Burden of Non-prescribed drug use and its associated factors among Pregnant Women in Peri-urban kebeles’ of Jimma town, southwest Ethiopia, 2023

Burden of Non-prescribed drug use and its associated factors among Pregnant Women in Peri-urban kebeles’ of Jimma town, southwest Ethiopia, 2023 | 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 Article Burden of Non-prescribed drug use and its associated factors among Pregnant Women in Peri-urban kebeles’ of Jimma town, southwest Ethiopia, 2023 Fentahun Yene, Berihun Bantie, Tarekegn Yilma, Idalamin Zinab, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4443746/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 02 Jul, 2025 Read the published version in Scientific Reports → Version 1 posted 10 You are reading this latest preprint version Abstract Background: Non-prescribed drug utilization is the act of using medication to treat self-diagnosed problems without consulting a healthcare provider. Pregnant women are among the most vulnerable population groups for self-medication to treat pregnancy-related problems. The use of non-prescribed drugs, however, has numerous detrimental effects on both the growing fetus and the mother. Besides, community-based information regarding the pattern of non-prescribed drug use is limited in Ethiopia. Hence, this study aims to investigate non-prescribed drug use and its associated factors among pregnant women in Jimma town, southwest Ethiopia, in 2023. Method and Materials: A community-based cross-sectional study was conducted among 358 pregnant mothers in the peri-urban kebeles of Jimma town, southwest Ethiopia. A systematic random sampling technique (every K = 3 households) was used to select the final study participants. Data were collected using an interviewer-administered structured questionnaire, entered into EpiData version 7.2.2 software, and exported to SPSS version 25 for further analysis. Both bivariable and multivariable logistic regression models were fitted to identify the factors influencing non-prescribed drug utilization status. The level of significance of the association was determined at a P-value < 0.05 with a 95% CI. Result: Overall, the prevalence of non-prescribed drug use among pregnant mothers was 37.7% (95% CI: 32.8–41.7%). Enrollment in health insurance (AOR = 0.21, 95% CI: 0.03–0.76), being primigravida (AOR = 3.05, 95% CI: 1.03–5.08), and experiencing any pregnancy-related complications (AOR = 2.34, 95% CI: 1.99–2.76) were found to be significant factors affecting the non-prescribed drug utilization status of pregnant mothers. Conclusion and recommendations: In the current study, non-prescribed drug use among pregnant mothers was high. Health insurance enrollment status, gravidity, and the presence of any pregnancy-related complications were identified as significant predictors of non-prescribed drug use among pregnant mothers. Hence, stakeholders should invest their efforts in increasing community enrollment in health insurance programs and place special emphasis on high-risk groups prone to non-prescribed drug use. Health sciences/Medical research/Epidemiology Health sciences/Health care/Drug regulation Health sciences/Health care/Health policy Health sciences/Health care/Health services non-prescribed drug use associated factors pregnant women Ethiopia Figures Figure 1 Figure 2 Figure 3 1. Introduction Non-prescribed drug use or self-medication is defined as the act of utilizing medications by patients to treat self-diagnosed health and health-related problems without getting advice from a healthcare provider. Pregnant women are among the most vulnerable groups for using non-prescribed drugs to prevent and/or treat pregnancy-related issues such as abortion, mood disorders, and anemia. Globally, 22%-44% of pregnant women are reported to use non-prescribed drugs. Despite the fact that non-prescribed drug use is increasing worldwide, its burden is particularly high in low and middle-income countries due to poor medical services and a lack of professional control of pharmaceutical products, which is estimated to be greater than 31.5%. In Ethiopia, the extent of non-prescribed drug use is high and varies significantly across regions and communities, influenced by different cultural practices and perspectives [ 1 ]. For instance, its burden ranges from 7.8% in the Tigray region [ 2 ], 45.2% in Nekmte town[ 3 ] to 69.4% in Harar town [ 4 ]. Though recent evidences were limited, a prior meta-analysis study also revealed that more than 30% of the pregnant mothers in Ethiopia practice self –medication [ 5 ]. The high prevalence of non-prescribed drug utilization among pregnant women can seriously affect the health of both the mother and fetus, potentially causing detrimental adverse effects such as congenital birth defects, miscarriage, and allergic diseases. It has been reported that at least 10% of birth defects result from the exposure of pregnant women to drugs, with the risk being particularly heightened during the first trimester of pregnancy [ 6 ]. Additionally, the increased practice of self-medication exacerbates the occurrence of drug interactions and adverse events. Pregnant women’s might frequently utilize non-prescribed drug due to numerous religious and cultural values and beliefs such as for the purpose of treating their psychological distress and other pregnancy -related complications[ 7 , 8 ]. In most developing countries like Ethiopia, in addition to the cultural perspectives, other several factors including poor access to health facility, socioeconomic status, age, gender, education level, occupation, lack of awareness of their side effects and interactions, time, perception of the risk of self-medication, previous medication use, gestational age, and experience of pregnancy-related complications affects the Non-prescribed drug utilization status of pregnant mothers [ 1 , 8 – 12 ]. The government of Ethiopia gives substantial emphasis on prioritizing the health and well-being of mothers and neonates[ 13 ]. Although non-prescribed drug use is difficult to eliminate, intervention can be made to minimize the burden of this malpractice. This requires extensive knowledge on the level and risk factors contributing to the increased prevalence of non-prescribed drug utilization among pregnant mothers in a certain geographical areas. In this regard, though there are several studies that asses the level of self-medication practice among pregnant women in Ethiopia, most of them were institution based which will not represent the general population. Hence, this study is aimed to investigate the use utilization status and associated factors associate of non-prescribed drug among pregnant women in peri-urban kebeles of Jimma town, south west Ethiopia. 2. Methods and materials 2.1 Study area, period and design This study was conducted among pregnant women in the peri-urban kebeles of Jimma town, south-west Ethiopia, from January 20 to March 1, 2023. Jimma town is located 352 kilometres south-west of Addis Abeba, the capital city of Ethiopia[ 14 ]. In the town, there are about 17 kebele’s, of which 5 are peri-urban areas (Jireen, Qofe, Haro gibe, Bore, and Ifa bula). There are about 4,686 households in these peri-urban kebeles. A community based cross sectional study was employed to assess the use and factors associated with non-prescribed drug among pregnant women in peri-urban kebeles of Jimma town, south west Ethiopia, 2023 2.2 Source and study population The source population was all pregnant women who have been residing in the study area for at least six months. Whereas, all pregnant women are in peri-urban kebeles of Jimma town and presented in the data collection period were the study populations. Pregnant mothers who were not mentally competent to provide adequate information were excluded from the study. 2.3 Sample size determination and sampling technique The sample size for this study was determined using EPINFO version 7.2.3.1 software through a single population proportion formula. Considering parameters like 80% power, 95% confidence level, 5% marginal error, 69.4% prevalence of non-prescribed drug use among pregnant women in Harar town, and 10% non-response rate, a final sample size of 360 pregnant mothers were included in this study. Study participants were selected using systematic random sampling techniques. Initially, the total number of pregnant women and household numbers were obtained from health extension workers in each keble. The total calculated sample size (n = 360) was proportionally allocated to each kebele. Finally, systematic sampling techniques (every k = 3 interval) were used to select the final eligible study participants. In the case of more than one pregnant woman per household, only one pregnant woman was selected randomly to reduce selection bias (Fig 1). Figure 1: Schematic presentation of sampling procedure among pregnant women in the peri-urban kebeles of Jimma town, south west Ethiopia, 2023. 2.4 .Study variable The main exposure variable for this study was the presence or absence of Non-prescribed drug use (yes/no). Whereas, variables socio-demographic variables (age, income, educational level), Pregnancy and health related factors ( history of abortion, gravidity, number of living children, previous pregnancy related problems ), health service delivery-related factors (distance from health facility, and health insurance enrollment ) and behavior related factors (perceived status of the disease, previous experiences of non-prescribed drug use). 