The effect of birth weight on time to neonatal mortality in Silte Zone, Central Ethiopia: A survival analysis

doi:10.21203/rs.3.rs-4355903/v1

Download PDF

Article

The effect of birth weight on time to neonatal mortality in Silte Zone, Central Ethiopia: A survival analysis

https://doi.org/10.21203/rs.3.rs-4355903/v1

This work is licensed under a CC BY 4.0 License

Version 1

posted

You are reading this latest preprint version

Introduction:

Globally, 2.4 million children died in the first month of life by 2019, approximately 6,700 neonatal deaths every day. Ethiopia is 4th leading country among the top 10 countries with the highest number of neonatal death. On the other hand, prospective studies regarding neonatal mortality are scarce in Ethiopia in general and the central Ethiopia part in particular which necessitates assessing survival status and predictors of mortality among neonates to design evidence-based locally specific intervention strategies.

Methods

An institution based prospective cohort study design was employed from May 01 to July 30, 2022. Data were collected from term neonates enrolled by their order of health facility visit then followed by data collectors in their home. Data were analyzed using STATA version 14.1. Neonatal survival was presented using Kaplan-Meyers survival curve. Crude and adjusted association was evaluated using cox-proportional hazard model and presented with 95% confidence interval and P value < 0.05 was used to declare statistical significance.

Result

1080 term neonates were followed for a total of 27643.6 neonatal day. The study showed a 95% cumulative probability of surviving the neonatal period. The incidence rate of neonatal death was 2.02 per 1000 neonatal days. Maternal history of neonatal death (AHR = 4.03; 95%CI: 2.28–9.52), complication during pregnancy (AHR = 3.08; 95%CI: 1.12–8.25), female sex (AHR = 0.45; 95%CI: 0.25–0.84), birth weight (AHR = 0.27; 95%CI: 0.11–0.63), and low and intermediate Apgar score (AHR = 3.11; 95%CI: 1.23–7.82 and AHR = 5.34; 95%CI: 1.63–17.51 respectively) were independent predictors of neonatal death.

Conclusion

It has been noted that neonatal mortality is higher than results from national and other study areas and thus needs strict attention, and interventions targeting both pre and post-natal periods. Promoting maternal nutrition thereby normal birth weight of the newborn increases the survival status of neonates.

Health sciences/Health care/Paediatrics

Health sciences/Health care/Nutrition

Birth weight

Neonatal mortality

Survival status

Silte Zone

Central Ethiopia

The neonatal period, which starts at birth and ends at 28 completed days of life, is recognized as the riskiest time in newborns. The World Health Organization(WHO) defines Neonatal Mortality(NM) as “deaths among live births during the first 28 completed days of life”, further classified as early neonatal deaths, between 0 and 7 completed days of life, and late neonatal deaths, that is between day 7 to 28 (1, 2).

The complex relationship between maternal, newborn, and healthcare-related conditions play a role in increasing the likelihood of Neonatal mortality. A higher proportion of stillbirth, maternal, and neonatal mortality occur because of poor care during pregnancy and delivery. (3). Hence neonatal mortality rate (NMR) is often used as a standard index for the evaluation of health, education, social systems, nutritional status, and health programs for neonates (4). According to WHO causes of most neonatal deaths were preterm birth, intra-partum-related complications (birth asphyxia or lack of breathing at birth), infections, and birth defects (5). Deaths resulted from preterm births (28%), intrapartum related complications (24%), and asphyxia follows sepsis (30–50%) associated deaths worldwide. Similarly, sepsis is the most common cause of neonatal death in developing countries (6, 7).

Since 1990 under-5 survival has been improving making a significant decline in deaths from 5.0 million to 2.4 million by 2019. However, Neonatal mortality decrement was slower than that of post-neonatal child mortality. Meanwhile, close to 1 million newborns die within the first 24 hours, and the first week of life is a period in which three quarters of all neonatal deaths occur, (5).

Sub-Saharan Africa, with 27 deaths per 1,000 live births, had the highest NMR in 2019, followed by Central and Southern Asia with 24 deaths per 1,000 live births (5). Preceded by India, Nigeria, and Pakistan in decreasing rank Ethiopia is the 4th leading country among the top 10 countries with the highest number of neonatal death with a total of 99 thousand newborn deaths by 2019 (8). According to the Ethiopian Demographic Health Survey (EDHS) 29 neonatal deaths per 1000 live births were documented in 2016 and later increased to 30 death per 1000 live birth in the 2019 report. Moreover, 42% of under-5 mortality in Ethiopia is attributable to neonatal deaths (9–11).

Although developing countries have been given the priority to achieve the global target of reducing neonatal death; compared to 25% of births and 50% of deaths in 2013 it is projected that sub-Saharan Africa will have 33% of births and 60% of deaths by 2030 (12, 13). On the current trend, it has been estimated that more than 60 countries will miss the Sustainable Development Goal (SDG) target of reducing NM to at least as low as 12 deaths per 1000 live births by 2030. Surprisingly, about half of these countries, which carry about 80 percent of the burden, will not reach the target even by 2050 (14).

