Abstract
Background
In Ethiopia, in 2021, more than 80% of all newborn deaths were caused by preventable and treatable conditions. This study aimed to measure the incidence of adverse perinatal outcomes and risk factors among women with pre-eclampsia in the Sidama region of southern Ethiopia.
Methods
A prospective open cohort study was conducted from 8 August 2019 to 1 October 2020. We enrolled 363 women with pre-eclampsia and 367 normotensive women at ≥20 weeks of gestation and followed them until the 37th week. We then followed them until the seventh day after delivery up to the last perinatal outcome status was ascertained. A log-binomial logistic regression model was used to estimate the incidence of adverse perinatal outcomes and its risk factors among women with pre-eclampsia. Relative risk (RR) with a 95% CI was reported. A p<0.05 was considered statistically significant.
Results
There were 224 adverse perinatal outcomes observed in the 363 women with pre-eclampsia compared with 136 adverse perinatal outcomes in the 367 normotensive women (p<0.001). There were 23 early neonatal deaths in the pre-eclampsia group compared with six deaths in the normotensive group (p<0.001). There were 35 perinatal deaths in the pre-eclampsia group compared with 16 deaths in the normotensive group (p<0.05). Women with severe features of pre-eclampsia had a 46% (adjusted RR 1.46, 95% CI 1.38 to 2.77) higher risk for adverse perinatal outcomes compared with women without severe features of pre-eclampsia.
Conclusions
In this study, more adverse perinatal outcomes occurred among women with pre-eclampsia after controlling for confounders. A higher perinatal outcome observed among women with pre-eclampsia, especially among women with severe features of pre-eclampsia, and those admitted to hospital at <34 weeks. This paper highlights the significantly elevated perinatal risks associated with pre-eclampsia, especially when it has severe features.
Keywords: epidemiology, health services research, neonatology, nursing care, nursing
WHAT IS ALREADY KNOWN ON THIS TOPIC
Studies conducted in Ethiopia on maternal and perinatal outcomes related to pre-eclampsia have not generated evidence that could be used by policy-makers or implemented in clinical practices because of study design. Most studies did not include control groups or measure the risk of outcomes of interest and there were missing sociodemographic variables such as maternal education level. A study in southern Ethiopia aiming to estimate the risk of pre-eclampsia on adverse perinatal outcomes did not include exposures and outcomes.
WHAT THIS STUDY ADDS
There were 224 adverse perinatal outcomes observed in the 363 women with pre-eclampsia compared with 136 adverse perinatal outcomes in the 367 normotensive women (p<0.001).
Women with severe features of pre-eclampsia had a 46% (adjusted relative risk, aRR 1.46, 95% CI 1.38 to 2.77) higher risk for adverse perinatal outcomes compared with women without severe features of pre-eclampsia.
Women without severe features of pre-eclampsia had a 39% (aRR 1.39, 95% CI 1.21 to 1.56) higher risk for adverse perinatal outcomes compared with women in the normotensive group.
HOW THIS STUDY MIGHT AFFECT RESEARCH, PRACTICE OR POLICY
This study provides epidemiological evidence for the incidence of adverse perinatal outcomes and risk factors among women with pre-eclampsia. Early detection and management of pre-eclampsia may improve maternal and infant outcomes. So, this could support clinical and public health practitioners to be aware of early signs and symptoms of pre-eclampsia. A cohort study should be conducted to evaluate other types of hypertensive disorders of pregnancy on the incidence of adverse perinatal outcomes and its risk factors among pregnant women.
