Determinants of premature membrane rupture among mothers receiving labor care at different public hospitals in Northeast Ethiopia: An unmatched case control study

Determinants of premature membrane rupture among mothers receiving labor care at different public hospitals in Northeast Ethiopia: An unmatched case control study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Determinants of premature membrane rupture among mothers receiving labor care at different public hospitals in Northeast Ethiopia: An unmatched case control study Selamyhun Tadesse Yosef, Elsabeth Adissu, Muluken Amare, Melaku Ashagire, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4047358/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background : Premature rupture of membranes is a painless gush of amniotic fluid resulting from the rupture of membranes through the vaginal canal before the onset of uterine contractions and is responsible for increased perinatal mortality and neonatal morbidity. Therefore, identifying the determining factors is essential for minimizing its adverse impact. Despite the existence of this problem in the study area, there is a gap in identifying the factors affecting its occurrence. Objectives : To assess the determinants of prematuremembrane rupture among mothers who attendedlabor at public hospitals in theNorth Wollo Zone, 2022/23. Methods : An unmatched case‒controlstudy was conducted from December 1, 2022, to March 30, 2023. Three public hospitals were selected through a lottery method, and by proportional allocation, a total of 353 participants (118 cases and 235 controls) receiving labor were recruited. Cases were selected through convenience sampling, while controls were recruited through systematic random sampling. The datawere collected using a structured questionnaire and card review, entered into EpiData 4.6 and analyzed using STATA version 17. Logistic regression was employed to identify determinants, and a P value < 0.05 in multivariable logistic regression was considered to indicate statistical significance. Results : Previous caesarian section (AOR: 2.11; 95% CI: 1.05–4.23), history of abortion (AOR: 3.68; 95% CI: 1.70–7.94), history of premature membrane rupture (AOR: 3.89; 95% CI: 1.73–8.71), chronic cough (AOR: 4.23; 95% CI: 1.47–12.18), mid-upper arm circumference <23 cm (AOR: 3.47; 95% CI: 1.53–7.84), suspected sepsis (AOR: 2.99; 95% CI: 1.25–1.99), and presence of urinary tract infection (AOR: 3.14; 95% CI: 1.50–6.60) were determinants of premature membrane rupture. Conclusions : This study indicated that the aforementioned factors are determinants of premature membrane rupture. Therefore, hospitals need to increasethe proportion of vaginal deliveriesand provide strong advice regarding the complications of abortion. Moreover, early screening, diagnosis, and treatment should be applied for malnutrition, chronic cough, sepsis, and urinary tract infections. PROM Premature membrane rupture Determinant Public hospitals Labor care Northeast Ethiopia Unmatched case control Introductions Premature rupture of membranes (PROM) is a condition characterized by the painless release of amniotic fluid before the onset of labor, typically through the vaginal canal (1). It presents a significant public health concern associated with maternal, fetal, and neonatal complications, impacting 5 to 20% of global pregnancies, with higher rates observed in Africa and specific regions such as Ethiopia. It presents a significant public health concern associated with maternal, fetal, and neonatal complications, impacting 5 to 20% of global pregnancies, with higher rates observed in Africa and specific regions such as Ethiopia (2-6). PROM significantly increases perinatal mortality and neonatal morbidity due to the loss of the protective intrauterine barrier, increasing the risk of infection for both mothers and fetuses, particularly with prolonged latent periods and repeated vaginal examinations (7, 8). It leads to fetal and neonatal complications such as distress, respiratory syndrome, and preterm birth, contributing to more than 40% of preterm deliveries in some instances (4, 9, 10). Moreover, its impact extends to mothers, increasing the risk of infections, chorioamnionitis, placental abruption, and other serious complications (3, 10-12). The etiology of PROM is often unknown, but structural defects in the membrane, bacterial infections, and activation of catabolic enzymes such as collagenase are contributing factors (13, 14). Multiple risk factors contribute to PROM, including previous history of abortion or PROM, cesarean delivery, lack of antenatal care, malnutrition, abnormal vaginal discharge, urinary tract infection, smoking, anemia, parity, pregnancy-induced hypertension, gestational diabetes, and invasive procedures (5, 15-18). PROM cases are primarily identified through patient history and amniotic fluid examination, with additional improvement in detection using tests such as the nitrazine test or crystallography test. Repeated vaginal examinations in mothers with PROM are discouraged due to the elevated risk of bacterial infection (19). Upon confirmation of PROM, assessments of gestational age, labor, fetal distress, and sepsis are essential, followed by rehydration, close fetal monitoring, and antibiotic administration (20). Women with PROM should undergo close monitoring before attempting another pregnancy (9, 20). In Ethiopia, several strategies beyond medical intervention aim to minimize neonatal and maternal morbidity and mortality, including the development of PROM guidelines, continuous professional development for health professionals, the establishment of maternal waiting rooms, safe transportation for laboring women, facility capacity enhancement, and the provision of free maternal and neonatal health services (21, 22). Despite the above strategies and protocols for PROM diagnosis and management in Ethiopia, there is a lack of focus on identifying and preventing risk factors, which is leading to a stagnant reduction in neonatal morbidity and mortality rates. Despite the above strategies and protocols for PROM diagnosis and management in Ethiopia, there is a lack of focus on identifying and preventing risk factors, which is leading to a stagnant reduction in neonatal morbidity and mortality rates (23). Although few studies have been performed in Ethiopia, many of them are cross-sectional studies, and there is still a scarcity of data around the study area. Moreover, some variables, such as the presence of sepsis and chronic cough, were not included in those studies. Thus, this study aimed to assess the determinants of PROM at different hospitals in Northeast Ethiopia. Methods and materials Study design, period, and setting An institutional-based, unmatched case control study was conducted from December 1, 2022, to March 30, 2023, at different public hospitals in the North Wollo zone in northeastern Ethiopia. The North Wollo Zone has a total of six public hospitals: one comprehensive, one general, and four primary hospitals. The study was conducted at Woldia Comprehensive Specialized Hospital (WCSH), Lalibela General Hospital, and Mersa Primary Hospital. The abovementioned public hospitals are providing continuous maternal and child health services, including ANC and delivery services, around the area. Study population and eligibility criteria All women who visited the selected public hospitals for labor care, had a gestational age of more than 28 weeks, were diagnosed with PROM by clinicians and were admitted to the labor and maternity wards of each hospital during the study period were enrolled as cases. Moreover, all women who visited the selected hospitals for labor care, had a gestational age of more than 28 weeks, were not diagnosed with PROM, were confirmed by clinicians and were admitted to the labor and maternity wards of each hospital during the study period were included as controls. Those mothers who were initially assigned to the control group but later switched to the case group and those who were seriously ill during the data collection period were excluded from the study. Additionally, women who underwent artificial membrane rupture, who experienced maternal deterioration requiring immediate delivery, who experienced intrauterine fetal death, or whose cases were due to trauma or accidents were excluded. Sample size determinations The sample size was determined using the StatCalc menu of Epi Info version 7.2.5 statistical software for an unmatched case control study. The following assumptions were used: a 95% confidence level, 80% power, a case-to-control ratio of 1:2, a percentage of exposure among controls (proportion of no ANC visit among women without PROM), and a percentage of exposure among cases (proportion of no ANC visit among women with PROM). The percentages of patients with no ANC visits (27.9%) and controls with no ANC follow-up (14.0%) were taken from a study conducted in southern Ethiopia (15). Based on the above assumptions, the sample size was 321 (107 cases and 214 controls), and after adding for a 10% nonresponse rate, the final sample size for the study was 353 (118 cases and 235 controls). Sampling techniques and procedures Among the 6 public hospitals found in the zone, three public hospitals (WCSH, Lalibela Referral Hospital and Mersa Primary Hospital) were selected by the lottery method. Then, the number of cases and controls were allocated proportionally based on the same period of previous year pregnant women attended in each hospital. Therefore, from a total of 1707 study participants from the last year at WCSH, we selected 193 participants (64 cases and 129 controls); from 938 pregnant women at Lalibela General Hospital, we selected 106 participants (35 cases and 71 controls); and from Mersa Primary Hospital, a total of 478 pregnant women were admitted last year, and we selected 54 participants (18 cases and 36 controls). Finally, all patients were selected until the sample size was reached. Moreover, controls were selected by systematic random sampling. Following the admission of a specific case to the unit, two controls were randomly selected using a lottery method from a list of controls admitted to the same unit, and the kth of those controls was selected accordingly. The process of control selection commenced promptly after the selection of each patient. Operational definitions Mid-upper arm circumference: The nutritional status of the mothers was evaluated by measuring the mid-upper arm circumference, which was assessed at the midpoint between the tips of the shoulder and the elbow of the left arm using standard MUAC tape. The measurements were taken to the nearest 0.1 cm and recorded in the provided questionnaire as less than 23 cm and greater than or equal to 23 cm (24). Chronic cough: Participants with a persistent cough that lasts for at least eight weeks and often much longer (25). Gestational hypertension was defined as a pregnant mother with a blood pressure greater than or equal to 140 mmHg and/or diastolic blood pressure greater than or equal to 90 mmHg on two separate occasions at least four hours apart after 20 weeks of pregnancy when the previous blood pressure was normal (26). Suspected sepsis was defined as a temperature below 36.0°C or above 38.0°C for a minimum of 2 hours and 1 hour, respectively; white blood cell counts below 4 × 10^9/l or above 12 × 10^9/l, or more than 10% immature (band) forms; a heart rate surpassing 90 beats per minute for at least 1 hour; and a respiratory rate exceeding 20 breaths per minute for at least 1 hour. Sepsis was characterized by the presence of a minimum of two of these criteria in addition to the clinical suspicion of infection as determined by experienced senior clinicians (27). Urinary tract infection was defined as a positive result for nitrite and leucocyte esterase on a urine dipstick and the presence of red and white blood cells, squamous cells and bacteria on a urine microscope (28). Data collection methods and procedures Interviewer-administered questionnaires were used for data collection. The questionnaires were initially prepared in English and then translated to Amharic and returned to English to check consistency. A review of the cards was also performed to obtain information on some variables. Three midwifery professionals at each hospital were recruited for data collection. One BSc midwife in each hospital was assigned as a supervisor to supervise the data collection throughout the process at each health institution. Data quality control To ensure the quality of the data, data collection tools were used after intensive review of the relevant literature. Pretesting of the questionnaire was carried out on 5% of the sample at the Haik Primary Hospital. Based on the pretest results, all relevant corrections were made. One-day training was given to the data collectors and supervisors about confidentiality, the respondents’ rights, informed consent, the objective of the study, the techniques of the interview and the completion of the questionnaire. The completeness of the data was checked by the data collectors during the data collection and immediately after the data collection by the supervisor and principal investigator. Data analysis The generated data were entered into EpiData version 3.14.6 and exported to STATA version 17 for analysis. Categorical variables are presented as frequencies and percentages. Odds ratios with 95% confidence intervals were used to measure the strength of associations. Bivariable logistic regression was performed to determine the crude associations of the independent variables with the dependent variables. Variables with P values < 0.25 in the bivariable logistic regression were exported to the multivariable logistic regression model to control for confounding factors and to identify the independent predictors of PROM. There was no collinearity between variables (ranging from 1 to 2.3), and the Hosmer‒Lemeshow test yielded a P value of 0.387, indicating that the assumption was not violated and that the goodness of fit was not met, and statistical significance was confirmed at a P value < 0.05. Results Sociodemographic characteristics of the participants A total of 353 study participants (118 cases and 235 controls) were involved in the study, for a 100% response rate. The mean age of the patients was 31.13 years. (± 6.3 SD) and controls (28.63 yrs). (± 5.8 SD). The majority of the patients (69, 58.4%) and controls (168, 71.5%) were aged 20-35 years. More than half of the patients and controls were from urban areas (71 [60.2%] and 123 [52.3%]). Regarding occupation, the majority of participants in both the 36 (30.5%) and control groups (83 (36.6%) were house wives. In terms of religious status, 75 (63.6%) patients were Orthodox Tewahido, and the same was true for 134 (57%) controls (Table 1) . Table 1 : Sociodemographic characteristics of labor attending women at public hospitals of North Wollo Zone, 2022/2023 Variable(n=353) Case N (%) Control N (%) Age 35 42 (35.6) 44 (18.7) Residence Rural 47 (39.8) 112 (47.7) Urban 71(60.2) 123 (52.3) Occupation House wife 36 (30.5) 86 (36.6) Merchant 22 (18.6) 43 (18.3) Government employee 28 (23.7) 36 (15.3) Private 19 (16.1) 49 (20.9) Others* 13 (11.0) 21 (8.9) Educational status Cannot read and write 17 (14.4) 31 (13.2) Only read and write 20 (17.0) 54 (23.0) 1-8 Grade 37 (31.4) 56 (23.8) 9-12 grade 20 (17.0) 56 (23.8) College and above 24 (20.3) 38 (16.2) Marital status Married 104 (88.1) 212 (90.2) Not Married 14 (11.9) 23 (9.8) Religion Orthodox Tewahido 75 (63.6) 134 (57.0) Muslim 38 (32.2) 94 (40.0) Protestant 5 (4.2) 7 (3.0) Total 118 (100) 235 (100) Obstetric- related characteristics of the study participants Eighty-one (68.5%) patients and 142 (60.5%) controls had term pregnancies. Based on gravidity, more than ninety of the patients (109, 92.4%) and 219 (93.2%) of the controls were multigravida. Less than half of the patients (47, 43.1%) and one-tenth (26, 12.0%) of the controls had at least one episode of abortion during their lifetime. A history of PROM was more pronounced among patients than among controls (60 [55.0%] and 26 [12.0%], respectively). A total of 76 (69.7%) and 170 (78.3%) of the participants in both the case and control groups, respectively, desired the index pregnancy (Table 2) . Table 2 : Obstetrics-related characteristics of labor attending women at public hospitals in