2.5 Operational definitions Non-prescribed drug is the use of non-prescription medications to treat self-diagnosed disorders or symptoms, without consulting a physician and without any health professional supervision. Pregnancy related complications were defined as those problems that are specifically linked to the pregnant state as well as conditions that commonly occur incidentally in women who are pregnant which includes pregnancy related hypertension, premature rupture of membranes, pre-term labor or birth, antepartum hemorrhage, headache, vaginal discharge, abdominal cramp [ 15 , 16 ]. The income status of the participants were categorized as low (≤ 1,025), lower middle (1,026 − 3,995) ,upper middle(3,996 − 12,375 ) and upper (> 12,375) based on the 2018 international monetary fund (IMF) income level scale for Ethiopia[ 17 ]. Gravidity was defined as the sum of all pregnancies, including all live births and pregnancies that terminated at < 6 months or did not result in a live birth [ 18 ] 2.6 Data collection techniques and tools A pretested interviewer administered standard questionnaire was developed after thoroughly reviewing the findings of prior related literatures. The questionnaire was initially prepared in English and translated to Afan Oromo and Amharic, then back to English to ensure consistency between the original and translated questionnaires. To ensure data quality, a pre-test was conducted on 5% (18) of the households at Ginjo Kebele of Jimma town, south west Ethiopia. Data were collected by five trained BSc Midwifery professionals. Additionally, one-day training was given for data collectors and supervisors about the objective of the study, how to obtain consent from participants, and how to ensure the confidentiality of the patient information. The collected data was checked for completeness every day before the following day of data collection by supervisors and the principal investigator, and corrective measures were taken according to the findings during supervision. 2.7 Data processing and analysis The data was entered using Epi-data version 7.2.2.2 statistical software and analyzed using SPSS version 25 statistical package. Descriptive statistics such as frequencies with percentage, mean with standard deviation were used to describe the study population sociodemographic and other characteristics. Logistic regression model was used to fit the data to identify factors associated with non-prescribed drug use. Variables with a P-value of < 0.25 in the simple binary logistic regression model were fitted to the multivariable binary logistic regression model, and finally, the level of significance was declared at a p-value of < 0.05. The backward likelihood ratio elimination method was used to identify factors which are significantly associated with the non-prescribed drug –use pattern. The overall goodness of the model with the fitted data was evaluated using the "Hosmer and Lomeshow" goodness of fit test. Finally, the result of this study was presented in texts, graphs and tables 2.8 Ethical considerations An ethical approval letter was obtained from the Institutional Review Board (IRB) of Bahirdar University with a protocol number of BDU 651/2022, and then a supportive letter was written to Jimma Town Health Administration and each kebele administration. Verbal informed consent was obtained from the mothers after explaining the purpose and benefit of the study. Confidentiality was assured to all informants, and their anonymity was guaranteed as no name or identification of the parent or study participant pregnant women was collected during the interview. Furthermore, all methods were carried out in accordance with relevant guidelines and regulations. 3. Result 3.1. Result of Socio-demographic characteristics From 360 samples, 358 (99.4%) pregnant women were participated in the study .The Mean age of the study participants were 25.06 years with the standard deviation of ± 4.25 years). Only 59 (16.5%) of the study participants were unable to read and write. Regarding the occupational status of the mother, majority (98.6%) of the study participants were housewife ( Table 1 ) . Table 1 Socio-demographic characteristics of pregnant women in Jimma town peri-urban kebeles, southwest Ethiopia, 2023 (N = 358) Variables ((N = 358) Category Frequency(n = 358) Percentage (%) Age of respondents in years 15–19 43 12.01 20–24 118 32.96 25–34 168 46.92 35-and above 29 8.1 Mean age = 25.06 years, Standard deviation ± 4.25 years Marital status Married 353 98.6 Not married 5 1.4 Occupation housewife 271 75.6 Employed 33 9.10 Merchant 45 12.57 Farmer 9 2.5 Educational status of women Can’t read and write 59 16.5 Can read and write 32 8.9 Primary 163 45.5 Secondary 56 15.6 College and above 48 13.4 Educational status of husband Can’t read and write 42 11.7 Can read and write 36 10.1 Primary 126 35.2 Secondary 77 21.5 College and above 77 21.5 Health Insurance Yes 269 75.1 No 89 24.9 Average monthly income* Low 106 29.6 Lower middle 154 43 Upper middle 98 27.4 3.2 Maternal and Obstetric history of the respondents During the current pregnancy, 302 (84.36%) of the respondents attended Antenatal care (ANC) visits. About 117 (32.7%) pregnant women experienced health problems during pregnancy. Constipation was the most common complaint that the pregnant women’s experienced during pregnancy, accounting for 61 (45.2%) (Table 2 ). Table 2 Obstetric history of pregnant women in peri-urban kebeles of Jimma town, south west Ethiopia, 2023 . Variable Category Frequency Percentage Gravidity Primigravda 89 24.86% Multigravida 269 75.14% Number of children No child 93 26 1–3 202 56.4 > 3 63 17.6 ANC follow up Yes 302 84.36% No 56 15.64% Health education on non-prescribed drug Yes 41 11.45% No 317 88.56% Previous pregnancy and delivery related problems No 316 88.27% Yes 42* 11.73 Type of previous pregnancy and delivery related problems Nausea and vomiting 22 16.23% heart burn 25 18.2% back pain 11 8.11% Headache 26 19.23% vaginal discharge 6 4.44% abdominal cramp 5 3.70% Constipation 28 20.74% Current pregnancy and delivery related problems No 241 67.32% Yes 117* 32.68% Type of current pregnancy and delivery related problems Nausea and vomiting 45 33.33% heart burn 48 35.56% back pain 19 14.07% Headache 59 43.7% vaginal discharge 9 6.67% abdominal cramp 8 5.93% Constipation 61 45.2% Hypertension 6 4.44% common cold 18 13.3% 3.3 Magnitude of non-prescribed drug use In the current study, the magnitude of non-prescribed drug use during pregnancy found to be 37.7% (95% CI: 33.4–42.0) (Fig. 2). The most common reason for using Non-prescribed drug was the easy availability of these non-prescribed drugs over the health institutions which account about 116 (85.92%) (Fig. 3). Figure 2 . Magnitude of non-prescribed drugs among pregnant women in the peri-urban kebeles of Jimma town, southwest Ethiopia, 2023(358)n= Figure 3 . Common reasons for the utilization of non-prescribed drug among pregnant women in the peri-urban kebeles of Jimma town, southwest Ethiopia, 2023 3.4. Factors associated with the use of non-prescribed drug during pregnancy In the final multivariable logistic regression model, at 5% of the level of significance, the following variables, namely being enrolled in health insurance, history of health problems during the current pregnancy, and gravidity were found to be significant predictors of non-prescribed drug use during pregnancy. In this aspect, the odd of non-prescribed drug use was found to be 79% times less likely among pregnant women’s who were enrolled in health insurance compared with their counterparts (AOR = 0.21, 95% CI: 0.03–0.76). Primigravida mothers 3.05 times more likely to practice non-prescribed drugs compared with their counterparts (AOR = 3.05, 95% CI: 1.03–5.08). Furthermore, this study also showed that the odd of utilizing non-prescribed drug in pregnant women’s who experienced any pregnancy – related problems was 2.34 times higher than their counterparts (AOR = 2. 34, 95%CI:1.99–2.76) (Table 3 ). Table 3 Bivariable and multivariable logistic regression analysis of factors associated with utilization of non-prescribed among pregnant women in Jimma town peri- urban kebeles, Southwest Ethiopia, 2023 (n = 358) Variables Non-described drug use COR (95%CI) AOR(95% CI) Yes No Distance from health facility Close ≤ 30min 42 88 1 1 Somewhat far 30-60min 57 56 11.7(4.31–26.5) 0.32(0.05–4.18) Far ≥ 60min 36 79 3.48(1.32–9.19) 0.41(0.06–2.72) Being enrolled to health insurance Yes 59 195 0.11(0.06–0.18) 0.21(0.03–0.76)* No 76 28 1.00 1.00 Presence of pregnancy related complications Yes 79 38 6.87 (1.84 11.9) 2. 