Agimas et al. BMC Pediatrics(2024) 24:523
https://doi.org/10.1186/s12887-024-04998-3

BMC Pediatrics

RESEARCH

Open Access

Trend, and multivariate decompositionof perinatal mortality in Ethiopia using further
analysis of EDHS 2005–2016
Muluken Chanie Agimas1*, Demewoz Kefale2, Tigabu Kidie Tesfie1, Worku Necho3, Tigabu Munye4, Gedefaw Abeje7,
Yohannes Tesfahun5, Amare Simegn6, Amare kassaw2, Shegaw Zeleke4, Solomon Demis3 andHabtamu Shimels Hailemeskel8
Abstract
Background Perinatal mortality is a global health problem, especially in Ethiopia, which has the highest perinatal
mortality rate. Studies about perinatal mortality were conducted in Ethiopia, but which factors specifically contributeto the change in perinatal mortality across time is unknown.
Objectives To assess the trend and multivariate decomposition of perinatal mortality in Ethiopia using EDHS
2005–2016.
Methods A community-based, cross-sectional study design was used. EDHS 2005–2016 data was used, andweighting has been applied to adjust the difference in the probability of selection. Logit-based multivariate
decomposition analysis was used using STATA version 14.1. The best model was selected using the lowest AIC value,and variables were selected with a p-value less than 0.05 at 95% CI.
Result The trend of perinatal mortality in Ethiopia decreased from 37 per 1000 births in 2005 to 33 per 1000
births in 2016. About 83.3% of the decrease in perinatal mortality in the survey was attributed to the differencein the endowment (composition) of the women. Among the differences in the endowment, the difference in thecomposition of ANC visits, taking the TT vaccine, urban residence, occupation, secondary education, and birthattendant significantly decreased perinatal mortality in the last 10 years. Among the differences in coefficients, skilled
birth attendants significantly decreased perinatal mortality.
Conclusion and recommendation The perinatal mortality rate in Ethiopia has declined over time. Variables like ANC
visits, taking the TT vaccine, urban residence, occupation, secondary education, and skilled birth attendants reduce
perinatal mortality. To reduce perinatal mortality more, scaling up maternal and newborn health services has a criticalrole.
Keywords Perinatal mortality, Decomposition analysis, Trend, Ethiopia*Correspondence:
Muluken Chanie Agimas
mulukensrc12@gmail.com
Full list of author information is available at the end of the article© The Author(s) 2024. Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0
International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you
give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified thelicensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images orother third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to thematerial. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation
or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://
creativecommons.org/licenses/by-nc-nd/4.0/.

Agimas et al. BMC Pediatrics(2024) 24:523

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Fig. 1 Schematic diagram for perinatal mortality in Ethiopia Using EDHS data

Introduction
Perinatal mortality is the death of a fetus starting at 28
weeks of gestation and newborn death up to 7 days after
delivery [1, 2]. It is an indicator of the maternal and newborn health service status of a country [3]. Goals are
set by the World Health Organization and sustainable
development goals to reduce the death of newborns by
2030 to less than 12 per 1000 live births [4, 5]. Ethiopia
also shared this plan to achieve the target of reducing

neonatal mortality by 12 to 1000 newborns by improving maternal and newborn health services, such as antenatal care utilization, iron supplementation, and skilled
delivery [6]. Even though this work has been done, thePM is still a major public health issue and a devastatingproblem.
Globally, in 2019, about 2.4 million newborn deaths[7] were reported, which is 7.6 times higher than in lowincome countries [7, 8]. PM Among the sub-Saharan

Agimas et al. BMC Pediatrics(2024) 24:523

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Fig. 2 trend of perinatal mortality in Ethiopia from EDHS 2005 to EDHS 2016

