Determinants of Neonatal Near Miss Among Newborns Admitted to SOS Mother & Child Hospital, Benadir Region, Somalia: A Case-Control Study

Determinants of Neonatal Near Miss Among Newborns Admitted to SOS Mother & Child Hospital, Benadir Region, Somalia: A 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 Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Determinants of Neonatal Near Miss Among Newborns Admitted to SOS Mother & Child Hospital, Benadir Region, Somalia: A Case-Control Study Hassan Abdullahi Dahie, Falis Ibrahim Mohamud, Mohamed Abdullahi Osman, and 10 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6743554/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 05 Nov, 2025 Read the published version in Maternal Health, Neonatology and Perinatology → Version 1 posted 10 You are reading this latest preprint version Abstract Background While the birth of a newborn is often a moment of great joy, it can be overshadowed by life-threatening complications that endanger survival in the early days of life. Neonatal near-miss (NNM) cases—infants who narrowly survive severe complications—offer a valuable lens for evaluating the quality of neonatal care. Somalia continues to experience one of the world’s highest neonatal mortality rates, reflecting major gaps in maternal and child health services. This study aimed to identify the determinants of neonatal near miss among neonates admitted to SOS Mother & Child Hospital, Benadir-Somalia. Methods An unmatched case-control study was conducted at SOS Mother and Child Hospital in Benadir region from December 2024 to April, 2025. A total of 243 NNM cases and 730 healthy neonate controls were included. Cases were identified using pragmatic and management criteria from the CLAP criteria. For each case, three controls were randomly selected. Data were collected using structured interviews and record reviews, and analyzed using SPSS v25. Logistic regression was employed to identify independent predictors of neonatal near miss. Results Significant predictors of neonatal near miss included lack of maternal (AOR: 2.61) and paternal education (AOR: 3.64), monthly household income below 100 USD (AOR: 2.82), short birth interval under 24 months (AOR: 1.97), lack of antenatal care (ANC) attendance (AOR: 6.25), history of stillbirth (AOR: 4.35), obstetric complications (AOR: 4.46), preterm or post-term birth (AOR: 1.89), prolonged labor (AOR: 3.58), home delivery (AOR: 4.76), maternal chronic illness (AOR: 3.37), male sex of the newborn (AOR: 1.86), and low birth weight (AOR: 9.34). Conclusion & recommendation Neonatal near miss remains a pressing public health concern in Somalia, influenced by socio-demographic, obstetric, and neonatal factors. Strengthening maternal education, promoting antenatal care, ensuring skilled birth attendance, and improving facility-based delivery services are essential to reducing neonatal complications and improving outcomes. Policymakers and humanitarian partners must prioritize investments in maternal and newborn health to address these preventable risks. Neonatal near miss Somalia determinants antenatal care neonatal outcomes maternal health case-control study. Background The arrival of a neonate evokes profound love and anticipation, as families eagerly await their beloved new addition 1 . However, this joyous occasion may sometimes be overshadowed by concerns stemming from critical life-threatening challenges for both the mother and the neonate. During this journey, many infants tragically lose their lives, while others experience near-miss events, narrowly escaping severe health complications. Annually, 135 million newborns enter the world, commencing their journey in an identical state of vulnerability. Yet, their prospects for survival and flourishing diverge markedly depending on the global context of their birth 2 . This spectrum ranges from high-income nations equipped with universal neonatal intensive care to environments where births occur at home, devoid of midwifery support, medical provisions, or institutional healthcare assistance. Globally, 2.3 million children died in the first month of life in 2022, equating to approximately 6,300 neonatal deaths every day. Sub-Saharan Africa accounted for 57% of these deaths, despite only having 30% of global live births. This disparity resulted in the region having the highest neonatal mortality rate in the world, with 27 deaths per 1,000 live births 3 . Although neonatal mortality is an indicator of neonatal health, it only reveals the tip of the iceberg, as most neonates who survive complications remain unnoticed. 2 Understanding the full extent of neonatal ill-health requires studying neonates who survived from severe complications (neonatal near miss) in addition to neonatal deaths 4 . Neonatal near miss is defined as a condition of newborn infant characterized by severe morbidity (near miss) of pragmatic and management criteria, but survived these conditions within the first 28 days of life 5 . Similar to the concept of maternal near miss, neonatal near miss (NNM) is gaining prominence as an emerging methodology and is increasingly recognized as a critical indicator for evaluating the quality of neonatal care 6 – 8 . This approach plays a pivotal role in efforts to mitigate preventable neonatal morbidity and mortality. Somalia faces one of the highest neonatal mortality rates globally, with 37 deaths per 1,000 live births, reflecting significant public health challenges. This crisis is compounded by limited access to quality healthcare and inadequate maternal health services, as only 24% of pregnant women receive at least four antenatal care visits, and just 32% of deliveries are attended by skilled birth attendants 9 , 10 . Prolonged conflict and instability have further weakened the country’s health infrastructure, leaving maternal and child healthcare services severely under-resourced and unable to meet the growing needs of the population 11 . Therefore, the study examined the determinants of neonatal near miss among neonates born in major public hospitals in the Benadir Region, Somalia. Methods Study Design This was a hospital-based unmatched case-control study designed to assess neonatal near-miss events by comparing affected neonates (cases) with healthy neonates (controls). Setting The study was conducted at SOS Mother and Child Hospital in the Benadir region, Somalia, from December 2024 to April 2025. This facility is a major maternal and child health hospital, offering comprehensive neonatal care with approximately 200 beds and admitting an average of 65 newborns monthly. Participants The study participants consisted of neonates admitted to SOS Mother and Child Hospital during the study period, classified into two groups: cases and controls. Cases included neonates who experienced at least one neonatal near-miss event within the first 27 days of life but ultimately survived. Identification of neonatal near-miss cases was based on criteria established by the Latin American Centre for Perinatology (CLAP), which include both pragmatic and management criteria. Pragmatic criteria were neonates born weighing less than 1750 grams, delivered before 33 weeks of gestation, or with an Apgar score of less than 7 at five minutes. Management criteria encompassed neonates who required critical clinical interventions such as therapeutic antibiotics, nasal continuous positive airway pressure (NCPAP), neonatal intubation, phototherapy initiated within 24 hours of birth, cardiopulmonary resuscitation, administration of vasoactive medications, anticonvulsants, surfactants, blood products, steroids for refractory hypoglycemia, or surgical procedures during their neonatal period 6 , 7 . Controls were healthy neonates selected from the hospital's postnatal wards. These neonates were born without complications, did not require any specialized medical interventions, and were discharged in stable condition. To enhance comparability, for every neonate identified as a near-miss case, three control neonates were carefully selected on the same day the near-miss event occurred 12 . Neonates were excluded from the study if they had an unknown or incomplete birth history, belonged to multiple gestations, experienced maternal absence during admission, possessed incomplete medical records, or were initially categorized as controls but subsequently reclassified as cases during the study period 13 . Sampling procedures Cases were selected using consecutive sampling. All neonates admitted to the newborn unit who met the neonatal near-miss (NNM) criteria during the study period were included as cases at the time of discharge. This ensured that every eligible case was captured without omission until the required sample size was achieved.For each case included in the study, three controls were randomly selected from among neonates who were born healthy and discharged without complications. A list of all eligible healthy neonates admitted to the postnatal ward was compiled using their registration numbers. From this list, controls were selected using computer-generated simple random sampling, maintaining a 1:3 case-to-control ratio. Sample size determination The sample size for this study was calculated using the double population proportion formula through the Epi Info 7 StatCalc program. The calculation was based on the following assumptions: a 95% confidence level, 80% power, and a case-to-control ratio of 1:3. The percentage of cases exposed to lack of ANC (12%) and the percentage of controls exposed to lack of ANC (5.7%) were taken from a study conducted in Northeast Ethiopia 14 . Based on these parameters, the required sample size was calculated to be 824 participants. After adjusting for an 18% non-response rate, the final sample size increased to 973 participants ( 243 cases and 730 controls). Data collection method Data was collected from the mothers of the neonates using a structured and pretested questionnaire, administered by trained interviewers. The questionnaire was carefully adapted from relevant literature to ensure its validity and relevance 13 , 15 , 16 . The data collectors used face-to-face interviews and client record review techniques to collect data. Interviews were conducted in private settings, primarily at the time of patient discharge, when cases had recovered from their illnesses and controls were physiologically stable and ready for discharge. In addition to interviews, relevant clinical data were extracted from hospital records with appropriate permissions. This dual approach enhanced data richness by providing objective clinical information alongside maternal reports. Study Variables The main outcome variable was neonatal near miss, defined as a newborn who survived a life-threatening complication within the first 28 days of life, coded as 1 = “Yes” and 0 = “No”. Independent variables included socio-demographic characteristics such as maternal age, education and occupation of both parents, marital status, household size, income, and residence. Obstetric history covered gravidity, parity, previous stillbirths, abortions, neonatal deaths, and birth intervals. Maternal health conditions during pregnancy—such as anemia, hypertension, diabetes, heart disease, and infections—were considered, along with health service factors like ANC attendance, number of visits, and complications during labor and delivery. Newborn-related variables included sex, gestational age, birth weight, APGAR score, and presentation. Critical interventions such as use of antibiotics, CPAP, intubation, phototherapy, CPR, and presence of congenital anomalies were also assessed to identify near-miss cases. Data quality control The data were collected by ten qualified midwives fluent in both English and Somali. Prior to data collection, they received an intensive two-day training that covered data collection procedures, the objectives of the study, questionnaire content, participant interaction, and ethical considerations such as confidentiality and privacy. One week before data collection began, a pretest was conducted on 5% of the sample to assess the clarity, validity, and usability of the questionnaire. Feedback from the pretest informed necessary revisions to enhance accuracy and ease of understanding for respondents. To ensure high data quality throughout the study, supervisors carried out random checks of completed questionnaires to verify adherence to the study protocol and maintain consistency and accuracy in data collection. Data analysis and processing All collected data were reviewed for completeness, accuracy, and consistency prior to analysis. Data cleaning was conducted to address any missing or inconsistent entries. The cleaned dataset was then analyzed using SPSS version 25. Descriptive statistics were used to summarize participants’ background characteristics. To assess associations between the dependent variable (neonatal near