Introduction
Pre-eclampsia and eclampsia are two of the most common hypertensive disorders of pregnancy (HDPs).1 It is the second-leading cause of direct maternal death and is directly responsible for 70 000 maternal deaths annually at the global level.2 In low-income and middle-income countries, 10%–15% of direct maternal mortalities were associated with pre-eclampsia and eclampsia in 2018.1 In Ethiopia, in 2019, the pooled prevalence of maternal death was 4%.3
In Ethiopia, in 2018, the overall pooled prevalence of HDPs was 6.07%.4 In the same study, a higher pooled prevalence of HDPs was observed in southern Ethiopia (10.13%), with the lowest prevalence observed in Addis Ababa, the capital city of Ethiopia (5.41%).4
Adverse perinatal outcomes include an overall <5 child mortality rate of 55 deaths per 1000 live births, and neonatal mortality was 30 deaths per 1000 live births5 and the pooled prevalence of low birth weight was 17.3%6 and stillbirths was 6.7%.7 A study conducted in northwest Ethiopia in 2021 found that the overall prevalence of adverse perinatal outcomes was 19.4%.8 According to a 2019 study in northwest Ethiopia, 46.5% of newborns delivered to women had unfavourable outcomes of severe pre-eclampsia and eclampsia, with 28.1% of those being stillbirths.9
A number of factors account for high rates of adverse perinatal outcomes, including poor infrastructure, scarcity of supplies and skilled labour, a weak referral system, poor quality of care, and lack of timely obstetric care, contributed to a higher proportion of adverse perinatal mortality in Ethiopia.10
In Ethiopia, in 2021, more than 80% of all newborn deaths were caused by preventable and treatable conditions.11 However, the reduction of mortality is still a challenge. The government of Ethiopia has taken steps to strengthen engagement with key local and international sectors and stakeholders to address determinants of health.12 Ethiopia recently replaced the previous four-visit focused antenatal care (ANC) model with the new ANC eight-contacts model.12
Studies conducted in Ethiopia have poor in generating evidence that could be used by policy-makers and in clinical practices because they did not include control groups or measure the risk of outcomes of interest and did not include sociodemographic variables such as maternal education status.9 13 14 A study in southern Ethiopia was limited in estimating the risk of pre-eclampsia on adverse perinatal outcomes because of poor ascertainment of exposures and outcomes using purposive sampling techniques.15 Another study in Ethiopia did not include a non-exposed group that would have been important to controlling confounders like the quality of perinatal care associated with morbidity and mortality.16 This study’s findings will provide epidemiological evidence for policy-makers and implementers to reduce adverse perinatal outcomes among women with pre-eclampsia and normotensive women. This paper highlights the significantly elevated perinatal risks associated with pre-eclampsia, especially when it has severe features. We aimed to measure the incidence of adverse perinatal outcomes and risk factors among women with pre-eclampsia in Sidama region of southern Ethiopia.
Methods
Study design and setting
A prospective open cohort study was conducted from 8 August 2019 to 1 October 2020 in the Sidama region of Ethiopia. In 2020, the population of the region was approximately 4 million. There were 13 public hospitals, 138 health centres and 540 health posts in the region that provided maternal, newborn and child health services. In 2020, approximately 132 031 pregnant women attended ≥4 ANC visits and 127 585 births were assisted by skilled birth attendants. Out of the 13 hospitals that are found in the region, we enrolled participants from 7 of the hospitals, including Adare, Hawassa, Yirgalem, Hula, Bona, Chuko and Daye hospitals.
Participants
The participants were women with pre-eclampsia and normotensive women who were enrolled at ≥20 weeks of gestation up until the 37th week. We followed them until the seventh day after delivery and waited for the last enrolled woman’s perinatal outcome status to be ascertained. During the follow-up, 194 women with pre-eclampsia and normotensive women were admitted to the hospitals at <34 weeks of gestation, and 536 women with pre-eclampsia and normotensive women were admitted to the hospitals at 34–37 weeks of gestation. During the follow-up, eight normotensive women developed pre-eclampsia. We, thus, included these eight women in the exposed group. Pregnant women with hypertension plus proteinuria, mild hypertension and evidence of organ dysfunction, severe hypertensive without proteinuria and evidence of organ dysfunction were included in the study.17 18 Pregnant women with pre-eclampsia and normotensive women were selected by healthcare providers: general medical practitioners, emergency surgical officers or obstetricians/gynaecologists during the follow-up.
Operational definitions
We ascertained exposure of interest supported by guidelines of the Obstetrics Management Protocol for Hospitals in Ethiopia in 2021 and on the recent International Society for the Study of Hypertension in Pregnancy.17 18 Birth asphyxia was defined as the condition of a baby with trouble in breathing (gasping or breathing very irregularly or no breathing). Small for gestational age of pregnancy was defined as a birth weight of a newborn below the 10th percentile of weight distribution at the specified gestational age of pregnancy.19 Stillbirth refers to a baby born with no sign of life at or after 28 weeks of gestation. Preterm delivery was defined as the delivery of a baby before 37 weeks gestation. Low birth weight describes a baby with a birth weight of less than 2.5 kg. A low Apgar score refers to a newborn baby with an Apgar score of less than seven at 1 and 5 min.
