Magnitude of Preterm Birth and Associated Factors among Mothers Who Gave Birth at Public Hospitals in Addis Ababa Ethiopia, 2022
Weinu B, Diane S and Mahaboob H
Published on: 2023-01-27
Abstract
Background: Developing countries like Ethiopia lack reliable data on preterm birth. The purpose of this study was to find the magnitude of preterm birth and its associated factors among mothers who gave birth at public hospitals in Addis Ababa Ethiopia 2022.
Methods: Facility based, cross-sectional study was conducted in four randomly selected public hospitals from august 25 –September 25, 2022. Data was collected from 325 mothers through face to face interview using structured questionnaire and their chart referred. Simple random sampling technique was used to select study participants. The collected data was entered to Epi Data version 3.1, and analysed by SPSS version 25.0. Binary and multi variable logistic regression were computed to test the association of variables at 95% CI.
Results: The magnitude of preterm birth in this study was 13.5% [95% CI (9.5%, 17.5 %). Gestational Hypertension (AOR=2.7,95%CI:1.235,6.144) ,PROM (AOR=3.0,95% CI :1.3291,6.868), multiple pregnancy (AOR=2.7 95% CI :1.028,7.356) and APH (AOR=3.3 95% CI: 1.166,9.625) found to be significantly associated with preterm birth.
Conclusion: There is high magnitude of preterm birth in the study area. Quality care, training health professionals, health education and community mobilization by concerned bodies are highly recommended.
Keywords
Pregnancy; Preterm birth; Gestational hypertension; NeonatalIntroduction
Preterm birth is defined as a delivery which occurs at less than 37 completed weeks of gestation [1]. Globally, prematurity is the leading cause of death in children under the age of five [2]. More than one in 10 births is born too early in the world and many of those babies die shortly after birth or suffer some type of lifelong physical, neurological or educational disabilities often at great cost to families and society [3]. Preterm births are the leading cause of neonatal deaths accounting for 35% of the world's annual deaths and he survival chances of the preterm babies dramatically depend on where they are born [2]. According to Global Burden of Disease Study, 3.1% of all disability-adjusted life-years was attributed to preterm birth which is similar to the burden of HIV or malaria [4].
Globally, 80% of PTB occur in Sub-Sahara Africa and South Asia with higher morbidity and mortality. Ethiopia is among the top 15countries along with Nigeria, Kenya and Malawi that contribute preterm babies with an estimated preterm birth rate of 14%-23%. The risk of a neonatal death due to complications of PTB is at least 12 times higher for babies born in this area than European baby [2,4]. In Ethiopia, 320,000 babies are born to soon each year, and the report of the Ethiopian Demographic and Health Survey (EDHS) indicated that 30 per 1000 live birth is PTB [2,5].The burden of preterm birth is significantly higher in low-income countries due to higher rates of pre- term birth and limited availability of the required resources in conjunction with low quality service [4]. Preterm birth can also be or provider initiated (induced) [6]. Globally, there are different policies, strategies, and programs that work towards prevention and care of preterm birth and reducing mortality [7]. Yet, still it is the first leading cause of neonatal mortality and the second most common cause of under-five mortality [8]. Ethiopia also developed different policies and programs including expanding Neonatal Intensive Care Unit (NICU), integrated management of neonatal and childhood illness, and quality improvement program to tackle new born death at institution and community levels by controlling major neonatal complications [9]. Besides these efforts, preterm neonatal mortality is still persistently high [9-12]. However, limited studies were done. This study gives current information about magnitude and associated factors of preterm birth to act up accordingly.
Methods And Materials
Study Area and Period
The study was conducted from April 25 to Sep 22, 2022at selected public hospitals in Addis Ababa, which is the capital city of Ethiopia. There are 12 public hospitals in Addis Ababa [13].
Study Design
Facility based, descriptive cross-sectional study was employed among mothers who gave birth in Gandhi Zewditu, Rasdesta and Menelik hospital during study period.
Study and Source Population
The source population was mothers who gave birth in randomly selected Hospitals. The study population was randomly selected mothers who gave birth during the study period.
Inclusion and Exclusion Criteria
Women who gave birth during the study period with known LNMP or had ultrasound check up result during their 1st trimester of pregnancy were include in this study, while women who were unable to communicate were excluded.
Sample Determination
Sample size was determined by using single population estimation formula with assumption of 95% confidence interval with 5% margin of error, and considering the 25.9% population proportion of preterm birth taking from the study conducted in Jimma University Specialized Teaching and Referral Hospital, with of 10% nonresponse rate.