To alleviate the problem and achieve the goal, in line with WHO global strategy Ethiopia has endorsed The National Newborn and Child Survival Strategy, which has been part of the Health Sector Transformation Plan (HSTP-I), as well as targeted reduction of Neonatal mortality in HSTP-II (15, 16). However, despite these efforts, NMR continued to be a significant problem in Ethiopia. A better understanding of the time and proximate determinants of neonatal mortality is therefore crucial to design time-relevant intervention strategies that will contribute to reducing the burden of neonatal mortality. Thus, the current study aimed to assess the time to death of neonates and identify predictors of neonatal mortality.

Study design and setting

Institution-based prospective cohort study design was employed from May 01 to July 30, 2022 in Silte zone, which is one of the fourteen Zones in Central Ethiopia region, found 172 km away from Addis Ababa (the capital city of Ethiopia). The study was conducted in two phases, the first Institution phase and the follow-up community phase. The institution phase was conducted in four Hospitals (Werabe Comprhensive, Alemgebeya, Kibet, and Tora Hospitals) and two Health centers under each Hospital. The community follow-up phase was then conducted on deliveries attended in those institutions

Population

Source population: - All term deliveries in Silte zone

Study population: - The study populations were sampled term pregnant women and their respective neonates available during the data collection period.

Inclusion criteria: - Term pregnant mothers who were residing in the catchment for more than six month with their Neonates, who gave live birth in the study area from May 01 to July 30, 2022 were included in the study.

Exclusion criteria: - Mothers who were unable to hear or speak and mothers with psychiatric illness were excluded from the study.

Sample size and Sampling technique

The sample size was calculated with double population proportion using STATA version 14.1 using event proportion of 41 death per 1000 live birth, Hazard Ratio(HR) of 2.8 for post-natal care, 2.4% withdrawal and 1.5 design effect. The final sample size was 1112 (17). All hospitals found in the zone were included then two Health centers under each hospital were selected using simple random sampling method. Consecutive samples of term deliveries were taken according to their order of delivery. The community follow up phase was then conducted on deliveries attended in those institutions.

Data collection tool and follow-up procedures

Data were collected prospectively using pre-tested interviewer-administered structured questionnaires were adapted from different literatures. The indicators for the wealth index are adapted from the Ethiopian Demographic and Health Survey (EDHS) (18). Indicators for neonatal care practices are adapted from the World Health Organization (WHO) minimum neonatal care packages (19). Moreover, the questionnaire contains pregnancy, ANC, and delivery-related questions. All the questionnaires were prepared in English, then translated into Amharic and used to collect the data. Multi-lingual midwives who can speak Siltigna and Amharic, with previous experience in similar areas and supervisors participated in data collection. Data were collected in three phases. Data collectors obtain consent and perform interviews on socio-demographic variables, about pregnancy, ANC, delivery and birth outcome during the initial visit. Then neonatal morbidity, postnatal care, and other relevant histories including survival status were obtained on weeks 1, and 4 of a home visit.

Study variables

Outcome variable

Survival status with an event of interest being neonatal death, that is the death of a neonate within 28 days of life according to the report of the mother who participated in the study, otherwise, it is censored or survival (17).

Predictor variables

Socio-demographic and economic factors

place of residence, marital status, education status of mother, wealth index, and occupational status of the mother and father.

Maternal factors

age at childbirth, gravidity, maternal complication during pregnancy delivery and immediate post-partum, ANC visit, place and type of delivery, postnatal care.

Neonatal factors

birth size, birth order, initiation of exclusive breast feeding (EBF) and neonatal complication like tachypnea, fever, hypothermia, and Apgar score.

Operational definition

Term pregnancy is a pregnancy between 37 completed weeks up 42 completed weeks of gestation (17).

Birth weight is the recorded weight of the newborn in gram immediately after birth which is then categorized in to less than 2500gm, 2500 to 4000gm and greater than 4000gm (17).

Maternal complication:- mother with one or more complications like prolonged labour, excessive bleeding before, during, or after delivery, diagnosed pre-eclampsia/ eclampsia, the premature rapture of a membrane (20).

Apgar score

- the score was measured in the 1st minute after birth and classified in to low (1–3), intermediate (4–6), and high (7–10) (32).

Data quality assurance

Data quality assurance was made through careful translation and back translation of the data collection tool. A two-day training on an instrument, about data collection and supervision was given for data collectors and supervisors by the principal investigator. A week before actual data collection pretesting of the tool was done on 10% of the sample size out of the woredas selected for this study. Data were checked for completeness during the actual data collection period daily and before entry then double data entry was used to check consistency.