miss) and independent variables, Chi-square tests were employed. Variables showing a statistically significant association (p < 0.05) in the Chi-square test were included in a binary logistic regression model to identify independent predictors of neonatal near-miss events. The strength of associations was quantified using adjusted odds ratios (aORs) with 95% confidence intervals (CIs). A p-value of less than 0.05 was considered statistically significant in the final model. Ethical Considerations The study received ethical clearance from the Research Ethics Committee of SOS College of Health Science (Reference: SOSCHS/REC/2025/015), underscoring adherence to the highest standards of ethical conduct and research integrity. Informed consent was obtained from all participants before data collection, with strict measures in place to safeguard their privacy and confidentiality. Participation was fully voluntary, and individuals retained the right to withdraw from the study at any point without any form of penalty or disadvantage. Results Socio-demographic Characteristics The study included 973 participants, with 243 neonatal near miss (NNM) cases and 730 controls. Most participants (85%) lived in urban areas, though a higher proportion of cases (24.7%) were from rural areas compared to controls (11.8%). Maternal age was similar across groups, with over half of mothers under 25 years. The majority of mothers were married (96.3%), but unmarried mothers were slightly more common among cases (7%) than controls (2.6%). A large portion of mothers lacked formal education (64.9%), with this proportion higher among cases (79.8%) than controls (59.9%). Similarly, more fathers of cases had no formal education (81.1%) compared to controls (50%). Maternal employment status and family size were comparable between groups, with about 82% of mothers working and roughly 42% of families having fewer than five members. Regarding income, nearly half of all families earned less than 100 USD monthly, with a notably higher percentage among cases (69.1%) versus controls (40.1%) (Table 1 ). Table 1 Socio-demographic characteristics of respondents Variables Neonatal Near Miss Total N (%) P-value Case n (%) Control n (%) Residence 0.000 Urban 183 (75.3) 644 (88.2) 827 (85.0) Rural 60 (24.7) 86 (11.8) 146 (15.0) Maternal Age 0.421 35 years 15 (6.2) 32 (4.4) 47 (4.9) Maternal Marital Status 0.002 Married 226 (93.0) 711 (97.4) 937 (96.3) Unmarried 17 (7.0) 19 (2.6) 36 (3.7) Maternal education 0.000 No formal education 194 (79.8) 437 (59.9) 631 (64.9) Formal education 49 (20.2) 293 (40.1) 342 (35.1) Paternal education 0.000 No formal education 197 (81.1) 365 (50.0) 562 (57.8) Formal education 46 (18.9) 365 (50.0) 411 (42.2) Maternal working status 0.993 Working 199 (81.9) 598 (81.9) 797 (81.9) Not working 44 (18.1) 132 (18.1) 176 (18.1) Family size 0.893 < 5 Individuals 101 (41.6) 307 (42.1) 408 (41.9) ≥ 5 Individuals 142 (58.4) 423 (57.9) 565 (58.1) Monthly family income 0.000 < 100 USD 168 (69.1) 293 (40.1) 461 (47.4) ≥ 100 USD 75 (30.9) 437 (59.9) 512 (52.6) Maternal obstetric history and neoborn characteristics The study also assessed various obstetric and neonatal variables in relation to neonatal near miss (NNM) outcomes. Regarding parity, a larger proportion of NNM cases (78.6%) had more than three children, compared to 57.8% of controls, highlighting higher parity among cases. Short birth intervals were more common in NNM cases, with 47.7% having intervals shorter than 2 years, compared to 26.6% of controls. Similarly, antenatal care (ANC) attendance was significantly lower in NNM cases (21.4%) than in controls (63.6%), indicating a notable gap in maternal healthcare utilization. In terms of history of stillbirth, 21.0% of NNM cases had a previous stillbirth, compared to only 4.5% of controls. Obstetric complications were also more prevalent among cases (34.2%) than controls (10.4%), indicating that complications are more common in NNM pregnancies. Premature rupture of membranes (PROM) showed no significant difference between groups (17.3% of cases vs. 17.8% of controls). Regarding gestational age, a higher proportion of NNM cases (32.9%) were preterm (< 37 weeks), compared to 17.1% of controls. In contrast, term births (37–41 weeks) were more common in controls (77.8%) than in cases (65.0%). Prolonged labor was more frequent in NNM cases (22.2%) compared to controls (7.4%), suggesting a link between prolonged labor and NNM. Concerning place of delivery, a higher proportion of NNM cases (78.6%) delivered at home, compared to 51.2% of controls. No significant difference was found in the mode of delivery, with 62.6% of NNM cases and 66.3% of controls delivering vaginally. Chronic medical conditions were more common among NNM cases (69.1%) compared to controls (40.1%), suggesting that underlying health issues may contribute to NNM. In terms of baby sex, 65.8% of NNM cases had male babies, compared to 49.0% of controls. Finally, birth weight was significantly associated with NNM, as 45.3% of NNM cases had low birth weight, compared to only 8.2% of controls, with most controls (91.8%) having normal birth weight (Table 2 ). Table 2 Maternal obstetric history and neoborn characteristics Variables Neonatal Near Miss Total N (%) P-value Case n (%) Control n (%) Parity 0.000 ≤ 3 52 (21.4) 422 (57.8) 474 (48.7) > 3 191 (78.6) 308 (42.2) 499 (51.3) Short birth interval 0.000 Yes 116 (47.7) 194 (26.6) 310 (31.9) No 127 (52.3) 536 (73.4) 663 (68.1) ANC attendance 0.000 Yes 52 (21.4) 464 (63.6) 516 (53.0) No 191 (78.6) 266 (36.4) 457 (47.0) History of Stillbirth 0.000 Yes 51 (21.0) 33 (4.5) 84 (8.6) No 192 (79.0) 697 (95.5) 889 (91.4) Obstetric Complications 0.000 Yes 83 (34.2) 76 (10.4) 159 (16.3) No 160 (65.8) 654 (89.6) 814 (83.7) Premature Rupture of Membranes 0.853 Yes 42 (17.3) 130 (17.8) 172 (17.7) No 201 (82.7) 600 (82.2) 801 (82.3) Gestational Age at Birth 0.000 Preterm (< 37 weeks) 80 (32.9) 125 (17.1) 205 (21.1) Post-term (≥ 42 weeks) 5 (2.1) 37 (5.1) 42 (4.3) Term (37–41 weeks) 158 (65.0) 568 (77.8) 726 (74.6) Prolonged labour 0.000 Yes 54 (22.2) 54 (7.4) 108 (11.1) No 189 (77.8) 676 (92.6) 865 (88.9) Place of Delivery 0.000 Health Facility 52 (21.4) 356 (48.8) 408 (41.9) Home 191 (78.6) 374 (51.2) 565 (58.1) Mode of Delivery 0.287 SVD 152 (62.6) 484 (66.3) 636 (65.4) Non SVD 91 (37.4) 246 (33.7) 337 (34.6) Chronic Medical Conditions 0.000 Yes 168 (69.1) 293 (40.1) 461 (47.4) No 75 (30.9) 437 (59.9) 512 (52.6) Baby sex 0.000 Male 160 (65.8) 372 (51.0) 532 (54.7) Female 83 (32.2) 358 (49.0) 441 (45.3) Birth weight 0.000 Low birth weight 110 (45.3) 60 (8.2) 170 (17.5) Normal birth weight 133 (54.7) 670 (91.8) 803 (82.5) Predictors of Neonatal Near Miss Identified Through Multivariable Analysis Variables that showed statistical significance in the chi-square analysis were further examined using multivariable logistic regression. The multivariable analysis identified several factors significantly associated with neonatal near miss. These included maternal and paternal education, low monthly family income, high parity, short birth interval, lack of antenatal care (ANC) attendance, history of stillbirth, obstetric complications, non-term gestational age, prolonged labor, place of delivery, chronic medical conditions, male sex of the newborn, and low birth weight. In contrast, variables such as residence did not show a statistically significant association with neonatal near miss after adjusting for potential confounders. Mothers without formal education had higher odds of neonatal near miss compared to those with formal education (AOR: 2.61; 95% CI: 2.004–2.412). Likewise, paternal lack of formal education was significantly associated with near miss events (AOR: 3.64; 95% CI: 2.448–5.419). Similarly, families with a monthly income of less than 100 USD were nearly three times more likely to experience a neonatal near miss (AOR: 2.82; 95% CI: 1.968–4.046). Having more than three children was associated with increased risk, while having three or fewer children was protective (AOR: 0.26; 95% CI: 0.179–0.392). A short birth interval of less than 24 months also significantly raised the odds (AOR: 1.97; 95% CI: 1.349–2.854). Notably, mothers who attended antenatal care (ANC) during their last pregnancy were approximately 6 times less likely to experience a neonatal near miss compared to those who did not attend (AOR: 0.16; 95% CI: 0.100–0.240), highlighting ANC as a strong protective factor. In contrast, mothers with a previous history of stillbirth had more than 4 times higher odds of experiencing a neonatal near miss (AOR: 4.35; 95% CI: 2.870–6.606). Similarly, the presence of obstetric complications significantly increased the odds by over fourfold (AOR: 4.46; 95% CI: 3.127–6.373). Additionally, neonates born outside the term gestational window (preterm or post-term) were nearly 2 times more likely to experience a near miss compared to those born at term (AOR: 1.89; 95% CI: 1.375–2.588). On the other hand, prolonged labor was associated with a more than 3.5-fold increase in risk (AOR: 3.58; 95% CI: 2.373–5.391), underscoring the importance of timely obstetric care. Delivering at a health facility significantly reduced the odds of experiencing a neonatal near miss by approximately five times (AOR: 0.21; 95% CI: 0.053–0.817), underscoring the protective role of institutional delivery. In contrast, mothers with chronic medical conditions had more than three times higher odds of experiencing a neonatal near miss compared to those without such conditions (AOR: 3.37; 95% CI: 4.484–12.120), indicating a strong association between maternal health status and neonatal outcomes. Moreover, male neonates were nearly twice as likely to be classified as near miss cases compared to females (AOR: 1.86; 95% CI: 1.371–2.510). Above all, low birth weight was the most significant predictor of neonatal near miss, with affected infants being over nine times more likely to experience life-threatening complications than those with normal birth weight (AOR: 9.34; 95% CI: 6.408–13.310) (Table 3 ). Table 3 Factors Associated with Neonatal Nearmiss Among Neonates Characteristics N (%) Neonatal Near miss AOR 95%(CI) Yes = 243 No = 730 Residence Urban 827 (85.0) 183 (75.3) 644 (88.2) 1.24 (0.714–2.158) Rural 146 (15.0) 60 (24.7) 86 (11.8) 1 Marital status Married 937 (96.3) 226 (93.0) 711 (97.4) 2.59 (0.978–6.863) Unmarried 36 (3.7) 17 (7.0) 19 (2.60) 1 Maternal education No formal education 631 (64.9) 194 (79.8) 437 (59.9) 2.61 (2.004–2.412) * Formal education 342 (35.1) 49 (20.2) 293 (40.1) 1 Paternal education No formal education 562 (57.8) 197 (81.1) 365 (50.0) 3.64 (2.448–5.419) * Formal education 411 (42.2) 46 (18.9) 365 (50.0) 1 Monthly family income 3 499 (51.3) 191 (78.6) 308 (42.2) 1 Short birth interval (< 24 Months) Yes 310 (31.9) 116 (47.7) 194 (26.6) 1.97 (1.349–2.854) * No 663 (68.1) 127 (52.3) 536 (73.4) 1 ANC attendance for last pregnancy Yes 516 (53.0) 52 (21.4) 464 (63.6) 0.16 (0.100–0.240) * No 457 (47.0) 191 (78.6) 266 (36.4) 1 History of Stillbirth Yes 84 (8.6) 51 (21.0) 33 (4.5) 4.35 (2.870–6.606) * No 889 (91.4) 192 (79.0) 697 (95.5) 1 Obstetric Complications Yes 159 (16.3) 83 (34.2) 76 (10.4) 4.46 (3.127–6.373) * No 814 (83.7) 160 (65.8) 654 (89.6) 1 Gestational Age at Birth Non-term (pre & post) 247 (25.4) 85 (35.0) 162 (22.2) 1.89 (1.375–2.588) * Term (37–41 weeks) 726 (74.6) 158 (65.0) 568 (77.8) 1 Prolonged labour Yes 108 (11.1) 54 (22.2) 54 (7.4) 3.58 (2.373–5.391) * No 865 (88.9) 189 (77.8) 676 (92.6) 1 Place of Delivery Health Facility 52 (21.4) 356 (48.8) 408 (41.9) 0.21 (0.053–0.817) * Home 191 (78.6) 374 (51.2) 565 (58.1) 1 Chronic Medical Conditions Yes 78 (8.0) 52 (21.4) 26 (3.60) 3.37 (4.484–12.120) * No 895 (92.0) 191 (78.6) 704 (96.4) 1 Baby sex Male 532 (54.7) 372 (51.0) 532 (54.7) 1.86 (1.371–2.510) * Female 441 (45.3) 358 (49.0) 441 (45.3) 1 Birth weight Low birth weight 170 (17.5) 110 (45.3) 60 (8.2) 9.34 (6.408–13.310) * Normal birth weight 803 (82.5) 133 (54.7) 670 (91.8) 1 Discussion The study examined the determinants of neonatal near miss among neonates born or admitted to SOS Mother & Child Hospital in Mogadishu. The findings revealed that neonatal near miss remains a significant public health concern, influenced by a range of maternal, socioeconomic, obstetric, and neonatal factors. Key determinants identified in this study include lack of maternal and paternal formal education, low household income, high parity, short birth interval, lack of antenatal care (ANC) attendance, history of stillbirth, obstetric complications, non-term gestational age, prolonged labor, home delivery, chronic maternal medical conditions, male sex of the newborn, and low birth weight. Mothers who attended ANC were approximately 6 times less likely to experience a neonatal near miss. A similar protective effect was reported in Ethiopia, where ANC attendance reduced the odds of neonatal near miss