the North Wollo Zone, 2022/2023 Variable Case n (%) Control n (%) Gestational age (n=353) Preterm 23 (19.5) 57 (24.3) Term 81 (68.6) 142 (60.5) Post term 14 (11.9) 36 (15.2) Gravidity(n=353) Primigravida 9 (7.6) 18 (7.6) Multigravida 109 (92.4) 217 (92.3) Parity (353) Nulliparity 9 (7.6) 18 (7.7) Primipara 29 (24.6) 84 (35.7) Multipara 80 (67.8) 133 (56.6) Interpregnancy interval (n=326) 24 Month 67 (61.5) 112 (51.6) History of Multiple pregnancy (n=326) Yes 19 (17.4) 18 (8.3) No 90 (82.6) 199 (91.7) History of abortion (n=326) Yes 47 (43.1) 26 (12.0) No 62 (56.9) 191 (88.0) Type of abortion (n=73) Induced 22 (46.8) 13 (50) Spontaneous 25 (53.2) 13(50) Previous history of PROM (n=326) Yes 60 (55.0) 26 (12.0) No 49 (45.0) 191 (88.0) Desire for last pregnancy (n=326) Yes 76 (69.7) 170 (78.3) No 33 (30.3) 47 (21.7) Previous history of C/S (n=326) Yes 44 (40.4) 49 (22.6) No 65(59.6) 168 (77.4) Maternal health service-related characteristics of the study participants Among the study participants, more than half (73 [61.9%]) and 128 (59.0%) had four ANC visits, and many of them had visited government health institutions. Moreover, 65 (59.6%) patients and 112 (51.6%) controls delivered at hospitals (Table 3) . Table 3 : Maternal health service variables of respondents attending at public hospitals in North Wollo Zone, 2022/2023 Variable Case Control No of ANC Visit (n=353) Less than Two ANC 6 (5.1) 17 (7.8) Three ANC 21 (17.8) 58 (26.7) Four ANC 73 (61.9) 128 (59.0) More than four 18 (15.2) 32 (14.7) Place for ANC (n=353) Gov’t Health Institution 87 (73.7) 159 (67.7) Private Institution 31 (26.3) 76 (32.3) Place of last delivery (n=326) Hospital 65 (59.6) 112 (51.6) Health Centre 39 (35.8) 89 (41.0) Private Clinic 5 (4.6) 16 (7.4) Mode of last delivery (n=326) SVD 61 (56.0) 161 (74.2) C/S 43 (39.4) 50 (20.3) Instrumental Delivery 5 (4.6) 6 (2.7) History of cervical cerclage (n=326) Yes 18 (16.5) 15 (6.9) No 91 (83.5) 202 (93.1) Clinical and medical characteristics of the study participants Regarding clinical conditions, chronic cough was experienced in 25 (21.2%) and 11 (4.7%) of the patients and controls, respectively. Furthermore, approximately half of the 63 patients (53.4%) and 39 (16.6%) of the controls had abnormal vaginal discharge. Twenty-five (21.2%) of the patients had polyhydramnios, and only 15 (6.4%) of the controls had this condition. There was a comparable percentage of participants in both the cases (6, 5.1%) and controls (13, 5.5%) with PIH. Almost half of the participants in the case group (63, 53.4%) had UTIs, but far fewer than a quarter of the participants in the control group (37, 15.7%) had infections (Table 4) . Table 4 : Clinical and medical conditions participants attending at public hospitals in the North Wollo Zone, 2022/2023 Variable Case Control Chronic cough (n=353) Yes 25 (21.2) 11 (4.7) No 93 (78.8) 224 (95.3) STI (n=353) Yes 16 (13.6) 13 (5.5) No 102 (86.4) 222 (94.5) Abnormal vaginal discharge (n=353) Yes 63 (53.4) 39 (16.6) No 55 (46.6) 196 (83.4) Polyhydramnios (n=353) Yes 25 (21.2) 15 (6.4) No 93 (78.8) 220 (93.6) Hemoglobin Value (n=353) =11 98 (83.0) 215 (91.5) MUAC in cm (n=353) =23 29 (24.6) 97 (41.3) PIH (n=353) Yes 6 (5.1) 13 (5.5) No 112 (94.9) 222 (94.5) Gestational DM (n=353) Yes 5 (4.2) 11 (4.7) No 113 (95.8) 224 (95.3) On ART (n=353) Yes 11 (9.3) 16 (6.8) No 107 (90.7) 219 (93.2) Suspected sepsis (n=353) Yes 41 (34.7) 18 (7.7) No 77 (65.3) 217 (92.3) UTI (n=353) Yes 63 (53.4) 37 (15.7) No 55 (46.6) 198 (84.3) Vaginal bleeding (n=353) Yes 13 (11.0) 15 (6.4) No 105 (89.0) 220 (93.6) Sexual intercourse at third trimester (n=353) Yes 53 (44.9) 100 (42.6) No 65 (55.1) 135 (57.4) Determinants of premature membrane rupture A bivariable logistic regression was performed for each independent variable. The variables included residence, history of C/S, history of cervical cerclage, desire for a previous pregnancy, history of multiple pregnancies, history of abortion, history of PROM, chronic cough, STIs, abnormal vaginal discharge, polyhydramnios, Hgb value <11 gm/dl, MAUC <23 cm, suspected sepsis, UTIs and vaginal bleeding, all of which had P values <0.25. These variables were transferred to a multivariable logistic regression model. Overall, a history of C/S, a history of abortion, a history of PROM, chronic cough, MAUC <23 cm, suspected sepsis and UTIs were found to be statistically significant determining factors for PROM, with p values <0.05. A history of C/S was identified as one of the determining factors for PROM. Those participants who had a history of C/S had 2.11 times greater odds (95% CI: 1.05-4.23) of having PROM than those who did not have a history of C/S. Participants who had a history of abortion were more likely to have PROM than those who had not had a history of abortion (AOR= 3.68 95% CI: 1.70-7.94). In addition, the odds of PROM among pregnant women who had a history of PROM and chronic cough were 3.89 and 4.23, respectively, with 95% CIs of 1.73-8.71 and 1.47-12.18, respectively, compared with their counterparts (Table 5) . Table 5: Determinant factors of premature rupture of membrane respondents at public hospitals in North Wollo Zone, 2022/2023 Variables Category PROM status COR (95%CI) AOR (95%CI) P value Case n (%) N=109 Control n (%) N=217 Resident Rural 43 (39.4) 102 (47.0) 0.73 (0.46-1.14) 0.90(0.45-1.82) 0.78 Urban 66(61.6) 115 (53.0) 1 1 History of C/S Yes 44 (40.4) 49 (22.6) 2.32 (1.41-3.82) 2.11 (1.05-4.23) 0.035 No 65(59.6) 168 (77.4) 1 1 History of cervical cerclage Yes 18 (16.5) 15 (6.9) 2.66 (1.29-5.52) 2.12 (0.75-5.97) 0.16 No 91 (83.5) 202 (93.1) 1 1 Desire for the pregnancy Yes 76 (69.7) 170 (78.3) 0.64 (0.38-1.07) 0.89 (0.41-1.93) 0.78 No 33 (30.3) 47 (21.7) 1 1 History of Multiple pregnancy Yes 19 (17.4) 18 (8.3) 2.33 (1.17-4.66) 1.58 (0.55-4.56) 0.39 No 90 (82.6) 199 (91.7) 1 1 History of Abortion Yes 47 (43.1) 26 (12.0) 5.57(3.19-9.73) 3.68 (1.70-7.94) 0.001 No 62 (56.9) 191 (88.0) 1 1 History of PROM Yes 60 (55.0) 26 (12.0) 9.0 (5.15-15.70) 3.89 (1.73-8.71) 0.001 No 49 (45.0) 191 (88.0) 1 1 Having Chronic cough Yes 24 (22.0) 9 (4.1) 5.47 (2.59-11.58) 4.23 (1.47-12.18) 0.008 No 85 (82.0) 208 (95.9) 1 1 Having STI Yes 15 (13.8) 11 (5.7) 2.68 (1.24-5.78) 0.94 (0.29-3.10) 0.92 No 94 (86.2) 206 (94.3) 1 1 Having abnormal vaginal Discharge Yes 60 (55.0) 38 (17.5) 5.76 (3.50-9.48) 2.56 (1.20-5.43) 0.15 No 49 (45.0) 179 (82.5) 1 1 Polyhydramnios Yes 23 (21.1) 14 (6.4) 3.94 (2.00-7.82) 1.89 (0.71-5.00) 0.21 No 86 (78.9) 203 (93.6) 1 1 Hgb Value =11 89 (81.7) 200 (92.2) 1 1 MAUC in Cm =23 26 (23.9) 89 (40.0) 1 1 Suspected sepsis Yes 41 (37.6) 17 (7.8) 6.45 (3.50-11.84) 2.99 (1.25-7.19) 0.014 No 68 (62.4) 200 (92.2) 1 1 UTI Yes 60 (55.0) 33 (15.2) 6.13 (3.70-10.15) 3.14 (1.50-6.60) 0.003 No 49 (45.0) 184 (84.8) 1 1 Having Vaginal bleeding Yes 12 (11.0) 14 (6.4) 1.82 (0.83-3.95) 1.17 (0.35-3.94) 0.80 No 97 (89.0) 203 (93.6) 1 1 Discussion Premature membrane rupture is one of the most common maternal health concerns globally and is more common in developing countries, including Ethiopia (2, 5, 6, 16). It contributes to a considerable number of maternal and neonatal morbidities and mortalities. Additionally, PROM leads to economic and developmental burdens for the country due to prolonged hospital stays, increased drug expenses, and increased workloads for healthcare professionals (12). Therefore, it is crucial to identify and prevent determinant factors to minimize the impact of this problem. In this study, pregnant women with a history of C/S had 2.11 times greater odds of developing PROM than their counterparts. This finding is consistent with studies conducted in Senegal, eastern Ethiopia, Harar, northern Ethiopia, Tigray, and southern Ethiopia (15-17, 29, 30). The reason for this might be that scar formation could result in abnormalities in the fetal membrane that may result in leakage and tear of the membrane (31). Different studies performed in Uganda and Ethiopia have indicated that a history of abortion is associated with increased odds for the occurrence of PROM (16, 17, 29, 32, 33). Concurrently, our study also identified a history of abortion as a determining factor. Premature rupture of the membrane was 3.68 times more likely to occur in pregnant women who had a history of abortion than in those who did not experience abortion. This finding is also in line with a study performed in Iran in which abortion was positively associated with PROM (10). The reason for this could be that unaseptic abortion procedures, particularly dilatation and curettage, can disturb the natural elasticity of the cervix and uterus. This disturbance may result in uterine perforation and scarring, cervical insufficiency, and ultimately the premature rupture of membranes in the following pregnancy (34). In the current study, women with a history of PROM were 3.89 times more likely to develop PROM in their current pregnancy than were those without a history of PROM. The results of this study are supported by studies performed in India, Indonesia, Nigeria, Egypt, and different areas of Ethiopia (16, 17, 29, 35-41). This might be because, as subsequent pregnancies occur, the composition of the membranes becomes more delicate, marked by a decrease in collagen content. This reduction in collagen serves as a catalyst for the premature rupture of membranes (36). In addition, this study indicated that having a chronic cough was a determining factor for PROM. Pregnant women who had chronic coughs were 4.23 times more likely to develop PROM than their counterparts were. Persistent coughing in pregnant women can result in chest spasms, leading to fatigue and pain. Additionally, prolonged, continuous, or intense coughing can trigger uterine contractions and premature membrane rupture. Additionally, detecting and addressing coughing promptly is crucial, as it may indicate an infection in the mother's body. A MAUC <23 cm was another factor identified for the occurrence of PROM in the current study. Participants who had a MAUC <23 cm had 3.47 times greater odds of experiencing PROM than their counterparts. This is in agreement with studies performed in Ethiopia (15, 32, 40). The possible reason for this might be that MAUC<23 cm in pregnant women indicates nutritional deficiency. Nutrient deficiencies, including deficiencies in micronutrients (vitamin D and ascorbic acid), affect the formation of collagen, which in turn distorts the structure and integrity of the fetal membrane. As a result, the body loses its ability to protect itself from degenerative processes caused by oxidative stress, which can easily lead to membrane leakage (42, 43). Pregnant women who were suspected of having sepsis had a 2.99 times greater likelihood of having PROM than those who were not suspected of having sepsis in the current study. The reason for this might be that if a pregnant individual develops a severe infection, including a uterine infection (chorioamnionitis), it can potentially contribute to PROM. In addition, infections in the reproductive tract can lead to inflammation and damage to fetal membranes, increasing the susceptibility to premature rupture (44). Women who had UTIs had 3.14 times greater odds of having PROM than did their counterparts. Supported results were shown among studies performed in Uganda and Ethiopia (32, 33, 39). This could be attributed to the fact that bacterial infections in the urinary tract may progress upward through the vaginal and cervical passages, reaching the decidua and fetal membrane. This progression ultimately triggers the release of prostaglandins and cytokines, leading to softening of the cervix and increased vulnerability to ascending infections, ultimately resulting in PROM. Additionally, the direct release of bacterial proteolytic enzymes, such as proteases, collagenases, or trypsin, can potentially cause damage and weakness to the fetal membrane, culminating in its rupture. Consequently, it is advisable for healthcare providers to routinely screen pregnant women for UTIs and administer appropriate treatment during ANC visits (45). Conclusions and Recommendations This study underscores the multifaceted nature of PROM, revealing its association with various maternal health factors, including a history of cesarean section, abortion, previous PROM occurrences, chronic cough, maternal abdominal uterine circumference (MAUC) measurements, suspicion of sepsis, and urinary tract infections (UTIs). These findings echo similar research conducted in diverse regions, highlighting the consistency of risk factors contributing to PROM. Importantly, interventions aimed at identifying and addressing these determinants are imperative to mitigate the adverse maternal and neonatal outcomes associated with PROM, alleviate economic burdens on healthcare systems, and enhance overall maternal health outcomes. Routine screening and targeted interventions during antenatal care visits could play a pivotal role in reducing the incidence of PROM and improving maternal and neonatal health outcomes in affected populations. Limitations of the study This study encountered limitations related to recall bias for certain variables, such as a history of PROM and cervical cerclage. Additionally, social desirability bias was observed concerning personal and sensitive behavior, specifically in relation to the variable of engaging in sexual intercourse during the third trimester. Furthermore, the diagnosis of PROM in our setting relies solely on clinical history and physical examination, potentially impacting the selection of cases and controls. Moreover, the diagnosis of sepsis did not involve culture, leading to potential selection bias. Abbreviations Antenatal Care (ANC), Antiretroviral Therapy (ART), Caesarian Section (C/S), Mid-upper Arm Circumference (MAUC), Pregnancy-induced Hypertension (PIH), Preterm Premature Rupture of Membrane (PPROM), Premature Rupture of Membrane (PROM), Sexual Transmitted Disease (STI), Spontaneous Vaginal Delivery (SVD), Urinary Tract Infection (UTI), Woldiya Comprehensive Specialized Hospital (WCSH), World Health Organization (WHO). Declarations Ethical approval The study was approved by the Woldiya University Ethical Review Committee of the College of Health Sciences, and ethical approval was obtained. Consent to participate Lalibela, Mersa, and Woldiya, hospitals in the Amhara region, also provided explicit consent letters. Having fully understood the purpose of the study, each respondent provided written consent prior to the interview. In addition, the study was carried out in accordance with the Declaration of Helsinki. Recalcitrant study participants were excluded from the survey. Anonymized data were collected, and participant information was kept confidential. Consent for publications: Not applicable. Availability of Data and Materials All the data generated or analyzed during this study are included in the manuscript and are available from the corresponding authors upon request. Conflicts of interest The authors declare that they have no competing interests in this work. Funding There was no financial aid available for the current study. Author Contribution ST: Conceptualized the study, analyzed the data and critically edited the manuscript; EA & TB: Involved in the analysis and interpretation of the data, substantially revised and critically edited the manuscript; and MA & MAs: Designed and supervised the entire study, critically revised and contributed to the scientific content of the manuscript. Acknowledgment The authors are grateful to the medical directors and professionals at Woldiya Comprehensive and Specialized Hospital, Lalibela Referral Hospital, and Mersa Primary Hospital for their kind cooperation. We are also grateful to the data collectors and respondents to the study. References DeCherney AH, Roman AS, Nathan L, Laufer N. Current diagnosis & treatment obstetrics & gynecology: McGraw Hill Professional; 2018. Huang S, Xia W, Sheng X, Qiu L, Zhang B, Chen T, et al. Maternal lead exposure and premature rupture of membranes: a birth cohort study in China. 2018;8(7): e021565. Sajitha A, Geetha K, Mumtaz PJIJCOG. The maternal and perinatal outcome in preterm premature rupture of membrane (PROM): a prospective observational study. 2020;5(4):208-12. Liu J, Feng Z-C, Wu JJJotp. The incidence rate of premature rupture of membranes and its influence on fetal–neonatal health: A Report from Mainland China. 