Perinatal death was defined as a stillbirth or an early neonatal death. Early neonatal death is defined as the death of a live newborn in the first 7 days of life. Intrauterine growth restriction of newborn is defined as birth weight and/or birth length below the 10th percentile for their gestational age and whose abdominal circumference was below the 2.5th percentile with pathological restriction of fetal growth.19 Gestational age at admission was defined as the time when the women were enrolled in the study. Skilled birth attendant was defined as a professionally trained health worker having the essential midwifery skills to manage normal labour and delivery, recognise complications early and perform any essential intervention including early referral.17
Sample size and sampling
The sample size was calculated using Epi Info V.7. We considered the following assumptions for sample size calculations: early neonatal death,20 the ratio of exposed to unexposed group (1–1), the proportion of early neonatal death among women with pre-eclampsia (5%) and the proportion of early neonatal death among normotensive women (1%). The sample size was estimated to be 733 (366 women with pre-eclampsia and 367 normotensive women), accounting for a design effect of 2% and 10% lost to follow-up. We also assumed a two-sided confidence level of 95% with a power of 80%.
A two-stage cluster sampling technique was used to recruit study participants. In the first stage, 7 of 13 hospitals were selected using a simple random sampling technique. In the second stage, perinatal conditions were selected from women with pre-eclampsia and normotensive women using a simple random sampling technique.
Exposure ascertainments
We ascertained exposure of interest supported by guidelines of the Obstetrics Management Protocol for Hospitals in Ethiopia in 2021 and on the recent International Society for the Study of Hypertension in Pregnancy.17 18 The main exposure variable in this study was pre-eclampsia with or without severity features. Pre-eclampsia with severe features was defined as the presence of one or more of the following conditions: blood pressure (BP) of ≥160 mm Hg systolic or ≥110 mm Hg diastolic, ≥3+ protein on two urine samples taken 4 hours or more apart or 5 g of protein in a 24- hour urine sample.18 Pre-eclampsia without severe features was defined as raised BP >140/90 mm Hg plus 24-hour urine protein >300 mg/24 hour or urine dipstick >+1 after 20 weeks of gestation in previously normotensive women.18 Normotensive women were pregnant women having a (BP) <140/90 mm Hg with ≥20 weeks of gestation or who did not develop pre-eclampsia and proteinuria. Gestational age was calculated based on a woman’s recall of her last menstrual period. However, an ultrasound scan was used for those women who could not remember their last menstrual period.18
Outcome variable
Adverse- perinatal outcomes were defined as a newborn with the occurrence of at least one of the following outcomes: birth asphyxia, low birth weight, small for gestational age, preterm delivery, admission to the neonatal intensive care unit and perinatal death.
Data collection
We validated the data collection tool before data collection.21 Two bilingual translators (speakers of both Sidamic and English languages), who were capable of translating the original tool in the English version into the Sidamic version, were selected. Translations into the Sidamic language more accurately reflected the tones of the language. The translations were compared and discrepancies were noted during the translation process. The poorer wording choices were identified and resolved in a discussion between the translators.
The back translations were done by two experts of the source language (English). This was a validity checking process to ensure that the translated version reflected the same item content as the original version did. Face and content validation of the tool was done by a panel of experts (midwife experts, epidemiologists and gynaecologists). The panel of experts independently assessed the tool for readability, intelligibility, clarity and ease of use. The internal consistency for each dimension was checked using Cronbach’s alpha (Cronbach’s alpha=0.98).21
In the first pilot test, conducted in a non-study area, all participants responded to all items in the data collection tool and marked them correctly. No missing items were found. Data collectors also reported no difficulty in asking the questions, and no participant reported having any problem understanding the items. The tool was tested for the second time 2 weeks after the first measurement. The 2-week test–retest reliability result was shown to have a good correlation with reliable strategies to assess these point scores (intraclass correlation coefficients (ICC) for agreement 0.78; p<0.001) because the ICC value was found to be in the range of 0.75 to 0.9, indicating good reliability.22 We also specified the kind of ICC was calculated we used the two-way mixed-effects model for calculating ICC as the model of choice for test–retest reliability measure.21 22
Trained midwives conducted face-to-face interviews at ANC clinics using the pretested validated tool. A checklist was used to collect information from the maternal and neonatal records of women with pre-eclampsia and normotensive women in each hospital. We collected sociodemographic information and clinical and laboratory variables linked to maternal and perinatal outcome status. The data collection procedures were supervised by three Maternal and Child Health maternity and reproductive health professionals.
