Effectiveness of focused preconception education and counseling (FPEC) on conception preparedness among premarital couples: A quasi-experimental pre-post study

Effectiveness of focused preconception education and counseling (FPEC) on conception preparedness among premarital couples: A quasi-experimental pre-post 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 Effectiveness of focused preconception education and counseling (FPEC) on conception preparedness among premarital couples: A quasi-experimental pre-post study Richard Nsengiyumva, Oliva Bazirete, Thiery Claudien Uhawenimana, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8694857/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Maternal and neonatal morbidity and mortality remain major public health challenges in sub-Saharan Africa, where modifiable preconception risk factors contribute to approximately 75% of adverse pregnancy outcomes. Preconception education and counseling provide a proactive strategy to optimize health before conception and improve safe pregnancy; however, it is less practiced and underexplored in low-resource settings like Rwanda. This study aimed to pilot and evaluate the effectiveness of focused preconception education and counseling (FPEC) on conception preparedness attitudes and practices among premarital couples in Rwanda. Methods A quasi-experimental pre-post study was conducted from May to August 2024 involving 600 premarital couples who were systematically assigned to either the intervention group or control group with 300 couples (150 males and 150 females) in each group. Only the intervention group received a single 45-minute group and couple-based FPEC session post-baseline, addressing fertility, screenings, nutrition, supplements, substance use, stress, gender-based violence, and environmental risks, supplemented by refresher handouts. The control group received routine premarital education without preconception content. Conception preparedness was measured using a 32-item questionnaire completed by each individual to assess their personal level of preparedness, with data collected at baseline and three months later. Analysis included descriptive statistics, paired t-tests, difference-in-differences (DiD), and linear regression in SPSS version 29 (p < 0.05). Results Participants were mostly young (64.7% aged 21–30 years), rural (81.5%), with primary education and low income. Baseline scores showed no group differences. Post-intervention, the intervention group demonstrated marked improvements in screenings (e.g., blood type/Rh + 64.3%, anemia + 59.7%), prophylactics (folic acid + 30.7%, tetanus + 42.0%), planning (conception timing + 56.3%), and risk reduction (alcohol − 18.6%). Mean scores rose from 35.3 to 58.3 (+ 23.0 points, p < 0.01) versus 38.2 to 41.7 in controls (+ 3.5, non-significant). DiD test confirm a + 19.5-point net effect (p < 0.001); regression showed nearly 20-fold higher scores in the intervention group (B = 19.8, 95% CI: 18.4–21.1, p < 0.01). Conclusion FPEC significantly enhanced conception preparedness among premarital couples compared to those who did not, supporting its integration into reproductive health, maternal health and premarital programs to promote healthy conception, safe pregnancy and family wellness. Future research should explore long-term outcomes and scalability. Maternal & Fetal Medicine Sexual & Reproductive Medicine Obstetrics & Gynecology Preconception education counseling conception preparedness premarital couples Figures Figure 1 BACKGROUND Maternal and neonatal mortality remain critical global public health challenges, with 287,000 maternal deaths and 2.4 million neonatal deaths occurring annually worldwide, disproportionately concentrated in sub-Saharan Africa where maternal mortality ratios average 542 deaths per 100,000 live births compared to 11 per 100,000 in high-income countries( 1 ),( 2 ). Approximately 80% of pregnancy-related deaths and complications are preventable through timely interventions and about 75% of maternal deaths and morbidities are associated with modifiable risk factors present before conception, including preexisting medical conditions, psychosocial stressors, environmental exposures, and lifestyle behaviors from either male, female, or both partners( 3 ). Evidence show that more than 60% of women and a considerable number of men of childbearing age in Sub-Saharan Africa have at least one changeable risk factor before pregnancy that significantly affects pregnancy outcomes( 4 ). Among women of reproductive age, 32% globally live with anemia (40–50% in sub-Saharan Africa), which raises the risk of maternal death by 3.5 times while leading to bleeding complications, postpartum hemorrhage, miscarriage, low birth weight, restricted fetal growth, and early delivery( 5 ). Pre-existing health problems affect substantial proportions: 2–5% live with diabetes( 6 ), 3–5% live with chronic hypertension( 7 ), and 13% globally live with obesity conditions that increase the likelihood of birth defects, miscarriage, fetal death, preeclampsia, gestational diabetes, cesarean delivery, and maternal death. Furthermore, approximately one-third of childbearing age population live in hazardous environment associated with risks of abortion, pre-eclampsia, gestational diabetes, preterm deliveries, stillbirths and congenital abnormalities( 8 ),( 9 ). In low- and middle-income countries, 10–20% of reproductive age women live with insufficient nutrition( 10 ) with risks of miscarriage, preterm birth, restricted fetal growth, stillbirth, breastfeeding associated disorders and intergenerational effects( 11 ), ( 12 ). Additionally, 15–25% of women and 10–15% of men in reproductive age live with mental health disorders( 13 ), which are linked to decreased fertility, miscarriage, preterm birth, and poor child neurodevelopmental outcomes( 14 ). Furthermore, millions of couples’ experience exposure to harmful substances from farming, workplace, and home environments, causing reduced fertility, miscarriage, birth defects, and neurodevelopmental disorders in children ( 15 ). In Rwanda, several pre-pregnancy modifiable factors are prevalent in both women and men like it is in other LMICs. For example, reports show 2.1–5.74% of women of reproductive age live with untreated syphilis infection, which may result in poor pregnancy outcomes in 50–80% of cases( 16 ), whereas 5.8% are underweight( 17 ), 17.2% live with anemia and with insufficient folic acid intake, raising neural tube defect risk by 70%( 18 ), ( 19 ). Among men of reproductive age, 5–8% live with type 2 diabetes( 20 ) and 9.2% live with obesity while 16% has undernutrition ( 19 ), leading to decreased sperm quality with increased risk of DNA damage, and elevated risks of miscarriage, birth defects, metabolic disorders in neonates and children and chronic conditions in offspring ( 21 ),( 22 ). Alcohol and substance use are prevalent in both reproductive age sex: 4.4% use cannabis, opiates and cocaine and cigarette use is in 2.9%( 23 ), which may reduce fertility, causes unintended pregnancy and causes miscarriage, placental problems, pre-eclampsia, preterm birth, low birth weight, stillbirth, sudden infant death syndrome, and childhood cancers( 24 ),( 25 ).Also 10–20% of women and 31.6% of men live with alcohol consumption patterns( 23 ) that may result in fetal alcohol spectrum disorders, miscarriage, and birth defects in prospect pregnancy( 26 )( 27 ). Additionally, mental disorders are prevalent among 23.2% of women than 16.6% men of reproductive age( 28 ) exposing them to risks unintended pregnancy, miscarriage, pre-eclampsia, stillbirth, preterm labor, perinatal depression, puerperal psychosis( 29 ),( 30 ),( 31 ).Furthermore, thousands of men and women of reproductive age are exposed to hazardous environment. For example, biomass fuel use is prevalent in 85% of households causing indoor air pollution. Agricultural pesticide exposure and smoke exposure is in 10–15%, ( 32 ),( 33 )which further may cause risks and complications on prospect pregnancy. Despite substantial investments in prenatal, delivery, and postnatal care, maternal and neonatal mortality and morbidity burden remain high, and progress toward achieving Sustainable Development Goal targets for reducing maternal mortality to less than 70 per 100,000 live births and neonatal mortality to 12 per 1,000 live births by 2030 has been slower than anticipated( 34 ). This persistent challenge has prompted renewed attention to preconception care, including education and counseling, which addresses pre-pregnancy health risks, health conditions, lifestyles, and risky practices that can affect prospective pregnancy. Unlike antenatal care education, which begins after pregnancy is confirmed in over 99% of cases and often too late, after the critical first eight weeks of embryonic development ( 35 )( 36 ), preconception counseling offers a 3 to 6-month period to optimize health before pregnancy, time needed to improve egg and sperm quality, address nutritional deficiencies, control chronic health conditions, limit toxin exposure, reduce stress, and build healthy habits, thereby minimizing unsafe pregnancies, enhancing pregnancy outcomes, and fostering family wellness( 37 ). Evidence demonstrates that preconception education and counseling serves as the foundational intervention that enables women and couples to understand, access, and implement preconception health measures, thereby significantly reducing maternal and neonatal morbidity and mortality( 38 ). The WHO estimates that comprehensive maternal care from preconception could prevent 54% of maternal and 71% of neonatal deaths globally( 39 ). Evidence show that in developing countries ,community-based preconception education can increase antenatal care uptake by 39%, reduce neonatal mortality by 17%, and increased breastfeeding by 71%( 40 ).Other various studies showed the impact of preconception education and counseling on conception preparedness behaviors and its impact on pregnancy outcomes. For example, a study found that women who receive structured preconception education are 2–3 times more likely to take folic acid supplements before pregnancy, reducing neural tube defects by 50–70%( 41 ). A preconception education programs increased the proportion of women with diabetes achieving optimal glycemic control before conception, reducing congenital malformation risk from 10% to 1–2%( 42 ). A study demonstrated women with chronic conditions receiving preconception counseling had fewer pregnancy complications, including reduced rates of preterm birth, low birth weight, and congenital abnormalities( 43 ).Then, a study conducted in India, Pakistan, Guatemala, and the Democratic Republic of Congo found preconception education about nutrition reduced pregnancy associated anemia and the risk of small for gestational age births, and 10–15% reductions in preterm birth ( 44 ). Despite proven benefits, significant gaps persist worldwide in preconception education and implementation. Between 60–94% of women globally do not receive structured preconception education( 45 ), with rates varying by setting. The vast majority of women in Sub-Saharan Africa 76% on average do not receive preconception care, with rates exceeding 90% in Sudan and Nigeria, and 74% in Ethiopia( 46 ); ( 47 ). Rwanda, lacking specific data but with limited preconception services, likely faces similar or higher gaps. While Rwanda has achieved impressive antenatal care coverage with over 95% of women attending at least one visit( 48 ), preconception care and education are largely absent from the healthcare continuum. Maternal and neonatal mortality remain high at 149 per 100,000 live births and 27 per 1,000 live births respectively, with many deaths linked to modifiable preconception factors( 49 ). Rwanda's healthcare system, similar to many low-income countries, allocates greater resources to antenatal and postnatal care than to preconception education. Community awareness of preconception health remains limited, with gaps in understanding modifiable risk factors and pregnancy preparation strategies. This lack of awareness may result in missed opportunities to prevent adverse outcomes such as neural tube defects, low birth weight, preterm birth, maternal anemia, and pregnancy complications associated with uncontrolled chronic conditions. Given the proven effectiveness of preconception education in improving conception preparedness and reducing maternal and neonatal morbidity and mortality, the persistently high maternal and neonatal mortality in Rwanda despite strong antenatal care coverage, the high prevalence of modifiable risk factors among reproductive-age men and women, and the absence of research and data on impact of structured preconception education on pregnancy preparedness in Rwanda, there is an urgent need for context-specific evidence. This study therefore aimed to pilot and evaluate the effectiveness of focused preconception education and counseling on conception preparedness among premarital couples in Rwanda. Rwanda's high marriage registration rates with 66% of couples living in formal/legal unions( 50 ), cultural emphasis on family preparation, and tradition of couples seeking premarital guidance provide an ideal platform for couple-based preconception education programs. However, current premarital education and counseling rarely include reproductive and maternal health discussions. Therefore, our study focused on premarital couples because they are easily reached through existing preparation programs and are at a critical life stage when pregnancy planning typically begins. They are also highly motivated to improve their health for future family formation and uniquely positioned to jointly adopt healthier practices as a couple. Importantly, this group offers the essential 3 to 6-month preconception window to correct nutritional deficiencies, stabilize chronic conditions, enhance gamete quality, and reduce harmful exposures. Both males and females were involved because preconception health risks and outcomes are influenced by both partners, and addressing them together ensures comprehensive preparation, improved fertility, and healthier pregnancies. Furthermore, both men and women were included since preconception health depends on both partners, and addressing them together leads to better preparation, fertility, and pregnancy outcomes. Men and women were both included because preconception health relies on both partners, and working together helps improve preparation, fertility, and pregnancy outcomes. While many studies have mostly focused on women and rarely involved men, this study aimed to highlight the important role of both partners in preconception care and address the existing research gap. Methods Study Design This study used a quasi-experimental pre-post design with non-equivalent groups to assess the effectiveness of focused preconception education and counseling (FPEC) on conception preparedness among premarital couples in Rwanda. All participants underwent baseline assessment, followed by FPEC delivery only to the intervention group and post-assessment of both groups three months later. Due to ethical and logistical constraints in premarital settings, systematic site-based allocation was used instead of randomization to balance groups and reduce contamination. Study Setting In Rwanda, premarital couples attend mandatory education sessions ("Ecoles des fiancés") held monthly for 3 to 6 months at sector offices and churches before receiving a marriage license. Participants were recruited from these venues nationwide. To ensure geographic diversity across urban and rural areas, 15 sites were randomly selected from all provinces: Mushonyi, Gisenyi, and Kanama (Western); Huye, Nyarusange, and Kamonyi (Southern); Muhoza, Ruli, and Shyorongi (Northern); Rwamagana, Kayonza, and Muhura (Eastern); and Kinyinya, Nyamirambo, and Masaka (Kigali City). Study Population and Eligibility Criteria This study enrolled premarital couples who were formally registered for civil or religious marriage and planning to have children after marriage. Eligible couples must have registered for marriage within six months before data collection. Female partners were required to be between 21 and 45 years of age (reproductive age), while male partners had to be at least 21 years old, in accordance with Rwanda's legal marriage age established by Presidential Decree No. 102/05 of March 13, 1992( 51 ). Both partners must have reported no current pregnancy at enrollment. Couples were excluded from the study if they did not plan to have children after marriage, if either partner was pregnant at the time of enrollment, or if either partner refused to participate or provide informed consent. These eligibility criteria ensured the study focused on premarital couples in the preconception period who would benefit from preparedness interventions. Sampling Technique and Sample Size A total of 720 couples were screened from prospective marriage registers at churches and sector offices to achieve the target sample size of 670 couples. This target was calculated using Cochran's formula for proportion estimation, assuming a preconception preparedness prevalence of 50% (to yield the maximum sample size), a 95% confidence level, and a 5% margin of error. Of those screened, 623 couples met the inclusion criteria and provided consent. These were systematically allocated by site to either the intervention group (n = 312 couples) or the control group (n = 311 couples). Ultimately, 600 couples completed both baseline and follow-up assessments and were included in the analysis (intervention: n = 300; control: n = 300), after excluding 23 couples lost to follow-up (2 from the intervention group and 21 from the control group). Data Collection Tool The questionnaire used in this study was specifically developed for this research by adapting items from established preconception checklists; the Becoming a Parent resource series by the Wisconsin Association for Perinatal Care ( 52 ) and the FIGO Preconception Checklist( 53 ), with contextual modifications for Rwanda. The full English version of the final 32-item questionnaire is provided in Supplementary File 1. Moreover, in developing that tool, additional evidence drawn from broader literature on preconception care, education, and counseling, as well as consultations with reproductive health experts. Furthermore, the instrument was customized to the Rwandan context by excluding items related to: screenings or vaccines that were unavailable locally (such as advanced genetic screenings or non-routine vaccines not part of the national immunization program); tests that were difficult to afford or inaccessible; specialized dietary recommendations for foods not readily available in local markets; and lifestyle modifications requiring resources beyond the reach of typical participants. The was developed in English and translated into Kinyarwanda by an expert translator using a forward-backward translation process with third-party verification, for linguistic and conceptual equivalence. The final instrument was then assessed by a multidisciplinary panel of experts to verify its completeness. Furthermore, a pilot testing with 30 participants was done to ensure the tool's clarity, cultural appropriateness, acceptability, and practical feasibility. The questionnaire comprised two sections: ( 1 ) socio-demographic characteristics (age, sex, residence, education, occupation, income, religion); ( 2 ) yes/no items assessing attitudes and practices related to clinical screenings (e.g., “Have you been tested for blood sugar levels?”; “Have you screened for anemia?”), prophylactic measures (e.g., “Are you taking folic acid supplements?”; “Have you received a tetanus vaccination?”), reproductive planning (e.g., “Have you planned the optimal time to conceive?”; “Have you checked for consanguinity with your partner?”), lifestyle behaviors (e.g., “Do you engage in regular physical exercise?”; “Do you consume alcohol?”), environmental exposures (e.g., “Do you take measures to avoid toxic environmental exposures?”), and protective actions (e.g., “Do you use measures to prevent unintended pregnancy?”; “Do you have measures in place to manage stress?”; “Do you protect yourself against gender-based violence?”). Data quality control, Validity, and Reliability Data quality was maintained through rigorous supervision and monitoring throughout the study. Ten trained midwives, overseen by two public health specialists, conducted daily reviews of all entries for completeness, consistency, and accuracy, with incomplete or inconsistent records immediately flagged and excluded. Real-time data entry via Kobo Toolbox with automated scoring minimized transcription errors and enabled instant quality verification. Data were securely stored with regular backups, and comprehensive cleaning in SPSS version 29 addressed outliers, duplicates, and errors before analysis. Validity and reliability of the instrument were established through multiple strategies. Content validity was confirmed by a multidisciplinary expert panel, while construct validity was ensured by adapting the tool from two internationally recognized instruments the Becoming a Parent Preconception Checklist and the FIGO Preconception Health Assessment Tool. Forward-backward translation into Kinyarwanda with expert verification established cultural and linguistic validity, and pilot testing with 30 (10percent) participants confirmed face validity. Reliability was maintained through standardized training of all ten data collectors in uniform interview techniques and questionnaire administration, ensuring consistency across sites. Using the same 32-item questionnaire at both time points enhanced test-retest reliability, while gender-matched private interviews promoted honest responses. The automated Kobo Toolbox scoring system eliminated scorer variability and ensured consistent calculation of preparedness scores, strengthening internal consistency. Data Collection Procedure Ten trained and Bachelor’s midwives, supervised by two public health specialists, administered face-to-face interviews using Kobo Toolbox on tablets. Interviews were conducted in private, gender-matched settings to ensure confidentiality and encourage candid responses. Signed informed consent was obtained from all participants, and unique coded identifiers were assigned. The same structured 32-item questionnaire was used for both baseline and post-assessments. Baseline assessments were performed at premarital registration sites. Post-assessments were conducted in the last two weeks before marriage, during final premarital sessions at the registration sites or by telephone for absent participants. Upon completion of the questionnaire, each individual's responses were scored immediately using the automated features of Kobo Toolbox, providing real-time calculation of preparedness levels. Intervention: Focused Preconception Education and Counseling (FPEC) Immediately after baseline