Neonatal Survival and Predictors of Mortality Among Neonates Admitted at Neonatal Intensive Care Unit in Ethiopia: A Prospective Cohort Study

Abstract

Introduction

Globally, neonatal mortality remains a significant challenge, with Sub-Saharan Africa bearing the highest burden. Ethiopia ranks among countries with the highest neonatal mortality rates, but limited data exist on timing and predictors of neonatal deaths in the study setting.

Objective(s)

To assess neonatal survival and identify predictors of mortality among neonates admitted to the neonatal intensive care unit (NICU).

Methods

A prospective cohort study was conducted on 504 neonates admitted to NICU. Adjusted hazard ratios (AHRs) with 95% confidence intervals (CIs) were calculated to evaluate associations between potential predictors and mortality.

Results

At study end, 23.6% (95% CI: 19.8, 27.4) of neonates died, with a mortality rate of 35.5 per 1,000 neonate-days. Neonatal survival declined from 90% on day 1 to 66% by day 28. Significant predictors of mortality included lack of antenatal care (ANC) (AHR = 3.09), failure to cry immediately at birth (AHR = 2.61), respiratory distress syndrome (AHR = 6.96), and meconium aspiration syndrome (AHR = 9.16).

Conclusion

Neonatal mortality remains high in the study setting. Strengthening maternal and neonatal care, especially ANC and institutional delivery, is vital to improve neonatal survival.

Keywords

neonatal intensive care unit neonatal mortality survival predictors Ethiopia

Introduction

Globally, approximately 2.3 million newborns died within the first 28 days of life in 2022, representing nearly half of all under-5 child deaths (World Health Organization, 2024). While substantial progress has been made since 1990, neonatal mortality rates remain disproportionately high in sub-Saharan Africa and South Asia, with rates of 27 and 21 deaths per 1,000 live births, respectively, compared to much lower rates in high-income regions (Mohamed et al., 2022; World Health Organization, 2024). Ethiopia's neonatal mortality rate remains above the Sustainable Development Goal target, with recent estimates around 23 deaths per 1,000 live births, highlighting ongoing challenges specific to the country (Kebede, 2025). The Sustainable Development Goals aim to reduce neonatal mortality to at least 12 per 1,000 live births by 2030 (Tolossa et al., 2022). Ethiopia's neonatal mortality rate decreased from 39 per 1,000 live births in 2005 to 29 per 1,000 in 2016 but increased to 33 per 1,000 in 2019 (Tekeba, Tamir et al., 2024).

Review of Literature

Major causes of neonatal mortality include preterm birth, perinatal asphyxia, infections, and congenital abnormalities. Contributing factors encompass poor maternal health, inadequate obstetric and neonatal care, and societal factors such as women's status, nutritional status, and traditional practices (Mengesha et al., 2016; Tolossa et al., 2022; Wondwossen et al., 2015; World Health Organization, 2017). Understanding the predictors and survival patterns of neonates in Ethiopia is critical to inform targeted interventions and accelerate progress toward national and global neonatal health goals (Kebede, 2025).

While Ethiopia has achieved notable reductions in neonatal mortality over the past decades, rates remain high due to multiple persistent challenges. System-level barriers such as inadequate health facility readiness, poor infrastructure including difficult geographic access and transportation, and shortages of skilled health personnel significantly limit effective neonatal care. Socio-economic inequities and cultural factors further hinder equitable access to timely, evidence-based interventions. Additionally, gaps in the implementation and utilization of proven maternal and neonatal health services, including antenatal care (ANC), skilled birth attendance, and postnatal follow-up, continue to impede progress. Addressing these multifaceted barriers is crucial to reduce neonatal deaths and achieve national and global health targets (Ethiopia Ministry of Health Fact Sheets, 2024; Kebede, 2025; Tebeje et al., 2025).

In Ethiopia, few studies have comprehensively examined neonatal mortality and its predictors. Existing research has largely been retrospective, omitting critical predictors and focusing only on survival status during neonatal intensive care unit (NICU) admission without follow-up post-discharge (Dessu et al., 2019; Enawgaw et al., 2025; Mengesha et al., 2016). To generate robust evidence for reducing neonatal mortality in Ethiopia, prospective studies with extended follow-up are essential. Addressing this knowledge gap, this study aimed to assess the survival status and identify predictors of neonatal mortality among neonates admitted to the NICU.

Methods and Materials

Study Design, Setting, and Period

A facility-based prospective cohort study was conducted from November 25, 2022, to February 25, 2023, at the NICU. The hospital has 15 departments and thirty units, with the NICU providing care to approximately 24,000 neonates annually. The NICU is equipped with essential supportive technologies including radiant warmers, continuous positive airway pressure (CPAP) machines, phototherapy units, and oxygen concentrators. Skilled staff, including pediatricians, neonatologists, and trained nurses, provide round-the-clock neonatal care in this facility.

Variables of the Study

Dependent variable: Neonatal mortality during the 28-day follow-up period.

Independent variables: Maternal sociodemographic factors (age, residence, marital status, education, ethnicity, religion, employment), maternal obstetric and medical factors (ANC, gestational age, pregnancy type, parity, birth interval, labor onset and duration, maternal medical diseases, obstetric complications), service delivery characteristics (mode and place of delivery, delivery attendant, iron-folic acid supplementation, postnatal care), and neonatal factors (sex, age at admission, birth weight, temperature, breastfeeding initiation, crying immediately after birth, respiratory distress syndrome (RDS), sepsis, perinatal asphyxia, meconium aspiration syndrome (MAS), congenital abnormalities, jaundice, resuscitation with bag and mask, CPAP intervention).

Sample Size Determination and Sampling Procedure

The sample size (n = 504) was calculated using Epi Info version 7 based on the cohort formula, with assumptions of 95% confidence interval (CI), 80% power, and a 1:1 ratio of exposed to non-exposed groups while considering different significant variables from previous studies (Berhanu et al., 2021; Eshete et al., 2021; Limaso et al., 2020). Predictor variables considered included fifth-minute APGAR score, birth weight, breastfeeding initiation time, and neonatal complications. Birth weight was identified as the primary predictor (Gebremariam et al., 2021; Park et al., 2018), yielding the largest sample size estimate of 480. An additional 5% was added to account for non-response and loss to follow-up, resulting in a final sample size of 504. Consecutive sampling was used to enroll eligible neonates until the sample size was reached.

Source and Study Population

The source population comprised all neonates admitted to the NICU during the study period. The study included neonates admitted between November 25, 2022, and February 25, 2023, whose mothers or caregivers were available to provide data during collection.

Data Collection Tools, Procedures, and Follow-Up

Data collection tools were adapted from the World Health Organization (WHO) standard verbal autopsy questionnaire (Mosley & Chen, 2003) and relevant literature, with modifications to fit the local context (Alebel et al., 2020; Eshete et al., 2021; Limaso et al., 2020). The questionnaire was initially prepared in English and translated into Afan Oromo and Amharic to ensure comprehensibility and consistency. Data were collected prospectively by five trained Bachelor of Science health professionals (two nurses, two midwives, and one supervisor) through interviews with mothers or caregivers and clinical assessments of neonates. Information collected included sociodemographic characteristics, maternal and neonatal clinical data, and service delivery factors. During hospitalization, neonates were followed daily in the NICU. Post-discharge follow-up was conducted via daily telephone calls to mothers and weekly home visits by health extension workers until the end of the neonatal period (28 days). Neonatal outcomes, including survival status and dates of any events (death or censoring), were recorded based on WHO verbal autopsy guidelines (Mosley & Chen, 2003). Cases where mothers or caregivers could not be reached despite home visits were recorded as lost to follow-up.

Data Quality Control

A pre-test was conducted on 5% of the sample at similar but another setting to assess the clarity and relevance of the questionnaire. Based on the pre-test results, some variables were amended for clarity, completeness, and contextual relevance. These amendments included refining definitions of key clinical predictors, improving the wording and sequence of questionnaire items to reduce ambiguity. Data collectors and supervisors received training on study protocols and data collection methods prior to fieldwork. The principal investigator and supervisor reviewed all completed questionnaires daily for completeness and accuracy, providing feedback as needed.

