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Prevalence of adverse birth outcome and associated factors among women who delivered in Hawassa town governmental health institutions, south Ethiopia, in 2017

Reproductive Health201815:193

https://doi.org/10.1186/s12978-018-0631-3

  • Received: 25 July 2018
  • Accepted: 28 October 2018
  • Published:
Open Peer Review reports

Abstract

Background

Most pregnancies are unplanned in Ethiopia. This is due to ignorance of the types and efficacy of each method of contraception they are associated with vast and unpredictable complications. Most of the time, these complications result in adverse birth outcomes. Information about prevalence of adverse birth outcome and it’s factors are relevant for designing, and initiating and intervening programs to decrease these undesirable out comes.

Objective

To assess prevalence of adverse birth outcome and associated factors among women who delivered in Hawassa town governmental health institutions, south Ethiopia, in 2017.

Method

We conducted institutional based cross sectional study among 580 pregnant women from december1–30/2017, by multistage systematic random sampling method in governmental health institution in Hawassa town. Data were collected through structured pre-tested, close ended and interview administered questionnaire in their post-partum period. Collected data was entered in Epi-info version 7 and analyzed using SPSS. Odds ratio with 95% confidence interval on multivariable logistic regression was computed and P-value< 0.05 considered as significance.

Result

From a total of 580 respondents 106(18.3%) respondent’s had child related adverse birth outcome. Previous History of child related adverse pregnancy outcome 4.2 (95%,CI = 2.5–6.9), Attend at list one antenatal care visit 2.3 (95%CI = 1.1–4.3), Own cat in the house 2.2 (95%,CI = 1.3–3.7), Had any chronic disease/s 2.1(95%,CI = 1.1–4.8), Age of the mother (from 35 to 45 Years) 2.3(95%,CI = 1.1–4.8), Poor participants’ Knowledge on preconception care 3 (95%CI = 1.4–1.6) were significant predictor of adverse birth outcome in this study .

Conclusion and recommendation

Prevalence of adverse birth outcome was found to be significant in the current study. Presence of Previous History of adverse pregnancy outcome, on ante-natal attendance, presence of cat in the house, presence of chronic disease/s, younger mother and Poor Knowledge of preconception care were significant predictor of adverse pregnancy outcome. Therefore it is better to give more attention on expanding preconception and antenatal care. Creating awareness about family planning methods type and efficacy for women of reproductive health is mandatory. Services, increasing health education on personal hygiene vaccination of cats. Moreover, early detecting and treatment of chronic disease.

Keywords

  • Adverse birth outcome
  • Women
  • Hawassa town
  • 2017

Plain English summary

Most pregnancy and childbirth is a joyful experience. But it sometimes end up in adverse birth outcome which disrupt the family condition leading to high individual and social costs. Adverse birth outcome in current study includes pregnancy loss/miscarriage, congenital anomaly or birth defect, preterm baby, low birth weight, perinatal death, macrosomia and intrauterine growth restriction. Most risk factors contributing to adverse birth outcome are amenable to modification. These poor reproductive life planning, substance use, abnormal pre-gestational BMI, irrational medication use, exposure to environmental toxin and contaminants, underlying chronic pre-gestational diseases, anemia and folic acid deficiency, poor regular exercise and physical activity, and presence of stress are included.

The current study use a multistage systematic random sampling technique to select the study participants. Data was collected using a validated structured pre-tested interviewer-administered questionnaire. From a total of 580 respondents 106 (18.3%) respondents had child related adverse birth outcome. Previous history of child-related adverse birth outcome, nonattendance to antenatal care owning cat in the house, having any chronic diseases, being in the age group from, and having poor knowledge about preconception care were found to be significant predictor of child-related adverse birth outcome. In conclusion: Overall prevalence of child-related abnormal birth outcome was found to be significant. Almost all predictors found as significant predictors of abnormal birth outcome are all preconception risk factors. Focusing on prevention and management of preconception risk factors through the provision of preconception care along with early engagement in maternity care continuums is highly advised.

Background

Adverse birth outcome is a critical health issue in developing countries like Ethiopia. It resulted in many bad consequences neonatal and infant morbidity and mortality. Globally, 15 million babies are born too prematurely each year. More than a million of them die immediately after birth; many other suffer from lifelong physical, neurological, or educational disabilities [1].

