Abstract
Background
Adverse birth outcome which attributes to most perinatal deaths is an important indicator of child health and survival. Hence, this study aims to identify determinants of adverse birth outcome among mothers who gave birth in public hospitals of Tigrai region, North Ethiopia.
Methods
Hospital based case-control study was conducted in Tigrai region, Ethiopia between December 2015 and January 2016 among 405 (135 cases and 270 controls) consecutively selected mothers who gave birth in four randomly selected public Hospitals. Mothers with adverse birth outcome (preterm birth; < 37 gestational weeks at birth, low birth weight; < 2.5 kg at birth, or still birth) were the cases while mothers without adverse birth outcome (live birth, birth weight ≥ 2.5 kg and of ≥37 gestational weeks at birth) were the controls. Data were collected by interview and reviewing medical records using structured questionnaire. The collected data were entered into database using EPI info version 3.5.1 then exported to SPSS version 21 for analysis. Finally, multivariate logistic regression was used to identify determinants of adverse birth outcomes at P value < 0.05.
Result
The mean age of cases and controls was 27.3 (SD = 6.6) and 26.14 (SD = 4.9) years, respectively. In a multivariate analysis; less than four antenatal care visits [AOR = 4.35, 95% CI: 1.15–13.50], not receiving dietary counseling [AOR = 11.24, 95% CI: 3.92–36.60], not using family planning methods [AOR = 4.06, 95% CI:1.35–17.34], less than 24 months inter pregnancy interval [AOR = 5.21, 95% CI: 1.89–13.86], and less than 11 g/dl hemoglobin level [AOR = 4.86, 95% CI: 1.83–14.01] were significantly associated with adverse birth outcomes.
Conclusion and recommendation
The number of antenatal care visits, ever use of family planning methods, not receiving dietary counseling during antenatal care follow up visits, short inter-pregnancy interval, and low hemoglobin level were identified as independent determinants of adverse birth outcome. A concerted effort should be taken improve family planning use, and antenatal care follow-up with special emphasis to maternal nutrition to prevent adverse birth outcomes.
Keywords: Adverse birth outcome, Ethiopia, Low birth weight, Preterm birth, Still birth
Background
Adverse birth outcome defined as low birth weight (LBW); birth weight < 2.5 kg, preterm birth (PTB); < 37 gestational weeks at birth) and stillbirth (fetal death at or after 28 gestational weeks) continues to be public health problem globally mainly in developing countries [1–8]. In 2013, nearly 22 million newborns which accounted for 16% of all babies born globally had low birth weight predominantly in Asia and Africa [8]. Almost all of the stillbirths (98%) occurred in low and middle income countries (LMICs) and nearly three fourth (77%) of the total stillbirths were in Sub-Saharan Africa and South Asia [9, 10]. About half of all stillbirths (1.3 million) occurred during labor and birth [10]. By most recent estimates, 14·9 million babies were born preterm in 2010, accounting for 11.1% of all live births worldwide [2]. According to this study, more than six in ten preterm births were in south Asia and sub-Saharan Africa, where more than half of the global live births occur [2]. Like other developing countries, evidences show that adverse birth outcome is highly prevalent in Ethiopia. For instance, recently conducted study showed that nearly one fourth (23%) of women experience adverse birth outcomes (14.3% preterm, 11.2% low birth weight and 7.1% stillbirth) [11].
Though adverse birth outcomes and their consequences are preventable [1, 6, 12, 13], preterm birth and low birth weight are major determinants of perinatal and child mortality and for survivors long term adverse health consequences mainly in low and middle income countries (LMICs) [1, 4, 5, 7, 14–19]. That is, preterm birth has significant contribution in child mortality. Complications of preterm birth caused 15.4% of the estimated 6.3 million under five children who died in 2013. Preterm birth is the leading cause of death amongst neonates (death in the first 28 days of life) [1]. Similarly, children with low birth weight have higher risk of perinatal death (still birth and neonatal death), and post-neonatal death [5, 7, 19, 20]. For survivors, preterm birth and low birth weight increases risk of stunting (chronic malnutrition), metabolic disorders and chronic non-communicable diseases [16, 18].
Different studies revealed that different factors could contribute for adverse birth outcome; for instance socio-demographic characteristics such as residence [21], age, marital status, education [22], occupation [23], and low socioeconomic status [24]. Related to reproductive and obstetric characteristics; parity, gravidity, birth interval [25], pregnancy plan [26], maternal nutritional status [2, 21, 23, 24, 27], past history of stillbirth, age of sexual debut [23], prolonged and obstructed labor [28], caesarean section delivery [19], history of preterm birth antepartum hemorrhage, and history of perinatal death [11]. Besides to this, maternal health service related factors like longer distance to walk to health facilities [21, 24], and lack of antenatal care follow-up [11, 20, 22, 24]. Additionally environmental factors such as water supply [29], washing hands with water only, not having separate kitchen room, using firewood for cooking, and using kerosene for cooking [30] could predict adverse birth outcomes.
To investigate the problem, epidemiological data pertaining to determinants of adverse birth outcome are required for planning and implementing proper interventions. However, determinants of adverse birth outcomes are poorly documented and understood in the study area. Therefore, local epidemiological studies are fundamental, to assess determinants of adverse birth outcome and identify target areas for future interventions. Thus, this hospital based case control study aims to identify determinants of adverse birth outcome among mothers who gave birth in public hospitals, Tigrai region, North Ethiopia.