N=295 + Non response rate of (0.1*295)
N=295+30=325
N=325
Where
n= the minimum sample size required
P = 0.259
q = (1-p)
d = the desired precision (marginal error) between sample size and population parameter is 5%.
Z α/2 = standard normal score at 95% confidence interval.
Sampling Procedure
Step 1: Among 12 public hospitals four hospitals were selected by simple random sampling technique (Gandhi Hospital, Zewditu Hospital, Rasdesta Hospital and Menelik Hospital).
Step 2: Sample size distribution was allocated for Hospitals according to their population size, average number of deliveries per month at each hospital.
Gandhi Hospital: N=850/2356x325=117
Zewditu Hospital: N=710/2356x325=98
Rasdesta Hospital: N=366/2356x325=51
Menelik Hospital: N=430/2356x325=59
Step 3: Simple random sampling technique was employed and study subjects were selected
Study Variables
Independent Variables: Age, marital Status, monthly income, ANC visit, history of PTB, pre-mature rupture of membrane (PROM), GHTN, APH, type of pregnancy, gestational age, birth weight, birth interval, parity
Dependent Variable: Preterm birth
Data Collection Procedures and Quality Assurance
Data was collected by face to face interviews using a structured and pretested questionnaire and reviewing patient chart. Gestational age was determined by last normal menstrual period and by early ultrasound which means ultrasound done in the first trimester. Data was collected by four nurses and four midwives, and one public health officer was assigned as supervisor. Both data collectors and supervisor were trained on how to collect the data.
Data Management and Data Analysis
The data was entered, cleaned, and edited using EpiData version 3.1 and was exported to SPSS version 25.0 software packages for analysis. Both bivariate and multiple logistic regression analysis was done. Variables with ???? value < 0.25 in bivariate analysis was entered in to multivariate analysis and variables with ???? value < 0.05, 95% CI in multivariate were considered statistically significant.
Operational Definitions
Anemia: is the condition that can occur during pregnancy when blood hemoglobin (Hb) concentration of less than 11g/dl [12].
Preterm Birth: Defined by the World Health Organization (WHO) as a birth occurring before 37 weeks of gestation.
Preterm Birth: a delivery which occurs at less than 37 completed weeks of Birth.
The Birth Interval: the number of months since the previous birth. It was considered as either being short or optimal if the birth interval was <24 months and ≥24 months, respectively.
APH (Antepartum Hemorrhage): Is defined as bleeding from the genital tract occurring from 24+0 weeks of pregnancy and prior to the birth of the baby.
Pre-Mature Rupture of Membrane (PROM): Premature / pre-labor rupture of fetal membranes is rupture of membranes (ROM) before the onset of labor.
Ethical Consideration
A written permission letter was obtained from research and community service of Yanet College, and ethical clearance was obtained from Addis Ababa health Bureau. Permission was obtained from Gandhi, Zewditu, Rasdesta and Menelik hospital administrator to conduct the study, and lastly, consent was obtained from the respondents and confidentiality of the data was ensured by omitting the names of the respondents.
Result
Socio-Demographic and Behavioral Characteristics
From the total of 325 participant most were in the range of 25-35 ages. Majority of the women, who gave birth 310 of 325 (95.4%) were urban dwellers, also most participants 309 (95.1%) were married. From overall proportion 21 (6.5%) had no formal education. In addition to these, all participants had not chewed chat, smoke cigarettes and drink alcohol in the last nine months. From occupational status of mothers few 34 (10.5%) were merchants and only few families had > 10,000-birr monthly income. Concerning family size only 59 (18.2%) mothers had greater than 5 families in the house (Table 1).
Table 1: Socio-Demographic Characteristics of respondents.