According to Ethiopian Demographic and Health Survey in 2016, there was high rate of perinatal mortality. Thirty-three death per 1000 live birth was reported. It was associated with increased maternal age, primi-parity, pregnancy interval of less than 15 months and urban residence [2].

Neonatal mortality has shown less improvement than under five mortality in Ethiopia. A modeled data, indicate that Ethiopia reduced its under five mortality rate to 64/1000 live birth in 2013. It is a 69% reduction since 1990 [3]. The amazing fact here is that almost half of neonatal mortality can be prevented through tetanus toxoid vaccine, clean and skilled care at the birth, newborn resuscitation, exclusive breastfeeding, clean umbilical cord care, and management of infections in the newborns [4].

Increased number of intrauterine growth restriction is caused by low pregnancy body mass index, low short maternal stature and gestational weight. This finally leads to many low birth weight neonates in developing countries [5]. A study conducted in northern Ethiopia indicates that there were 63 deaths per 1000 live births. Among these deaths two thirds (34%) were attributable to prematurity and 21 (31%) deaths are caused by asphyxia [6].

Adverse pregnancy outcome generally increase with age. A study conducted in Nigeria, 2012 indicated that perinatal mortality, intrauterine fetal death, and neonatal death increased with age [7]. As evidenced by many research findings, adverse pregnancy outcomes had both child and maternal short term and long term undesirable effects. A study conducted in North West Ethiopia, 2016 showed that Low birth weight and preterm delivery increased the risk of asthma at age of 7 [8]. A study conducted in Nepal, 2013 showed that birth order of the child, with which wantedness is inextricably linked, has more powerful and pervasive effects, with first-born and second-born children being much less likely to show adverse effects [8]. Experiencing intimate partner violence during pregnancy has been associated with women’s increased risk of antepartum hemorrhage, and perinatal death. [9] A study conducted in Boricha district of Sidama zone, southern Ethiopia,2014, indicates that having had a neonatal, infant and/or child deaths was associated with symptoms of depression at 14-year follow-up [10].

The achievement of sustainable development goal is highly associated with declining of neonatal death. Though, there are studies on the various forms of adverse birth outcomes particularly in developing countries and few part of Ethiopia, there is limited data on the overall adverse birth outcome at country level specifically at Hawassa town governmental health institution. Therefore, the aim of this study is to determine the prevalence and associated factor of adverse birth outcomes among women who give birth in Governmental health institution in Hawassa town.

Methods and materials

Study area and period

Hawassa city administration is a capital city of southern nation nationality people region and located 275 km South from Addis Ababa. Hawassa city in which 359,358 people are living according to city’s Health Department Estimation in 2017, has been structured by 7 urban sub-cities collectively have 21 kebeles and 1 Rural sub-city includes 11 kebeles. The city has 83 public and private health institutions. In detail, these are one public referral and teaching hospital, one public general hospital, four private primary hospitals, 9 Public Health Centers, 17 Public Health Posts and 51 Private Clinics.

There are about a total of 852 health professionals working in the randomly selected PHIs of the city. Together with about 600 health professionals working in Hawassa University Comprehensive Specialized Hospital, the number reached1452.

Hawassa University Comprehensive Specialized Hospital is the largest hospital in southern Ethiopia with more than 300 beds which renders service to both the people in the region and other people coming from the neighboring region. The hospital was established in 2004/05, provides specialized services and comprehensive health services (prevention, treatment and research). The outpatient department consists of 17 rooms and inpatient service consists of five main departments. The average number of patients flow at the outpatient department is more than 200 people per day. The Hawassa University Comprehensive Specialized Hospital and Adare General Hospital are the only public health hospitals providing comprehensive essential obstetric care in the City. The remaining nine PHC are giving Basic essential obstetric care. In the past 6 months of the year 2009, there were a total of 4780 deliveries reported from Hawassa University Comprehensive Specialized Hospital (2073), Adare General public health officer (2022), Adare primary health care (313), Millennium primary health care (311), and Tilte primary health care (61).