Data processing and analysis

Data were entered into Epi-data version 3.1, and then transported to STATA version 14 to be coded, cleaned, and analyzed. Variables were described using mean with standard deviation (SD) or median with Inter quartile range (IQR) for continuous data, and frequency with proportion for categorical data accordingly. Kaplan–Meier survival curve was used to show the pattern of neonatal death in 28 days. The neonatal outcome variable was examined against all predictor variables using bivariable analysis and those with p value ≤ 0.25 were considered to be a candidate for multivariable analysis. Cox proportional hazard regression model was fitted to see independent and adjusted relationships of different predictors with neonates’ survival. Mortality risk was presented with a hazard ratio and 95% confidence interval. A P-value less than 0.05 was considered to declare statistical significance. Multicollinearity was considered presented for VIF greater than 10 before interpreting the final output. Model fitness was checked by plotting a curve of –ln[-ln(survival probability)] against ln(survival time) as well as the global goodness of fit test.

Ethics approval

Ethical clearance (Ref. No. ወራ/ዩ/ም/ህ/ዳ/1/57/14) was obtained from Werabe University Ethical Review Board (ERB). The ethical clearance was then submitted to the Silte zone health office to get permission. Following this, the selected samples were contacted with the assigned person; assent for anthropometric, vital sign and other data of newborns, and a written informed consent for maternal related data from each participant/ mothers/ caregivers were obtained after detailed information was given regarding the research objectives, data collection methods, and the right to give, deny, and withdraw from the interview and/or from the study at any time. All methods were performed in accordance with the relevant guidelines and regulations.

Participants characteristics

In this study, 1112 term deliveries were planned to be included and followed up to 28 days. Initially, 10 refused to participate and 1102 were included in the study. From this 22 questionnaires were incomplete and discarded from the analysis. (See Fig. 1 below)

Socio-demographic characteristics

The mean ± SD maternal age at the current birth of respondents was 26.8 ± 4.9 years with the majority of them (91.4%) between 20 and 35 years. Around 39% of them were in primary school level of education. Moreover, 6.4% of mothers were employed in work that could generate an income. Around half of the fathers were farmers, and around 26% fell in the 4th quartile wealth category. (See Table 1 below)

Table 1

Socio-demographic characteristics of mothers participated in survival status and predictors of mortality among neonates in Silte zone Central Ethiopia, 2022
Variable	Category	Frequency	Percent
Maternal age at current birth	< 20	49	4.5
	20–35	987	91.4
	> 35	44	4.1
Marital status	Single	49	4.5
	Married and/or live with a partner	1008	93.3
	Widowed/ divorced	23	2.2
Maternal educational level	No formal education	468	33.3
	Primary education	419	38.8
	Secondary and preparatory education	129	11.9
	Higher education	64	5.9
Maternal occupation	Housewife	821	76.0
	Farmer	138	12.8
	Employed	69	6.4
	Self-employee	52	4.8
Father occupation	Farmer	534	49.4
	Employed	261	24.2
	Self-employee	285	26.4
Wealth index	1st quartile	276	25.6
	2nd quartile	263	24.4
	3rd quartile	256	23.7
	4th quartile	285	26.4

Pregnancy related characteristics

Among the total respondents, 929 (86%) were multi-gravida women. Among the multi-gravida women their previous pregnancy outcome showed 127(13.7%) of them had a previous abortions while 61(6.6%) had a previous neonatal loss and 84(9.1%) had stillbirth. In this study 28(2.6%), 68(6.3%), and 4(0.4%) mothers were ever smokers, chewers, and alcohol drinkers of any amount in their lifetime. Among mothers who attend the ANC clinic 225 (27.9%) of them had > = 4 ANC visits, and 336 (41.8%) followed their ANC in the hospital. Seven hundred and twelve (88.4%) of mothers received at least one dose of TT in their current pregnancy while ninety percent had one or more doses of TT vaccination in their lifetime (see Table2 below)

Table 2

Pregnancy related characteristics of mothers participated in survival status and predictors of mortality among neonates in Silte zone Central Ethiopia, 2022.
Variable	Category	Frequency	Percent
Attend ANC clinic	Yes	804	74.4
	No	276	25.6
Place of ANC care	Hospital	336	41.8
	Health center	369	45.9
	Health post	98	12.2
Number of ANC visits	Less than four	579	72.0
Number of ANC visits	four or more	225	28.0
Counseling services they got	Hygiene and self-care	461	57.3
	Breast feeding	491	61.1
	Child Nutrition	508	63.2
	Infant immunization	528	65.7
Received Iron tablet	Yes	663	82.5
Received Iron tablet	No	141	17.5
Received TT vaccine in the current pregnancy	Yes	712	88.4
Received TT vaccine in the current pregnancy	No	92	11.6
Doses of TT in current	One	352	49.4
Doses of TT in current	Two or more	360	50.6
Ever received TT vaccine	Yes	982	90.9
Ever received TT vaccine	No	98	9.1
Doses of TT ever received	One	659	67.1
Doses of TT ever received	Two or more	323	32.9
MUAC	< 23cm	141	13.1
MUAC	>=23cm	939	86.9

Delivery related characteristics

Of the total participants, 149 (13.8%) deliveries had one or more delivery complications (22.1% HDP, 34.2% were multiple-gestation birth, 38.9% were PROM). About 627 (58.1%) newborns were delivered at the hospital; furthermore, 998 (92.4%) were vaginal deliveries (see Table 3 below).