Outcome ascertainment
Adverse perinatal outcomes were ascertained by obstetricians/gynaecologists and trained midwives. Client medical registration was also used to retrieve adverse perinatal outcome status. The perinatal condition was determined at the follow-up appointment for those who were discharged, and a phone call was made for those who did not show up for this follow-up.
Statistical analysis
Data were cleaned, coded and analysed using Stata 14. We identified outliers and missing values and checked data consistency using the original questionnaire for the responses using participants’ code numbers. Mean and SDs were computed for continuous variables. Frequencies and percentages were computed for categorical variables. An incidence proportion of adverse perinatal outcomes was conducted on women who had pre-eclampsia and normotensive women. Cross-tabulation was also performed to test the relationship of exposure variables with the outcome variable. A χ2 test was used to compare categorical variables between women with pre-eclampsia and normotensive women.
Principal component analysis was computed and used for wealth index computation and was ranked in three groups as low, middle and high. It was a composite measure of household cumulative living standard, and calculated by using data on household ownership of selected assets, like various household assets and means of transportation. Different items for urban and rural areas were computed separately. We included 21 items for rural residents and 16 items for urban residents. The suitability of data was computed by using Bartlett’s test of sphericity and the Kaiser-Meyer-Olkin (KMO) measure of sample adequacy.23 The KMO >0.6 was used to confirm the sample adequacy for factor analysis.23
A multivariable log-binomial logistic regression model was performed to identify the risk factors for adverse perinatal outcomes. According to Hosmer and Lemeshow, a variable with a p<0.25 was recommended as a screening criterion for the selection of candidate variables used in a multivariable log-binomial logistic regression model.24 This confirmed that insignificant variables from the first step were reanalysed in later steps.24 Moreover, the candidate variables were also considered based on subject matter expertise, such as gynaecologists, obstetricians, epidemiologists and statisticians who were working as a supervisor, and who provided more subject matter expertise to improve the modelling process substantially. This insight from subject matter experts substantially improved the modelling process.24 A variable with a p<0.05 was used to identify statistically significant risk factors for adverse perinatal outcomes. Maternal age was treated as a continuous variable and reported using the beta-coefficient with a 95% CI.
We checked the multicollinearity among predictors using a variance inflation factor at a cut-off point of 10.25 We confirmed that there was no collinearity among predictors. The goodness of the fit was tested using the Hosmer-Lemeshow test.26 The predictor that was greater than the significance level (p>0.05) was accepted.26 This indicates that the observed model did not significantly differ from the expected model.
Results
Sociodemographic and economic characteristics of study participants
Of the 733 women eligible for this study, 730 were enrolled. Two (0.27%) of the participants were lost to follow-up. Of these two participants, one was from the pre-eclamptic group and one from the normotensive group. One participant refused to participate in the study. During the follow-up, eight normotensive women developed pre-eclampsia. We; thus, included these eight women in the exposed group (figure 1).
Figure 1.
Flow diagram of the overall study process in Sidama region, southern Ethiopia, 8 August 2019 to 1 October 2020.
The mean gestational age at the diagnosis of pre-eclampsia was 32.85±3.25 weeks and that of normotensive women was (33.90±2.75) weeks. The mean duration of follow-up of women with pre-eclampsia was 6.51±3.15 weeks and that of normotensive women was 5.68±2.97 weeks (figure 1).
The mean age of the women with pre-eclampsia was 25.42±4.76 years, and 24.6±4.48 years for the normotensive group. Nearly half of the women had pre-eclampsia (45.2%, 164/363) were attended primary school education, compared with the normotensive group (39.5%, 145/367, p<0.05). A higher proportion of women with pre-eclampsia was observed (81%, 294/363) among women who resided in rural areas compared with urban residents (19%, 69/363), p<0.001) (table 1).
Table 1.