Study variables

The dependent variable was the ‘overall adverse birth outcomes ’. Whereas, the independent variables tested in this study included factors grouped into five categories. The first category includes socio-demographic factors such as age, parity, educational status, religion, occupation, partner’s occupation, residence, and family size. The next category is the mother’s current obstetric condition. This obstetric condition includes parity, gravidity, antenatal care attendance, gestation, pregnancy complication, birth order, and mother’s age at current pregnancy.

The third category is the presence of pre-existing medical conditions. This included conditions such as diabetes mellitus, hypertension, cardiac disease, HIV/AIDS, anemia, malaria, and oral health status. The preconception risk factors occurring before pregnancy such as the woman’s pregnancy intention, psychoactive substance use, coffee consumption, pre-gestational BMI, periodontal disease, medication use, previous history of, the use of traditional medicine, environmental exposure, pre-gestational disease, preconception folic acid supplementation use status, presence of external stressors, familial/genetic history, medical insurance status, physical abuse, women’s preconception health/care knowledge, inter-pregnancy interval, regular exercise, and uptake of preconception counseling. The last or fifth category is health facility-related factors. This included factors such as availability of health facility, distance, and cost of service.

Operational definition

‘Adverse birth outcome” in this study implies the presence of at least one or more of the following conditions in the current pregnancies. These include fetal loss/miscarriage, low birth weight, congenital anomaly, and preterm labour. Thus, if the mothers admitted to the labour ward gave birth to a baby with a congenital anomaly, low birth weight, preterm labour, small for gestational age, perinatal death, macrosomia then the these were labeled as “mothers with a child-related adverse birth outcome. Those who gave normal live birth, without the above mentioned abnormal birth outcome , were labeled as “mothers with normal child related pregnancy outcome”.

Perinatal mortality: Is defined as deaths inside uterus (Macerated and fresh stillbirths) and early neonatal deaths (first week of life).Perinatal mortality rate is the sum of both of them per 1000 total deliveries [11].

Miscarriage: Is the natural death of an embryo or fetus before it is able to survive independently [12].

Low birth weight: The weight of the newborn < 2.5 kg [13].

Preterm labour: Preterm labor is defined as regular contractions of the uterus resulting in changes in the cervix that start before 37 weeks of pregnancy [14].

Macrosomia: Macrosomia is defined as birth-weight over 4000 g irrespective of gestational age [15].

Congenital anomaly: A congenital anomaly defined as any abnormality of physical structure found at birth or during the first few weeks of life; or any irreversible condition exiting in a child before birth in which there is sufficient deviation in the usual number, size, shape, location of any part, organ, cell to warrant its designation as abnormal [16, 17].

Sample size and sampling procedures

At first stage, out of the 11 public health institutions, five public health institutions were selected using simple random sampling technique. At the second stage, we applied a systematic random sampling method to identify and include all the study participants. The calculated sampling interval (K) was 1.2. Based on the finding we consecutively recruited the study subject’s i.e. using SRS up until the minimum sample size obtained. This is in accord with the assumption that deliveries in nature happened randomly. The samples were taken proportionate to the number of expected deliveries from each selected PHIs. All participants included in the study were all consented verbally to participate in the study. Excluded out of the study were mothers with a twin pregnancy.

Study design and population

A cross-sectional study was conducted among women giving birth in public health institution of Hawassa City Administration. The source populations were all pregnant women living in the Hawassa City Administration. Whereas, the study population were those laboring mothers who attended the randomly selected public health institutions for delivery service during the study period.

This study applied a multistage sampling technique to identify a total of 580 study participants.

The sample size required for this study was determined using the formula for estimating single population proportion. Since there is no research (as per the investigators best systematic literature search) no published article reported the overall prevalence of abnormal birth outcome, and also the proportion of client’s attitude towards preconception care. Thus a prevalence value of 0.5 was assumed to calculate the minimum sample size. On the basis of this assumption the minimum possible sample size (n) sufficient enough to meet objectives of the study. The sample size determination considered the following assumptions. This included a 95% confidence interval (CI), a margin of error (α = 0.05), population correction factor, a design effect of 2 and 10% non-response rate.