assessment, couples in the intervention group received a single 45-minute interactive group and couple-based education session delivered by trained midwives in private settings at the premarital sites. The session was structured in three phases to ensure comprehensive coverage of preconception health topics. The first phase involved introduction and rapport building (5–7 minutes), during which trained midwives welcomed couples, explained the purpose of preconception health The second phase consisted of core education and discussion (30–33 minutes) covering essential preconception topics. These included fertility factors (e.g., calculating fertile days and age-related fertility changes); nutrition and supplementation (e.g., daily folic acid intake and iron-rich foods); vaccinations and screenings (e.g., tetanus immunization and testing for anemia and blood sugar,); substance use risks (e.g., alcohol and tobacco effects on fetal development); stress management and mental health strategies (e.g., relaxation techniques and good sleep patterns); gender-based violence prevention (e.g., recognizing warning signs); and safe environments and reproductive health access (e.g., reducing exposure to pesticides and indoor smoke and locating nearby clinics). The final phase involved summary and reinforcement (5–7 minutes), during which key messages were recapped, couples' questions were addressed, and printed handouts summarizing the content were provided for home review. No incentives were offered to participants. Couples in the control group received only the usual premarital counseling delivered by religious officers or local administration officers. This standard counseling focused on faith, conflict resolution, financial management, and general parenthood but included no education on preconception preparation. Data Management Data quality was rigorously maintained through daily supervision. Supervisors reviewed all entries on the day of collection for completeness, consistency, and logical accuracy. Incomplete or inconsistent records were flagged and excluded to preserve analytical integrity. Real-time data from Kobo Toolbox were securely stored on the server with periodic backups. At the conclusion of fieldwork, data were exported to Microsoft Excel for preliminary review and subsequently imported into SPSS version 29 for comprehensive cleaning. This process included identification and correction of outliers, duplicate entries, and typographical errors. Outcome Measurement Conception preparedness was operationalized as a composite score derived from the 32 yes/no questionnaire items. Each item was scored dichotomously (yes = 1 point for preparedness or positive practice; no = 0 points), yielding an individual raw score ranging from 0 to 32 (maximum 32 points per participant). To reflect the couple-based nature of preconception health, individual scores were summed to create a couple-level raw score (maximum 64 points). For ease of interpretation and comparison, these couple-level raw scores were normalized to a percentage scale (0–100%), where higher percentages indicated greater preparedness. This approach allowed assessment of both individual contributions and joint couple readiness while facilitating statistical analysis of pre-post changes and group differences. Data Analysis Participant characteristics and preparedness scores were summarized using descriptive statistics, including frequencies and percentages for categorical variables and means with standard deviations for continuous variables. Normality of continuous variables was assessed with the Shapiro-Wilk and Kolmogorov-Smirnov tests. The primary outcome, change in conception preparedness scores was analyzed using difference-in-differences (DiD) t-tests and paired t-tests to examine pre-to-post improvements within each group. Multivariable linear regression was used to quantify the association between group assignment and post-test preparedness scores. Results included 95% confidence intervals, and statistical significance was set at p < 0.05. All analyses were performed in SPSS version 29. Ethical Considerations The study was approved by the Institutional Review Board of the University of Rwanda College of Medicine and Health Sciences (Approval No. 337/CMHS-IRB/2024). Permissions were obtained from local authorities and church leaders. Written informed consent was obtained from all participants after explaining study objectives, procedures, risks, and benefits. Participation was voluntary, with the right to withdraw at any time without consequence. Confidentiality was maintained through coded identifiers, secure data storage, and private interviews. Results This study evaluated the effectiveness of focused preconception education and counseling (FPEC) on conception preparedness among soon-to-be-married couples using a pre-post-test design. Following data entry and cleaning, 600 couples (300 intervention group, 300 control group) were included in the analysis. Data from 32 couples who dropped out during follow-up were excluded. Socio-demographic characteristics of respondents Table 1 Distribution of Socio-demographic characteristics among participants Socio-demographic characteristic of participants Items Frequency(n) Percentage (%) Sex Female 600 50.0 Male 600 50.0 Age (in years and category) 21–30 years old 776 64.7 31–40 years old 346 28.8 41 > years old 78 6.5 µ = 29.5. SD = ± 5.5 Maximum = 45 Minimum age = 21 Education level Non-literate 53 4.4 Primary 550 45.8 Secondary 416 34.7 TVET 78 6.5 University 103 8.6 Occupation Cultivator/Farmer 499 41.6 Private sector servant 174 14.5 Public sector 71 5.9 Self-employed 213 17.8 Not employed/student 199 16.6 Religion Adventist 71 5.9 Catholic 670 55.8 Muslim 61 5.1 Other 119 9.9 Protestant 227 18.9 Churchless 52 4.3 Habitation Rural 978 81.5 Urban 222 18.5 Monthly income status From 200 000Rwf ( $ 137 USD) and < 726 60.5 Above 200 000Rwf ( $ 137 USD) 474 39.5 Notes : Individuals aged 21 to 35 are categorized as "Young age," while those over 35 are considered "Advanced age." Education below the secondary school level is labeled as "low educated," whereas education ranging from secondary school to university level is referred to as "high educated." VET stands for Technical and Vocational Education and Training. ​Table 1 illustrates the distribution of socio-demographic characteristics among the participants in this study.​ The gender breakdown demonstrates an equal representation, with males and females each constituting 50% of the sample. The majority of participants (64.7%) fall within the age range of 21 to 30 years, resulting in an overall mean age of 29.5 years, with a standard deviation of ± 5.5. A significant portion of the participants (45.8%) has attained only a primary education level, while 41.6% are engaged in agricultural work. Catholicism is the most prevalent religion, representing over half (55.8%) of the sample, and a considerable majority of participants (81.5%) reside in rural areas. Finally, the findings indicate that more than 60.5% of the participants earn a monthly income of 200,000 Rwandan Francs (approximately $ 137 USD or less. Distribution of Conception Preparedness Attitudes and Practices by Sex at Pretest and Post-test among Control and Intervention Groups Table 2 Sex-Disaggregated Changes in Conception Preparedness Practices from Pretest to Post-test in Intervention and Control Groups CP items Pretest Male/Female for IG (n, %) Post-test Male/Female for IG (n, %) Pretest Male/Female for CG (n, %) Post-test Male/Female for CG (n, %) Post-test change Male/Female for IG Post-test change Male/Female for CG Tested for blood sugar 8 (2.7) / 14 (4.7) 36 (12.0) / 130 (43.3) 7 (2.3) / 11 (3.7) 9 (3.0) / 21 (7.0) + 9.3 / +38.7 0.7 / 3.3 Tested for high blood pressure 12 (4.0) / 19 (6.3) 48 (16.0) / 165 (55.0) 13 (4.3) / 21 (7.0) 13 (4.3) / 22 (7.3) + 12.0 / +48.7 0.0 / 0.3 Asked /checked for family genetic predisposition 1 (0.3) / 3 (1.0) 22 (7.3) / 87 (29.0) 2 (0.7) / 4 (1.3) 2 (0.7) / 4 (1.3) + 7.0 / +28.0 0.0 / 0.0 Screened for anemia 6 (2.0) / 9 (3.0) 41 (13.7) / 153 (51.0) 4 (1.3) / 8 (2.7) 4 (1.3) / 9 (3.0) + 11.7 / +48.0 0.0 / 0.3 Checked/control BMI and Weight 8 (2.7) / 13 (4.3) 35 (11.7) / 122 (40.7) 9 (3.0) / 14 (4.7) 9 (3.0) / 16 (5.3) + 9.0 / +36.3 0.0 / 0.7 Screened for syphilis, other STIs/ UTIs 4 (1.3) / 6 (2.0) 21 (7.0) / 75 (25.0) 4 (1.3) / 8 (2.7) 4 (1.3) / 8 (2.7) + 5.7 / +23.0 0.0 / 0.0 Pay attention/Avoid teratogenic medication 63 (21.0) / 95 (31.7) 83 (27.7) / 177 (59.0) 64 (21.3) / 96 (32.0) 75 (25.0) / 144 (48.0) + 6.7 / +27.3 3.7 / 16.0 Screened for HIV/AIDS 5 (1.7) / 9 (3.0) 24 (8.0) / 86 (28.7) 6 (2.0) / 10 (3.3) 6 (2.0) / 12 (4.0) + 6.3 / +25.7 0.0 / 0.7 Screened for / vaccinated for Hepatitis 1 (0.3) / 3 (1.0) 9 (3.0) / 39 (13.0) 2 (0.7) / 3 (1.0) 1 (0.3) / 4 (1.3) + 2.7 / +12.0 -0.3 / 0.3 Went for Tetanus vaccine shot NA / 17 (5.7) NA / 118 (39.3) NA / 18 (6.0) NA / 20 (6.7) NA / +33.7 NA / 0.7 Tested for Blood type and Rh 2 (0.7) / 3 (1.0) 40 (13.3) / 158 (52.7) 3 (1.0) / 6 (2.0) 3 (1.0) / 10 (3.3) + 12.7 / +51.7 0.0 / 1.3 Took folic acid /vitamins supplements 20 (6.7) / 32 (10.7) 38 (12.7) / 106 (35.3) 24 (8.0) / 36 (12.0) 25 (8.3) / 43 (14.3) + 6.0 / +24.7 0.3 / 2.3 Assessed & planed the convenient time to conceive 9 (3.0) / 15 (5.0) 42 (14.0) / 151 (50.3) 8 (2.7) / 12 (4.0) 8 (2.7) / 14 (4.7) + 11.0 / +45.3 0.0 / 0.7 Started/calculate fertile days 3 (1.0) / 5 (1.7) 12 (4.0) / 45 (15.0) 4 (1.3) / 6 (2.0) 3 (1.0) / 7 (2.3) + 3.0 / +13.3 -0.3 / 0.3 Made a plan of number of children 49 (16.3) / 75 (25.0) 73 (24.3) / 173 (57.7) 52 (17.3) / 79 (26.3) 52 (17.3) / 83 (27.7) + 8.0 / +32.7 0.0 / 1.3 Take/strive for balanced diet 40 (13.3) / 61 (20.3) 44 (14.7) / 79 (26.3) 42 (14.0) / 64 (21.3) 36 (12.0) / 68 (22.7) + 1.3 / +6.0 -2.0 / 1.3 Set measures to protect against unintended pregnancy 20 (6.7) / 31 (10.3) 38 (12.7) / 106 (35.3) 19 (6.3) / 29 (9.7) 13 (4.3) / 26 (8.7) + 6.0 / +25.0 -2.0 / -1.0 Protect and set measures to protect self against STIs other than HIV 44 (14.7) / 66 (22.0) 2 (0.7) / 4 (1.3) 40 (13.3) / 60 (20.0) 35 (11.7) / 65 (21.7) +-14.0 / +-20.7 -1.7 / 1.7 Protect and set measures to protect self against HIV 74 (24.7) / 113 (37.7) 87 (29.0) / 165 (55.0) 69 (23.0) / 105 (35.0) 70 (23.3) / 110 (36.7) + 4.3 / +17.3 0.3 / 1.7 Smoke tobacco 6 (2.0) / 9 (3.0) 2 (0.7) / 6 (2.0) 6 (2.0) / 11 (3.7) 6 (2.0) / 13 (4.3) +-1.3 / +-1.0 0.0 / 0.7 Take alcohol 36 (12.0) / 55 (18.3) 12 (4.0) / 23 (7.7) 38 (12.7) / 58 (19.3) 38 (12.7) / 60 (20.0) +-8.0 / +-10.7 0.0 / 0.7 Take much caffeine 2 (0.7) / 4 (1.3) 2 (0.7) / 5 (1.7) 4 (1.3) / 6 (2.0) 5 (1.7) / 12 (4.0) + 0.0 / +0.3 0.3 / 2.0 Use illicit drugs 2 (0.7) / 5 (1.7) 2 (0.7) / 7 (2.3) 2 (0.7) / 5 (1.7) 2 (0.7) / 7 (2.3) + 0.0 / +0.7 0.0 / 0.7 Use non-prescribed medicines 37 (12.3) / 56 (18.7) 13 (4.3) / 26 (8.7) 40 (13.3) / 60 (20.0) 43 (14.3) / 76 (25.3) +-8.0 / +-10.0 1.0 / 5.3 Use herbal drugs 32 (10.7) / 48 (16.0) 8 (2.7) / 16 (5.3) 30 (10.0) / 45 (15.0) 30 (10.0) / 48 (16.0) +-8.0 / +-10.7 0.0 / 1.0 Practice physical exercise 62 (20.7) / 95 (31.7) 54 (18.0) / 102 (34.0) 46 (15.3) / 70 (23.3) 37 (12.3) / 69 (23.0) +-2.7 / +2.3 -3.0 / -0.3 Established measures to avoid and manage stress 39 (13.0) / 59 (19.7) 52 (17.3) / 111 (37.0) 32 (10.7) / 48 (16.0) 25 (8.3) / 49 (16.3) + 4.3 / +17.3 -2.3 / 0.3 Adopt good sleep patterns and avoid sleep disturbances 55 (18.3) / 84 (28.0) 62 (20.7) / 112 (37.3) 48 (16.0) / 73 (24.3) 39 (13.0) / 74 (24.7) + 2.3 / +9.3 -3.0 / 0.3 Protect-self against toxic environment exposure 16 (5.3) / 25 (8.3) 30 (10.0) / 82 (27.3) 15 (5.0) / 24 (8.0) 12 (4.0) / 24 (8.0) + 4.7 / +19.0 -1.0 / 0.0 Went to seek fertility checkup/advice at health facility 4 (1.3) / 6 (2.0) 18 (6.0) / 63 (21.0) 2 (0.7) / 5 (1.7) 2 (0.7) / 9 (3.0) + 4.7 / +19.0 0.0 / 1.3 Checked consanguinity relationship with the partner 6 (2.0) / 10 (3.3) 38 (12.7) / 140 (46.7) 3 (1.0) / 6 (2.0) 4 (1.3) / 11 (3.7) + 10.7 / +43.3 0.3 / 1.7 Protect-self/partner against GBV 98 (32.7) / 148 (49.3) 103 (34.3) / 169 (56.3) 103 (34.3) / 155 (51.7) 107 (35.7) / 173 (57.7) + 1.7 / +7.0 1.3 / 6.0 As described in Table 2 , at baseline, males and females from both intervention and control groups exhibited low engagement in preconception preparedness practices, with most screening and preventive behaviors practiced by fewer than 10% of participants. Following intervention, dramatic improvements were observed in clinical screening behaviors among intervention participants: blood pressure testing increased by 48.7 percentage points for females and 12.0 points for males; anemia screening rose by 48.0 and 11.7 points respectively; and blood type/Rh testing increased by 51.7 and 12.7 points. Infectious disease screening showed similar patterns, with HIV testing increasing by 25.7 points for intervention females and 6.3 points for males, while syphilis/STI screening rose by 23.0 and 5.7 points respectively. Reproductive planning behaviors improved substantially, with conception timing assessment increasing by 45.3 points for intervention females and 11.0 points for males. In stark contrast, control group participants of both sexes showed a very low changes across these same measures (typically 0–3 percentage points). Pronounced and consistent gender differences emerged throughout the findings, with intervention females demonstrating approximately four-fold greater behavior change than intervention males across virtually all domains despite similar baseline levels. This pattern persisted across diverse screening tests. Reproductive planning reveals the largest absolute gender disparities: half of intervention females engaged in conception timing planning compared to only one-seventh of males, and 21% of intervention females sought fertility consultation compared to 6% of males. However, risk behavior reduction showed notable gender convergence, with alcohol consumption decreasing by 10.7 points for intervention females and 8.0 points for males, and herbal drug use declining by 10.7 and 8.0 points respectively representing similar gender effects (1.3-fold differences) rather than the four-fold disparities seen in screening behaviors. The intervention successfully promoted comprehensive preconception health preparation spanning clinical, behavioral, nutritional, and psychosocial domains. Folic acid supplementation increased by 24.7 percentage points among intervention females compared to 2.3 points in controls. Genetic counseling and consanguinity checking, virtually non-existent at baseline (0.3-1.0%), increased to 7.3–29.0% and 12.7–46.7% respectively in intervention participants while remaining unchanged in controls. Stress management improved by 17.3 points for intervention females versus 0.3 points for controls, and protection against toxic environmental exposures increased by 19.0 points versus no change. Furthermore, results show that there is a persistent gender disparity with intervention females consistently achieving 40–55% screening rates while males reached only 12–16%. Table 3 Distribution of CP Attitudes and Practices Between Intervention and Control Groups at Pre- and Post-Intervention (Yes Responses, n [%], Males+Females) Preparedness Item Intervention Group Control Group Overall Post intervention change (Increase/Decrease) Pretest / Post test, n, % Pretest / Post test, n, % Intervention group/ Control group, % Tested for blood sugar 22 (7.3) / 166 (55.3) 18 (6.0) / 30 (10.0) + 48.0 / +4.0 Tested for high blood pressure 31 (10.3) / 213 (71.0) 34 (11.3) / 35 (11.7) + 60.7 / +0.4 Asked /checked for family genetic predisposition 4 (1.3) / 109 (36.3) 6 (2.0) / 6 (2.0) + 35.0 / 0.0 Screened for anemia 15 (5.0) / 194 (64.7) 12 (4.0) / 13 (4.3) + 59.7 / +0.3 Checked/control BMI 21 (7.0) / 157 (52.3) 23 (7.7) / 25 (8.3) + 45.3 / +0.6 Screened for syphilis, other STIs/ UTIs 10 (3.3) / 96 (32.0) 12 (4.0) / 12 (4.0) + 28.7 / 0.0 Pay attention/Avoid teratogenic medication 158 (52.7) / 260 (86.7) 160 (53.3) / 219 (73.0) + 34.0 / +19.7 Screened for HIV/AIDS 14 (4.7) / 110 (36.7) 16 (5.3) / 18 (6.0) + 32.0/ +0.7 Screened for / vaccinated for Hepatitis 4 (1.3) / 48 (16.0) 5 (1.7) / 5 (1.7) + 14.7/ 0.0 Went for Tetanus vaccine shot 27 (9.0) / 153 (51.0) 30 (10.0) / 32 (10.7) + 42.0 / +0.7 Tested for Blood type and Rh factor 5 (1.7) / 198 (66.0) 9 (3.0) / 13 (4.3) + 64.3 / +1.3 Took folic acid and other vitamins supplements 52 (17.3) / 144 (48.0) 60 (20.0) / 68 (22.7) + 30.7 / +2.7 Assessed & planed the convenient time to conceive 24 (8.0) / 193 (64.3) 20 (6.7) / 22 (7.3) + 56.3 / +0.6 Started/calculate fertile days 8 (2.7) / 57 (19.0) 10 (3.3) / 10 (3.3) + 16.3/ 0.0 Made a plan of number of children 124 (41.3) / 246 (82.0) 131 (43.7) / 135 (45.0) + 40.7/ +1.3 Take/strive for balanced diet 101 (33.7) / 123 (41.0) 106 (35.3) / 104 (34.7) + 7.3/ −0.6 Set measures to protect against unintended pregnancy 51 (17.0) / 144 (48.0) 48 (16.0) / 39 (13.0) + 31.0 / −3.0 Protect and set measures to protect self against STIs other than HIV 110 (36.7) / 6 (2.0) 100 (33.3)/ 100 (33.3) −34.7 / 0.0 Protect and set measures to protect self against HIV 187 (62.3) / 252 (84.0) 174 (58.0) / 180 (60.0) + 21.7 / +2.0 Smoke tobacco 15 (5.0) / 8 (2.7) 17 (5.7) / 19 (6.3) −2.3/ +0.6 Heavy alcohol drinking 91 (30.3) / 35 (11.7) 96 (32.0) / 98 (32.7) −18.6 / +0.7 Take caffeine 6 (2.0) / 7 (2.3) 10 (3.3) / 17 (5.7) + 0.3/ +2.4 Use drugs or caffeine 7 (2.3) / 9 (3.0) 7 (2.3) / 9 (3.0) + 0.7/ +0.7 Use non-prescribed medicines 93 (31.0) / 39 (13.0) 100 (33.3) / 119 (39.7) −18.0 / +6.4 Use herbal drugs 80 (26.7) / 24 (8.0) 75 (25.0) / 78 (26.0) −18.7/ +1.0 Adopt physical activity 157 (52.3) / 156 (52.0) 116 (38.7) / 106 (35.3) −0.3/ −3.4 Established measures to avoid and manage stress (at home, job) 98 (32.7) / 163 (54.3) 80 (26.7) / 74 (24.7) + 21.6/ −2.0 Good sleep patterns and avoid sleep disturbances 139 (46.3) / 174 (58.0) 121 (40.3) / 113 (37.7) + 11.7 / −2.6 Protect-self against toxic environment exposure 41 (13.7) / 112 (37.3) 39 (13.0) / 36 (12.0) + 23.6/ −1.0 Went to seek fertility checkup/advice at health facility 10 (3.3) / 81 (27.0) 7 (2.3) / 11 (3.7) + 23.7 / +1.4 Checked consanguinity relationship with the partner 16 (5.3) / 178 (59.3) 9 (3.0) / 15 (5.0%) + 54.0 / +2.0 Protect-self/partner against GBV 246 (82.0) / 272 (90.7) 258 (86.0) / 280 (93.3) + 8.7 / +7.3 Note: n = number of those who responded ‘Yes” (males and females combined) at each item Total sample: 600 participants in intervention group (300 males, 300 females) % = percentage of participants within group (intervention or control). Means % was calculated based on 300 participants in each group Overall post-intervention change = the absolute percentage point increase or decrease from pre-test to post-test. Table 3 demonstrates the substantial effectiveness of the focused preconception education and counseling (FPEC) intervention in promoting conception preparedness screening attitudes and practices among premarital and soon-to-be-married couples in Rwanda. The most striking improvements occurred in blood type and Rh factor testing (+ 64.3%), blood pressure screening (+ 60.7%), anemia screening (+ 59.7%), and blood sugar testing (+ 48.0%), all showing dramatic increases compared to minimal changes in the control group. Additional screening behaviors also improved significantly, including HIV/AIDS screening (+ 32.0%), syphilis and STI/UTI screening (+ 28.7%), hepatitis screening (+ 14.7%), family genetic predisposition checking (+ 35.0%), and BMI monitoring (+ 45.3%). The intervention also enhanced family planning practices: planning conception timing (+ 56.3%), checking consanguinity with partners (+ 54.0%), making plans about desired number of children (+ 40.7%), calculating fertile days (+ 16.3%), and seeking fertility checkups (+ 23.7%). These comprehensive improvements across multiple screening domains indicate that the FPEC program successfully raised awareness among couples about the importance of clinical assessments before conception and improved their utilization of healthcare services as part of conception preparedness. Concerning prophylactic treatments and preventive medical interventions for conception preparedness, the FPEC intervention achieved notable success among premarital couples. Tetanus vaccination increased by 42.0% in the intervention group compared to virtually no change in controls (+ 0.7%). Folic acid and vitamin supplementation improved by 30.7% versus only 2.7% in controls, rising from 17.3% to 48.0% of participants. Attention to avoiding teratogenic medications increased by 34.0%, though the control group also showed improvement (+ 19.7%), possibly reflecting broader community awareness in Rwanda. Hepatitis vaccination showed more modest gains (+ 14.7%) from a very low baseline, suggesting this may be a less accessible service. These findings demonstrate strong effectiveness in promoting prophylactic treatments, particularly for immunizations and supplementation that couples could readily access as part of their conception preparedness and marriage preparation. Regarding behavioral and lifestyle modifications related to conception preparedness, the FPEC intervention demonstrated mixed results. The program achieved notable success in substance use reduction: heavy alcohol consumption decreased by 18.6% while increasing in controls (+ 0.7%), non-prescribed medicine use decreased by 18.0% versus increasing by 6.4% in controls, and herbal drug use declined by 18.7% compared to a 1.0% increase in controls. Tobacco smoking decreased slightly (2.3%) while increasing in controls (+ 0.6%). The intervention also improved stress management (+ 21.6%), sleep patterns (+ 11.7%), protection against unintended pregnancy (+ 31.0%), environmental toxin exposure protection (+ 23.6%), and HIV protection measures (+ 21.7%). However, certain lifestyle modifications proved resistant to change: physical activity declined slightly in both groups, balanced diet improved by only 7.3%, and caffeine and drug use remained stable at low levels. One concerning finding was that protection against STIs other than HIV decreased by 34.7% in the intervention group while remaining stable in controls, possibly reflecting changes in risk perception among couples approaching marriage who may view monogamy as sufficient protection. Figure 1 illustrates the trends in attitudes and practices related to preconception care (CP) in the intervention and control groups at baseline and follow-up assessments. The figure clearly demonstrates the substantial effectiveness of the Family Planning and Preconception Education (FPEC) intervention in enhancing conception preparedness across all performance levels. The intervention group exhibited marked improvements from baseline to follow-up: minimum scores rose from 15.6 to 34.4 (+ 18.8 points), mean scores increased from 35.3 to 58.3 (+ 23.0 points), and maximum scores surged from 50.0 to 81.3 (+ 31.3 points). In contrast, the control group showed minimal changes: minimum scores increased slightly from 18.8 to 31.3, mean scores rose