34 (1.99–2.76) No 56 185 1 1 Waiting time at health institutions Normal 58 150 1 1 Short 13 11 4.75 (1.07–8.43) 0.08(0.01–1.06) Long 64 62 8.51(4.3-13.36) 2.32(0.54–7.77) Gravidity Primigravda 49 40 1.61(1.01–2.21) 3.05(1.03–5.08)* Multigravida 116 153 1 1 Previous experience of self-medication Yes 92 110 1.15 (0.65–1.65) 0.89 (0.7–1.08 No 66 90 1 1 Counselled about self-medication Yes 37 28 1 1 No 98 190 0.39(0.23–0.68) 0.05(0.02–0.31) AOR- Adjusted odds ratio, COR- Crude odds ratio, CI- confidence interval, Bold letter- significantly associated factors, *p-value < 0.05, **p-value < 0.01 4. Discussion This research tried to assess non-prescribed drug use and its associated factors among pregnant women in Jimma town, peri-urban Kebeles, south-west Ethiopia. Despite the potential harmful effect of self-mediation during pregnancy, 135 (37.7%, 95%CI: 32.8–41.7%) of pregnant women used non-prescribed drugs during their pregnancy. This finding is in line with the study conducted at Jimma University medical centre, in Ayder comprehensive specialized hospital, in Iran, and in the United Arab Emirates [ 14 , 19 – 21 ]. Moreover, this figure is higher than the findings of the study conducted in Addis Ababa, in Goba Town located in souteast Ethiopia and in South Africa [ 12 , 22 , 23 ]. These variations could be attributed to the differences in population demographics, over-the-counter sale of most medications in drugstores and inadequate access to healthcare services. On the contrary, the findings of this study were lower than the results of studies done in Harari town in Ethiopia, Ghana, and Tanzania [ 4 , 24 , 25 ]. This discrepancy could be due to the presence easily accessibility of over the counter medication in Jimma town and due to the differences in drug regulation policies in different countries. In the present study, the most commonly reported reasons for using non-prescribed drugs during pregnancy were ease of access to medicines, feeling that disease is minor, low cost, and prolonged waiting time. In agreement with our study, similar findings were reported from previous studies conducted in Addis Ababa and the Democratic Republic of the Congo[ 23 , 24 ]. The possible explanation might be the lack of attention and priorities of health policymakers and other stakeholders on the burden of self-medication risks [ 23 ]. Therefore, necessary measures should be taken to strengthen the regulatory system and enforce regulations so as to reduce the practice of non-prescribed drugs during pregnancy. This study showed that pregnant women who were enrolled in health insurance were 79% less likely to use non-prescribed drugs than women without health insurance (AOR 0.24, 95% CI: 0.03–0.76). This is supported by the results of the study conducted in Ayder Comprehensive Hospital, Tigray region and in Iran[ 21 , 26 ]. The possible explanation for the observed association might be due to the fact that being enrolled to health insurance would increase healthcare utilization of individuals [ 27 ], thereby reducing the necessity for utilization of non-prescribed drugs. This result might indicate a need for public insurance coverage for all people in the community. In this research, pregnant women who had experienced pregnancy-related problems were. 2.34 times more likely to use non-prescribed drug use compared with their counterparts. This finding is supported by literatures conducted in southeast Ethiopia, Jordan, Indonesia, Western Nepa and a systematic review and meta-analysis report of 13 studies [ 12 , 28 – 31 ]. The possible elucidation for the observed association might be since pregnancy-related complications were both physically and emotionally overwhelmed[ 32 ], mothers might seek self-medication in order to alleviate their symptoms promptly and get immediate solution. Furthermore, this study also showed that the odd of non-prescribed drug use was 3.05 times more likely among prmigravida women’s than mutigravida women’s. This finding is in agreement with prior studies conducted in Mizan-Tepi University Teaching Hospital, Southwest Ethiopia, in Tanzania and Indonesia [ 33 – 35 ]. The possible explanation for the observed association would primigravida women may have limited knowledge about the potential risks and safety concerns associated with medication use during pregnancy, making them more likely to use self-medication without understanding the potential harm it can cause. Indeed, women’s experiencing pregnancy-related problems for the first time may lack experience and knowledge about these complications. They may feel anxious or uncertain about seeking medical advice, leading them to look for alternative solutions like self-medication. 4.1. Limitation of the study The limitation of this study might be the study being prone to recall bias that may affect the result of this study, because the pregnant women might not remember the types of drug they used. The other possible limitation could be women in early pregnancy might not have the chance yet to use medications consequently affecting the reported results on drugs commonly used during pregnancy. 5. Conclusion and recommendation This community based cross-sectional study has revealed that significant number of pregnant mothers in used self- medication during their pregnancy time. Being enrolled in to health insurance, experiencing pregnancy-related complications and gravidity were found to be the factors affecting the utilization of non-prescribed drugs. Therefore, special attention need to be given for first time pregnant women’s and the government has to work to increase community’s engagement on health insurance programs. Abbreviations ANC -Ante Natal Care, BDU - Bahir Dar University, ETB- Ethiopian Birr, HMIS-Health Management Information System, JUMC- Jimma University Medical Centre, NGO-Non-Governmental Organization, , SM - Self-Medication , WHO- World Health Organization Declarations Ethical Approval and Consent to participate An ethical approval letter was obtained from the Institutional Review Board (IRB) of Bahirdar University with a protocol number of BDU 651/2022, and then a supportive letter was written to Jimma Town Health Administration and each kebele administrations. Verbal informed consent was obtained from the mothers after explaining the purpose and benefit of the study. Confidentiality was assured to all informants, and their anonymity was guaranteed as no name or identification of the parent or study participant pregnant women was collected during the interview. Furthermore, all methods were carried out in accordance with relevant guidelines and regulations. Consent for Publication Not applicable. Data Availability All data that have been used to support the conclusion of this study are available in the manuscript the manuscript. Competing Interests The authors declare that they have no conflicts of interest for this work. Funds This study had no specific funding. Authors contribution All the authors made significant contributions to the improvement of this manuscript. IZ, FY, and SM participated in the synthesizing the research question, formulating research objectives, data extraction, analysis, interpretation and conclusion of the finding the study. BB and TY were participated in data extraction, analysis, interpretation and preparing the initial draft of the manuscript. All authors had thoroughly read and approved the manuscript. 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BMC pregnancy and childbirth 2020, 20:1–11. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 02 Jul, 2025 Read the published version in Scientific Reports → Version 1 posted Editorial decision: Revision requested 13 Aug, 2024 Reviews received at journal 18 Jul, 2024 Reviewers agreed at journal 04 Jul, 2024 Reviews received at journal 19 Jun, 2024 Reviewers agreed at journal 19 Jun, 2024 Reviewers invited by journal 08 Jun, 2024 Editor assigned by journal 08 Jun, 2024 Editor invited by journal 24 May, 2024 Submission checks completed at journal 24 May, 2024 First submitted to journal 19 May, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4443746","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":310023903,"identity":"9a7becdb-137e-4767-9dda-8b9b5ebf22cd","order_by":0,"name":"Fentahun Yene","email":"","orcid":"","institution":"Bahir Dar University","correspondingAuthor":false,"prefix":"","firstName":"Fentahun","middleName":"","lastName":"Yene","suffix":""},{"id":310023904,"identity":"9374dd34-a3bc-43dd-bf77-f02efc9e1e8e","order_by":1,"name":"Berihun Bantie","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA60lEQVRIiWNgGAWjYBACAyA+DMQJYN4HIGZjJ14LMwPjDJAWZiK0MMO0MPMwQLn4gDl778PDhW138vhn9x98bPNrmzwf0LYPH3Nwa7HsOW5weGbbs2KJO4eZjXP7bhu2AW2TnLkNj8NupDEc5m07nNhwI5lNOrfnNiNQCxszLz4t959BtMy/kcz+27Lntj1hLTfYIFo2AG1hZvhxO5GgFsseoMN4zh0uNryRbCzZ23A7uY2ZsRmvX8zZjzF/5ik7nCd3I/Hhhx9/btvOb28++OEjHi2ogLENTDYQqx4E/pCieBSMglEwCkYKAADFZlOV8AMFngAAAABJRU5ErkJggg==","orcid":"","institution":"Debre Tabor University","correspondingAuthor":true,"prefix":"","firstName":"Berihun","middleName":"","lastName":"Bantie","suffix":""},{"id":310023905,"identity":"6d893aa5-d80c-48d4-90b9-0d9b797e05a6","order_by":2,"name":"Tarekegn Yilma","email":"","orcid":"","institution":"Wogeda Primary hospital","correspondingAuthor":false,"prefix":"","firstName":"Tarekegn","middleName":"","lastName":"Yilma","suffix":""},{"id":310023906,"identity":"0272f255-b683-48d2-bc19-6ac3c592affb","order_by":3,"name":"Idalamin Zinab","email":"","orcid":"","institution":"Jimma University","correspondingAuthor":false,"prefix":"","firstName":"Idalamin","middleName":"","lastName":"Zinab","suffix":""},{"id":310023907,"identity":"351d82ad-a84e-41a6-815e-1b04fe299774","order_by":4,"name":"Simachew Animen","email":"","orcid":"","institution":"Bahir Dar University","correspondingAuthor":false,"prefix":"","firstName":"Simachew","middleName":"","lastName":"Animen","suffix":""}],"badges":[],"createdAt":"2024-05-19 09:38:22","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4443746/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4443746/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1038/s41598-024-80247-y","type":"published","date":"2025-07-02T15:58:04+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":58147742,"identity":"95d48a25-0226-4e38-89a3-0365a0b34900","added_by":"auto","created_at":"2024-06-11 18:44:43","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":24529,"visible":true,"origin":"","legend":"\u003cp\u003eSchematic presentation of sampling procedure among pregnant women in the peri-urban kebeles of Jimma town, south west Ethiopia, 2023.