African countries Ethiopia had the highest perinatal
death rate (51.3 per 1000 births) in the years 1997–2019[9]. Among the most critical times of maternal and newborn death, the first hour and week of delivery contributeto the highest death rate [10]. To measure the reliable figure of mortality during delivery, PM is a more comprehensive indicator than the neonatal mortality indicator[11, 12].
The PM has several consequences. For example, psychological problems (depression, suicidal behavior)
reduce work productivity because of grieving and negatively affect couples’ relationships [13, 14]. Other mental
disorders like anxiety, stress, and poor partnership arealso associated with perinatal loss [15]. Quality of careduring birth can save about three million stillbirths andnewborns each year [4].
Although interventions such as expanding maternal and child health services are implemented in Ethiopia to reverse the impact of the PM, the PM is still themost challenging public health problem [16]. As different evidence shows, age, delivery place, sex of the child,residence of the woman, antenatal care utilization status,and source of drinking water were the significant factors
for PM [17–20]. Even though PM is a critical problem
in Ethiopia, the spatial distribution of the problem, thetrend of PM using national-level data (Ethiopian demographic health survey data), and the factors for the trendof PM were not addressed using decomposition analysis.
Additionally, most studies about PM were conducted at
the health institution level, but there are no adequate
studies at the community level about the trend and spatial distribution of PM in Ethiopia. Therefore, the current
study aimed to assess the trend and determinants of PM
in Ethiopia using further analysis of the Ethiopian Demographic Health Survey (EDHS) 2005–2016 data set using
decomposition analysis.
Objectives

To determine the trend of perinatal mortality in Ethiopia
using EDHS 2005–2016 data.
To identify the factors attributed to the change in perinatal mortality in Ethiopia using decomposition analysis.

Methods
Data

The EDHS data sets of 2005, 2011, and 2016 were used
for the intended analysis using a community-based crosssectional study design. These demographic surveys usedstratified, two-stage cluster sampling techniques. For
EDHS-2005, the sampling frame was developed basedon the 1994 Ethiopian population and housing census.
For EDHS-2011 and EDHS-201, the 2007 Ethiopian
population and housing census was used for samplingframe preparation. Geographical areas, or urban andAgimas et al. BMC Pediatrics(2024) 24:523

rural areas, were used for stratification purposes. About
21 sampling strata were used for the survey. A total of
540, 624, and 645 enumeration areas with independentand probability-proportional enumeration areas wereselected for EDHS-2005, 2011, and 2016, respectively.
Then household listing and selection were conducted
before the actual data collection procedure, and, on
average, 28 households in the enumeration areas wereselected using systematic sampling. The detailed selection process was reported in EDHS-2005, EDHS-2011,and EDHS-2016 [21–23]. A total of 33,998 sample sizes
were used in all surveys (EDHS-2005 = 12035, EDHS2011 = 10588, EDHS-2016 = 11375) (Fig .1).
Study and source population

The source population was all births from reproductiveage women in Ethiopia. Whereas, the study population
was the selected enumeration area in Ethiopia.
Eligibility criteria

All births from the reproductive age women were
included in the study whereas those have incomplete data
mainly the gestational age, birth dates, and ages at deaths
were excluded in the study.
Outcome of interest

Perinatal mortality (Yes, No).
Operational definition

Perinatal mortality is the death of a fetus starting at 28
weeks of gestation and newborn death up to 7 days after
delivery (1, 2). The perinatal mortality rate was a dependent variable, including both stillbirths and early neonatal deaths in the five years preceding the survey divided
by all births (including stillbirths) that have a pregnancy
duration of seven or more months. Stillbirth is defined as
pregnancy terminated after seven or more months. Early
neonatal death is death within seven days (days 0–6). The
outcome variables were coded as “0” for the absence of
perinatal mortality and “1” for the presence of perinatal
mortality [24].
Data collection procedure

The EDHS data set was used for the current study. Thisdata was accessed by requesting the DHS program website www.measuredhs.com and by explaining the ultimate objective of the current study. The raw data wascollected from reproductive-age women who gave birthusing a pretested, structured questionnaire. The data was
extracted from the birth records of the three consecutive
EDHS data sets (2005–2016).

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Data management and analysis

Before descriptive and analytical analysis, data were
weighted using sampling weight techniques to be more
representative. To describe the study subjects and participants, descriptive measures like cross-tabulation wereused using STATA version 14. After important predictors
are cleaned, coded, and extracted, the EDHS 2005, 2011,
and 2016 data sets are merged together for further trend
and decomposition analysis.
Trend and decomposition analysis

To assess the trend of perinatal mortality, descriptive
analysis was used using selected variables and a combination of EDHS data separately (2005–2011, 2011–2016,
and 2005–2016). To determine the trend of perinatal
mortality changes, the possible contributing predictors,
and the source of the difference in perinatal mortality
percentage in Ethiopia from 2005 to 2016, multivariate
decomposition analysis was employed. Two importantcomponents, such as the composition of the populationand the coefficient, were considered to be the contributing factors for the decreasing or increasing pattern ofperinatal mortality in Ethiopia since 2005 to 2016. The
logit-based multivariate decomposition analysis was used
to identify the possible factors for the trend of perinatal
mortality in Ethiopia. The logit-based decomposition wasusing the STATA command mvdcmp [25]. The observed
difference in perinatal mortality between the surveys
was decomposed into endowment (E) and coefficient (C)components. The endowment (E) means the difference incharacteristics, whereas the coefficient (C) means the difference in effects.