Regarding data cleaning, the researchers conducted a comprehensive process including range and consistency checks, identification and management of outliers, duplicate record detection, and correction of typographical and logical errors. Missing data were assessed and handled to minimize bias. Regarding subjects lost to follow-up in the survival analysis, these neonates were treated as censored observations at their last known follow-up time. Double data entry was performed to minimize entry errors prior to analysis.

Statistical Assumptions and Analysis

Multicollinearity among predictor variables was assessed using the variance inflation factor; values exceeding 10 indicated multicollinearity. Due to multicollinearity between attendant of delivery and postnatal care, attendant of delivery was excluded from the multivariable analysis. The proportional hazards assumption was checked graphically using log-minus-log survival plots for categorical variables; no violations were found, validating the use of the Cox proportional hazards model.

Data Processing and Analysis

Data were entered into EpiData version 3.1 and exported to SPSS version 20 for analysis. Descriptive statistics were calculated, including frequencies, percentages, means, medians, and standard deviations. Survival time was estimated using Kaplan–Meier (Kaplan & Meier, 1958; Shreffler & Huecker, 2020) survival curves, with comparisons performed via the log-rank test. Bivariable Cox proportional hazards regression was conducted to identify candidate predictors (p < 0.20) for multivariable analysis. Multivariable Cox regression models were used to estimate adjusted hazard ratios (AHRs) and 95% CIs for variables associated with neonatal mortality, with statistical significance set at p < 0.05.

Operational Definitions

Censored: Neonates who did not experience death during the follow-up period (including those who recovered, self-discharged, lost to follow-up, transferred, or still admitted beyond 28 days) (Mengistu et al., 2020). Event: Confirmed neonatal death during the follow-up period (Alebel et al., 2020). Survival status: The recorded outcome of each neonate (death or censored) at the end of follow-up. It was coded as a binary event indicator, where 1 represented death of the neonate and 0 represented censoring. Survival time: Duration in days from NICU admission until death or censoring (Tolossa et al., 2022).

Results

Maternal Sociodemographic Characteristics

A total of 504 neonates and their mothers participated in the study. The mean maternal age was 26.3 ± 5.3 years, with 48.4% aged under 25 years. Most mothers (75.2%) resided in urban areas. The Oromo ethnic group constituted 71.2% of participants. Housewives accounted for 73.2%, and 26.4% of mothers had completed secondary education (Table 1).

Table 1.

Maternal Sociodemographic Characteristics of Neonates Admitted to NICU from November 2022 to February 2023.

Variable	Category	Frequency	Percent	Survival Status
Variable	Category	Frequency	Percent	Death n (%)	Censored n (%)
Age of mother	<25 years	244	48.4	49 (20.1)	195 (79.9)
	25–30 years	173	34.3	44 (25.4)	129 (74.6)
	>30 years	87	17.3	26 (29.9)	61 (70.1)
Residence	Urban	379	75.2	84 (22.2)	295 (77.8)
Residence	Rural	125	24.8	35 (28)	90 (72)
Marital status	Married	481	95.4	110 (22.9)	371 (77.1)
Marital status	Divorced/Widowed	23	4.6	9 (39.1)	14 (60.9)
Ethnicity	Oromo	359	71.2	78 (21.7)	281 (78.3)
	Amhara	98	19.4	28 (28.6)	70 (71.4)
	Others^a	47	9.3	13 (27.7)	34 (72.3)
Religion	Muslim	185	36.7	40 (21.6)	145 (78.4)
	Orthodox	223	44.2	60 (26.9)	163 (73.1)
	Protestant	87	17.3	17 (19.5)	70 (80.5)
	Others^b	9	1.8	2 (22.2)	7 (77.8)
Educational status	Unable to read	65	12.9	22 (33.8)	43 (66.2)
	Primary	185	36.7	42 (22.7)	143 (77.3)
	Secondary	133	26.4	29 (21.8)	104 (78.2)
	College and above	121	24	26 (21.5)	95 (78.5)
Employment	Housewife	369	73.2	90 (24.4)	279 (75.6)
	Government	35	6.9	7 (20)	28 (80)
	Private	100	19.9	22 (22.0)	78 (78.0)

Indicates Sulte, Tigre, Gurage and Walaita; ^bIndicates Wakefata.

Maternal Obstetric and Medical Characteristics

Nearly all (97.2%) mothers attended at least one ANC visit, with 67.5% completing four or more visits. Two-thirds (66.9%) of mothers had one child, and 87.9% had singleton pregnancies. Medical conditions were present in 14.7% of mothers, with anemia affecting 9.3%. Obstetric complications during the current pregnancy were reported by 27.4% of mothers (Table 2).

Table 2.

Maternal Obstetric and Medical-Related Characteristics of Neonates Admitted to NICU from November 2022 to February 2023.

Variable	Category	Frequency	Percent	Survival Status
Variable	Category	Frequency	Percent	Death n (%)	Censored n (%)
ANC follow-up	Yes	490	97.2	112 (22.9)	378 (77.1)
ANC follow-up	No	14	2.8	7 (50)	7 (50)
Number of ANC follow-up (490)	<4 visits	150	30.6	56 (37.3)	94 (62.7)
Number of ANC follow-up (490)	≥4 visits	340	69.4	56 (16.5)	284 (83.5)
Type of pregnancy	Singleton	443	87.9	94 (21.2)	349 (78.8)
Type of pregnancy	Multiple	61	12.1	25 (41)	36 (59)
Gestational age at birth	<37 weeks	188	37.3	73 (38.8)	115 (61.2)
	37–40 weeks	271	53.8	38 (14.0)	233 (86.0)
	>40 weeks	45	8.9	8 (17.8)	37 (82.2)
Parity	1	337	66.9	71 (21.1)	266 (78.9)
	2–4	114	22.6	35 (30.7)	79 (69.3)
	>4	53	10.5	13 (24.5)	40 (75.5)
Preceding birth interval (167)	<2 years	24	14.4	8 (33.3)	16 (66.7)
	2–4 years	76	45.5	23 (30.3)	53 (69.7)
	>4 years	67	40.1	17 (25.4)	50 (74.6)
Onset of labor	Spontaneous	330	65.5	81 (24.5)	249 (75.5)
	Induced	95	18.8	26 (27.4)	69 (72.6)
	Not started	79	15.7	12 (15.2)	67 (84.8)
Duration of labor	≤12 h	310	61.5	73 (23.5)	237 (76.5)
Duration of labor	>12 h	115	22.8	34 (29.6)	81 (70.4)
Medical disease	Yes	74	14.7	24 (32.4)	50 (67.6)
Medical disease	No	430	85.3	95 (22.1)	335 (77.9)
Type of medical disease (74)	Hypertension	7	9.4	6 (85.7)	1 (14.3)
	DM	9	12.2	4 (44.4)	5 (55.6)
	Anemia	47	63.5	12 (25.5)	35 (74.5)
	Others^a	11	14.9	2 (18.2)	9 (81.8)
Obstetric complication	Yes	138	27.4	38 (27.5)	100 (72.5)
Obstetric complication	No	366	72.6	81 (22.1)	285 (77.9)
Type of obstetric complication (138)	Preeclampsia	52	37.7	20 (38.5)	32 (61.5)
	APH	13	9.4	3 (23.1)	10 (76.9)
	PROM	60	43.5	13 (21.7)	47 (78.3)
	Others^b	13	9.4	2 (15.4)	11 (84.6)

Indicates hepatitis, human immunodeficiency virus, heart failure, gastritis, ^bIndicates oligohydramnios, polyhydramnios.

APH = Antepartum hemorrhage; DM = Diabetes-mellitus; PROM = Prolonged rupture of membrane; ANC=antenatal care.

Service Delivery-Related Characteristics

Most mothers (80.6%) received iron-folic acid supplementation during pregnancy. Deliveries occurred predominantly in health facilities (94%), including hospitals (67.9%) and health centers (16.3%), while 6% occurred at home. Spontaneous vaginal delivery accounted for 54.8% of births. Postnatal care utilization was high at 94.4% (Table 3).

Table 3.