\u003c/p\u003e","description":"","filename":"OnlineFig1.SamplingprocedureforNonprescribeddrugusestatusinJimmatown.png","url":"https://assets-eu.researchsquare.com/files/rs-4443746/v1/23644972a75016c35e28265f.png"},{"id":58147740,"identity":"8e1c4f1d-3093-403a-b347-2f37a749bbb9","added_by":"auto","created_at":"2024-06-11 18:44:43","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":6166,"visible":true,"origin":"","legend":"\u003cp\u003eMagnitude of non-prescribed drugs among pregnant women in the peri-urban kebeles of Jimma town, southwest Ethiopia, 2023.\u003c/p\u003e","description":"","filename":"OnlineFig2.NonprescribeddrugusestatusinJimmatown.png","url":"https://assets-eu.researchsquare.com/files/rs-4443746/v1/95897ff6195c4c2da55497dd.png"},{"id":58148145,"identity":"95296844-69d8-4ed8-8191-f9907d76b2fc","added_by":"auto","created_at":"2024-06-11 18:52:43","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":17209,"visible":true,"origin":"","legend":"\u003cp\u003eCommon reasons for the utilization of non-prescribed drug among pregnant women in the peri-urban kebeles of Jimma town, southwest Ethiopia, 2023\u003c/p\u003e","description":"","filename":"OnlineFig3.Commonreasonsforusingnonprescribeddrugs.png","url":"https://assets-eu.researchsquare.com/files/rs-4443746/v1/50d628598732d428f22c332a.png"},{"id":86179754,"identity":"08af606d-0d55-4420-b88b-d1544ef2258d","added_by":"auto","created_at":"2025-07-07 16:19:22","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1063724,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4443746/v1/afc211c5-ac2e-47fa-b337-6f85faf0d85c.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Burden of Non-prescribed drug use and its associated factors among Pregnant Women in Peri-urban kebeles’ of Jimma town, southwest Ethiopia, 2023","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eNon-prescribed drug use or self-medication is defined as the act of utilizing medications by patients to treat self-diagnosed health and health-related problems without getting advice from a healthcare provider. Pregnant women are among the most vulnerable groups for using non-prescribed drugs to prevent and/or treat pregnancy-related issues such as abortion, mood disorders, and anemia. Globally, 22%-44% of pregnant women are reported to use non-prescribed drugs. Despite the fact that non-prescribed drug use is increasing worldwide, its burden is particularly high in low and middle-income countries due to poor medical services and a lack of professional control of pharmaceutical products, which is estimated to be greater than 31.5%. In Ethiopia, the extent of non-prescribed drug use is high and varies significantly across regions and communities, influenced by different cultural practices and perspectives [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. For instance, its burden ranges from 7.8% in the Tigray region [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e], 45.2% in Nekmte town[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e] to 69.4% in Harar town [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Though recent evidences were limited, a prior meta-analysis study also revealed that more than 30% of the pregnant mothers in Ethiopia practice self \u0026ndash;medication [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe high prevalence of non-prescribed drug utilization among pregnant women can seriously affect the health of both the mother and fetus, potentially causing detrimental adverse effects such as congenital birth defects, miscarriage, and allergic diseases. It has been reported that at least 10% of birth defects result from the exposure of pregnant women to drugs, with the risk being particularly heightened during the first trimester of pregnancy [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Additionally, the increased practice of self-medication exacerbates the occurrence of drug interactions and adverse events. Pregnant women\u0026rsquo;s might frequently utilize non-prescribed drug due to numerous religious and cultural values and beliefs such as for the purpose of treating their psychological distress and other pregnancy -related complications[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. In most developing countries like Ethiopia, in addition to the cultural perspectives, other several factors including poor access to health facility, socioeconomic status, age, gender, education level, occupation, lack of awareness of their side effects and interactions, time, perception of the risk of self-medication, previous medication use, gestational age, and experience of pregnancy-related complications affects the Non-prescribed drug utilization status of pregnant mothers [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan additionalcitationids=\"CR9 CR10 CR11\" citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe government of Ethiopia gives substantial emphasis on prioritizing the health and well-being of mothers and neonates[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Although non-prescribed drug use is difficult to eliminate, intervention can be made to minimize the burden of this malpractice. This requires extensive knowledge on the level and risk factors contributing to the increased prevalence of non-prescribed drug utilization among pregnant mothers in a certain geographical areas. In this regard, though there are several studies that asses the level of self-medication practice among pregnant women in Ethiopia, most of them were institution based which will not represent the general population. Hence, this study is aimed to investigate the use utilization status and associated factors associate of non-prescribed drug among pregnant women in peri-urban kebeles of Jimma town, south west Ethiopia.\u003c/p\u003e"},{"header":"2. Methods and materials","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Study area, period and design\u003c/h2\u003e \u003cp\u003eThis study was conducted among pregnant women in the peri-urban kebeles of Jimma town, south-west Ethiopia, from January 20 to March 1, 2023. Jimma town is located 352 kilometres south-west of Addis Abeba, the capital city of Ethiopia[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. In the town, there are about 17 kebele\u0026rsquo;s, of which 5 are peri-urban areas (Jireen, Qofe, Haro gibe, Bore, and Ifa bula). There are about 4,686 households in these peri-urban kebeles. A community based cross sectional study was employed to assess the use and factors associated with non-prescribed drug among pregnant women in peri-urban kebeles of Jimma town, south west Ethiopia, 2023\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Source and study population\u003c/h2\u003e \u003cp\u003eThe source population was all pregnant women who have been residing in the study area for at least six months. Whereas, all pregnant women are in peri-urban kebeles of Jimma town and presented in the data collection period were the study populations. Pregnant mothers who were not mentally competent to provide adequate information were excluded from the study.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Sample size determination and sampling technique\u003c/h2\u003e \u003cp\u003eThe sample size for this study was determined using EPINFO version 7.2.3.1 software through a single population proportion formula. Considering parameters like 80% power, 95% confidence level, 5% marginal error, 69.4% prevalence of non-prescribed drug use among pregnant women in Harar town, and 10% non-response rate, a final sample size of 360 pregnant mothers were included in this study. Study participants were selected using systematic random sampling techniques. Initially, the total number of pregnant women and household numbers were obtained from health extension workers in each keble. The total calculated sample size (n = 360) was proportionally allocated to each kebele. Finally, systematic sampling techniques (every k = 3 interval) were used to select the final eligible study participants. In the case of more than one pregnant woman per household, only one pregnant woman was selected randomly to reduce selection bias (Fig 1).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFigure 1: Schematic presentation of sampling procedure among pregnant women in the peri-urban kebeles of Jimma town, south west Ethiopia, 2023.\u003c/p\u003e\u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 .Study variable\u003c/h2\u003e \u003cp\u003eThe main exposure variable for this study was the presence or absence of Non-prescribed drug use (yes/no). Whereas, variables socio-demographic variables (age, income, educational level), Pregnancy and health related factors ( history of abortion, gravidity, number of living children, previous pregnancy related problems ), health service delivery-related factors (distance from health facility, and health insurance enrollment ) and behavior related factors (perceived status of the disease, previous experiences of non-prescribed drug use).