Results
Socio-demographic characteristics of the participants

In all surveys, 16,853 (49.6%) of the participants wereaged 20–29 years. Regarding employment status, there
was a slight decrease in no work (unemployment) from2177 (18.1%) in 2005 EDHS to 1457 (12.8%) in 2016
EDHS. From all surveys, about 18,439 (54.2%) participants have had an occupation. Additionally, 4997 (43.9%)of the participants were included in the 2016 EDHS. Furthermore, the majority of participants, 24,551 (72.2%)
who were included in the three surveys, had no education, and there was a decline from 9541 (79.3%) in 2005
to 7606 (66.9%) in 2016 (Table 1).
The trend of perinatal mortality rate in Ethiopia

The rate of perinatal mortality in Ethiopia has significantly decreased from a 37 death rate per 1000 births in2005 to a 33 death rate per 1000 births in 2016 (Fig. 2).

Agimas et al. BMC Pediatrics(2024) 24:523

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Table 1 Socio demographic characteristics of the participants in 2005, 2011 and 2016 EDHS
Variable
Women age

Residence
RegionReligion

Maternal educational level

Wealth index

Parent’s education

Parent’s occupation

Mother occupation

< 20
20–29
30–39
40–49
Urban
Rural
TigrayAfar
AmharaOromiaSomalia
Benishangul
SNNPRsHarari
Addis Ababa
Dire Dawa
GambelaOrthodox
MuslimOthers
No education
Primary education
Secondary and higher education
PoorestPoorerMiddleRicherRichestNo education
Primary
Secondary education
No work
Non agricultural
Agricultural
No occupation
Had occupation

Environmental and health service related characteristics

About 11,154 (92.7%), 9182 (86.7%), and 10,750 (94.5%)of the participants used toilet facilities in 2005, 2011, and2016, respectively, and there was an increment in toilet
facility utilization from 11,154 (92.7%) in 2005 to 10,750(94.5%) in 2016. Skilled births increased from 5147 (51%)
in 2005 to 6563 (62%) in 2011 to 8697 (76.5%) in 2016.
The overall ANC utilization in all surveys was 20,635(61%), and the magnitude increased from 43.3% in 2005
to 61.6% in 2011 to 78.2% in 2016 (Table 2).
Fetal and neonatal related characteristics

The majority of the births 10,836 (90%) in 2005, 9602
(90.7%) in 2011, and 10,186 (89.5%) in 2016 were single.
More than half of 23,447 (69%) births in all surveys were

Weighted frequency (%)
2005(N = 12037)
2011(N = 10588)
576 (4.8%)361 (3.4%)
5825 (48.4%)
5429 (51.3%)
4344 (36.1%)
3823 (36%)
1292 (10.7%)985 (9.3%)
883 (7.3%)
1406 (13.3%)
11,154 (92.7%)
9182 (86.7%)775 (6.4%)
678 (6.4%)
122 (0.01%)
114 (1.1%)
2827(23.5%)2538 (24%)
4666 (38.8%)4291 (40.6%)522 (4.3%)
296 (2.8%)
115 (0.9%)131 (1.2%)
2742 (22.8%)2248 (21.2%)
23 (0.2%)
27 (0.2%)
170 (1.5%)
192 (1.8%)
41 (0.3%)
35 (0.3%)
34 (0.03%)
38 (0.4%)5094 (42.3%)
4233 (40%)
4123 (34.3%)
3563 (33.7%)
2820 (23.4%)
2792 (26.3%)
9541 (79.3%)
7404 (69.9%)
1993 (16.5%)2801(26.5%)
503 (4.2%)
383 (3.6%)
2646 (22%)
2421(22.9%)2497(20.7%)2382 (22.5%)2607 (21.7%)2151 (20.3%)2468 (20.5%)
2018(19.1%)
1819 (15.1%)
1616 (15.3%)3458(28.7%)
2598 (24.5%)4568 (38%)
6201(58.6%)4011(33.3%)
1789 (16.9%)2177(18.1%)
2346 (22.2%)6052(50.3%)5468 (51.6%)
3808(31.6%)
2774 (26.2%)
4348 (36%)
4861(45.9%)7689 (64%)
5727 (54.1%)

