Magnitude of Neonatal Admission Diagnosis and Associated Factors at Selected Hospitals in Wollo, Northeast Ethiopia

Background

Millions of babies are born each year, and a significant number of them are admitted to hospitals for various reasons.¹ Neonatal admission generally refers to the admission of a newborn <29 days old to a health facility for medical care.² Neonatal intensive care units (NICUs) provide life support to newborns; however, admission to an NICU entails risk for families and their admitted infants, including high costs.^3,4 Admission to the NICU interrupts the mother–infant bonding and establishment of breastfeeding.^5,6 Neonatal mortality and newborn compromise is a major concern in sub-Saharan Africa, and their rates reflect a nation’s socioeconomic status, efficiency, and effectiveness of health-care services.⁷ Ethiopia is one of the 10 countries where newborn mortality and morbidity are the highest.¹

The reasons for entry into NICUs are the result of different morbidities. Neonatal morbidities include hypothermia, sepsis, prematurity, polycythemia hypoglycemia, meconium aspiration syndrome, perinatal asphyxia, congenital anomaly, and others.^8–10 Developmental delay following neonatal morbidity leads to high health-care costs and intense use of medical resources.¹¹

Many of the conditions that lead to early neonatal mortality and morbidity in low-income countries can be avoided with relatively simple and cost-effective interventions like contraception, vaccination of pregnant women, hygienic delivery in a hospital, training health-care workers in resuscitation practices, simplified algorithms that allow for early detection of perinatal infections, and early initiation of breastfeeding and skin-to-skin care.¹²

If not recognized and managed quickly, morbidities can escalate to serious complications, such as impaired vision and movement, learning, or behavior problems, which all have devastating effects on long-term developmental outcome and at severe levels lead to mortality.^11,13 Several strategies have been launched to enhance neonatal survival and promotion of health and well-being, such as essential newborn-care services and reproductive, maternal, newborn, and child health in universal health coverage.^14,15

Neonatal admission can be influenced by numerous factors: maternal sociodemographic characteristics (age, marital status, residence, educational status, monthly income),^16–18 neonatal characteristics (sex, appearance, pulse, grimace, activity, and respiration [APGAR]),^19–21 Maternal behavioral and medical related conditions (HIV/AIDS, diabetes mellitus, malaria, anemia, alcohol intake status),^22–26 and gynecological and obstetric factors (premature rupture of membrane, prolonged labor, mode of delivery, urinary tract infection, antenatal care).^27–31

While our country has implemented different policies to mitigate neonatal mortality, it remains tilted. According to the Ethiopian Demographic and Health Survey 2016, neonatal mortality was 29 deaths per 1000 live births, but after 3 years it had declined to 30.^32,33 Ethiopia has undertaken to reduce the number of neonatal deaths from its present level to 12 per 1000 live births. Therefore, this study aimed to assess the magnitude of neonatal admission diagnosis and associated factors at selected hospitals in Wollo, northeast Ethiopia in 2022.

Methods

Study Area, Study Design, and Participants

A hospital-based cross-sectional study was conducted in selected South Wollo and North Wollo hospitals in Amhara Regional State from May 7 to August 10, 2022. Four governmental hospitals were selected according to their case flow after reviewing their 45 days of registration: Dessie Comprehensive Specialized Hospital (DCSH), Woldia Comprehensive Specialized Hospital (WCSH), Kombolcha General Hospital (KGH), and Kobo Primary Hospital (KPH).

Inclusion and Exclusion Criteria

Mother–neonate pairs that were selected by systematic random sampling were included in the study. Mother–neonate pairs who were admitted to NICUs in the selected hospitals were included All neonates who were admitted to NICUs whose mothers were not available were excluded, as shown in Figure 1.

Figure 1 Geographical areas of selected study hospitals.

Sample Size and Sampling Procedure

The sample size was calculated by a single-population proportion formula based on the prevalence of neonatal sepsis in Nepal (50%),³⁴ 95% confidence level, and 5% margin of error. After factoring in a 10% nonresponse rate, the final sample for this study was 422. Among governmental hospitals in North Wollo and South Wollo, four hospitals were selected — DCSH, WCSH, KGH, and KPH — based on case flows after reviewing 45 days of admission. The calculated sample size was proportionately allocated based on the previous number of neonates admitted per 45 days in each hospital. Again, the sampling interval was determined by dividing the average number of neonates admitted per 45 days by the number of cases that were included in the study for each hospital, and then the study participants were selected by systematic random sampling after deciding on the random start randomly for each selected hospital, as illustrated in Figure 2.