Methods
Study design, setting and population
Hospital based unmatched case-control study was conducted from December 2015 to January 2016 among mothers who gave birth in four randomly selected public hospitals to identify determinants of adverse birth outcome. The study was conducted in Tigrai region, northern Ethiopia. The region is administratively divided into 7 zones, 52 woredas and 814 Kebeles (kebele is the smallest administrative unit in Ethiopia). In Tigrai regional state, there are 2 comprehensive specialized hospitals, 15 general hospitals, 20 primary hospitals, 204 health centers, 712 health posts and over 500 private health facilities. Our study was conducted in general hospitals. General hospitals provide inpatient and outpatient services, including maternal and child care. General hospitals also serve as a referral center for primary hospitals. Hence the setups of the general hospitals are similar in kind of services they deliver, health information recording system, and in number and qualification of health professional required.
According to the 2007 census projection, the total population of Tigrai regional state is 5,055,999 (50.8% females and 49.2% males). A total estimated number of 116,506 births have been registered annually in the region. For this particular study, the source population was all mothers who gave birth and infants in pair in general hospitals in Tigrai region, Northern Ethiopia. Cases were mothers with adverse birth outcome (preterm birth; < 37 gestational weeks at birth, low birth weight; weight of < 2.5 kg at birth, or stillbirth), and controls were mothers without adverse birth outcome (live birth, weight ≥ 2.5 kg at birth and ≥ 37 gestational weeks at birth).
Sample size and sampling procedure
The sample size was determined using EPI-Info 3.5.1 statistical software. The assumptions for the sample size calculation were: proportion of non-educated mothers among controls [30], minimum detectable odds ratio of 2, confidence level of 95%, power of 80%, a case to control ratio of 1:2 and non-response rate of 5%. The total sample size was 418 (139 cases and 279 controls). From the public hospitals that provide institutional delivery services in Tigrai region, four hospitals were selected randomly. Considering the number of mothers who gave birth at each of the selected hospitals in four months prior to the data collection time, the average number of mothers expected to give birth per month in each of the respective hospitals was estimated. Then, the total sample size was allocated proportionally to each of the four randomly selected hospitals. Finally, cases and controls were selected consecutively until the allocated sample was reached at each hospital. Eventually, a total of 405 mothers (135 cases and 270 controls) were participated in this study.
Data collection tool and procedure
Data were collected by interview using structured questionnaire adopted from Ethiopian Demographic and Health Survey and other related literatures [11, 20–22, 25, 26, 28, 30–32]. In addition, medical records were also reviewed. The questionnaire was translated into Tigrigna, which is the local language of the study area. The contents of the questionnaire included: socio-demographic and economic characteristics, reproductive and obstetric factors, maternal service utilization and birth outcomes. Prior to data collection, the questionnaire was pre-tested on 20 of mothers who gave birth at Axum St. Marry Hospital. Necessary modifications were made based on the nature of gap identified in the questionnaire. Mothers with their newborn pairs were the study participants. The mothers were interviewed and birth weight of the newborn was evaluated by trained midwives. The socio-demographic characteristics, reproductive and obstetric factors, and maternal health services information was collected from the mothers whereas birth weight was measured from newborns. Furthermore, the data collection process was closely monitored by the principal investigators. Both data collectors and supervisors were trained for two days on the objectives of the study, sampling technique, ethical consideration, data collection tool and techniques of collecting data to maintain precaution throughout the study. The collected data were checked daily for completeness by the supervisors and feedback was provided to data collectors when necessary.
The weight of the newborns was measured using a Salter’s hang-up scale to the nearest 100 g following standard techniques within 15 min after delivery and basic newborn care has been given. The newborns were weighted naked or in minimal clothing. Maternal MUAC (mid upper arm circumference) was also measured following the appropriate procedure to the nearest centimeter using the standard measuring tape.
Data processing and analysis
Data were coded, cleaned, edited and entered to EPI info version 3.5.1 and exported to SPSS version 21 for analysis. Descriptive statistics such as means and proportions were used to summarize the data. In this study, cases were coded as 1 and controls were coded as 0. Bivariate logistic regression analysis was used to see the unadjusted effect of each independent variable on the dependent variable of the study. Considering all independent variables with a p < 0.25 in the bivariate analyses as candidates, multivariable logistic regression model was fitted to identify independent determinants of adverse birth outcome. Finally, variables at a P < 0.05 were considered statistically significant in the final multivariable logistic regression model. Model fitness was checked by Hosmer and Lemeshow (P value = 0.39). Adjusted odds ratio (AOR) with 95% CI was computed to determine the strength of association between the variables of interest.
Results
Socio - demographic characteristics of participants
A total of 405 mothers (135 cases and 270 controls) were included in the present study. The cases were consists of low birth weight, preterm and stillbirth; 78 (57.8%), 45 (33.3%) and 12 (8.9%) respectively. The mean age of cases and controls with standard deviation (SD) was 27.3 ± 6.6 and 26.14 ± 4.9 years, respectively. Majority of mothers, 84.4% of the cases and 93.0% of the controls were married. Among the total mothers included in the study, 46 (34.1%) of the cases and 37 (13.7%) of the controls were unable to read and write. Most mothers, 72.6% of the cases and 70% of the controls were housewives. Likewise, majority of the cases (89.6%) and the controls (88.9%) were Orthodox Christian by religion. Seventy seven (57%) of the cases and 221 (81.5%) of the controls were living in urban (Table 1).
Table 1.