Service Delivery-Related Characteristics of Neonates Admitted to NICU from November 2022 to February 2023.

Variable	Category	Frequency	Percent	Survival Status
Variable	Category	Frequency	Percent	Death n (%)	Censored n (%)
Iron-folic acid supplementation	Yes	406	80.6	103 (25.4)	303 (74.6)
Iron-folic acid supplementation	No	98	19.4	16 (16.3)	82 (83.7)
Place of delivery	Hospital	342	67.9	81 (23.7)	261 (76.3)
	Health center	82	16.3	13 (15.9)	69 (84.1)
	Home	30	6	12 (40)	18 (60)
	Private MCHC	50	9.9	13 (26)	37 (74)
Attendant of delivery	HP	477	94.6	107 (22.4)	370 (77.6)
Attendant of delivery	TBA	27	5.4	12 (44.4)	15 (55.6)
Mode of delivery	SVD	276	54.8	75 (27.2)	201 (72.8)
	IAD	50	9.9	6 (12)	44 (88)
	CS	178	35.3	38 (21.3)	140 (78.7)
Postnatal care	Yes	476	94.4	108 (22.7)	368 (77.3)
Postnatal care	No	28	5.6	11 (39.3)	17 (60.7)

CS = Cesarean section; HP = Health professional; IAD = Instrumental assisted delivery; MCHC = Maternal and child health center; SVD = Spontaneous vaginal delivery; TBA = Traditional birth attendant.

Neonatal Characteristics

Among neonates admitted to the NICU, 60.1% were male. Most (70.8%) were admitted within 24 h of birth. Approximately 30.2% did not cry immediately after birth, and 70.8% did not initiate breastfeeding within the first hour. Normal birth weight (2,500–4,000 g) was observed in 54%, and a normal admission temperature (36.5–37.5 °C) in 31.3%. One-fourth (25.8%) of neonates were admitted with sepsis. Resuscitation with bag and mask and CPAP intervention were provided to 10.3% and 20% of neonates, respectively (Table 4).

Table 4.

Neonatal Characteristics of Neonates Admitted to NICU from November 2022 to February 2023.

Variable	Category	Frequency	Percent	Survival Status
Variable	Category	Frequency	Percent	Death n (%)	Censored n (%)
Sex of neonate	Female	201	39.9	55 (27.4)	146 (72.6)
Sex of neonate	Male	303	60.1	64 (21.1)	239 (78.9)
Age of neonate at admission	≤24 h	357	70.8	106 (29.7)	251 (70.3)
	2–7 days	81	16.1	8 (9.9)	73 (90.1)
	8–14 days	35	6.9	4 (11.4)	31 (88.6)
	15–28 days	31	6.2	1 (3.2)	30 (96.8)
Cry immediately at birth	Yes	352	69.8	47 (13.4)	305 (86.6)
Cry immediately at birth	No	152	30.2	72 (47.4)	80 (52.6)
Breastfeeding within 1 h	Yes	147	29.2	7 (4.8)	140 (95.2)
Breastfeeding within 1 h	No	357	70.8	112 (31.4)	245 (68.6)
Birth weight at admission in gram	<2500	219	43.5	78 (35.6)	141 (64.4)
	2500–4000	272	54	40 (14.7)	232 (85.3)
	>4000	13	2.6	1 (7.7)	12 (92.3)
Neonate's temperature at admission	<36.5 °C	300	59.5	96 (32)	204 (68)
	36.5 °C–37.5 °C	158	31.3	14 (8.9)	144 (91.1)
	>37.5 °C	46	9.1	9 (19.6)	37 (80.4)
Respiratory distress syndrome	Yes	72	14.3	52 (72.2)	20 (27.8)
Respiratory distress syndrome	No	432	85.7	67 (15.5)	365 (84.5)
MAS	Yes	23	4.6	10 (43.5)	13 (56.5)
MAS	No	481	95.4	109 (22.7)	372 (77.3)
Perinatal asphyxia	Yes	46	9.1	22 (47.8)	24 (52.2)
Perinatal asphyxia	No	458	90.9	97 (21.2)	361 (78.8)
Sepsis	Yes	130	25.8	17 (13.1)	113 (86.9)
Sepsis	No	374	74.2	102 (27.3)	272 (72.7)
Jaundice	Yes	46	9.1	1 (2.2)	45 (97.8)
Jaundice	No	458	90.9	118 (25.8)	340 (74.2)
Congenital abnormality	Yes	38	7.5	4 (10.5)	34 (89.5)
Congenital abnormality	No	466	92.5	115 (24.7)	351 (75.3)
Bag and mask resuscitation	Yes	52	10.3	32 (61.5)	20 (38.5)
Bag and mask resuscitation	No	452	89.7	87 (19.2)	365 (80.8)
CPAP intervention	Yes	101	20	64 (63.4)	37 (36.6)
CPAP intervention	No	403	80	55 (13.6)	348 (86.4)

CPAP = Continuous positive airway pressure; MAS = Meconium aspiration syndrome.

Neonatal Survival Status

During the 28-day follow-up, 119 neonates (23.6%; 95% CI: 19.8, 27.4) died, resulting in a mortality rate of 35.5 deaths per 1,000 neonate-days based on 3,349 neonate-days of observation. Notably, 41% of deaths occurred within the first 24 h, and 90% within the first seven days. Among the 385 censored neonates, the majority recovered, with smaller proportions self-discharging, remaining under follow-up, transferring to other facilities, or lost to follow-up (Figure 1).

Figure 1.

Outcomes of neonates admitted to NICU from November 2022 to February 2023. NICU=neonatal intensive care unit

Kaplan–Meier Survival Analysis

The Kaplan–Meier survival estimates indicated cumulative survival probabilities of 90.1%, 75.3%, 67.5%, and 66.1% at days 1, 7, 14, and 28, respectively. The overall mean survival time was 20 days (95% CI: 18.9–21.5). The Kaplan–Meier survival estimate represents the probability of survival accounting for censoring and time-at-risk, while crude mortality is a simple observed proportion. Both metrics provide complementary insights but should be interpreted in the context of censoring and follow-up patterns (Figure 2).

Figure 2.

Overall Kaplan-Meier survival curve among neonates admitted to NICU from November 2022 to February 2023.

Neonates who did not cry immediately at birth had significantly lower survival probabilities (38.1%) compared to those who cried immediately (80.2%) (p = 0.001). The median survival time for neonates who did not cry at birth was 10 days (95% CI: 6.49–13.51). This difference was statistically significant with p-value <0.001. The x-axis is labeled clearly as “Time (days)” spanning from 0 to 28 days to represent neonatal follow-up time. The y-axis is labeled as “Estimated Survival Probability,” ranging from 0 to 1, corresponding to 0% to 100% survival.

Two survival curves compare neonates who cried immediately at birth (higher survival) versus those who did not (lower survival). Small tick/censor marks appear on curves at times when neonates were censored (lost to follow-up or study end without death). Below the curves, risk tables display the number of neonates still at risk at key time points (e.g., 0, 7, 14, 21, 28 days), contextualizing reliability of survival estimates. This presentation visually clarifies the significant survival difference between groups, with median survival around 10 days for neonates who did not cry immediately (Figure 3).

Figure 3.

Comparison of the survival function of neonates who cried versus did not cry immediately at birth admitted to NICU from November 2022 to February 2023.

Predictors of Neonatal Mortality

After controlling for confounding variables, multivariable Cox proportional hazards regression analysis identified seven significant predictors of neonatal mortality:

Age of mother: Neonates born to mothers aged >30 years had twice the hazard of mortality compared to those born to mothers <25 years ([AHR] = 2.10, 95% CI: 1.26–3.50).

ANC follow-up: Neonates born to mothers without ANC follow-up had three times the hazard compared to those whose mothers had ANC (AHR = 3.09, 95% CI: 1.32–7.22).

Place of delivery: Neonates delivered at health centers showed lower mortality hazard vs. hospitals (AHR = 0.51, 95% CI: 0.26–0.98), likely due to referral bias—low-risk cases remain at health centers, while high-risk transfers to hospitals incur delays.