Figure 2 Schematic diagram of sampling procedure. Abbreviations: NICU, neonatal intensive care unit; DCSH, Dessie Comprehensive Specialized Hospital; WCSH, Woldia Comprehensive Specialized Hospital; KGH, Kombolcha General Hospital; KPH, Kobo Primary Hospital.

Data-Collection Procedures and Measurements

Data were collected through an interviewer-administered structured Amharic version questionnaire and data-extraction checklist to extract data from charts developed from previous literature and guidelines. Maternal characteristics were asked about, ensuring the mothers’ privacy and confidentiality, after they had finished their contact with the health professional. Some of the questionnaires were also filled by referring to neonate folders/cards, eg, birth weight and APGAR score. Two BSc public health officer supervisors and four BSc nurses who are currently employed in the same health facility were employed as data collectors. Every incomplete questionnaire was sent back to the corresponding data collector for checkup.

Neonatal admission refers to the admission of the newborn <29 days old to a health facility for medical care.² Neonates were considered to have sepsis if they had a clinical syndrome of bacteremia with systemic signs and symptoms of infection in the first 4 weeks of life. The neonate may present with any of the systemic manifestations of danger signs: not feeding well, convulsions, drowsy or unconscious, movement only when stimulated or no movement at all, fast breathing [60 breaths/min), grunting, severe inward drawing of chest, raised temperature >38°C, hypothermia <35.5°C, central cyanosis, severe jaundice, severe abdominal distension, or localizing signs of infection. Signs of pneumonia include many or severe skin pustules, bulging fontanel, painful joints, joint swelling, and reduced movement.³⁵ A neonate is said to be hypoglycemic when blood glucose is <47 mg/dL.³⁵ A newborn is considered premature when he/she was delivered before a gestational age of 37 weeks (259 days) starting from the last normal menstrual period. For those mothers who did not know their last normal menstrual period, early ultrasound and new Ballard score were employed.^36,37 A neonate is considered to have low birth weight (LBW) at <2500 grams, regardless of gestational age.^36,38

Statistical Analysis

The data were entered into EpiData version 3.1 and analyzed using Stata version 14. Descriptive analyses, such as frequencies and percentages, were detemined and discriminant analyses employed to identify the predictors of neonatal mortality. Then, after bivariate binary logistic regression analysis, those variables with P<0.25 were included in a multivariate logistic regression model to control for all possible confounders and to identify predictors of the outcome variable. Hosmer and Lemeshow goodness of fit and standard error were used to check the model goodness of the test and multicollinearity, respectively. In the final model, those variables with P<0.05 were considered statistically significant. AORs and 95% CI were estimated to measure the strength and direction of association.

Ethics Approval

This research was carried out in line with the Declaration of Helsinki. Data collection was carried out after obtaining ethics approval from the ethics review committee of Wollo University College of Medicine and Health Sciences (reference CMHS1473/2014). Participants <18 years of age were approved by the ethics committee to provide informed consent on their own behalf. In addition, official letters of cooperation were submitted to each selected hospital. Verbal informed consent was obtained from each respondent prior to enrollment and was considered acceptable and approved by the ethics committee. Each participant was informed about the aim and importance of the study. Anyone who was not willing to participate in the study was not forced to do so and had the full right to refuse or even withdraw from the study. Privacy of the participants and confidentiality of the information they gave was secured at all levels. The information was used only for the purposes of the study.

Results

Sociodemographic Characteristics of Mothers

In sum, 422 mother–neonate pairs participated in this study for a response rate of 100%. The mean age of the mothers was 27±4.76 years, 396 (93.84%) were married, 62.3% (263) resided in an urban setting, 128 (30.33%) had had no formal education, and 206 (48.82%) were housewives, as indicated in Table 1. Of the 422 admitted neonates, 54.74% (231) were female with a mean age of four days, 43.27% (90) had an APGAR score <7 at 1 minute after birth and 70.67% (147) had an APGAR score ≥7 at five minutes after birth. More than half (58.25%, 240) had normal birth weight, as shown in Table 2.

Table 1 Sociodemographic characteristics of mothers (n=422)

Table 2 Characteristics of admitted neonates (n=422)

Medical and Behavioral Factors of Mothers

Of the participants, 49 (11.61%) of the mothers were anemic during their pregnancy period while they were pregnant, five mothers were HIV/AIDS-positive, and six were known diabetes mellitus clients. Nineteen (4.5%) drank alcohol and 26 (6.16%) chewed khat during their pregnancy. A total of 406 (96.21%) did not read a newspaper at least once per week, 357 (84.6%) did not listen to the radio at least once per week, and 253 (59.95%) watched TV at least once per week, as illustrated in Table 3.