Sociodemographic and economic characteristics of women with pre-eclampsia and normotensive women in Sidama region, Southern Ethiopia from 8 August 2019 to 1 October 2020
| Variables | Women with pre-eclampsia (n=363) | Normotensive women (n=367) | Total (n=730) | P value |
| Maternal age (in year) | 25.42±4.76 | 24.6±4.48 | 25.02±4.64 | |
| Maternal education | ||||
| No formal education | 33 (9.1) | 16 (4.3) | 49 (6.7) | <0.05 |
| Primary education | 164 (45.2) | 145 (39.5) | 309 (42.3) | |
| Secondary education | 98 (27) | 110 (30) | 208 (28.5) | |
| College/university | 68 (18.7) | 96 (26.2) | 164 (22.5) | |
| Husband education | ||||
| No formal education | 15 (4.1) | 7 (1.9) | 22 (3) | <0.05 |
| Primary education | 122 (33.6) | 87 (23.7) | 209 (28.5) | |
| Secondary education | 99 (27.3) | 117 (31.9) | 216 (29.6) | |
| College/university | 127(35) | 156 (42.5) | 283 (38.8) | |
| Maternal occupation | ||||
| House wife | 191 (52.6) | 163 (44.4) | 354 (48.5) | >0.05 |
| Merchant | 70 (19.3) | 76 (20.7) | 146 (20) | |
| Employed | 64 (17.6) | 88 (24) | 152 (20.8) | |
| Student | 23 (6.3) | 21 (5.7) | 44 (6) | |
| Farmer | 10 (2.8) | 10 (2.7) | 20 (2.7) | |
| Daily labourer | 5 (1.4) | 9 (2.5) | 14 (1.9) | |
| Husband occupation | ||||
| Employed | 116 (32) | 149 (40.6) | 265 (36.3) | <0.05 |
| Merchant | 126 (34.7) | 136 (37.1) | 262 (35.9) | |
| Farmer | 75 (20.7) | 45 (12.3) | 120 (16.4) | |
| Daily labourer | 31 (8.5) | 23 (6.3) | 54 (7.4) | |
| Student | 7 (1.9) | 10 (2.7) | 17 (2.3) | |
| Unemployed | 8 (2.2) | 4 (1.1) | 12 (1.6) | |
| Place of residence | ||||
| Rural | 294 (81) | 331 (90.4) | 104 (14.3) | <0.001 |
| Urban | 69 (19) | 35 (9.6) | 625 (85.7) | |
| Wealth Index | ||||
| Low | 157 (43.3) | 95 (26) | 252 (34.6) | <0.001 |
| Middle | 105 (28.9) | 139 (28) | 244 (33.5) | |
| Rich | 101 (27.8) | 132 (36.1) | 233 (32) |
A p<0.05 was considered statistically significant.
Obstetric characteristics of women with pre-eclampsia and normotensive
Compared with the normotensive group (35.7%, 131/367), a higher proportion of women with pre-eclampsia (40.8%, 148/363, p<0.001) was observed in Yirgalem hospital. A higher proportion of twins was reported in the pre-eclampsia group (7.2%, 26/363) compared with the normotensive group (4.6%, 17/367, p>0.05). However, there was no significant difference between the two groups. A higher proportion of women with pre-eclampsia (28.4%, 103/363) was observed among women who were admitted at <34 weeks compared with the normotensive group (24.5%, 91/367, p<0.05) (table 2).
Table 2.
Obstetrics factors for women with pre-eclampsia and normotensive women in Sidama region, Southern Ethiopia from 1 August 2019 to 1 October 2020
| Variables | Women with pre-eclampsia (n=363) | Normotensive women (n=367) | Total (n=730) | P value |
| Fetal sex | ||||
| Male | 202 (55.6) | 195 (53.1) | 397 (54.4) | >0.05 |
| Female | 161 (44.4) | 172 (46.9) | 333 (45.6) | |
| No of neonates delivered | ||||
| Singleton | 337 (92.8) | 350 (95.4) | 687 (95.4) | >0.05 |
| Twin | 26 (7.2) | 17 (4.6) | 43 (5.9) | |
| Gravida | ||||
| 1 | 46 (12.7) | 77 (21) | 123 (16.8) | >0.05 |
| 2–3 | 253 (69.7) | 208 (56.7) | 461 (63.2) | |
| ≥4 | 64 (17.6) | 82 (22.3) | 146 (20) | |
| Parity | >0.05 | |||
| Nullipara | 12 (3.3) | 5 (1.4) | 17 (2.3) | |
| 1 | 37 (10.2) | 94 (25.6) | 131 (17.9) | |
| 2–3 | 264 (72.4) | 222 (60.5) | 486 (66.6) | |
| ≥4 | 50 (13.8) | 46 (12.5) | 96 (13.2) | |