Socio-demographic characteristics of mothers who gave birth in public hospitals, Tigrai region, Ethiopia, December 2015–January 2016 (n = 405; cases: 135 and controls: 270)
| Variables | Categories | Cases n = 135 n (%) |
Controls n = 270 n (%) |
|---|---|---|---|
| Maternal age (years) | 15–19 | 10 (7.4) | 12 (4.5) |
| 20–24 | 48 (35.6) | 91 (33.7) | |
| 25–29 | 30 (22.2) | 107 (39.6) | |
| 30–34 | 19 (14.1) | 40 (14.8) | |
| ≥35 | 28 (20.7) | 20 (7.4) | |
| Marital status | Single | 14 (10.4.0) | 11 (4.0) |
| Married | 114 (84.4) | 251 (93.0) | |
| Others | 7 (5.2) | 8 (3.0) | |
| Maternal education | Unable to read and write | 49 (36.3) | 34 (12.6) |
| Able to read and write only | 12 (8.9) | 26 (9.5) | |
| Primary school | 27 (20) | 77 (28.5) | |
| Secondary school | 30 (22.2) | 77 (28.5) | |
| College and above | 17 (12.6) | 56 (20.7) | |
| Husband’s education | Unable to read and write | 37 (27.4) | 21 (7.8) |
| Able to read and write only | 21 (15.5) | 29 (10.7) | |
| Primary school | 22 (16.3) | 53 (19.6) | |
| Secondary school | 33 (24.5) | 84 (31.1) | |
| College and above | 22 (16.3) | 83 (30.8) | |
| Occupation | House wife | 98 (72.6) | 189 (70.0) |
| Student | 10 (7.4) | 9 (3.3) | |
| Employed | 27 (20.0) | 72 (26.7) | |
| Religion | Orthodox | 121 (89.6) | 249 (92.2) |
| Muslim | 12 (8.9) | 14 (5.2) | |
| Catholic | 2 (1.5) | 7 (2.6) | |
| Residence | Urban | 77 (57) | 221 (81.9) |
| Rural | 58 (43) | 49 (18.1) | |
| Monthly household income (ETB) * | ≤650 | 37 (27.4) | 14 (5.2) |
| 651–1400 | 35 (25.9) | 53 (19.6) | |
| 1401–2350 | 24 (17.8) | 63 (23.3) | |
| 2351–3550 | 26 (19.2) | 71 (26.3) | |
| 3551–5000 | 12 (8.9) | 49 (18.2) | |
| ≥5001 | 1 (0.8) | 20 (7.4) |
*1ETB ~ O.045 USD
Obstetric characteristics of participants
Most of the participants, 66% cases and 80% controls had a total lifetime gravidity of less than four. Ninety three (68.9%) of cases and 221 (81.8%) of controls had less than four parity. Among participants of the study, 61 (70.1%) cases and 40 (27.6%) controls had less than 24 months inter-pregnancy interval. Majority of the participants of the study, 110 (81.5%) cases and 270 (100%) controls attended ANC at least once in health facility. Meanwhile, mothers who had at least four ANC visits were 40 (29.6%) among cases and 195 (72.2%) among controls. Among the total participants 88 (65.2%) of the cases and 30 (11.1%) of the controls did not receive dietary counseling during the index pregnancy. Among the total mothers included in the present study, 76 (56.3%) of the cases and 235 (87%) of the controls had hemoglobin level of 11 g/dl or more during the index pregnancy. In addition, in 50 (37%) of the cases and 28 (10.4%) of the controls the index pregnancy was unwanted (Table 2).
Table 2.
Obstetric characteristics of mothers who gave birth in public hospitals, Tigrai region, Ethiopia, 2016
| Variables | Categories | Cases (135) n (%) |
Control (270) n (%) |
|---|---|---|---|
| Gravidity | < 4 | 89 (66) | 216 (80) |
| ≥ 4 | 46 (44) | 54 (20) | |
| Parity | < 4 | 93 (68.9) | 221 (81.8) |
| ≥ 4 | 42 (31.1) | 49 (18.2) | |
| Antenatal care (ANC) follow up | No | 25 (18.5) | 0 (0.0) |
| Yes | 110 (81.5) | 270 (100) | |
| Gestational age (GA) at first ANC visit | < 28 weeks | 75 (68.2) | 249 (92.2) |
| ≥28 weeks | 35 (31.8) | 21 (7.8) | |
| Number of ANC visits | < 4 | 95 (70.4) | 75 (27.8) |
| ≥ 4 | 40 (29.6) | 195 (72.2) | |
| Iron folic acid (IFA) supplementation | No | 46 (34.1) | 31 (11.5) |
| Yes | 89 (65.9) | 239 (88.5) | |
| Amount of IFA taken | < 90 | 59 (80.8) | 133 (61.9) |
| 90 and more | 14 (19.2) | 82 (38.1) | |
| Received dietary counseling | No | 88 (65.2) | 30 (11.1) |
| Yes | 47 (34.8) | 240 (88.9) | |
| Hemoglobin level | < 11 g/dl | 59 (43.7) | 35 (13.0) |
| ≥ 11 g/dl | 76 (56.3) | 235 (87.0) | |
| MUAC | < 21 cm | 83 (61.5) | 3 (1.1) |
| ≥ 21 cm | 52 (38.5) | 267 (98.9) | |
| Maternal height | < 150 cm | 15 (11.1) | 11 (4.1) |
| ≥ 150 cm | 120 (88.9) | 259 (95.9) | |
| Maternal RH factor | Positive | 123 (91.1) | 252 (93.3) |
| Negative | 12 (8.9) | 18 (6.7) | |
| Pregnancy wanted/planned | No | 50 (37.0) | 28 (10.4) |
| Yes | 85 (63.0) | 242 (89.6) | |
| Ever use of family planning methods | No | 75 (55.5) | 61 (22.6) |
| Yes | 60 (44.5) | 209 (77.4) | |
| History of medical illness | No | 123 (91.1) | 253 (93.7) |
| Yes | 12 (8.9) | 17 (6.3) | |
| Current labor complication | No | 110 (81.5) | 219 (81.1) |
| Yes | 25 (18.5) | 51 (18.9) | |
| Sex of index neonate | Male | 69 (51.1) | 132 (48.9) |
| Female | 66 (48.9) | 138 (51.1) | |
| APGAR score | < 8 | 84 (62.2) | 57 (21.1) |
| 8 and more | 51 (37.8) | 213 (78.9) |
Determinants of adverse birth outcome
In the bivariate analysis, factors found to be significantly associated with adverse birth outcome were maternal education, residence, husband’s education, monthly household income, gravidity, inter-pregnancy birth interval, number of ANC visits, iron folic acid supplementation (IFA), receiving dietary counseling during the prenatal care of the index pregnancy, ever use of family planning, wanted/plan of the index pregnancy, experience complication in the index pregnancy, and hemoglobin level.