Table 3 Medical and behavioral data of mothers (n=422)

Obstetric and Gynecological Factors

Of all study participants, 238 (56.4%) mothers were multiparous, 403 (95.5%) mothers had had antenatal care visits at least once, 30 (7.11%) were diagnosed with antepartum hemorrhage (APH), and 70 (17.3%) had premature rupture of membrane. In total, 403 (95.5%) mothers delivered in a health institution and 275 (65.17%) of the neonates were delivered through SVD, 53 (12.05%) via instrumental means (either vacuum or forceps), and the remaining 94 (22.27%) by cesarean section, as indicated in Table 4.

Table 4 Obstetric and gynecological factors (n=422)

Reasons for NICU Admission

The most common reasons for neonatal admission to the NICU were neonatal sepsis (53.8%), LBW (36.9%), hypothermia (32.3%), respiratory distress (26.9%), prematurity (24.2%), asphyxia (20.1%), congenital malformation (12.9%), anemia (12.4%), hypoglycemia (9.7%), jaundice (9.5%), meconium aspiration syndrome (9.2%), and hypoxic–ischemic encephalopathy/encephalopathy (3.2%). Based on discriminant analysis results, LBW (P=0.001), prematurity (P=0.001), neonatal sepsis (P=0.001), and hypoglycemia (P=0.008) were predictors of neonatal mortality.

Factors Associated with NICU Admission

Low Birth Weight

Following bivariate logistic regression, 11 variables with P<0.25 were considered in multivariate analysis. The results showed that urinary tract infection, history of abortion, and birth type were had statistically significant associations with LBW. Those mothers who had had a UTI during pregnancy period were 2.22 times as likely to deliver an LBW neonate as mothers who had not. Mothers with a history of abortion were 1.95 times as likely to deliver an LBW neonate as mothers with no history of abortion. Mothers who had a twin gestation were 6.34 times as likely to deliver an LBW neonate as mothers who had a single gestation, as shown in Table 5.

Table 5 Bivariate and multivariate binary logistic regression for mothers of low-birth-weight neonates

Neonatal Sepsis

Following bivariate logistic regression, 11 variables with P<0.25 were considered in multivariatle analysis. The results showed that PROM, history of abortion, and mode of delivery have statistically significant associations with neonatal sepsis. Neonates delivered from PROM mothers were 2.87 times as likely to develop sepsis as their counterparts. Neonates delivered from mothers who had had at least one abortion were 2.36 times as likely to develop sepsis as their counterparts. The odds of developing sepsis for neonates who were delivered via instrumental delivery were 5.25 times those of neonates who were delivered by spontaneous vaginal delivery, as illustrated in Table 6.

Table 6 Bivariate and multivariate binary logistic regression for neonatal sepsis

Prematurity

Multivariate analysis result showed that sex, pregnancy-induced hypertension (PIH), PROM, and APH, were found to have statistically significant associations with prematurity. Male neonates were 2.78 times as likely to be premature as female neonates. Mothers who were hypertensive during pregnancy were 2.73 times as likely to deliver a premature baby as their counterparts. Mothers who encountered APH were 3.2 times as likely to have premature neonates as mothers who had no APH. Mothers who had PROM were 2.8 times as likely to deliver premature neonates as their counterparts, as indicated in Table 7.

Table 7 Bivariate and multivariate binary logistic regression for premature birth

Discussion

Our study aimed to identify neonatal admission diagnoses and associated factors at selected hospitals in Wollo, northeast Ethiopia. We identified LBW, prematurity, sepsis, and hypoglycemia as predictors of neonatal mortality by discriminant analysis.

Magnitude of Hypoglycemia

Our study identified hypoglycemia as the admission diagnosis in 9.7% of patients. This is consistent with the reported incidence in Jerusalem, Israel of 12.1%,³⁹ but is higher than that found in a Ugandan study of 2.2%.⁴⁰ This rate is less than that identified in a study conducted at St Paul’s Hospital Millennium Medical College, Ethiopia of 25%.⁴¹ These differences may be due to study design, diagnostic modality, patient populations, lactation education and support, and effectiveness in breastfeeding initiation.