2010;56(1):36-42. Diriba TDJEG. Incidence, maternal and perinatal outcome of premature rupture of fetal membrane cases in Jimma University Teaching Hospital, South west Ethiopia. 2017; 5:163-72. Tiruye G, Shiferaw K, Tura AK, Debella A, Musa AJSom. Prevalence of premature rupture of membrane and its associated factors among pregnant women in Ethiopia: A systematic review and meta-analysis. 2021; 9:20503121211053912. Lovereen S, Khanum MA, Nargis N, Begum S, Afroze RJBjomS. Maternal and Neonatal outcome in premature rupture of membranes. 2018;17(3):479-83. Caughey AB, Robinson JN, Norwitz ERJRio, gynecology. Contemporary diagnosis and management of preterm premature rupture of membranes. 2008;1(1):11. Yu H, Wang X, Gao H, You Y, Xing AJBt. Perinatal outcomes of pregnancies complicated by preterm premature rupture of the membranes before 34 weeks of gestation in a tertiary center in China: A retrospective review. 2015;9(1):35-41. Boskabadi H, Zakerihamidi MJJoPR. Evaluation of maternal risk factors, delivery, and neonatal outcomes of premature rupture of membrane: a systematic review study. 2019;7(2):77-88. İflazoğlu N, Eroğlu H, Tolunay HE, Yücel AJJoO, Research G. Comparison of the maternal serum endocan levels in preterm premature rupture of membrane and normal pregnancy. 2021;47(9):3151-8. Workineh Y, Birhanu S, Kerie S, Ayalew E, Yihune MJBrn. Determinants of premature rupture of membrane in Southern Ethiopia, 2017: case control study design. 2018;11(1):1-7. Maryuni M, Kurniasih DJKJKMN. Risk factors for premature rupture of membrane. 2017;11(3):133-7. Zeng L-n, Zhang L-l, Shi J, Gu L-l, Grogan W, Gargano MM, et al. The primary microbial pathogens associated with premature rupture of the membranes in China: a systematic review. 2014;53(4):443-51. Habte A, Dessu S, Lukas KJIJoWsH. Determinants of Premature Rupture of Membranes Among Pregnant Women Admitted to Public Hospitals in Southern Ethiopia, 2020: A Hospital-Based Case–Control Study. 2021; 13:613. Assefa NE, Berhe H, Girma F, Berhe K, Berhe YZ, Gebreheat G, et al. Risk factors for premature rupture of membranes in public hospitals at Mekele city, Tigray, a case control study. 2018;18(1):1-7. Enjamo M, Deribew A, Semagn S, Mareg MJIJoWsH. Determinants of Premature Rupture of Membrane (PROM) Among Pregnant Women in Southern Ethiopia: A Case‒Control Study. 2022; 14:455. Choudhary M, Rathore SB, Chowdhary J, Garg SJIJoRiMS. Pre and post conception risk factors in PROM. 2017;3(10):2594-8. Meller CH, Carducci ME, Ceriani Cernadas JM, Otaño LJAAP. Preterm premature rupture of membranes. 2018;116(4): e575-e81. Lawn JE, Blencowe H, Oza S, You D, Lee AC, Waiswa P, et al. Every Newborn: progress, priorities, and potential beyond survival. 2014;384(9938):189-205. Pearson L, Gandhi M, Admasu K, Keyes EBJIjog, obstetrics. User fees and maternity services in Ethiopia. 2011;115(3):310-5. Health FMo. Management of common obstetric complications. Federal Ministry of Health. 2010. Institute EPH. Ethiopia mini demographic and health survey key indicators. Chemical Information and Modeling. 2019; 53:1689-99. Kpewou DE, Poirot E, Berger J, Som SV, Laillou A, Belayneh SN, et al. Maternal mid‐upper arm circumference during pregnancy and linear growth among Cambodian infants during the first months of life. 2020;16: e12951. Morice A, Dicpinigaitis P, McGarvey L, Birring SSJERR. Chronic cough: new insights and future prospects. 2021;30(162). Ford ND, Cox S, Ko JY, Ouyang L, Romero L, Colarusso T, et al. Hypertensive disorders in pregnancy and mortality at delivery hospitalization—United States, 2017–2019. 2022;71(17):585. Srzić I, Adam VN, Pejak DTJACC. Sepsis definition: What’s new in the Treatment Guidelines. 2022;61(Suppl 1):67. Werter DE, Kazemier BM, van Leeuwen E, de Rotte MC, Kuil SD, Pajkrt E, et al. Diagnostic work-up of urinary tract infections in pregnancy: study protocol of a prospective cohort study. 2022;12(9): e063813. Getnet A, Oljira L, Assefa N, Tiruye G, Figa ZJH. Determinants of premature rupture of membrane among pregnant women in Harar town, Eastern Ethiopia: A case‒control study. 2023;9(4). Delafield R, Pirkle CM, Dumont AJBp, childbirth. Predictors of uterine rupture in a large sample of women in Senegal and Mali: cross-sectional analysis of QUARITE trial data. 2018;18(1):1-8. Kaya DJEAmj. Risk factors for preterm premature rupture of membranes at Mulago hospital Kampala. 2001;78(2):65-9. Assefa EM, Chane G, Teme A, Nigatu TAJPo. Determinants of prelabor rupture of membrane among pregnant women attending governmental hospitals in Jimma zone, Oromia region, Ethiopia: A multicenter case‒control study. 2023;18(11): e0294482. Byonanuwe S, Nzabandora E, Nyongozi B, Pius T, Ayebare DS, Atuheire C, et al. Predictors of premature rupture of membranes among pregnant women in rural Uganda: a cross-sectional study at a tertiary teaching hospital. 2020;2020. Zhou W, Sørensen HT, Olsen JJIjoe. Induced abortion and low birthweight in the following pregnancy. 2000;29(1):100-6. Kovavisarach E, Sermsak PJA, Obstetrics NZJo, Gynecology. Risk factors related to premature rupture of membranes in term pregnant women: a case‐control study. 2000;40(1):30-2. Sihombing JA, Miqbel M, Sirait BIJAJoRiID. Relationship between Premature Rupture of the Membrane and Cesarean Delivery: Case from Jakarta, Indonesia. 2023;12(4):41-51. Emechebe CJP. Determinants and complications of prelabor rupture of membranes (PROM) at the University of Calabar Teaching Hospital (UCTH), Calabar, Nigeria. 2015;95(100.0):15-9. Wondosen M. Determinants of term premature rupture of membrane: case‒control study in Saint Paul’s Millennium Medical College Hospital, Addis Ababa, Ethiopia. 2023. Diriba TA, Geda B, Wayessa ZJJIJoANS. Premature rupture of membrane and associated factors among pregnant women admitted to maternity wards of public hospitals in West Guji Zone, Ethiopia, 2021. 2022; 17:100440. Addisu D, Melkie A, Biru S. Prevalence of Preterm Premature Rupture of Membrane and Its Associated Factors among Pregnant Women Admitted in Debre Tabor General Hospital, North West Ethiopia: Institutional-Based Cross-Sectional Study. Obstetrics and gynecology international. 2020; 2020:4034680. Abdel Maaboud RMR, Nossair WS, Ali AE-S, Ibrahem SAJTEJoHM. Incidence rate, risk factors and outcome of premature rupture of membranes (PROM) at zagazig university hospitals. 2021;85(1):2744-50. Oguntibeju OOJAJoB. The biochemical, physiological and therapeutic roles of ascorbic acid. 2008;7(25). Hassanzadeh A, Paknahad Z, Khoigani MGJAbr. The relationship between macroand micronutrients intake and risk of preterm premature rupture of membranes in pregnant women of Isfahan. 2016;5. Surgers L, Valin N, Carbonne B, Bingen E, Lalande V, Pacanowski J, et al. Evolving microbiological epidemiology and high fetal mortality in 135 cases of bacteremia during pregnancy and postpartum. 2013; 32:107-13. Parry EJO, Gynecology. Managing PROM and PPROM. 2006;8(4):35-8. Additional Declarations No competing interests reported. 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It presents a significant public health concern associated with maternal, fetal, and neonatal complications, impacting 5 to 20% of global pregnancies, with higher rates observed in Africa and specific regions\u0026nbsp;such as\u0026nbsp;Ethiopia. It presents a significant public health concern associated with maternal, fetal, and neonatal complications, impacting 5 to 20% of global pregnancies,\u0026nbsp;with higher rates observed in Africa and specific regions\u0026nbsp;such as\u0026nbsp;Ethiopia (2-6).\u003c/p\u003e\n\u003cp\u003ePROM significantly increases perinatal mortality and neonatal morbidity due to the loss of the protective intrauterine barrier,\u0026nbsp;increasing\u0026nbsp;the risk of infection for both\u0026nbsp;mothers\u0026nbsp;and\u0026nbsp;fetuses, particularly with prolonged latent periods and repeated vaginal examinations (7, 8). It leads to fetal and neonatal complications such as distress, respiratory syndrome, and preterm birth, contributing to\u0026nbsp;more than\u0026nbsp;40% of preterm deliveries in some instances (4, 9, 10). Moreover, its impact extends to mothers, increasing the risk of infections, chorioamnionitis, placental abruption, and other serious complications (3, 10-12).\u003c/p\u003e\n\u003cp\u003eThe etiology of PROM is often unknown, but structural defects in the membrane, bacterial infections, and activation of catabolic enzymes\u0026nbsp;such as\u0026nbsp;collagenase are contributing factors (13, 14). Multiple risk factors contribute to PROM, including previous history of abortion or PROM,\u0026nbsp;cesarean\u0026nbsp;delivery, lack of antenatal care, malnutrition, abnormal vaginal discharge, urinary tract infection, smoking,\u0026nbsp;anemia, parity, pregnancy-induced hypertension, gestational diabetes, and invasive procedures (5, 15-18).\u003c/p\u003e\n\u003cp\u003ePROM cases are primarily identified through patient history and amniotic fluid examination, with additional improvement\u0026nbsp;in detection\u0026nbsp;using tests\u0026nbsp;such as\u0026nbsp;the nitrazine test or crystallography test. Repeated vaginal examinations in mothers\u0026nbsp;with PROM\u0026nbsp;are discouraged due to the elevated risk of bacterial infection (19). Upon confirmation of PROM,\u0026nbsp;assessments\u0026nbsp;of gestational age, labor, fetal distress, and sepsis\u0026nbsp;are\u0026nbsp;essential, followed by rehydration, close fetal monitoring, and antibiotic administration (20). Women with PROM should undergo close monitoring before attempting another pregnancy (9, 20).\u003c/p\u003e\n\u003cp\u003eIn Ethiopia, several strategies beyond medical intervention aim to minimize neonatal and maternal morbidity and mortality, including the development of PROM guidelines, continuous professional development for health professionals, the establishment of maternal waiting rooms, safe transportation for laboring women, facility capacity enhancement, and the provision of free maternal and neonatal health services (21, 22).\u003c/p\u003e\n\u003cp\u003eDespite the above strategies and protocols for PROM diagnosis and management in Ethiopia, there is a lack of focus on identifying and preventing risk factors, which is leading to a stagnant reduction in neonatal morbidity and mortality rates. Despite the above strategies and protocols for PROM diagnosis and management in Ethiopia, there is a lack of focus on identifying and preventing risk factors, which is leading to a stagnant reduction in neonatal morbidity and mortality rates (23). Although few studies have been performed in Ethiopia, many of them are cross-sectional studies, and there is still a scarcity of data around the study area. Moreover, some variables, such as the presence of sepsis and chronic cough, were not included in those studies. Thus, this study aimed to assess the determinants of PROM at different hospitals in Northeast Ethiopia.\u003c/p\u003e"},{"header":"Methods and materials","content":"\u003cp\u003e\u003cstrong\u003eStudy design, period, and setting\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAn institutional-based, unmatched case control study was conducted from December 1, 2022, to March 30, 2023, at different public hospitals in the North Wollo zone in northeastern Ethiopia. The North Wollo Zone has a total of six public hospitals: one comprehensive, one general, and four primary hospitals. The study was conducted at Woldia Comprehensive Specialized Hospital (WCSH), Lalibela General Hospital, and Mersa Primary Hospital. The abovementioned public hospitals are providing continuous maternal and child health services, including ANC and delivery\u0026nbsp;services, around the area.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStudy population and eligibility criteria\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll women who visited the selected public hospitals for labor care,\u0026nbsp;had a\u0026nbsp;gestational age of more than 28 weeks, were\u0026nbsp;diagnosed\u0026nbsp;with\u0026nbsp;PROM by clinicians and\u0026nbsp;were\u0026nbsp;admitted to\u0026nbsp;the\u0026nbsp;labor and maternity wards of each\u0026nbsp;hospital\u0026nbsp;during the study period were enrolled as cases. Moreover, all women who visited the selected hospitals for labor care,\u0026nbsp;had a\u0026nbsp;gestational age of more than 28 weeks, were\u0026nbsp;not diagnosed\u0026nbsp;with\u0026nbsp;PROM,\u0026nbsp;were\u0026nbsp;confirmed by clinicians and\u0026nbsp;were\u0026nbsp;admitted to\u0026nbsp;the\u0026nbsp;labor and maternity wards of each\u0026nbsp;hospital\u0026nbsp;during the study period were included as\u0026nbsp;controls.\u003c/p\u003e\n\u003cp\u003eThose mothers who were initially\u0026nbsp;assigned\u0026nbsp;to the control group but later switched to the case group and those who were seriously ill during the data collection period were excluded from the study. Additionally, women who\u0026nbsp;underwent\u0026nbsp;artificial\u0026nbsp;membrane\u0026nbsp;rupture,\u0026nbsp;who experienced\u0026nbsp;maternal deterioration\u0026nbsp;requiring\u0026nbsp;immediate delivery,\u0026nbsp;who experienced\u0026nbsp;intrauterine fetal death,\u0026nbsp;or\u0026nbsp;whose\u0026nbsp;cases\u0026nbsp;were due to trauma or\u0026nbsp;accidents were\u0026nbsp;excluded.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSample size determinations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe sample size was determined using the StatCalc menu of Epi Info version 7.2.5 statistical software for an unmatched\u0026nbsp;case control\u0026nbsp;study. The following assumptions were used: a 95% confidence level, 80% power, a case-to-control ratio of 1:2, a\u0026nbsp;percentage\u0026nbsp;of exposure among controls (proportion of no ANC visit among women without PROM), and a\u0026nbsp;percentage\u0026nbsp;of exposure among cases (proportion of no ANC visit among women with PROM). The\u0026nbsp;percentages\u0026nbsp;of\u0026nbsp;patients\u0026nbsp;with no ANC\u0026nbsp;visits\u0026nbsp;(27.9%) and controls with no ANC follow-up (14.0%)\u0026nbsp;were\u0026nbsp;taken from a study conducted in\u0026nbsp;southern\u0026nbsp;Ethiopia (15).\u0026nbsp;Based on the above assumptions, the sample size was 321 (107 cases and 214 controls), and after adding for a 10%\u0026nbsp;nonresponse\u0026nbsp;rate, the final sample size for the study was 353 (118 cases and 235 controls).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSampling techniques and procedures\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAmong the 6 public hospitals found in the zone, three public\u0026nbsp;hospitals\u0026nbsp;(WCSH, Lalibela\u0026nbsp;Referral Hospital\u0026nbsp;and Mersa\u0026nbsp;Primary Hospital) were selected by\u0026nbsp;the\u0026nbsp;lottery method. Then,\u0026nbsp;the number of cases and controls were allocated proportionally based on the same period of previous year pregnant women\u0026nbsp;attended\u0026nbsp;in each hospital. Therefore, from\u0026nbsp;a\u0026nbsp;total\u0026nbsp;of\u0026nbsp;1707 study participants\u0026nbsp;from the\u0026nbsp;last year at WCSH,\u0026nbsp;we\u0026nbsp;selected\u0026nbsp;193 participants (64 cases and 129 controls);\u0026nbsp;from 938 pregnant women\u0026nbsp;at\u0026nbsp;Lalibela\u0026nbsp;General Hospital, we selected\u0026nbsp;106 participants (35 cases and 71 controls);\u0026nbsp;and from Mersa\u0026nbsp;Primary Hospital,\u0026nbsp;a total of 478 pregnant women were\u0026nbsp;admitted\u0026nbsp;last year,\u0026nbsp;and we\u0026nbsp;selected\u0026nbsp;54 participants (18 cases and 36 controls). Finally, all\u0026nbsp;patients\u0026nbsp;were selected until the sample size was reached. Moreover, controls were selected by systematic random sampling. Following the admission of a specific case to the unit, two controls were randomly selected using a lottery method from a list of controls admitted to the same unit, and the kth of those controls\u0026nbsp;was\u0026nbsp;selected accordingly. The process of control selection commenced promptly after the selection of each\u0026nbsp;patient.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eOperational definitions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMid-upper arm circumference: The nutritional status\u0026nbsp;of the mothers\u0026nbsp;was evaluated by measuring the mid-upper arm circumference, which was assessed at the midpoint between the tips of the shoulder and the elbow of the left arm using standard MUAC tape. The measurements were taken to the nearest 0.1 cm and recorded in the provided questionnaire as less than 23\u0026nbsp;cm\u0026nbsp;and greater than\u0026nbsp;or\u0026nbsp;equal to 23 cm\u0026nbsp;(24).