Data collection and analysis

The principal investigator developed the instrument used in this study by referring to various literatures. The instrument is developed based on the objectives of the study. It was primarily designed to measure all the variables listed in the preceding two paragraphs. The instrument was a validated interviewer-administered questionnaire. The instrument was first developed in English and translated into Amharic and then back to English to check the accuracy. Before the actual data collection, the questionnaire was tested on 10% of health care providers working in Public health Institutions of a nearby town called Shashemene.

Every woman who came to deliver in the selected primary health institutions during the data collection period was all interviewed. In addition to the interview, the data collectors abstracted clinical data by reviewing the mother and the babies’ medical records. They also measured and confirmed the baby’s birth weight, and conducted selected examinations for which they get additional training. The Data was collected by 5 BSC female midwives and 5 BSC female nurses after one-day Training about informed consent, techniques of interviewing, data collection procedures, and different sections of the questionnaire. Two health officers were assigned as Supervisors for the data collectors.

Overall supervision also made by the Principal Investigators. All collected questionnaires were rechecked for completeness and coded. Then these data were entered and cleaned using SPSS version 20 for analysis. Bivariable and multivariable logistic regression was employed to identify an association between the independent predictors and the outcome variable i.e. “child-related adverse birth outcome”. Those factors found with their P-value ≤0.20 in the bi-variable logistic regression model were fitted into the multivariable logistic regression model to control the effect of confounding variables. Multivariable analysis using standard logistic regression technique was done to evaluate the independent effect of each covariate on ‘child-related adverse birth outcome by controlling the effect of others. Variable having P-value of less than 0.05 in the multivariable logistic regression analysis was considered as significantly associated factors of ‘child-related adverse birth outcome ’. The adjusted odds ratios with the 95% Confidence Intervals (CI) were reported. Before the actual logistic regression analysis was done, the necessary assumption of logistic regression model was checked by using Hosmer-Lemeshow test of goodness of fit which has a chi-square distribution. For further analysis, descriptive statistics like frequencies and cross tabulation were performed. Tables and bar chart were used to present the findings of the study.

Result

Socio-demographic characteristics

From a total of 580 women delivered at governmental health institutions in Hawassa town, all participated fully in this study making a response rate of 100%. The mean age of respondents is 25.63 + 4.9 years. Majorities 492(84.6%) were in the age range of 20–34 years. Most of the study participants 560(96.6%) were married. More than half, 325(56%), of participants attended in elementary education. Whereas, only few (8.3%) attended college or university level education.

Most of the study participants (68.8%) were housewives and the greater proportion (78.6%) had a family size less than five person per a household. From the total of 580 study participants, most 375(64.7%) of the study participants were living in urban (Table 1). Almost equal number of respondent's partner (50.5%) use family planing methods (see Table 2).
Table 1

Socio-demographic characteristics women in postpartum period in Hawassa university referral hospital, southern Ethiopia, 2017(n = 580)

Variables

Categories

N

Percent (%)

AGE

< 20

45

7.8

20–34

492

84.6

35–49

43

7.4

Religion

protestant

293

50.5

Orthodox

157

27.1

Muslim

87

15

catholic

8

1.4

others

13

2.2

Marital status

Married

560

96.6

Single

20

3.4

Ethnicity

sidama

232

40

Amhara

42

7.2

Gurauge

46

7.9

Oromo

115

19.8

wolayta

106

18.3

silte

39

6.8

educational status

no formal education

110

19

Primary education (1–8 grade)

325

56

Secondary education (9–12 grade)

97

16.7

Tertiary (college or university)

48

8.3

Women’s occupation

housewife

399

68.8

private business

87

15

daily worker

14

2.4

salaried employed

61

10.5

Student

19

3.3

Husband occupation

Farmer

153

26.4

Daily worker

41

7.1

private business

237

40.9

salaried employed

124

21.4

Student

3

0.5

others

22

3.8

Monthly income

< 1000 ETB

174

30

1001–2000 ETB

119

20

2001–3675 ETB

142

25

> 3675 ETB

145

24

Total family size

< 5

456

78.6

5–6

89

15.3

> 6

35

6

residence

urban

375

64.7

rural

150

25.9

peri-urban

55

9.4

keyETB = ethiopian birr(1US$ = 27ETB)

Table 2

Reproductive characteristics of women in postpartum period in Hawassa university referral hospital, southern Ethiopia, 2017(n = 580)

Variables

Categories

Frequency

Percent

Did you or your partner use FP?