Magnitude of Prematurity and Factors Influencing It

Prematurity accounted for 24.2% of admissions in the current study. Male sex, PIH, PROM and APH were significantly associated with prematurity. Our study’s prevalence of preterm birth is consistent with a previous study conducted in Pakistan⁴² of 27.9%, but is higher than studies conducted in Nigeria (19%)⁴³ and Jimma (0.2%).¹⁹ It is lower than a previous study conducted in an Addis Ababa tertiary care hospital, St Paul’s Hospital Millennium Medical College, which was found to be 36.6%.⁴⁴ Differences in reported rates of hospital admissions due to prematurity are likely due to hospital setting and patient population served, as well as newborn assessment using standardized tools, such as Ballard score.⁴⁵

In the current study, we found that male newborns were 2.8 times as likely to be born prematurely as females. This is consistent with studies conducted in France and the Netherlands,^20,21 but differs from a study conducted at Jimma University Specialized Hospital, Ethiopia.¹⁹ The etiopathogenesis of higher rates of prematurity in male fetuses is multifactorial and could be related to intrauterine growth rates or hormonal differences between sexes.^46,47 Birthing parents who were hypertensive during the pregnancy were 2.7 times as likely to deliver prematurely as those who were not hypertensive. This was also found in a study conducted in China.⁴⁸ This may be related to PIH-associated uteroplacental insufficiency and higher rates of placental abruption.⁴⁹

Antepartum hemorrhage was associated with a 3.2-fold increased risk of prematurity. This finding is consistent with studies from Israel and Japan.^50,51 This association is plausible, since profuse, life-threatening vaginal bleeding is an indication for immediate delivery.⁵² Premature rupture of membranes in our study was associated with a 2.7-fold increased risk of prematurity, a finding consistent with previous studies conducted in Kenya, Nigeria, and India.^53–55 Whether this is the result of an inflammatory or infectious process is beyond the scope of the present study, but has been reviewed previously.

Magnitude of Low Birth Weight and Factors Influencing It

LBW in our study population was 36.9%. Maternal factors including urinary tract infection and previous abortion as well as mode of delivery were significantly associated with LBW. Rates of LBW were lower than in previous Ethiopian studies conducted in the northwest and southwestern regions: 14.6% and 11.0%, respectively.^56,57 These differences are multifactorial, but may be largely explained by referral patterns to the specialty hospital.

In the current study, the odds of delivering an LBW newborn were significantly higher in twin versus singleton gestation. This finding is in line with studies conducted in sub-Saharan Africa and Nigeria.^58,59 In addition, we found that maternal urinary tract infection during pregnancy was associated with LBW, a finding also noted in studies conducted in the USA, Dumlupinar University in Turkey, and Israel.^60–63Gravidas with at least one previous abortion doubles the risk risk of LBW. This finding is supported by studies conducted in Denmark, Hawassa, and a systematic review.^64–66 There are many contributing factors that may be related to prior cervical or uterine injury⁶⁷ and/or psychological stress, depression, and stigmatization. Those factors could contribute to decreased dietary diversity and higher risk of LBW delivery.^68,69

Magnitude of Neonatal Sepsis and Factors Influencing It

The incidence of neonatal sepsis in our study population was 53.8%, with PROM, prior abortion, and mode of delivery found to be significantly associated. The prevalence of sepsis correlates with a study conducted in Nepal,³⁴ but is higher than that found in a Pakistan study⁴² and a South African study — 20%, 21%, respectively⁹ — and lower than the incidence of 68% found in Gondar.⁸ The variance in reported prevalence of neonatal sepsis could be explained by patient characteristics, referral patterns, and infection-control practices.

Premature rupture of membranes was associated with threefold increased odds of developing sepsis, a finding consistent with studies in Jordan, Pakistan, and some studies in Ethiopia.^66,70–73 This finding is plausible given the increased risk of chorioamnionitis and sepsis from ascending infection.^52,74 Prior abortion was associated with double the odds of sepsis, and mode of delivery, particularly with the use of instruments (vacuum or forceps), showed five times the odds of neonatal sepsis. These findings are consistent with previous studies conducted in Sri Lanka, India, and Ethiopia,^75–77 possibly related to fetal scalp/head trauma and less than optimal infection-control measures in place.⁷⁸

Conclusion

Our study of patients admitted to hospitals in Wollo, northeast Ethiopia identified LBW, prematurity, sepsis, and hypoglycemia as predictors of neonatal mortality by discriminant analysis. Half of the newborns were septic on admission and a third were LBW. Future studies should examine interventions to reduce risks of sepsis and LBW.

Strengths and Limitations

Strengths

Predictors of neonatal mortality addressed after implementing discriminant analysis and this research address both maternal and neonatal factors using primary and secondary data. This will be an input for planning and guiding neonatal investments in the catchment area.

Limitations

The results may not be representative of all newborns in South Wollo and North Wollo, due to the study being hospital-based and cross-sectional. Additionally, the subjective nature of diagnosis is another limitation, and lastly it shares the drawbacks of cross-sectional design.