Table 3

Delivery related characteristics of mothers participated in survival status and predictors of mortality among neonates in Silte zone, Central Ethiopia, 2022.
Variable	Category	Frequency	Percent
Place of delivery	Hospital	627	58.1
Place of delivery	Health center	453	41.9
Reason for visit	Self-initiated	1020	94.4
Reason for visit	Referral from other health facility	60	5.6
Social accompany	Accompanied by others	1063	98.4
Social accompany	Not accompanied by others	17	1.6
Diagnosed delivery complication	Yes	149	13.8
Diagnosed delivery complication	No	931	86.2
Type of complication	HDP	33	22.1
	Prolonged labor	29	19.5
	PROM	58	38.9
	Multiple gestation	51	34.2
	Others	21	14.1
Type of delivery	Vaginal	998	92.4
	Cesarean section	82	7.6
Birth order in multiple gestation	First	34	66.7
Birth order in multiple gestation	Second or more	17	33.3

New born characteristics

Male to female birth ratio was 1:1.2. The mean birth weight was 3270 ± 494.7gram with 91.9% of them falling between 2500 to 4000gm; and the mean temperature was 36.8 ± 0.3^oc. Newborns with Apgar score of 7–10 was 96.1%, 4–6 was 1.4% while the rest are 0–3%. Twenty-six (2.4%) newborns had a congenital deformity, 990 (91.7%) started breastfeeding within 1 hr and 1024 (94.8%) get colostrum on the 1st day. From the total deliveries only 460 (42.6%), and 512(47.4%) newborns got BCG and OPV0 vaccines immediately after birth respectively. Moreover only 435 (40.3%) of them get cord ointment. (See Table4 below)

Table 4

New born characteristics of participants in survival status and predictors of mortality among neonates in Silte zone, Central Ethiopia, 2022.
Variable	Category	Frequency	Percent
Sex	Female	589	54.5
Sex	Male	491	45.5
Birth weight	< 2500gm	50	4.6
	2500-4000gm	992	91.9
	> 4000gm	38	3.5
Temperature	< 36.5 ^oc	55	5.1
Temperature	≥ 36.5 ^oc	1025	94.9
APGAR score	0–3	27	2.5
	4–6	15	1.4
	7–10	1038	96.1
Congenital deformity	Yes	26	2.4
Congenital deformity	No	1054	97.6
Resuscitated	Yes	172	15.9
Resuscitated	No	908	84.1
Received TTC	Yes	963	89.2
Received TTC	No	117	10.8
Received Vitamin K injection	Yes	873	80.8
Received Vitamin K injection	No	207	19.2
Received umbilical ointment	Yes	435	40.3
Received umbilical ointment	No	645	59.7
Received OPV0	Yes	512	47.4
Received OPV0	No	568	52.6
Received BCG	Yes	460	42.6
Received BCG	No	620	57.4
Breastfeeding initiated with in 1hr	Yes	990	91.7
Breastfeeding initiated with in 1hr	No	90	8.3
Baby get colostrum	Yes	1024	94.8
Baby get colostrum	No	56	5.2

Survival status and outcome of the follow-up

The total follow up day was 27643.6 neonatal days. From those who completed the study 56 neonates died (cumulative incidence of 52 deaths/1000 live birth) which makes a cumulative probability of surviving 28 days among neonates 95% (see Fig. 2 below). The overall incidence rate is 2.02 death per 1000 neonatal days. Twenty-five (44.6%) death occurred in the first. While forty-two (75.0%) deaths occurred in the first week the rest 14 (25.0%) died between 8–28 days. Furthermore, the cumulative hazard during the early neonatal period (days 0–7) was 0.039 while in the late neonatal period (day 8–28) was 0.014. Birth asphyxia 26 (46.4%), and neonatal infections 21 (37.5%) were the two leading causes of neonatal mortality followed by others accounting for 9 (16.1%) deaths.

Predictors of neonatal mortality

Bi-variable analysis

In the bi-variable association of survival status and socio-demographic characteristics, almost all variables except marital status, and wealth index are insignificantly associated with a p-value ≤ 0.25. Regarding pregnancy and ANC-related characteristics, history and the number of TT vaccines ever injected, previous history of neonatal death, gravidity, and presence of complication in current pregnancy or delivery, history of smoking and alcohol drinking showed crude association with neonatal death. Additionally, referral history, delivery mode, and birth order of a baby from multiple gestations have shown an association. Moreover, sex, Apgar score, resuscitation after birth, BCG vaccination immediately after birth initiation of breast-feeding within 1 hour, and getting colostrum are newborn characteristics that have a crude association at p-value ≤ 0.25 (See Table 5 below).

