Factors Associated with Inadequate Antenatal Contacts at the Yaounde Central Hospital in Cameroon

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Given concerns about adverse births, at least 8 ANC have been recommended since 2016 in resource-limited settings. Methods A cross-sectional study was conducted among women who had delivered within the last 24 hours in Yaounde Central Hospital (YCH), Cameroon, between June 8th and August 7th 2021. Logistic regression was used to determine factors associated with Inadequate ANC (IANC). Analyses were done using Epi Info 7.0. Any P-value < 0.05 was considered statistically significant. Results Of the 200 participants enrolled, the majority (70.5%) had IANC and the mean age was 28.0 ± 6.7 years. Referrals women were more likely to have IANC than non-referrals, with an Adjusted Odds Ratio (AOR) of 5.4 (95% Confidence Interval [CI]: 2.2–12.9; P < 0.001). Likewise, unmarried women were more likely to have IANC than married, with an AOR of 2.5 (95% CI: 1.2–5.4; P < 0.001). Conclusions About 7 out of 10 women who delivered at the YCH had IANC. Accordingly, risk factors for IANC should be monitored throughout pregnancy particularly among young women in Cameroon. Factors Associated Inadequate Antenatal Contacts Yaounde Central Hospital Figures Figure 1 Background Until end-2015, the World Health Organization (WHO) recommended at least 4 Antenatal Contacts (ANC) [ 1 ]. This number of ANC differs from one country to another; 11 in the United States, 10 in Germany and England, 9 in France, 8 in Italy and 4 in Cameroon [ 2 – 3 ]. ANC in developing countries is often of poor quality. The rate of Inadequate ANC (IANC) is fluctuating, depending on the country; 38% in the Central African Republic [ 4 ] and 32% in Kenya [ 5 ]. Since 2016 and based on recent evidences, the WHO recognizes that the 4 ANC model, which was developed in the years 2000, is likely associated with higher perinatal mortality than models that include at least 8 ANC [ 6 ]. Adverse pregnancy outcomes prevention includes ANC, family planning, skilled labor and essential obstetric care [ 7 ]. Nearly 303,000 women died in 2015 from complications related to pregnancy and childbirth [ 8 ]. About 2.6 million children were stillborn in the same year. Almost all maternal (99%) and infant (98%) deaths occurred in low- and middle-income countries. These deaths would have been avoided if the parturients had access to at least 8 ANC [ 9 ]. Sixty percent (60%) of stillbirths (1.46 million) occurred during the prenatal period and were mainly due to untreated maternal infection, hypertension and intrauterine growth retardation [ 10 ]. In Sub-Saharan Africa (SSA), the choice of the number of ANC raises important economic questions, especially where the evaluation of pregnancy and childbirth surveillance remains limited [ 11 ]. In Cameroon, few studies have been carried out to address the issue of IANC [ 12 ]. Consequently, this study aimed at determine factors associated with IANC at the Yaounde Central Hospital (YCY) in Cameroon. Methods Study design This was a cross-sectional study conducted from June 8th to August 07th 2021 at the YCH in Cameroon. Study population Participants enrolled in the study were aged 15 years and over, had delivered in the last 24 hours at the moment of inclusion and had given their informed consent. Sample size : The sample size was calculated using the formula z²p(1-P)/e², where: z refers to 95% confidence interval = 1.96; p refers to proportion of IANC according to WHO recommendations = 17.4% [ 13 ] and e refers to margin of sampling error = 6%. This gave a sample size of 145. The sample size was increased by 5% (8 cases) to allow for incomplete interviews. Hence, the minimum sample size was 153. Sampling Participants were recruited consecutively until the sample size was reached. The total number of participants included in the study was 203. Of those, 3 participants were excluded due to incomplete questionnaires (2 cases) and inappropriate data (1 case) from their patient records (Fig. 1 ). Data collection A face-to-face interview based on a standard questionnaire was done. After obtaining the consent of participants, primary data were completed through this interview while secondary data were completed by extracting information from the patient’s medical records. Variables measurement The dependent variable was IANC. At the moment of delivery, the number of ANC completed was considered either as inadequate (< 8 ANC) or adequate (≥ 8 ANC). Independent variables were related to age, delivery term, parity, referrals, education, marital status, residence, occupation and chronic disease. Data analysis After each data collection day, the principal investigator incorporated data into Epi Info Version 7.0 for analyses. Descriptive statistics were used to assess all variables. Univariate logistic regression was used for categorical independent variables. Multivariate logistic regression was performed by entering all the variables associated with IANC in univariate analysis. Of note, all the variables associated with IANC at P ≤ 0.2 in univariate analysis were also included in the final model. The significance level was considered at 5%. Odds Ratios were calculated with a 95% Confidence Interval (95%CI). Results Descriptive analysis Characteristics of participants are summarized in Table 1 . Almost one-half (47.5%) of the participants were aged between 26 and 36 years. The mean age was 28 years, with a standard deviation of 6.7 years. The majority (79.5%) of women delivered before 40 weeks of amenorrhea. Three-quarter (75.5%) were pauciparous, while 46% were referrals and 62.5% had a secondary education. Moreover, we found that unmarried women (58.0%) were more represented than married (42.0%). Most of the respondents (96.5%) were living in an urban area, while about one-half (54.0%) were not unemployed and one-fifth (19.0%) had a chronic disease. Table 1 Grouped frequency distribution of the variables, Yaounde Central Hospital, June to August 2021 (N = 200) Studied variables Number of participants Percent Age (mean: 28 ± 6.7) 15 to 25 71 35.5 26 to 36 95 47.5 37 to 49 34 17.0 Delivery term ≤ 40 