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Operational definitions\u003c/h2\u003e \u003cp\u003eNon-prescribed drug is the use of non-prescription medications to treat self-diagnosed disorders or symptoms, without consulting a physician and without any health professional supervision. Pregnancy related complications were defined as those problems that are specifically linked to the pregnant state as well as conditions that commonly occur incidentally in women who are pregnant which includes pregnancy related hypertension, premature rupture of membranes, pre-term labor or birth, antepartum hemorrhage, headache, vaginal discharge, abdominal cramp [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. The income status of the participants were categorized as low (\u0026le;\u0026thinsp;1,025), lower middle (1,026\u0026thinsp;\u0026minus;\u0026thinsp;3,995) ,upper middle(3,996\u0026thinsp;\u0026minus;\u0026thinsp;12,375 ) and upper (\u0026gt;\u0026thinsp;12,375) based on the 2018 international monetary fund (IMF) income level scale for Ethiopia[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Gravidity was defined as the sum of all pregnancies, including all live births and pregnancies that terminated at \u0026lt;\u0026thinsp;6 months or did not result in a live birth [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.6 Data collection techniques and tools\u003c/h2\u003e \u003cp\u003eA pretested interviewer administered standard questionnaire was developed after thoroughly reviewing the findings of prior related literatures. The questionnaire was initially prepared in English and translated to Afan Oromo and Amharic, then back to English to ensure consistency between the original and translated questionnaires. To ensure data quality, a pre-test was conducted on 5% (18) of the households at Ginjo Kebele of Jimma town, south west Ethiopia. Data were collected by five trained BSc Midwifery professionals. Additionally, one-day training was given for data collectors and supervisors about the objective of the study, how to obtain consent from participants, and how to ensure the confidentiality of the patient information. The collected data was checked for completeness every day before the following day of data collection by supervisors and the principal investigator, and corrective measures were taken according to the findings during supervision.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e2.7 Data processing and analysis\u003c/h2\u003e \u003cp\u003eThe data was entered using Epi-data version 7.2.2.2 statistical software and analyzed using SPSS version 25 statistical package. Descriptive statistics such as frequencies with percentage, mean with standard deviation were used to describe the study population sociodemographic and other characteristics. Logistic regression model was used to fit the data to identify factors associated with non-prescribed drug use. Variables with a P-value of \u0026lt;\u0026thinsp;0.25 in the simple binary logistic regression model were fitted to the multivariable binary logistic regression model, and finally, the level of significance was declared at a p-value of \u0026lt;\u0026thinsp;0.05. The backward likelihood ratio elimination method was used to identify factors which are significantly associated with the non-prescribed drug \u0026ndash;use pattern. The overall goodness of the model with the fitted data was evaluated using the \"Hosmer and Lomeshow\" goodness of fit test. Finally, the result of this study was presented in texts, graphs and tables\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e2.8 Ethical considerations\u003c/h2\u003e \u003cp\u003e An ethical approval letter was obtained from the Institutional Review Board (IRB) of Bahirdar University with a protocol number of BDU 651/2022, and then a supportive letter was written to Jimma Town Health Administration and each kebele administration. Verbal informed consent was obtained from the mothers after explaining the purpose and benefit of the study. Confidentiality was assured to all informants, and their anonymity was guaranteed as no name or identification of the parent or study participant pregnant women was collected during the interview. Furthermore, all methods were carried out in accordance with relevant guidelines and regulations.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Result","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Result of Socio-demographic characteristics\u003c/h2\u003e \u003cp\u003e From 360 samples, 358 (99.4%) pregnant women were participated in the study .The Mean age of the study participants were 25.06 years with the standard deviation of \u0026plusmn;\u0026thinsp;4.25 years). Only 59 (16.5%) of the study participants were unable to read and write. Regarding the occupational status of the mother, majority (98.6%) of the study participants were housewife ( Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e) .\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSocio-demographic characteristics of pregnant women in Jimma town peri-urban kebeles, southwest Ethiopia, 2023 (N\u0026thinsp;=\u0026thinsp;358)\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\u003eVariables ((N\u0026thinsp;=\u0026thinsp;358)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCategory\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFrequency(n\u0026thinsp;=\u0026thinsp;358)\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=\"4\" rowspan=\"5\"\u003e \u003cp\u003eAge of respondents in years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e15\u0026ndash;19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20\u0026ndash;24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e118\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32.96\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25\u0026ndash;34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e168\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e46.92\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e35-and above\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eMean age\u0026thinsp;=\u0026thinsp;25.06 years, Standard deviation\u0026thinsp;\u0026plusmn;\u0026thinsp;4.25 years\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMarital status\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMarried\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e353\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e98.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNot married\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eOccupation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ehousewife\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e271\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e75.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEmployed\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMerchant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e12.57\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFarmer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eEducational status of women\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCan\u0026rsquo;t read and write\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCan read and write\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.9\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\u003e163\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e45.5\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\u003e56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCollege and above\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003eEducational status of husband\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCan\u0026rsquo;t read and write\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCan read and write\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.1\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\u003e126\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e35.2\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\u003e77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCollege and above\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eHealth Insurance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e269\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e75.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eAverage monthly income*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLow\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e106\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLower middle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e154\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e43\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUpper middle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27.4\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/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Maternal and Obstetric history of the respondents\u003c/h2\u003e \u003cp\u003eDuring the current pregnancy, 302 (84.36%) of the respondents attended Antenatal care (ANC) visits. About 117 (32.7%) pregnant women experienced health problems during pregnancy. Constipation was the most common complaint that the pregnant women\u0026rsquo;s experienced during pregnancy, accounting for 61 (45.2%) (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\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\u003e\u003cb\u003eObstetric history of pregnant women in peri-urban kebeles of Jimma town, south west Ethiopia, 2023\u003c/b\u003e.