by 73% 17 . This could be explained by the fact that antenatal care provides an essential opportunity to identify and manage maternal and fetal complications early, promote birth preparedness, and ensure timely referral for high-risk pregnancies. The study also reported that low birth weight increased the odds of neonatal near miss more than 9-fold. This aligns with studies in India, where low birth weight was a key criterion for NNM 18 . This might be due to the fact that low birth weight neonates often suffer from immature organ development, reduced immunity, and poor thermoregulation, making them more susceptible to life-threatening conditions such as infections, respiratory distress, and feeding difficulties—especially in low-resource settings where access to neonatal intensive care may be limited. Regarding the institutional delivery, the study found out that health facility delivery reduced the odds of neonatal near miss by about five times. This can be explained by the fact that institutional deliveries are attended by skilled health professionals who are equipped to manage labor complications, provide timely neonatal resuscitation, and ensure immediate postnatal care 19 . In line with this, the study found that women who experienced obstetric complications had a 4.5-fold increased risk of neonatal near miss compared to those without such complications 20 . More specifically, prolonged labor—one of the most common obstetric complications—was associated with over a 3.5-fold increase in the odds of neonatal near miss. Almost similar findings were reported in a study conducted in Ethiopia, where obstetric complications were significantly associated with increased odds of neonatal near miss 21 . With respect to gestational age, non-term neonates (preterm and post-term) had 1.9 times higher odds of neonatal near miss. This is due to the fact that preterm infants are more vulnerable to complications such as respiratory distress, hypothermia, and infections due to organ immaturity, while post-term births are often associated with increased risk of birth asphyxia, meconium aspiration, and placental insufficiency—all of which contribute to adverse neonatal outcomes. Studies in India and Ghana identified non-term gestational age as a critical criterion for neonatal near miss. These studies highlighted that both preterm and post-term births are associated with increased risks of severe neonatal complications 18 , 22 . It was shown that chronic maternal conditions (e.g., anemia, hypertension) were linked to 3.4 times higher odds of neonatal near miss (NNM). A similar study conducted in India found that 74.5% of NNM cases involved maternal comorbidities 18 . This is due to the fact that chronic maternal health issues, such as hypertension, diabetes, and anemia, can significantly impair the physiological processes necessary for a healthy pregnancy. Finally, regarding the sex of the newborn, the study revealed that male neonates had nearly double the odds of experiencing a neonatal near miss compared to females. This can be explained by the biological vulnerability of male infants, who are more prone to respiratory distress, infections, and slower lung maturation during the neonatal period. Although not conclusively evidenced by this study, existing literature suggests that male neonates generally have a higher risk of adverse outcomes due to these physiological factors 23 , 24 . Strengths and Limitations A key strength of this study is the use of standardized neonatal near miss criteria based on internationally recognized CLAP guidelines, which ensured consistency in case identification. The relatively large sample size and use of both maternal interviews and medical record reviews enhanced the reliability of the findings. Additionally, the multivariable analysis allowed for adjustment of confounding variables, strengthening the validity of the associations identified. Despite its valuable contributions, the study has certain limitations. Although it included a relatively large sample size, it was conducted in a single hospital, which may not capture the full variability of neonatal care practices. In addition, some variables were based on maternal recall, which may have introduced recall bias and affected the precision of the data collected. Conclusion & recommendation The burden of neonatal near miss remains a critical public health concern in Somalia. This study identified several factors significantly associated with neonatal near miss among neonates in Mogadishu. These included lack of formal maternal and paternal education, low household income, high parity, short birth interval, absence of antenatal care (ANC), history of stillbirth, obstetric complications, non-term gestational age, prolonged labor, home delivery, maternal chronic illnesses, male sex of the newborn, and low birth weight. Addressing these factors is essential to reducing neonatal morbidity and improving survival. Interventions that promote ANC attendance, safe delivery practices, maternal education, and early identification of high-risk pregnancies should be prioritized by both governmental and humanitarian actors. Strengthening facility-based care and improving access to skilled birth attendants can play a pivotal role in preventing life-threatening neonatal complications and achieving better outcomes for newborns in resource-limited settings. Declarations Availability of data and materials The datasets and materials utilized in this study can be obtained by reaching out to the corresponding author upon request. Funding There is no funding for this manuscript. Ethical approval and participant consent The study was approved by the SOS College of Health Science Research Ethics Committee (Ref: SOSCHS/REC/2025/015). Informed consent was obtained from all participants, with strict confidentiality maintained. Participation was voluntary, and respondents could withdraw at any time without consequence. Consent for publication Not applicable. CRediT authorship contribution statement Hassan Abdullahi Dahie: Writing – review & editing, Writing – original draft, Visualization, Validation, Supervision, Software, Resources, Project administration, Methodology, Investigation, Formal analysis, Data curation, Conceptualization. Falis Ibrahim Mohamud: Writing – review & editing, Writing – original draft, Supervision. Mohamed Abdullahi Osman: Supervision, Methodology, Data curation. Abukar Abdi Osman: Writing – original draft, Data Collection. Yusuf Ali Jimale: Visualization, Supervision, Investigation. Hamdi Ahmed Hussein: Supervision, Investigation, Formal analysis. Mohamed Osman Alasow: Visualization, Software. Abukar Abdi Osman: Writing – original draft. Abdirahman Mohamed Abdullahi: Writing – review & editing, Writing – original draft. Mohamed Maalin Dakane: Writing – review & editing, Writing – original draft, Formal analysis. Dek Abdi Hussein: Writing – review & editing, Writing – original draft, Formal analysis. Declaration of competing interest The authors have no financial and non-financial competing interests. Acknowledgements The authors express their gratitude to all individuals and organizations whose support and contributions were instrumental in the completion of this study. References Parents’ experiences of meeting and bonding. with their babies - Healthtalk Australia [Internet]. [cited 2024 May 29]. Available from: https://www.healthtalkaustralia.org/early-parenthood/parents-experiences-of-meeting-and-bonding-with-their-babies/ Lawn JE, Blencowe H, Darmstadt GL, Bhutta ZA. Beyond newborn survival: the world you are born into determines your risk of disability-free survival. Pediatr Res [Internet]. 2013 Dec [cited 2024 May 29];74 Suppl 1(Suppl 1):1–3. Available from: https://pubmed.ncbi.nlm.nih.gov/24240732/ Newborn mortality [Internet]. [cited 2024 May 29]. Available from: https://www.who.int/news-room/fact-sheets/detail/newborn-mortality da Silva AAM, Leite ÁJM, Lamy ZC, Moreira MEL, Gurgel RQ, da Cunha AJLA et al. Morbidade neonatal near miss na pesquisa Nascer no Brasil. Cad Saude Publica [Internet]. 2014 [cited 2024 May 30];30(SUPPL1):S182–91. Available from: http://dx.doi.org/10.1590/0102-311X00129613 Tamirat A, Id D, Siyoum M, Id D. Prevalence and determinants of neonatal near miss in Ethiopia: A systematic review and meta-analysis. PLoS One [Internet]. 2023 Feb 1 [cited 2024 May 29];18(2):e0278741. Available from: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0278741 Santos JP, Pileggi-Castro C, Camelo JS, Silva AA, Duran P, Serruya SJ et al. Neonatal near miss: a systematic review. BMC Pregnancy Childbirth [Internet]. 2015 Dec 1 [cited 2024 May 30];15(1). Available from: https://pubmed.ncbi.nlm.nih.gov/26625905/ Pileggi-Castro C, Camelo JS, Perdoná GC, Mussi-Pinhata MM, Cecatti JG, Mori R et al. Development of criteria for identifying neonatal near-miss cases: analysis of two WHO multicountry cross-sectional studies. BJOG [Internet]. 2014 [cited 2024 May 30];121 Suppl 1:110–8. Available from: https://pubmed.ncbi.nlm.nih.gov/24641541/ Dahie HA. Determinants of maternal near miss events among women admitted to tertiary hospitals in Mogadishu, Somalia: a facility-based case–control study. BMC Pregnancy Childbirth [Internet]. 2022 Dec 1 [cited 2024 Feb 17];22(1):1–13. Available from: https://bmcpregnancychildbirth.biomedcentral.com/articles/ 10.1186/s12884-022-04987-3 WHO EMRO |. __404__ [Internet]. [cited 2024 Nov 19]. Available from: https://www.emro.who.int/images/stories/somalia/RMNCAH-Policy-Brief-August-2023 Ali IA, Inchon P, Suwannaporn S, Achalapong J. Neonatal mortality and associated factors among newborns in Mogadishu, Somalia: a multicenter hospital-based cross-sectional study. BMC Public Health [Internet]. 2024 Dec 1 [cited 2024 Nov 19];24(1):1–15. Available from: https://bmcpublichealth.biomedcentral.com/articles/ 10.1186/s12889-024-19149-7 Ahmed Z, Ataullahjan A, Gaffey MF, Osman M, Umutoni C, Bhutta ZA et al. Understanding the factors affecting the humanitarian health and nutrition response for women and children in Somalia since 2000: A case study. Confl Health [Internet]. 2020 May 27 [cited 2024 Nov 19];14(1):1–15. Available from: https://conflictandhealth.biomedcentral.com/articles/ 10.1186/s13031-019-0241-x Habte A, Lukas K, Melis T, Tamene A, Sahle T, Hailu M et al. Determinants of neonatal near miss among neonates admitted to public hospitals in Southern Ethiopia, 2021: A case-control study. PLoS One [Internet]. 2022 May 1 [cited 2024 Nov 20];17(5):e0268041. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC9075625/ Yasin S, Abdisa L, Roba HS, Tura AK. Predictors of neonatal near-misses in Worabe Comprehensive Specialized Hospital, Southern Ethiopia. Front Pediatr [Internet]. 2024 [cited 2024 Oct 22];12:1326568. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC11176496/ Endawkie A, Cherie N, Mebratu W, Arefaynie M, Melake D, Adamu K et al. Determinants of neonatal near miss among neonates admitted in Dessie comprehensive and specialized hospitals Northeast Ethiopia: A case – control study. Global Pediatrics [Internet]. 2023 Dec 1 [cited 2025 May 15];6:100087. Available from: https://www.sciencedirect.com/science/article/pii/S2667009723000532 De Lima THB, Katz L, Kassar SB, Amorim MM. Neonatal near miss determinants at a maternity hospital for high-risk pregnancy in Northeastern Brazil: a prospective study. BMC Pregnancy Childbirth [Internet]. 2018 Oct 12 [cited 2024 Oct 22];18(1). Available from: https://pubmed.ncbi.nlm.nih.gov/30314456/ De Lima THB, Katz L, Kassar SB, Amorim MM. Neonatal near miss determinants at a maternity hospital for high-risk pregnancy in Northeastern Brazil: a prospective study. BMC Pregnancy Childbirth [Internet]. 2018 Oct 12 [cited 2024 Oct 22];18(1):401. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC6186100/ Abebe H, Wasie A, Yeshaneh A, Shitu S, Mose A, Adane D et al. Determinant Factors of Neonatal Near Miss Among Neonates in Gurage Zone Hospitals, Ethiopia: A Case-Control Study. Pediatric Health Med Ther [Internet]. 2021 Mar [cited 2025 May 22];12:129. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC7989378/ Parulekar M, Thakur H, Samant P. Analysis of Maternal Factors Impacting Neonatal Near Miss (NNM) Events: A Tertiary Centre Experience. J Obstet Gynaecol India [Internet]. 2021 Aug 1 [cited 2025 May 22];72(Suppl 1):75. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC9343503/ Dahie HA, Osman MA, Jimale YA, Mohamud FI, Hussein HA, Alasow MO et al. Determinants of institutional delivery service utilization among internally displaced vulnerable populations in Benadir region, Somalia: A community based cross-sectional study. J Migr Health [Internet]. 2025 Jan 1 [cited 2025 May 22];11. Available from: https://pubmed.ncbi.nlm.nih.gov/40070514/ Sushma R, Norhayati MN, Nik Hazlina NH. Prevalence of neonatal near miss and associated factors in Nepal: a cross-sectional study. BMC Pregnancy Childbirth [Internet]. 