Yes

293

50.5

No

287

49.5

what type of FP do you use? (n = 293)

coc

38

6.6

Depo

189

32.6

Implanon

23

4

iucd

34

5.9

Natural

8

1.4

no FP

287

49.5

Do you plan this pregnancy?

Yes

520

89.7

no

60

10.3

Gestational age of the current pregnancy?

preterm

58

10

term

519

89.5

post term

3

0.5

Did the mother had at least 1 ANC visit?

yes

521

89.8

no

59

10.2

mode of delivery

SVD

461

9.5

instrumental

11

1.9

CS

108

18.6

sex of the current baby?

male

330

56.9

female

250

43.1

future pregnancy intention

up to 6moth

1

0.2

7–12 months

2

0.3

13–24 months

9

1.6

25–36 months

8

1.4

after 3 years

132

22.8

undecided

375

64.7

I don’t want any more

531

9.1

KEY=FP family planning, IUCD intrauterine contraceptive device, SVD spontaneous vertex delivery, CS cesarean section

Maternal related adverse pregnancy outcome

Pregnancy induced hpertension which account(4.3%) is the observed predominant maernal related adverse outcome (Fig. 1).

Prevalence of adverse pregnancy outcomes

The current study reveal that 472(81.3%) births are normal live births, while the remaining 108(18.6%) births were births with child related adverse birth outcomes. The current study identified 7 types of abnormal birth outcome. Out of which 67 (11.6%) was low birth weight and the perinatal death was 16(2.7%). The magnitude of congenital anomaly was 6(1%). The study also identified two types of abnormal birth outcome among 33 (5%) of the newborns (Table 3).
Table 3

Magnitudes and types of adverse pregnancy outcome related to the child among deliveries attended in public health institutions of Hawassa, Southern Ethiopia 2017

S.N

List of adverse pregnancy outcomes

Frequency

Percent

1

Perinatal death

No

564

97.2

Yes

16

2.7

Total

580

100.0

3

Preterm baby or birth (PB)

No

559

96.4

Yes

21

3.6

Total

580

100.0

4

Congenital anomaly

No

574

99.0

Yes

6

1.0

Total

580

100.0

5

Macrosomia

No

517

89.13

Yes

63

10.86

Total

580

100.0

6

IUGR

No

577

99.5

Yes

3

.5

Total

580

100.0

7

Low Birth Weight

No

513

88.4

Yes

67

11.6

Total

580

100.0

8

Number of APOs observed in a new birth

No APO observed

474

81.7

Only 1 APO observed

73

12.6

Two (2) types of APO observed

33

5.7

Total

580

100.0

9

Over all APO related to the child

No APO

474

81.7

APO

106

18.3

Total

580

100.0

KEY

LBW low birth weight

Predictors of overall adverse pregnancy outcomes identified

This study identified six statistically significant predictors of adverse pregnancy outcomes related to the child. The chance of developing an abnormal birth outcome among mothers with a previous history of child-related abnormal birth outcomes was by four times higher than those mothers who didn’t have the history (AOR = 4.2, 95% CI: 2.5–6.9). Compared to mothers within the age range 20–34 years, those mothers within the age range 35–45 had two-fold higher odds of giving birth to a baby with APO than those mothers who aged 20–34 years (AOR = 2.3, 95% CI: 1.1–4.2). Non attendance to antenatal care, in contrast to attending at least one ANC, showed an increased odd of APO (AOR = 2.2, 95% CI: 1.1–4.3). The likely hood of giving a baby with an adverse pregnancy outcome was by two times higher among those mothers owned a cat in their house (AOR = 2.2, 95% CI: 1.3–3.7) and those who had any chronic diseases(AOR = 2.2, 95% CI: 1.1–4.8). The analysis also revealed that the odds of giving birth to a baby with APO are by three-fold higher among mother with poor preconception care/health knowledge than those with good preconception care/health knowledge (AOR = 3.0, 95% CI: 1.4–6.6) (Tables 3 and 4).
Table 4