Crying immediately at birth: Neonates who did not cry immediately had nearly three times higher hazard compared to those who cried (AHR = 2.61, 95% CI: 1.70–4.01).

RDS: Neonates with RDS had almost seven times higher hazard (AHR = 6.96, 95% CI: 3.60–13.43).

MAS: Neonates with this syndrome had nine times higher hazard (AHR = 9.16, 95% CI: 3.58–23.4).

Perinatal asphyxia: Those with perinatal asphyxia had four times higher hazard (AHR = 4.34, 95% CI: 2.01–9.35) (Table 5).

Table 5.

Bivariable and Multivariable Cox Regression Analysis of Neonates Admitted to NICU from November 2022 to February 2023.

Variable	Category	Death	Censored	CHR (95% CI)	AHR (95% CI)	p-Value
Age of mother	<25	49	195	1.00	1.00
	25–30	44	129	1.40 (0.93, 2.11)	1.57 (1.00, 2.43)	0.050
	>30	26	61	1.52 (0.94, 2.44)	2.10 (1.26, 3.50)	0.004
Antenatal care (ANC) follow-up	Yes	112	378	1.00	1.00
Antenatal care (ANC) follow-up	No	7	7	2.61 (1.22, 5.60)	3.09 (1.32, 7.22)	0.009
Gestational age at birth	<37 weeks	73	115	2.72 (1.83, 4.02)	1.16 (0.65, 2.09)	0.617
	37–40 weeks	38	233	1.00	1.00
	>40 weeks	8	37	1.27 (0.59, 2.73)	1.06 (0.47, 2.39)	0.894
Type of pregnancy	Singleton	94	349	1.00	1.00
Type of pregnancy	Multiple	25	36	1.96 (1.26, 3.04)	1.61 (0.97, 2.68)	0.065
Sex of neonate	Female	55	146	1.34 (0.94, 1.93)	1.14 (0.78, 1.67)	0.503
Sex of neonate	Male	64	239	1.00	1.00
Place of delivery	Hospital	81	261	1.00	1.00
	Health center	13	69	0.64 (0.36, 1.16)	0.51 (0.26, 0.98)	0.043
	Home	12	18	1.83 (1.00, 3.35)	1.31 (0.64, 2.68)	0.463
	Private MCHC	13	37	1.18 (0.66, 2.12)	1.55 (0.82, 2.93)	0.182
Mode of delivery	SVD	75	201	1.00	1.00
	IAD	6	44	0.41 (0.18, 0.95)	0.43 (0.18, 1.04)	0.062
	Cesarean section	38	140	0.78 (0.53, 1.16)	0.98 (0.63, 1.55)	0.944
Cried immediately at birth	Yes	47	305	1.00	1.00
Cried immediately at birth	No	72	80	3.86 (2.67, 5.57)	2.61 (1.70, 4.01)	0.001
Breastfeeding initiation within 1 h	Yes	7	140	1.00	1.00
Breastfeeding initiation within 1 h	No	112	245	6.28 (2.93, 13.5)	1.60 (0.66, 3.89)	0.304
Birth weight at admission in gram	<2500	78	141	2.33 (1.59, 3.41)	1.24 (0.71, 2.17)	0.452
	2500–4000	40	232	1.00	1.00
	>4000	1	12	0.48 (0.07, 3.48)	0.80 (0.11, 5.97)	0.824
Temperature of the neonate at admission	<36.5 °C	96	204	3.41 (1.95, 5.98)	1.01 (0.53, 1.89)	0.999
	36.5–37.5 °C	14	144	1.00	1.00
	>37.5 °C	9	37	2.05 (0.89, 4.73)	2.09 (0.86, 5.10)	0.106
Respiratory distress syndrome	Yes	52	20	6.01 (4.18, 8.64)	6.96 (3.6, 13.43)	0.001
Respiratory distress syndrome	No	67	365	1.00	1.00
Meconium aspiration syndrome	Yes	10	13	2.04 (1.07, 3.90)	9.16 (3.58, 23.4)	0.001
Meconium aspiration syndrome	No	109	372	1.00	1.00
Perinatal asphyxia	Yes	22	24	2.19 (1.38, 3.48)	4.34 (2.01, 9.35)	0.001
Perinatal asphyxia	No	97	361	1.00	1.00
Sepsis	Yes	17	113	0.41 (0.25, 0.69)	1.34 (0.64, 2.80)	0.441
Sepsis	No	102	272	1.00	1.00
Jaundice	Yes	1	45	0.08 (0.01, 0.59)	0.31 (0.04, 2.44)	0.265
Jaundice	No	118	340	1.00	1.00
Congenital abnormality	Yes	4	34	0.39 (0.14, 1.05)	1.03 (0.31, 3.40)	0.964
Congenital abnormality	No	115	351	1.00	1.00

AHR = Adjusted Hazard Ratio; CHR = Crude Hazard Ratio; IAD = Instrumental Assisted Delivery; MCHC = Maternal and child health center; SVD = Spontaneous Vaginal Delivery; 1.00 = Reference Category; CI=confidence interval.

Discussion

This prospective cohort study evaluated the survival status and predictors of neonatal mortality among neonates admitted to the NICU. The neonatal mortality rate observed was 35.5 per 1,000 neonate-days, with an overall mortality proportion of 23.6% (95% CI: 19.8, 27.4). This finding aligns with studies conducted in Eastern Ethiopia (20%) and Debre Markos (21.3%) (Alebel et al., 2020; Desalew et al., 2020). However, it was higher than reports from Dire Dawa (11.4%) (Thomas et al., 2021), Hawassa (14.2%) (Taye et al., 2024), Nekemte town (15.3%) (Tolossa et al., 2022), Southern Ethiopia (16.5%) (Orsido et al., 2019), and Hadiya zone (18.8%) (Moges et al., 2021), possibly reflecting differences in sample sizes, socio-economic factors, health service utilization, and retrospective versus prospective study designs (Orsido et al., 2019; Thomas et al., 2021). These differences may reflect variations in sample sizes, socio-economic factors, healthcare utilization, institutional settings, economic disparities, and study designs, with retrospective cohorts potentially underestimating mortality due to incomplete records (Taye et al., 2024).

The cumulative neonatal survival proportion at 28 days in this study was 66.1%, which is lower than the 71.11% reported in Amhara regional referral hospitals and 93.96% in Tigray, Northern Ethiopia (Mengesha et al., 2016; Mengistu et al., 2020). This discrepancy likely arises because this study focused on admitted neonates, representing a high-risk group, whereas the other studies included all live births, which generally have better outcomes. Conversely, the survival proportion in this study exceeds the 57.14% reported in a study at the University of Gondar, which exclusively investigated preterm neonates—a particularly vulnerable subgroup (Yismaw et al., 2019). This suggests that risk of death among premature neonates is higher and they frequently succumb shortly after birth due to adjustment difficulties outside the uterus (Huka et al., 2023; Toma et al., 2021).

Survival at the end of the first day was 90.1%, comparable to Amhara regional referral hospitals (89.15%) (Mengistu et al., 2020), but lower than findings in Southern Ethiopia's Bombe Primary Hospital (97.2%) (Berhanu et al., 2021) and the University of Gondar (96.71%) (Yismaw et al., 2019). Differences may reflect study design variability, as retrospective studies risk underestimating early mortality due to incomplete data.

Maternal age over 30 years was associated with a twofold increased risk of neonatal death compared to mothers under 25 years. This is consistent with findings from Sudan, Southern Ethiopia, and Amhara regional referral hospitals (Bashir et al., 2013; Eshete et al., 2021; Mengistu et al., 2020). Advanced maternal age (AMA) influences mortality through a complex interplay of biological, health system, socio-cultural, and nursing-related factors. AMA is associated with the increased risk of adverse neonatal outcomes including preterm birth, low birth weight, congenital anomalies, and perinatal asphyxia. Biologically, AMA increases maternal comorbidities such as hypertension and diabetes, and contributes to placental insufficiency, which compromise fetal development and neonatal health. Studies in Ethiopia and globally document that neonates born to AMA mothers have higher mortality, partly due to increased perinatal complications and lower Apgar scores. Socio-economic factors, such as lower access to quality maternal health services and delayed care-seeking, exacerbate risks. Older maternal age is linked to higher incidence of complications and prematurity, which may explain this increased risk (Kim et al., 2021; Mutz-Dehbalaie et al., 2014; Tekeba, Techane et al., 2024).