|
Variable |
Category |
Frequency |
Percentage |
|
Age |
15-24 years |
107 |
32.9 |
|
25-35 years |
168 |
51.7 |
|
|
>35 years |
50 |
15.4 |
|
|
Residence |
Urban |
310 |
95.4 |
|
Rural |
15 |
4.6 |
|
|
Marital Status |
Married |
390 |
95.1 |
|
Unmarried |
16 |
4.9 |
|
|
Education |
No formal education |
21 |
6.5 |
|
Primary school |
121 |
37.2 |
|
|
Secondary school |
121 |
37.2 |
|
|
Certificate or diploma |
29 |
8.9 |
|
|
Degree and above |
33 |
10.2 |
|
|
Number of family Members |
<5 |
266 |
81.8 |
|
>5 |
59 |
18.2 |
|
|
Occupation |
House wife |
127 |
39.1 |
|
Private employee |
124 |
38.2 |
|
|
Government employee |
40 |
12.3 |
|
|
Merchant |
34 |
10.5 |
|
|
Income |
<5000 birr |
159 |
48.9 |
|
5000-10,000 birr |
124 |
38.2 |
|
|
>10,000 |
42 |
12.9 |
Mother and Fetus Related Characteristics
From result 306 (94.2%) of respondents had ANC follow up, majority of them 281 (86.5%) had greater than or equal to four ANC visits. Concerning parity, 184 (56.6%) were primipara and 10 (3.1%) of them were greater or equal to Para 5 and birth interval of greater or equal to 24 months were 104 (32%). Among respondents 46 (14.15%) had gestational hypertension and 50 (15.38%) had anemia. From previous obstetric history, 42 (12.9%) of participants had previous history of preterm birth and 40 (12.3%) had premature rupture of membrane in the current birth. In this study about 23 (7.08%) were multiple pregnancy. According to birth weight the majority 243 (74.8%) were at the range of birth weight (2,500g-4,000g) and 11 (3.4%) were above 4000g.
Table 2: Mother and fetus related Characteristic.
|
Variables |
Category |
Frequency |
Percentage |
|
Anemia |
Yes |
50 |
15.4 |
|
No |
275 |
84.6 |
|
|
PROM |
Yes |
40 |
12.3 |
|
No |
285 |
87.7 |
|
|
APH |
Yes |
21 |
6.46 |
|
No |
304 |
93.54 |
|
|
GHTN |
Yes |
46 |
14 |
|
No |
279 |
86 |
|
|
Type of pregnancy |
Single |
302 |
93 |
|
Multiple |
23 |
7 |
|
|
Birth weight in gram |
<2500 |
71 |
21.8 |
|
2500-4000 |
243 |
74.8 |
|
|
>4000 |
11 |
3.4 |
|
|
Gestational age at birth in week |
<37 |
44 |
13.5 |
|
≥37 |
281 |
86.5 |
|
|
Parity |
1 |
184 |
56.6 |
|
01-Apr |
131 |
40.3 |
|
|
>4 |
10 |
3.1 |
|
|
Birth interval |
< 24months |
221 |
32 |
|
≥ 24 months |
104 |
68 |
|
|
Previous history of PTB |
Yes |
40 |
12.3 |
|
No |
285 |
87.7 |
|
|
ANC visit |
No visit |
19 |
5.8 |
|
1-3 visit |
25 |
7.7 |
|
|
≥ 4 visit |
281 |
86.5 |
|
|
Current PTB |
Yes |
44 |
13.5 |
|
No |
281 |
86.5 |
Magnitude of Preterm Birth
The magnitude of preterm birth in this study was 13.5% [95% CI (9.5%, 17.5 %)].
Factors Associated With Preterm Birth
In this study multivariable logistic regression shows that: Gestational Hypertension (AOR=2.7,95% CI:1.235,6.144) ,PROM (AOR=3.0,95% CI :1.3291,6.868), multiple pregnancy (AOR=2.7 95% CI :1.028,7.356) and APH (AOR=3.3 95% CI: 1.166,9.625) found to be significantly associated with preterm birth (Table 3).
Table 3: Factors associated with preterm births among women who gave birth at public hospitals in Addis Ababa Ethiopia 2022.
|
Preterm Birth |
||||||
|
Variable |
Yes |
No |
COR (95%CI) |
SIG |
AOR (95%CI) |
SIG |
|
Anemia |
||||||
|
Yes |
10(20%) |
40(80%) |
1.6(0.7,3.6)* |
0.2 |
1.3(0.565,3.201) |
0.503 |
|
No |
34(12.6%) |
242(87.6%) |
1 |
1 |
||
|
APH |
||||||
|
Yes |
6(28.5%) |
15(71.4%) |
2.8(1.0,7.6)* |
0.45 |
3.3(1.166,9.625)* |
0.025 |
|
No |
38(12.5%) |
266(87.5%) |
1 |
1 |
||
|
Pregnancy type |
||||||
|
multiple |
8(34.7%) |
15(65.2%) |
3.9(1.5,9.9)* |
0.004 |
2.7(1.028,7.356)* |
0.044 |
|
singleton |
36(11.9%) |
266(88.0%) |
1 |
1 |
||
|
Gestational HTN |
||||||
|
Yes |
12(26.0%) |
34(73.9%) |
2.7(1.2,5.7)* |
0.009 |
2.7(1.235,6.144)* |
0.013 |
|
No |
32(11.5%) |
247(88.5%) |
1 |
1 |
||
Discussion
In this study, the prevalence of preterm birth was observed to be 13.5% [95% CI (9.5%, 17.5 %)].This finding is consistent with the study conducted in United States, Central and Eastern Europe, Nigeria, Debretabor (Ethiopia), French Caribbean population ,Malawi and Addis Ababa which were 10.23%,10.2%, 11.8%,12.8% 15.8%,16.3% and 16.15% respectively . This may be due to similar study design [14-17]. The magnitude in this study was lower than study conducted in Sub-Saharan Africa and Kenya, which were 60% and 18.3% respectively [4,18], and in contrast studies done in Algeria (9.26%) and England (7.8%) have lower prevalence of preterm birth compared to this study. This might be due to better preventive intervention in health-related program in Algeria and England [15].