\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\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCategory\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eFrequency\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\u003eGravidity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrimigravda\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24.86%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMultigravida\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e269\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e75.14%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eNumber of children\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo child\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u0026ndash;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e202\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e56.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026gt;\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eANC follow up\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e302\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e84.36%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.64%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eHealth education on non-prescribed drug\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.45%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e317\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e88.56%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePrevious pregnancy and delivery related problems\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e316\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e88.27%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.73\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"6\" rowspan=\"7\"\u003e \u003cp\u003eType of previous pregnancy and delivery related problems\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNausea and vomiting\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16.23%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eheart burn\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18.2%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eback pain\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8.11%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHeadache\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e19.23%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003evaginal discharge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.44%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eabdominal cramp\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.70%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eConstipation\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20.74%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCurrent pregnancy and delivery related problems\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e241\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e67.32%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e117*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32.68%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"8\" rowspan=\"9\"\u003e \u003cp\u003eType of current pregnancy and delivery related problems\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNausea and vomiting\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33.33%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eheart burn\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e35.56%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eback pain\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.07%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHeadache\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e43.7%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003evaginal discharge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.67%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eabdominal cramp\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5.93%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eConstipation\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\u003e45.2%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.44%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ecommon cold\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e13.3%\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/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Magnitude of non-prescribed drug use\u003c/h2\u003e \u003cp\u003eIn the current study, the magnitude of non-prescribed drug use during pregnancy found to be 37.7% (95% CI: 33.4\u0026ndash;42.0) (Fig.\u0026nbsp;2). The most common reason for using Non-prescribed drug was the easy availability of these non-prescribed drugs over the health institutions which account about 116 (85.92%) (Fig.\u0026nbsp;3).\u003c/p\u003e \u003cp\u003e \u003cb\u003eFigure 2\u003c/b\u003e. Magnitude of non-prescribed drugs among pregnant women in the peri-urban kebeles of Jimma town, southwest Ethiopia, 2023(358)n=\u003c/p\u003e \u003cp\u003e \u003cb\u003eFigure 3\u003c/b\u003e. Common reasons for the utilization of non-prescribed drug among pregnant women in the peri-urban kebeles of Jimma town, southwest Ethiopia, 2023\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e3.4. Factors associated with the use of non-prescribed drug during pregnancy\u003c/h2\u003e \u003cp\u003eIn the final multivariable logistic regression model, at 5% of the level of significance, the following variables, namely being enrolled in health insurance, history of health problems during the current pregnancy, and gravidity were found to be significant predictors of non-prescribed drug use during pregnancy. In this aspect, the odd of non-prescribed drug use was found to be 79% times less likely among pregnant women\u0026rsquo;s who were enrolled in health insurance compared with their counterparts (AOR\u0026thinsp;=\u0026thinsp;0.21, 95% CI: 0.03\u0026ndash;0.76). Primigravida mothers 3.05 times more likely to practice non-prescribed drugs compared with their counterparts (AOR\u0026thinsp;=\u0026thinsp;3.05, 95% CI: 1.03\u0026ndash;5.08). Furthermore, this study also showed that the odd of utilizing non-prescribed drug in pregnant women\u0026rsquo;s who experienced any pregnancy \u0026ndash; related problems was 2.34 times higher than their counterparts (AOR\u0026thinsp;=\u0026thinsp;2. 34, 95%CI:1.99\u0026ndash;2.76) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBivariable and multivariable logistic regression analysis of factors associated with utilization of non-prescribed among pregnant women in Jimma town peri- urban kebeles, Southwest Ethiopia, 2023 (n\u0026thinsp;=\u0026thinsp;358)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\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 \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003eNon-described\u003c/p\u003e \u003cp\u003edrug use\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCOR (95%CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAOR(95% CI)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eDistance from health facility\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eClose\u0026thinsp;\u0026le;\u0026thinsp;30min\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSomewhat far 30-60min\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11.7(4.31\u0026ndash;26.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.32(0.05\u0026ndash;4.18)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFar\u0026thinsp;\u0026ge;\u0026thinsp;60min\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3.48(1.32\u0026ndash;9.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.41(0.06\u0026ndash;2.72)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eBeing enrolled to health insurance\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e59\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e195\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.11(0.06\u0026ndash;0.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.21(0.03\u0026ndash;0.76)*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1.00\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePresence of pregnancy related complications\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6.87 (1.84 11.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2. 34 (1.99\u0026ndash;2.76)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e56\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e185\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eWaiting time at health institutions\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNormal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e150\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eShort\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4.75 (1.07\u0026ndash;8.43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.08(0.01\u0026ndash;1.06)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLong\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e64\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8.51(4.3-13.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.32(0.54\u0026ndash;7.77)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eGravidity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrimigravda\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.61(1.01\u0026ndash;2.