Lack of ANC follow-up tripled the hazard of neonatal mortality, aligning with previous studies from Nigeria, Western Ethiopia, Wolaita, Debre Markos, Hadiya, Gedeo, and Asella (Adetola et al., 2011; Alebel et al., 2020; Aredo et al., 2024; Eshete et al., 2021; Moges et al., 2021; Orsido et al., 2019; Tolossa et al., 2022). ANC offers critical opportunities to detect and manage pregnancy complications early and impart birth preparedness education, ultimately reducing neonatal morbidity and mortality (Tolossa et al., 2022). Socio-economic factors, such as lower access to quality maternal health services and delayed care-seeking, exacerbate risks. Inadequate ANC compounds this risk by missing opportunities for early detection and management of pregnancy complications, vaccination, and birth preparedness education. Health system gaps like shortages of skilled providers, limited infrastructure, and poor continuity of care reduce ANC effectiveness, especially in rural and underserved areas (Asaye et al., 2025; Ethiopian Public Health Institute, 2022). From a nursing perspective, failure to provide comprehensive ANC including counseling and timely intervention increases vulnerability to adverse outcomes. Nurses and midwives play a pivotal role in identifying high-risk pregnancies and facilitating referrals, but may face challenges such as heavy workloads and limited resources. Socio-cultural barriers including traditional beliefs, gender norms, and financial constraints also reduce ANC attendance and skilled birth attendance, further threatening neonatal survival (Alemu et al., 2025; Awoke et al., 2024; Gebrekirstos et al., 2025; Ministry of Health Ethiopia, 2024). AMA and lack of ANC influence neonatal mortality through biological vulnerabilities compounded by systemic inadequacies and socio-cultural barriers. Addressing these factors requires integrated interventions targeting health system strengthening, community engagement, and capacity-building for maternal and neonatal care providers to improve outcomes (Tekeba, Tamir et al., 2024).

Interestingly, neonates delivered at health centers had a lower mortality hazard than those at hospitals (adjusted HR 0.51, 95% CI: 0.26–0.98). This counterintuitive finding likely stems from referral bias: low-risk cases are typically managed at health centers, whereas high-risk mothers are transferred to hospitals, where delays may contribute to adverse outcomes. Lack of timely transportation, financial constraints, and hospital capacity issues may exacerbate this risk. As no prior studies have reported this association, further research is needed to understand the impact of delivery setting on neonatal survival.

Neonates who did not cry immediately after birth had nearly a threefold increased mortality risk, consistent with studies from the University of Gondar and Nekemte Referral Hospital (Gudayu et al., 2020; Roro et al., 2019). Not crying signifies ineffective lung inflation and cardiopulmonary instability, serving as a simple clinical indicator of increased mortality risk (Kc et al., 2020).

RDS increased mortality risk nearly sevenfold, corroborating studies from Mexico, Afar, Debre Markos, Hadiya, and Addis Ababa (Alebel et al., 2020; Menalu et al., 2022; Moges et al., 2021; Reyes et al., 2018; Zekarias et al., 2024). The vulnerability of premature neonates, who represent over one-third (37.3%) of admissions, likely explains this high association as RDS is a leading cause of death among this group (Basiri et al., 2015; Dev et al., 2022; Mbawala et al., 2014; Taye et al., 2024).

MAS increased the risk of death ninefold. MAS, resulting from inhalation of meconium-stained amniotic fluid, is a significant cause of respiratory distress and a major contributor to neonatal morbidity and mortality, frequently necessitating NICU admission (Adugna et al., 2025; Dini et al., 2024; Louis et al., 2014).

Perinatal asphyxia quadrupled neonatal mortality risk, supporting findings from Ghana (Apanga et al., 2024) and various Ethiopian regions, including East Wollega, Wolaita, Hadiya, Hawassa, and Addis Ababa (Abera et al., 2021; Menalu et al., 2022; Moges et al., 2021; Orsido et al., 2019; Taye et al., 2024). Asphyxia impairs neonatal respiratory function at birth and is a critical determinant of survival (Woday et al., 2019).

Neonatal nurses play a pivotal role in the early identification and management of common life-threatening conditions such as respiratory distress, perinatal asphyxia, and MAS. Through continuous monitoring of vital signs, assessment of respiratory effort, and timely initiation of supportive therapies such as oxygen administration, CPAP, and suctioning nurses can stabilize neonates and reduce morbidity and mortality. Their expertise in neonatal resuscitation and adherence to protocols improves outcomes for infants experiencing birth asphyxia (Alemu et al., 2025; Mathai et al., 2007). Furthermore, nurses and midwives are essential in providing antenatal education and counseling, emphasizing birth preparedness, danger sign recognition, and the importance of facility-based deliveries. Community-based follow-up programs, often led by nurses, facilitate early postnatal visits and monitor growth and development, ensuring prompt referral of at-risk neonates (Alemu et al., 2025). Training and capacity-building interventions led by experienced neonatal nurses enhance the skills of less experienced staff and birth attendants, strengthening emergency newborn care across facilities. Such programs focus on evidence-based practices, newborn resuscitation, and supportive care techniques, which have proven effective in reducing neonatal mortality in resource-limited settings (Awoke et al., 2024).

Strengths and Limitations

The study's strengths include its prospective cohort design with 28-day follow-up, enabling timely and comprehensive assessment of neonatal survival during hospitalization and post-discharge, which reduces biases typical in retrospective studies. Inclusion of consecutive NICU admissions with daily clinical monitoring and systematic follow-up captured data from a high-risk population, allowing robust evaluation of mortality predictors.

Limitations involve being single-center in a referral hospital NICU with many severely ill cases, limiting generalizability and possibly overestimating mortality. Referral delays and inborn versus outborn status were not modeled, potentially confounding delivery place associations. Lack of clustering adjustment for twins and variable post-discharge follow-up response may affect precision and outcome completeness. Analytical limitations include potential overfitting, omitted variable bias, lack of model validation, and unmeasured confounders like socio-economic status and staffing ratios. Counterintuitive findings, such as lower mortality at health centers, likely reflect unmeasured referral severity bias; these warrant cautious interpretation and further research. No recommendations are intended for preferring health centers over hospitals—multi-site studies are needed.

Implications for Practice

Enhancing Antenatal Care Coverage

The finding of this study that lack of ANC triples neonatal mortality risk (AHR 3.09, 95% CI 1.32–7.22) underscores ANC's role in early detection of risks like preterm birth and maternal complications (e.g., anemia in 9.3% of cases). High-quality ANC—defined per WHO as ≥8 contacts—enables screening, iron-folic acid supplementation (received by 80.6% here), and birth preparedness, reducing hazards by addressing modifiable factors. Nurses should lead community outreach to boost uptake from 97.2% ever-attendance to ≥4 visits (currently 69.4%), targeting rural mothers (24.8% of sample) via home visits and education on danger signs. Policy-wise, integrate ANC with health extension programs to achieve Ethiopia's Health Sector Transformation Plan II goals.

Optimizing Institutional Deliveries with Referral Awareness

Neonates delivered at health centers showed 49% lower mortality hazard than hospitals (AHR 0.51, 95% CI 0.26–0.98), likely due to referral bias: low-risk cases (e.g., spontaneous vaginal deliveries, 54.8%) stay local, while high-risk transfers delay care. This counterintuitive result cautions against preferring health centers outright; instead, strengthen first-line facilities with basic resuscitation tools. Midwives/nurses should promote ≥94.6% health professional-attended births (current rate) but ensure seamless referrals via ambulance networks, reducing home deliveries (6%). Conceptualize as a tiered system: equip health centers for stable cases, reserving hospitals for complications like RDS (14.3% prevalence).