2016(N = 11375)
374 (3.3%)
5599 (49.2%)
4382 (38.5%)1020 (9%)
1229 (10.8%)
10,146 (89.2%)
709 (6.2%)
119 (1%)2121 (18.6%)4997 (43.9%)554 (4.9%)133(1.3%)2402 (21.1%)
27 (0.2%)
234 (2.1%)
49 (0.4%)
29 (0.3%)3844 (33.8%)4696 (41.3%)
2835 (24.9%)7606 (66.9%)
2961 (26%)
808 (7.1%)
2483 (21.8%)2877 (25.3%)2318 (20.4%)2084 (18.3%)
1613 (14.2%)
3201(28.1%)4562(40.1%)
3612 (31.8%)
1457 (12.8%)5901(51.9%)4017 (35.3%)
6352 (55.8%)5023 (44.2%)

24 months and older. Furthermore, there was a decline
in cigarette smoking from 256 (21.3%) in 2005 to 189(17.8%) in 2011 and 126 (1.1%) in 2016 (Table 3).
Trends of perinatal mortality rate by women characteristics

The trend of the perinatal mortality rate according to
women’s characteristics in Ethiopia from 2005 to 2016
EDHS showed that there was a decline in perinatal mortality in urban residences across all surveys, from 23.3
per 1000 births in 2005 to 16.6 per 1000 births in 2011
and 6.6 per 1000 in 2016. Regarding the regional distribution of the perinatal mortality rate, in the Amhara
region, the trend decline across all phases in 2005–2011(phase-I) declined by 29.9 per 1000 births. In 2011–2016(phase II), the death rate the death rate declined by 10.6

Agimas et al. BMC Pediatrics(2024) 24:523

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Table 2 Distribution of environmental and health service related characteristics of respondents in 2005, 2011 and 2016 EDHS
Variable
Source of drinking water

Piped
Protected
Unprotected
Yes
No
Solid
Non solid
Non skilled
SkilledVaginal
Cesarean-section
Yes
No
Not use1 dose≥ 2 doses

Use of toilet facilities
Type of cooking fuelDelivery assistanceMode of delivery
ANC utilization
Tetanus vaccination status

Weighted frequency (%)
2005(N = 12037)
2576(21.4%)5825 (48.4%)3636 (30.2%)
11,154 (92.7%)
883 (7.3%)
7752 (64.4%)4285(35.6%)
5890 (49%)
5147 (51%)
10,036 (83.4%)
2001 (16.6%)
5211(43.3%)
6826 (56.7%)2123(17.7%)5579(45.3%)4335(36%)

2011(N = 10588)
1361 (12.9%)
5404 (51%)
3823 (36.1%)
9182 (86.7%)1406 (13.3%)
6789 (64%)
3789 (36%)
4025 (38%)
6563 (62%)
7687 (72.6%)2901 (27.4%)6524 (61.6%)4064 (38.4%)
2620 (24.7%)4900 (46.3%)
3068 (29%)

2016(N = 11375)
1924 (16.9%)5519 (48.5%)3932 (34.6%)
10,750 (94.5%)625 (5.5%)
6701 (58.9%)4674 (41.1%)
2678 (23.5%)
8697 (76.5%)8606 (75.7%)2769 (24.3%)
8900 (78.2%)
2475 (21.8%)
1890 (16.6%)4005 (35.2%)4480 (39.4%)

Table 3 Fetal/neonatal and maternal behavior related characteristics of respondents in 2005, 2011 and 2016 EDHS
Variable
Birth interval
Sex of child
Birth order

Types of births
Smoking cigarette< 24 months≥ 24 months
Female
Male
≤3
4–5
≥6
SingleMultiple
Yes
No