marginally from 38.2 to 41.7, and maximum scores remained nearly unchanged at approximately 53. At follow-up, a wide gap emerged between the groups, with a 16.6-point difference in mean scores and a 28.7-point difference in maximum scores. Table.4. Pre and Post scores and means differences amidst intervention and control group Pre- and Post-Intervention Scores and means differences between Control and Intervention Groups Table 3 presents the results of a difference-in-differences (DiD) analysis comparing conception preparedness attitudes and practices scores between the intervention and control groups at baseline and follow-up. Group Assessment Time Min. Score Max. Score Avg Score Change in Average Score Mean Square F-test p-value Control Group Pre-Test 18.8 53.1 38.2 - 262.9 - .18 Post-Test 31.3 52.6 41.7 + 3.5 248.7 1.8 Intervention Group Pre-Test 15.6 50.0 35.3 — 174.1 - Post-Test 34.4 81.3 58.3 + 23.0 289.4 12.4 .001** DiD - - - + 19.5 315.2 270.7 - Note • Min Score / Max Score / Avg Score: Minimum, maximum, and average scores for each group at each time point. • Avg Score: Change in average score from pre-test to post-test. • Mean Square: Variance estimate used in the F-test calculation. • F-Test: Test statistic indicating whether the change is statistically significant. • p-value: Probability value indicating significance level. • DiD: Difference-in-Differences effect, calculated as (Intervention Avg) − (Control Avg). • p < .05 = statistically significant • p < .01 = highly statistically significant (**) The intervention group showed substantial improvement, with mean scores increasing from 35.3 at baseline to 58.3 at follow-up (+ 23.0 points; F = 12.4, p = 0.001), indicating a highly significant effect of the FPEC intervention. In contrast, the control group exhibited only minimal change, with mean scores rising from 38.2 to 41.7 (+ 3.5 points; F = 1.8, p = 0.18), which was not statistically significant. The DiD analysis, isolating the true intervention effect by accounting for changes in the control group, revealed a net effect of + 19.5 points (F = 270.7, p < 0.001). This confirms that the FPEC intervention significantly enhanced conception preparedness attitudes and practices beyond any natural changes over time Table 4 Linear regression analysis Coefficients a Model Unstandardized Coefficients Standardized Coefficients t Sig. 95% CI B Std. Error Beta Lower Bound Upper Bound 1 Control group 19.0 1.100 - 17.31 .120 18.43 21.16 Intervention 19.8 .696 .758 28.45 .000** 18.50 21.10 **p value < 0.01 statistical significance CI=confidence interval Table 4 presents linear regression analysis results examining the effect of group assignment on conception preparedness attitudes and practices scores. The control group demonstrated a significant baseline score (OR = 19.0, 95% CI [18.43, 21.16], p < .001), while the intervention group showed substantially higher scores, being 19.8 times more likely to achieve improved conception preparedness compared to the control group (OR = 19.8, 95% CI [18.50, 21.10], p < .001). This finding confirms that couples who received the FPEC intervention were nearly 20 times more likely to demonstrate enhanced conception preparedness attitudes and practices compared to couples who did not receive the intervention. Discussion The purpose of this study was to evaluate the effectiveness of focused preconception education and counseling (FPEC) on conception preparedness attitudes and practices among premarital and soon-to-be-married couples in Rwanda. Using a quasi-experimental pre-post-test design, the study examined whether a couple-based educational intervention could improve conception preparedness behaviors in a context where couples must self-finance all services and navigate healthcare systems independently without integrated preconception care programs. Overall FPEC intervention effectiveness In overall, the FPEC intervention in our study demonstrated substantial effectiveness in improving conception preparedness attitudes and practices across multiple domains among participants. We found intervention group participants’ scores rose by 23 points compared to only 3.5 points in the control group, yielding a significant net difference of 19.5 points. Additionally, we revealed that participants in intervention group were nearly 20 times more likely to achieve higher preparedness scores than controls. Together, these results provide strong evidence that couple-based preconception education significantly improved attitudes and practices, even in the absence of integrated care systems and despite financial constraints. Our findings collaborate with those from a study in Iran that revealed a premarital counseling enhanced conception preparedness positive attitudes and practices among brides and grooms( 54 ) We revealed that couple-based preconception education and counseling delivered at the premarital period can drive substantial, causally attributable behavior change even in resource-constrained contexts. The intervention's integration with premarital counseling created a uniquely receptive moment, as couples preparing for marriage and parenthood were highly motivated to invest in preparation. Research from Malaysia confirms that preconception interventions during marriage preparation achieve 40% higher uptake than general reproductive-age interventions( 55 ). Effect of FPEC on preconception clinical screening uptake The FPEC intervention achieved particularly impressive results in clinical screening behaviors, substantially exceeding outcomes reported in similar studies. For example, Blood type and Rh factor testing increased by 64.3%, blood pressure screening by 60.7%, and anemia screening by 59.7% far surpassing rates from comparable interventions in two studies conducted China( 56 ), ( 57 ) and in Ethiopia( 58 ). What might have contributed to these achievements differences is the inclusion of both male and female partners in the FPEC intervention in our study, as some evidences consistently shows that couple-based interventions achieve 35–42% higher screening completion rates compared to women-only programs through mutual support, pooled resources, and shared accountability ( 59 ), ( 60 ). Effect of FPEC on preconception prophylactic treatments and supplementation uptake Prophylactic treatments and supplementation also showed notable improvements in our study. For example, we found that Tetanus vaccination increased by 42.0%, substantially outperforming the 15–20% average improvement reported in systematic reviews of similar interventions in low- and middle-income countries( 40 ). Folic acid supplementation reached 48.0% of participants (30.7% increase), superior to 11.4% found in Ethiopia( 61 ), uptake rate of only 8% after education intervention in the study conducted in Kenya( 62 ). On contrast, a systematic review showed preconception folic acid supplementation uptake was 45.2%( 63 ) and 72.7% in France ( 64 ).The substantial increase of prophylactic treatments and supplementation uptake among our participants might have been triggered that we applied the couple-based education and counseling approach, where both partners may understand the importance of preconceptional vitamins and jointly commit to prioritizing and uptake supplementation despite low financial income revealed in majority of our study participants. The evidences from literature supports this mechanism, finding that women are 2.3 times more likely to maintain supplementation when male partners were educated about its importance( 65 ),( 66 ). Prophylactic treatments and supplementation showed notable improvements in our study. Tetanus vaccination increased by 42.0%, substantially outperforming the 15–20% average improvement reported in systematic reviews of similar interventions in low- and middle-income countries( 40 ). Folic acid supplementation reached 48.0% of participants (30.7% increase), markedly superior to rates in Ethiopia (11.4%) and Kenya (8%) ( 61 ), ( 62 ) where educational interventions targeted women only. However, our findings remained below rates in higher-resource settings, including a systematic review reporting 45.2% uptake( 63 ) and France achieving 72.7%( 64 ). These disparities may reflect integrated preconception care systems, subsidized or free supplements, and longstanding public health campaigns in developed countries. The couple-based education approach used in our study might have contributed to more substantial success compared to similar low-resource contexts that involved only women. Evidence supports this mechanism, showing women are 2.3 times more likely to maintain supplementation when male partners are educated about its importance as when both partners understand the importance of periconceptional vitamin supplements, it stimulates mutual accountability and commitment to prioritizing supplementation and pooling resources toward this goal( 65 ) ( 66 ). Effect of FPEC on Behavioral and lifestyle modifications Behavioral and lifestyle modifications related to substance use showed impressive sustained change despite the absence of any follow-up support after the initial education session. For example, we found that heavy alcohol consumption decreased by 18.6%, non-prescribed medicine use by 18.0%, and herbal drug use by 18.7% all substantially exceeding rates from comparable studies in Tanzania (7% reduction) and Uganda reduction) that included multiple counseling sessions ( 67 );but the improvement rate was higher in the Netherland study( 68 ). Our study findings might be related to that given that 81.5% of the participants resided in rural areas where traditional medicine use is culturally embedded, yet the intervention might have successfully challenged these practices. Additionally, as over the quarter (45.8%) of participants had only primary education, the FPEC might have contributed to improved health literacy even among participants with low education level, triggering behavior and lifestyle change to individuals and couples. Behavioral and lifestyle modifications related to substance use showed impressive sustained change despite the absence of follow-up support after the initial education session. Heavy alcohol consumption decreased by 18.6%, non-prescribed medicine use by 18.0%, and herbal drug use by 18.7%, substantially exceeding rates from comparable studies in Tanzania (7% reduction) and Uganda (8% reduction) that included multiple counseling sessions( 67 ). However, our findings were below those reported in the Netherlands( 68 ), likely reflecting differences in baseline health literacy, healthcare access, and socioeconomic resources between settings. In our study, the couple-based approach used may have created mutual accountability that sustained behavior changes, with both partners monitoring and supporting each other without professional oversight. Also, the premarital timing may have enhanced receptivity, as couples preparing for marriage and parenthood are highly motivated to adopt healthier lifestyles as stipulated by the literature( 69 ). Areas of FPEC limited success among participants Nevertheless, the FPEC intervention in our study showed some limited success in conception preparedness attitudes and practices uptakes among participants. For example, physical activity increased minimally (0.3%), while balanced diet adoption improved by only 7.3% comparable to studies in Turkey (9%) and the United States (6%) that provided ongoing nutritional counseling and cooking demonstrations( 70 );( 71 ). These findings are consistent with the literature, which suggests that education-only interventions generally require supplementary support to achieve meaningful lifestyle behavior change( 72 ).That literature indicates that sustained improvements in preconception dietary and physical activity behaviors require multifaceted support, including ongoing resources, environmental modifications, and continuous guidance to couples beyond initial educational interventions( 72 ). We also observed a 34.7% decrease in protection against STIs other than HIV in the intervention group, consistent with findings from studies by Utami et al. and Amizar et al., where premarital counseling increased knowledge without producing significant changes in preconception STI self-protection behaviors( 73 ),( 74 ). Notably, while HIV protection behaviors improved (21.7% increase), protection against other STIs declined. These divergent outcomes may be attributable to participants distinguishing between HIV commonly included in mandatory premarital screening protocols and other STIs that may lack similar institutional requirements or public health emphasis. Furthermore, evidence argue that married or committed couples frequently assume mutual fidelity eliminates STI risk, leading them to discontinue protective practices ( 75 ),( 76 ). Influence of sociodemographic characteristics on study findings The sociodemographic profile of study participants may have significantly influenced intervention outcomes in complex ways. With regard to sex, in general we found low baseline preconception preparedness followed by substantial post-intervention improvements in both sexes. Post-intervention, females demonstrated four-fold greater improvements in screening behaviors than males: blood pressure testing increased 48.7% vs. 12.0%, blood type/Rh testing rose 51.7% vs. 12.7%, screening rates reached 40–55% vs. 12–16%, and folic acid use increased 24.7% with lower male uptake. Half of females planned conception timing versus only one-seventh of males. These findings represent novel contributions, as limited sub-Saharan African studies have examined men's preconception care utilization( 46 ), and evidence for male intervention effectiveness remains limited ( 77 ). However, gender convergence appeared in risky behavior reduction, with similar decreases in alcohol (10.7% vs. 8.0%) and herbal drug use, suggesting behavioral cessation interventions work equally well for both sexes. Persistent gaps despite identical interventions indicate that achieving equity requires specially designed male-targeted programs addressing gender norms, and structural barriers as recommended by different researchers( 78 ),( 79 ). The predominantly young age distribution (64.7% aged 21–30) may have enhanced intervention receptivity, as research shows young couples transitioning to parenthood demonstrate high motivation to optimize health( 80 ). Rural residence (81.5%) may have created dual effects: limiting access to diverse foods and exercise facilities, contributing to minimal improvements in physical activity (0.3%) and balanced diet (7.3%), consistent with literature documenting rural barriers including limited health clinics, limited specialty services, lower health literacy, financial constraints and insufficient transport. However, rural communities may have provided stronger social networks( 81 ) that reinforced the 18.7% reduction in culturally embedded herbal drug use. Despite 45.8% having only primary education and 60.5% earning below $ 137 USD monthly, the couple-based approach may have compensated through partner discussion and shared decision-making, potentially improving health literacy more effectively than individual counseling, supported by evidence that interactive couple-based interventions successfully improve health behaviors even among low-education populations( 82 ). Economic constraints may have created barriers to sustained dietary improvements but appeared overcome for one-time clinical screenings (blood pressure + 60.7%, anemia + 59.7%, blood type + 64.3%) when couples pooled resources, aligning with research showing couple counseling improves health service uptake through shared decision-making and resource pooling as demonstrated in the study from rural KwaZulu-Natal, South Africa ( 83 ). Religious affiliation (80.6% Christian) may have reinforced intervention messages since religious communities often encourage abstaining from harmful substances (alcohol, drugs, smoking), and as also faith can provide emotional strength thus reducing anxiety and stress( 84 ). Being that there was gender equity (50% male, 50% female) may have transformed preconception preparation into a shared endeavor as evidence indicates partner involvement increases women's likelihood of maintaining preconception care uptake by 2.3 times ( 85 ) and mutual support enhances health behavior initiation and maintenance( 86 ). Impact of fragmented healthcare system on study findings The absence of an integrated preconception care program in Rwanda's health system may have created substantial barriers to translating knowledge into practice, despite couples' motivation following the FPEC intervention. After receiving education, couples had to independently identify where services were available, make appointments at multiple facilities, arrange transportation, and finance each service separately challenges particularly acute for the 81.5% of participants residing in rural areas where specialized clinics and pharmacies are rare. This fragmentation may explain the wide variation in screening uptake observed in our study. Accessible, affordable tests available at most health centers and health posts (blood pressure screening, blood type testing, anemia screening) showed dramatic increases (60–64%), while specialized services requiring referral to higher-level facilities (hepatitis screening) increased by only 14.7%. The lack of a structured pathway meant couples may have faced cumulative navigation complexity across multiple visits without systematic support, coordination, or follow-up. Research in Pakistan demonstrates that even when couples can pay for services, fragmented systems significantly reduce uptake because navigation barriers accumulate across multiple required visits( 87 ). The lack of preconception subsidized preconception care packages or health insurance coverage for preventive services, may have created financial barriers. Without subsidized preconception care packages or health insurance coverage for preventive services, couples had to pay out-of-pocket for each screening, vaccination, and supplement. The observed pattern high uptake of essential, affordable services but lower uptake of more expensive specialized screenings may reflect couples' rational prioritization within severe budget constraints. An integrated preconception care program with bundled services at reduced cost could substantially improve uptake across all recommended practices. The lack of integration between premarital counseling (typically provided by religious institutions or civil authorities) and healthcare services may have created missed opportunities for seamless referral and follow-up. While our FPEC intervention temporarily bridged this gap, sustainable impact requires institutionalized linkages between marriage preparation programs and health facilities. Countries with successful preconception care programs( 59 ), have established formal partnerships between community organizations providing marriage preparation and healthcare systems offering preconception services, creating clear pathways for couples to access comprehensive care. Despite these systemic barriers, the FPEC intervention achieved substantial improvements in conception preparedness attitudes and practices, demonstrating that even single-session couple-based education can produce meaningful behavior change in fragmented healthcare contexts. Strength and limitations of the study Our study evaluating the effectiveness of focused preconception education and counseling among premarital couples in Rwanda has several important strengths and limitations, particularly in a country lacking a comprehensive preconception care program within its national healthcare system. Key strengths include a large, diverse sample of 600 couples from urban and rural areas, ensuring high relevance to the Rwandan population; the inclusion of both men and women, addressing a critical research gap in male involvement in pregnancy preparation; evidence that a feasible, brief single-session intervention delivered during routine premarital counseling can significantly improve conception preparedness even without broader health service support; and its conduct in a predominantly rural, low-income setting with a fragmented healthcare system, demonstrating that targeted education alone can drive meaningful behavior change in resource-constrained environments. However, limitations include the absence of random assignment, potentially introducing selection bias from unobserved group differences; a short three-month follow-up period insufficient for capturing sustained lifestyle changes; reliance on self-reported data susceptible to social desirability bias; and the use of only one brief session, limiting insights into more intensive approaches. While the findings are highly applicable to similar low-resource sub-Saharan African settings with comparable sociocultural and healthcare challenges, generalizability may be restricted to populations such as established couples not seeking premarital counseling, high-income countries with existing preconception infrastructure, or contexts with differing cultural attitudes toward marriage preparation and reproductive health. Conclusion This study demonstrates that couple-based preconception education and counseling delivered during the premarital period in Rwanda significantly enhances conception preparedness, with intervention participants nearly 20 times more likely to achieve improved attitudes and practices compared to controls. The FPEC program proved to be effective in promoting behaviors requiring one-time or short-term decision-making, including uptake of screenings, vaccinations, and reduction of substance use and alcohol consumption. However, behaviors requiring sustained resources and ongoing commitment such as dietary modifications and regular physical activity showed limited improvement, highlighting the need for continued support beyond initial counseling sessions. These findings provide compelling evidence for integrating the FPEC program into Rwanda's existing premarital services and broader reproductive, maternal, and child health promotion initiatives, particularly those targeting reproductive-age populations. To maximize the program's impact and sustainability, we recommend establishing a comprehensive national preconception care framework that includes: ( 1 ) subsidized or free access to preconception services, ( 2 ) coordinated care pathways linking premarital counseling with primary healthcare, ( 3 ) structured follow-up support to reinforce sustained behavior change, and ( 4 ) targeted assistance for resource-intensive health behaviors. Future research should prioritize longitudinal studies examining the long-term effects of FPEC interventions on maternal, neonatal, and child health outcomes, as well as implementation science studies to identify optimal strategies for scaling and sustaining preconception care programs in low-resource settings including Rwanda. Declarations Ethics approval and consent to participate The study was conducted in accordance with the ethical principles of the Declaration of Helsinki. Ethical approval was obtained from the Institutional Review Board of the University of Rwanda, College of Medicine and Health Sciences (Approval No. 337/CMHS-IRB/2024). Additional permissions were secured from relevant local authorities and church leaders. Written informed consent was obtained from all participants prior to enrollment, and anonymity was ensured by using identification codes only, without collecting personal identifiers. Consent for publication Not applicable. No individual person’s data (such as medical records, images, videos, or personal details) are included in this article. Competing interests The authors declare that there is no conflict of interest. Funding The authors declare that this research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. Authors' contributions RN, OB, TCU and DG contributed to the study conception and design. RN, TCU and OB contributed to data collectors training and data collection. RN, OB, TCU, DG and I-MC contributed to data analysis and interpretation of results. RN, OB, TCU, I-MC, HL and JRL contributed to preparing and drafting the manuscript. All authors reviewed the results and approved the final version of the manuscript. Acknowledgements We extend our sincere gratitude to the midwives who facilitated data collection, the engaged couples who generously participated in this study, and the church leaders and local administrators whose support was instrumental in making this research possible. We are also grateful to the University of Michigan African Presidential Scholars (UMAPS) Program for providing valuable technical guidance and writing assistance throughout this project. Availability of data and materials All data supporting the findings of this study are available within the paper and its Supplementary Information. References Moller AB, Patten J, Hanson C, Essén B, Jacobsson B (2025) Five decades of advancing global maternal and newborn health and rights: Milestones and initiatives. 