In this study mothers who had gestational hypertension were 2.7 times more likely to deliver preterm birth in comparison to mothers with normotensive mothers. This study is consistent with study done in public hospitals of western Ethiopia and Tigray regional state [16,19]. This may be caused by hypertension decreasing utero-placental blood flow, which in turn causes intrauterine growth restriction and ultimately preterm birth. Mothers who had experienced PROM were 3 times more likely to deliver preterm birth than their counterparts. This result is consistent with study done in Iran [20]. Mothers with APH were 3.3 times more likely to have preterm delivery than counterparts. This might be because APH puts both the fetus and the mother at danger during pregnancy [17,19,21], and also multiple pregnancies were 2.7 more likely to have preterm births than counter parts. The outcome is consistent with previously published studies [22].
Conclusion
Preterm birth is still public concern in the study area. The common risk factors for preterm birth at public hospitals in Addis Ababa were Pregnancy induced hypertension, premature rupture of membrane (PROM) multiple pregnancy and Antepartum Hemorrhage (APH) which are major public health problems. Early detection and treatment of diseases or disorders among pregnant women as well as the improving health care quality delivered to pregnant woman may reduce risk factors for preterm delivery. Obstetric Care providers are highly recommended to early identify and refer for specialized obstetrical evaluation and management of those who have high risk of preterm birth mothers in early pregnancy. In Ethiopia, Preterm birth is still a public health problem it is better to expand neonatal intensive care unit that equipped with the necessary materials and trained staff to management and prevention of complication.
Limitation
Our study is limited to Hospital-based quantitative study. It would be better if qualitative approach study was triangulated to investigate further factors on preterm birth. Recall biases in remembering the exact day of last normal menstrual period.
Strength
Since there were no enough studies done in an area according to the magnitude of the problem, this study contributes by alerting researchers for further study.
Abbreviations
ANC: Ante Natal Care, EDHS: Ethiopian Demographic Health Survey, HIV: Human Immune deficiency Virus, LBW: Low Birth Weight, LNMP: Last Normal Menstrual Period, NICU: Neonatal Intensive Care Unit, PROM: Premature Rupture of Membrane, PTB: Pre Term Birth, SPSS: Statistical Package for the Social Science, WHO: World Health Organization.
Data Availability
The data set used and analyzed for the current study is available from the corresponding author on a reasonable request.
Supplementary Materials
This study is reported according to the STROCSS 2021 guide line for reporting cross-sectional study [23].
Conflict of Interest
There is no conflict of interest
Funding Statement
This research did not receive any specific grant from funding agencies
Acknowledgment
We would like to forward our gratitude to Yanet College, for giving ethical clearance to conduct the research. We also submit our sincere gratitude to data collectors for their undeniable efforts. We thank our respondents for their respect and proper responses. Likewise we would like to send our special thanks to ministry of health and administrator of Gandhi, Zewditu, Menenilik and Rasdesta hospital that allows us to do this research and provide necessary information.
References
- Lumley J. Defining the problem: the epidemiology of preterm birth. BJOG: An Int J Obstetrics and Gynaecol. 2003; 110: 3-7.
- Muhumed II, Kebira JY, Mabalhin MO. Preterm Birth and Associated Factors Among Mothers Who Gave Birth in Fafen Zone Public Hospitals, Somali Regional State, Eastern Ethiopia. Research and Reports in Neonatol. 2021; 11: 23-33.
- Wade DM, Hankins M, Smyth DA, Rhone EE, Mythen MG, Howell DC, et al. Detecting acute distress and risk of future psychological morbidity in critically ill patients: validation of the intensive care psychological assessment tool. Critical Care. 2014; 18: 1-9.