Weighted frequency (%)
2005(N = 12037)
4212 (35%)
7825 (65%)
5987 (49.7%)6050 (50.3%)3679 (30.6%)4356 (36.2%)
4002 (33.2%)
10,836 (90%)
1201 (10%)
256 (21.3%)
11,781(78.7%)

per 1000 births, and the maximum amount of change wasobserved in phase III (2005–2016), which was declined
by a death rate of 40.5 per 1000 births. Furthermore, thetrend of perinatal mortality rate by women aged less than
20 years showed that in phase I (2011–2005), it decreasedby 1.6 per 1000 births, in phase III (2016–2011), by 3.4
per 1000 births (Table 4).
Over all decomposition analysis

The overall perinatal mortality in Ethiopia has significantly decreased from 2005 to 2016. As the overall decomposition (2005–2016) analysis showed, thedecrease in perinatal mortality in Ethiopia was explainedby the endowment of women between each EDHS. Thus,around 83.3% of the perinatal mortality decline was
because of the endowment (composition) of the participants, which was statistically significant. The rest was
attributed to the change in the coefficients (C) (Table 5).

2011(N = 10588)
3565 (33.7%)7023 (66.3%)
5067 (47.9%)5521(52.1%)
3101((29.3%)3780 (35.7%)3707 (35%)
9602 (90.7%)986 (9.3%)
189 (17.8%)
10,399 (81.2%)

2016(N = 11375)
2776 (24.4%)
8599 (75.6%)
5897 (51.8%)5478 (49.2%)
2989 (26.3%)
5231(46%)3155 (27.7%)
10,186 (89.5%)
1189 (10.5%)
126 (1.1%)
11,249 (98.9%)

Detailed decomposition analysis

Among the differences in the endowment, the differencesin the endowment, the difference in the composition of
ANC visits (B = = -0.00072, 95% CI = -0.0012, -0.0011,
p-value = 0.007), taking ≥ 2 TT vaccines (B = -0.0019,
95% CI = -0.0028, -0.0011, p-value = < 0.001), urban
residence (B = -0.000499, 95% CI == -0.0033, -0.00061,
p-value = 0.004), secondary education (B = 0.0023,
95% CI = 0.000046, 0.0041, p-value = 0.014), and skill
birth attendant (B = 0.0069, 95% CI; 0.00068, 0.013,
p-value = 0.03) were significantly decrease the perinatal
mortality in the last 10 years. Among the differences incoefficients, skilled birth attendant (B = 0.000099, 95% CI:
0.00002, 0.00018, p-value = 0.013) significantly decreased
perinatal mortality (Table 6).

Discussion
Perinatal mortality is the most devastating issue in Ethiopia. But the trend and what factors contributed to theincrement or decline of perinatal mortality were notAgimas et al. BMC Pediatrics(2024) 24:523

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Table 4 Trends in perinatal mortality rate among women’s who gave birth in the last five years prior to the surveys by selectedcharacteristics 2005, 2011, and 2016 EDHS

Women age

Residence
RegionReligion

Maternal educational level

Wealth index

Parent’s education

Parent’s occupation

Mother occupation
Source of drinking water

Use of toilet facilities
Type of cooking fuelDelivery assistanceMode of delivery
ANC utilization

< 20
20–29
30–39
40–49
Urban
Rural
TigrayAfar
AmharaOromiaSomalia
Benishangul
SNNPRsHarari
Addis Ababa
Dire Dawa
GambelaOrthodox
MuslimOthers
No education
Primary education
Secondary and above
PoorestPoorerMiddleRicherRichestNo education
Primary
Secondary education
No work
Non agricultural
Agricultural
No occupation
Had occupation
Piped
Protected
Unprotected
Yes
No
Solid
Non-solid
Non skilled
SkilledVaginal
Cesarean section
Yes
No

2005
(N = 12037)

2011(N = 10588)

2016(N = 11375)

13.9
17.9
23.1
11.7
22.3
39.3
2.6
8.9
47.1
14.8
22.1
40.1
29.9
23
5.9
17.8
3.4
3.9
19.4
16.2
34.2
32.6
19.4
38.5
25.9
17.6
12.5
6.8
23.4
24.4
21.8
34.7
23.8
29.5
29.5
18.4
25.4
12.7
32.8
36.7
12.8
14.6
26.4
38.4
13.7
20.1
25.8
3.6
39.2