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Welfare","correspondingAuthor":false,"prefix":"","firstName":"Ing-Marie","middleName":"","lastName":"Carlsson","suffix":""},{"id":580166485,"identity":"7c42fa41-d19d-470d-bf9e-12b599dfe468","order_by":5,"name":"HaEun Lee","email":"","orcid":"https://orcid.org/0000-0002-1259-6425","institution":"University of Michigan, Department of Systems, Population, and Leadership/School of Nursing","correspondingAuthor":false,"prefix":"","firstName":"HaEun","middleName":"","lastName":"Lee","suffix":""},{"id":580166486,"identity":"aa23eb16-3897-4d67-979e-9d41a4fc1f92","order_by":6,"name":"Jody Rae Lori","email":"","orcid":"https://orcid.org/0000-0003-0564-5783","institution":"University of Michigan, Department of Health Behavior and Clinical Sciences/School of Nursing","correspondingAuthor":false,"prefix":"","firstName":"Jody","middleName":"Rae","lastName":"Lori","suffix":""}],"badges":[],"createdAt":"2026-01-25 21:04:24","currentVersionCode":1,"declarations":{"humanSubjects":true,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":true,"humanSubjectConsent":true,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-8694857/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8694857/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":101214165,"identity":"a5417860-6a92-4020-9c7b-32025a968b5d","added_by":"auto","created_at":"2026-01-27 10:34:00","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":177699,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eTrends of CP attitudes and practices at initial and follow up assessment between intervention and control group\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8694857/v1/60cf63ad4ca286854d426dc5.png"},{"id":101214308,"identity":"1bb83a62-6ca0-49d9-a009-a8e3a3af67bc","added_by":"auto","created_at":"2026-01-27 10:34:37","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2255880,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8694857/v1/6c134189-126e-4306-98a6-860c37688ddd.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eEffectiveness of focused preconception education and counseling (FPEC) on conception preparedness among premarital couples: \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003eA quasi-experimental pre-post study\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e","fulltext":[{"header":"BACKGROUND","content":"\u003cp\u003eMaternal and neonatal mortality remain critical global public health challenges, with 287,000 maternal deaths and 2.4\u0026nbsp;million neonatal deaths occurring annually worldwide, disproportionately concentrated in sub-Saharan Africa where maternal mortality ratios average 542 deaths per 100,000 live births compared to 11 per 100,000 in high-income countries(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e),(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Approximately 80% of pregnancy-related deaths and complications are preventable through timely interventions and about 75% of maternal deaths and morbidities are associated with modifiable risk factors present before conception, including preexisting medical conditions, psychosocial stressors, environmental exposures, and lifestyle behaviors from either male, female, or both partners(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eEvidence show that more than 60% of women and a considerable number of men of childbearing age in Sub-Saharan Africa have at least one changeable risk factor before pregnancy that significantly affects pregnancy outcomes(\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Among women of reproductive age, 32% globally live with anemia (40\u0026ndash;50% in sub-Saharan Africa), which raises the risk of maternal death by 3.5 times while leading to bleeding complications, postpartum hemorrhage, miscarriage, low birth weight, restricted fetal growth, and early delivery(\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Pre-existing health problems affect substantial proportions: 2\u0026ndash;5% live with diabetes(\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e), 3\u0026ndash;5% live with chronic hypertension(\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e), and 13% globally live with obesity conditions that increase the likelihood of birth defects, miscarriage, fetal death, preeclampsia, gestational diabetes, cesarean delivery, and maternal death. Furthermore, approximately one-third of childbearing age population live in hazardous environment associated with risks of abortion, pre-eclampsia, gestational diabetes, preterm deliveries, stillbirths and congenital abnormalities(\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e),(\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). In low- and middle-income countries, 10\u0026ndash;20% of reproductive age women live with insufficient nutrition(\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e) with risks of miscarriage, preterm birth, restricted fetal growth, stillbirth, breastfeeding associated disorders and intergenerational effects(\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e), (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Additionally, 15\u0026ndash;25% of women and 10\u0026ndash;15% of men in reproductive age live with mental health disorders(\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e), which are linked to decreased fertility, miscarriage, preterm birth, and poor child neurodevelopmental outcomes(\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). Furthermore, millions of couples\u0026rsquo; experience exposure to harmful substances from farming, workplace, and home environments, causing reduced fertility, miscarriage, birth defects, and neurodevelopmental disorders in children (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn Rwanda, several pre-pregnancy modifiable factors are prevalent in both women and men like it is in other LMICs. For example, reports show 2.1\u0026ndash;5.74% of women of reproductive age live with untreated syphilis infection, which may result in poor pregnancy outcomes in 50\u0026ndash;80% of cases(\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e), whereas 5.8% are underweight(\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e), 17.2% live with anemia and with insufficient folic acid intake, raising neural tube defect risk by 70%(\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e), (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). Among men of reproductive age, 5\u0026ndash;8% live with type 2 diabetes(\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e) and 9.2% live with obesity while 16% has undernutrition (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e), leading to decreased sperm quality with increased risk of DNA damage, and elevated risks of miscarriage, birth defects, metabolic disorders in neonates and children and chronic conditions in offspring (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e),(\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e). Alcohol and substance use are prevalent in both reproductive age sex: 4.4% use cannabis, opiates and cocaine and cigarette use is in 2.9%(\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e), which may reduce fertility, causes unintended pregnancy and causes miscarriage, placental problems, pre-eclampsia, preterm birth, low birth weight, stillbirth, sudden infant death syndrome, and childhood cancers(\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e),(\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e).Also 10\u0026ndash;20% of women and 31.6% of men live with alcohol consumption patterns(\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e) that may result in fetal alcohol spectrum disorders, miscarriage, and birth defects in prospect pregnancy(\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e)(\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). Additionally, mental disorders are prevalent among 23.2% of women than 16.6% men of reproductive age(\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e) exposing them to risks unintended pregnancy, miscarriage, pre-eclampsia, stillbirth, preterm labor, perinatal depression, puerperal psychosis(\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e),(\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e),(\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e).Furthermore, thousands of men and women of reproductive age are exposed to hazardous environment. For example, biomass fuel use is prevalent in 85% of households causing indoor air pollution. Agricultural pesticide exposure and smoke exposure is in 10\u0026ndash;15%, (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e),(\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e)which further may cause risks and complications on prospect pregnancy.\u003c/p\u003e \u003cp\u003eDespite substantial investments in prenatal, delivery, and postnatal care, maternal and neonatal mortality and morbidity burden remain high, and progress toward achieving Sustainable Development Goal targets for reducing maternal mortality to less than 70 per 100,000 live births and neonatal mortality to 12 per 1,000 live births by 2030 has been slower than anticipated(\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e). This persistent challenge has prompted renewed attention to preconception care, including education and counseling, which addresses pre-pregnancy health risks, health conditions, lifestyles, and risky practices that can affect prospective pregnancy. Unlike antenatal care education, which begins after pregnancy is confirmed in over 99% of cases and often too late, after the critical first eight weeks of embryonic development (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e)(\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e), preconception counseling offers a 3 to 6-month period to optimize health before pregnancy, time needed to improve egg and sperm quality, address nutritional deficiencies, control chronic health conditions, limit toxin exposure, reduce stress, and build healthy habits, thereby minimizing unsafe pregnancies, enhancing pregnancy outcomes, and fostering family wellness(\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eEvidence demonstrates that preconception education and counseling serves as the foundational intervention that enables women and couples to understand, access, and implement preconception health measures, thereby significantly reducing maternal and neonatal morbidity and mortality(\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e). The WHO estimates that comprehensive maternal care from preconception could prevent 54% of maternal and 71% of neonatal deaths globally(\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e). Evidence show that in developing countries ,community-based preconception education can increase antenatal care uptake by 39%, reduce neonatal mortality by 17%, and increased breastfeeding by 71%(\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e).Other various studies showed the impact of preconception education and counseling on conception preparedness behaviors and its impact on pregnancy outcomes. For example, a study found that women who receive structured preconception education are 2\u0026ndash;3 times more likely to take folic acid supplements before pregnancy, reducing neural tube defects by 50\u0026ndash;70%(\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e). A preconception education programs increased the proportion of women with diabetes achieving optimal glycemic control before conception, reducing congenital malformation risk from 10% to 1\u0026ndash;2%(\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e). A study demonstrated women with chronic conditions receiving preconception counseling had fewer pregnancy complications, including reduced rates of preterm birth, low birth weight, and congenital abnormalities(\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e).Then, a study conducted in India, Pakistan, Guatemala, and the Democratic Republic of Congo found preconception education about nutrition reduced pregnancy associated anemia and the risk of small for gestational age births, and 10\u0026ndash;15% reductions in preterm birth (\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eDespite proven benefits, significant gaps persist worldwide in preconception education and implementation. Between 60\u0026ndash;94% of women globally do not receive structured preconception education(\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e), with rates varying by setting. The vast majority of women in Sub-Saharan Africa 76% on average do not receive preconception care, with rates exceeding 90% in Sudan and Nigeria, and 74% in Ethiopia(\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e); (\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e). Rwanda, lacking specific data but with limited preconception services, likely faces similar or higher gaps. While Rwanda has achieved impressive antenatal care coverage with over 95% of women attending at least one visit(\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e), preconception care and education are largely absent from the healthcare continuum. Maternal and neonatal mortality remain high at 149 per 100,000 live births and 27 per 1,000 live births respectively, with many deaths linked to modifiable preconception factors(\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e). Rwanda's healthcare system, similar to many low-income countries, allocates greater resources to antenatal and postnatal care than to preconception education. Community awareness of preconception health remains limited, with gaps in understanding modifiable risk factors and pregnancy preparation strategies. This lack of awareness may result in missed opportunities to prevent adverse outcomes such as neural tube defects, low birth weight, preterm birth, maternal anemia, and pregnancy complications associated with uncontrolled chronic conditions.\u003c/p\u003e \u003cp\u003eGiven the proven effectiveness of preconception education in improving conception preparedness and reducing maternal and neonatal morbidity and mortality, the persistently high maternal and neonatal mortality in Rwanda despite strong antenatal care coverage, the high prevalence of modifiable risk factors among reproductive-age men and women, and the absence of research and data on impact of structured preconception education on pregnancy preparedness in Rwanda, there is an urgent need for context-specific evidence. This study therefore aimed to pilot and evaluate the effectiveness of focused preconception education and counseling on conception preparedness among premarital couples in Rwanda.\u003c/p\u003e \u003cp\u003eRwanda's high marriage registration rates with 66% of couples living in formal/legal unions(\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e), cultural emphasis on family preparation, and tradition of couples seeking premarital guidance provide an ideal platform for couple-based preconception education programs. However, current premarital education and counseling rarely include reproductive and maternal health discussions. Therefore, our study focused on premarital couples because they are easily reached through existing preparation programs and are at a critical life stage when pregnancy planning typically begins. They are also highly motivated to improve their health for future family formation and uniquely positioned to jointly adopt healthier practices as a couple. Importantly, this group offers the essential 3 to 6-month preconception window to correct nutritional deficiencies, stabilize chronic conditions, enhance gamete quality, and reduce harmful exposures. Both males and females were involved because preconception health risks and outcomes are influenced by both partners, and addressing them together ensures comprehensive preparation, improved fertility, and healthier pregnancies. Furthermore, both men and women were included since preconception health depends on both partners, and addressing them together leads to better preparation, fertility, and pregnancy outcomes. Men and women were both included because preconception health relies on both partners, and working together helps improve preparation, fertility, and pregnancy outcomes. While many studies have mostly focused on women and rarely involved men, this study aimed to highlight the important role of both partners in preconception care and address the existing research gap.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eStudy Design\u003c/h2\u003e \u003cp\u003eThis study used a quasi-experimental pre-post design with non-equivalent groups to assess the effectiveness of focused preconception education and counseling (FPEC) on conception preparedness among premarital couples in Rwanda. All participants underwent baseline assessment, followed by FPEC delivery only to the intervention group and post-assessment of both groups three months later. Due to ethical and logistical constraints in premarital settings, systematic site-based allocation was used instead of randomization to balance groups and reduce contamination.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eStudy Setting\u003c/h3\u003e\n\u003cp\u003eIn Rwanda, premarital couples attend mandatory education sessions (\"Ecoles des fianc\u0026eacute;s\") held monthly for 3 to 6 months at sector offices and churches before receiving a marriage license. Participants were recruited from these venues nationwide. To ensure geographic diversity across urban and rural areas, 15 sites were randomly selected from all provinces: Mushonyi, Gisenyi, and Kanama (Western); Huye, Nyarusange, and Kamonyi (Southern); Muhoza, Ruli, and Shyorongi (Northern); Rwamagana, Kayonza, and Muhura (Eastern); and Kinyinya, Nyamirambo, and Masaka (Kigali City).\u003c/p\u003e\n\u003ch3\u003eStudy Population and Eligibility Criteria\u003c/h3\u003e\n\u003cp\u003eThis study enrolled premarital couples who were formally registered for civil or religious marriage and planning to have children after marriage. Eligible couples must have registered for marriage within six months before data collection. Female partners were required to be between 21 and 45 years of age (reproductive age), while male partners had to be at least 21 years old, in accordance with Rwanda's legal marriage age established by Presidential Decree No. 102/05 of March 13, 1992(\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e). Both partners must have reported no current pregnancy at enrollment.\u003c/p\u003e \u003cp\u003eCouples were excluded from the study if they did not plan to have children after marriage, if either partner was pregnant at the time of enrollment, or if either partner refused to participate or provide informed consent. These eligibility criteria ensured the study focused on premarital couples in the preconception period who would benefit from preparedness interventions.\u003c/p\u003e\n\u003ch3\u003eSampling Technique and Sample Size\u003c/h3\u003e\n\u003cp\u003eA total of 720 couples were screened from prospective marriage registers at churches and sector offices to achieve the target sample size of 670 couples. This target was calculated using Cochran's formula for proportion estimation, assuming a preconception preparedness prevalence of 50% (to yield the maximum sample size), a 95% confidence level, and a 5% margin of error.\u003c/p\u003e \u003cp\u003eOf those screened, 623 couples met the inclusion criteria and provided consent. These were systematically allocated by site to either the intervention group (n\u0026thinsp;=\u0026thinsp;312 couples) or the control group (n\u0026thinsp;=\u0026thinsp;311 couples). Ultimately, 600 couples completed both baseline and follow-up assessments and were included in the analysis (intervention: n\u0026thinsp;=\u0026thinsp;300; control: n\u0026thinsp;=\u0026thinsp;300), after excluding 23 couples lost to follow-up (2 from the intervention group and 21 from the control group).\u003c/p\u003e\n\u003ch3\u003eData Collection Tool\u003c/h3\u003e\n\u003cp\u003eThe questionnaire used in this study was specifically developed for this research by adapting items from established preconception checklists; the Becoming a Parent resource series by the Wisconsin Association for Perinatal Care (\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e) and the FIGO Preconception Checklist(\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e), with contextual modifications for Rwanda. The full English version of the final 32-item questionnaire is provided in Supplementary File 1. Moreover, in developing that tool, additional evidence drawn from broader literature on preconception care, education, and counseling, as well as consultations with reproductive health experts. Furthermore, the instrument was customized to the Rwandan context by excluding items related to: screenings or vaccines that were unavailable locally (such as advanced genetic screenings or non-routine vaccines not part of the national immunization program); tests that were difficult to afford or inaccessible; specialized dietary recommendations for foods not readily available in local markets; and lifestyle modifications requiring resources beyond the reach of typical participants. The was developed in English and translated into Kinyarwanda by an expert translator using a forward-backward translation process with third-party verification, for linguistic and conceptual equivalence. The final instrument was then assessed by a multidisciplinary panel of experts to verify its completeness. Furthermore, a pilot testing with 30 participants was done to ensure the tool's clarity, cultural appropriateness, acceptability, and practical feasibility.