Table 5

Predictors of mortality among neonates in Silte zone, Central Ethiopia, 2022.
Variable	CHR (95% CI)	p-value	AHR (95% CI)	p-value
Marital status
Single/lives with no partner^⁋	1		1
Married or live with partner	0.17 (0.04, 1.82	0.172	0.37 (0.05, 2.92)	0.346
Wealth index
First quartile	2.61 (1.15, 5.94)	0.021	1.61 (0.67, 3.85)	0.285
Second quartile	1.20 (0.46, 3.11)	0.708	0.87 (0.32, 2.33)	0.779
Third quartile	2.70 (1.18, 6.18)	0.018	1.78 (0.74, 4.27)	0.196
Fourth quartile	1		1
TT vaccination history
No	1		1
Yes	0.52 (0.25, 1.06)	0.071	0.88 (0.39, 2.03)	0.773
Number of TT vaccine received
Less than two	2.12 (1.04, 4.44)	0.039	2.05 (0.90, 4.63)	0.086
Two or more	1		1
History of smoking
No	1		1
Yes	2.28 (0.71, 7.31)	0.164	2.19 (0.57, 8.48)	0.256
History of drinking alcohol
No	1		1
Yes	1.81 (0.78, 4.22)	0.171	2.00 (0.77, 5.22)	0.156
Reason for visit
Referral from other health facilities	1		1
Self—initiated	0.40 (0.18, 0.89	0.024	0.58 (0.23, 1.47)	0.255
Gravidity
Multi gravida	1		1
Primi-gravida	1.55 (0.80, 3.00)	0.191	1.37 (0.64, 2.92)	0.419
History of neonatal death
No	1		1
Yes	6.84 (3.78, 12.35)	< 0.001	4.03 (2.28, 9.52)	< 0.001**
Pregnancy complication
No	1		1
Yes	1.97 (0.84, 4.59)	0.117	1.06 (0.41, 2.74)	0.909
Diagnosed complication during delivery
No	1		1
Yes	7.48 (4.42, 12.63)	< 0.001	3.08 (1.12, 8.25)	0.029*
Delivery mode
Vaginal	1		1
Caesarian section	7.17 (4.12, 12.48)	< 0.001	1.66 (0.64, 4.33)	0.297
Birth order^⁋⁋
Second or more	1		1
First	0.39 (0.13, 1.16)	0.092	0.37 (0.10, 1.31)	0.123
Sex of the newborn
Male	1		1
Female	0.39 (0.22, 0.68)	0.001	0.45 (0.25, 0.84)	0.011*
Weight of the newborn
< 2500gm	1		1
2500-4000gm	0.28 (0.13, 0.58)	0.001	0.27 (0.11, 0.63)	0.003**
> 4000gm	0.15 (0.02, 1.21)	0.074	0.15 (0.02, 1.37)	0.092
Apgar score
0–3	11.1 (5.56, 22.18)	< 0.001	3.11 (1.23, 7.82)	0.016*
4–6	9.84 (3.89, 29.92)	< 0.001	5.34 (1.63, 17.51)	0.006*
7–10	1		1
Resuscitation received
No	1		1
Yes	1.95 (1.08, 3.51)	0.027	1.60 (0.78, 3.26)	0.196
Received BCG immediately
No	1		1
Yes	0.63 (0.36, 1.10)	0.102	0.89 (0.46, 1.72)	0.732
Started breast feeding with in 1hr
No	1		1
Yes	0.63 (0.28, 1.39)	0.249	0.87 (0.21, 3.67)	0.851
Received colostrum immediately
No	1		1
Yes	0.56 (0.22, 1.39)	0.209	1.10(0.28, 5.31)	0.825

*= p value < 0.05, **p value < 0.005

^⁋ =single is a combination of unmarried, divorced, and widowed mothers

^⁋⁋ =birth order is the order of delivery in multiple gestation deliveries

Multi-variable analysis

Predictors of neonatal mortality were assessed by fitting a cox proportional hazard model using those variables showing a crude association. All of the socio-demographic characteristics were not significantly associated with neonatal death. History of and doses of TT vaccine in lifetime was also showed to have a non-significant association in multivariable analysis.

Regarding pregnancy-related characteristics neonates born from mothers with a history of previous neonatal death were 4 times more likely to die than their counter (AHR = 4.03; 95%CI = 2.28–9.52; p < 0.001). In addition, neonates of mothers who had delivery-related complications were about three times more likely to have neonatal death than neonates delivered without delivery complications (AHR = 3.08; 95%CI = 1.12–8.25; p = 0.029). A survivor function based on presence or absence of delivery complication adjusted for sex also showed a lower survival probability among complicated deliveries than uncomplicated one throughout the neonatal period. (See Fig. 3)