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e3.05(1.03\u0026ndash;5.08)*\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMultigravida\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e116\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e153\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePrevious experience of self-medication\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e110\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.15 (0.65\u0026ndash;1.65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.89 (0.7\u0026ndash;1.08\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCounselled about self-medication\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e190\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.39(0.23\u0026ndash;0.68)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.05(0.02\u0026ndash;0.31)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"6\" nameend=\"c6\" namest=\"c1\"\u003e \u003cp\u003eAOR- Adjusted odds ratio, COR- Crude odds ratio, CI- confidence interval, Bold letter- significantly associated factors, *p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05, **p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.01\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/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThis research tried to assess non-prescribed drug use and its associated factors among pregnant women in Jimma town, peri-urban Kebeles, south-west Ethiopia. Despite the potential harmful effect of self-mediation during pregnancy, 135 (37.7%, 95%CI: 32.8\u0026ndash;41.7%) of pregnant women used non-prescribed drugs during their pregnancy. This finding is in line with the study conducted at Jimma University medical centre, in Ayder comprehensive specialized hospital, in Iran, and in the United Arab Emirates [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan additionalcitationids=\"CR20\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Moreover, this figure is higher than the findings of the study conducted in Addis Ababa, in Goba Town located in souteast Ethiopia and in South Africa [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. These variations could be attributed to the differences in population demographics, over-the-counter sale of most medications in drugstores and inadequate access to healthcare services. On the contrary, the findings of this study were lower than the results of studies done in Harari town in Ethiopia, Ghana, and Tanzania [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. This discrepancy could be due to the presence easily accessibility of over the counter medication in Jimma town and due to the differences in drug regulation policies in different countries.\u003c/p\u003e \u003cp\u003eIn the present study, the most commonly reported reasons for using non-prescribed drugs during pregnancy were ease of access to medicines, feeling that disease is minor, low cost, and prolonged waiting time. In agreement with our study, similar findings were reported from previous studies conducted in Addis Ababa and the Democratic Republic of the Congo[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. The possible explanation might be the lack of attention and priorities of health policymakers and other stakeholders on the burden of self-medication risks [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Therefore, necessary measures should be taken to strengthen the regulatory system and enforce regulations so as to reduce the practice of non-prescribed drugs during pregnancy.\u003c/p\u003e \u003cp\u003eThis study showed that pregnant women who were enrolled in health insurance were 79% less likely to use non-prescribed drugs than women without health insurance (AOR 0.24, 95% CI: 0.03\u0026ndash;0.76). This is supported by the results of the study conducted in Ayder Comprehensive Hospital, Tigray region and in Iran[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. The possible explanation for the observed association might be due to the fact that being enrolled to health insurance would increase healthcare utilization of individuals [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], thereby reducing the necessity for utilization of non-prescribed drugs. This result might indicate a need for public insurance coverage for all people in the community.\u003c/p\u003e \u003cp\u003eIn this research, pregnant women who had experienced pregnancy-related problems were. 2.34 times more likely to use non-prescribed drug use compared with their counterparts. This finding is supported by literatures conducted in southeast Ethiopia, Jordan, Indonesia, Western Nepa and a systematic review and meta-analysis report of 13 studies [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan additionalcitationids=\"CR29 CR30\" citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. The possible elucidation for the observed association might be since pregnancy-related complications were both physically and emotionally overwhelmed[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e], mothers might seek self-medication in order to alleviate their symptoms promptly and get immediate solution.\u003c/p\u003e \u003cp\u003eFurthermore, this study also showed that the odd of non-prescribed drug use was 3.05 times more likely among prmigravida women\u0026rsquo;s than mutigravida women\u0026rsquo;s. This finding is in agreement with prior studies conducted in Mizan-Tepi University Teaching Hospital, Southwest Ethiopia, in Tanzania and Indonesia [\u003cspan additionalcitationids=\"CR34\" citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. The possible explanation for the observed association would primigravida women may have limited knowledge about the potential risks and safety concerns associated with medication use during pregnancy, making them more likely to use self-medication without understanding the potential harm it can cause. Indeed, women\u0026rsquo;s experiencing pregnancy-related problems for the first time may lack experience and knowledge about these complications. They may feel anxious or uncertain about seeking medical advice, leading them to look for alternative solutions like self-medication.\u003c/p\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e4.1. Limitation of the study\u003c/h2\u003e \u003cp\u003eThe limitation of this study might be the study being prone to recall bias that may affect the result of this study, because the pregnant women might not remember the types of drug they used. The other possible limitation could be women in early pregnancy might not have the chance yet to use medications consequently affecting the reported results on drugs commonly used during pregnancy.\u003c/p\u003e \u003c/div\u003e"},{"header":"5. Conclusion and recommendation","content":"\u003cp\u003eThis community based cross-sectional study has revealed that significant number of pregnant mothers in used self- medication during their pregnancy time. Being enrolled in to health insurance, experiencing pregnancy-related complications and gravidity were found to be the factors affecting the utilization of non-prescribed drugs. Therefore, special attention need to be given for first time pregnant women\u0026rsquo;s and the government has to work to increase community\u0026rsquo;s engagement on health insurance programs.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eANC -Ante Natal Care, BDU - Bahir Dar University, ETB- Ethiopian Birr, HMIS-Health Management Information System, JUMC- Jimma University Medical Centre, NGO-Non-Governmental Organization, , SM - Self-Medication , WHO- World Health Organization\u003c/p\u003e"},{"header":"Declarations","content":"\u003ch2\u003eEthical Approval and Consent to participate \u0026nbsp;\u003c/h2\u003e\n\u003cp\u003e\u0026nbsp;An ethical approval letter was obtained from the Institutional Review Board (IRB) of Bahirdar University with a protocol number of BDU 651/2022, and then a supportive letter was written to Jimma Town Health Administration and each kebele administrations. Verbal informed consent was obtained from the mothers after explaining the purpose and benefit of the study. Confidentiality was assured to all informants, and their anonymity was guaranteed as no name or identification of the parent or study participant pregnant women was collected during the interview. \u0026nbsp;Furthermore, all methods were carried out in accordance with relevant guidelines and regulations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for Publication\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data that have been used to support the conclusion of this study are available in the manuscript the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no conflicts of interest for this work.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003eFunds\u003c/h2\u003e\n\u003cp\u003eThis study had no specific funding.\u003c/p\u003e\n\u003ch2\u003eAuthors contribution \u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eAll the authors made significant contributions to the improvement of this manuscript. IZ, FY, and SM participated in the synthesizing the research question, formulating research objectives, data extraction, analysis, interpretation and conclusion of the finding the study. BB and TY were participated in data extraction, analysis, interpretation and preparing the initial draft of the manuscript. All authors had thoroughly read and approved the manuscript. \u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eMekuria AB, Erku DA, Gebresillassie BM, Birru EM, Tizazu B, Ahmedin A: Prevalence and associated factors of herbal medicine use among pregnant women on antenatal care follow-up at University of Gondar referral and teaching hospital, Ethiopia: a cross-sectional study. BMC complementary and alternative medicine 2017, 17:1\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEticha T, Mesfin K: Self-medication practices in Mekelle, Ethiopia. 