Predictors of child related adverse pregnancy outcome from backward stepwise (Wald) logistic regression, in Governmental health institutions, Hawassa Ethiopia, 2017

Predictors

Adverse pregnancy outcome (APO)

COR[95%CI]

AOR[95%CI]

No APO

Yes APO

Previous History of child related APO

Yes

87

48

2.3(1.3–4.1) *

4.2(2.5–6.9)***

No

387

58

1§

1

Previous History of maternal APO

Yes

42

19

3.7(2.4–5.8) ***

1.7(0.8–3.6)

No

432

87

1

1

Age of the Mother

20–34 Years

411

81

1

1

18–19 Years

27

16

1.3(0.6–2.7)

1.5(0.6–3.7)

35–45 Years

36

9

3.0(1.6–5.8) **

2.3(1.1–4.8) *

Attend at list one ANC visit

Not attended

40

19

2.4(1.3–4.3) *

2.2(1.1–4.3)*

Attended

434

87

1

1

Duration b/n the current & previous pregnancies in months

1st pregnancy

229

38

1

1

<  12 Months

21

14

4.0(1.9–8.6) ***

2.3 (0.9–5.4)

12–17 Months

29

8

1.7(0.7–3.9)

1.3(0.5–3.3)

18–23 Months

66

17

1.6(0.8–2.9)

1.6(0.8–3.3)

> 24 Months

129

29

1.4(0.8–2.3)

0.7(0.4–1.3)

Anemia in current pregnancy

Yes

60

21

1.7(0.9–3.0)

1.5(0.8–2.8)

No

414

85

1

1

Own cat in the house?

Yes

162

55

1.8(1.2–2.7) *

2.2(1.3–3.7) **

No

312

51

1

1

Had any chronic disease/s

Yes

34

16

2.3(1.2–4.4)*

2.2(1.1–4.8)*

No

440

90

1

1

Mothers’ PCC knowledge

Good Knowledge

105

10

1

1

Fair Knowledge

139

25

1.9(0.9–4.1)

2.2(0.9–5.5)

Poor Knowledge

230

71

3.2(1.6–6.5) **

3.0(1.4–6.6) *

Monthly income

≤1000.0birr

133

41

1.8(1.1–3.3)*

1.4(0.7–2.7)

1001.0-2000.0birr

99

20

1.2(0.6–2.3)

1.1(0.5–2.4)

2001.0 -3675.0 birr

118

24

1.2(0.6–2.3)

1.2(0.6–2.4)

≥ 3676 birr

124

21

1

1

Key 1 = references group, * = PV < 0.05, ** = PV < 0.001, *** = PV < 0.0001, CI confidence interval, COR crude odds ratio, AOR adjusted odds ratio, ANC antenatal care, PCC preconception care, ETB Ethiopian birr(1$ = 27ETB)

Discussion

This study aimed to assess the overall prevalence of abnormal birth outcome and preconception risk factors contributing to child-related abnormal birth outcome among deliveries attended in primary health institutions of Hawassa. All women approached to be included in the study attended the study. This makes the response rate 100%. The overall prevalence of adverse birth outcome in the current study was found to be 18.6% (95%CI = 0.3–38.6%). Whereas, the types and proportions of the specific abnormal birth outcome identified in this study were; low birth weight 67(11.6%), macrosomia 26(4.5%), preterm birth 21(3.6%), congenital anomaly 6(1.0%), intrauterine growth restriction 3(0.5%), and perinatal death 16 (2.7%).
Fig. 1
Fig. 1

Maternal related adverse obstetrics complications of women in Governmental health institutions in Hawassa town, southern Ethiopia, 2017. (n=580)

The magnitude of abnormal birth outcome in the current study is significant. Compared to other similar study findings reported from Ethiopia [18, 19], the prevalence of the overall abnormal birth outcome identified in this study is low. The possible explanation for this discrepancy may be attributable to socioeconomic variations and the difference in the quality of maternal health service. In addition the variation with regard to nutritional and cultural practices may also contribute to the observed differences.