Newborn characteristics were also found to be significant predictors of neonatal mortality. In this study, females were found to have 54% less hazard than males (AHR = 0.46; 95%CI = 0.25–0.84; p = 0.011). Newborn weight was also another significant predictor in which newborns in the weight category of 2500-4000gm were 73% less likely to die in the neonatal period than low birth weight (< 2500gm) newborns (AHR = 0.27; 95%CI = 0.11–0.63; p = 0.003). However, the effect of high birth weight (> 4000gm) was seen to be statistically non-significant as compared to low birth weight. Though both the Apgar score and newborn resuscitation have shown a significant bi-variable association with neonatal survival status, in an adjusted analysis only the Apgar score category was a significant predictor of neonatal mortality. Neonates whose Apgar score was between 0–3 and 4–6 are found to have 3 times (AHR = 3.11; 95%CI = 1.23–7.82; p = 0.016) and 5 times (AHR = 5.34; 95%CI = 1.63–17.51) more hazard of experiencing neonatal death respectively than newborns whose Apgar score was 7–10 (see Table 5).

Model fitness

The model fitness was checked for bi-variable and multivariable analysis by plotting a curve of –ln[-ln(survival probability)] against ln(survival time) using the global Schenfolds residual test and cox-Snellen residuals plot. The schenfolds residual test showed p-value of 0.739 which is non-significant and the cox-snellens residuals graph also follows the 45-degree hazard which shows the model is fit. (See Fig. 4 below)

The study assessed survival status and predictors of mortality among neonates. Based on the result Silte zone has a neonatal mortality rate of 52 deaths/1000 live birth. Compared to the global rate by 2019 the result from this study is higher (21). This figure is also higher than the result conducted in Kenya and South Africa (22). Moreover, this result is higher than the EDHS 2019 (11), a study conducted in Jimma zone (20) as well as Aroressa district (17). The possible reasons might be study area and design differences as well as healthcare delivery characteristics. However, this result is lower than the recent study conducted in the Tigray region (7). Though the explanation for the difference in mortality might be as mentioned above still the finding indicates our study area needs attention concerning neonatal death.

In this study 25 (44.6%), and 42 (75.0%) death occurred on the first day and first week respectively. This finding is similar to previously conducted studies by Jimma, Tigray and Aroressa (7, 17, 20). The reason might be that in developing countries majority of neonatal mortalities are related to conditions of immediate pre-partum, intra-partum and immediate newborn care practices. Moreover, the major causes of death in our study are birth asphyxia and early neonatal infections. This again clearly pointed out that neonatal survival interventions have to target the intra-partum as well as immediate and early neonatal periods furthermore Poor quality of antenatal care, delay in identification and poor management of complications during pregnancy and birth by health workers might also be possible reasons as such reasons are common in low and middle-income countries and found to determine neonatal death in previous studies (7).

In this study, the history of previous neonatal death was found to significantly predict neonatal survival. This finding is consistent with previous studies (23–25). The need for a special follow up care and screening during initial visit for pregnant mothers with previous history of neonatal death could therefore be another implication. As WHO ANC high-risk pregnancy definition don’t consider previous history of neonatal death as high risk, this study paves a way to include it into a high risk pregnancy category.

Complicated deliveries (i.e. common maternal complications during labor) are also found to predict the risk of neonatal death in this study. Similar findings were reported from previous studies (7, 20, 26). The reasons could be the low availability and quality of services including emergency obstetric services supplemented by poor recognition of mothers with complications and delayed referrals. This is supported by some studies’ findings, which indicated that high NM often occurs because of delivery and pregnancy-related complications and denotes the quality of healthcare in an area (27). Moreover, our study has also showed a higher proportion of newborns with lower Apgar scores in complicated deliveries as compared to those in non-complicated deliveries which has a clear association with asphyxia and death.

Newborn characteristics are also found to predict neonatal death. In this study, female neonates have shown lesser hazards than male neonates. This finding is similar to results from South Asia, Aroressa district and other national studies (10, 17, 28). One of the explanations for such matter could be that males are at higher risk of intrauterine growth restriction. Additionally, they are at higher risk of respiratory morbidities, and gastrointestinal infections likely due to high testosterone levels that suppress the immune system (28). Though not a direct implication our study has also found a little bit higher risk of low Apgar score in male than female newborns.

In this study low birth weight (< 2500gm) neonates are found to have a higher hazard of death than normal-weight newborns. This finding is similar with Tigray, Jimma, Aroressa and Felegehiwot studies (17, 20, 26, 29). This could be due to that low birth weight newborns are at higher risk of infection (30). Our study also showed a higher proportion of infection symptom occurrence among low birth weight than normal weight newborns.

Low Apgar scores of both 0–3 and 4–6 were significant predictors of neonatal death which increase the risk of neonatal mortality up to three and fivefold respectively. This finding is consistent with studies conducted in China, Sweden, and Arbaminch (31–33). The reason might be that a lower Apgar scores even within the normal range such as 7, 8, or 9 are strongly associated with increased risks of neonatal morbidity. Furthermore, some others also found progressively higher relative odds of infections, asphyxia-related complications, neonatal hypoglycemia, and respiratory distress with lower Apgar scores (33).