2021 Dec 1 [cited 2025 May 22];21(1). Available from: https://pubmed.ncbi.nlm.nih.gov/34107909/ Abebe H, Wasie A, Yeshaneh A, Shitu S, Mose A, Adane D et al. Determinant Factors of Neonatal Near Miss Among Neonates in Gurage Zone Hospitals, Ethiopia: A Case-Control Study. Pediatric Health Med Ther [Internet]. 2021 Mar [cited 2025 May 22];12:129. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC7989378/ Bakari A, Bell AJ, Oppong SA, Bockarie Y, Wobil P, Plange-Rhule G et al. Neonatal near-misses in Ghana: a prospective, observational, multi-center study. BMC Pediatr [Internet]. 2019 Dec 23 [cited 2025 May 22];19(1):509. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC6927122/ Migliori C, Braga M, Siragusa V, Villa MC, Luzi L. The impact of gender medicine on neonatology: the disadvantage of being male: a narrative review. Ital J Pediatr [Internet]. 2023 Dec 1 [cited 2025 May 22];49(1):65. Available from: https://pmc.ncbi.nlm.nih.gov/articles/PMC10245647/ Di Renzo GC, Rosati A, Sarti RD, Cruciani L, Cutuli AM. Does fetal sex affect pregnancy outcome? Gend Med [Internet]. 2007 Mar [cited 2025 May 22];4(1):19–30. Available from: https://pubmed.ncbi.nlm.nih.gov/17584623/ Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 05 Nov, 2025 Read the published version in Maternal Health, Neonatology and Perinatology → Version 1 posted Editorial decision: Revision requested 08 Aug, 2025 Reviews received at journal 27 Jul, 2025 Reviews received at journal 26 Jul, 2025 Reviewers agreed at journal 26 Jul, 2025 Reviewers agreed at journal 25 Jul, 2025 Reviewers agreed at journal 23 Jul, 2025 Reviewers invited by journal 20 Jul, 2025 Editor assigned by journal 27 May, 2025 Submission checks completed at journal 27 May, 2025 First submitted to journal 25 May, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6743554","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":488699610,"identity":"2864e439-4816-453d-8a8e-2d3f03c5b0de","order_by":0,"name":"Hassan Abdullahi 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Villages","correspondingAuthor":false,"prefix":"","firstName":"Abdirahman","middleName":"Mohamed","lastName":"Abdullahi","suffix":""},{"id":488699619,"identity":"1f63b332-51d4-4be1-9211-827c70acb067","order_by":8,"name":"Mohamed Maalin Dakane","email":"","orcid":"","institution":"SOS College of Health Science, SOS Children’s Villages","correspondingAuthor":false,"prefix":"","firstName":"Mohamed","middleName":"Maalin","lastName":"Dakane","suffix":""},{"id":488699621,"identity":"dd5fe989-4d63-4fec-8009-938859facc74","order_by":9,"name":"Dek Abdi","email":"","orcid":"","institution":"SOS College of Health Science, SOS Children’s Villages","correspondingAuthor":false,"prefix":"","firstName":"Dek","middleName":"","lastName":"Abdi","suffix":""},{"id":488699623,"identity":"f9dfa2f0-92ca-4f0d-a1f7-d567e1c1c444","order_by":10,"name":"Abdullahi Adan Isak","email":"","orcid":"","institution":"SOS College of Health Science, SOS Children’s Villages","correspondingAuthor":false,"prefix":"","firstName":"Abdullahi","middleName":"Adan","lastName":"Isak","suffix":""},{"id":488699625,"identity":"5517a2ef-e0a6-480e-8e0c-ad0bc962d013","order_by":11,"name":"Lukman Sheikh Omar","email":"","orcid":"","institution":"SOS College of Health Science, SOS Children’s Villages","correspondingAuthor":false,"prefix":"","firstName":"Lukman","middleName":"Sheikh","lastName":"Omar","suffix":""},{"id":488699627,"identity":"66c4a9d0-5600-46a9-baaa-c37b610c168f","order_by":12,"name":"Sadia Hussein Mohamud","email":"","orcid":"","institution":"SOS College of Health Science, SOS Children’s Villages","correspondingAuthor":false,"prefix":"","firstName":"Sadia","middleName":"Hussein","lastName":"Mohamud","suffix":""}],"badges":[],"createdAt":"2025-05-25 12:08:11","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6743554/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6743554/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s40748-025-00234-7","type":"published","date":"2025-11-05T15:56:59+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":95563918,"identity":"e269df38-fb7f-4afb-a975-eccb4c372fb9","added_by":"auto","created_at":"2025-11-10 16:03:47","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1650450,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6743554/v1/5c666b21-bc6c-40fd-9fae-cb30d5965af7.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Determinants of Neonatal Near Miss Among Newborns Admitted to SOS Mother \u0026 Child Hospital, Benadir Region, Somalia: A Case-Control Study","fulltext":[{"header":"Background","content":"\u003cp\u003eThe arrival of a neonate evokes profound love and anticipation, as families eagerly await their beloved new addition\u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. However, this joyous occasion may sometimes be overshadowed by concerns stemming from critical life-threatening challenges for both the mother and the neonate. During this journey, many infants tragically lose their lives, while others experience near-miss events, narrowly escaping severe health complications.\u003c/p\u003e\u003cp\u003eAnnually, 135\u0026nbsp;million newborns enter the world, commencing their journey in an identical state of vulnerability. Yet, their prospects for survival and flourishing diverge markedly depending on the global context of their birth\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. This spectrum ranges from high-income nations equipped with universal neonatal intensive care to environments where births occur at home, devoid of midwifery support, medical provisions, or institutional healthcare assistance.\u003c/p\u003e\u003cp\u003eGlobally, 2.3\u0026nbsp;million children died in the first month of life in 2022, equating to approximately 6,300 neonatal deaths every day. Sub-Saharan Africa accounted for 57% of these deaths, despite only having 30% of global live births. This disparity resulted in the region having the highest neonatal mortality rate in the world, with 27 deaths per 1,000 live births\u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eAlthough neonatal mortality is an indicator of neonatal health, it only reveals the tip of the iceberg, as most neonates who survive complications remain unnoticed.\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e Understanding the full extent of neonatal ill-health requires studying neonates who survived from severe complications (neonatal near miss) in addition to neonatal deaths\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. Neonatal near miss is defined as a condition of newborn infant characterized by severe morbidity (near miss) of pragmatic and management criteria, but survived these conditions within the first 28 days of life\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. Similar to the concept of maternal near miss, neonatal near miss (NNM) is gaining prominence as an emerging methodology and is increasingly recognized as a critical indicator for evaluating the quality of neonatal care\u003csup\u003e\u003cspan additionalcitationids=\"CR7\" citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e. This approach plays a pivotal role in efforts to mitigate preventable neonatal morbidity and mortality.\u003c/p\u003e\u003cp\u003eSomalia faces one of the highest neonatal mortality rates globally, with 37 deaths per 1,000 live births, reflecting significant public health challenges. This crisis is compounded by limited access to quality healthcare and inadequate maternal health services, as only 24% of pregnant women receive at least four antenatal care visits, and just 32% of deliveries are attended by skilled birth attendants\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. Prolonged conflict and instability have further weakened the country\u0026rsquo;s health infrastructure, leaving maternal and child healthcare services severely under-resourced and unable to meet the growing needs of the population\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Therefore, the study examined the determinants of neonatal near miss among neonates born in major public hospitals in the Benadir Region, Somalia.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy Design\u003c/h2\u003e\u003cp\u003eThis was a hospital-based unmatched case-control study designed to assess neonatal near-miss events by comparing affected neonates (cases) with healthy neonates (controls).\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eSetting\u003c/h3\u003e\n\u003cp\u003eThe study was conducted at SOS Mother and Child Hospital in the Benadir region, Somalia, from December 2024 to April 2025. This facility is a major maternal and child health hospital, offering comprehensive neonatal care with approximately 200 beds and admitting an average of 65 newborns monthly.\u003c/p\u003e\n\u003ch3\u003eParticipants\u003c/h3\u003e\n\u003cp\u003eThe study participants consisted of neonates admitted to SOS Mother and Child Hospital during the study period, classified into two groups: cases and controls. Cases included neonates who experienced at least one neonatal near-miss event within the first 27 days of life but ultimately survived. Identification of neonatal near-miss cases was based on criteria established by the Latin American Centre for Perinatology (CLAP), which include both pragmatic and management criteria. Pragmatic criteria were neonates born weighing less than 1750 grams, delivered before 33 weeks of gestation, or with an Apgar score of less than 7 at five minutes. Management criteria encompassed neonates who required critical clinical interventions such as therapeutic antibiotics, nasal continuous positive airway pressure (NCPAP), neonatal intubation, phototherapy initiated within 24 hours of birth, cardiopulmonary resuscitation, administration of vasoactive medications, anticonvulsants, surfactants, blood products, steroids for refractory hypoglycemia, or surgical procedures during their neonatal period\u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eControls were healthy neonates selected from the hospital's postnatal wards. These neonates were born without complications, did not require any specialized medical interventions, and were discharged in stable condition. To enhance comparability, for every neonate identified as a near-miss case, three control neonates were carefully selected on the same day the near-miss event occurred\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eNeonates were excluded from the study if they had an unknown or incomplete birth history, belonged to multiple gestations, experienced maternal absence during admission, possessed incomplete medical records, or were initially categorized as controls but subsequently reclassified as cases during the study period\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\n\u003ch3\u003eSampling procedures\u003c/h3\u003e\n\u003cp\u003eCases were selected using consecutive sampling. All neonates admitted to the newborn unit who met the neonatal near-miss (NNM) criteria during the study period were included as cases at the time of discharge. This ensured that every eligible case was captured without omission until the required sample size was achieved.For each case included in the study, three controls were randomly selected from among neonates who were born healthy and discharged without complications. A list of all eligible healthy neonates admitted to the postnatal ward was compiled using their registration numbers. From this list, controls were selected using computer-generated simple random sampling, maintaining a 1:3 case-to-control ratio.\u003c/p\u003e\n\u003ch3\u003eSample size determination\u003c/h3\u003e\n\u003cp\u003eThe sample size for this study was calculated using the double population proportion formula through the Epi Info 7 StatCalc program. The calculation was based on the following assumptions: a 95% confidence level, 80% power, and a case-to-control ratio of 1:3. The percentage of cases exposed to lack of ANC (12%) and the percentage of controls exposed to lack of ANC (5.7%) were taken from a study conducted in Northeast Ethiopia\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. Based on these parameters, the required sample size was calculated to be 824 participants. After adjusting for an 18% non-response rate, the final sample size increased to 973 participants ( 243 cases and 730 controls).\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eData collection method\u003c/h2\u003e\u003cp\u003eData was collected from the mothers of the neonates using a structured and pretested questionnaire, administered by trained interviewers. The questionnaire was carefully adapted from relevant literature to ensure its validity and relevance\u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. The data collectors used face-to-face interviews and client record review techniques to collect data. Interviews were conducted in private settings, primarily at the time of patient discharge, when cases had recovered from their illnesses and controls were physiologically stable and ready for discharge. In addition to interviews, relevant clinical data were extracted from hospital records with appropriate permissions. This dual approach enhanced data richness by providing objective clinical information alongside maternal reports.