weeks 159 79.5 > 40 weeks 41 20.5 Parity Pauciparous 151 75.5 Multiparous 49 24.5 Referrals No 108 54.0 Yes 92 46.0 Education level Low 14 7.0 Medium 125 62.5 High 61 30.5 Marital status Married 84 42.0 Unmarried 116 58.0 Residence Urban area 193 96.5 Rural area 7 3.5 Occupation Employed 92 46.0 Unemployed 108 54.0 Chronic disease No 162 81.0 Yes 38 19.0 Univariate analysis A summary of the univariate analysis of descriptive data associated with IANC is provided in Table 2 . The risk for IANC was higher among referrals than non-referrals (P < 0.001). Secondary or higher education was significantly associated with IANC than primary education (P < 0.001). Unmarried women were more likely to have IANC compared to those in couple (P < 0.001). There was more risk for IANC among women with chronic disease compared to those without chronic disease (P < 0.001). Table 2 Associations between inadequate antenatal contacts and independent variables (N = 200) Variables IANC* n (%) AANC** n (%) COR*** (95% CI ¶ ) P-value AOR**** (95% CI ¶ ) P-value Age 15 to 25 52 (36.9) 19 (32.2) 1 1 26 to 36 70 (49.6) 25 (42.4) 1.4 (0.7–2.5) 0.381 NA ¶¶ 37 to 49 19 (13.5) 15 (25.4) 0.5 (0.2–1.1) 0.115 0.7 (0.5–1.3) 0.139 Parity Pauciparous 108 (71.6) 43 (72.9) 1 1 Multiparous 33 (23.4) 16 (27.1) 0.9 (0.5–1.9) 0.979 NA ¶¶ NA ¶¶ Referral No 60 (42.6) 48 (81.4) 1 1 Yes 81 (57.4) 11 (18.6) 5.9 (2.8–12.3) < 0.001 5.4 (2.2–12.9) < 0.001 Education Primary 12 (8.5) 2 (3.4) 1 1 Secondary 100 (70.9) 25 (42.4) 3.3 (1.8–6.2) < 0.001 1.2 (0.2–7.4) 0.068 Higher 29 (20.6) 32 (54.2) 0.2 (0.1–0.4) < 0.001 0.3 (0.0-1.8) 0.083 Marital status Married 53 (37.6) 31 (52.5) 1 1 Unmarried 88 (62.4) 28 (47.5) 3.0 (1.6–5.6) < 0.001 2.5 (1.2–5.4) < 0.001 Residence Urban 136 (96.4) 1 1 Rural 5 (3.6) 1.0 (0.2–5.6) 0.713 NA ¶¶ NA ¶¶ Occupation Employed 59 (41.8) 57 (96.6) 1 1 Unemployed 82 (58.2) 2 (3.4) 1.4 (0.8–2.6) 0.357 NA ¶¶ NA ¶¶ Chronic disease No 110 (78.0) 52 (88.1) 1 1 Yes 31 (22.0) 7 (11.9) 9.7 (1.3–73.8) 0.016 3.3 (0.4–28.9) 0.201 *: Inadequate Antenatal Contact; **: Adequate Antenatal Contact; ***: Crude Odds Ratio; ****: Adjusted Odds Ratio; ¶ : Confidence Interval Multivariate analysis Some conclusions based on the univariate analysis described above were not confirmed in this model (Table 2 ). On adjustment for other established risk factors for IANC, those that remained significantly associated with IANC were referrals (AOR = 5.4; 95% CI = 2.2–12.9; p < 0.001) and unmarried (AOR = 2.5; 95% CI = 1.2–5.4; p < 0.001). Discussion The results of this study showed that the majority (70.5%) of participants had IANC. This proportion was higher to that of Mugo et al. (59%) in Myanmar, with a sample size of 2,943, but lower to that of Ekholuenetale et al. (82.6%) in Nigeria, with a sample size of 1,404 [ 14 , 15 ]. Such findings might be explained by our small sample size (200). Like in other Low- and Middle-Income Countries (LMICs), most of the participants included in this study were young adults (21–35 years). There was no association between parity and IANC. This finding corroborates that of Maleya et al. [ 13 ] but differs from those of Baumann and Roth [ 16 ] who recorded that the number of IANC decreases as parity increases [ 17 , 18 ]. Participants in higher education were less likely to have IANC than primary level. In contrast, Ali et al. in a study in Bangladesh (2014) revealed that women in higher education were more likely to have IANC than no education [ 19 ]. Indeed, educated women had a better understanding of risk factors for IANC during interviews. Unmarried women were 3.0 times more likely to have IANC than married. In fact, there was a delay to start ANC among unmarried since pregnancy disclosure to family was limited [ 16 ]. Moreover, not being in couple limited access to IANC, particularly in poor setting [ 20 ]. Other reasons included the lack of support by family or health workers. Chronic disease was positively associated with IANC. This observation confirmed in other publications [ 4 ] showed that taking medications for life increases the risk of having IANC. The final logistic regression model revealed that referrals and unmarried were positively associated with IANC. Therefore, potential confounding factors taken into account might explain why some independent variables were not retained in this model. Such cases included chronic disease, secondary and higher education. These results are similar to that of Maleya et al. in Lubumbashi in 2019 [ 13 ]. Limitations The cross-sectional design of this study limited the evaluation over time of our findings, while the monocentric nature limited the external validity. Conclusions This study revealed a high proportion of IANC, which was positively associated with unmarried and referrals. The monitoring of these risk factors is therefore necessary to prevent adverse births, particularly in resource-limited settings. Declarations Conflict of interest: The authors declare that they have no conflict of interest. Ethics approval and consent to participate: The study proposal was submitted and received approvals from the Institutional Ethics Committee (IEC) of the Faculty of Medicine and Biomedical Sciences (FMBS) (reference number: 219 / 2021 / UY1 / FMSB / VDRC / DAASR / CSD) and the administration of the YCH (reference number: 322 / 2021 / AR / MINSANTE / SG / DHCY / CM / SM). All participants included in this study had given their consent to participate. Consent for publication: Written informed consent for publication of these findings was obtained from the participants. Data availability: The datasets analyzed in this study are available from the corresponding author on reasonable request. Competing interests: The authors declare that they have no competing interests. Funding: No funding was obtained to carry out this study. Authors' contributions: AJNC, MWL and REM designed and implemented the study. AJNC collected the data. AJNC, MWL, CFMN and FGTK analyzed and interpreted the data. AJNC and MWL initiated the manuscript. AJNC, MWL, CFMN and ERM revised the initial version of the manuscript. All authors revised and approved the final version of the manuscript. Acknowledgements: The authors are grateful to the staff of the YCH who facilitated the access to the medical records and to data collection. References Dowswell T, Carroli G, Duley L, Gates S, Gülmezoglu AM, Khan‐Neelofur D et al. Alternative versus standard packages of antenatal care for low‐risk pregnancy. Cochrane Database Syst Rev . 