12.3
19.4
21.4
2
16.6
46.6
12
9.2
17.2
16.1
48.2
24.6
32.4
27
2.3
13.1
6.9
39.4
13.4
36.8
25.8
34.5
23.5
49.2
31.4
18.9
16.8
9.2
28.2
25.6
22.8
36.3
24.9
28.1
9.7
7.9
28.9
21.2
23.5
23.6
23.3
38.6
23.8
43.6
13.2
38.9
44.8
9.6
47.1

8.9
6.7
12.2
8.9
6.6
34.6
5.7
10.6
6.6
9.3
18.9
29.1
21.7
21.8
1.9
8.9
2.2
34.9
5.3
19.4
17.3
31.7
20.6
32.6
28.4
13.7
10.6
4.4
18.6
13.9
10.6
16.7
18.3
29.6
28.1
11.4
12.4
19.8
18.2
12.9
29.5
24.9
34.9
31.4
11.8
27.7
29.6
2.4
25.2

% difference in perinatal
mortality
2011
2016 to2016 toto 2005
2011
2005
-1.6
-3.4
-5
1.5
-12.7
-11.2
-1.7
-9.2
-10.9
-9.7
6.9
-2.8
-5.7
-10
-15.7
7.3
-12
-4.7
9.4
-6.3
3.1
0.3
1.4
1.7
-29.9
-10.6
-40.5
1.3
-6.8
-6.8
26.1
-29.2
-3.2
-15.5
4.5
-11
2.5
-10.7
-8.2
4
-5.2
-1.2
-3.9
-0.4
-4
-4.7
-4.2
-8.9
3.5
-4.7
-1.2
35.5
-4.5
31
-6
-8.1
-14.1
20.6
-17.4
3.2
-8.4
-8.4
-16.9
1.9
-2.8
-0.9
4.1
-2.9
1.2
10.5
-16.6
-5.9
5.5
-3
2.5
1.3
-5.2
-3.9
4.3
-6.2
-1.9
2.4
-4.8
-2.4
4.8
-9.6
-4.8
1.2
-12
-10.5
1
-12.2
-11.2
1.6
-19.6
-18
1.1
-6.6
-5.5
-1.4
1.5
0.1
-19.8
18.4
-1.4
-21.6
3.5
-7
3.5
-16.5
-13
8.5
-1.4
7.1
-9.3
-5.3
-14.3
-13.1
-10.7
-23.8
10.5
6.2
16.7
24
-13.7
10.3
-2.6
11.1
8.5
5.2
-12.2
-7
-0.5
-1.4
-1.9
18.8
-11.2
7.6
19
-15.2
3.8
6
-7.2
-1.2
7.9
-21.9
-14

Agimas et al. BMC Pediatrics(2024) 24:523

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Table 4 (continued)

Tetanus vaccination status

Birth interval
Sex of child
Birth order

Types of births
Smoking cigaretteNot use1 dose≥ 2 doses< 24 months≥ 24 months
Female
Male
≤3
4–5
≥6
SingleMultiple
Yes
No

Overall rate

2005
(N = 12037)

2011(N = 10588)

2016(N = 11375)

31.4
28.9
29.1
29.2
21.8
34.8
36.2
36.3
39.3
39
12
38.3
18.5
37.8
37 (32.6–41.4)

51.1
41.2
23.2
48.1
32.2
37.8
29.3
44.4
26.2
37
9.8
28.9
23.5
40.1
46(39.2–52.8%)

23.9
27.4
12.3
35.6
27.9
23.8
19.3
19
39.9
31
11.9
18.8
12.6
43.4
33(27.8–38.2)

Table 5 Overall decomposition analysis of change in perinatal
mortality in Ethiopia 2005–2016
Perinatal mortality
E
C
R