\u003c/p\u003e \u003cp\u003eThe questionnaire comprised two sections: (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) socio-demographic characteristics (age, sex, residence, education, occupation, income, religion); (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) yes/no items assessing attitudes and practices related to clinical screenings (e.g., \u0026ldquo;Have you been tested for blood sugar levels?\u0026rdquo;; \u0026ldquo;Have you screened for anemia?\u0026rdquo;), prophylactic measures (e.g., \u0026ldquo;Are you taking folic acid supplements?\u0026rdquo;; \u0026ldquo;Have you received a tetanus vaccination?\u0026rdquo;), reproductive planning (e.g., \u0026ldquo;Have you planned the optimal time to conceive?\u0026rdquo;; \u0026ldquo;Have you checked for consanguinity with your partner?\u0026rdquo;), lifestyle behaviors (e.g., \u0026ldquo;Do you engage in regular physical exercise?\u0026rdquo;; \u0026ldquo;Do you consume alcohol?\u0026rdquo;), environmental exposures (e.g., \u0026ldquo;Do you take measures to avoid toxic environmental exposures?\u0026rdquo;), and protective actions (e.g., \u0026ldquo;Do you use measures to prevent unintended pregnancy?\u0026rdquo;; \u0026ldquo;Do you have measures in place to manage stress?\u0026rdquo;; \u0026ldquo;Do you protect yourself against gender-based violence?\u0026rdquo;).\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eData quality control, Validity, and Reliability\u003c/h2\u003e \u003cp\u003eData quality was maintained through rigorous supervision and monitoring throughout the study. Ten trained midwives, overseen by two public health specialists, conducted daily reviews of all entries for completeness, consistency, and accuracy, with incomplete or inconsistent records immediately flagged and excluded. Real-time data entry via Kobo Toolbox with automated scoring minimized transcription errors and enabled instant quality verification. Data were securely stored with regular backups, and comprehensive cleaning in SPSS version 29 addressed outliers, duplicates, and errors before analysis.\u003c/p\u003e \u003cp\u003eValidity and reliability of the instrument were established through multiple strategies. Content validity was confirmed by a multidisciplinary expert panel, while construct validity was ensured by adapting the tool from two internationally recognized instruments the Becoming a Parent Preconception Checklist and the FIGO Preconception Health Assessment Tool. Forward-backward translation into Kinyarwanda with expert verification established cultural and linguistic validity, and pilot testing with 30 (10percent) participants confirmed face validity. Reliability was maintained through standardized training of all ten data collectors in uniform interview techniques and questionnaire administration, ensuring consistency across sites. Using the same 32-item questionnaire at both time points enhanced test-retest reliability, while gender-matched private interviews promoted honest responses. The automated Kobo Toolbox scoring system eliminated scorer variability and ensured consistent calculation of preparedness scores, strengthening internal consistency.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eData Collection Procedure\u003c/h3\u003e\n\u003cp\u003eTen trained and Bachelor\u0026rsquo;s midwives, supervised by two public health specialists, administered face-to-face interviews using Kobo Toolbox on tablets. Interviews were conducted in private, gender-matched settings to ensure confidentiality and encourage candid responses. Signed informed consent was obtained from all participants, and unique coded identifiers were assigned. The same structured 32-item questionnaire was used for both baseline and post-assessments. Baseline assessments were performed at premarital registration sites. Post-assessments were conducted in the last two weeks before marriage, during final premarital sessions at the registration sites or by telephone for absent participants. Upon completion of the questionnaire, each individual's responses were scored immediately using the automated features of Kobo Toolbox, providing real-time calculation of preparedness levels.\u003c/p\u003e\n\u003ch3\u003eIntervention: Focused Preconception Education and Counseling (FPEC)\u003c/h3\u003e\n\u003cp\u003eImmediately after baseline assessment, couples in the intervention group received a single 45-minute interactive group and couple-based education session delivered by trained midwives in private settings at the premarital sites. The session was structured in three phases to ensure comprehensive coverage of preconception health topics. The first phase involved introduction and rapport building (5\u0026ndash;7 minutes), during which trained midwives welcomed couples, explained the purpose of preconception health\u003c/p\u003e \u003cp\u003eThe second phase consisted of core education and discussion (30\u0026ndash;33 minutes) covering essential preconception topics. These included fertility factors (e.g., calculating fertile days and age-related fertility changes); nutrition and supplementation (e.g., daily folic acid intake and iron-rich foods); vaccinations and screenings (e.g., tetanus immunization and testing for anemia and blood sugar,); substance use risks (e.g., alcohol and tobacco effects on fetal development); stress management and mental health strategies (e.g., relaxation techniques and good sleep patterns); gender-based violence prevention (e.g., recognizing warning signs); and safe environments and reproductive health access (e.g., reducing exposure to pesticides and indoor smoke and locating nearby clinics). The final phase involved summary and reinforcement (5\u0026ndash;7 minutes), during which key messages were recapped, couples' questions were addressed, and printed handouts summarizing the content were provided for home review. No incentives were offered to participants.\u003c/p\u003e \u003cp\u003eCouples in the control group received only the usual premarital counseling delivered by religious officers or local administration officers. This standard counseling focused on faith, conflict resolution, financial management, and general parenthood but included no education on preconception preparation.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eData Management\u003c/h2\u003e \u003cp\u003eData quality was rigorously maintained through daily supervision. Supervisors reviewed all entries on the day of collection for completeness, consistency, and logical accuracy. Incomplete or inconsistent records were flagged and excluded to preserve analytical integrity.\u003c/p\u003e \u003cp\u003eReal-time data from Kobo Toolbox were securely stored on the server with periodic backups. At the conclusion of fieldwork, data were exported to Microsoft Excel for preliminary review and subsequently imported into SPSS version 29 for comprehensive cleaning. This process included identification and correction of outliers, duplicate entries, and typographical errors.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eOutcome Measurement\u003c/h2\u003e \u003cp\u003eConception preparedness was operationalized as a composite score derived from the 32 yes/no questionnaire items. Each item was scored dichotomously (yes\u0026thinsp;=\u0026thinsp;1 point for preparedness or positive practice; no\u0026thinsp;=\u0026thinsp;0 points), yielding an individual raw score ranging from 0 to 32 (maximum 32 points per participant). To reflect the couple-based nature of preconception health, individual scores were summed to create a couple-level raw score (maximum 64 points). For ease of interpretation and comparison, these couple-level raw scores were normalized to a percentage scale (0\u0026ndash;100%), where higher percentages indicated greater preparedness. This approach allowed assessment of both individual contributions and joint couple readiness while facilitating statistical analysis of pre-post changes and group differences.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eData Analysis\u003c/h2\u003e \u003cp\u003eParticipant characteristics and preparedness scores were summarized using descriptive statistics, including frequencies and percentages for categorical variables and means with standard deviations for continuous variables. Normality of continuous variables was assessed with the Shapiro-Wilk and Kolmogorov-Smirnov tests.\u003c/p\u003e \u003cp\u003eThe primary outcome, change in conception preparedness scores was analyzed using difference-in-differences (DiD) t-tests and paired t-tests to examine pre-to-post improvements within each group. Multivariable linear regression was used to quantify the association between group assignment and post-test preparedness scores. Results included 95% confidence intervals, and statistical significance was set at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05. All analyses were performed in SPSS version 29.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eEthical Considerations\u003c/h2\u003e \u003cp\u003e The study was approved by the Institutional Review Board of the University of Rwanda College of Medicine and Health Sciences (Approval No. 337/CMHS-IRB/2024). Permissions were obtained from local authorities and church leaders. Written informed consent was obtained from all participants after explaining study objectives, procedures, risks, and benefits. Participation was voluntary, with the right to withdraw at any time without consequence. Confidentiality was maintained through coded identifiers, secure data storage, and private interviews.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eThis study evaluated the effectiveness of focused preconception education and counseling (FPEC) on conception preparedness among soon-to-be-married couples using a pre-post-test design. Following data entry and cleaning, 600 couples (300 intervention group, 300 control group) were included in the analysis. Data from 32 couples who dropped out during follow-up were excluded.\u003c/p\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eSocio-demographic characteristics of respondents\u003c/h2\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\u003eDistribution of Socio-demographic characteristics among participants\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\"\u003e \u003cp\u003eSocio-demographic characteristic of participants\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eItems\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFrequency(n)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePercentage (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eSex\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e600\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e50.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e600\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e50.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003cb\u003eAge (in years and category)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21\u0026ndash;30 years old\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e776\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e64.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31\u0026ndash;40 years old\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e346\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e41\u0026thinsp;\u0026gt;\u0026thinsp;years old\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026micro;\u0026thinsp;=\u0026thinsp;29.5. SD\u0026thinsp;=\u0026thinsp;\u0026plusmn;\u0026thinsp;5.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMaximum\u0026thinsp;=\u0026thinsp;45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMinimum age\u0026thinsp;=\u0026thinsp;21\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e\u003cb\u003eEducation level\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNon-literate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrimary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e550\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e45.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSecondary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e416\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e34.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTVET\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUniversity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e103\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e\u003cb\u003eOccupation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCultivator/Farmer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e499\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e41.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrivate sector servant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e174\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePublic sector\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSelf-employed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e213\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNot employed/student\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e199\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003e\u003cb\u003eReligion\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAdventist\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCatholic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e670\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e55.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMuslim\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e119\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eProtestant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e227\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eChurchless\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eHabitation\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e978\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e81.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUrban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e222\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eMonthly income status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFrom 200 000Rwf (\u003cspan\u003e$\u003c/span\u003e137 USD) and \u0026lt;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e726\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e60.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAbove 200 000Rwf (\u003cspan\u003e$\u003c/span\u003e137 USD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e474\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e39.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003cb\u003eNotes\u003c/b\u003e: Individuals aged 21 to 35 are categorized as \"Young age,\" while those over 35 are considered \"Advanced age.\" Education below the secondary school level is labeled as \"low educated,\" whereas education ranging from secondary school to university level is referred to as \"high educated.\" VET stands for Technical and Vocational Education and Training.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e​Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e illustrates the distribution of socio-demographic characteristics among the participants in this study.​ The gender breakdown demonstrates an equal representation, with males and females each constituting 50% of the sample. The majority of participants (64.7%) fall within the age range of 21 to 30 years, resulting in an overall mean age of 29.5 years, with a standard deviation of \u0026plusmn;\u0026thinsp;5.5. A significant portion of the participants (45.8%) has attained only a primary education level, while 41.6% are engaged in agricultural work. Catholicism is the most prevalent religion, representing over half (55.8%) of the sample, and a considerable majority of participants (81.5%) reside in rural areas. Finally, the findings indicate that more than 60.5% of the participants earn a monthly income of 200,000 Rwandan Francs (approximately \u003cspan\u003e$\u003c/span\u003e137 USD or less.\u003c/p\u003e \u003cp\u003e \u003cb\u003eDistribution of Conception Preparedness Attitudes and Practices by Sex at Pretest and Post-test among Control and Intervention Groups\u003c/b\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\u003eSex-Disaggregated Changes in Conception Preparedness Practices from Pretest to Post-test in Intervention and Control Groups\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCP items\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePretest Male/Female for IG (n, %)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePost-test Male/Female for IG (n, %)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ePretest Male/Female for CG (n, %)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePost-test Male/Female for CG (n, %)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePost-test change Male/Female for IG\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePost-test change Male/Female for CG\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTested for blood sugar\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 (2.7) / 14 (4.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36 (12.0) / 130 (43.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7 (2.3) / 11 (3.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9 (3.0) / 21 (7.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+\u0026thinsp;9.3 / +38.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.7 / 3.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTested for high blood pressure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12 (4.0) / 19 (6.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48 (16.0) / 165 (55.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13 (4.3) / 21 (7.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13 (4.3) / 22 (7.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+\u0026thinsp;12.0 / +48.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.0 / 0.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAsked /checked for family genetic predisposition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (0.3) / 3 (1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22 (7.3) / 87 (29.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (0.7) / 4 (1.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2 (0.7) / 4 (1.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+\u0026thinsp;7.0 / +28.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.0 / 0.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eScreened for anemia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (2.0) / 9 (3.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41 (13.7) / 153 (51.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 (1.3) / 8 (2.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4 (1.3) / 9 (3.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+\u0026thinsp;11.7 / +48.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.0 / 0.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChecked/control BMI and Weight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 (2.7) / 13 (4.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e35 (11.7) / 122 (40.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9 (3.0) / 14 (4.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9 (3.0) / 16 (5.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+\u0026thinsp;9.0 / +36.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.0 / 0.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eScreened for syphilis, other STIs/ UTIs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (1.3) / 6 (2.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21 (7.0) / 75 (25.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 (1.3) / 8 (2.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4 (1.3) / 8 (2.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+\u0026thinsp;5.7 / +23.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.0 / 0.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePay attention/Avoid teratogenic medication\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e63 (21.0) / 95 (31.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e83 (27.7) / 177 (59.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e64 (21.3) / 96 (32.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e75 (25.0) / 144 (48.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+\u0026thinsp;6.7 / +27.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.7 / 16.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eScreened for HIV/AIDS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 (1.7) / 9 (3.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24 (8.0) / 86 (28.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6 (2.0) / 10 (3.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6 (2.0) / 12 (4.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+\u0026thinsp;6.3 / +25.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.0 / 0.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eScreened for / vaccinated for Hepatitis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (0.3) / 3 (1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (3.0) / 39 (13.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (0.7) / 3 (1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1 (0.3) / 4 (1.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+\u0026thinsp;2.7 / +12.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.3 / 0.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWent for Tetanus vaccine shot\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNA / 17 (5.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNA / 118 (39.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNA / 18 (6.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNA / 20 (6.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNA / +33.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNA / 0.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTested for Blood type and Rh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (0.7) / 3 (1.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e40 (13.3) / 158 (52.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (1.0) / 6 (2.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3 (1.0) / 10 (3.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+\u0026thinsp;12.7 / +51.