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eStudy Variables\u003c/h3\u003e\n\u003cp\u003eThe main outcome variable was neonatal near miss, defined as a newborn who survived a life-threatening complication within the first 28 days of life, coded as 1 = \u0026ldquo;Yes\u0026rdquo; and 0 = \u0026ldquo;No\u0026rdquo;.\u003c/p\u003e\u003cp\u003eIndependent variables included socio-demographic characteristics such as maternal age, education and occupation of both parents, marital status, household size, income, and residence. Obstetric history covered gravidity, parity, previous stillbirths, abortions, neonatal deaths, and birth intervals.\u003c/p\u003e\u003cp\u003eMaternal health conditions during pregnancy\u0026mdash;such as anemia, hypertension, diabetes, heart disease, and infections\u0026mdash;were considered, along with health service factors like ANC attendance, number of visits, and complications during labor and delivery.\u003c/p\u003e\u003cp\u003eNewborn-related variables included sex, gestational age, birth weight, APGAR score, and presentation. Critical interventions such as use of antibiotics, CPAP, intubation, phototherapy, CPR, and presence of congenital anomalies were also assessed to identify near-miss cases.\u003c/p\u003e\n\u003ch3\u003eData quality control\u003c/h3\u003e\n\u003cp\u003eThe data were collected by ten qualified midwives fluent in both English and Somali. Prior to data collection, they received an intensive two-day training that covered data collection procedures, the objectives of the study, questionnaire content, participant interaction, and ethical considerations such as confidentiality and privacy.\u003c/p\u003e\u003cp\u003eOne week before data collection began, a pretest was conducted on 5% of the sample to assess the clarity, validity, and usability of the questionnaire. Feedback from the pretest informed necessary revisions to enhance accuracy and ease of understanding for respondents.\u003c/p\u003e\u003cp\u003eTo ensure high data quality throughout the study, supervisors carried out random checks of completed questionnaires to verify adherence to the study protocol and maintain consistency and accuracy in data collection.\u003c/p\u003e\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e\u003ch2\u003eData analysis and processing\u003c/h2\u003e\u003cp\u003eAll collected data were reviewed for completeness, accuracy, and consistency prior to analysis. Data cleaning was conducted to address any missing or inconsistent entries. The cleaned dataset was then analyzed using SPSS version 25. Descriptive statistics were used to summarize participants\u0026rsquo; background characteristics. To assess associations between the dependent variable (neonatal near miss) and independent variables, Chi-square tests were employed. Variables showing a statistically significant association (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) in the Chi-square test were included in a binary logistic regression model to identify independent predictors of neonatal near-miss events. The strength of associations was quantified using adjusted odds ratios (aORs) with 95% confidence intervals (CIs). A p-value of less than 0.05 was considered statistically significant in the final model.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\u003ch2\u003eEthical Considerations\u003c/h2\u003e\u003cp\u003e The study received ethical clearance from the Research Ethics Committee of SOS College of Health Science (Reference: SOSCHS/REC/2025/015), underscoring adherence to the highest standards of ethical conduct and research integrity. Informed consent was obtained from all participants before data collection, with strict measures in place to safeguard their privacy and confidentiality. Participation was fully voluntary, and individuals retained the right to withdraw from the study at any point without any form of penalty or disadvantage.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003eSocio-demographic Characteristics\u003c/h2\u003e\u003cp\u003eThe study included 973 participants, with 243 neonatal near miss (NNM) cases and 730 controls. Most participants (85%) lived in urban areas, though a higher proportion of cases (24.7%) were from rural areas compared to controls (11.8%). Maternal age was similar across groups, with over half of mothers under 25 years. The majority of mothers were married (96.3%), but unmarried mothers were slightly more common among cases (7%) than controls (2.6%).\u003c/p\u003e\u003cp\u003eA large portion of mothers lacked formal education (64.9%), with this proportion higher among cases (79.8%) than controls (59.9%). Similarly, more fathers of cases had no formal education (81.1%) compared to controls (50%). Maternal employment status and family size were comparable between groups, with about 82% of mothers working and roughly 42% of families having fewer than five members. Regarding income, nearly half of all families earned less than 100 USD monthly, with a notably higher percentage among cases (69.1%) versus controls (40.1%) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eSocio-demographic characteristics of respondents\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e\u003cp\u003eVariables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003eNeonatal Near Miss\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eTotal N (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eP-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCase n (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eControl n (%)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cem\u003eResidence\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cem\u003e0.000\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eUrban\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e183 (75.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e644 (88.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e827 (85.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eRural\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e60 (24.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e86 (11.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e146 (15.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMaternal Age\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.421\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;25 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e131 (53.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e383 (52.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e514 (52.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e26\u0026ndash;35 years\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e97 (39.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e315 (43.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e412 (42.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;35 years\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e15 (6.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e32 (4.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e47 (4.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMaternal Marital Status\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.002\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eMarried\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e226 (93.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e711 (97.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e937 (96.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eUnmarried\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e17 (7.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e19 (2.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e36 (3.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMaternal education\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.000\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eNo formal education\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e194 (79.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e437 (59.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e631 (64.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eFormal education\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e49 (20.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e293 (40.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e342 (35.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePaternal education\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.000\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eNo formal education\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e197 (81.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e365 (50.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e562 (57.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eFormal education\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e46 (18.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e365 (50.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e411 (42.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMaternal working status\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.993\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eWorking\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e199 (81.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e598 (81.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e797 (81.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eNot working\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e44 (18.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e132 (18.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e176 (18.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eFamily size\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.893\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;5 Individuals\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e101 (41.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e307 (42.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e408 (41.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e\u0026ge;\u0026thinsp;5 Individuals\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e142 (58.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e423 (57.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e565 (58.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMonthly family income\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.000\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;100 USD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e168 (69.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e293 (40.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e461 (47.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e\u0026ge;\u0026thinsp;100 USD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e75 (30.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e437 (59.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e512 (52.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003eMaternal obstetric history and neoborn characteristics\u003c/h2\u003e\u003cp\u003eThe study also assessed various obstetric and neonatal variables in relation to neonatal near miss (NNM) outcomes. Regarding parity, a larger proportion of NNM cases (78.6%) had more than three children, compared to 57.8% of controls, highlighting higher parity among cases. Short birth intervals were more common in NNM cases, with 47.7% having intervals shorter than 2 years, compared to 26.6% of controls. Similarly, antenatal care (ANC) attendance was significantly lower in NNM cases (21.4%) than in controls (63.6%), indicating a notable gap in maternal healthcare utilization.\u003c/p\u003e\u003cp\u003eIn terms of history of stillbirth, 21.0% of NNM cases had a previous stillbirth, compared to only 4.5% of controls. Obstetric complications were also more prevalent among cases (34.2%) than controls (10.4%), indicating that complications are more common in NNM pregnancies. Premature rupture of membranes (PROM) showed no significant difference between groups (17.3% of cases vs. 17.8% of controls).\u003c/p\u003e\u003cp\u003eRegarding gestational age, a higher proportion of NNM cases (32.9%) were preterm (\u0026lt;\u0026thinsp;37 weeks), compared to 17.1% of controls. In contrast, term births (37\u0026ndash;41 weeks) were more common in controls (77.8%) than in cases (65.0%). Prolonged labor was more frequent in NNM cases (22.2%) compared to controls (7.4%), suggesting a link between prolonged labor and NNM.