16 Jul 2015;(7). Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7061257/. Recommandations de l’OMS concernant les soins prénatals pour que la grossesse soit une expérience positive. WHO . 2020. Available from: http://www.who.int/reproductivehealth/publications/maternal_perinatal_health/anc-positive-pregnancy-experience/fr/. Jiwani SS, Amouzou-Aguirre A, Carvajal L, Chou D, Keita Y, Moran AC, et al. Timing and number of antenatal care contacts in low and middle-income countries: Analysis in the Countdown to 2030 priority countries. J Glob Health . 2020;10(1). Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7101027/. Okedo-Alex IN, Akamike IC, Ezeanosike OB, Uneke CJ. Determinants of antenatal care utilisation in sub-Saharan Africa: a systematic review. BMJ open . 2019;9(10):031890. Brown CA, Sohani SB, Khan K, Lilford R, Mukhwana W. Antenatal care and perinatal outcomes in Kwale district, Kenya. BMC Pregnancy and Childbirth . 2008;8:2. PubMed | Google Scholar. Vogel JP, Habib NA, Souza JP, Gülmezoglu AM, Dowswell T, Carroli G, et al . Antenatal care packages with reduced visits and perinatal mortality: a secondary analysis of the WHO Antenatal Care Trial. Reproductive Health . 2013;10(1):19. doi:10.1186/1742-4755-10 -19. Ekholuenetale M, Benebo FO, Idebolo AF. Individual-, household-, and community-level factors associated with eight or more antenatal care contacts in Nigeria: Evidence from Demographic and Health Survey. PLoS One . 2020;15(9):0239855. Tekelab T, Chojenta C, Smith R, Loxton D. Factors affecting utilization of antenatal care in Ethiopia: A systematic review and meta-analysis. PLoS ONE . 2019;14(4). Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6459485/. Mortalité maternelle : Principaux repères. Genève (2016). Organisation mondiale de la Santé . Available from : http://www.who.int/fr/news-room/fact-sheets/detail/maternal-mortality. Blencowe H, Cousens S, Jassir FB, Say L, Chou D, Mathers C, et al. National, regional, and worldwide estimates of stillbirth rates in 2015, with trends from 2000: a systematic analysis. Lancet . 2016;4(2):98–108. doi:10.1016/S2214-109X(15)00275-2. Nikiema, B., Beninguisse, G., & Haggerty, J. L. (2009). Providing information on pregnancy complications during antenatal visits: Unmet educational needs in sub-Saharan Africa. Health Policy and Planning. 24(5), 367-376. Rwenge, J-R.M., & Tchamgoue-Nguemaleu, H.B. (2011). Facteurs sociaux de l'utilisation des services de soins obstétricaux parmi les adolescentes camerounaises. African Journal of Reproductive Health 15(3), 87-99. Available from: http://www.bioline.org.br/request?rh11038. Maleya A, Kalume KY, Munan MR, Bulenda NJ, Ilunga NH, Mukuku O et al. Issues materno-fœtales des grossesses non suivies à Lubumbashi, République Démocratique du Congo. The Pan African Medical Journal . 2019; 33:66. Mugo NS, Mya KS, Raynes-Greenow C. Country compliance with WHO-recommended antenatal care guidelines: equity analysis of the 2015–2016 Demography and Health Survey in Myanmar. BMJ Glob Health . 2020;5(12). Tolefac PN, Halle-Ekane GE, Agbor VN, Sama CB, Ngwasiri C, Tebeu PM. Why do pregnant women present late for their first antenatal care consultation in Cameroon? Maternal health, neonatology and perinatology . 2017; 3(1):1–6. https://doi.org/10.1186/s40748-017-0067-8 PMID: 29255616. Gandzien PC. Les grossesses non suivies : pronostic obstétrical et néonatal. Méd Afr Noire . 2007; 54: 166-168. El Hamdani FZ, Vimard P, Baali A, Zouini M, Cherkaoui M. Soins prénatals dans la ville de Marrakech . Med Sante Trop . 2013; 23:162-167. Mustafa MH, Mukhtar AM. Factors associated with antenatal and delivery care in Sudan: analysis of the 2010 Sudan household survey. BMC Health Services Research . 2015; 15:452. PubMed | Google Scholar. Ali N, Sultana M, Sheikh N, Akram R, Mahumud RA, Asaduzzaman M et al. Predictors of Optimal Antenatal Care Service Utilization Among Adolescents and Adult Women in Bangladesh. Health Serv Res Manag Epidemiol . 2 juill 2018;5. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6069020/. Islam MM, Masud MS. Determinants of frequency and contents of antenatal care visits in Bangladesh: Assessing the extent of compliance with the WHO recommendations. PLoS One . 2018;13(9). Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6160162/ Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 04 Nov, 2025 Read the published version in BMC Pregnancy and Childbirth → Version 1 posted Editorial decision: Revision requested 03 May, 2024 Submission checks completed at journal 26 Apr, 2024 Editor assigned by journal 26 Apr, 2024 First submitted to journal 20 Apr, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4297104","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":297486769,"identity":"4f2f2246-7d8b-4932-90ab-81012920656c","order_by":0,"name":"Anne Jocelyne Nguemedyam Cheudjui","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAy0lEQVRIiWNgGAWjYDACCSDm4WHg4QdxEgpI0SLZANJiQLQWIDY4AOIRo4V/dvMxiTcyh2WMz69O/PDAgEGeX+wAAUvuHEuTnMNzmMfsxtvNEkCHGc6cnYBfi4FEjpk0D1jL2Q0gLQkGtwlqyf8G1mI84+zmH0RqyWEDazHg791GnC0SN9KMLefwpPNI3ODdZpFgIEHYL/wzkh/eeNtjbc/ff3bzzR8VNvL80gS0gAFjD8g+sEoJIpSDwQ+QfQeIVT0KRsEoGAUjDQAABv8+l/stI1YAAAAASUVORK5CYII=","orcid":"","institution":"University of Yaounde I","correspondingAuthor":true,"prefix":"","firstName":"Anne","middleName":"Jocelyne Nguemedyam","lastName":"Cheudjui","suffix":""},{"id":297486773,"identity":"3b0c36dd-e261-4cd6-b552-288ea2ee9301","order_by":1,"name":"Martial Wandji Lantche","email":"","orcid":"","institution":"Catholic University for Central Africa","correspondingAuthor":false,"prefix":"","firstName":"Martial","middleName":"Wandji","lastName":"Lantche","suffix":""},{"id":297486775,"identity":"465904a1-c7c8-4023-8e1a-3ae533701a36","order_by":2,"name":"Catherine Fanny Mayoh Nguemfo","email":"","orcid":"","institution":"University of Yaounde