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.0 / 1.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTook folic acid /vitamins supplements\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20 (6.7) / 32 (10.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38 (12.7) / 106 (35.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24 (8.0) / 36 (12.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e25 (8.3) / 43 (14.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+\u0026thinsp;6.0 / +24.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.3 / 2.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAssessed \u0026amp; planed the convenient time to conceive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9 (3.0) / 15 (5.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42 (14.0) / 151 (50.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8 (2.7) / 12 (4.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8 (2.7) / 14 (4.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+\u0026thinsp;11.0 / +45.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.0 / 0.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStarted/calculate fertile days\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (1.0) / 5 (1.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12 (4.0) / 45 (15.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 (1.3) / 6 (2.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3 (1.0) / 7 (2.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+\u0026thinsp;3.0 / +13.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-0.3 / 0.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMade a plan of number of children\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e49 (16.3) / 75 (25.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e73 (24.3) / 173 (57.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e52 (17.3) / 79 (26.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e52 (17.3) / 83 (27.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+\u0026thinsp;8.0 / +32.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.0 / 1.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTake/strive for balanced diet\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e40 (13.3) / 61 (20.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e44 (14.7) / 79 (26.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e42 (14.0) / 64 (21.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e36 (12.0) / 68 (22.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+\u0026thinsp;1.3 / +6.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-2.0 / 1.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSet measures to protect against unintended pregnancy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20 (6.7) / 31 (10.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38 (12.7) / 106 (35.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19 (6.3) / 29 (9.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13 (4.3) / 26 (8.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+\u0026thinsp;6.0 / +25.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-2.0 / -1.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProtect and set measures to protect self against STIs other than HIV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e44 (14.7) / 66 (22.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (0.7) / 4 (1.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e40 (13.3) / 60 (20.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e35 (11.7) / 65 (21.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+-14.0 / +-20.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-1.7 / 1.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProtect and set measures to protect self against HIV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e74 (24.7) / 113 (37.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e87 (29.0) / 165 (55.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e69 (23.0) / 105 (35.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e70 (23.3) / 110 (36.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+\u0026thinsp;4.3 / +17.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.3 / 1.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoke tobacco\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (2.0) / 9 (3.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (0.7) / 6 (2.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6 (2.0) / 11 (3.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6 (2.0) / 13 (4.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+-1.3 / +-1.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.0 / 0.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTake alcohol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36 (12.0) / 55 (18.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12 (4.0) / 23 (7.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38 (12.7) / 58 (19.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e38 (12.7) / 60 (20.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+-8.0 / +-10.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.0 / 0.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTake much caffeine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (0.7) / 4 (1.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (0.7) / 5 (1.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 (1.3) / 6 (2.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5 (1.7) / 12 (4.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+\u0026thinsp;0.0 / +0.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.3 / 2.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUse illicit drugs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 (0.7) / 5 (1.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (0.7) / 7 (2.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (0.7) / 5 (1.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2 (0.7) / 7 (2.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+\u0026thinsp;0.0 / +0.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.0 / 0.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUse non-prescribed medicines\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e37 (12.3) / 56 (18.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13 (4.3) / 26 (8.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e40 (13.3) / 60 (20.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e43 (14.3) / 76 (25.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+-8.0 / +-10.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.0 / 5.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUse herbal drugs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e32 (10.7) / 48 (16.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8 (2.7) / 16 (5.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30 (10.0) / 45 (15.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e30 (10.0) / 48 (16.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+-8.0 / +-10.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.0 / 1.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePractice physical exercise\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e62 (20.7) / 95 (31.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e54 (18.0) / 102 (34.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e46 (15.3) / 70 (23.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e37 (12.3) / 69 (23.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+-2.7 / +2.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-3.0 / -0.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEstablished measures to avoid and manage stress\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e39 (13.0) / 59 (19.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52 (17.3) / 111 (37.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32 (10.7) / 48 (16.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e25 (8.3) / 49 (16.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+\u0026thinsp;4.3 / +17.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-2.3 / 0.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdopt good sleep patterns and avoid sleep disturbances\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e55 (18.3) / 84 (28.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e62 (20.7) / 112 (37.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e48 (16.0) / 73 (24.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e39 (13.0) / 74 (24.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+\u0026thinsp;2.3 / +9.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-3.0 / 0.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProtect-self against toxic environment exposure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16 (5.3) / 25 (8.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30 (10.0) / 82 (27.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15 (5.0) / 24 (8.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e12 (4.0) / 24 (8.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+\u0026thinsp;4.7 / +19.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e-1.0 / 0.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWent to seek fertility checkup/advice at health facility\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (1.3) / 6 (2.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18 (6.0) / 63 (21.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (0.7) / 5 (1.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2 (0.7) / 9 (3.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+\u0026thinsp;4.7 / +19.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.0 / 1.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChecked consanguinity relationship with the partner\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (2.0) / 10 (3.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e38 (12.7) / 140 (46.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3 (1.0) / 6 (2.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4 (1.3) / 11 (3.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+\u0026thinsp;10.7 / +43.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.3 / 1.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProtect-self/partner against GBV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e98 (32.7) / 148 (49.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e103 (34.3) / 169 (56.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e103 (34.3) / 155 (51.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e107 (35.7) / 173 (57.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+\u0026thinsp;1.7 / +7.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.3 / 6.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAs described in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, at baseline, males and females from both intervention and control groups exhibited low engagement in preconception preparedness practices, with most screening and preventive behaviors practiced by fewer than 10% of participants. Following intervention, dramatic improvements were observed in clinical screening behaviors among intervention participants: blood pressure testing increased by 48.7 percentage points for females and 12.0 points for males; anemia screening rose by 48.0 and 11.7 points respectively; and blood type/Rh testing increased by 51.7 and 12.7 points. Infectious disease screening showed similar patterns, with HIV testing increasing by 25.7 points for intervention females and 6.3 points for males, while syphilis/STI screening rose by 23.0 and 5.7 points respectively. Reproductive planning behaviors improved substantially, with conception timing assessment increasing by 45.3 points for intervention females and 11.0 points for males. In stark contrast, control group participants of both sexes showed a very low changes across these same measures (typically 0\u0026ndash;3 percentage points).\u003c/p\u003e \u003cp\u003ePronounced and consistent gender differences emerged throughout the findings, with intervention females demonstrating approximately four-fold greater behavior change than intervention males across virtually all domains despite similar baseline levels. This pattern persisted across diverse screening tests. Reproductive planning reveals the largest absolute gender disparities: half of intervention females engaged in conception timing planning compared to only one-seventh of males, and 21% of intervention females sought fertility consultation compared to 6% of males. However, risk behavior reduction showed notable gender convergence, with alcohol consumption decreasing by 10.7 points for intervention females and 8.0 points for males, and herbal drug use declining by 10.7 and 8.0 points respectively representing similar gender effects (1.3-fold differences) rather than the four-fold disparities seen in screening behaviors.\u003c/p\u003e \u003cp\u003eThe intervention successfully promoted comprehensive preconception health preparation spanning clinical, behavioral, nutritional, and psychosocial domains. Folic acid supplementation increased by 24.7 percentage points among intervention females compared to 2.3 points in controls. Genetic counseling and consanguinity checking, virtually non-existent at baseline (0.3-1.0%), increased to 7.3\u0026ndash;29.0% and 12.7\u0026ndash;46.7% respectively in intervention participants while remaining unchanged in controls. Stress management improved by 17.3 points for intervention females versus 0.3 points for controls, and protection against toxic environmental exposures increased by 19.0 points versus no change. Furthermore, results show that there is a persistent gender disparity with intervention females consistently achieving 40\u0026ndash;55% screening rates while males reached only 12\u0026ndash;16%.\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\u003eDistribution of CP Attitudes and Practices Between Intervention and Control Groups at Pre- and Post-Intervention (Yes Responses, n [%], Males+Females)\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\u003ePreparedness Item\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIntervention Group\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eControl Group\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eOverall Post intervention change (Increase/Decrease)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePretest / Post test, n, %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePretest / Post test, n, %\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIntervention group/ Control group, %\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTested for blood sugar\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22 (7.3) / 166 (55.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18 (6.0) / 30 (10.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u0026thinsp;48.0 / +4.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTested for high blood pressure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31 (10.3) / 213 (71.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34 (11.3) / 35 (11.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u0026thinsp;60.7 / +0.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAsked /checked for family genetic predisposition\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (1.3) / 109 (36.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (2.0) / 6 (2.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u0026thinsp;35.0 / 0.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eScreened for anemia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15 (5.0) / 194 (64.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12 (4.0) / 13 (4.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u0026thinsp;59.7 / +0.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChecked/control BMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e21 (7.0) / 157 (52.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23 (7.7) / 25 (8.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u0026thinsp;45.3 / +0.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eScreened for syphilis, other STIs/ UTIs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 (3.3) / 96 (32.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12 (4.0) / 12 (4.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u0026thinsp;28.7 / 0.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePay attention/Avoid teratogenic medication\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e158 (52.7) / 260 (86.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e160 (53.3) / 219 (73.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u0026thinsp;34.0 / +19.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eScreened for HIV/AIDS\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14 (4.7) / 110 (36.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16 (5.3) / 18 (6.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u0026thinsp;32.0/ +0.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eScreened for / vaccinated for Hepatitis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 (1.3) / 48 (16.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (1.7) / 5 (1.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u0026thinsp;14.7/ 0.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWent for Tetanus vaccine shot\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e27 (9.0) / 153 (51.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30 (10.0) / 32 (10.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u0026thinsp;42.0 / +0.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTested for Blood type and Rh factor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 (1.7) / 198 (66.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (3.0) / 13 (4.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u0026thinsp;64.3 / +1.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTook folic acid and other vitamins supplements\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e52 (17.3) / 144 (48.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e60 (20.0) / 68 (22.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u0026thinsp;30.7 / +2.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAssessed \u0026amp; planed the convenient time to conceive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24 (8.0) / 193 (64.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20 (6.7) / 22 (7.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u0026thinsp;56.3 / +0.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStarted/calculate fertile days\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 (2.7) / 57 (19.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (3.3) / 10 (3.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u0026thinsp;16.3/ 0.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMade a plan of number of children\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e124 (41.3) / 246 (82.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e131 (43.7) / 135 (45.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u0026thinsp;40.7/ +1.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTake/strive for balanced diet\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e101 (33.7) / 123 (41.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e106 (35.3) / 104 (34.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u0026thinsp;7.3/ \u0026minus;0.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSet measures to protect against unintended pregnancy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e51 (17.0) / 144 (48.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48 (16.0) / 39 (13.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u0026thinsp;31.0 / \u0026minus;3.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProtect and set measures to protect self against STIs other than HIV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e110 (36.7) / 6 (2.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100 (33.3)/ 100 (33.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;34.7 / 0.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProtect and set measures to protect self against HIV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e187 (62.3) / 252 (84.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e174 (58.0) / 180 (60.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u0026thinsp;21.7 / +2.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSmoke tobacco\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15 (5.0) / 8 (2.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17 (5.7) / 19 (6.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;2.3/ +0.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeavy alcohol drinking\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e91 (30.3) / 35 (11.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e96 (32.0) / 98 (32.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;18.6 / +0.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTake caffeine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (2.0) / 7 (2.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e10 (3.3) / 17 (5.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u0026thinsp;0.3/ +2.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUse drugs or caffeine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (2.3) / 9 (3.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (2.3) / 9 (3.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u0026thinsp;0.7/ +0.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUse non-prescribed medicines\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e93 (31.0) / 39 (13.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100 (33.3) / 119 (39.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;18.0 / +6.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUse herbal drugs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e80 (26.7) / 24 (8.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e75 (25.0) / 78 (26.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;18.7/ +1.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAdopt physical activity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e157 (52.3) / 156 (52.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e116 (38.7) / 106 (35.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026minus;0.3/ \u0026minus;3.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEstablished measures to avoid and manage stress (at home, job)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e98 (32.7) / 163 (54.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e80 (26.7) / 74 (24.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u0026thinsp;21.6/ \u0026minus;2.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGood sleep patterns and avoid sleep disturbances\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e139 (46.3) / 174 (58.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e121 (40.3) / 113 (37.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u0026thinsp;11.7 / \u0026minus;2.