\u003c/p\u003e\u003cp\u003eConcerning place of delivery, a higher proportion of NNM cases (78.6%) delivered at home, compared to 51.2% of controls. No significant difference was found in the mode of delivery, with 62.6% of NNM cases and 66.3% of controls delivering vaginally. Chronic medical conditions were more common among NNM cases (69.1%) compared to controls (40.1%), suggesting that underlying health issues may contribute to NNM. In terms of baby sex, 65.8% of NNM cases had male babies, compared to 49.0% of controls. Finally, birth weight was significantly associated with NNM, as 45.3% of NNM cases had low birth weight, compared to only 8.2% of controls, with most controls (91.8%) having normal birth weight (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eMaternal obstetric history and neoborn characteristics\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"6\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e\u003cp\u003eVariables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003eNeonatal Near Miss\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eTotal N (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eP-value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCase n (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eControl n (%)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eParity\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cem\u003e0.000\u003c/em\u003e\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e\u0026le;\u0026thinsp;3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e52 (21.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e422 (57.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e474 (48.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e191 (78.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e308 (42.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e499 (51.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eShort birth interval\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.000\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e116 (47.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e194 (26.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e310 (31.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e127 (52.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e536 (73.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e663 (68.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eANC attendance\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.000\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e52 (21.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e464 (63.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e516 (53.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e191 (78.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e266 (36.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e457 (47.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHistory of Stillbirth\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.000\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e51 (21.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e33 (4.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e84 (8.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e192 (79.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e697 (95.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e889 (91.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eObstetric Complications\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.000\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e83 (34.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e76 (10.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e159 (16.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e160 (65.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e654 (89.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e814 (83.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePremature Rupture of Membranes\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.853\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e42 (17.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e130 (17.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e172 (17.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e201 (82.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e600 (82.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e801 (82.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eGestational Age at Birth\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.000\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003ePreterm (\u0026lt;\u0026thinsp;37 weeks)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e80 (32.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e125 (17.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e205 (21.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003ePost-term (\u0026ge;\u0026thinsp;42 weeks)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5 (2.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e37 (5.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e42 (4.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eTerm (37\u0026ndash;41 weeks)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e158 (65.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e568 (77.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e726 (74.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eProlonged labour\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.000\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e54 (22.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e54 (7.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e108 (11.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e189 (77.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e676 (92.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e865 (88.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePlace of Delivery\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.000\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eHealth Facility\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e52 (21.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e356 (48.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e408 (41.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eHome\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e191 (78.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e374 (51.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e565 (58.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMode of Delivery\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.287\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eSVD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e152 (62.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e484 (66.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e636 (65.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eNon SVD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e91 (37.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e246 (33.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e337 (34.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eChronic Medical Conditions\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.000\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e168 (69.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e293 (40.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e461 (47.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e75 (30.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e437 (59.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e512 (52.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eBaby sex\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.000\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e160 (65.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e372 (51.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e532 (54.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e83 (32.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e358 (49.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e441 (45.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eBirth weight\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u003cb\u003e0.000\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eLow birth weight\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e110 (45.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e60 (8.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e170 (17.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u003cp\u003eNormal birth weight\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e133 (54.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e670 (91.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e803 (82.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\u003ch2\u003ePredictors of Neonatal Near Miss Identified Through Multivariable Analysis\u003c/h2\u003e\u003cp\u003eVariables that showed statistical significance in the chi-square analysis were further examined using multivariable logistic regression. The multivariable analysis identified several factors significantly associated with neonatal near miss. These included maternal and paternal education, low monthly family income, high parity, short birth interval, lack of antenatal care (ANC) attendance, history of stillbirth, obstetric complications, non-term gestational age, prolonged labor, place of delivery, chronic medical conditions, male sex of the newborn, and low birth weight. In contrast, variables such as residence did not show a statistically significant association with neonatal near miss after adjusting for potential confounders.\u003c/p\u003e\u003cp\u003eMothers without formal education had higher odds of neonatal near miss compared to those with formal education (AOR: 2.61; 95% CI: 2.004\u0026ndash;2.412). Likewise, paternal lack of formal education was significantly associated with near miss events (AOR: 3.64; 95% CI: 2.448\u0026ndash;5.419). Similarly, families with a monthly income of less than 100 USD were nearly three times more likely to experience a neonatal near miss (AOR: 2.82; 95% CI: 1.968\u0026ndash;4.046). Having more than three children was associated with increased risk, while having three or fewer children was protective (AOR: 0.26; 95% CI: 0.179\u0026ndash;0.392). A short birth interval of less than 24 months also significantly raised the odds (AOR: 1.97; 95% CI: 1.349\u0026ndash;2.854).\u003c/p\u003e\u003cp\u003eNotably, mothers who attended antenatal care (ANC) during their last pregnancy were approximately 6 times less likely to experience a neonatal near miss compared to those who did not attend (AOR: 0.16; 95% CI: 0.100\u0026ndash;0.240), highlighting ANC as a strong protective factor. In contrast, mothers with a previous history of stillbirth had more than 4 times higher odds of experiencing a neonatal near miss (AOR: 4.35; 95% CI: 2.870\u0026ndash;6.606). Similarly, the presence of obstetric complications significantly increased the odds by over fourfold (AOR: 4.46; 95% CI: 3.127\u0026ndash;6.373). Additionally, neonates born outside the term gestational window (preterm or post-term) were nearly 2 times more likely to experience a near miss compared to those born at term (AOR: 1.89; 95% CI: 1.375\u0026ndash;2.588). On the other hand, prolonged labor was associated with a more than 3.5-fold increase in risk (AOR: 3.58; 95% CI: 2.373\u0026ndash;5.391), underscoring the importance of timely obstetric care.\u003c/p\u003e\u003cp\u003eDelivering at a health facility significantly reduced the odds of experiencing a neonatal near miss by approximately five times (AOR: 0.21; 95% CI: 0.053\u0026ndash;0.817), underscoring the protective role of institutional delivery. In contrast, mothers with chronic medical conditions had more than three times higher odds of experiencing a neonatal near miss compared to those without such conditions (AOR: 3.37; 95% CI: 4.484\u0026ndash;12.120), indicating a strong association between maternal health status and neonatal outcomes. Moreover, male neonates were nearly twice as likely to be classified as near miss cases compared to females (AOR: 1.86; 95% CI: 1.371\u0026ndash;2.510). Above all, low birth weight was the most significant predictor of neonatal near miss, with affected infants being over nine times more likely to experience life-threatening complications than those with normal birth weight (AOR: 9.34; 95% CI: 6.408\u0026ndash;13.310) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eFactors Associated with Neonatal Nearmiss Among Neonates\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eCharacteristics\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eN (%)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003eNeonatal Near miss\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eAOR 95%(CI)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eYes\u0026thinsp;=\u0026thinsp;243\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eNo\u0026thinsp;=\u0026thinsp;730\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003eResidence\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUrban\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e827 (85.