Coefficient-0.0083-0.00167-0.01

95% CI(-0.0157, -0.001)(-0.0031,-0.00025)-0.017, -0.0029

p-value Pct.
0.026
83.3
0.02
16.7
0.006

Note E = Endowment C = Coefficient R = Residual

studied. Thus, in this study, an attempt has been made toassess the trend and multivariate decomposition of perinatal mortality in Ethiopia.
The trend of perinatal mortality in Ethiopia has
decreased over time, from 37 deaths per 1000 births in2005 to 34 deaths per 1000 births in 2016. This was supported by a systematic review and meta-analysis conducted in Ethiopia [9]. This may be because the Ethiopian
government placed an emphasis on maternal and childhealth services by strengthening the health extension
program and exempting the service [26]. The other possible reason might be associated with the fact that the
number of skilled birth attendants and the basic service
coverage like ANC, post-natal care service, family planning service, and institutional delivery service in Ethiopia increased over time, which enabled the women to getcounselling about their pregnancy, their health, fetal condition, birth preparedness, nutrition, and other important messages [27, 28].
Regarding the multivariate decomposition findings, theoverall contribution of women’s composition to perinatal mortality in the entire survey (2005–2016) was 83.3%.
With an increase in the endowment of urban resident
women over the course of the course of the survey, there
was a significant decrease in perinatal mortality in Ethiopia. This may be because the expansion of urbanization% difference in perinatal
mortality
2011
2016 to2016 toto 2005
2011
2005
19.7
-27.2
-7.5
12.3
-13.8
-1.5
-5.9
-10.9
-16.8
18.9
-12.5
6.4
10.4
-4.3
6.1
3
-14
-11
-6.9
-10
-16.9
8.1
-25.4
-17.3
-13.1
13.7
0.6
-3
-6
-8
-2.2
2.1
-0.1
-9.4
-10.1
-19.5
5
-10.9
-5.9
2.3
3.3
5.6

in Ethiopia may increase the chance of getting maternaland child health services and access to health information for rural women [29, 30].
The increase in the women’s composition of ANC utilization over the survey also had a significant effect on thedecrement in perinatal mortality in Ethiopia. This may
be because women who visit for ANC service are more
likely to give birth and have more children than women
who have no history of ANC service [31]. An increase in
taking the TT vaccine (taking one or more TT vaccines)
over the course of the course of the survey decreased
perinatal mortality significantly. The possible reason thatmight be associated with improving TT vaccination coverage could be to substantially increase the number ofnewborns protected at birth compared to their counterparts and subsequently reduce the number of newborn
deaths [32]. The other possible reason might be thatthose women who take the TT vaccine are more likely toaccess other health services like education about pregnancy complications, danger signs, nutrition counselling,
and other key messages.
An increase in women who had occupations also hada significant effect on the reduction of perinatal mortality in Ethiopia. This might be because women who havean occupation are more likely to become employed andlive in a better socio-economic condition, which leads tobetter household food security and may reduce maternalmalnutrition and its complications [33]. The other possible reason might be that women who have an occupation
are more likely to have better knowledge and educational
status than those who have no occupation. Thus, better knowledge and educational background are keys tohaving better information about their health and having

Agimas et al. BMC Pediatrics(2024) 24:523

Page 9 of 11

Table 6 Detailed decomposition analysis of perinatal mortality in Ethiopia from 2005 to 2016
Experiencing perinatal mortality
Mode of delivery

Vaginal delivery
Cesarean section

ANC

Yes

TT vaccine uptake status

No
1
≥2

Place of residence

No
Urban

Maternal occupation

Rural
Occupation

Maternal education

No occupation
No education
Primary education
Secondary education

Delivery assistance

SkilledDifference due to characteristics (E)Coef.
p-value
Pct.

Difference due to coefficient (C)Coef.
p-value-0.000042(-0.00039, 0.00031)-0.002164(-0.0035, -0.00358)

0.59

2.8

0.812

-0.39

0.001

-19.83-0.00031(-0.0008,0.0014)-0.00358(-0.0089,0.0018)

0.193-32.84-0.00072(-0.0012, -0.0011)-0.0019(-0.0028, -0.0011)

0.007

-6.6

0.77

-3.38

< 0.001-17.8-0.00036(-0.0028,0.0021)-0.0011(-0.0064,-0041)

0.67-10.44-0.000499(-0.0009, -0.00007)

0.02

-4.59

-0.0073(-0.01, 0.025)

0.419

65.24

-0.019(-0.0033, -0.00061)

0.004

-18.1

0.0082(-0.0043,0.021)

0.2

75.13

0.00033(-0.0002, 0.0027)
0.0023(0.000046, 0.0041)
0.0069(0.00068, 0.013)

0.78

-0.33

0.56

9.4

0.014

-2.31

0.58

16.4

0.03

-69

-0.00094(-0.0041,0.0022)-0.0016(-0.0074,0.0041)
0.000099(0.00002,0.00018)

0.013

-0.98

Pct.