After controlling for confounders using multivariate analysis, number of ANC visit, receiving dietary counseling or not during the index pregnancy, inter-pregnancy interval, ever use of family planning methods, and hemoglobin level were identified as independent determinant factors of adverse birth outcome. That is; mothers who had less than four ANC visits were about four times more at risk of experiencing adverse birth outcome than mothers who had at least four ANC visit [AOR = 4.35, 95% CI:1.15–13.50]. Mothers who did not receive dietary counseling were 11 times more at risk of experiencing adverse birth outcomes compared to their counterparts, [AOR = 11.24, 95% CI: 3.92–36.60]. Furthermore, mothers with hemoglobin level of less than 11 g/dl were nearly five times more at risk to experience adverse birth outcome than those with hemoglobin level of 11 g/dl or more [AOR = 4.86, 95% CI: 1.83–14.01]. Ever use of family planning methods was also another important variable independently associated with adverse birth outcome; mothers who had not ever used family planning methods were four times more likely to experience adverse birth outcome compared to their counterparts, [AOR = 4.06, 95% CI: 1.35–17.34]. Mothers with less than 24 months inter pregnancy interval were five times more risk to experience adverse birth outcome than mothers with greater than 24 months inter-pregnancy interval, [AOR = 5.21, 95% CI: 1.89–13.86 (Table 3).
Table 3.
Determinants of adverse birth outcome among mothers who gave birth in public hospitals, Tigrai region, Ethiopia, 2016 (n = 405)
| Variables | Cases | Controls | COR (95% CI) | AOR (95% CI)* |
|---|---|---|---|---|
| n (%) | n (%) | |||
| Maternal education | ||||
| Non formal educated | 61 (45.2) | 60 (22.2) | 2.86 (3.01–8.59) | 0.62 (0.16–2.41) |
| Formal educated | 74 (54.8) | 210 (77.8) | 1 | 1 |
| Residence | ||||
| Urban | 77 (25.8) | 221 (74.2) | 0.29 (0.19–0.47) | 0.50 (0.12–2.09) |
| Rural | 58 (54.2) | 49 (45.8) | 1 | 1 |
| Monthly household income | ||||
| < 1200 | 72 (51.8) | 67 (48.2) | 5.66 (2.97–10.78) | 0.97 (0.20–4.76) |
| 1200–3000 | 48 (27.9) | 124 (72.1) | 2.04 (1.07–3.88) | 1.05 (0.29–3.71) |
| > 3000 | 15 (16.0) | 79 (84.0) | 1 | 1 |
| Husband’s education | ||||
| Non formal educated | 58 (53.7) | 50 (46.3) | 3.31 (2.09–5.24) | 1.08 (0.28–4.25) |
| Formal educated | 77 (25.9) | 220 (74.1) | 1 | 1 |
| Gravidity | ||||
| 1–3 | 89 (29.2) | 216 (70.8) | 0.48 (0.30–0.77) | 1.78 (0.67–4.76) |
| ≥ 4 | 46 (46.0) | 54 (54.0) | 1 | 1 |
| Number of ANC visits | ||||
| < 4 | 95 (55.9) | 75 (44.1) | 6.17 (3.92–9.74) | 4.35 (1.15–13.50)* |
| ≥ 4 | 40 (17.0) | 195 (83.0) | 1 | 1 |
| Received dietary counseling | ||||
| No | 88 (74.6) | 30 (25.4) | 14.98 (8.91–25.17) | 11.24 (3.92–36.60)*** |
| Yes | 47 (16.4) | 240 (83.6) | 1 | 1 |
| Ever use of family planning methods | ||||
| No | 75 (55.1) | 61 (44.9) | 4.28 (2.75–6.67) | 4.06 (1.35–17.34)* |
| Yes | 60 (22.3) | 209 (77.7) | 1 | 1 |
| Wanted /planed the indexed pregnancy | ||||
| No | 50 (64.1) | 28 (35.9) | 5.08 (3.01–8.59) | 1.46 (0.40–5.33) |
| Yes | 85 (26.0) | 242 (74.0) | 1 | 1 |
| Experienced pregnancy complication | ||||
| No | 103 (29.7) | 244 (70.3) | 0.34 (.19–.60) | 0.61 (0.15–2.43) |
| Yes | 32 (55.2) | 26 (44.8) | 1 | 1 |
| Hemoglobin level | ||||
| < 11 mg/dl | 59 (62.8) | 35 (37.2) | 5.21 (3.19–8.52) | 4.86 (1.83–14.01)** |
| ≥ 11 mg/dl | 76 (24.4) | 235 (75.6) | 1 | 1 |
| Received IFA | ||||
| No | 46 (59.7) | 31 (40.3) | 3.98 (2.38–6.68) | 0.67 (0.18–2.57) |
| Yes | 89 (27.1) | 239 (72.9) | 1 | 1 |
| Inter- pregnancy interval | ||||
| < 24 months | 61 (60.4) | 40 (39.6) | 6.16 (3.43–16.06) | 5.21 (1.89–13.86)*** |
| > = 24 months | 26 (19.8) | 105 (80.2) | 1 | 1 |
*** Significant at P- value < 0.001, **significant at P- value < 0.01 and *significant at P- value < 0.05
*Adjusted for: number of ANC visits, iron folic acid (IFA) supplementation, dietary counseling, ever use family planning, inter-pregnancy interval, and hemoglobin level
Discussion
This study assessed determinants of adverse birth outcome among mothers who gave birth in public hospitals in Tigrai region, North Ethiopia. the results revealed that limited number of ANC visit, not receiving dietary counseling, short inter-pregnancy interval, not ever using of family planning methods, and low hemoglobin level were independently associated with adverse birth outcome.