Immediate Neonatal Resuscitation and Supportive Care

Failure to cry at birth nearly tripled mortality (AHR 2.61, 95% CI 1.70–4.01), signaling cardiopulmonary instability in 30.2% of admissions. Nurses must prioritize Helping Babies Breathe protocols: dry, stimulate, and bag-mask ventilate (used in 10.3%) within the Golden Minute. For RDS (AHR 6.96, 95% CI 3.60–13.43; 14.3% cases), MAS (AHR 9.16, 95% CI 3.58–23.4), and asphyxia (AHR 4.34, 95% CI 2.01–9.35), scale CPAP (20% usage) and oxygen in all NICUs, targeting preterm neonates (37.3%). Train staff on kangaroo care and early breastfeeding (only 29.2% within 1 h), conceptually bridging intrapartum stability to postnatal survival.

System-Level Strengthening: Referrals, Transport, and Follow-Up

With 41% deaths in first 24 h and survival dropping to 66.1% by day 28, post-discharge monitoring (94.4% postnatal care) is vital. Implement daily phone/home visits by nurses/health extensions for high-risk neonates (e.g., low birth weight, 43.5%). Address transport gaps exacerbating referral risks via subsidized ambulances and community financing.

Empowering Nursing Workforce

Nurses/midwives (key in 94.6% deliveries) should drive identification (e.g., hypothermia in 59.5%), resuscitation, ANC counseling, and follow-up. Provide simulation-based training on NICU protocols, empowering them as change agents in Ethiopia's 23.6% NICU mortality context.

Health System and Community Integration

Bolster infrastructure (e.g., CPAP units, staffing), training, and awareness campaigns are to increase ANC/institutional uptake. Partner with Ethiopia's Ministry of Health for scalable interventions, conceptually aligning predictors with Sustainable Development Goal 3.2 (≤12 deaths/1,000 live births by 2030). These evidence-based steps can halve hazards from top predictors, improving survival from 66.1% to national targets.

Recommendations to Improve Neonatal Mortality Rates

To improve neonatal mortality rates, focus on expanding high-quality ANC and promoting institutional deliveries, especially at health centers with lower mortality risk. Prioritize maternal health for women aged 30 and above. Implement immediate neonatal care, including resuscitation, and manage respiratory distress, meconium aspiration, and perinatal asphyxia. Equip NICUs with respiratory support like CPAP and bag-mask ventilation. Strengthen referral systems with timely transport and post-discharge follow-up. Promote community awareness on ANC and institutional deliveries, train healthcare workers in neonatal care, and ensure skilled staff and essential equipment in facilities. These actions collectively reduce neonatal deaths effectively.

Conclusion

Neonatal mortality remains high among NICU admissions in the study area, with significant predictors including maternal age over 30, lack of ANC, place of delivery, failure to cry at birth, RDS, MAS, and perinatal asphyxia. These findings emphasize the need to strengthen maternal and neonatal healthcare through improved ANC coverage, institutional deliveries with referral systems, and enhanced neonatal resuscitation and respiratory support. While the study's design and observation offer valuable insights, methodological limitations affect generalizability. Future research should enhance analytic rigor and population representativeness. Policy efforts must focus on expanding access to quality care, building workforce capacity—particularly among nurses and midwives—and integrating community education and follow-up. Investment in infection control, infrastructure, and data monitoring aligns with national programs such as the Quality Equity and Dignity initiative and the 10 Million Safer Births Initiative, supporting Ethiopia's progress toward SDGs. The active role of neonatal nurses and midwives in early complication management and multidisciplinary collaboration is vital, consistent with Ethiopia's Health Sector Transformation Plan II priorities.

Supplemental Material

sj-docx-1-son-10.1177_23779608261437595 - Supplemental material for Neonatal Survival and Predictors of Mortality Among Neonates Admitted at Neonatal Intensive Care Unit in Ethiopia: A Prospective Cohort Study

Supplemental material, sj-docx-1-son-10.1177_23779608261437595 for Neonatal Survival and Predictors of Mortality Among Neonates Admitted at Neonatal Intensive Care Unit in Ethiopia: A Prospective Cohort Study by Gemechu Dereje Feyissa, Daniel G/tsadik, Tilaye Workneh, Endashaw Mandefro Kidane and Mokonnen Dereje in SAGE Open Nursing

Supplemental Material

sj-docx-2-son-10.1177_23779608261437595 - Supplemental material for Neonatal Survival and Predictors of Mortality Among Neonates Admitted at Neonatal Intensive Care Unit in Ethiopia: A Prospective Cohort Study

Supplemental material, sj-docx-2-son-10.1177_23779608261437595 for Neonatal Survival and Predictors of Mortality Among Neonates Admitted at Neonatal Intensive Care Unit in Ethiopia: A Prospective Cohort Study by Gemechu Dereje Feyissa, Daniel G/tsadik, Tilaye Workneh, Endashaw Mandefro Kidane and Mokonnen Dereje in SAGE Open Nursing

Footnotes

Abbreviations

Acknowledgment

The authors would like to thank the data collectors, the NICU staff of AHMC for their cooperation, and the mothers of neonates who voluntarily participated and provided the required information to complete this research.

ORCID iD

Gemechu Dereje Feyissa

Ethical Statement

The study protocol conformed to the Declaration of Helsinki and was approved by the Institutional Review Committee of Rift Valley University (Ref/No: 18817/28/22). Administrative permission was obtained from AHMC and the NICU. Verbal informed consent was obtained from mothers or legal guardians after providing clear explanations of the study's purpose. The ethics committee waived written informed consent given the minimal risk involved, with assurances of confidentiality and secure data management. Only the principal investigator accessed identifiable data.

Authors Contributions

GDF contributed to study conception, design, and acquisition of data, software, analysis and interpretation, a critical review of the document and development of the manuscript. DG and TW participated in reviewing the study design, data analysis, interpretation, and revision of the manuscript. EMK and MD involved in reviewing the study design, data analysis, and interpretation. All authors read and approved the final manuscript.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data Sharing and Data Availability Statement

Data supporting the findings of this study are available from the corresponding author upon reasonable request.

Supplemental Material

Supplemental material for this article is available online.

References

Abera

Bayisa

Bekele

Dessalegn

Mulisa

Gamtessa

L. C.

(2021). Neonatal mortality and its associated factors among neonates admitted to Wollega University Referral Hospital Neonatal Intensive Care Unit, East Wollega, Ethiopia. Global Pediatric Health, 8(1), 2333794X211030157. https://doi.org/10.1177/2333794X211030157

Adetola

A. O.

Tongo

O. O.

Orimadegun

A. E.

Osinusi

(2011). Neonatal mortality in an urban population in Ibadan, Nigeria. Pediatrics & Neonatology, 52(5), 243–250. https://doi.org/10.1016/j.pedneo.2011.06.001

Adugna

Asmare

Wondim

(2025). Meconium aspiration syndrome and associated factors among neonates admitted at neonatal intensive care unit at Northwest Ethiopia comprehensive specialized hospitals Northwest Ethiopia 2023. BMC Pediatrics, 25(1), 167. https://doi.org/10.1186/s12887-024-05181-4

Alebel

Wagnew

Petrucka

Tesema

Moges

N. A.

Ketema

D. B.

Yismaw

Melkamu

M. W.

Hibstie

Y. T.

Temesgen

Bitew

Z. W.

Tadesse

A. A.

Kibret

G. D.

(2020). Neonatal mortality in the neonatal intensive care unit of Debre Markos referral hospital, Northwest Ethiopia: A prospective cohort study. BMC Pediatrics, 20(1), 1–11. https://doi.org/10.1186/s12887-020-1963-z

Alemu

A. A.

Welsh

Getachew

Khajehei

(2025). Assessment of antenatal care quality in Ethiopia: Facility-based study using service provision assessment data. PLoS One, 20(1), e0313527. https://doi.org/10.1371/journal.pone.0313527

Apanga

D. A.

Kumbeni

M. T.

Salifu

A. M.

Mireku-Gyimah

Apanga

P. A.

(2024). Predictors of neonatal mortality in the Eastern Regional Hospital in Ghana: A retrospective cohort study. PLoS Global Public Health, 4(6), e0003295. https://doi.org/10.1371/journal.pgph.0003295

Aredo

M. T.

Habtamu

Bekele

Legese

Yihdego

Hailu

Alemnew

Marara

(2024). Prevalence and associated factor of neonatal mortality among neonates admitted to Asella referral and teaching hospital, Asella, Ethiopia, 2024. Journal of Pediatrics & Neonatal Care, 14(1), 86–93. https://doi.org/10.15406/jpnc.2024.14.00547

Asaye

Sekata

Birhanu

Gudeta

Besho

Getnet

Tura Debelew

Berhanu

Siraneh

Abamecha

Tamiru

(2025). Trends and determinants of neonatal mortality in rural Ethiopia. Sage Open Pediatrics, 12, 30502225251319871. https://doi.org/10.1177/30502225251319871

Awoke

Ababulgu

S. A.

Hanfore

L. K.

Gebeyehu

E. G.

Wake

S. K.

(2024). Regional disparities in antenatal care utilization among pregnant women and its determinants in Ethiopia. Frontiers in Global Women's Health, 5, 1230975. https://doi.org/10.3389/fgwh.2024.1230975

10.