I","correspondingAuthor":false,"prefix":"","firstName":"Catherine","middleName":"Fanny Mayoh","lastName":"Nguemfo","suffix":""},{"id":297486777,"identity":"bdc7c2b8-48ce-46e7-b152-92abf5404b15","order_by":3,"name":"Firmin Girèce Kakeu Tandjong","email":"","orcid":"","institution":"Regional Technical Group for the Fight against HIV/AIDS","correspondingAuthor":false,"prefix":"","firstName":"Firmin","middleName":"Girèce Kakeu","lastName":"Tandjong","suffix":""},{"id":297486779,"identity":"35fa1fba-9251-44b4-9900-838135d8598a","order_by":4,"name":"Robinson Enow Mbu","email":"","orcid":"","institution":"University of Yaounde I","correspondingAuthor":false,"prefix":"","firstName":"Robinson","middleName":"Enow","lastName":"Mbu","suffix":""}],"badges":[],"createdAt":"2024-04-20 10:42:29","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4297104/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4297104/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12884-025-08256-x","type":"published","date":"2025-11-04T15:57:28+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":55770323,"identity":"eb0e8cf9-caf0-4366-bc86-01f421e12b7f","added_by":"auto","created_at":"2024-05-02 20:58:32","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":116073,"visible":true,"origin":"","legend":"\u003cp\u003eFlow diagram of participants recruited for analysis, Yaounde Central Hospital, June to August 2021\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-4297104/v1/ac21b09047c37cc5805bbd07.png"},{"id":95564736,"identity":"e67f575f-764b-4fd9-965c-e7b1c3ed9988","added_by":"auto","created_at":"2025-11-10 16:10:28","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":873823,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4297104/v1/2c70b9ac-5677-4f3a-829f-7df1bfba8a47.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Factors Associated with Inadequate Antenatal Contacts at the Yaounde Central Hospital in Cameroon","fulltext":[{"header":"Background","content":"\u003cp\u003eUntil end-2015, the World Health Organization (WHO) recommended at least 4 Antenatal Contacts (ANC) [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. This number of ANC differs from one country to another; 11 in the United States, 10 in Germany and England, 9 in France, 8 in Italy and 4 in Cameroon [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. ANC in developing countries is often of poor quality. The rate of Inadequate ANC (IANC) is fluctuating, depending on the country; 38% in the Central African Republic [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e] and 32% in Kenya [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSince 2016 and based on recent evidences, the WHO recognizes that the 4 ANC model, which was developed in the years 2000, is likely associated with higher perinatal mortality than models that include at least 8 ANC [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Adverse pregnancy outcomes prevention includes ANC, family planning, skilled labor and essential obstetric care [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eNearly 303,000 women died in 2015 from complications related to pregnancy and childbirth [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. About 2.6\u0026nbsp;million children were stillborn in the same year. Almost all maternal (99%) and infant (98%) deaths occurred in low- and middle-income countries. These deaths would have been avoided if the parturients had access to at least 8 ANC [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Sixty percent (60%) of stillbirths (1.46\u0026nbsp;million) occurred during the prenatal period and were mainly due to untreated maternal infection, hypertension and intrauterine growth retardation [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn Sub-Saharan Africa (SSA), the choice of the number of ANC raises important economic questions, especially where the evaluation of pregnancy and childbirth surveillance remains limited [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. In Cameroon, few studies have been carried out to address the issue of IANC [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Consequently, this study aimed at determine factors associated with IANC at the Yaounde Central Hospital (YCY) in Cameroon.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e \u003cstrong\u003eStudy design\u003c/strong\u003e \u003cp\u003eThis was a cross-sectional study conducted from June 8th to August 07th 2021 at the YCH in Cameroon.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eStudy population\u003c/strong\u003e \u003cp\u003e Participants enrolled in the study were aged 15 years and over, had delivered in the last 24 hours at the moment of inclusion and had given their informed consent.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eSample size\u003c/b\u003e: The sample size was calculated using the formula z\u0026sup2;p(1-P)/e\u0026sup2;, where: z refers to 95% confidence interval\u0026thinsp;=\u0026thinsp;1.96; p refers to proportion of IANC according to WHO recommendations\u0026thinsp;=\u0026thinsp;17.4% [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] and e refers to margin of sampling error\u0026thinsp;=\u0026thinsp;6%. This gave a sample size of 145. The sample size was increased by 5% (8 cases) to allow for incomplete interviews. Hence, the minimum sample size was 153.\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eSampling\u003c/strong\u003e \u003cp\u003e Participants were recruited consecutively until the sample size was reached. The total number of participants included in the study was 203. Of those, 3 participants were excluded due to incomplete questionnaires (2 cases) and inappropriate data (1 case) from their patient records (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eData collection\u003c/strong\u003e \u003cp\u003eA face-to-face interview based on a standard questionnaire was done. After obtaining the consent of participants, primary data were completed through this interview while secondary data were completed by extracting information from the patient\u0026rsquo;s medical records.