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e183 (75.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e644 (88.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.24 (0.714\u0026ndash;2.158)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRural\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e146 (15.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e60 (24.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e86 (11.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMarital status\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMarried\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e937 (96.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e226 (93.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e711 (97.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.59 (0.978\u0026ndash;6.863)\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUnmarried\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e36 (3.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e17 (7.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e19 (2.60)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMaternal education\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo formal education\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e631 (64.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e194 (79.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e437 (59.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.61 (2.004\u0026ndash;2.412)\u003cb\u003e*\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFormal education\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e342 (35.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e49 (20.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e293 (40.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePaternal education\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo formal education\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e562 (57.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e197 (81.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e365 (50.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.64 (2.448\u0026ndash;5.419)\u003cb\u003e*\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFormal education\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e411 (42.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e46 (18.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e365 (50.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eMonthly family income\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;100 USD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e461 (47.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e168 (69.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e293 (40.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.82 (1.968\u0026ndash;4.046)\u003cb\u003e*\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026ge;\u0026thinsp;100 USD\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e512 (52.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e75 (30.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e437 (59.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eParity\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026le;\u0026thinsp;3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e474 (48.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e52 (21.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e422 (57.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.26 (0.179\u0026ndash;0.392)\u003cb\u003e*\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u0026gt;\u0026thinsp;3\u003c/p\u003e \u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e499 (51.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e191 (78.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e308 (42.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eShort birth interval (\u0026lt;\u0026thinsp;24 Months)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e310 (31.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e116 (47.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e194 (26.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.97 (1.349\u0026ndash;2.854)\u003cb\u003e*\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e663 (68.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e127 (52.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e536 (73.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eANC attendance for last pregnancy\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e516 (53.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e52 (21.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e464 (63.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.16 (0.100\u0026ndash;0.240)\u003cb\u003e*\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e457 (47.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e191 (78.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e266 (36.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHistory of Stillbirth\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e84 (8.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e51 (21.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e33 (4.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4.35 (2.870\u0026ndash;6.606)\u003cb\u003e*\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e889 (91.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e192 (79.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e697 (95.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eObstetric Complications\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e159 (16.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e83 (34.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e76 (10.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4.46 (3.127\u0026ndash;6.373)\u003cb\u003e*\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e814 (83.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e160 (65.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e654 (89.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eGestational Age at Birth\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNon-term (pre \u0026amp; post)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e247 (25.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e85 (35.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e162 (22.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.89 (1.375\u0026ndash;2.588)\u003cb\u003e*\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTerm (37\u0026ndash;41 weeks)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e726 (74.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e158 (65.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e568 (77.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eProlonged labour\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e108 (11.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e54 (22.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e54 (7.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.58 (2.373\u0026ndash;5.391)\u003cb\u003e*\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e865 (88.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e189 (77.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e676 (92.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003ePlace of Delivery\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHealth Facility\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e52 (21.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e356 (48.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e408 (41.9)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.21 (0.053\u0026ndash;0.817)\u003cb\u003e*\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHome\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e191 (78.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e374 (51.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e565 (58.1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eChronic Medical Conditions\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e78 (8.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e52 (21.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e26 (3.60)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.37 (4.484\u0026ndash;12.120)\u003cb\u003e*\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e895 (92.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e191 (78.6)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e704 (96.4)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eBaby sex\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e532 (54.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e372 (51.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e532 (54.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.86 (1.371\u0026ndash;2.510)\u003cb\u003e*\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e441 (45.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e358 (49.0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e441 (45.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e\u003cp\u003e\u003cb\u003eBirth weight\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLow birth weight\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e170 (17.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e110 (45.3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e60 (8.2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e9.34 (6.408\u0026ndash;13.310)\u003cb\u003e*\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNormal birth weight\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e803 (82.5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e133 (54.7)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e670 (91.8)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe study examined the determinants of neonatal near miss among neonates born or admitted to SOS Mother \u0026amp; Child Hospital in Mogadishu. The findings revealed that neonatal near miss remains a significant public health concern, influenced by a range of maternal, socioeconomic, obstetric, and neonatal factors. Key determinants identified in this study include lack of maternal and paternal formal education, low household income, high parity, short birth interval, lack of antenatal care (ANC) attendance, history of stillbirth, obstetric complications, non-term gestational age, prolonged labor, home delivery, chronic maternal medical conditions, male sex of the newborn, and low birth weight.\u003c/p\u003e\u003cp\u003eMothers who attended ANC were approximately 6 times less likely to experience a neonatal near miss. A similar protective effect was reported in Ethiopia, where ANC attendance reduced the odds of neonatal near miss by 73%\u003csup\u003e17\u003c/sup\u003e. This could be explained by the fact that antenatal care provides an essential opportunity to identify and manage maternal and fetal complications early, promote birth preparedness, and ensure timely referral for high-risk pregnancies. The study also reported that low birth weight increased the odds of neonatal near miss more than 9-fold. This aligns with studies in India, where low birth weight was a key criterion for NNM\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. This might be due to the fact that low birth weight neonates often suffer from immature organ development, reduced immunity, and poor thermoregulation, making them more susceptible to life-threatening conditions such as infections, respiratory distress, and feeding difficulties\u0026mdash;especially in low-resource settings where access to neonatal intensive care may be limited.