In the present study, mothers who had less than four ANC follow-up visits had four times more risk of having adverse birth outcome than those who have had at least four ANC follow up visits. This finding is similar with a similar study in Gaza strip [31], in which the risk of preterm birth increased two folds among mothers who had less than four ANC visits compared to their counterparts. Similarly, the current finding is supported by similar studies in Ethiopia and India [24, 26, 30, 33–35], in which not having ANC has been shown as a significant risk factor of low birth weight. Furthermore, the current finding is in agreement with similar studies in Ethiopia and China, and a systematic review in LIMICs [11, 17, 20, 22, 36], in which the risk of still birth was significantly higher among mothers who had no ANC visits compared to their counterparts. This could be explained by mothers who have the recommended number of ANC visits have access to information on maternal nutrition which eventually results in better dietary practice. This finding implies that adverse birth outcomes could be reduced by improving maternal service utilization.
Dietary counseling was another independent predictor of adverse birth outcome; mothers who did not receive dietary counseling during the index pregnancy had twelve fold increased risk of experiencing adverse birth outcome than those who received dietary counseling. This finding is supported by a recently conducted systematic review [37]. This suggests that antenatal care should give much more emphasis to dietary counseling with special focus to stunted mothers who are at increased risk of adverse birth outcome. Besides to dietary counseling, hemoglobin level was associated with adverse birth outcome; mothers with hemoglobin level of less than 11 g/dl had five times increased risk of adverse birth outcome compared to their counterparts. This is supported by similar studies in India, Nigeria, Sudan and Ethiopia [19, 36, 38–42], in which low hemoglobin level has been reported as a risk factor of low birth weight and/or preterm birth and/or still birth. This could be explained by the fact that hemoglobin level is a proxy indicator of nutritional status which significantly influence birth outcome due to low fetal supply of oxygen and nutrient. This implies that maternal interventions should primarily focus on maternal nutrition and iron folic acid supplementation.
Mothers with short (less than 24 months) inter-pregnancy interval were five times more likely to experience adverse birth outcome compared to their counterparts. This result is in line with studies in Indonesia, India, Tanzania and Ethiopia [25, 41, 43–46], in which short inter-pregnancy interval was a risk factor for low birth weight and/or preterm birth. Likewise, the current finding is in agreement with similar study in Bangladesh [47], in which short inter- pregnancy interval has been a significant risk factor for stillbirth. This could be due to the fact that short inter-pregnancy interval results in maternal depletion syndrome which eventually increases the risk of adverse birth outcome [48]. Furthermore, ever use of family planning was significantly associated with adverse birth outcome; mothers who have not ever used family planning methods had five times more risk to experience adverse birth outcome than their counterparts. This is supported by a recently conducted systematic review and meta-analysis study [46], in which continuum of care – linking pre-pregnancy care and pregnancy care has been found to be effective in reducing adverse birth outcome. This could be explained by the fact that not using family planning may results in too early, too many and too close births which increases the risk of maternal depletion and adverse birth outcome [49, 50]. The implication of this finding is interventions targeted adverse birth outcomes should give emphasis to family planning [51].
This study has its own drawbacks. The study did not assess the contribution of important variables such as knowledge, husband involvement and food security. Furthermore, this study is not free from recall and social desirability biases.
Conclusion
In this study less than four ANC visits, not receiving dietary counseling during the index pregnancy, not ever using family planning methods, inter-pregnancy interval of less than 24 months, and hemoglobin level of less than 11 g/dl were significantly associated with adverse birth outcomes. Therefore, a concerted effort should be taken to improve family planning, and ANC follow-up with special emphasis to maternal nutrition to prevent adverse birth outcome.
Acknowledgements
Aksum University is acknowledged for supporting this research work. We are also grateful for the data collectors and the study participants for their valuable contribution.
Fundings
Aksum University has partially supported this research work. The sponsor of the study had no role in study design, data collection, data analysis or interpretation, but did review this report prior to submission for publication. The corresponding author had full access to all the data in the study and had final responsibility for the decision to submit for publication.