\u003c/p\u003e\n\u003cp\u003eChronic cough:\u0026nbsp;Participants\u0026nbsp;with a persistent cough that lasts for at least eight weeks and often much longer (25).\u003c/p\u003e\n\u003cp\u003eGestational hypertension\u0026nbsp;was defined as a\u0026nbsp;pregnant mother with a blood pressure greater than or equal to\u0026nbsp;140 mmHg\u0026nbsp;and/or diastolic blood pressure greater than or equal to 90 mmHg on two separate occasions at least four hours apart after 20 weeks of pregnancy when\u0026nbsp;the\u0026nbsp;previous blood pressure was normal (26).\u003c/p\u003e\n\u003cp\u003eSuspected sepsis\u0026nbsp;was defined as\u0026nbsp;a temperature below 36.0°C\u0026nbsp;or above 38.0°C\u0026nbsp;for a minimum of 2 hours and 1 hour, respectively; white blood cell counts below 4 × 10^9/l or above 12 × 10^9/l, or more than 10% immature (band) forms;\u0026nbsp;a\u0026nbsp;heart rate surpassing 90 beats per minute for at least 1 hour;\u0026nbsp;and a\u0026nbsp;respiratory rate exceeding 20 breaths per minute for at least 1 hour. Sepsis was characterized by the presence of a minimum of two\u0026nbsp;of\u0026nbsp;these criteria in addition to the clinical suspicion of infection as determined by experienced senior clinicians (27).\u003c/p\u003e\n\u003cp\u003eUrinary tract infection\u0026nbsp;was defined as a\u0026nbsp;positive result\u0026nbsp;for\u0026nbsp;nitrite and leucocyte esterase\u0026nbsp;on\u0026nbsp;a\u0026nbsp;urine dipstick and\u0026nbsp;the\u0026nbsp;presence of red and white blood cells, squamous cells and bacteria\u0026nbsp;on\u0026nbsp;a\u0026nbsp;urine\u0026nbsp;microscope\u0026nbsp;(28).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData collection methods and procedures\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInterviewer-administered questionnaires were used for data collection. The questionnaires\u0026nbsp;were\u0026nbsp;initially prepared in English and\u0026nbsp;then\u0026nbsp;translated to Amharic and\u0026nbsp;returned\u0026nbsp;to English to check consistency.\u0026nbsp;A\u0026nbsp;review\u0026nbsp;of the cards\u0026nbsp;was also\u0026nbsp;performed\u0026nbsp;to\u0026nbsp;obtain\u0026nbsp;information on some variables. Three\u0026nbsp;midwifery\u0026nbsp;professionals\u0026nbsp;at\u0026nbsp;each\u0026nbsp;hospital\u0026nbsp;were recruited for data collection. One BSc\u0026nbsp;midwife\u0026nbsp;in each hospital was assigned as\u0026nbsp;a\u0026nbsp;supervisor to supervise the data collection throughout the process\u0026nbsp;at\u0026nbsp;each health\u0026nbsp;institution.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData quality control\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo ensure the quality of\u0026nbsp;the data, data collection tools were\u0026nbsp;used\u0026nbsp;after intensive review of\u0026nbsp;the\u0026nbsp;relevant\u0026nbsp;literature. Pretesting\u0026nbsp;of the questionnaire was carried out on 5% of\u0026nbsp;the\u0026nbsp;sample at the Haik\u0026nbsp;Primary\u0026nbsp;Hospital. Based on the\u0026nbsp;pretest results, all relevant corrections were made. One-day training was given to the data collectors and supervisors about confidentiality,\u0026nbsp;the respondents’ rights, informed consent,\u0026nbsp;the\u0026nbsp;objective of the study,\u0026nbsp;the\u0026nbsp;techniques of the interview and\u0026nbsp;the completion of\u0026nbsp;the questionnaire. The completeness of the data was checked by\u0026nbsp;the\u0026nbsp;data collectors during\u0026nbsp;the\u0026nbsp;data collection and immediately after\u0026nbsp;the\u0026nbsp;data collection by the supervisor and principal investigator.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe generated data were entered into EpiData version 3.14.6 and exported to STATA version 17 for analysis. Categorical variables are presented as frequencies and percentages. Odds ratios with 95% confidence intervals were used to measure the strength of associations. Bivariable logistic regression was performed to determine the crude associations of the independent variables with the dependent variables. Variables with P values \u0026lt; 0.25 in the bivariable logistic regression were exported to the multivariable logistic regression model to control for confounding factors and to identify the independent predictors of PROM. There was no collinearity between variables (ranging from 1 to 2.3), and the Hosmer‒Lemeshow test yielded a P value of 0.387, indicating that the assumption was not violated and that the goodness of fit was not met, and statistical significance was confirmed at a P value \u0026lt; 0.05.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eSociodemographic characteristics of the participants\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA total of 353 study participants (118 cases and 235 controls) were involved in the study, for a\u0026nbsp;100% response rate. The mean age of the\u0026nbsp;patients\u0026nbsp;was 31.13\u0026nbsp;years. (\u0026plusmn; 6.3 SD) and controls\u0026nbsp;(28.63 yrs). (\u0026plusmn; 5.8 SD). The majority of\u0026nbsp;the patients (69,\u0026nbsp;58.4%) and controls\u0026nbsp;(168,\u0026nbsp;71.5%) were\u0026nbsp;aged\u0026nbsp;20-35\u0026nbsp;years.\u0026nbsp;More than half of the\u0026nbsp;patients\u0026nbsp;and controls were from\u0026nbsp;urban areas (71 [60.2%]\u0026nbsp;and 123\u0026nbsp;[52.3%]).\u0026nbsp;Regarding occupation,\u0026nbsp;the\u0026nbsp;majority of participants in both\u0026nbsp;the\u0026nbsp;36 (30.5%) and\u0026nbsp;control groups (83 (36.6%) were house wives. In\u0026nbsp;terms\u0026nbsp;of religious status,\u0026nbsp;75 (63.6%)\u0026nbsp;patients\u0026nbsp;were Orthodox Tewahido, and the same\u0026nbsp;was\u0026nbsp;true for 134 (57%)\u0026nbsp;controls\u0026nbsp;\u003cstrong\u003e(Table 1)\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003cstrong\u003e: Sociodemographic characteristics of labor attending women at public hospitals of North Wollo Zone, 2022/2023\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"651\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.267281105990783%\" valign=\"top\"\u003e\n \u003cp\u003eVariable(n=353)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.417818740399387%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.195084485407065%\" valign=\"top\"\u003e\n \u003cp\u003eCase N (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.119815668202765%\" valign=\"top\"\u003e\n \u003cp\u003eControl N (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.267281105990783%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.417818740399387%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.195084485407065%\" valign=\"top\"\u003e\n \u003cp\u003e7 (6.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.119815668202765%\" valign=\"top\"\u003e\n \u003cp\u003e23 (9.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.541666666666664%\" valign=\"top\"\u003e\n \u003cp\u003e20-35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.458333333333332%\" valign=\"top\"\u003e\n \u003cp\u003e69 (58.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30%\" valign=\"top\"\u003e\n \u003cp\u003e168 (71.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.541666666666664%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026gt;35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.458333333333332%\" valign=\"top\"\u003e\n \u003cp\u003e42 (35.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30%\" valign=\"top\"\u003e\n \u003cp\u003e44 (18.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.267281105990783%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eResidence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.417818740399387%\" valign=\"top\"\u003e\n \u003cp\u003eRural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.195084485407065%\" valign=\"top\"\u003e\n \u003cp\u003e47 (39.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.119815668202765%\" valign=\"top\"\u003e\n \u003cp\u003e112 (47.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.541666666666664%\" valign=\"top\"\u003e\n \u003cp\u003eUrban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.458333333333332%\" valign=\"top\"\u003e\n \u003cp\u003e71(60.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30%\" valign=\"top\"\u003e\n \u003cp\u003e123 (52.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.267281105990783%\" rowspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003eOccupation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.417818740399387%\" valign=\"top\"\u003e\n \u003cp\u003eHouse wife\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.195084485407065%\" valign=\"top\"\u003e\n \u003cp\u003e36 (30.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.119815668202765%\" valign=\"top\"\u003e\n \u003cp\u003e86 (36.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.541666666666664%\" valign=\"top\"\u003e\n \u003cp\u003eMerchant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.458333333333332%\" valign=\"top\"\u003e\n \u003cp\u003e22 (18.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30%\" valign=\"top\"\u003e\n \u003cp\u003e43 (18.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.541666666666664%\" valign=\"top\"\u003e\n \u003cp\u003eGovernment employee\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.458333333333332%\" valign=\"top\"\u003e\n \u003cp\u003e28 (23.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30%\" valign=\"top\"\u003e\n \u003cp\u003e36 (15.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.541666666666664%\" valign=\"top\"\u003e\n \u003cp\u003ePrivate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.458333333333332%\" valign=\"top\"\u003e\n \u003cp\u003e19 (16.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30%\" valign=\"top\"\u003e\n \u003cp\u003e49 (20.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.541666666666664%\" valign=\"top\"\u003e\n \u003cp\u003eOthers*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.458333333333332%\" valign=\"top\"\u003e\n \u003cp\u003e13 (11.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30%\" valign=\"top\"\u003e\n \u003cp\u003e21 (8.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.267281105990783%\" rowspan=\"5\" valign=\"top\"\u003e\n \u003cp\u003eEducational status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.417818740399387%\" valign=\"top\"\u003e\n \u003cp\u003eCannot read and write\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.195084485407065%\" valign=\"top\"\u003e\n \u003cp\u003e17 (14.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.119815668202765%\" valign=\"top\"\u003e\n \u003cp\u003e31 (13.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.541666666666664%\" valign=\"top\"\u003e\n \u003cp\u003eOnly read and write\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.458333333333332%\" valign=\"top\"\u003e\n \u003cp\u003e20 (17.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30%\" valign=\"top\"\u003e\n \u003cp\u003e54 (23.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.541666666666664%\" valign=\"top\"\u003e\n \u003cp\u003e1-8 Grade\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.458333333333332%\" valign=\"top\"\u003e\n \u003cp\u003e37 (31.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30%\" valign=\"top\"\u003e\n \u003cp\u003e56 (23.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.541666666666664%\" valign=\"top\"\u003e\n \u003cp\u003e9-12 grade\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.458333333333332%\" valign=\"top\"\u003e\n \u003cp\u003e20 (17.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30%\" valign=\"top\"\u003e\n \u003cp\u003e56 (23.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.541666666666664%\" valign=\"top\"\u003e\n \u003cp\u003eCollege and above\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.458333333333332%\" valign=\"top\"\u003e\n \u003cp\u003e24 (20.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30%\" valign=\"top\"\u003e\n \u003cp\u003e38 (16.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.267281105990783%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eMarital status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.417818740399387%\" valign=\"top\"\u003e\n \u003cp\u003eMarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.195084485407065%\" valign=\"top\"\u003e\n \u003cp\u003e104 (88.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.119815668202765%\" valign=\"top\"\u003e\n \u003cp\u003e212 (90.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.541666666666664%\" valign=\"top\"\u003e\n \u003cp\u003eNot Married\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.458333333333332%\" valign=\"top\"\u003e\n \u003cp\u003e14 (11.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30%\" valign=\"top\"\u003e\n \u003cp\u003e23 (9.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.267281105990783%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003eReligion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.417818740399387%\" valign=\"top\"\u003e\n \u003cp\u003eOrthodox Tewahido\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.195084485407065%\" valign=\"top\"\u003e\n \u003cp\u003e75 (63.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.119815668202765%\" valign=\"top\"\u003e\n \u003cp\u003e134 (57.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.541666666666664%\" valign=\"top\"\u003e\n \u003cp\u003eMuslim\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.458333333333332%\" valign=\"top\"\u003e\n \u003cp\u003e38 (32.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30%\" valign=\"top\"\u003e\n \u003cp\u003e94 (40.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"38.541666666666664%\" valign=\"top\"\u003e\n \u003cp\u003eProtestant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.458333333333332%\" valign=\"top\"\u003e\n \u003cp\u003e5 (4.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30%\" valign=\"top\"\u003e\n \u003cp\u003e7 (3.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"26.267281105990783%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"28.417818740399387%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.195084485407065%\" valign=\"top\"\u003e\n \u003cp\u003e118 (100)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.119815668202765%\" valign=\"top\"\u003e\n \u003cp\u003e235 (100)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eObstetric-\u003c/strong\u003e\u003cstrong\u003erelated characteristics of the study participants\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEighty-one\u0026nbsp;(68.5%)\u0026nbsp;patients\u0026nbsp;and 142 (60.5%)\u0026nbsp;controls had term pregnancies. Based on gravidity, more than ninety of the\u0026nbsp;patients (109,\u0026nbsp;92.4%) and 219 (93.2%)\u0026nbsp;of the controls\u0026nbsp;were multigravida. Less than half of the\u0026nbsp;patients (47,\u0026nbsp;43.1%) and one-tenth\u0026nbsp;(26,\u0026nbsp;12.0%) of the controls had at least one episode of abortion\u0026nbsp;during\u0026nbsp;their\u0026nbsp;lifetime. A history\u0026nbsp;of PROM\u0026nbsp;was\u0026nbsp;more pronounced among\u0026nbsp;patients\u0026nbsp;than\u0026nbsp;among\u0026nbsp;controls\u0026nbsp;(60\u0026nbsp;[55.0%]\u0026nbsp;and 26\u0026nbsp;[12.0%], respectively).\u0026nbsp;A total of\u0026nbsp;76 (69.7%) and 170 (78.3%) of the participants in both\u0026nbsp;the case\u0026nbsp;and\u0026nbsp;control groups, respectively, desired the\u0026nbsp;index pregnancy \u003cstrong\u003e(Table 2)\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003cstrong\u003e: Obstetrics-related characteristics of\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003elabor attending women at public hospitals in the North Wollo Zone, 2022/2023\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"644\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003eCase n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003eControl n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003eGestational age (n=353)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003ePreterm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e23 (19.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e57 (24.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eTerm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e81 (68.