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProtect-self against toxic environment exposure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e41 (13.7) / 112 (37.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e39 (13.0) / 36 (12.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u0026thinsp;23.6/ \u0026minus;1.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWent to seek fertility checkup/advice at health facility\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 (3.3) / 81 (27.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (2.3) / 11 (3.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u0026thinsp;23.7 / +1.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChecked consanguinity relationship with the partner\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16 (5.3) / 178 (59.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9 (3.0) / 15 (5.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u0026thinsp;54.0 / +2.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProtect-self/partner against GBV\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e246 (82.0) / 272 (90.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e258 (86.0) / 280 (93.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e+\u0026thinsp;8.7 / +7.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eNote:\u003c/p\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;number of those who responded \u0026lsquo;Yes\u0026rdquo; (males and females combined) at each item\u003c/p\u003e \u003cp\u003eTotal sample: 600 participants in intervention group (300 males, 300 females)\u003c/p\u003e \u003cp\u003e% = percentage of participants within group (intervention or control). Means % was calculated based on 300 participants in each group\u003c/p\u003e \u003cp\u003eOverall post-intervention change\u0026thinsp;=\u0026thinsp;the absolute percentage point increase or decrease from pre-test to post-test.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e3\u003c/span\u003e demonstrates the substantial effectiveness of the focused preconception education and counseling (FPEC) intervention in promoting conception preparedness screening attitudes and practices among premarital and soon-to-be-married couples in Rwanda. The most striking improvements occurred in blood type and Rh factor testing (+\u0026thinsp;64.3%), blood pressure screening (+\u0026thinsp;60.7%), anemia screening (+\u0026thinsp;59.7%), and blood sugar testing (+\u0026thinsp;48.0%), all showing dramatic increases compared to minimal changes in the control group. Additional screening behaviors also improved significantly, including HIV/AIDS screening (+\u0026thinsp;32.0%), syphilis and STI/UTI screening (+\u0026thinsp;28.7%), hepatitis screening (+\u0026thinsp;14.7%), family genetic predisposition checking (+\u0026thinsp;35.0%), and BMI monitoring (+\u0026thinsp;45.3%). The intervention also enhanced family planning practices: planning conception timing (+\u0026thinsp;56.3%), checking consanguinity with partners (+\u0026thinsp;54.0%), making plans about desired number of children (+\u0026thinsp;40.7%), calculating fertile days (+\u0026thinsp;16.3%), and seeking fertility checkups (+\u0026thinsp;23.7%). These comprehensive improvements across multiple screening domains indicate that the FPEC program successfully raised awareness among couples about the importance of clinical assessments before conception and improved their utilization of healthcare services as part of conception preparedness.\u003c/p\u003e \u003cp\u003eConcerning prophylactic treatments and preventive medical interventions for conception preparedness, the FPEC intervention achieved notable success among premarital couples. Tetanus vaccination increased by 42.0% in the intervention group compared to virtually no change in controls (+\u0026thinsp;0.7%). Folic acid and vitamin supplementation improved by 30.7% versus only 2.7% in controls, rising from 17.3% to 48.0% of participants. Attention to avoiding teratogenic medications increased by 34.0%, though the control group also showed improvement (+\u0026thinsp;19.7%), possibly reflecting broader community awareness in Rwanda. Hepatitis vaccination showed more modest gains (+\u0026thinsp;14.7%) from a very low baseline, suggesting this may be a less accessible service. These findings demonstrate strong effectiveness in promoting prophylactic treatments, particularly for immunizations and supplementation that couples could readily access as part of their conception preparedness and marriage preparation.\u003c/p\u003e \u003cp\u003eRegarding behavioral and lifestyle modifications related to conception preparedness, the FPEC intervention demonstrated mixed results. The program achieved notable success in substance use reduction: heavy alcohol consumption decreased by 18.6% while increasing in controls (+\u0026thinsp;0.7%), non-prescribed medicine use decreased by 18.0% versus increasing by 6.4% in controls, and herbal drug use declined by 18.7% compared to a 1.0% increase in controls. Tobacco smoking decreased slightly (2.3%) while increasing in controls (+\u0026thinsp;0.6%). The intervention also improved stress management (+\u0026thinsp;21.6%), sleep patterns (+\u0026thinsp;11.7%), protection against unintended pregnancy (+\u0026thinsp;31.0%), environmental toxin exposure protection (+\u0026thinsp;23.6%), and HIV protection measures (+\u0026thinsp;21.7%). However, certain lifestyle modifications proved resistant to change: physical activity declined slightly in both groups, balanced diet improved by only 7.3%, and caffeine and drug use remained stable at low levels. One concerning finding was that protection against STIs other than HIV decreased by 34.7% in the intervention group while remaining stable in controls, possibly reflecting changes in risk perception among couples approaching marriage who may view monogamy as sufficient protection.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e illustrates the trends in attitudes and practices related to preconception care (CP) in the intervention and control groups at baseline and follow-up assessments. The figure clearly demonstrates the substantial effectiveness of the Family Planning and Preconception Education (FPEC) intervention in enhancing conception preparedness across all performance levels.\u003c/p\u003e \u003cp\u003eThe intervention group exhibited marked improvements from baseline to follow-up: minimum scores rose from 15.6 to 34.4 (+\u0026thinsp;18.8 points), mean scores increased from 35.3 to 58.3 (+\u0026thinsp;23.0 points), and maximum scores surged from 50.0 to 81.3 (+\u0026thinsp;31.3 points). In contrast, the control group showed minimal changes: minimum scores increased slightly from 18.8 to 31.3, mean scores rose marginally from 38.2 to 41.7, and maximum scores remained nearly unchanged at approximately 53.\u003c/p\u003e \u003cp\u003eAt follow-up, a wide gap emerged between the groups, with a 16.6-point difference in mean scores and a 28.7-point difference in maximum scores.\u003c/p\u003e \u003cp\u003e \u003cb\u003eTable.4. Pre and Post scores and means differences amidst intervention and control group\u003c/b\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003ePre- and Post-Intervention Scores and means differences between Control and Intervention Groups\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003epresents the results of a difference-in-differences (DiD) analysis comparing conception preparedness attitudes and practices scores between the intervention and control groups at baseline and follow-up.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGroup\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAssessment Time\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eMin. Score\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMax. Score\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAvg Score\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eChange in Average Score\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eMean Square\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eF-test\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003ep-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eControl Group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePre-Test\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e53.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e38.2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e262.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e.18\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePost-Test\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e31.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e52.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e41.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+\u0026thinsp;3.5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e248.7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eIntervention Group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePre-Test\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15.6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e50.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e35.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u0026mdash;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e174.1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePost-Test\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e81.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e58.3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e+\u0026thinsp;23.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e289.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e12.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e.001**\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDiD\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-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e\u003cb\u003e+\u0026thinsp;19.5\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u003cb\u003e315.2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003e270.7\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"9\" nameend=\"c9\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eNote\u003c/b\u003e\u003c/p\u003e \u003cp\u003e\u0026bull; Min Score / Max Score / Avg Score: Minimum, maximum, and average scores for each group at each time point.\u003c/p\u003e \u003cp\u003e\u0026bull; Avg Score: Change in average score from pre-test to post-test.\u003c/p\u003e \u003cp\u003e\u0026bull; Mean Square: Variance estimate used in the F-test calculation.\u003c/p\u003e \u003cp\u003e\u0026bull; F-Test: Test statistic indicating whether the change is statistically significant.\u003c/p\u003e \u003cp\u003e\u0026bull; p-value: Probability value indicating significance level.\u003c/p\u003e \u003cp\u003e\u0026bull; DiD: Difference-in-Differences effect, calculated as (Intervention Avg) \u0026minus; (Control Avg).\u003c/p\u003e \u003cp\u003e\u0026bull; p \u0026lt; .05\u0026thinsp;=\u0026thinsp;statistically significant\u003c/p\u003e \u003cp\u003e\u0026bull; p \u0026lt; .01\u0026thinsp;=\u0026thinsp;highly statistically significant (**)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe intervention group showed substantial improvement, with mean scores increasing from 35.3 at baseline to 58.3 at follow-up (+\u0026thinsp;23.0 points; F\u0026thinsp;=\u0026thinsp;12.4, p\u0026thinsp;=\u0026thinsp;0.001), indicating a highly significant effect of the FPEC intervention. In contrast, the control group exhibited only minimal change, with mean scores rising from 38.2 to 41.7 (+\u0026thinsp;3.5 points; F\u0026thinsp;=\u0026thinsp;1.8, p\u0026thinsp;=\u0026thinsp;0.18), which was not statistically significant.\u003c/p\u003e \u003cp\u003eThe DiD analysis, isolating the true intervention effect by accounting for changes in the control group, revealed a net effect of +\u0026thinsp;19.5 points (F\u0026thinsp;=\u0026thinsp;270.7, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). This confirms that the FPEC intervention significantly enhanced conception preparedness attitudes and practices beyond any natural changes over time\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLinear regression analysis\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"9\" nameend=\"c9\" namest=\"c1\"\u003e \u003cp\u003eCoefficients\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e \u003cp\u003eModel\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eUnstandardized Coefficients\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eStandardized Coefficients\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003et\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eSig.\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e \u003cp\u003e95% CI\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eB\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eStd. Error\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBeta\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eLower Bound\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eUpper Bound\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eControl group\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e-\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e17.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.120\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e18.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e21.16\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIntervention\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19.8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e.696\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e.758\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e28.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e.000**\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e18.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e21.10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"9\" nameend=\"c9\" namest=\"c1\"\u003e \u003cp\u003e**p value\u0026thinsp;\u0026lt;\u0026thinsp;0.01 statistical significance\u003c/p\u003e \u003cp\u003eCI=confidence interval\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e4\u003c/span\u003e presents linear regression analysis results examining the effect of group assignment on conception preparedness attitudes and practices scores. The control group demonstrated a significant baseline score (OR\u0026thinsp;=\u0026thinsp;19.0, 95% CI [18.43, 21.16], p \u0026lt; .001), while the intervention group showed substantially higher scores, being 19.8 times more likely to achieve improved conception preparedness compared to the control group (OR\u0026thinsp;=\u0026thinsp;19.8, 95% CI [18.50, 21.10], p \u0026lt; .001). This finding confirms that couples who received the FPEC intervention were nearly 20 times more likely to demonstrate enhanced conception preparedness attitudes and practices compared to couples who did not receive the intervention.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe purpose of this study was to evaluate the effectiveness of focused preconception education and counseling (FPEC) on conception preparedness attitudes and practices among premarital and soon-to-be-married couples in Rwanda. Using a quasi-experimental pre-post-test design, the study examined whether a couple-based educational intervention could improve conception preparedness behaviors in a context where couples must self-finance all services and navigate healthcare systems independently without integrated preconception care programs.\u003c/p\u003e \u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003eOverall FPEC intervention effectiveness\u003c/h2\u003e \u003cp\u003e In overall, the FPEC intervention in our study demonstrated substantial effectiveness in improving conception preparedness attitudes and practices across multiple domains among participants. We found intervention group participants\u0026rsquo; scores rose by 23 points compared to only 3.5 points in the control group, yielding a significant net difference of 19.5 points. Additionally, we revealed that participants in intervention group were nearly 20 times more likely to achieve higher preparedness scores than controls. Together, these results provide strong evidence that couple-based preconception education significantly improved attitudes and practices, even in the absence of integrated care systems and despite financial constraints. Our findings collaborate with those from a study in Iran that revealed a premarital counseling enhanced conception preparedness positive attitudes and practices among brides and grooms(\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e)\u003c/p\u003e \u003cp\u003eWe revealed that couple-based preconception education and counseling delivered at the premarital period can drive substantial, causally attributable behavior change even in resource-constrained contexts. The intervention's integration with premarital counseling created a uniquely receptive moment, as couples preparing for marriage and parenthood were highly motivated to invest in preparation. Research from Malaysia confirms that preconception interventions during marriage preparation achieve 40% higher uptake than general reproductive-age interventions(\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003eEffect of FPEC on preconception clinical screening uptake\u003c/h2\u003e \u003cp\u003eThe FPEC intervention achieved particularly impressive results in clinical screening behaviors, substantially exceeding outcomes reported in similar studies. For example, Blood type and Rh factor testing increased by 64.3%, blood pressure screening by 60.7%, and anemia screening by 59.7% far surpassing rates from comparable interventions in two studies conducted China(\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e), (\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e) and in Ethiopia(\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e). What might have contributed to these achievements differences is the inclusion of both male and female partners in the FPEC intervention in our study, as some evidences consistently shows that couple-based interventions achieve 35\u0026ndash;42% higher screening completion rates compared to women-only programs through mutual support, pooled resources, and shared accountability (\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e), (\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003eEffect of FPEC on preconception prophylactic treatments and supplementation uptake\u003c/h2\u003e \u003cp\u003eProphylactic treatments and supplementation also showed notable improvements in our study. For example, we found that Tetanus vaccination increased by 42.0%, substantially outperforming the 15\u0026ndash;20% average improvement reported in systematic reviews of similar interventions in low- and middle-income countries(\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e). Folic acid supplementation reached 48.0% of participants (30.7% increase), superior to 11.4% found in Ethiopia(\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e), uptake rate of only 8% after education intervention in the study conducted in Kenya(\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e). On contrast, a systematic review showed preconception folic acid supplementation uptake was 45.2%(\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e) and 72.7% in France (\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e).The substantial increase of prophylactic treatments and supplementation uptake among our participants might have been triggered that we applied the couple-based education and counseling approach, where both partners may understand the importance of preconceptional vitamins and jointly commit to prioritizing and uptake supplementation despite low financial income revealed in majority of our study participants. The evidences from literature supports this mechanism, finding that women are 2.3 times more likely to maintain supplementation when male partners were educated about its importance(\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e),(\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eProphylactic treatments and supplementation showed notable improvements in our study. Tetanus vaccination increased by 42.0%, substantially outperforming the 15\u0026ndash;20% average improvement reported in systematic reviews of similar interventions in low- and middle-income countries(\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e). Folic acid supplementation reached 48.0% of participants (30.7% increase), markedly superior to rates in Ethiopia (11.4%) and Kenya (8%) (\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e), (\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e) where educational interventions targeted women only.\u003c/p\u003e \u003cp\u003eHowever, our findings remained below rates in higher-resource settings, including a systematic review reporting 45.2% uptake(\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e) and France achieving 72.7%(\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e). These disparities may reflect integrated preconception care systems, subsidized or free supplements, and longstanding public health campaigns in developed countries.\u003c/p\u003e \u003cp\u003eThe couple-based education approach used in our study might have contributed to more substantial success compared to similar low-resource contexts that involved only women. Evidence supports this mechanism, showing women are 2.3 times more likely to maintain supplementation when male partners are educated about its importance as when both partners understand the importance of periconceptional vitamin supplements, it stimulates mutual accountability and commitment to prioritizing supplementation and pooling resources toward this goal(\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e) (\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003eEffect of FPEC on Behavioral and lifestyle modifications\u003c/h2\u003e \u003cp\u003eBehavioral and lifestyle modifications related to substance use showed impressive sustained change despite the absence of any follow-up support after the initial education session. For example, we found that heavy alcohol consumption decreased by 18.6%, non-prescribed medicine use by 18.0%, and herbal drug use by 18.7% all substantially exceeding rates from comparable studies in Tanzania (7% reduction) and Uganda reduction) that included multiple counseling sessions (\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e);but the improvement rate was higher in the Netherland study(\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e). Our study findings might be related to that given that 81.5% of the participants resided in rural areas where traditional medicine use is culturally embedded, yet the intervention might have successfully challenged these practices. Additionally, as over the quarter (45.8%) of participants had only primary education, the FPEC might have contributed to improved health literacy even among participants with low education level, triggering behavior and lifestyle change to individuals and couples.