This study assessed neonatal survival status time to death and predictors of neonatal death. Based on the finding, it has been noted that neonatal mortality is higher than most of the other study areas and needs strict attention, programs, and interventions based on the found predictors. Newborns of mothers with a previous history of neonatal death, and complicated delivery are at higher risk of neonatal death. Male sex, low birth weight, and lower Apgar score are also newborn characteristics that increase the risk of neonatal mortality. Therefore, Health offices, Health professionals, other NGO’s and other stakeholders shall work in harmony targeting both pre and post-natal period factors in order to reduce neonatal mortality in Silte zone.

AHR Adjusted Hazard Ratio

CHR Crude Hazard Ratio

CI Confidence Interval

EDHS Ethiopian Demographic and Health Survey

NMR Neonatal Mortality Rate

SDG Sustainable Development Goal

WHO World Health Organization.

Contribution to the field

This study assessed neonatal survival status time to death and predictors of neonatal death. Having this it will help to design time-relevant intervention strategies that will contribute to reducing the burden of neonatal mortality. Moreover, association of current and previous neonatal death history paves a way to consider this factor as a high risk pregnancy classification criteria.

Acknowledgment

We would like to acknowledge Werabe University for its financial and technical support. Furthermore we extend our gratitude to the study participants and research teams for their invaluable contribution.

Data availability: - Data used for this study is uploaded with this manuscript.

Competing interest: - The authors have declared that they have no competing interests.

Funding: - Financial support was obtained from Werabe University.

Authors' contributions: - MJ, DB, and SK conceived the research idea, and participated in supervision, analysis, draft, and final report writing. AK, and BM participated in the analysis, report writing and review process of manuscript. All authors read and approved the final manuscript.