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e142 (60.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003ePost term\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e14 (11.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e36 (15.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eGravidity(n=353)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003ePrimigravida\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e9 (7.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e18 (7.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eMultigravida\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e109 (92.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e217 (92.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003eParity (353)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003eNulliparity\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e9 (7.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e18 (7.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003ePrimipara\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e29 (24.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e84 (35.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eMultipara\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e80 (67.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e133 (56.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003eInterpregnancy interval (n=326)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;12 Month\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e11 (10.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e25 (11.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e12-24 Month\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e31 (28.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e80 (36.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026gt;24 Month\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e67 (61.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e112 (51.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eHistory of Multiple pregnancy (n=326)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e19 (17.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e18 (8.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e90 (82.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e199 (91.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eHistory of abortion (n=326)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e47 (43.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e26 (12.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e62 (56.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e191 (88.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eType of abortion (n=73)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003eInduced\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e22 (46.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e13 (50)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eSpontaneous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e25 (53.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e13(50)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003ePrevious history of PROM (n=326)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e60 (55.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e26 (12.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e49 (45.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e191 (88.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eDesire for last pregnancy (n=326)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e76 (69.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e170 (78.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e33 (30.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e47 (21.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"25%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003ePrevious history of C/S (n=326)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e44 (40.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"25%\" valign=\"top\"\u003e\n \u003cp\u003e49 (22.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e65(59.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"33.333333333333336%\" valign=\"top\"\u003e\n \u003cp\u003e168 (77.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eMaternal health service-related characteristics of\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003ethe\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003estudy participants\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAmong\u0026nbsp;the study participants,\u0026nbsp;more than half\u0026nbsp;(73\u0026nbsp;[61.9%]) and 128 (59.0%) had four ANC\u0026nbsp;visits,\u0026nbsp;and many of them had\u0026nbsp;visited\u0026nbsp;government health institutions. Moreover, 65 (59.6%)\u0026nbsp;patients\u0026nbsp;and 112 (51.6%) controls delivered at\u0026nbsp;hospitals\u0026nbsp;\u003cstrong\u003e(Table 3)\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003cstrong\u003e: Maternal health service variables of\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003erespondents attending at public hospitals in North Wollo Zone, 2022/2023\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"635\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.708661417322833%\" valign=\"top\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.448818897637796%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.055118110236222%\" valign=\"top\"\u003e\n \u003cp\u003eCase\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.787401574803148%\" valign=\"top\"\u003e\n \u003cp\u003eControl\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.708661417322833%\" rowspan=\"4\" valign=\"top\"\u003e\n \u003cp\u003eNo of ANC Visit (n=353)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.448818897637796%\" valign=\"top\"\u003e\n \u003cp\u003eLess than Two ANC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.055118110236222%\" valign=\"top\"\u003e\n \u003cp\u003e6 (5.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.787401574803148%\" valign=\"top\"\u003e\n \u003cp\u003e17 (7.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.5%\" valign=\"top\"\u003e\n \u003cp\u003eThree ANC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.5%\" valign=\"top\"\u003e\n \u003cp\u003e21 (17.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30%\" valign=\"top\"\u003e\n \u003cp\u003e58 (26.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.5%\" valign=\"top\"\u003e\n \u003cp\u003eFour ANC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.5%\" valign=\"top\"\u003e\n \u003cp\u003e73 (61.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30%\" valign=\"top\"\u003e\n \u003cp\u003e128 (59.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.5%\" valign=\"top\"\u003e\n \u003cp\u003eMore than four\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.5%\" valign=\"top\"\u003e\n \u003cp\u003e18 (15.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30%\" valign=\"top\"\u003e\n \u003cp\u003e32 (14.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.708661417322833%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003ePlace for ANC (n=353)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.448818897637796%\" valign=\"top\"\u003e\n \u003cp\u003eGov\u0026rsquo;t Health Institution\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.055118110236222%\" valign=\"top\"\u003e\n \u003cp\u003e87 (73.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.787401574803148%\" valign=\"top\"\u003e\n \u003cp\u003e159 (67.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.5%\" valign=\"top\"\u003e\n \u003cp\u003ePrivate Institution\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.5%\" valign=\"top\"\u003e\n \u003cp\u003e31 (26.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30%\" valign=\"top\"\u003e\n \u003cp\u003e76 (32.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.708661417322833%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003ePlace of last delivery (n=326)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.448818897637796%\" valign=\"top\"\u003e\n \u003cp\u003eHospital\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.055118110236222%\" valign=\"top\"\u003e\n \u003cp\u003e65 (59.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.787401574803148%\" valign=\"top\"\u003e\n \u003cp\u003e112 (51.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.5%\" valign=\"top\"\u003e\n \u003cp\u003eHealth Centre\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.5%\" valign=\"top\"\u003e\n \u003cp\u003e39 (35.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30%\" valign=\"top\"\u003e\n \u003cp\u003e89 (41.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.5%\" valign=\"top\"\u003e\n \u003cp\u003ePrivate Clinic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.5%\" valign=\"top\"\u003e\n \u003cp\u003e5 (4.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30%\" valign=\"top\"\u003e\n \u003cp\u003e16 (7.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.708661417322833%\" rowspan=\"3\" valign=\"top\"\u003e\n \u003cp\u003eMode of last delivery (n=326)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.448818897637796%\" valign=\"top\"\u003e\n \u003cp\u003eSVD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.055118110236222%\" valign=\"top\"\u003e\n \u003cp\u003e61 (56.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.787401574803148%\" valign=\"top\"\u003e\n \u003cp\u003e161 (74.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.5%\" valign=\"top\"\u003e\n \u003cp\u003eC/S\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.5%\" valign=\"top\"\u003e\n \u003cp\u003e43 (39.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30%\" valign=\"top\"\u003e\n \u003cp\u003e50 (20.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.5%\" valign=\"top\"\u003e\n \u003cp\u003eInstrumental Delivery\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.5%\" valign=\"top\"\u003e\n \u003cp\u003e5 (4.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30%\" valign=\"top\"\u003e\n \u003cp\u003e6 (2.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.708661417322833%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eHistory of cervical cerclage (n=326)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.448818897637796%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.055118110236222%\" valign=\"top\"\u003e\n \u003cp\u003e18 (16.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.787401574803148%\" valign=\"top\"\u003e\n \u003cp\u003e15 (6.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"42.5%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.5%\" valign=\"top\"\u003e\n \u003cp\u003e91 (83.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"30%\" valign=\"top\"\u003e\n \u003cp\u003e202 (93.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eClinical and medical characteristics of\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003ethe\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003estudy participants\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eRegarding clinical conditions,\u0026nbsp;chronic cough was experienced in 25 (21.2%) and 11 (4.7%) of the\u0026nbsp;patients\u0026nbsp;and controls, respectively. Furthermore,\u0026nbsp;approximately\u0026nbsp;half of the 63\u0026nbsp;patients\u0026nbsp;(53.4%) and 39 (16.6%)\u0026nbsp;of the controls\u0026nbsp;had abnormal vaginal discharge. Twenty-five (21.2%) of the\u0026nbsp;patients\u0026nbsp;had polyhydramnios,\u0026nbsp;and only 15 (6.4%) of\u0026nbsp;the\u0026nbsp;controls had\u0026nbsp;this\u0026nbsp;condition. There was a comparable percentage of participants in both\u0026nbsp;the\u0026nbsp;cases\u0026nbsp;(6,\u0026nbsp;5.1%) and controls\u0026nbsp;(13,\u0026nbsp;5.5%) with PIH. Almost half of the participants in the case group\u0026nbsp;(63,\u0026nbsp;53.4%) had\u0026nbsp;UTIs,\u0026nbsp;but far\u0026nbsp;fewer\u0026nbsp;than a quarter of the participants in the control group\u0026nbsp;(37,\u0026nbsp;15.7%)\u0026nbsp;had infections\u0026nbsp;\u003cstrong\u003e(Table 4)\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e4\u003c/strong\u003e\u003cstrong\u003e: Clinical and medical conditions participants attending\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;at public hospitals in the North Wollo Zone, 2022/2023\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"656\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.36585365853659%\" valign=\"top\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.78048780487805%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.75%\" valign=\"top\"\u003e\n \u003cp\u003eCase\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.103658536585368%\" valign=\"top\"\u003e\n \u003cp\u003eControl\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.36585365853659%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eChronic cough (n=353)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.78048780487805%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.75%\" valign=\"top\"\u003e\n \u003cp\u003e25 (21.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.103658536585368%\" valign=\"top\"\u003e\n \u003cp\u003e11 (4.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.79245283018868%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.00943396226415%\" valign=\"top\"\u003e\n \u003cp\u003e93 (78.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.198113207547166%\" valign=\"top\"\u003e\n \u003cp\u003e224 (95.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.36585365853659%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eSTI (n=353)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.78048780487805%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.75%\" valign=\"top\"\u003e\n \u003cp\u003e16 (13.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.103658536585368%\" valign=\"top\"\u003e\n \u003cp\u003e13 (5.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.79245283018868%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.00943396226415%\" valign=\"top\"\u003e\n \u003cp\u003e102 (86.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.198113207547166%\" valign=\"top\"\u003e\n \u003cp\u003e222 (94.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.36585365853659%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eAbnormal vaginal discharge (n=353)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.78048780487805%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.75%\" valign=\"top\"\u003e\n \u003cp\u003e63 (53.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.103658536585368%\" valign=\"top\"\u003e\n \u003cp\u003e39 (16.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.79245283018868%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.00943396226415%\" valign=\"top\"\u003e\n \u003cp\u003e55 (46.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.198113207547166%\" valign=\"top\"\u003e\n \u003cp\u003e196 (83.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.36585365853659%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003ePolyhydramnios (n=353)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.78048780487805%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.75%\" valign=\"top\"\u003e\n \u003cp\u003e25 (21.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.103658536585368%\" valign=\"top\"\u003e\n \u003cp\u003e15 (6.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.79245283018868%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.00943396226415%\" valign=\"top\"\u003e\n \u003cp\u003e93 (78.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.198113207547166%\" valign=\"top\"\u003e\n \u003cp\u003e220 (93.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.36585365853659%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eHemoglobin Value (n=353)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.78048780487805%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.75%\" valign=\"top\"\u003e\n \u003cp\u003e20 (17.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.103658536585368%\" valign=\"top\"\u003e\n \u003cp\u003e20 (8.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.79245283018868%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026gt;=11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.00943396226415%\" valign=\"top\"\u003e\n \u003cp\u003e98 (83.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.198113207547166%\" valign=\"top\"\u003e\n \u003cp\u003e215 (91.