Abbreviations
- ANC
Antenatal care
- AOR
Adjusted odds ratio
- CI
Confidence interval
- COR
Crude odds ratio
- ETB
Ethiopian birr
- GA
Gestational age
- IFA
Iron Folic Acid
- LBW
Low birth weight
- LMICs
Low and middle income countries
- MUAC
Mid upper arm circumference
- PTB
Preterm birth
- SD
Standard deviation
- WHO
World Health Organization
Authors’ contribution
HT: conception, design, data analysis, interpretation of findings and manuscript writing. GT, HB, MG and KH: design, data analysis, interpretation of findings and manuscript preparation. All authors read and approved the final manuscript.
Availability of data and materials
Datasets obtained or analyzed during the current study are available from the corresponding author on reasonable request.
Ethics approval and consent to participate
Ethical clearance was obtained from Institutional Research Review Board of College of Health Science and Referral Hospital, Aksum University. Permission letter was also attained from Tigrai regional health bureau and respective district health offices. Moreover, written and verbal consent was obtained from each study participant before data collection. For minors (age less than 16 years) informed assent and consent was obtained from their guardians. The written consents and assents were kept confidential.
Consent for publication
Not applicable.
Competing interests
The authors declare that they have no competing interests.
Footnotes
Publisher’s Note
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Contributor Information
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References
- 1.Liu L, Oza S, Hogan D, Perin J, Rudan I, Lawn JE, et al. Global, regional, and national causes of child mortality in 2000-13, with projections to inform post-2015 priorities: an updated systematic analysis. Lancet Lond Engl. 2015;385(9966):430–440. doi: 10.1016/S0140-6736(14)61698-6. [DOI] [PubMed] [Google Scholar]
- 2.Blencowe H, Cousens S, Oestergaard MZ, Chou D, Moller A-B, Narwal R, et al. National, regional, and worldwide estimates of preterm birth rates in the year 2010 with time trends since 1990 for selected countries: a systematic analysis and implications. Lancet Lond Engl. 2012;379(9832):2162–2172. doi: 10.1016/S0140-6736(12)60820-4. [DOI] [PubMed] [Google Scholar]
- 3.National and regional estimates of term and preterm babies born small for gestational age in 138 low-income and middle-income countries in 2010 - PIIS2214-109X (13)70006–8. [Internet]. [cited 2016 Dec 14]. [DOI] [PMC free article] [PubMed]
- 4.Beck S, Wojdyla D, Say L, Betran AP, Merialdi M, Requejo JH, et al. The worldwide incidence of preterm birth: a systematic review of maternal mortality and morbidity. Bull World Health Organ. 2010;88(1):31–38. doi: 10.2471/BLT.08.062554. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Lawn JE, Cousens S, Zupan J. 4 million neonatal deaths: When? Where? Why? The lancet [internet] 2005;365(9462):891–900. doi: 10.1016/S0140-6736(05)71048-5. [DOI] [PubMed] [Google Scholar]
- 6.Lawn JE, Blencowe H, Pattinson R, Cousens S, Kumar R, Ibiebele I, et al. Stillbirths: where? When? Why? How to make the data count? Lancet Lond Engl. 2011;377(9775):1448–1463. doi: 10.1016/S0140-6736(10)62187-3. [DOI] [PubMed] [Google Scholar]
- 7.WHO | Causes of child mortality [Internet]. [cited 2016 Dec 22]. Available from: http://www.who.int/gho/child_health/mortality/causes/en/. Accessed 24 May 2016.
- 8.Low birthweight - UNICEF DATA [Internet]. [cited 2016 Dec 22]. Available from: http://data.unicef.org/topic/nutrition/low-birthweight/. Accessed 24 May 2016.
- 9.Blencowe H, Cousens S, Jassir FB, Say L, Chou D, Mathers C, et al. National, regional, and worldwide estimates of stillbirth rates in 2015, with trends from 2000: a systematic analysis. Lancet Glob Health. 2016;4(2):e98–108. doi: 10.1016/S2214-109X(15)00275-2. [DOI] [PubMed] [Google Scholar]
- 10.stillbirths2016-exec-summ.pdf [Internet]. [cited 2016 Dec 14]. Available from: http://www.thelancet.com/pb/assets/raw/Lancet/stories/series/stillbirths2016-exec-summ.pdf. Accessed 24 May 2016.
- 11.Adane AA, Ayele TA, Ararsa LG, Bitew BD, Zeleke BM. Adverse birth outcomes among deliveries at Gondar University Hospital, Northwest Ethiopia. BMC Pregnancy Childbirth. 2014 Feb 27;14:90. [DOI] [PMC free article] [PubMed]
- 12.Major risk factors for stillbirth in high-income countries: a systematic review and meta-analysis - The Lancet [Internet]. [cited 2016 Dec 18]. [DOI] [PubMed]
- 13.Stanton C, Lawn JE, Rahman H, Wilczynska-Ketende K, Hill K. Stillbirth rates: delivering estimates in 190 countries. Lancet Lond Engl. 2006;367(9521):1487–1494. doi: 10.1016/S0140-6736(06)68586-3. [DOI] [PubMed] [Google Scholar]
- 14.Maternal morbidity and preterm birth in 22 low- and middle-income countries: a secondary analysis of the WHO Global Survey dataset | BMC Pregnancy and Childbirth | Full Text [Internet]. [cited 2016 Dec 14]. [DOI] [PMC free article] [PubMed]
- 15.Saigal S, Doyle LW. An overview of mortality and sequelae of preterm birth from infancy to adulthood. Lancet Lond Engl. 2008;371(9608):261–269. doi: 10.1016/S0140-6736(08)60136-1. [DOI] [PubMed] [Google Scholar]
- 16.Rogers LK, Velten M. Maternal inflammation, growth retardation, and preterm birth: insights into adult cardiovascular disease. Life Sci. 2011;89(13–14):417–421. doi: 10.1016/j.lfs.2011.07.017. [DOI] [PubMed] [Google Scholar]
- 17.Causes of and factors associated with stillbirth in low- and middle-income countries: a systematic literature review - Aminu - 2014 - BJOG: An International Journal of Obstetrics & Gynaecology - Wiley Online Library [Internet]. [cited 2016 Dec 17]. [DOI] [PubMed]
- 18.Sutherland MR, Bertagnolli M, Lukaszewski M-A, Huyard F, Yzydorczyk C, Luu TM, et al. Preterm Birth and Hypertension Risk. Hypertension [Internet] 2014;63(1):12–18. doi: 10.1161/HYPERTENSIONAHA.113.01276. [DOI] [PubMed] [Google Scholar]
- 19.Risk factors and adverse perinatal outcome associated with low birth weight in Northern Tanzania: a registry-based retrospective cohort study - 1-s2.0-S2305050015000640-main.pdf [Internet]. [cited 2016 Dec 15].
