these findings suggest that contraceptive behaviors among midlife adults are influenced by broader social and relational contexts. Addressing these determinants requires expanding family planning initiatives beyond younger populations to include counseling and resources for adults who may underestimate their fertility risk. Strengthening health planning and interventions inclusive of older individuals, promoting reproductive health education tailored to adults, and integrating IPV screening into reproductive care could significantly reduce unintended pregnancies in this population.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e"},{"header":"5. Conclusions","content":"\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThis study highlights that contraceptive utilization among adults aged 34\u0026ndash;42 in the United States is influenced by a multidimensional interplay of demographic, socioeconomic, and interpersonal factors. Younger age within the age group of 34\u0026ndash;42, female sex, heterosexual identification, higher education, not living with partner, and clear reproductive intentions were associated with greater contraceptive use, whereas experiences of partner violence reduced use.\u003c/p\u003e \u003cp\u003eThese findings emphasize that interventions to reduce unintended pregnancy among adults should extend beyond access to contraceptive methods and focus on the social and relational environments in which reproductive choices occur. Public health programs should incorporate ongoing reproductive counseling for midlife adults, including discussions about fertility awareness, and method options suitable for older users. Additionally, integrating IPV screening and trauma-informed care into reproductive health services can protect contraceptive autonomy for vulnerable individuals.\u003c/p\u003e \u003cp\u003eFuture research should explore how evolving social norms, gender roles, and healthcare education influence contraceptive decision-making in adulthood. By centering this often-overlooked age group, public health practitioners can design inclusive, evidence-based interventions that support informed reproductive choices and further reduce unintended pregnancies across the lifespan.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor Contributions:\u003c/strong\u003e Conceptualization, K.D., A.G., H.B., and I.G.; methodology, K.D., A.G., H.B., and I.G.; formal analysis, K.D.; writing\u0026mdash;original draft preparation, K.D., A.G., H.B., and I.G.; writing\u0026mdash;review and editing, K.D., M.A., S.D., A.M., E.F.A.A., H.N., and Su.D.; supervision, M.A. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e This research received no external funding.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInstitutional Review Board Statement:\u003c/strong\u003e Ethical review and approval were waived for this study due to publicly available information and data with no identifying information.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement:\u003c/strong\u003e The original data presented in the study are openly available in Add Health at https://addhealth.cpc.unc.edu/data/\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments:\u003c/strong\u003e We acknowledge Dr. Manik Ahuja for the supervision and technical expertise.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of Interest:\u003c/strong\u003e The authors declare no conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study involved secondary analysis of de‑identified data from the National Longitudinal Study of Adolescent to Adult Health (Add Health), originally collected by the University of North Carolina at Chapel Hill. The East Tennessee State University Institutional Review Board reviewed the project and determined that it is exempt from IRB oversight because it uses existing, fully de‑identified data. As no identifiable information was accessed and no direct contact with participants occurred, informed consent was not required.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis manuscript does not contain any individual person\u0026rsquo;s data in an identifiable form (including individual details, images, or videos); therefore, individual consent for publication is not applicable. All authors have reviewed the final version of the manuscript and give their full consent for its publication.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eCenter for Health Statistics N, Vital, Statistics H. Series 2, Number 201 n.d. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.15620/cdc:124395\u003c/span\u003e\u003cspan address=\"10.15620/cdc:124395\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGantt A, Metz TD, Kuller JA, Louis JM, Cahill AG, Turrentine MA. Pregnancy at Age 35 Years or Older: ACOG Obstetric Care Consensus 11. 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Fertility Desires and Contraceptive Transition. Popul Dev Rev. 2024;50:511. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1111/PADR.12669\u003c/span\u003e\u003cspan address=\"10.1111/PADR.12669\" 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":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"discover-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Discover Public Health](https://link.springer.com/journal/12982)","snPcode":"12982","submissionUrl":"https://submission.springernature.com/new-submission/12982/3","title":"Discover Public Health","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"contraceptive use, unintended pregnancy, adult sexual and reproductive health, Add health study","lastPublishedDoi":"10.21203/rs.3.rs-9260603/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9260603/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBackground: Most research has focused on adolescents, leaving a gap in understanding contraceptive behaviors among adults. This study aims to identify patterns and determinants of contraceptive use among adults aged 34–42.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eMethods: A cross-sectional analysis was conducted using Wave V of the Add Health dataset. The analytic sample included 3,552 sexually active individuals. Weighted descriptive, bivariate, and multivariable analyses were performed to explore associations between contraceptive use and demographic, socioeconomic, and relational factors.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eResults: Our study reveals lower odds of contraception use associated with older age (AOR: 0.92; 95% CI: 0.87–0.97), non-heterosexual identity (AOR: 0.64; 95% CI: 0.47–0.87), lower education (AOR: 0.49; 95% CI: 0.33–0.72), and cohabiting with a partner. Notably, experiencing partner violence significantly reduced the odds of contraception use (AOR: 0.64; 95% CI: 0.46–0.90). Conversely, those with no immediate pregnancy intentions had the highest odds of contraceptive use (p\u0026lt;0.001), while race and income were not significant predictors.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eConclusions: Contraceptive use among adults is influenced by a complex interplay of individual, social, and relational factors.\u003c/p\u003e","manuscriptTitle":"Unveiling Factors That Shape Contraceptive Use Among Adults in the US - Findings from the Add Health Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-11 11:53:02","doi":"10.21203/rs.3.rs-9260603/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"154287493608569671075737608383693004112","date":"2026-05-06T19:27:26+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-05-01T13:07:12+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-04-20T20:56:02+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-02T06:23:06+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-04-02T06:22:44+00:00","index":"","fulltext":""},{"type":"submitted","content":"Discover Public Health","date":"2026-03-29T18:37:57+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"discover-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"","sideBox":"Learn more about [Discover Public Health](https://link.springer.com/journal/12982)","snPcode":"12982","submissionUrl":"https://submission.springernature.com/new-submission/12982/3","title":"Discover Public Health","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Discover Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"d299dc49-46f2-43e4-8869-181ff08e03e6","owner":[],"postedDate":"May 11th, 2026","published":true,"recentEditorialEvents":[{"type":"reviewerAgreed","content":"154287493608569671075737608383693004112","date":"2026-05-06T19:27:26+00:00","index":23,"fulltext":""},{"type":"reviewersInvited","content":"5","date":"2026-05-01T13:07:12+00:00","index":"","fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-11T11:53:02+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-11 11:53:02","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9260603","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9260603","identity":"rs-9260603","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}