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.36585365853659%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eMUAC in cm (n=353)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.78048780487805%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.75%\" valign=\"top\"\u003e\n \u003cp\u003e89 (75.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.103658536585368%\" valign=\"top\"\u003e\n \u003cp\u003e138 (58.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.79245283018868%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026gt;=23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.00943396226415%\" valign=\"top\"\u003e\n \u003cp\u003e29 (24.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.198113207547166%\" valign=\"top\"\u003e\n \u003cp\u003e97 (41.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.36585365853659%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003ePIH (n=353)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.78048780487805%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.75%\" valign=\"top\"\u003e\n \u003cp\u003e6 (5.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.103658536585368%\" valign=\"top\"\u003e\n \u003cp\u003e13 (5.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.79245283018868%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.00943396226415%\" valign=\"top\"\u003e\n \u003cp\u003e112 (94.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.198113207547166%\" valign=\"top\"\u003e\n \u003cp\u003e222 (94.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.36585365853659%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eGestational DM (n=353)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.78048780487805%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.75%\" valign=\"top\"\u003e\n \u003cp\u003e5 (4.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.103658536585368%\" valign=\"top\"\u003e\n \u003cp\u003e11 (4.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.79245283018868%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.00943396226415%\" valign=\"top\"\u003e\n \u003cp\u003e113 (95.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.198113207547166%\" valign=\"top\"\u003e\n \u003cp\u003e224 (95.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.36585365853659%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eOn ART (n=353)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.78048780487805%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.75%\" valign=\"top\"\u003e\n \u003cp\u003e11 (9.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.103658536585368%\" valign=\"top\"\u003e\n \u003cp\u003e16 (6.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.79245283018868%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.00943396226415%\" valign=\"top\"\u003e\n \u003cp\u003e107 (90.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.198113207547166%\" valign=\"top\"\u003e\n \u003cp\u003e219 (93.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.36585365853659%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eSuspected sepsis (n=353)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.78048780487805%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.75%\" valign=\"top\"\u003e\n \u003cp\u003e41 (34.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.103658536585368%\" valign=\"top\"\u003e\n \u003cp\u003e18 (7.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.79245283018868%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.00943396226415%\" valign=\"top\"\u003e\n \u003cp\u003e77 (65.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.198113207547166%\" valign=\"top\"\u003e\n \u003cp\u003e217 (92.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.36585365853659%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eUTI (n=353)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.78048780487805%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.75%\" valign=\"top\"\u003e\n \u003cp\u003e63 (53.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.103658536585368%\" valign=\"top\"\u003e\n \u003cp\u003e37 (15.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.79245283018868%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.00943396226415%\" valign=\"top\"\u003e\n \u003cp\u003e55 (46.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.198113207547166%\" valign=\"top\"\u003e\n \u003cp\u003e198 (84.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.36585365853659%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eVaginal bleeding (n=353)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.78048780487805%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.75%\" valign=\"top\"\u003e\n \u003cp\u003e13 (11.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.103658536585368%\" valign=\"top\"\u003e\n \u003cp\u003e15 (6.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.79245283018868%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.00943396226415%\" valign=\"top\"\u003e\n \u003cp\u003e105 (89.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.198113207547166%\" valign=\"top\"\u003e\n \u003cp\u003e220 (93.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"35.36585365853659%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eSexual intercourse at third trimester (n=353)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"23.78048780487805%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"18.75%\" valign=\"top\"\u003e\n \u003cp\u003e53 (44.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"22.103658536585368%\" valign=\"top\"\u003e\n \u003cp\u003e100 (42.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"36.79245283018868%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"29.00943396226415%\" valign=\"top\"\u003e\n \u003cp\u003e65 (55.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"34.198113207547166%\" valign=\"top\"\u003e\n \u003cp\u003e135 (57.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eDeterminants of premature membrane\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;rupture\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA bivariable logistic regression was performed for each independent variable.\u0026nbsp;The\u0026nbsp;variables\u0026nbsp;included\u0026nbsp;residence, history of C/S, history of cervical cerclage, desire for\u0026nbsp;a previous\u0026nbsp;pregnancy, history of multiple\u0026nbsp;pregnancies, history of abortion, history of PROM, chronic cough,\u0026nbsp;STIs,\u0026nbsp;abnormal vaginal discharge, polyhydramnios, Hgb value \u0026lt;11 gm/dl, MAUC \u0026lt;23 cm, suspected sepsis,\u0026nbsp;UTIs\u0026nbsp;and vaginal bleeding,\u0026nbsp;all of which had P values\u0026nbsp;\u0026lt;0.25. These variables were transferred to\u0026nbsp;a multivariable\u0026nbsp;logistic regression model.\u0026nbsp;Overall, a\u0026nbsp;history of C/S,\u0026nbsp;a\u0026nbsp;history of abortion,\u0026nbsp;a\u0026nbsp;history of PROM, chronic cough, MAUC \u0026lt;23 cm, suspected sepsis and\u0026nbsp;UTIs\u0026nbsp;were found\u0026nbsp;to be\u0026nbsp;statistically significant\u0026nbsp;determining\u0026nbsp;factors for PROM,\u0026nbsp;with\u0026nbsp;p\u0026nbsp;values\u0026nbsp;\u0026lt;0.05.\u003c/p\u003e\n\u003cp\u003eA history\u0026nbsp;of C/S was identified as one of the\u0026nbsp;determining\u0026nbsp;factors for PROM. Those participants who had\u0026nbsp;a\u0026nbsp;history\u0026nbsp;of\u0026nbsp;C/S\u0026nbsp;had\u0026nbsp;2.11\u0026nbsp;times greater\u0026nbsp;odds (95% CI: 1.05-4.23) of having PROM than those who\u0026nbsp;did not\u0026nbsp;have\u0026nbsp;a history of\u0026nbsp;C/S. Participants who had\u0026nbsp;a\u0026nbsp;history of abortion\u0026nbsp;were\u0026nbsp;more\u0026nbsp;likely to have\u0026nbsp;PROM\u0026nbsp;than\u0026nbsp;those who\u0026nbsp;had not had a history of abortion\u0026nbsp;(AOR= 3.68 95% CI: 1.70-7.94).\u0026nbsp;In addition,\u0026nbsp;the odds of PROM among pregnant women who had\u0026nbsp;a\u0026nbsp;history of PROM and chronic cough were 3.89 and 4.23, respectively,\u0026nbsp;with 95%\u0026nbsp;CIs of\u0026nbsp;1.73-8.71 and 1.47-12.18, respectively, compared with their\u0026nbsp;counterparts \u003cstrong\u003e(Table 5)\u003c/strong\u003e.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 5:\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eDeterminant\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;factors of premature rupture of membrane respondents at public hospitals\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003ein\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;North Wollo Zone, 2022/2023\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"784\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.18158567774936%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eVariables\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.718670076726342%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eCategory\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"27.74936061381074%\" colspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003ePROM status\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.728900255754477%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eCOR (95%CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.601023017902813%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eAOR (95%CI)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.020460358056265%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"47.92626728110599%\" valign=\"top\"\u003e\n \u003cp\u003eCase n (%) N=109\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"52.07373271889401%\" valign=\"top\"\u003e\n \u003cp\u003eControl n (%) N=217\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.18158567774936%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eResident\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.718670076726342%\" valign=\"top\"\u003e\n \u003cp\u003eRural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.29923273657289%\" valign=\"top\"\u003e\n \u003cp\u003e43 (39.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.450127877237852%\" valign=\"top\"\u003e\n \u003cp\u003e102 (47.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.728900255754477%\" valign=\"top\"\u003e\n \u003cp\u003e0.73 (0.46-1.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.601023017902813%\" valign=\"top\"\u003e\n \u003cp\u003e0.90(0.45-1.82)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.020460358056265%\" valign=\"top\"\u003e\n \u003cp\u003e0.78\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.025316455696203%\" valign=\"top\"\u003e\n \u003cp\u003eUrban\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.455696202531644%\" valign=\"top\"\u003e\n \u003cp\u003e66(61.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.879746835443036%\" valign=\"top\"\u003e\n \u003cp\u003e115 (53.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.462025316455698%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.303797468354432%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.873417721518987%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.18158567774936%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eHistory of C/S\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.718670076726342%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.29923273657289%\" valign=\"top\"\u003e\n \u003cp\u003e44 (40.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.450127877237852%\" valign=\"top\"\u003e\n \u003cp\u003e49 (22.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.728900255754477%\" valign=\"top\"\u003e\n \u003cp\u003e2.32 (1.41-3.82)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.601023017902813%\" valign=\"top\"\u003e\n \u003cp\u003e2.11 (1.05-4.23)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.020460358056265%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.035\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.025316455696203%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.455696202531644%\" valign=\"top\"\u003e\n \u003cp\u003e65(59.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.879746835443036%\" valign=\"top\"\u003e\n \u003cp\u003e168 (77.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.462025316455698%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.303797468354432%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.873417721518987%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.18158567774936%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eHistory of cervical cerclage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.718670076726342%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.29923273657289%\" valign=\"top\"\u003e\n \u003cp\u003e18 (16.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.450127877237852%\" valign=\"top\"\u003e\n \u003cp\u003e15 (6.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.728900255754477%\" valign=\"top\"\u003e\n \u003cp\u003e2.66 (1.29-5.52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.601023017902813%\" valign=\"top\"\u003e\n \u003cp\u003e2.12 (0.75-5.97)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.020460358056265%\" valign=\"top\"\u003e\n \u003cp\u003e0.16\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.025316455696203%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.455696202531644%\" valign=\"top\"\u003e\n \u003cp\u003e91 (83.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.879746835443036%\" valign=\"top\"\u003e\n \u003cp\u003e202 (93.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.462025316455698%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.303797468354432%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.873417721518987%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.18158567774936%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eDesire for the pregnancy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.718670076726342%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.29923273657289%\" valign=\"top\"\u003e\n \u003cp\u003e76 (69.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.450127877237852%\" valign=\"top\"\u003e\n \u003cp\u003e170 (78.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.728900255754477%\" valign=\"top\"\u003e\n \u003cp\u003e0.64 (0.38-1.07)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.601023017902813%\" valign=\"top\"\u003e\n \u003cp\u003e0.89 (0.41-1.93)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.020460358056265%\" valign=\"top\"\u003e\n \u003cp\u003e0.78\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.025316455696203%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.455696202531644%\" valign=\"top\"\u003e\n \u003cp\u003e33 (30.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.879746835443036%\" valign=\"top\"\u003e\n \u003cp\u003e47 (21.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.462025316455698%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.303797468354432%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.873417721518987%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.18158567774936%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eHistory of Multiple pregnancy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.718670076726342%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.29923273657289%\" valign=\"top\"\u003e\n \u003cp\u003e19 (17.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.450127877237852%\" valign=\"top\"\u003e\n \u003cp\u003e18 (8.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.728900255754477%\" valign=\"top\"\u003e\n \u003cp\u003e2.33 (1.17-4.66)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.601023017902813%\" valign=\"top\"\u003e\n \u003cp\u003e1.58 (0.55-4.56)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.020460358056265%\" valign=\"top\"\u003e\n \u003cp\u003e0.39\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.025316455696203%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.455696202531644%\" valign=\"top\"\u003e\n \u003cp\u003e90 (82.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.879746835443036%\" valign=\"top\"\u003e\n \u003cp\u003e199 (91.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.462025316455698%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.303797468354432%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.873417721518987%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.18158567774936%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eHistory of Abortion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.718670076726342%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.29923273657289%\" valign=\"top\"\u003e\n \u003cp\u003e47 (43.