\u003c/p\u003e\u003cp\u003eRegarding the institutional delivery, the study found out that health facility delivery reduced the odds of neonatal near miss by about five times. This can be explained by the fact that institutional deliveries are attended by skilled health professionals who are equipped to manage labor complications, provide timely neonatal resuscitation, and ensure immediate postnatal care\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. In line with this, the study found that women who experienced obstetric complications had a 4.5-fold increased risk of neonatal near miss compared to those without such complications \u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. More specifically, prolonged labor\u0026mdash;one of the most common obstetric complications\u0026mdash;was associated with over a 3.5-fold increase in the odds of neonatal near miss. Almost similar findings were reported in a study conducted in Ethiopia, where obstetric complications were significantly associated with increased odds of neonatal near miss\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eWith respect to gestational age, non-term neonates (preterm and post-term) had 1.9 times higher odds of neonatal near miss. This is due to the fact that preterm infants are more vulnerable to complications such as respiratory distress, hypothermia, and infections due to organ immaturity, while post-term births are often associated with increased risk of birth asphyxia, meconium aspiration, and placental insufficiency\u0026mdash;all of which contribute to adverse neonatal outcomes. Studies in India and Ghana identified non-term gestational age as a critical criterion for neonatal near miss. These studies highlighted that both preterm and post-term births are associated with increased risks of severe neonatal complications\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e,\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cp\u003eIt was shown that chronic maternal conditions (e.g., anemia, hypertension) were linked to 3.4 times higher odds of neonatal near miss (NNM). A similar study conducted in India found that 74.5% of NNM cases involved maternal comorbidities\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. This is due to the fact that chronic maternal health issues, such as hypertension, diabetes, and anemia, can significantly impair the physiological processes necessary for a healthy pregnancy.\u003c/p\u003e\u003cp\u003eFinally, regarding the sex of the newborn, the study revealed that male neonates had nearly double the odds of experiencing a neonatal near miss compared to females. This can be explained by the biological vulnerability of male infants, who are more prone to respiratory distress, infections, and slower lung maturation during the neonatal period. Although not conclusively evidenced by this study, existing literature suggests that male neonates generally have a higher risk of adverse outcomes due to these physiological factors\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e,\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\u003ch2\u003eStrengths and Limitations\u003c/h2\u003e\u003cp\u003e A key strength of this study is the use of standardized neonatal near miss criteria based on internationally recognized CLAP guidelines, which ensured consistency in case identification. The relatively large sample size and use of both maternal interviews and medical record reviews enhanced the reliability of the findings. Additionally, the multivariable analysis allowed for adjustment of confounding variables, strengthening the validity of the associations identified.\u003c/p\u003e\u003cp\u003eDespite its valuable contributions, the study has certain limitations. Although it included a relatively large sample size, it was conducted in a single hospital, which may not capture the full variability of neonatal care practices. In addition, some variables were based on maternal recall, which may have introduced recall bias and affected the precision of the data collected.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\u003ch2\u003eConclusion \u0026amp; recommendation\u003c/h2\u003e\u003cp\u003eThe burden of neonatal near miss remains a critical public health concern in Somalia. This study identified several factors significantly associated with neonatal near miss among neonates in Mogadishu. These included lack of formal maternal and paternal education, low household income, high parity, short birth interval, absence of antenatal care (ANC), history of stillbirth, obstetric complications, non-term gestational age, prolonged labor, home delivery, maternal chronic illnesses, male sex of the newborn, and low birth weight.\u003c/p\u003e\u003cp\u003eAddressing these factors is essential to reducing neonatal morbidity and improving survival. Interventions that promote ANC attendance, safe delivery practices, maternal education, and early identification of high-risk pregnancies should be prioritized by both governmental and humanitarian actors. Strengthening facility-based care and improving access to skilled birth attendants can play a pivotal role in preventing life-threatening neonatal complications and achieving better outcomes for newborns in resource-limited settings.\u003c/p\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets and materials utilized in this study can be obtained by reaching out to the corresponding author upon request.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThere is no funding for this manuscript.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval and participant consent\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was approved by the SOS College of Health Science Research Ethics Committee (Ref: SOSCHS/REC/2025/015). Informed consent was obtained from all participants, with strict confidentiality maintained. Participation was voluntary, and respondents could withdraw at any time without consequence.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCRediT authorship contribution statement\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHassan Abdullahi Dahie:\u0026nbsp;\u003c/strong\u003eWriting – review \u0026amp; editing, Writing – original draft, Visualization, Validation, Supervision, Software, Resources, Project administration, Methodology, Investigation, Formal analysis, Data curation, Conceptualization. \u003cstrong\u003eFalis Ibrahim Mohamud:\u0026nbsp;\u003c/strong\u003eWriting – review \u0026amp; editing, Writing – original draft, Supervision. \u003cstrong\u003eMohamed Abdullahi Osman:\u0026nbsp;\u003c/strong\u003eSupervision, Methodology, Data curation. \u003cstrong\u003eAbukar Abdi Osman:\u0026nbsp;\u003c/strong\u003eWriting – original draft, Data Collection. \u003cstrong\u003eYusuf Ali Jimale:\u0026nbsp;\u003c/strong\u003eVisualization, Supervision, Investigation. \u003cstrong\u003eHamdi Ahmed Hussein:\u0026nbsp;\u003c/strong\u003eSupervision, Investigation, Formal analysis. \u003cstrong\u003eMohamed Osman Alasow:\u0026nbsp;\u003c/strong\u003eVisualization, Software. \u003cstrong\u003eAbukar Abdi Osman:\u0026nbsp;\u003c/strong\u003eWriting – original draft. \u003cstrong\u003eAbdirahman Mohamed Abdullahi:\u003c/strong\u003e Writing – review \u0026amp; editing, Writing – original draft.\u003cstrong\u003e\u0026nbsp;Mohamed Maalin Dakane:\u0026nbsp;\u003c/strong\u003eWriting – review \u0026amp; editing, Writing – original draft, Formal analysis.\u003cstrong\u003e\u0026nbsp;Dek Abdi Hussein:\u0026nbsp;\u003c/strong\u003eWriting – review \u0026amp; editing, Writing – original draft, Formal analysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDeclaration of competing interest\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no financial and non-financial competing interests.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors express their gratitude to all individuals and organizations whose support and contributions were instrumental in the completion of this study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eParents\u0026rsquo; experiences of meeting and bonding. with their babies - Healthtalk Australia [Internet]. 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Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://pubmed.ncbi.nlm.nih.gov/17584623/\u003c/span\u003e\u003cspan address=\"https://pubmed.ncbi.nlm.nih.gov/17584623/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"maternal-health-neonatology-and-perinatology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"mhnp","sideBox":"Learn more about [Maternal Health, Neonatology and Perinatology](http://mhnpjournal.biomedcentral.com)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/mhnp/default.aspx","title":"Maternal Health, Neonatology and Perinatology","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Neonatal near miss, Somalia, determinants, antenatal care, neonatal outcomes, maternal health, case-control study.","lastPublishedDoi":"10.21203/rs.3.rs-6743554/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6743554/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eBackground\u003c/b\u003e\u003c/p\u003e\u003cp\u003eWhile the birth of a newborn is often a moment of great joy, it can be overshadowed by life-threatening complications that endanger survival in the early days of life. Neonatal near-miss (NNM) cases\u0026mdash;infants who narrowly survive severe complications\u0026mdash;offer a valuable lens for evaluating the quality of neonatal care. Somalia continues to experience one of the world\u0026rsquo;s highest neonatal mortality rates, reflecting major gaps in maternal and child health services. This study aimed to identify the determinants of neonatal near miss among neonates admitted to SOS Mother \u0026amp; Child Hospital, Benadir-Somalia.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods\u003c/b\u003e\u003c/p\u003e\u003cp\u003eAn unmatched case-control study was conducted at SOS Mother and Child Hospital in Benadir region from December 2024 to April, 2025. A total of 243 NNM cases and 730 healthy neonate controls were included. Cases were identified using pragmatic and management criteria from the CLAP criteria. For each case, three controls were randomly selected. Data were collected using structured interviews and record reviews, and analyzed using SPSS v25. Logistic regression was employed to identify independent predictors of neonatal near miss.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e\u003c/p\u003e\u003cp\u003eSignificant predictors of neonatal near miss included lack of maternal (AOR: 2.61) and paternal education (AOR: 3.64), monthly household income below 100 USD (AOR: 2.82), short birth interval under 24 months (AOR: 1.97), lack of antenatal care (ANC) attendance (AOR: 6.25), history of stillbirth (AOR: 4.35), obstetric complications (AOR: 4.46), preterm or post-term birth (AOR: 1.89), prolonged labor (AOR: 3.58), home delivery (AOR: 4.76), maternal chronic illness (AOR: 3.37), male sex of the newborn (AOR: 1.86), and low birth weight (AOR: 9.34).\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusion \u0026amp; recommendation\u003c/b\u003e\u003c/p\u003e\u003cp\u003eNeonatal near miss remains a pressing public health concern in Somalia, influenced by socio-demographic, obstetric, and neonatal factors. Strengthening maternal education, promoting antenatal care, ensuring skilled birth attendance, and improving facility-based delivery services are essential to reducing neonatal complications and improving outcomes. Policymakers and humanitarian partners must prioritize investments in maternal and newborn health to address these preventable risks.\u003c/p\u003e","manuscriptTitle":"Determinants of Neonatal Near Miss Among Newborns Admitted to SOS Mother \u0026amp; Child Hospital, Benadir Region, Somalia: A Case-Control Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-23 09:21:42","doi":"10.21203/rs.3.rs-6743554/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-08-08T11:40:38+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-27T10:19:27+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-07-26T10:50:20+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"133555331850058205859114603440178092501","date":"2025-07-26T09:45:36+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"306118263444388960825458629394114052044","date":"2025-07-26T03:15:46+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"138330543675640682411345040244514927489","date":"2025-07-23T04:20:47+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-07-20T23:18:06+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-05-27T06:25:34+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-05-27T06:24:18+00:00","index":"","fulltext":""},{"type":"submitted","content":"Maternal Health, Neonatology and Perinatology","date":"2025-05-25T11:57:47+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"maternal-health-neonatology-and-perinatology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"mhnp","sideBox":"Learn more about [Maternal Health, Neonatology and Perinatology](http://mhnpjournal.biomedcentral.com)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/mhnp/default.aspx","title":"Maternal Health, Neonatology and Perinatology","twitterHandle":"@BioMedCentral","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"c6d05606-1bb0-4c17-bdb0-946e7807f2c9","owner":[],"postedDate":"July 23rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-11-10T15:58:59+00:00","versionOfRecord":{"articleIdentity":"rs-6743554","link":"https://doi.org/10.1186/s40748-025-00234-7","journal":{"identity":"maternal-health-neonatology-and-perinatology","isVorOnly":false,"title":"Maternal Health, Neonatology and Perinatology"},"publishedOn":"2025-11-05 15:56:59","publishedOnDateReadable":"November 5th, 2025"},"versionCreatedAt":"2025-07-23 09:21:42","video":"","vorDoi":"10.1186/s40748-025-00234-7","vorDoiUrl":"https://doi.org/10.1186/s40748-025-00234-7","workflowStages":[]},"version":"v1","identity":"rs-6743554","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6743554","identity":"rs-6743554","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}