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Patient Education and Counseling 2020, 103(10):2142\u0026ndash;2154.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWernli KJ, Wang Y, Zheng Y, Potter JD, Newcomb PA: The relationship between gravidity and parity and colorectal cancer risk. Journal of women's health (2002) 2009, 18(7):995\u0026ndash;1001.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBotyar M, Kashanian M, Abadi ZRH, Noor MH, Khoramroudi R, Monfaredi M, Nasehe G: A comparison of the frequency, risk factors, and type of self-medication in pregnant and nonpregnant women presenting to Shahid Akbar Abadi Teaching Hospital in Tehran. Journal of family medicine and primary care 2018, 7(1):124.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAbduelkarem AR, Mustafa H: Use of over-the-counter medication among pregnant women in Sharjah, United Arab Emirates. Journal of pregnancy 2017, 2017.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNiriayo YL, Mohammed K, Asgedom SW, Demoz GT, Wahdey S, Gidey K: Self-medication practice and contributing factors among pregnant women. PloS one 2021, 16(5):e0251725.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBulabula AN, Dramowski A, Mehtar S: Antibiotic use in pregnancy: knowledge, attitudes and practices among pregnant women in Cape Town, South Africa. Journal of Antimicrobial Chemotherapy 2020, 75(2):473\u0026ndash;481.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBeyene KGM, Beza SW: Self-medication practice and associated factors among pregnant women in Addis Ababa, Ethiopia. Tropical medicine and health 2018, 46:1\u0026ndash;14.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOleke F: Prevalence and Factors Associated with Self-Medication Among Pregnant Women Attending Antenatal Care at Lira Regional Referral Hospital. J Biomed Biosens 2022, 2:60\u0026ndash;76.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMarwa KJ, Njalika A, Ruganuza D, Katabalo D, Kamugisha E: Self-medication among pregnant women attending antenatal clinic at Makongoro health centre in Mwanza, Tanzania: a challenge to health systems. BMC pregnancy and childbirth 2018, 18(1):1\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKarimy M, Rezaee-Momtaz M, Tavousi M, Montazeri A, Araban M: Risk factors associated with self-medication among women in Iran. BMC public health 2019, 19(1):1\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTilahun H, Atnafu DD, Asrade G, Minyihun A, Alemu YM: Factors for healthcare utilization and effect of mutual health insurance on healthcare utilization in rural communities of South Achefer Woreda, North West, Ethiopia. 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Bio Med Central Family Practice 2002, 3.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMohseni M, Azami-Aghdash S, Sheyklo SG, Moosavi A, Nakhaee M, Pournaghi-Azar F, Rezapour A: Prevalence and reasons of self-medication in pregnant women: a systematic review and meta-analysis. International journal of community based nursing and midwifery 2018, 6(4):272.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZewdu B, Belachew T, Ahmed K, Tilahun L, Dagnaw K: Incidence and determinants of diabetic ketoacidosis among people with diabetes in Woldiya comprehensive specialized hospital, Ethiopia: a retrospective cohort study. BMC Endocrine Disorders 2024, 24(1):34.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKatabalo D, Robert D, Mwita S, Minja W, Abbas S: Self-Medication during First Trimester Among Pregnant Women Attending Antenatal Care Clinic at a District Hospital in Mwanza, North-western Tanzania. J Preg Child Health 2022, 5:119.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKahssay SW, Tadege G, Muhammed F: Self-medication practice with modern and herbal medicines and associated factors among pregnant women attending antenatal care at Mizan-Tepi University Teaching Hospital, Southwest Ethiopia. Heliyon 2022, 8(9).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAtmadani RN, Nkoka O, Yunita SL, Chen Y-H: Self-medication and knowledge among pregnant women attending primary healthcare services in Malang, Indonesia: a cross-sectional study. BMC pregnancy and childbirth 2020, 20:1\u0026ndash;11.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"non-prescribed drug use, associated factors, pregnant women, Ethiopia","lastPublishedDoi":"10.21203/rs.3.rs-4443746/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4443746/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBackground: Non-prescribed drug utilization is the act of using medication to treat self-diagnosed problems without consulting a healthcare provider. Pregnant women are among the most vulnerable population groups for self-medication to treat pregnancy-related problems. The use of non-prescribed drugs, however, has numerous detrimental effects on both the growing fetus and the mother. Besides, community-based information regarding the pattern of non-prescribed drug use is limited in Ethiopia. Hence, this study aims to investigate non-prescribed drug use and its associated factors among pregnant women in Jimma town, southwest Ethiopia, in 2023.\u003c/p\u003e\n\u003cp\u003eMethod and Materials: A community-based cross-sectional study was conducted among 358 pregnant mothers in the peri-urban kebeles of Jimma town, southwest Ethiopia. A systematic random sampling technique (every K = 3 households) was used to select the final study participants. Data were collected using an interviewer-administered structured questionnaire, entered into EpiData version 7.2.2 software, and exported to SPSS version 25 for further analysis. Both bivariable and multivariable logistic regression models were fitted to identify the factors influencing non-prescribed drug utilization status. The level of significance of the association was determined at a P-value \u0026lt; 0.05 with a 95% CI.\u003c/p\u003e\n\u003cp\u003eResult: Overall, the prevalence of non-prescribed drug use among pregnant mothers was 37.7% (95% CI: 32.8–41.7%). Enrollment in health insurance (AOR = 0.21, 95% CI: 0.03–0.76), being primigravida (AOR = 3.05, 95% CI: 1.03–5.08), and experiencing any pregnancy-related complications (AOR = 2.34, 95% CI: 1.99–2.76) were found to be significant factors affecting the non-prescribed drug utilization status of pregnant mothers.\u003c/p\u003e\n\u003cp\u003eConclusion and recommendations: \u0026nbsp;In the current study, non-prescribed drug use among pregnant mothers was high. Health insurance enrollment status, gravidity, and the presence of any pregnancy-related complications were identified as significant predictors of non-prescribed drug use among pregnant mothers. Hence, stakeholders should invest their efforts in increasing community enrollment in health insurance programs and place special emphasis on high-risk groups prone to non-prescribed drug use.\u003c/p\u003e","manuscriptTitle":"Burden of Non-prescribed drug use and its associated factors among Pregnant Women in Peri-urban kebeles’ of Jimma town, southwest Ethiopia, 2023","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-06-11 18:44:38","doi":"10.21203/rs.3.rs-4443746/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-08-13T06:24:47+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-07-18T13:55:33+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"78689706601693092221422156606612762327","date":"2024-07-04T13:38:22+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-06-19T07:42:48+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"337194914451919107362570763475476717158","date":"2024-06-19T07:28:46+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-06-09T01:50:07+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-06-09T01:47:53+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2024-05-24T12:47:11+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-05-24T12:45:54+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2024-05-19T09:25:04+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"6b8e8a57-9044-425d-8051-564384364713","owner":[],"postedDate":"June 11th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":32759462,"name":"Health sciences/Medical research/Epidemiology"},{"id":32759463,"name":"Health sciences/Health care/Drug regulation"},{"id":32759464,"name":"Health sciences/Health care/Health policy"},{"id":32759465,"name":"Health sciences/Health care/Health services"}],"tags":[],"updatedAt":"2025-07-07T16:11:28+00:00","versionOfRecord":{"articleIdentity":"rs-4443746","link":"https://doi.org/10.1038/s41598-024-80247-y","journal":{"identity":"scientific-reports","isVorOnly":false,"title":"Scientific Reports"},"publishedOn":"2025-07-02 15:58:04","publishedOnDateReadable":"July 2nd, 2025"},"versionCreatedAt":"2024-06-11 18:44:38","video":"","vorDoi":"10.1038/s41598-024-80247-y","vorDoiUrl":"https://doi.org/10.1038/s41598-024-80247-y","workflowStages":[]},"version":"v1","identity":"rs-4443746","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4443746","identity":"rs-4443746","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}