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.450127877237852%\" valign=\"top\"\u003e\n \u003cp\u003e26 (12.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.728900255754477%\" valign=\"top\"\u003e\n \u003cp\u003e5.57(3.19-9.73)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.601023017902813%\" valign=\"top\"\u003e\n \u003cp\u003e3.68 (1.70-7.94)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.020460358056265%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.025316455696203%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.455696202531644%\" valign=\"top\"\u003e\n \u003cp\u003e62 (56.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.879746835443036%\" valign=\"top\"\u003e\n \u003cp\u003e191 (88.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.462025316455698%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.303797468354432%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.873417721518987%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.18158567774936%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eHistory of PROM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.718670076726342%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.29923273657289%\" valign=\"top\"\u003e\n \u003cp\u003e60 (55.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.450127877237852%\" valign=\"top\"\u003e\n \u003cp\u003e26 (12.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.728900255754477%\" valign=\"top\"\u003e\n \u003cp\u003e9.0 (5.15-15.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.601023017902813%\" valign=\"top\"\u003e\n \u003cp\u003e3.89 (1.73-8.71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.020460358056265%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.025316455696203%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.455696202531644%\" valign=\"top\"\u003e\n \u003cp\u003e49 (45.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.879746835443036%\" valign=\"top\"\u003e\n \u003cp\u003e191 (88.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.462025316455698%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.303797468354432%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.873417721518987%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.18158567774936%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eHaving Chronic cough\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.718670076726342%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.29923273657289%\" valign=\"top\"\u003e\n \u003cp\u003e24 (22.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.450127877237852%\" valign=\"top\"\u003e\n \u003cp\u003e9 (4.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.728900255754477%\" valign=\"top\"\u003e\n \u003cp\u003e5.47 (2.59-11.58)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.601023017902813%\" valign=\"top\"\u003e\n \u003cp\u003e4.23 (1.47-12.18)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.020460358056265%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.008\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.025316455696203%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.455696202531644%\" valign=\"top\"\u003e\n \u003cp\u003e85 (82.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.879746835443036%\" valign=\"top\"\u003e\n \u003cp\u003e208 (95.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.462025316455698%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.303797468354432%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.873417721518987%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.18158567774936%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eHaving STI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.718670076726342%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.29923273657289%\" valign=\"top\"\u003e\n \u003cp\u003e15 (13.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.450127877237852%\" valign=\"top\"\u003e\n \u003cp\u003e11 (5.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.728900255754477%\" valign=\"top\"\u003e\n \u003cp\u003e2.68 (1.24-5.78)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.601023017902813%\" valign=\"top\"\u003e\n \u003cp\u003e0.94 (0.29-3.10)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.020460358056265%\" valign=\"top\"\u003e\n \u003cp\u003e0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.025316455696203%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.455696202531644%\" valign=\"top\"\u003e\n \u003cp\u003e94 (86.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.879746835443036%\" valign=\"top\"\u003e\n \u003cp\u003e206 (94.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.462025316455698%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.303797468354432%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.873417721518987%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.18158567774936%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eHaving abnormal vaginal Discharge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.718670076726342%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.29923273657289%\" valign=\"top\"\u003e\n \u003cp\u003e60 (55.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.450127877237852%\" valign=\"top\"\u003e\n \u003cp\u003e38 (17.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.728900255754477%\" valign=\"top\"\u003e\n \u003cp\u003e5.76 (3.50-9.48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.601023017902813%\" valign=\"top\"\u003e\n \u003cp\u003e2.56 (1.20-5.43)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.020460358056265%\" valign=\"top\"\u003e\n \u003cp\u003e0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.025316455696203%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.455696202531644%\" valign=\"top\"\u003e\n \u003cp\u003e49 (45.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.879746835443036%\" valign=\"top\"\u003e\n \u003cp\u003e179 (82.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.462025316455698%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.303797468354432%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.873417721518987%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.18158567774936%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003ePolyhydramnios\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.718670076726342%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.29923273657289%\" valign=\"top\"\u003e\n \u003cp\u003e23 (21.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.450127877237852%\" valign=\"top\"\u003e\n \u003cp\u003e14 (6.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.728900255754477%\" valign=\"top\"\u003e\n \u003cp\u003e3.94 (2.00-7.82)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.601023017902813%\" valign=\"top\"\u003e\n \u003cp\u003e1.89 (0.71-5.00)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.020460358056265%\" valign=\"top\"\u003e\n \u003cp\u003e0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.025316455696203%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.455696202531644%\" valign=\"top\"\u003e\n \u003cp\u003e86 (78.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.879746835443036%\" valign=\"top\"\u003e\n \u003cp\u003e203 (93.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.462025316455698%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.303797468354432%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.873417721518987%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.18158567774936%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eHgb Value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.718670076726342%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.29923273657289%\" valign=\"top\"\u003e\n \u003cp\u003e20 (18.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.450127877237852%\" valign=\"top\"\u003e\n \u003cp\u003e17 (7.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.728900255754477%\" valign=\"top\"\u003e\n \u003cp\u003e2.20 (1.32-3.53)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.601023017902813%\" valign=\"top\"\u003e\n \u003cp\u003e1.20 (0.44-3.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.020460358056265%\" valign=\"top\"\u003e\n \u003cp\u003e0.67\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.025316455696203%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026gt;=11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.455696202531644%\" valign=\"top\"\u003e\n \u003cp\u003e89 (81.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.879746835443036%\" valign=\"top\"\u003e\n \u003cp\u003e200 (92.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.462025316455698%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.303797468354432%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.873417721518987%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.18158567774936%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eMAUC in Cm\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.718670076726342%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.29923273657289%\" valign=\"top\"\u003e\n \u003cp\u003e83 (76.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.450127877237852%\" valign=\"top\"\u003e\n \u003cp\u003e128 (60.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.728900255754477%\" valign=\"top\"\u003e\n \u003cp\u003e2.16 (1.32-3.53)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.601023017902813%\" valign=\"top\"\u003e\n \u003cp\u003e3.47 (1.53-7.84)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.020460358056265%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.003\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.025316455696203%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026gt;=23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.455696202531644%\" valign=\"top\"\u003e\n \u003cp\u003e26 (23.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.879746835443036%\" valign=\"top\"\u003e\n \u003cp\u003e89 (40.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.462025316455698%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.303797468354432%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.873417721518987%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.18158567774936%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eSuspected sepsis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.718670076726342%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.29923273657289%\" valign=\"top\"\u003e\n \u003cp\u003e41 (37.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.450127877237852%\" valign=\"top\"\u003e\n \u003cp\u003e17 (7.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.728900255754477%\" valign=\"top\"\u003e\n \u003cp\u003e6.45 (3.50-11.84)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.601023017902813%\" valign=\"top\"\u003e\n \u003cp\u003e2.99 (1.25-7.19)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.020460358056265%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.014\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.025316455696203%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.455696202531644%\" valign=\"top\"\u003e\n \u003cp\u003e68 (62.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.879746835443036%\" valign=\"top\"\u003e\n \u003cp\u003e200 (92.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.462025316455698%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.303797468354432%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.873417721518987%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.18158567774936%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eUTI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.718670076726342%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.29923273657289%\" valign=\"top\"\u003e\n \u003cp\u003e60 (55.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.450127877237852%\" valign=\"top\"\u003e\n \u003cp\u003e33 (15.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.728900255754477%\" valign=\"top\"\u003e\n \u003cp\u003e6.13 (3.70-10.15)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.601023017902813%\" valign=\"top\"\u003e\n \u003cp\u003e3.14 (1.50-6.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.020460358056265%\" valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.003\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.025316455696203%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.455696202531644%\" valign=\"top\"\u003e\n \u003cp\u003e49 (45.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.879746835443036%\" valign=\"top\"\u003e\n \u003cp\u003e184 (84.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.462025316455698%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.303797468354432%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.873417721518987%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.18158567774936%\" rowspan=\"2\" valign=\"top\"\u003e\n \u003cp\u003eHaving Vaginal bleeding\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.718670076726342%\" valign=\"top\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.29923273657289%\" valign=\"top\"\u003e\n \u003cp\u003e12 (11.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.450127877237852%\" valign=\"top\"\u003e\n \u003cp\u003e14 (6.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.728900255754477%\" valign=\"top\"\u003e\n \u003cp\u003e1.82 (0.83-3.95)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.601023017902813%\" valign=\"top\"\u003e\n \u003cp\u003e1.17 (0.35-3.94)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"12.020460358056265%\" valign=\"top\"\u003e\n \u003cp\u003e0.80\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"12.025316455696203%\" valign=\"top\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.455696202531644%\" valign=\"top\"\u003e\n \u003cp\u003e97 (89.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.879746835443036%\" valign=\"top\"\u003e\n \u003cp\u003e203 (93.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.462025316455698%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.303797468354432%\" valign=\"top\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.873417721518987%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"Discussion","content":"\u003cp\u003ePremature membrane\u0026nbsp;rupture\u0026nbsp;is one of the most\u0026nbsp;common\u0026nbsp;maternal health concerns globally and\u0026nbsp;is more common\u0026nbsp;in developing countries,\u0026nbsp;including Ethiopia (2, 5, 6, 16). It contributes to a considerable number of maternal and neonatal\u0026nbsp;morbidities and mortalities. Additionally, PROM leads to economic and developmental burdens for the country due to prolonged hospital stays, increased drug expenses, and\u0026nbsp;increased workloads\u0026nbsp;for healthcare professionals (12). Therefore, it is crucial to identify and prevent determinant factors to minimize the impact of this problem.\u003c/p\u003e\n\u003cp\u003eIn this study, pregnant women with a history of C/S had 2.11 times\u0026nbsp;greater\u0026nbsp;odds of developing PROM\u0026nbsp;than\u0026nbsp;their counterparts. This finding is consistent with studies conducted in Senegal, eastern Ethiopia, Harar, northern Ethiopia, Tigray, and southern Ethiopia (15-17, 29, 30). The reason for this might be\u0026nbsp;that scar formation\u0026nbsp;could result\u0026nbsp;in\u0026nbsp;abnormalities in the fetal membrane that may result\u0026nbsp;in\u0026nbsp;leakage and tear of\u0026nbsp;the\u0026nbsp;membrane (31).\u003c/p\u003e\n\u003cp\u003eDifferent studies\u0026nbsp;performed\u0026nbsp;in Uganda and Ethiopia\u0026nbsp;have\u0026nbsp;indicated\u0026nbsp;that a\u0026nbsp;history of abortion\u0026nbsp;is associated with\u0026nbsp;increased odds for the occurrence of PROM (16, 17, 29, 32, 33).\u0026nbsp;Concurrently, our study also identified\u0026nbsp;a\u0026nbsp;history of abortion as a\u0026nbsp;determining\u0026nbsp;factor. Premature rupture of the membrane was 3.68 times more likely to occur in pregnant women who had a history of abortion than in those who\u0026nbsp;did not\u0026nbsp;experience abortion.