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eVariables measurement\u003c/strong\u003e \u003cp\u003eThe dependent variable was IANC. At the moment of delivery, the number of ANC completed was considered either as inadequate (\u0026lt;\u0026thinsp;8 ANC) or adequate (\u0026ge;\u0026thinsp;8 ANC). Independent variables were related to age, delivery term, parity, referrals, education, marital status, residence, occupation and chronic disease.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eData analysis\u003c/strong\u003e \u003cp\u003eAfter each data collection day, the principal investigator incorporated data into Epi Info Version 7.0 for analyses. Descriptive statistics were used to assess all variables. Univariate logistic regression was used for categorical independent variables. Multivariate logistic regression was performed by entering all the variables associated with IANC in univariate analysis. Of note, all the variables associated with IANC at P\u0026thinsp;\u0026le;\u0026thinsp;0.2 in univariate analysis were also included in the final model. The significance level was considered at 5%. Odds Ratios were calculated with a 95% Confidence Interval (95%CI).\u003c/p\u003e \u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e \u003cstrong\u003eDescriptive analysis\u003c/strong\u003e \u003cp\u003eCharacteristics of participants are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Almost one-half (47.5%) of the participants were aged between 26 and 36 years. The mean age was 28 years, with a standard deviation of 6.7 years. The majority (79.5%) of women delivered before 40 weeks of amenorrhea. Three-quarter (75.5%) were pauciparous, while 46% were referrals and 62.5% had a secondary education. Moreover, we found that unmarried women (58.0%) were more represented than married (42.0%). Most of the respondents (96.5%) were living in an urban area, while about one-half (54.0%) were not unemployed and one-fifth (19.0%) had a chronic disease.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eGrouped frequency distribution of the variables, Yaounde Central Hospital, June to August 2021 (N\u0026thinsp;=\u0026thinsp;200)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStudied variables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNumber of participants\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePercent\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (mean: 28\u0026thinsp;\u0026plusmn;\u0026thinsp;6.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15 to 25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e35.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e26 to 36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e47.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e37 to 49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDelivery term\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;40 weeks\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e159\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e79.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;40 weeks\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e20.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePauciparous\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e151\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e75.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMultiparous\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eReferrals\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e108\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e54.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e46.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation level\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMedium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e125\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e62.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigh\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e30.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarital status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e84\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnmarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e116\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e58.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResidence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrban area\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e193\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e96.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRural area\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOccupation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEmployed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e46.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnemployed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e108\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e54.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChronic disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e162\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e81.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eUnivariate analysis\u003c/strong\u003e \u003cp\u003eA summary of the univariate analysis of descriptive data associated with IANC is provided in Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. The risk for IANC was higher among referrals than non-referrals (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Secondary or higher education was significantly associated with IANC than primary education (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Unmarried women were more likely to have IANC compared to those in couple (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). There was more risk for IANC among women with chronic disease compared to those without chronic disease (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAssociations between inadequate antenatal contacts and independent variables (N\u0026thinsp;=\u0026thinsp;200)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"8\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" 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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIANC*\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAANC**\u003c/p\u003e \u003cp\u003en (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eCOR***\u003c/p\u003e \u003cp\u003e(95% CI\u003csup\u003e\u0026para;\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eAOR****\u003c/p\u003e \u003cp\u003e(95% CI\u003csup\u003e\u0026para;\u003c/sup\u003e)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e15 to 25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e52 (36.