Bashir

A. O.

Ibrahim

G. H.

Bashier

I. A.

Adam

(2013). Neonatal mortality in Sudan: Analysis of the Sudan household survey, 2010. BMC Public Health, 13, 1–9. https://doi.org/10.1186/1471-2458-13-287

11.

Basiri

Ashari

F. E.

Shokouhi

Sabzehei

M. K.

(2015). Neonatal mortality and its main determinants in premature infants hospitalized in neonatal intensive care unit in Fatemieh Hospital, Hamadan, Iran. Journal of Comprehensive Pediatrics, 6(3). https://doi.org/10.17795/compreped-26965

12.

Berhanu

Oljira

Demana

Negash

Mamo Ayana

Beshir Raru

Haile

(2021). Survival and predictors of mortality among neonates admitted to neonatal intensive care unit at Bombe Primary Hospital, Southern Ethiopia: Institution-based retrospective cohort study. Pediatric Health, Medicine and Therapeutics, 12, 239–249. https://doi.org/10.2147/PHMT.S303158

13.

Desalew

Sintayehu

Teferi

Amare

Geda

Worku

Abera

Asefaw

(2020). Cause and predictors of neonatal mortality among neonates admitted to neonatal intensive care units of public hospitals in eastern Ethiopia: A facility-based prospective follow-up study. BMC Pediatrics, 20(1), 1–11. https://doi.org/10.1186/s12887-020-02051-7

14.

Dessu

Kote

Gebremeskel

Girum

(2019). Predictors of neonatal mortality among neonates who admitted in neonatal intensive care unit at Arba Minch General Hospital. Ethiopian Journal of Health Development, 33(1), 46–52. https://doi.org/10.4314/ejhd.v33i1.11

15.

Dev

Casseus

Baptiste

W. J.

LeWinter

Joseph

Wright

(2022). Neonatal mortality in a public referral hospital in southern Haiti: A retrospective cohort study. BMC Pediatrics, 22(1), 81. https://doi.org/10.1186/s12887-022-03141-4

16.

Dini

Ceccarelli

Celi

Semeraro

C. M.

Gorello

Verrotti

(2024). Meconium aspiration syndrome: From pathophysiology to treatment. Annals of Medicine and Surgery, 86(4), 2023–2031. https://doi.org/10.1097/MS9.0000000000001835

17.

Enawgaw

A. S.

Belay

Nigate

Yeshiwas

A. G.

Shumet

Endalew

Bishaw

K. A.

(2025). Survival status and predictors of mortality among neonates admitted to neonatal intensive care unit at Bichena Primary Hospital, Northwest Ethiopia. A retrospective cohort study. Frontiers in Pediatrics, 13, 1529089. https://doi.org/10.3389/fped.2025.1529089

18.

Eshete

Tadesse

Tesfaye

Abiy

(2021). Magnitude and risk of neonatal death in neonatal intensive care unit at referral hospital in Godeo Zone: a prospective cohort study. Pan African Medical Journal, 38(1). https://doi.org/10.11604/pamj.2021.38.201.20650

19.

Ethiopia Ministry of Health Fact Sheets. (2024).

20.

Ethiopian Public Health Institute. (2022). Maternal and Neonatal Health Exemplar study, Ethiopia.

21.

Gebrekirstos

L. G.

Gebremedhin

M. H.

Berhe

Wube

T. B.

(2025). Factors associated with antenatal care service content utilization in selected rural areas of Southern Ethiopia: Assessing the extent of compliance with World Health Organization recommendations—A mixed-methods study. Women's Health, 21, 17455057251375220. https://doi.org/10.1177/17455057251375220

22.

Gebremariam

A. D.

Tiruneh

S. A.

Engidaw

M. T.

Tesfa

Azanaw

M. M.

Yitbarek

G. Y.

Asmare

(2021). Development and validation of a clinical prognostic risk score to predict early neonatal mortality, Ethiopia: A receiver operating characteristic curve analysis. Clinical Epidemiology, 13, 637–647. https://doi.org/10.2147/CLEP.S321763

23.

Gudayu

T. W.

Zeleke

E. G.

Lakew

A. M.

(2020). Time to death and its predictors among neonates admitted in the intensive care unit of the University of Gondar Comprehensive Specialized Hospital, Northwest Ethiopia. Research and Reports in Neonatology, 10, 1–10. https://doi.org/10.2147/RRN.S233828

24.

Huka

A. E.

Oljira

Weldesenbet

A. B.

Bushra

A. A.

Ahmed

I. A.

Tura

A. K.

Tuluka

A. A.

(2023). Predictors of time to death among preterm neonates admitted to neonatal intensive care units at public hospitals in southern Ethiopia: A cohort study. PLoS One, 18(10), e0283143. https://doi.org/10.1371/journal.pone.0283143

25.

Kaplan

E. L.

Meier

(1958). Nonparametric estimation from incomplete observations. Journal of the American Statistical Association, 53(282), 457–481. https://doi.org/10.1080/01621459.1958.10501452

26.

Lawn

J. E.

Zhou

Ewald

Gurung

Sunny

A. K.

Day

L. T.

Singhal

(2020). Not crying after birth as a predictor of not breathing. Pediatrics, 145(6). https://doi.org/10.1542/peds.2019-2719

27.

Kebede

S. D.

(2025). Forecasting neonatal mortality in Ethiopia to assess progress toward national and international reduction targets using classical techniques and deep learning: Time-series forecasting study. Online Journal of Public Health Informatics, 17(1), e66798. https://doi.org/10.2196/66798

28.

Kim

Y. N.

Choi

D. W.

Kim

D. S.

Park

E. C.

Kwon

J. Y.

(2021). Maternal age and risk of early neonatal mortality: A national cohort study. Scientific Reports, 11(1), 814. https://doi.org/10.1038/s41598-021-80968-4

29.

Limaso

A. A.

Dangisso

M. H.

Hibstu

D. T.

(2020). Neonatal survival and determinants of mortality in Aroresa district, Southern Ethiopia: A prospective cohort study. BMC Pediatrics, 20(1), 1–8. https://doi.org/10.1186/s12887-019-1907-7

30.

Louis

Sundaram

Mukhopadhyay

Dutta

Kumar

(2014). Predictors of mortality in neonates with meconium aspiration syndrome. Indian Pediatrics, 51(8), 637–640. https://doi.org/10.1007/s13312-014-0466-0

31.

Mathai

S. S.

Raju

Kanitkar

(2007). Management of respiratory distress in the newborn. Medical Journal Armed Forces India, 63(3), 269–272. https://doi.org/10.1016/S0377-1237(07)80152-3

32.

Mbawala

G. B.

Fredrick

Kamugisha

Konje

Hokororo

(2014). Factors associated with mortality among premature babies admitted at Bugando Medical Centre, Mwanza-Tanzania. East African Journal of Public Health, 11(1), 641–645. https://doi.org/10.4314/eajph.v11i1.106

33.

Menalu

M. M.

Gebremichael

Desta

K. W.

Kebede

W. M.

Tarekegn

F. N.

Mulu

G. B.

Atinafu

B. T.

(2022). Time to death and its predictors among neonates who were admitted to the neonatal intensive care unit at tertiary hospital, Addis Ababa, Ethiopia: Retrospective follow up study. Frontiers in Pediatrics, 10, 913583. https://doi.org/10.3389/fped.2022.913583

34.