| Interpregnancy Interval (IPI) | ||||
| <24 months (short (IPI) | 8 (2.2) | 4 (1.1) | 12 (1.6) | <0.001 |
| 24–59 months (optimal IPI) | 180 (49.6) | 263 (71.7) | 443 (60.7) | |
| 60+ months (long IPI) | 115 (31.7) | 35 (9.5) | 150 (20.5) | |
| Not applicable (prim) | 60 (16.5) | 65 (17.7) | 125 (17.1) | |
| Gestational age at admission (week) | ||||
| <34 | 103 (28.4) | 91 (24.5) | 194 (26.6) | <0.05 |
| 34–37 | 260 (71.6) | 276 (75.5) | 536 (73.4) | |
| Maternal intensive care unit admission | ||||
| Yes | 5 (1.4) | 1 (0.3) | 6 (0.8) | >0.05 |
| No | 358 (98.6) | 366 (99.7) | 724 (99.2) | |
| Gestational age at delivery (week) | ||||
| Extremely preterm (<28) | 10 (2.8) | 5 (1.4) | 15 (2.1) | <0.001 |
| Very preterm (28–32) | 24 (6.6) | 1 (0.3) | 25 (3.4) | |
| Moderate to late preterm (32–37) | 123 (33.9) | 67 (18.3) | 190 (26) | |
| Term+ (≥37) | 206 (56.7) | 294 (80) | 500 (68.5) | |
| Hospitals | ||||
| Adare general hospital | 60 (16.5) | 109 (29.7) | 169 (23.2) | |
| Hawassa referral hospital | 53 (14.6) | 47 (12.8) | 100 (13.7) | |
| Yirgalem general hospital | 148 (40.8) | 131 (35.7) | 279 (38.2) | <0.001 |
| Hula primary hospital | 7 (1.9) | 7 (1.4) | 12 (1.6) | |
| Bona general hospital | 51 (14) | 29 (7.9) | 80 (11) | |
| Chuko primary hospital | 11 (3) | 6 (1.6) | 17 (2.3) | |
| Daye primary hospital | 33 (9.1) | 40 (10.9) | 73 (10) | |
A p<0.05 was considered statistically significant.
Incidence of adverse perinatal outcomes women with pre-eclampsia
There were 224 adverse perinatal outcomes observed in the 363 pre-eclampsia women compared with 136 adverse perinatal outcomes in the 367 normotensive women (p<0.001). There were 23 early neonatal deaths reported in the pre-eclampsia group compared with 6 deaths in the normotensive group (p<0.001). Also, there were 96 preterm births observed in the pre-eclampsia group compared with 17 preterm births in the normotensive group (p<0.001). There were 35 perinatal deaths reported in the pre-eclampsia group compared with 16 deaths in the normotensive group (p<0.05) (table 3).
Table 3.
Neonatal outcomes among women with pre-eclampsia and normotensive women in Sidama region Southern Ethiopia from 8 August 2019 to 1 October 2020
| Variables | Women with pre-eclampsia (n=363) | Normotensive women (n=367) | Total (n=730) | P value |
| Birth weight of neonate (g) | ||||
| <1500 | 33 (9.1) | 6 (1.6) | 39 (5.3) | <0.001 |
| 1500–2499 | 103 (28.4) | 31 (8.4) | 134 (18.4) | |
| 2500–3999 | 211 (58.1) | 302 (82.3) | 513 (70.3) | |
| ≥4000 | 16 (4.4) | 28 (7.6) | 44 (6) | |
| Apgar score <7 at 1 min | 64 (17.6) | 52 (14.2) | 116 (15.9) | <0.05 |
| Apgar score <7 at 5 min | 62 (17.1) | 54 (14.7) | 116 (15.9) | >0.05 |
| Intrauterine growth restriction | 22 (6.1) | 4 (1.1) | 26 (3.6) | <0.001 |
| Stillbirth | 21 (5.8) | 11 (3) | 32 (4.4) | <0.05 |
| Early neonatal death | 23 (6.3) | 6 (1.6) | 29 (4) | <0.001 |
| Preterm birth | 96 (26.4) | 17 (4.6) | 113 (15.5) | <0.001 |
| Perinatal death | 35 (9.6) | 16 (3.8) | 49 (6.7) | <0.05 |
| Low birth weight | 98 (27) | 73 (19.9) | 171 (23.4) | <0.05 |
| Small for gestational age | 66 (18.2) | 30 (8.2) | 96 (13.2) | <0.001 |
| Birth asphyxia | 39 (10.7) | 15 (4.1) | 54 (7.4) | <0.05 |
| Admission to NICU | 88 (24.2) | 39 (10.6) | 127 (17.4) | <0.001 |
| Adverse perinatal outcomes | 224 (61.7) | 136 (37.1) | 360 (49.3) | <0.001 |
A p<0.05 was considered statistically significant.