UNICEF. Levels_and_Trends_in_Child_Mortality. Estimates Developed by the UN Inter-agency Group for Child Mortality Estimation. 2014.
Wold Health Organization. The Global Health Observatory [Internet]. Available from: https://www.who.int/data/gho/indicator-metadata-registry/imr-details/67
Tujare T. TM. Predictors of Neonatal mortality in Neonatal intensive care unit at referral Hospital in Southern Ethiopia: a retrospective cohort study. BMC Pregnancy Child Birth. 2019;1–9.
Profit J, Gould JB, Draper D, Zupancic JA, Kowalkowski MA, Woodard L et al. Variations in definitions of mortality have little influence on neonatal intensive care unit performance ratings. J Pediatr. 2013;162(1):50–5.
World Health Organization. Children: improving survival and well-being [Internet]. 2020. p. 1–4. Available from: https://www.who.int/news-room/fact-sheets/detail/children-reducing-mortality
Agnche Z, Yeshita HY, Gonete KA. Neonatal sepsis and its associated factors among neonates admitted to neonatal intensive care units in primary hospitals in central gondar zone, northwest ethiopia, 2019. Infect Drug Resist. 2020;13:3957–67.
Mengesha HG, Wuneh AD, Lerebo WT TT. Survival of neonates and predictors of their mortality in Tigray region, Northern Ethiopia: prospective cohort study. BMC Pregnancy Childbirth. 2016;16(1):202.
World Health Organization. Newborn Mortality [Internet]. 2021. Available from: https://www.who.int/news-room/fact-sheets/detail/levels-and-trends-in-child-mortality-report-2021
Central Statistical Agency. Federal Democratic Republic of Ethiopia; Ethiopian Demographic and Health Survey 2016. 2016.
Mekonnen, Y., Tensou, B., Telake DS et al. Neonatal mortality in Ethiopia: trends and determinants. BMC Public Health. 2013;13(483).
Ethiopian Public Health Institute. Federal Democratic Republic Of Ethiopia; Ethiopia Mini Demographic and Health Survey; Key Indicators. 2019;
Liu, L., Oza, S., Hogan, D., Perin, J., Rudan, I., Lawn, J. E., Cousens, S., Mathers, C., & Black RE. Global, regional, and national causes of child mortality in 2000-13, with projections to inform post-2015 priorities: an updated systematic analysis. Lancet. 2015;385(9966):430–40.
Ndombo PK, Ekei QM, Tochie JN, Temgoua MN, Angong FTE, Ntock FN et al. A cohort analysis of neonatal hospital mortality rate and predictors of neonatal mortality in a sub-urban hospital of Cameroon. Ital J Pediatr. 2017;43(1):52.
THE WORLD BANK. Latest child mortality estimates; A press release. [Internet]. 2021. Available from: https://www.worldbank.org/en/news/press-release/2021/12/20/latest-child-mortality-estimates-reveal-world-remains-off-track-to-meeting-sustainable-development-goals
FMoH. National Newborn and Child Survival Strategy Document Brief Summary2015/16-2019/2020. 2015;
Ethiopian Ministry of Health. Health Sector Transformation Plan II (HSTP-II). Vol. 25. 2021.
Limaso, A.A., Dangisso, M.H. & Hibstu D. Neonatal survival and determinants of mortality in Aroresa district, Southern Ethiopia: a prospective cohort study. BMC Pediatr. 2020;
Ethiopian Ministry of Health. Ethiopian Demographic Health Survey. 2011.
World Health Organization. Managing programs to improve child health. 2009.
Gurmesa Tura Debelew MFA AWY. Determinants and Causes of Neonatal Mortality in Jimma Zone, Southwest Ethiopia: A Multilevel Analysis of Prospective Follow Up Study. PLoS One. 2013;1–9.
David S, Lucia H, Danzhen Y, Alkema L, Robert B, Simon C, et al. Global, regional, and national trends in under-5 mortality between 1990 and 2019 with scenario-based projections until 2030: a systematic analysis by the UN Inter-agency Group for Child Mortality Estimation. Lancet. 2022;10(2).
Masaba, B. B., & Mmusi-Phetoe RM. Neonatal Survival in Sub-Sahara: A Review of Kenya and South Africa. J Multidiscip Healthc. 2020;13:709–16.
Li, Z., Kapoor, M., Kim, R., & Subramanian S V. Association of maternal history of neonatal death with subsequent neonatal death across 56 low- and middle-income countries. Sci Rep. 2021;11(1):19919.
Avoka, J.A., Adanu, R.M., Wombeogo M et al. Maternal and neonatal characteristics that influence very early neonatal mortality in the Eastern Regional Hospital of Ghana, Koforidua: a retrospective review. BMC Res Notes. 2018;11(91).
Yirgu R, Molla M SL. Determinants of neonatal mortality in rural Northern Ethiopia: A population based nested case control study. PLoS One. 2017;12(4):e0172875.
Hayelom Gebrekirstos M, A D W, Wondwossen Terefe L, Tesfay Hailu T. Survival of neonates and predictors of their mortality in Tigray region, Northern Ethiopia: prospective cohort study. BMC Pregnancy Childbirth. 2016;
Baqui, A. H., Darmstadt, G. L., Williams, E. K., Kumar, V., Kiran, T. U., Panwar, D., Srivastava, V. K., Ahuja, R., Black, R. E., & Santosham M. Rates, timing and causes of neonatal deaths in rural India: implications for neonatal health programmes. Bull World Health Organ. 2006;84(9):706–713.
Aghai, Z.H., Goudar, S.S., Patel A et al. Gender variations in neonatal and early infant mortality in India and Pakistan: a secondary analysis from the Global Network Maternal Newborn Health Registry. Reprod Health. 2020;13(178).
Tewabe T, Mehariw Y, Negatie E YB. Neonatal mortality in the case of Felege Hiwot referral hospital, Bahir Dar, Amhara Regional State, North West Ethiopia 2016: a one year retrospective chart review. Ital J Pediatr. 2018;44(1):57.
Belachew A, Tewabe T. Neonatal sepsis and its association with birth weight and gestational age among admitted neonates in Ethiopia: systematic review and meta-analysis. BMC Pediatr [Internet]. 2020;20(1):55. Available from: https://doi.org/10.1186/s12887-020-1949-x
Samuel D, Zinabu D AB. Magnitude of Neonatal Mortality and associated factors among Neonates at Arba Minch General Hospital. Asploro J Pediatr Child Heal. 2019;1:20–8.
Mu Y, Lii M, Zhu J, Wang Y, Xing A, Liu Z, et al. Apgar score and neonatal mortality in China: an observational study from a national surveillance system. BMC Pregnancy Childbirth. 2021;21(1):47.
Razaz, N., Cnattingius, S., & Joseph KS. Association between Apgar scores of 7 to 9 and neonatal mortality and morbidity: population based cohort study of term infants in Sweden. BMJ. 2019;365:l1656.

No competing interests reported.

S1.EnglishVersionquestionnaire.docx
S1 File. English version questionnaire. (DOCX)
S2.Sourcedata.xlsx
S2 File. Data set of the study. (XLSX)

Download PDF

Version 1

posted

You are reading this latest preprint version

The effect of birth weight on time to neonatal mortality in Silte Zone, Central Ethiopia: A survival analysis

Status:

Version 1

Abstract

Introduction:

Methods

Result

Conclusion

Figures

Introduction

Methods and materials

Study design and setting

Population

Sample size and Sampling technique

Data collection tool and follow-up procedures

Study variables

Outcome variable

Predictor variables

Operational definition

Data quality assurance

Data processing and analysis

Ethics approval

Result

Participants characteristics

Socio-demographic characteristics

Pregnancy related characteristics

Delivery related characteristics

New born characteristics

Survival status and outcome of the follow-up

Predictors of neonatal mortality

Bi-variable analysis

*= p value < 0.05, **p value < 0.005

Multi-variable analysis

Model fitness

Discussion

Conclusion and recommendation

Abbreviations

Declarations

References

Additional Declarations

Supplementary Files

Status:

Version 1