Non skilled
Total
Constant

good health-seeking behavior for maternal and childhealth services.
In the current study, an increase in the endowmentof women with secondary education also significantly
reduced perinatal mortality compared to women withno education. This might be due to women with better
educational status, which may increase the chance of
having better health information, better nutrition, andbetter health-seeking behavior than those women who
have no education in return, which improves infant survival and healthy maternal conditions [34]. Furthermore,
an increase in the endowment (composition) of women
who give birth with the assistance of a skilled birth attendant significantly reduces perinatal mortality compared
to women who give birth to a non-skilled birth attendant. Regarding the difference in coefficient, giving birthby a skilled birth attendant also significantly contributed
to the reduction of perinatal mortality in Ethiopia. The
finding was consistent with a systematic and meta-analysis study and a study conducted in the United States ofAmerica [35, 36]. This can be justified by the fact that thefact that women who give birth to skilled birth attendants
get better delivery care than their counterparts. This canbe justified by the fact that the fact that women who give

83.3

16.7
-0.0045(-0.0023,-0.0098)

birth to skilled birth attendants get better delivery carethan their counterparts. This could reduce the chanceof newborn death from sepsis, hypothermia, prolonged
labour, and other complications during giving birth. The
limitation of the study was that some of the most important variables, such as clinical data, maternal medical
and obstetric conditions, and RH incompatibility, were
missed in the EDHS data. So further study by considering
the above factors is very important.

Conclusion
The trend of perinatal mortality in Ethiopia has declined
across time. The change in women’s endowment contributes to more than a third of the perinatal mortality
decrease. Among the changes in women’s endowment,variables such as the uptake of the TT vaccine, skilled
birth attendants, secondary education, occupation,
and ANC utilization contributed to the decline of PM.
According to the change in difference coefficients, giving
birth by a skilled birth attendant was the most significant
predictor of the decline of PM in Ethiopia. To further
reduce the PM, scaling up the maternal health service hasan abundant advantage. The finding has implications forAgimas et al. BMC Pediatrics(2024) 24:523

designing PM reduction strategies and the wise allocation of resources for the interventions.

Page 10 of 114.
5.

Abbreviations
ANC	Antenatal Care
DHS	Demographic Health Survey
EDHS	Ethiopian Demographic Health Survey
PM	Perinatal Mortality
TT	Tetanus Toxoid

6.

Acknowledgements
The authors would like to give thanks to DHS international for giving
permission to utilize the data.

8.

Author contributions
Conceptualization: MCA, SD, WN, HSH. Data curation: SD, AS, TM, YT. Formal
analysis: MC, AK, AS, DK. Investigation: MCA, TK, TM, YT. Methodology:
MCA, DK, WN, GA. Software: MCA, YT, AS, SZ, HSH. Supervision: MCA, HSH.
Visualization: SZ, SD, TM, TK, YT, WN, DK, GA. Writing – original draft: MCA, SD,
SZ, GA.
Funding
No funding source.

7.

9.
10.
11.
12.
13.

Data availability
All data are accessed in the article.

14.

Declarations

15.

Ethical approval and consent to participate
Ethical approval from individual participants was not obtained because of
secondary data. Rather, permission was obtained from DHS International toaccess the data.

16.

Consent for publication
Not applicable.

17.

Competing interests
The authors declare no competing interests.

18.

Author details
1
Department of Epidemiology and Biostatistics, Institute of Public Health,College Of Medicine And Health Science, University of Gondar, Gondar,
Ethiopia
2
College of Health Sciences, Department Of Pediatrics And Child HealthNursing, Debre Tabor University, Debre Tabor, Ethiopia
3
COllege Of Health Science, Department Of Maternal And Neonatal
Health Nursing, Debre Tabor University, Debre Tabor, Ethiopia
4
College of Health Sciences, Department of Adult Health Nursing, Debre
Tabor University, Debre Tabor, Ethiopia
5College of Health Sciences, Department of Emergency and Critical
Health Nursing, Debre Tabor University, Debre Tabor, Ethiopia
6
College of Health Sciences, Department of Reproductive Health, Debre
Tabor University, Debre Tabor, Ethiopia
7
Debre Tabor Health Science College, Debre Tabor, Ethiopia
8
Department of Pediatrics and Neonatal Nursing, College Of Health
Science, Debre Tabor University, Debre Tabor, Ethiopia

19.
20.
21.
22.
23.
24.
25.
26.

Received: 20 October 2023 / Accepted: 8 August 2024
27.
28.
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