\u0026nbsp;This finding\u0026nbsp;is also in line with a study\u0026nbsp;performed\u0026nbsp;in Iran in which abortion\u0026nbsp;was\u0026nbsp;positively associated with PROM (10). The reason for this could be that unaseptic abortion procedures, particularly dilatation and curettage, can disturb the natural elasticity of the cervix and uterus. This disturbance may result in uterine perforation and scarring, cervical insufficiency, and ultimately the premature rupture of membranes in the following pregnancy (34).\u003c/p\u003e\n\u003cp\u003eIn the current study, women with a history of PROM were 3.89 times more likely to develop PROM in their current pregnancy than\u0026nbsp;were\u0026nbsp;those without a history of PROM. The\u0026nbsp;results\u0026nbsp;of this study\u0026nbsp;are\u0026nbsp;supported by studies\u0026nbsp;performed\u0026nbsp;in India, Indonesia, Nigeria, Egypt, and different areas of Ethiopia (16, 17, 29, 35-41). This might be because, as subsequent pregnancies occur, the composition of the membranes becomes more delicate, marked by a decrease in collagen content. This reduction in collagen serves as a catalyst for the premature rupture of membranes (36).\u003c/p\u003e\n\u003cp\u003eIn addition, this study indicated\u0026nbsp;that\u0026nbsp;having a chronic cough was a\u0026nbsp;determining\u0026nbsp;factor for PROM. Pregnant women who had chronic coughs were 4.23 times more likely to develop PROM than their counterparts\u0026nbsp;were. Persistent coughing in pregnant women can result in chest spasms, leading to fatigue and pain. Additionally, prolonged, continuous, or intense coughing can trigger uterine contractions and premature membrane rupture. Additionally, detecting and addressing coughing promptly is crucial, as it may indicate an infection in the mother\u0026apos;s body.\u003c/p\u003e\n\u003cp\u003eA\u0026nbsp;MAUC \u0026lt;23 cm was another factor\u0026nbsp;identified\u0026nbsp;for the occurrence of PROM in the current study. Participants who had a MAUC \u0026lt;23 cm had 3.47 times\u0026nbsp;greater\u0026nbsp;odds of experiencing PROM than\u0026nbsp;their\u0026nbsp;counterparts. This is in agreement with studies\u0026nbsp;performed\u0026nbsp;in Ethiopia (15, 32, 40). The possible reason for this might be that MAUC\u0026lt;23 cm in pregnant women\u0026nbsp;indicates\u0026nbsp;nutritional deficiency. Nutrient deficiencies, including\u0026nbsp;deficiencies in\u0026nbsp;micronutrients (vitamin\u0026nbsp;D and ascorbic acid), affect the formation of collagen, which in turn distorts the structure and integrity of the fetal membrane. As a result, the body loses its ability to protect itself from degenerative processes caused by oxidative stress, which can\u0026nbsp;easily\u0026nbsp;lead to\u0026nbsp;membrane\u0026nbsp;leakage (42, 43).\u003c/p\u003e\n\u003cp\u003ePregnant women who were suspected of having sepsis had a 2.99 times\u0026nbsp;greater\u0026nbsp;likelihood of having PROM than those who were not suspected\u0026nbsp;of having sepsis\u0026nbsp;in the current study. The reason for this might be that if a pregnant individual develops a severe infection, including a uterine infection (chorioamnionitis), it can potentially contribute to PROM.\u0026nbsp;In addition, infections in the reproductive tract can lead to inflammation and damage to fetal membranes,\u0026nbsp;increasing the susceptibility to premature rupture\u0026nbsp;(44).\u003c/p\u003e\n\u003cp\u003eWomen who had UTIs had 3.14 times greater odds of having PROM than did their counterparts. Supported results were shown among studies performed in Uganda and Ethiopia (32, 33, 39). This could be attributed to the fact that bacterial infections in the urinary tract may progress upward through the vaginal and cervical passages, reaching the decidua and fetal membrane. This progression ultimately triggers the release of prostaglandins and cytokines, leading to softening of the cervix and increased vulnerability to ascending infections, ultimately resulting in PROM. Additionally, the direct release of bacterial proteolytic enzymes, such as proteases, collagenases, or trypsin, can potentially cause damage and weakness to the fetal membrane, culminating in its rupture. Consequently, it is advisable for healthcare providers to routinely screen pregnant women for UTIs and administer appropriate treatment during ANC visits (45).\u003c/p\u003e"},{"header":"Conclusions and Recommendations","content":"\u003cp\u003eThis study underscores the multifaceted nature of PROM, revealing its association with various maternal health factors,\u0026nbsp;including\u0026nbsp;a\u0026nbsp;history of\u0026nbsp;cesarean\u0026nbsp;section, abortion, previous PROM occurrences, chronic cough, maternal abdominal uterine circumference (MAUC) measurements, suspicion of sepsis, and urinary tract infections (UTIs). These findings echo similar research conducted in diverse regions, highlighting the consistency of risk factors contributing to PROM. Importantly, interventions aimed at identifying and addressing these determinants are imperative to mitigate the adverse maternal and neonatal outcomes associated with PROM, alleviate economic burdens on healthcare systems, and enhance overall maternal health outcomes. Routine screening and targeted interventions during antenatal care visits could play a pivotal role in reducing the incidence of PROM and improving maternal and neonatal health outcomes in affected populations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLimitations\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;of the study\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study encountered limitations related to recall bias for certain variables, such as a history of PROM and cervical cerclage. Additionally, social desirability bias was observed concerning personal and sensitive behavior, specifically in relation to the variable of engaging in sexual intercourse during the third trimester. Furthermore, the diagnosis of PROM in our setting relies solely on clinical history and physical examination, potentially impacting the selection of cases and controls. Moreover, the diagnosis of sepsis did not involve culture, leading to potential selection bias.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eAntenatal Care (ANC), Antiretroviral Therapy (ART), Caesarian Section (C/S), Mid-upper Arm Circumference (MAUC), Pregnancy-induced Hypertension (PIH), Preterm Premature Rupture of Membrane (PPROM), Premature Rupture of Membrane (PROM), Sexual Transmitted Disease (STI), Spontaneous Vaginal Delivery (SVD), Urinary Tract Infection (UTI), Woldiya Comprehensive Specialized Hospital (WCSH), World Health Organization (WHO).\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthical approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was approved by the Woldiya University Ethical Review Committee of the College of Health Sciences, and ethical approval was obtained.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLalibela, Mersa, and Woldiya, hospitals in the Amhara region, also provided explicit consent letters. Having fully understood the purpose of the study, each respondent provided written consent prior to the interview. In addition, the study was carried out in accordance with the Declaration of Helsinki. Recalcitrant study participants were excluded from the survey. Anonymized data were collected, and participant information was kept confidential.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publications:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eNot applicable.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of Data and Materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll the data generated or analyzed during this study are included in the manuscript and are available from the corresponding authors upon request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts\u0026nbsp;of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests in this work.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThere was no financial aid available for the current study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eST: Conceptualized the study, analyzed the data and critically edited the manuscript; EA \u0026amp; TB: Involved in the analysis and interpretation of the data, substantially revised and critically edited the manuscript; and MA \u0026amp; MAs: Designed and supervised the entire study, critically revised and contributed to the scientific content of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors are grateful to the medical directors and professionals at Woldiya Comprehensive and Specialized Hospital, Lalibela Referral Hospital, and Mersa Primary Hospital for their kind cooperation. We are also grateful to the data collectors and respondents to the study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eDeCherney AH, Roman AS, Nathan L, Laufer N. Current diagnosis \u0026amp; treatment obstetrics \u0026amp; gynecology: McGraw Hill Professional; 2018.\u003c/li\u003e\n\u003cli\u003eHuang S, Xia W, Sheng X, Qiu L, Zhang B, Chen T, et al. Maternal lead exposure and premature rupture of membranes: a birth cohort study in China. 2018;8(7): e021565.\u003c/li\u003e\n\u003cli\u003eSajitha A, Geetha K, Mumtaz PJIJCOG. The maternal and perinatal outcome in preterm premature rupture of membrane (PROM): a prospective observational study. 2020;5(4):208-12.\u003c/li\u003e\n\u003cli\u003eLiu J, Feng Z-C, Wu JJJotp. The incidence rate of premature rupture of membranes and its influence on fetal\u0026ndash;neonatal health: A Report from Mainland China. 2010;56(1):36-42.\u003c/li\u003e\n\u003cli\u003eDiriba TDJEG. 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Determinants of Premature Rupture of Membrane (PROM) Among Pregnant Women in Southern Ethiopia: A Case‒Control Study. 2022; 14:455.\u003c/li\u003e\n\u003cli\u003eChoudhary M, Rathore SB, Chowdhary J, Garg SJIJoRiMS. Pre and post conception risk factors in PROM. 2017;3(10):2594-8.\u003c/li\u003e\n\u003cli\u003eMeller CH, Carducci ME, Ceriani Cernadas JM, Ota\u0026ntilde;o LJAAP. Preterm premature rupture of membranes. 2018;116(4): e575-e81.\u003c/li\u003e\n\u003cli\u003eLawn JE, Blencowe H, Oza S, You D, Lee AC, Waiswa P, et al. Every Newborn: progress, priorities, and potential beyond survival. 2014;384(9938):189-205.\u003c/li\u003e\n\u003cli\u003ePearson L, Gandhi M, Admasu K, Keyes EBJIjog, obstetrics. User fees and maternity services in Ethiopia. 2011;115(3):310-5.\u003c/li\u003e\n\u003cli\u003eHealth FMo. Management of common obstetric complications. Federal Ministry of Health. 2010.\u003c/li\u003e\n\u003cli\u003eInstitute EPH. 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Sepsis definition: What\u0026rsquo;s new in the Treatment Guidelines. 2022;61(Suppl 1):67.\u003c/li\u003e\n\u003cli\u003eWerter DE, Kazemier BM, van Leeuwen E, de Rotte MC, Kuil SD, Pajkrt E, et al. Diagnostic work-up of urinary tract infections in pregnancy: study protocol of a prospective cohort study. 2022;12(9): e063813.\u003c/li\u003e\n\u003cli\u003eGetnet A, Oljira L, Assefa N, Tiruye G, Figa ZJH. Determinants of premature rupture of membrane among pregnant women in Harar town, Eastern Ethiopia: A case‒control study. 2023;9(4).\u003c/li\u003e\n\u003cli\u003eDelafield R, Pirkle CM, Dumont AJBp, childbirth. Predictors of uterine rupture in a large sample of women in Senegal and Mali: cross-sectional analysis of QUARITE trial data. 2018;18(1):1-8.\u003c/li\u003e\n\u003cli\u003eKaya DJEAmj. Risk factors for preterm premature rupture of membranes at Mulago hospital Kampala. 2001;78(2):65-9.\u003c/li\u003e\n\u003cli\u003eAssefa EM, Chane G, Teme A, Nigatu TAJPo. 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Prevalence of Preterm Premature Rupture of Membrane and Its Associated Factors among Pregnant Women Admitted in Debre Tabor General Hospital, North West Ethiopia: Institutional-Based Cross-Sectional Study. Obstetrics and gynecology international. 2020; 2020:4034680.\u003c/li\u003e\n\u003cli\u003eAbdel Maaboud RMR, Nossair WS, Ali AE-S, Ibrahem SAJTEJoHM. Incidence rate, risk factors and outcome of premature rupture of membranes (PROM) at zagazig university hospitals. 2021;85(1):2744-50.\u003c/li\u003e\n\u003cli\u003eOguntibeju OOJAJoB. The biochemical, physiological and therapeutic roles of ascorbic acid. 2008;7(25).\u003c/li\u003e\n\u003cli\u003eHassanzadeh A, Paknahad Z, Khoigani MGJAbr. The relationship between macroand micronutrients intake and risk of preterm premature rupture of membranes in pregnant women of Isfahan. 2016;5.\u003c/li\u003e\n\u003cli\u003eSurgers L, Valin N, Carbonne B, Bingen E, Lalande V, Pacanowski J, et al. Evolving microbiological epidemiology and high fetal mortality in 135 cases of bacteremia during pregnancy and postpartum. 2013; 32:107-13.\u003c/li\u003e\n\u003cli\u003eParry EJO, Gynecology. Managing PROM and PPROM. 2006;8(4):35-8.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"PROM, Premature membrane rupture, Determinant, Public hospitals, Labor care, Northeast Ethiopia, Unmatched case control","lastPublishedDoi":"10.21203/rs.3.rs-4047358/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4047358/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e: Premature rupture of membranes is a painless gush of amniotic fluid resulting from the rupture of membranes through the vaginal canal before the onset of uterine contractions and is responsible for increased perinatal mortality and neonatal morbidity. Therefore, identifying the determining factors is essential for minimizing its adverse impact. Despite the existence of this problem in the study area, there is a gap in identifying the factors affecting its occurrence.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eObjectives\u003c/strong\u003e: To assess the determinants of prematuremembrane rupture among mothers who attendedlabor at public hospitals in theNorth Wollo Zone, 2022/23.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods\u003c/strong\u003e: An unmatched case‒controlstudy was conducted from December 1, 2022, to March 30, 2023. Three public hospitals were selected through a lottery method, and by proportional allocation, a total of 353 participants (118 cases and 235 controls) receiving labor were recruited. Cases were selected through convenience sampling, while controls were recruited through systematic random sampling. The datawere collected using a structured questionnaire and card review, entered into EpiData 4.6 and analyzed using STATA version 17. Logistic regression was employed to identify determinants, and a P value \u0026lt; 0.05 in multivariable logistic regression was considered to indicate statistical significance.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e: Previous caesarian section (AOR: 2.11; 95% CI: 1.05–4.23), history of abortion (AOR: 3.68; 95% CI: 1.70–7.94), history of premature membrane rupture (AOR: 3.89; 95% CI: 1.73–8.71), chronic cough (AOR: 4.23; 95% CI: 1.47–12.18), mid-upper arm circumference \u0026lt;23 cm (AOR: 3.47; 95% CI: 1.53–7.84), suspected sepsis (AOR: 2.99; 95% CI: 1.25–1.99), and presence of urinary tract infection (AOR: 3.14; 95% CI: 1.50–6.60) were determinants of premature membrane rupture.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e: This study indicated that the aforementioned factors are determinants of premature membrane rupture. Therefore, hospitals need to increasethe proportion of vaginal deliveriesand provide strong advice regarding the complications of abortion. Moreover, early screening, diagnosis, and treatment should be applied for malnutrition, chronic cough, sepsis, and urinary tract infections.\u003c/p\u003e","manuscriptTitle":"Determinants of premature membrane rupture among mothers receiving labor care at different public hospitals in Northeast Ethiopia: An unmatched case control study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-13 06:06:36","doi":"10.21203/rs.3.rs-4047358/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"3ba3213b-a0b4-42a7-99d1-9763bb853e89","owner":[],"postedDate":"March 13th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-03-14T01:29:42+00:00","versionOfRecord":[],"versionCreatedAt":"2024-03-13 06:06:36","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4047358","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4047358","identity":"rs-4047358","version":["v1"]},"buildId":"zQwnuV7TCBrMSSSToR1PI","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}