- 20.Bayou G, Berhan Y. Perinatal Mortality and Associated Risk Factors: A Case Control Study. Ethiop J Health Sci [Internet] 2012;22(3):153–162. [PMC free article] [PubMed] [Google Scholar]
- 21.Gebremedhin M, Ambaw F, Admassu E, Berhane H. Maternal associated factors of low birth weight: a hospital based cross-sectional mixed study in Tigray, Northern Ethiopia. [Internet]. BMC Pregnancy Childbirth. 2015;15 [cited 2016 Dec 20]. [DOI] [PMC free article] [PubMed]
- 22.Zhu J, Liang J, Mu Y, Li X, Guo S, Scherpbier R, et al. Sociodemographic and obstetric characteristics of stillbirths in China: a census of nearly 4 million health facility births between 2012 and 2014. Lancet Glob Health. 2016;4(2):e109–e118. doi: 10.1016/S2214-109X(15)00271-5. [DOI] [PubMed] [Google Scholar]
- 23.Watson-Jones D, Weiss HA, Changalucha JM, Todd J, Gumodoka B, Bulmer J, et al. Adverse birth outcomes in United Republic of Tanzania--impact and prevention of maternal risk factors. Bull World Health Organ. 2007;85(1):9–18. doi: 10.2471/BLT.06.033258. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Wealth Status, Mid Upper Arm Circumference (MUAC) and Antenatal Care (ANC) Are Determinants for Low Birth Weight in Kersa, Ethiopia [Internet]. [cited 2016 Dec 17]. Available from: http://journals.plos.org/plosone/article?id=10.1371/. Accessed 8 June 2016. [DOI] [PMC free article] [PubMed]
- 25.Sebayang SK, Dibley MJ, Kelly PJ, Shankar AV, Shankar AH, SUMMIT Study Group Determinants of low birthweight, small-for-gestational-age and preterm birth in Lombok, Indonesia: analyses of the birthweight cohort of the SUMMIT trial. Trop Med Int Health TM IH. 2012;17(8):938–950. doi: 10.1111/j.1365-3156.2012.03039.x. [DOI] [PubMed] [Google Scholar]
- 26.Teklehaimanot N. Prevalence and Factors Associated with Low Birth Weight in Axum and Laelay Maichew Districts, North Ethiopia: A Comparative Cross Sectional Study. Int J Nutr Food Sci [Internet] 2014;3(6):560. doi: 10.11648/j.ijnfs.20140306.21. [DOI] [Google Scholar]
- 27.Risk factors for low birth weight in Nigeria: evidence from the 2013 Nigeria Demographic and Health Survey | Dahlui | Global Health Action [Internet]. [cited 2016 Dec 17]. [DOI] [PMC free article] [PubMed]
- 28.McClure EM, Goldenberg RL. Stillbirth in Developing Countries: A review of causes, risk factors and prevention strategies. J Matern-Fetal Neonatal Med Off J Eur Assoc Perinat Med Fed Asia Ocean Perinat Soc Int Soc Perinat Obstet [Internet] 2009;22(3):183–190. doi: 10.1080/14767050802559129. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Kayode Gbenga A., Amoakoh-Coleman Mary, Agyepong Irene Akua, Ansah Evelyn, Grobbee Diederick E., Klipstein-Grobusch Kerstin. Contextual Risk Factors for Low Birth Weight: A Multilevel Analysis. PLoS ONE. 2014;9(10):e109333. doi: 10.1371/journal.pone.0109333. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Demelash H, Motbainor A, Nigatu D, Gashaw K, Melese A. Risk factors for low birth weight in bale zone hospitals. South-East Ethiopia : a case-control study. BMC Pregnancy Childbirth. 2015;15:264. doi: 10.1186/s12884-015-0677-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Abu Hamad K, Abed Y, Abu HB. Risk factors associated with preterm birth in the Gaza strip: hospital-based case-control study. East Mediterr Health J Rev Sante Mediterr Orient Al-Majallah Al-Sihhiyah Li-Sharq Al-Mutawassit. 2007;13(5):1132–1141. doi: 10.26719/2007.13.5.1132. [DOI] [PubMed] [Google Scholar]
- 32.EDHS. Demographic Health Survey 2011 Ethiopia Final Report.pdf [Internet]. [cited 2016 May 28].