Mengesha

H. G.

Wuneh

A. D.

Lerebo

W. T.

Tekle

T. H.

(2016). Survival of neonates and predictors of their mortality in Tigray region, Northern Ethiopia: Prospective cohort study. BMC Pregnancy and Childbirth, 16(1), 1–13. https://doi.org/10.1186/s12884-016-0994-9

35.

Mengistu

B. A.

Yismaw

A. E.

Azene

Z. N.

Mihret

M. S.

(2020). Incidence and predictors of neonatal mortality among neonates admitted in Amhara regional state referral hospitals, Ethiopia: Prospective follow up study. BMC Pediatrics, 20(1), 1–14. https://doi.org/10.1186/s12887-020-02031-x

36.

Ministry of Health Ethiopia. (2024). National Antenatal Care Guideline.

37.

Moges

Mekango

D. E.

Astatkie

(2021). Mortality and its predictors among neonates admitted to a Neonatal Intensive Care Unit in Hadiya Zone, Southern Ethiopia: A retrospective cohort study. Journal of Pediatrics and Neonatology, 2(1), 10–16. https://doi.org/10.5455/jpn.2030-10-10.rh12345

38.

Mohamed

H. A.

Shiferaw

Roble

A. K.

Kure

M. A.

(2022). Neonatal mortality and associated factors among neonates admitted to neonatal intensive care unit at public hospitals of Somali Regional State, Eastern Ethiopia: A multicenter retrospective analysis. PLoS One, 17(5), e0268648. https://doi.org/10.1371/journal.pone.0268648

39.

Mosley

W. H.

Chen

L. C.

(2003). An analythical framework for the study of child survival in developing countries. Bulletin of the World Health Organization, 81, 140–145. https://doi.org/10.2471/BLT.03.010140

40.

Mutz-Dehbalaie

Scheier

Jerabek-Klestil

Brantner

Windbichler

G. H.

Leitner

Egle

Ramoni

Oberaigner

(2014). Perinatal mortality and advanced maternal age. Gynecologic and Obstetric Investigation, 77(1), 50–57. https://doi.org/10.1159/000357168

41.

Orsido

T. T.

Asseffa

N. A.

Berheto

T. M.

(2019). Predictors of Neonatal mortality in Neonatal intensive care unit at referral Hospital in Southern Ethiopia: A retrospective cohort study. BMC Pregnancy and Childbirth, 19(1), 1–9. https://doi.org/10.1186/s12884-019-2227-5

42.

Park

J. H.

Chang

Y. S.

Ahn

S. Y.

Sung

S. I.

Park

W. S.

(2018). Predicting mortality in extremely low birth weight infants: Comparison between gestational age, birth weight, Apgar score, CRIB II score, initial and lowest serum albumin levels. PLoS One, 13(2), e0192232. https://doi.org/10.1371/journal.pone.0192232

43.

Reyes

J. L.

Ramírez

R. P.

Ramos

L. L.

Ruiz

L. G.

Vázquez

E. B.

Patino

V. R.

(2018). Neonatal mortality and associated factors in newborn infants admitted to a Neonatal Care Unit. Archivos Argentinos de Pediatría, 116(1), 42–48. https://doi.org/10.5546/aap.2018.eng.42

44.

Roro

E. M.

Tumtu

M. I.

Gebre

D. S.

(2019). Predictors, causes, and trends of neonatal mortality at Nekemte Referral Hospital, east Wollega Zone, western Ethiopia (2010–2014). Retrospective cohort study. PLoS One, 14(10), e0221513. https://doi.org/10.1371/journal.pone.0221513

45.

Shreffler

Huecker

M. R.

(2020). Survival analysis.

46.

Taye

Kebede

Tsegaw

Ketema

(2024). Predictors of neonatal mortality among neonates admitted to the neonatal intensive care unit at Hawassa University Comprehensive Specialized Hospital, Sidama regional state, Ethiopia. BMC Pediatrics, 24(1), 237. https://doi.org/10.1186/s12887-024-04689-z

47.

Tebeje

T. M.

Seifu

B. L.

Asgedom

Y. S.

Mare

K. U.

Asmare

Z. A.

Asebe

H. A.

Shibeshi

A. H.

Lombebo

A. A.

Sabo

K. G.

Fente

B. M.

Kase

B. F.

(2025). Trends and determinants of early neonatal mortality in Ethiopia: Evidence from the Ethiopian demographic and health survey data. BMC Pediatrics, 25(1), 704. https://doi.org/10.1186/s12887-025-06022-8

48.

Tekeba

Tamir

T. T.

Workneh

B. S.

Zegeye

A. F.

Gonete

A. T.

Alemu

T. G.

Wassie

Kassie

A. T.

Ali

M. S.

Mekonen

E. G.

(2024). Early neonatal mortality and determinants in Ethiopia: Multilevel analysis of Ethiopian demographic and health survey, 2019. BMC Pediatrics, 24(1), 558. https://doi.org/10.1186/s12887-024-05027-z

49.

Tekeba

Techane

M. A.

Workneh

B. S.

Zegeye

A. F.

Gonete

A. T.

Alemu

T. G.

Wassie

Kassie

A. T.

Ali

M. S.

Mekonen

E. G.

Tamir

T. T.

(2024). Mortality of neonates born to mothers of extreme reproductive age in Ethiopia; multilevel mixed effect analysis of Ethiopian demographic and health survey data of 2016. Frontiers in Pediatrics, 12, 1390952. https://doi.org/10.3389/fped.2024.1390952

50.

Thomas

Demena

Hawulte

Eyeberu

Heluf

Tamiru

(2021). Neonatal mortality and associated factors among neonates admitted to the Neonatal Intensive Care Unit of Dil Chora Referral Hospital, Dire Dawa City, Ethiopia, 2021: A facility-based study. Frontiers in Pediatrics, 9, 578901. https://doi.org/10.3389/fped.2021.578901

51.

Tolossa

Wakuma

Mengist

Fetensa

Mulisa

Ayala

Feyisa

Fekadu

Jara

Bikila

Getahun

(2022). Survival status and predictors of neonatal mortality among neonates admitted to Neonatal Intensive care Unit (NICU) of Wollega University referral hospital (WURH) and Nekemte Specialized hospital, Western Ethiopia: A prospective cohort study. PLoS One, 17(7), e0268744. https://doi.org/10.1371/journal.pone.0268744

52.

Toma

T. M.

Merga

Dube

(2021). Survival status and predictors of mortality among preterm neonates in Southwest Ethiopia: A retrospective cohort study.

53.

Woday

Muluneh

St Denis

(2019). Birth asphyxia and its associated factors among newborns in public hospital, northeast Amhara, Ethiopia. PLoS One, 14(12), e0226891. https://doi.org/10.1371/journal.pone.0226891

54.

Wondwossen

Abrehet

Mache

(2015). Magnitude and associated factors of late booking for antenatal care in public health centers of Adigrat town, Tigray, Ethiopia. Clinics in Mother and Child Health, 12(1), 1000171. https://doi.org/10.4172/2090-7214.1000171

55.

World Health Organization. (2017). Reaching the every newborn national 2020 milestones: country progress, plans and moving forward.

56.

World Health Organization. (2024). Newborn mortality. Accessed November 09, 2025, from https://www.who.int/news-room/fact-sheets/detail/newborn-mortality

57.

Yismaw

A. E.

Gelagay

A. A.

Sisay

M. M.

(2019). Survival and predictors among preterm neonates admitted at University of Gondar comprehensive specialized hospital neonatal intensive care unit, Northwest Ethiopia. Italian Journal of Pediatrics, 45(1), 1–11. https://doi.org/10.1186/s13052-018-0597-3

58.

Zekarias

Shemsu

Abdulkadr

A. A.

Aychiluhm

S. B.

(2024). Predictors of neonatal mortality among neonates admitted to NICU at Dubti General Hospital, Northeast Ethiopia. Heliyon, 10(12), e32924. https://doi.org/10.1016/j.heliyon.2024.e32924

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