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e19 (32.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e26 to 36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e70 (49.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25 (42.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.4 (0.7\u0026ndash;2.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.381\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNA\u003csup\u003e\u0026para;\u0026para;\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e37 to 49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e19 (13.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e15 (25.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.5 (0.2\u0026ndash;1.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.115\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.7 (0.5\u0026ndash;1.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.139\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eParity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePauciparous\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e108 (71.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e43 (72.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMultiparous\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e33 (23.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16 (27.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.9 (0.5\u0026ndash;1.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.979\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNA\u003csup\u003e\u0026para;\u0026para;\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNA\u003csup\u003e\u0026para;\u0026para;\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eReferral\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e60 (42.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e48 (81.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e81 (57.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11 (18.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.9 (2.8\u0026ndash;12.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.4 (2.2\u0026ndash;12.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEducation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePrimary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e12 (8.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2 (3.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSecondary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e100 (70.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25 (42.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.3 (1.8\u0026ndash;6.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.2 (0.2\u0026ndash;7.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.068\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHigher\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e29 (20.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e32 (54.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.2 (0.1\u0026ndash;0.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.3 (0.0-1.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.083\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarital status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e53 (37.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e31 (52.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnmarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e88 (62.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e28 (47.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.0 (1.6\u0026ndash;5.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.5 (1.2\u0026ndash;5.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResidence\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUrban\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e136 (96.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5 (3.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.0 (0.2\u0026ndash;5.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.713\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNA\u003csup\u003e\u0026para;\u0026para;\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNA\u003csup\u003e\u0026para;\u0026para;\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOccupation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEmployed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e59 (41.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e57 (96.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eUnemployed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e82 (58.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2 (3.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.4 (0.8\u0026ndash;2.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.357\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eNA\u003csup\u003e\u0026para;\u0026para;\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eNA\u003csup\u003e\u0026para;\u0026para;\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChronic disease\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e110 (78.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e52 (88.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e31 (22.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7 (11.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.7 (1.3\u0026ndash;73.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.3 (0.4\u0026ndash;28.