Moreover, since most of the current study participants were urban residence their level of knowledge and utilization of health service might be the other reason to the observed lower abnormal birth outcome. Except for the mother’s non-attendance to ante natal care, all of the five predictors identified in the current studies are preconception risk factors contributing to the development of child-related abnormal birth outcome. Similar to two studies in Gondar [18]and Dessie [20], the odds of giving birth to a baby with abnormal birth outcome was found higher than those mothers who attended antenatal care (AOR = 2.2, 95% CI: 1.1–4.2). In Ethiopia, non-attendance to antenatal care is one of the most important public health problems which preconception care intervention can solve. There is an evidence that the odd of uptake of antenatal care is higher among mothers who get preconception care than those who are not getting the service [21]. In Ethiopia, for the past two decades, the antenatal care service uptake remained very low. This is evident from those national demographic health survey reported an increase from 27% in 2000 to 62% in 2016 [2]. This sluggish increment in antenatal care attendance may be accelerated by the introduction of preconception service in the countries health care system. As one study denoted, despite the world health organization’s recommendation, preconception care is not yet formally and officially introduced in the Ethiopian health care system [22].

The chance of developing an abnormal birth outcome among mothers with a previous history of child-related abnormal birth outcome was by four times higher than those mothers who had not had the history (AOR = 4.1, 95% CI:2.5–6.8). Having had a child with abnormal birth outcome, in the previous pregnancy/ies, is one of the most important predictors of all the five predictors identified in this study. A similar study conducted in Shire town of North Ethiopia showed the fact those mothers with the previous history of child related abnormal birth outcome are at greater risk of giving birth to a baby with [19]. There is well-established evidence that previous history of abnormal birth outcome is a risk factor to the occurrence of abnormal birth outcome in subsequent pregnancies. Significant proportion 135(23.3%) of the study participants, in the current study, had a history of child-related adverse pregnancy outcomes. Through preconception care the healthcare, the provider can screen out such risk factors prior to pregnancy. This preventive preconception care intervention is one of the recommended evidence-based practice to solve the occurrence of similar abnormal birth outcome in subsequent pregnancies. One study showed the need and uptake of preconception care are higher among women with previous history abnormal birth outcome [23].

Similarly, the odd of giving birth to a baby with abnormal birth outcome was by 2 times higher among women with chronic diseases than those who didn’t have(AOR = 2.3, 95% CI: 1.1–4.9). This finding is consistent with a study conducted at Dessie [20]. Chronic diseases such as diabetes, hypertension, asthma, epilepsy, depression are well-known risk factors to abnormal birth outcome [24, 25]. Early identification and management of chronic diseases including mental health, prior to conception, is proven to bring a normal pregnancy outcome [4]. Delaying pregnancy until the control of the underlying chronic diseases is one of the objectives of preconception care. This is managed by using preconception family planning service and effective medical care. Nevertheless, there is high the unmet need for family planning among this group of people. Those women with chronic medical conditions are at risk of abnormal birth outcome demanding preconception care [26].There is evidence that advanced maternal age is a risk factor for the occurrences of both maternal and child related abnormal birth outcome s [27]. In line with these evidence, this study revealed a twofold higher odds of abnormal birth outcome among women in the age group 35–45 Years than those in the age group 20-34 years (AOR = 2.395% CI: 1.1–4.8). The co-occurrence of chronic diseases with pregnancy is common. This is one of the cases that complicate the outcome of pregnancies. Though, an advanced maternal age is one of the non-modifiable risk factors for pregnancy, early enrolment of women in preconception care may help couples to make a wise reproductive plan [26]. Those women with a poor knowledge of preconception health/care were 3 times (AOR = .3.0,95%, CI: 1.4–6.6) more likely to have an abnormal birth outcome than those who had good knowledge. A community-based study conducted at Adet, North Ethiopia, showed poor knowledge among the vast majority of the women [28]). If the woman has appropriate knowledge of preconception health and care, she can seek or easily attend to the preconception care service. This can help her to easily identify and effectively control the underlying risk condition that leads to abnormal birth outcome. Health care providers participated in one research reported that poor awareness or knowledge of preconception health and care as a barrier to the uptake and delivery of preconception care [28]. Another systematic study that investigated the reasons why women are not using preconception care reported poor PCC knowledge and awareness as a barrier to preconception care uptake [29].