- Muhe LM, McClure EM, Mekasha A, Worku B, Worku A, Dimtse A, et al. A prospective study of causes of illness and death in preterm infants in Ethiopia: the SIP study protocol. Reproductive Health. 2018; 15: 1-9.
- Wado YD. Women’s autonomy and reproductive health-care-seeking behavior in Ethiopia. Women and health. 2018; 58: 729-743.
- Moafi F, Kazemi F, Samiei Siboni F, Alimoradi Z. The relationship between food security and quality of life among pregnant women. BMC pregnancy and childbirth. 2018; 18: 1-9.
- Howson CP, Kinney MV, McDougall L, Lawn JE. Born too soon: preterm birth matters. Reproductive health. 2013; 10: 1-9.
- Li Z, Hsiao Y, Godwin J, Martin BD, Wakefield J, Clark SJ, et al. Changes in the spatial distribution of the under-five mortality rate: Small-area analysis of 122 DHS surveys in 262 subregions of 35 countries in Africa. PloS one. 2019; 14: e0210645.
- Mengesha HG, Wuneh AD, Lerebo WT, Tekle TH. Survival of neonates and predictors of their mortality in Tigray region, Northern Ethiopia: prospective cohort study. BMC pregnancy and childbirth. 2016; 16: 1-13.
- Walde MT, Enyew DB, Tusa BS, Weldesenbet AB, Bahiru N. More than one-third of pregnant women in Ethiopia had dropped out from their ANC follow-up: Evidence from the 2019 Ethiopia mini demographic and health survey. Frontiers in Global Women's Health. 2022: 89.
- Maulana R, Helms-Lorenz M, Irnidayanti Y, Van de Grift W. Autonomous motivation in the Indonesian classroom: Relationship with teacher support through the lens of self-determination theory. The Asia Pacific Education Res. 2016; 25: 441-451.
- Bekele A, Mussema Y, Tadesse Y, Taylor ME. Reaching every newborn: delivering an integrated maternal and newborn health care package. Ethiopian Medical J. 2019.
- Andualem H, Beyene T, Tuli W. Knowledge and Practice about Glasgow Coma Scale Assessment among Nurses Working in Adult Intensive Care Units of Federal Public Hospitals in Addis Ababa, Ethiopia: A Cross-Sectional Study. Ethiopian J Health Sci. 2022; 32: 895-904.
- Hardcastle K, Ford K, Bellis MA. Maternal adverse childhood experiences and their association with preterm birth: secondary analysis of data from universal health visiting. BMC pregnancy and childbirth. 2022; 22: 1-11.
- Mc Dorman MF, Thoma M, Declercq E, Howell EA. The relationship between obstetrical interventions and the increase in US preterm births. 2014-2019. Plos one. 2022; 17: e0265146.
- Abadiga M, Wakuma B, Oluma A, Fekadu G, Hiko N, Mosisa G. Determinants of preterm birth among women delivered in public hospitals of Western Ethiopia, 2020: Unmatched case-control study. PloS one. 2021; 16: e0245825.
- Zini ME, Omo-Aghoja LO. Clinical and sociodemographic correlates of preterm deliveries in two tertiary hospitals in southern Nigeria. Ghana medical J. 2019; 53: 20-28.
- Zhang J, Sun K, Zhang Y. The rising preterm birth rate in China: a cause for concern. The Lancet Global Health. 2021; 9: e1179-e80.
- Wagura P, Wasunna A, Laving A, Wamalwa D, Nganga P. Prevalence and factors associated with preterm birth at kenyatta national hospital. BMC pregnancy and childbirth. 2018; 18: 1-8.
- Earnest J, Mansi R, Bayati S, Earnest JA, Thompson SC. Resettlement experiences and resilience in refugee youth in Perth, Western Australia. BMC research notes. 2015; 8: 1-10.
- Fuchs F, Monet B, Ducruet T, Chaillet N, Audibert F. Effect of maternal age on the risk of preterm birth: A large cohort study. PloS one. 2018; 13: e0191002.
- Temu TB, Masenga G, Obure J, Mosha D, Mahande MJ. Maternal and obstetric risk factors associated with preterm delivery at a referral hospital in northern-eastern Tanzania. Asian Pacific J Reproduction. 2016; 5: 365-370.
- Mathew G, Agha R, Albrecht J, Goel P, Mukherjee I, Pai P, et al. STROCSS 2021: strengthening the reporting of cohort, cross-sectional and case-control studies in surgery. Int J Surgery Open. 2021; 37: 100430.