\u003c/p\u003e \u003cp\u003eBehavioral and lifestyle modifications related to substance use showed impressive sustained change despite the absence of follow-up support after the initial education session. Heavy alcohol consumption decreased by 18.6%, non-prescribed medicine use by 18.0%, and herbal drug use by 18.7%, substantially exceeding rates from comparable studies in Tanzania (7% reduction) and Uganda (8% reduction) that included multiple counseling sessions(\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e). However, our findings were below those reported in the Netherlands(\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e), likely reflecting differences in baseline health literacy, healthcare access, and socioeconomic resources between settings. In our study, the couple-based approach used may have created mutual accountability that sustained behavior changes, with both partners monitoring and supporting each other without professional oversight. Also, the premarital timing may have enhanced receptivity, as couples preparing for marriage and parenthood are highly motivated to adopt healthier lifestyles as stipulated by the literature(\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e).\u003c/p\u003e \u003cdiv id=\"Sec23\" class=\"Section3\"\u003e \u003ch2\u003eAreas of FPEC limited success among participants\u003c/h2\u003e \u003cp\u003eNevertheless, the FPEC intervention in our study showed some limited success in conception preparedness attitudes and practices uptakes among participants. For example, physical activity increased minimally (0.3%), while balanced diet adoption improved by only 7.3% comparable to studies in Turkey (9%) and the United States (6%) that provided ongoing nutritional counseling and cooking demonstrations(\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e);(\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e). These findings are consistent with the literature, which suggests that education-only interventions generally require supplementary support to achieve meaningful lifestyle behavior change(\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e).That literature indicates that sustained improvements in preconception dietary and physical activity behaviors require multifaceted support, including ongoing resources, environmental modifications, and continuous guidance to couples beyond initial educational interventions(\u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e72\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWe also observed a 34.7% decrease in protection against STIs other than HIV in the intervention group, consistent with findings from studies by Utami et al. and Amizar et al., where premarital counseling increased knowledge without producing significant changes in preconception STI self-protection behaviors(\u003cspan citationid=\"CR73\" class=\"CitationRef\"\u003e73\u003c/span\u003e),(\u003cspan citationid=\"CR74\" class=\"CitationRef\"\u003e74\u003c/span\u003e). Notably, while HIV protection behaviors improved (21.7% increase), protection against other STIs declined. These divergent outcomes may be attributable to participants distinguishing between HIV commonly included in mandatory premarital screening protocols and other STIs that may lack similar institutional requirements or public health emphasis. Furthermore, evidence argue that married or committed couples frequently assume mutual fidelity eliminates STI risk, leading them to discontinue protective practices (\u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e75\u003c/span\u003e),(\u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e76\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003eInfluence of sociodemographic characteristics on study findings\u003c/h2\u003e \u003cp\u003eThe sociodemographic profile of study participants may have significantly influenced intervention outcomes in complex ways.\u003c/p\u003e \u003cp\u003eWith regard to sex, in general we found low baseline preconception preparedness followed by substantial post-intervention improvements in both sexes. Post-intervention, females demonstrated four-fold greater improvements in screening behaviors than males: blood pressure testing increased 48.7% vs. 12.0%, blood type/Rh testing rose 51.7% vs. 12.7%, screening rates reached 40\u0026ndash;55% vs. 12\u0026ndash;16%, and folic acid use increased 24.7% with lower male uptake. Half of females planned conception timing versus only one-seventh of males. These findings represent novel contributions, as limited sub-Saharan African studies have examined men's preconception care utilization(\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e), and evidence for male intervention effectiveness remains limited (\u003cspan citationid=\"CR77\" class=\"CitationRef\"\u003e77\u003c/span\u003e). However, gender convergence appeared in risky behavior reduction, with similar decreases in alcohol (10.7% vs. 8.0%) and herbal drug use, suggesting behavioral cessation interventions work equally well for both sexes. Persistent gaps despite identical interventions indicate that achieving equity requires specially designed male-targeted programs addressing gender norms, and structural barriers as recommended by different researchers(\u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e78\u003c/span\u003e),(\u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e79\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe predominantly young age distribution (64.7% aged 21\u0026ndash;30) may have enhanced intervention receptivity, as research shows young couples transitioning to parenthood demonstrate high motivation to optimize health(\u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e80\u003c/span\u003e). Rural residence (81.5%) may have created dual effects: limiting access to diverse foods and exercise facilities, contributing to minimal improvements in physical activity (0.3%) and balanced diet (7.3%), consistent with literature documenting rural barriers including limited health clinics, limited specialty services, lower health literacy, financial constraints and insufficient transport. However, rural communities may have provided stronger social networks(\u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e81\u003c/span\u003e) that reinforced the 18.7% reduction in culturally embedded herbal drug use. Despite 45.8% having only primary education and 60.5% earning below \u003cspan\u003e$\u003c/span\u003e137 USD monthly, the couple-based approach may have compensated through partner discussion and shared decision-making, potentially improving health literacy more effectively than individual counseling, supported by evidence that interactive couple-based interventions successfully improve health behaviors even among low-education populations(\u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e82\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eEconomic constraints may have created barriers to sustained dietary improvements but appeared overcome for one-time clinical screenings (blood pressure\u0026thinsp;+\u0026thinsp;60.7%, anemia\u0026thinsp;+\u0026thinsp;59.7%, blood type\u0026thinsp;+\u0026thinsp;64.3%) when couples pooled resources, aligning with research showing couple counseling improves health service uptake through shared decision-making and resource pooling as demonstrated in the study from rural KwaZulu-Natal, South Africa (\u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e83\u003c/span\u003e). Religious affiliation (80.6% Christian) may have reinforced intervention messages since religious communities often encourage abstaining from harmful substances (alcohol, drugs, smoking), and as also faith can provide emotional strength thus reducing anxiety and stress(\u003cspan citationid=\"CR84\" class=\"CitationRef\"\u003e84\u003c/span\u003e). Being that there was gender equity (50% male, 50% female) may have transformed preconception preparation into a shared endeavor as evidence indicates partner involvement increases women's likelihood of maintaining preconception care uptake by 2.3 times (\u003cspan citationid=\"CR85\" class=\"CitationRef\"\u003e85\u003c/span\u003e) and mutual support enhances health behavior initiation and maintenance(\u003cspan citationid=\"CR86\" class=\"CitationRef\"\u003e86\u003c/span\u003e).\u003c/p\u003e \u003cdiv id=\"Sec25\" class=\"Section3\"\u003e \u003ch2\u003eImpact of fragmented healthcare system on study findings\u003c/h2\u003e \u003cp\u003eThe absence of an integrated preconception care program in Rwanda's health system may have created substantial barriers to translating knowledge into practice, despite couples' motivation following the FPEC intervention. After receiving education, couples had to independently identify where services were available, make appointments at multiple facilities, arrange transportation, and finance each service separately challenges particularly acute for the 81.5% of participants residing in rural areas where specialized clinics and pharmacies are rare. This fragmentation may explain the wide variation in screening uptake observed in our study.\u003c/p\u003e \u003cp\u003eAccessible, affordable tests available at most health centers and health posts (blood pressure screening, blood type testing, anemia screening) showed dramatic increases (60\u0026ndash;64%), while specialized services requiring referral to higher-level facilities (hepatitis screening) increased by only 14.7%. The lack of a structured pathway meant couples may have faced cumulative navigation complexity across multiple visits without systematic support, coordination, or follow-up. Research in Pakistan demonstrates that even when couples can pay for services, fragmented systems significantly reduce uptake because navigation barriers accumulate across multiple required visits(\u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e87\u003c/span\u003e). The lack of preconception subsidized preconception care packages or health insurance coverage for preventive services, may have created financial barriers. Without subsidized preconception care packages or health insurance coverage for preventive services, couples had to pay out-of-pocket for each screening, vaccination, and supplement. The observed pattern high uptake of essential, affordable services but lower uptake of more expensive specialized screenings may reflect couples' rational prioritization within severe budget constraints. An integrated preconception care program with bundled services at reduced cost could substantially improve uptake across all recommended practices.\u003c/p\u003e \u003cp\u003eThe lack of integration between premarital counseling (typically provided by religious institutions or civil authorities) and healthcare services may have created missed opportunities for seamless referral and follow-up. While our FPEC intervention temporarily bridged this gap, sustainable impact requires institutionalized linkages between marriage preparation programs and health facilities. Countries with successful preconception care programs(\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e), have established formal partnerships between community organizations providing marriage preparation and healthcare systems offering preconception services, creating clear pathways for couples to access comprehensive care. Despite these systemic barriers, the FPEC intervention achieved substantial improvements in conception preparedness attitudes and practices, demonstrating that even single-session couple-based education can produce meaningful behavior change in fragmented healthcare contexts.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec26\" class=\"Section3\"\u003e \u003ch2\u003eStrength and limitations of the study\u003c/h2\u003e \u003cp\u003eOur study evaluating the effectiveness of focused preconception education and counseling among premarital couples in Rwanda has several important strengths and limitations, particularly in a country lacking a comprehensive preconception care program within its national healthcare system. Key strengths include a large, diverse sample of 600 couples from urban and rural areas, ensuring high relevance to the Rwandan population; the inclusion of both men and women, addressing a critical research gap in male involvement in pregnancy preparation; evidence that a feasible, brief single-session intervention delivered during routine premarital counseling can significantly improve conception preparedness even without broader health service support; and its conduct in a predominantly rural, low-income setting with a fragmented healthcare system, demonstrating that targeted education alone can drive meaningful behavior change in resource-constrained environments. However, limitations include the absence of random assignment, potentially introducing selection bias from unobserved group differences; a short three-month follow-up period insufficient for capturing sustained lifestyle changes; reliance on self-reported data susceptible to social desirability bias; and the use of only one brief session, limiting insights into more intensive approaches. While the findings are highly applicable to similar low-resource sub-Saharan African settings with comparable sociocultural and healthcare challenges, generalizability may be restricted to populations such as established couples not seeking premarital counseling, high-income countries with existing preconception infrastructure, or contexts with differing cultural attitudes toward marriage preparation and reproductive health.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study demonstrates that couple-based preconception education and counseling delivered during the premarital period in Rwanda significantly enhances conception preparedness, with intervention participants nearly 20 times more likely to achieve improved attitudes and practices compared to controls.\u003c/p\u003e \u003cp\u003eThe FPEC program proved to be effective in promoting behaviors requiring one-time or short-term decision-making, including uptake of screenings, vaccinations, and reduction of substance use and alcohol consumption. However, behaviors requiring sustained resources and ongoing commitment such as dietary modifications and regular physical activity showed limited improvement, highlighting the need for continued support beyond initial counseling sessions.\u003c/p\u003e \u003cp\u003eThese findings provide compelling evidence for integrating the FPEC program into Rwanda's existing premarital services and broader reproductive, maternal, and child health promotion initiatives, particularly those targeting reproductive-age populations. To maximize the program's impact and sustainability, we recommend establishing a comprehensive national preconception care framework that includes: (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) subsidized or free access to preconception services, (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) coordinated care pathways linking premarital counseling with primary healthcare, (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) structured follow-up support to reinforce sustained behavior change, and (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e) targeted assistance for resource-intensive health behaviors.\u003c/p\u003e \u003cp\u003eFuture research should prioritize longitudinal studies examining the long-term effects of FPEC interventions on maternal, neonatal, and child health outcomes, as well as implementation science studies to identify optimal strategies for scaling and sustaining preconception care programs in low-resource settings including Rwanda.\u003c/p\u003e"},{"header":"Declarations","content":" \u003cp\u003e \u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e \u003cp\u003e The study was conducted in accordance with the ethical principles of the Declaration of Helsinki. Ethical approval was obtained from the Institutional Review Board of the University of Rwanda, College of Medicine and Health Sciences (Approval No. 337/CMHS-IRB/2024). Additional permissions were secured from relevant local authorities and church leaders. Written informed consent was obtained from all participants prior to enrollment, and anonymity was ensured by using identification codes only, without collecting personal identifiers.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent for publication\u003c/strong\u003e \u003cp\u003eNot applicable. No individual person\u0026rsquo;s data (such as medical records, images, videos, or personal details) are included in this article.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eCompeting interests\u003c/h2\u003e \u003cp\u003eThe authors declare that there is no conflict of interest.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThe authors declare that this research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\u003ch2\u003eAuthors' contributions\u003c/h2\u003e \u003cp\u003eRN, OB, TCU and DG contributed to the study conception and design. RN, TCU and OB contributed to data collectors training and data collection. RN, OB, TCU, DG and I-MC contributed to data analysis and interpretation of results. RN, OB, TCU, I-MC, HL and JRL contributed to preparing and drafting the manuscript. All authors reviewed the results and approved the final version of the manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e \u003cp\u003e We extend our sincere gratitude to the midwives who facilitated data collection, the engaged couples who generously participated in this study, and the church leaders and local administrators whose support was instrumental in making this research possible. We are also grateful to the University of Michigan African Presidential Scholars (UMAPS) Program for providing valuable technical guidance and writing assistance throughout this project.\u003c/p\u003e\u003ch2\u003eAvailability of data and materials\u003c/h2\u003e \u003cp\u003eAll data supporting the findings of this study are available within the paper and its Supplementary Information.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eMoller AB, Patten J, Hanson C, Ess\u0026eacute;n B, Jacobsson B (2025) Five decades of advancing global maternal and newborn health and rights: Milestones and initiatives. 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Acta Med Philipp 54(4):373\u0026ndash;386\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"University of Rwanda","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Preconception education, counseling, conception preparedness, premarital couples","lastPublishedDoi":"10.21203/rs.3.rs-8694857/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8694857/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eBackground\u003c/b\u003e\u003c/p\u003e \u003cp\u003eMaternal and neonatal morbidity and mortality remain major public health challenges in sub-Saharan Africa, where modifiable preconception risk factors contribute to approximately 75% of adverse pregnancy outcomes. Preconception education and counseling provide a proactive strategy to optimize health before conception and improve safe pregnancy; however, it is less practiced and underexplored in low-resource settings like Rwanda. This study aimed to pilot and evaluate the effectiveness of focused preconception education and counseling (FPEC) on conception preparedness attitudes and practices among premarital couples in Rwanda.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods\u003c/b\u003e\u003c/p\u003e \u003cp\u003eA quasi-experimental pre-post study was conducted from May to August 2024 involving 600 premarital couples who were systematically assigned to either the intervention group or control group with 300 couples (150 males and 150 females) in each group. Only the intervention group received a single 45-minute group and couple-based FPEC session post-baseline, addressing fertility, screenings, nutrition, supplements, substance use, stress, gender-based violence, and environmental risks, supplemented by refresher handouts. The control group received routine premarital education without preconception content. Conception preparedness was measured using a 32-item questionnaire completed by each individual to assess their personal level of preparedness, with data collected at baseline and three months later. Analysis included descriptive statistics, paired t-tests, difference-in-differences (DiD), and linear regression in SPSS version 29 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e\u003c/p\u003e \u003cp\u003eParticipants were mostly young (64.7% aged 21\u0026ndash;30 years), rural (81.5%), with primary education and low income. Baseline scores showed no group differences. Post-intervention, the intervention group demonstrated marked improvements in screenings (e.g., blood type/Rh\u0026thinsp;+\u0026thinsp;64.3%, anemia\u0026thinsp;+\u0026thinsp;59.7%), prophylactics (folic acid\u0026thinsp;+\u0026thinsp;30.7%, tetanus\u0026thinsp;+\u0026thinsp;42.0%), planning (conception timing\u0026thinsp;+\u0026thinsp;56.3%), and risk reduction (alcohol \u0026minus;\u0026thinsp;18.6%). Mean scores rose from 35.3 to 58.3 (+\u0026thinsp;23.0 points, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01) versus 38.2 to 41.7 in controls (+\u0026thinsp;3.5, non-significant). DiD test confirm a\u0026thinsp;+\u0026thinsp;19.5-point net effect (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001); regression showed nearly 20-fold higher scores in the intervention group (B\u0026thinsp;=\u0026thinsp;19.8, 95% CI: 18.4\u0026ndash;21.1, p\u0026thinsp;\u0026lt;\u0026thinsp;0.01).\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusion\u003c/b\u003e\u003c/p\u003e \u003cp\u003eFPEC significantly enhanced conception preparedness among premarital couples compared to those who did not, supporting its integration into reproductive health, maternal health and premarital programs to promote healthy conception, safe pregnancy and family wellness. Future research should explore long-term outcomes and scalability.\u003c/p\u003e","manuscriptTitle":"Effectiveness of focused preconception education and counseling (FPEC) on conception preparedness among premarital couples: A quasi-experimental pre-post study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-27 10:29:40","doi":"10.21203/rs.3.rs-8694857/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"04483350-7f53-426b-91c5-03d61f453a8a","owner":[],"postedDate":"January 27th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":61722442,"name":"Maternal \u0026 Fetal Medicine"},{"id":61722443,"name":"Sexual \u0026 Reproductive Medicine"},{"id":61722444,"name":"Obstetrics \u0026 Gynecology"}],"tags":[],"updatedAt":"2026-01-27T10:29:40+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-27 10:29:40","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8694857","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8694857","identity":"rs-8694857","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}