- 33.Sutan R, Mohtar M, Mahat AN, Tamil AM. Determinant of Low Birth Weight Infants: A Matched Case Control Study. Open J Prev Med [Internet] 2014;4(3):91–99. doi: 10.4236/ojpm.2014.43013. [DOI] [Google Scholar]
- 34.Zeleke BM, Zelalem M, Mohammed N. Incidence and correlates of low birth weight at a referral hospital in Northwest Ethiopia. Pan Afr Med J[Internet]. 2012;12 [cited 2016 Dec 16]. [PMC free article] [PubMed]
- 35.Mumbare SS, Maindarkar G, Darade R, Yenge S, Tolani MK, Patole K. Maternal risk factors associated with term low birth weight neonates: a matched-pair case control study. Indian Pediatr. 2012;49(1):25–28. doi: 10.1007/s13312-012-0010-z. [DOI] [PubMed] [Google Scholar]
- 36.Logistic regression analysis on the determinants of stillbirth in Ethiopia | Maternal Health, Neonatology and Perinatology | Full Text [Internet]. [cited 2016 Dec 16]. [DOI] [PMC free article] [PubMed]
- 37.Ota E, Hori H, Mori R, Tobe-Gai R, Farrar D. Antenatal dietary education and supplementation to increase energy and protein intake. Cochrane Database Syst Rev. 2015;2:6. doi: 10.1002/14651858.CD000032.pub3. [DOI] [PubMed] [Google Scholar]
- 38.Levy A, Fraser D, Katz M, Mazor M, Sheiner E. Maternal anemia during pregnancy is an independent risk factor for low birthweight and preterm delivery. Eur J Obstet Gynecol Reprod Biol. 2005;122(2):182–186. doi: 10.1016/j.ejogrb.2005.02.015. [DOI] [PubMed] [Google Scholar]
- 39.Elhassan EM, Abbaker AO, Haggaz AD, Abubaker MS, Adam I. Anaemia and low birth weight in Medani, Hospital Sudan. BMC Res Notes[Internet] 2010;3:181. doi: 10.1186/1756-0500-3-181. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40.Allen LH. Anemia and iron deficiency: effects on pregnancy outcome. Am J Clin Nutr[Internet] 2000;71(5):1280s–1284s. doi: 10.1093/ajcn/71.5.1280s. [DOI] [PubMed] [Google Scholar]
- 41.Determinants of low birth weight in a rural area of Tamil Nadu, India: a case–control study - International Journal of Medical Science and Public Health - ScopeMed.org - Online Journal Management System [Internet]. [cited 2016 Dec 16].
- 42.Bodeau-Livinec F, Briand V, Berger J, Xiong X, Massougbodji A, Day KP, et al. Maternal Anemia in Benin: Prevalence, Risk Factors, and Association with Low Birth Weight. Am J Trop Med Hyg [Internet] 2011;85(3):414–420. doi: 10.4269/ajtmh.2011.10-0599. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 43.Mahande MJ, Obure J. Effect of interpregnancy interval on adverse pregnancy outcomes in northern Tanzania: a registry-based retrospective cohort study. BMC Pregnancy Childbirth [Internet]. 2016;16 [cited 2016 Dec 16]. [DOI] [PMC free article] [PubMed]
- 44.Haq A, Lallar M, Akhter S, Baba Y, Ahmad J, Hamid M. Interpregnancy interval raise odds of adverse perinatal outcome in high fertility region Mewat, Haryana. Int J Reprod Contracept Obstet Gynecol [Internet]. 2014:598–603 [cited 2016 Dec 17].
- 45.Rodrigues T, Barros H. Short interpregnancy interval and risk of spontaneous preterm delivery. Eur J Obstet Gynecol Reprod Biol. 2008;136(2):184–188. doi: 10.1016/j.ejogrb.2007.03.014. [DOI] [PubMed] [Google Scholar]
- 46.Effectiveness of Continuum of Care—Linking Pre-Pregnancy Care and Pregnancy Care to Improve Neonatal and Perinatal Mortality: A Systematic Review and Meta-Analysis [Internet]. [cited 2016 Dec 15]. [DOI] [PMC free article] [PubMed]
- 47.de Jonge HC, Azad K, Seward N, Kuddus A, Shaha S, Beard J, et al. Determinants and consequences of short birth interval in rural Bangladesh: a cross-sectional study. BMC Pregnancy Childbirth [Internet] 2014;14:427. doi: 10.1186/s12884-014-0427-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 48.van Eijsden M, Smits LJ, van der Wal MF, Bonsel GJ. Association between short interpregnancy intervals and term birth weight: The role of folate depletion. Am J Clin Nutr [internet] 2008;88(1):147–153. doi: 10.1093/ajcn/88.1.147. [DOI] [PubMed] [Google Scholar]
- 49.Report of a WHO Technical Consultation on Birth Spacing, Geneva, Switzerland, 13–15 June 2005. | POPLINE.org [Internet]. [cited 2016 Dec 15].
- 50.Conde-Agudelo A, Rosas-Bermúdez A, Kafury-Goeta AC. Birth spacing and risk of adverse perinatal outcomes: a meta-analysis. JAMA. 2006;295(15):1809–1823. doi: 10.1001/jama.295.15.1809. [DOI] [PubMed] [Google Scholar]
- 51.Badshah S, Mason L, McKelvie K, Payne R, Lisboa PJ. Risk factors for low birthweight in the public-hospitals at Peshawar, NWFP-Pakistan. BMC Public Health [Internet] 2008;8:197. doi: 10.1186/1471-2458-8-197. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
Datasets obtained or analyzed during the current study are available from the corresponding author on reasonable request.