The last predictor identified by the current study showed that those women who have cat in their house had two times higher odds of abnormal birth outcome than those who didn’t have (AOR = 2.3, 95% CI: 1.4–3.8). The possible explanation for this result may be toxoplasmosis infection that uses cats as a reservoir can lead leads adverse birth outcome like premature birth and low birth weight. Studies conducted at different areas of Ethiopia showed high prevalence of Sero-prevalence of Toxoplasma gondii (T.gondii) antibodies for IgM among pregnant women [3032]. This studies reported that contact with cat or cat ownership as factors that increased the odds of women’s to T.gondii infection and recommended avoidance of contact with cats and avoidance of raw and under cooked foods [3133]).

In general this study identified five preconception risk factors or that increased the mothers odds of giving birth to a baby with abnormal birth outcome. Nevertheless, his study is not without limitation. Some of participants of the study may not remember some of the questions. This may lead to underreporting of the findings reported in this study. For some of the variables, such as previous history of abnormal birth outcomes, this study relied on the study participants verbal response. This study never included abnormal birth outcomes s happening at an and post pregnancy period. This include abnormal birth outcome such as miscourage, pregnancy loss, neonatal and infant death. As a cross sectional study this study do didn’t determined causal relationship and also temporal relationship. Despite this study, might tried to focus on preconception risk factors contributing to abnormal birth outcomes. To the best of authors best systematic search, there are not published articles reported preconception risk factors contributing to abnormal birth outcomes in Ethiopia.

Conclusion and recommendation

The prevalence of the overall adverse birth outcome is significant. Previous History of child related abnormal birth outcomes, women’s poor knowledge of preconception health/care, having any chronic diseases, advanced maternal age (35–45 years), and having a cat in the house were all preconception risk factors that increased the likelihood of developing child related abnormal birth outcomes. Non attendance to antenatal care was the other factor that increased the odds of the occurrence of abnormal birth outcomes. Provision of preconception and inter-conception care is the best approach to the identification and early management of risk factors to abnormal birth outcomes. The continuums of the maternal and child health care services are incomplete without the inclusion of PCC. Adverse pregnancy outcome reduction strategies should consider early identification and management of the preconception risk factors. The preconception care should include educating all eligible or reproductive-aged couples about preconception care/health. Creating awareness about family planning methods type and efficacy for women of reproductive health is mandatory.

Abbreviations

ABO: 

Adverse birth outcome

AOR: 

Adjusted odds ratios

CI: 

Confidence interval

COR: 

Crudes odds ratios

CSA: 

Central Statistical Agency

EDHS: 

Ethiopian Demographic and Health survey

PCC: 

Preconception care

Declarations

Acknowledgements

Our heartfelt gratitude is to supervisors, data collectors, and all study participants. Our particular appreciation goes to Mr. Arega Donka who supervised the overall data collection process. Finally, we would like to thank Hawassa University for funding the research project.

Funding

There was no any funding or sponsoring organization for this paper.

Availability of data and materials

We have sent all the available data and we do not want to share the raw data as we are doing related study.

Authors’ contributions

AK conceived the study and wrote the proposal, facilitated data collection, analysis, data interpretation, drafted the final report write up and prepared manuscript. BT, participated in developing the tools and data collection process, data analysis and involved in report write up. Both the authors revised the subsequent drafts of the paper and read and approved the final manuscript.

Ethics approval and consent to participate

Ethical clearance was obtained from Department of Midwifery, College of Medicine and Health Sciences, Hawassa university institutional review committee and letter of approval was granted. Finally, each participant gave their informed verbal consent or parents and/or guardians provided consent on behalf of participates below 18 years old. Confidentiality was assured by making the questionnaire anonymous.

Consent for publication

Not applicable

Competing interests

The authors declare that they have no competing interests.

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Authors’ Affiliations

(1)
Department of Midwifery, College of Medicine and Health Sciences, Hawassa University, P.O. Box 1560, Hawassa, Ethiopia

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Copyright

© The Author(s). 2018

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