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.201\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"8\"\u003e*: Inadequate Antenatal Contact; **: Adequate Antenatal Contact; ***: Crude Odds Ratio; ****: Adjusted Odds Ratio; \u003csup\u003e\u0026para;\u003c/sup\u003e: Confidence Interval\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eMultivariate analysis\u003c/strong\u003e \u003cp\u003eSome conclusions based on the univariate analysis described above were not confirmed in this model (Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). On adjustment for other established risk factors for IANC, those that remained significantly associated with IANC were referrals (AOR\u0026thinsp;=\u0026thinsp;5.4; 95% CI\u0026thinsp;=\u0026thinsp;2.2\u0026ndash;12.9; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and unmarried (AOR\u0026thinsp;=\u0026thinsp;2.5; 95% CI\u0026thinsp;=\u0026thinsp;1.2\u0026ndash;5.4; p\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe results of this study showed that the majority (70.5%) of participants had IANC. This proportion was higher to that of Mugo \u003cem\u003eet al.\u003c/em\u003e (59%) in Myanmar, with a sample size of 2,943, but lower to that of Ekholuenetale \u003cem\u003eet al.\u003c/em\u003e (82.6%) in Nigeria, with a sample size of 1,404 [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Such findings might be explained by our small sample size (200). Like in other Low- and Middle-Income Countries (LMICs), most of the participants included in this study were young adults (21\u0026ndash;35 years).\u003c/p\u003e \u003cp\u003eThere was no association between parity and IANC. This finding corroborates that of Maleya \u003cem\u003eet al.\u003c/em\u003e [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e] but differs from those of Baumann and Roth [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e] who recorded that the number of IANC decreases as parity increases [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Participants in higher education were less likely to have IANC than primary level. In contrast, Ali \u003cem\u003eet al.\u003c/em\u003e in a study in Bangladesh (2014) revealed that women in higher education were more likely to have IANC than no education [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. Indeed, educated women had a better understanding of risk factors for IANC during interviews. Unmarried women were 3.0 times more likely to have IANC than married. In fact, there was a delay to start ANC among unmarried since pregnancy disclosure to family was limited [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Moreover, not being in couple limited access to IANC, particularly in poor setting [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Other reasons included the lack of support by family or health workers. Chronic disease was positively associated with IANC. This observation confirmed in other publications [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e] showed that taking medications for life increases the risk of having IANC.\u003c/p\u003e \u003cp\u003eThe final logistic regression model revealed that referrals and unmarried were positively associated with IANC. Therefore, potential confounding factors taken into account might explain why some independent variables were not retained in this model. Such cases included chronic disease, secondary and higher education. These results are similar to that of Maleya \u003cem\u003eet al.\u003c/em\u003e in Lubumbashi in 2019 [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cstrong\u003eLimitations\u003c/strong\u003e \u003cp\u003eThe cross-sectional design of this study limited the evaluation over time of our findings, while the monocentric nature limited the external validity.\u003c/p\u003e \u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis study revealed a high proportion of IANC, which was positively associated with unmarried and referrals. The monitoring of these risk factors is therefore necessary to prevent adverse births, particularly in resource-limited settings.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eConflict of interest:\u003c/strong\u003e The authors declare that they have no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eEthics approval and consent to participate:\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eThe study proposal was submitted and received approvals from the Institutional Ethics Committee (IEC) of the Faculty of Medicine and Biomedical Sciences (FMBS) (reference number: 219 / 2021 / UY1 / FMSB / VDRC / DAASR / CSD) and the administration of the YCH (reference number:\u003csup\u003e\u0026nbsp;\u003c/sup\u003e322 / 2021 / AR / MINSANTE / SG / DHCY / CM / SM). All participants included in this study had given their consent to participate.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eConsent for publication:\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eWritten informed consent for publication of these findings was obtained from the participants.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eData availability:\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eThe datasets analyzed in this study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eCompeting interests:\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eFunding:\u0026nbsp;\u003c/em\u003e\u003c/strong\u003eNo funding was obtained to carry out this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAuthors\u0026apos; contributions:\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eAJNC, MWL\u0026nbsp;and REM designed and implemented the study.\u0026nbsp;AJNC\u0026nbsp;collected the data.\u0026nbsp;AJNC, MWL, CFMN and FGTK\u0026nbsp;analyzed and interpreted the data.\u0026nbsp;AJNC\u0026nbsp;and\u0026nbsp;MWL\u0026nbsp;initiated the manuscript. AJNC, MWL, CFMN and ERM revised the initial version of the manuscript. All authors revised and approved the final version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAcknowledgements:\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003eThe authors are grateful to the staff of the YCH who facilitated the access to the medical records and to data collection.\u003c/p\u003e\n"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eDowswell T, Carroli G, Duley L, Gates S, G\u0026uuml;lmezoglu AM, Khan‐Neelofur D \u003cem\u003eet al.\u003c/em\u003e Alternative versus standard packages of antenatal care for low‐risk pregnancy. \u003cem\u003eCochrane Database Syst Rev\u003c/em\u003e. 16 Jul 2015;(7). Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7061257/.\u003c/li\u003e\n\u003cli\u003eRecommandations de l\u0026rsquo;OMS concernant les soins pr\u0026eacute;natals pour que la grossesse soit une exp\u0026eacute;rience positive. \u003cem\u003eWHO\u003c/em\u003e. 2020. Available from: http://www.who.int/reproductivehealth/publications/maternal_perinatal_health/anc-positive-pregnancy-experience/fr/.\u003c/li\u003e\n\u003cli\u003eJiwani SS, Amouzou-Aguirre A, Carvajal L, Chou D, Keita Y, Moran AC, \u003cem\u003eet al.\u003c/em\u003e Timing and number of antenatal care contacts in low and middle-income countries: Analysis in the Countdown to 2030 priority countries. \u003cem\u003eJ Glob Health\u003c/em\u003e. 2020;10(1). Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7101027/.\u003c/li\u003e\n\u003cli\u003eOkedo-Alex IN, Akamike IC, Ezeanosike OB, Uneke CJ. 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Available from : http://www.who.int/fr/news-room/fact-sheets/detail/maternal-mortality.\u003c/li\u003e\n\u003cli\u003eBlencowe H, Cousens S, Jassir FB, Say L, Chou D, Mathers C, \u003cem\u003eet al.\u003c/em\u003e National, regional, and worldwide estimates of stillbirth rates in 2015, with trends from 2000: a systematic analysis. \u003cem\u003eLancet\u003c/em\u003e. 2016;4(2):98\u0026ndash;108. doi:10.1016/S2214-109X(15)00275-2.\u003c/li\u003e\n\u003cli\u003eNikiema, B., Beninguisse, G., \u0026amp; Haggerty, J. L. (2009). Providing information on pregnancy complications during antenatal visits: Unmet educational needs in sub-Saharan Africa. \u003cem\u003eHealth Policy and Planning.\u003c/em\u003e 24(5), 367-376.\u003c/li\u003e\n\u003cli\u003eRwenge, J-R.M., \u0026amp; Tchamgoue-Nguemaleu, H.B. (2011). 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PubMed | Google Scholar.\u003c/li\u003e\n\u003cli\u003eAli N, Sultana M, Sheikh N, Akram R, Mahumud RA, Asaduzzaman M \u003cem\u003eet al.\u003c/em\u003e Predictors of Optimal Antenatal Care Service Utilization Among Adolescents and Adult Women in Bangladesh. \u003cem\u003eHealth Serv Res Manag Epidemiol\u003c/em\u003e. 2 juill 2018;5. Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6069020/.\u003c/li\u003e\n\u003cli\u003eIslam MM, Masud MS. Determinants of frequency and contents of antenatal care visits in Bangladesh: Assessing the extent of compliance with the WHO recommendations. \u003cem\u003ePLoS One\u003c/em\u003e. 2018;13(9). Available from: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6160162/\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-pregnancy-and-childbirth","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"prch","sideBox":"Learn more about [BMC Pregnancy and Childbirth](http://bmcpregnancychildbirth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/prch/default.aspx","title":"BMC Pregnancy and Childbirth","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Factors Associated, Inadequate Antenatal Contacts, Yaounde Central Hospital","lastPublishedDoi":"10.21203/rs.3.rs-4297104/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4297104/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eUntil 2015, 4 Antenatal Contacts (ANC) was the World Health Organisation (WHO) preferred model for pregnancy follow-up. Given concerns about adverse births, at least 8 ANC have been recommended since 2016 in resource-limited settings.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA cross-sectional study was conducted among women who had delivered within the last 24 hours in Yaounde Central Hospital (YCH), Cameroon, between June 8th and August 7th 2021. Logistic regression was used to determine factors associated with Inadequate ANC (IANC). Analyses were done using Epi Info 7.0. Any P-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eOf the 200 participants enrolled, the majority (70.5%) had IANC and the mean age was 28.0\u0026thinsp;\u0026plusmn;\u0026thinsp;6.7 years. Referrals women were more likely to have IANC than non-referrals, with an Adjusted Odds Ratio (AOR) of 5.4 (95% Confidence Interval [CI]: 2.2\u0026ndash;12.9; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Likewise, unmarried women were more likely to have IANC than married, with an AOR of 2.5 (95% CI: 1.2\u0026ndash;5.4; P\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eAbout 7 out of 10 women who delivered at the YCH had IANC. Accordingly, risk factors for IANC should be monitored throughout pregnancy particularly among young women in Cameroon.\u003c/p\u003e","manuscriptTitle":"Factors Associated with Inadequate Antenatal Contacts at the Yaounde Central Hospital in Cameroon","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-05-02 20:58:28","doi":"10.21203/rs.3.rs-4297104/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-05-03T07:23:54+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-04-26T06:18:37+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-04-26T06:18:37+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Pregnancy and Childbirth","date":"2024-04-20T10:28:35+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-pregnancy-and-childbirth","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"prch","sideBox":"Learn more about [BMC Pregnancy and Childbirth](http://bmcpregnancychildbirth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/prch/default.aspx","title":"BMC Pregnancy and Childbirth","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"d2d6cd65-8eda-4103-91b5-da67341a0e7e","owner":[],"postedDate":"May 2nd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-11-10T16:09:23+00:00","versionOfRecord":{"articleIdentity":"rs-4297104","link":"https://doi.org/10.1186/s12884-025-08256-x","journal":{"identity":"bmc-pregnancy-and-childbirth","isVorOnly":false,"title":"BMC Pregnancy and Childbirth"},"publishedOn":"2025-11-04 15:57:28","publishedOnDateReadable":"November 4th, 2025"},"versionCreatedAt":"2024-05-02 20:58:28","video":"","vorDoi":"10.1186/s12884-025-08256-x","vorDoiUrl":"https://doi.org/10.1186/s12884-025-08256-x","workflowStages":[]},"version":"v1","identity":"rs-4297104","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4297104","identity":"rs-4297104","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}