NICU, neonatal intensive care unit.
Women with or without severity features of pre-eclampsia on adverse perinatal outcomes and other risk factors
In the bivariable log-binomial logistic regression model, the following variables were identified as candidate variables for multivariable log-binomial logistic regression analysis: maternal age, maternal and husband’s education, maternal and husband’s occupation, parity, gravidity, wealth index, women without severe features of pre-eclampsia, mode of delivery, women with severe features of pre-eclampsia, maternal ICU admission, systolic and diastolic BP.
After controlling for confounders, we identified significant risk factors for adverse perinatal outcomes as women with severe features of pre-eclampsia, those admitted to hospital at <34 weeks, women without severe features of pre-eclampsia, maternal age, women with no formal education or with only primary school education and women with high systolic BP.
Women with severe feature of pre-eclampsia had a 46% (adjusted relative risk, aRR 1.46, 95% CI 1.38 to 2.77) higher risk for adverse perinatal outcomes compared with women without severe features of pre-eclampsia. Women without severe features of pre-eclampsia had a 39% (aRR 1.39, 95% CI 1.21 to 1.56) higher risk for adverse perinatal outcomes compared with women in the normotensive group. Maternal age was found to have a significantly higher risk on adverse perinatal outcomes of women with pre-eclampsia (β=1.9, 95% CI 1.5 to 3.3) compared with normotensive women, while other factors were kept constant. Women who were admitted to the hospital at <34 weeks had a 15% (aRR 1.15, 95% CI: 1.03 to 1.28) higher risk for adverse perinatal outcomes compared with women who were admitted between 34 and 37 weeks (table 4).
Table 4.
A multivariable log-binomial logistic regression model for risk factors for adverse perinatal outcomes among women with pre-eclampsia in Sidama region southern Ethiopia from 8 August 2019 to 1 October 2020
| Variables | Adverse perinatal outcomes | Unadjusted RR (95% Cl) | Adjusted RR (95% Cl†) | |
| Yes (n=360) | No (n=370) | |||
| Maternal age (in year) | 25.42±4.76 | 24.6±4.48 | 2.2** (1.8 to 3.9) | 1.9* (1.5 to 3.3) |
| Parity | ||||
| Nullipara | 11 (64.7) | 6 (35.3) | 0.94 (0.64 to 1.78) | 0.86 (0.65 to 1.78) |
| 1 | 139 (43.7) | 179 (56.3) | 0.68*** (0.57 to 0.80) | 0.86 (0.60 to 1.22) |
| 2–3 | 148 (51.7) | 138 (48.3) | 0.83* (0.70 to 0.97) | 0.93 (0.72 to 1.19) |
| ≥4 | 62 (56.9) | 47 (43.1) | 1 | 1 |
| Maternal education | ||||
| No formal education | 32 (63.3) | 17 (34.7) | 1.52** (1.19 to 1.93) | 1.41** (1.14 to 1.73) |
| Primary education | 175 (56.6) | 134 (43.4) | 1.30** (1.08 to 1.57) | 1.22* (1.06 to 1.46) |
| Secondary education | 84 (40.4) | 124 (59.6) | 0.99 (0.79 to 1.23) | 0.56 (0.44 to 1.25) |
| College/university | 69 (42.1) | 95 (57.9) | 1 | 1 |
| Husband education | ||||
| No formal education | 17 (77.3) | 5 (22.7) | 1 | 1 |
| Primary education | 123 (58.9) | 86 (41.1) | 0.76* (0.59 to 0.98) | 0.92 (0.76 to 1.97) |
| Secondary education | 105 (48.6) | 111 (51.4) | 0.62** (0.48 to 0.81) | 0.83 (0.67 to 1.04) |
| College/university | 115 (40.6) | 168 (59.4) | 0.52*** (0.40 to 0.68) | 0.74 (0.57 to 2.97) |
| Wealth Index | ||||
| Low | 176 (69.6) | 77 (30.4) | 1.77*** (1.48 to 2.12) | 1.72 (0.44 to 2.06) |
| Middle | 98 (40.2) | 146 (59.8) | 1.03 (0.83 to 1.29) | 1.02 (0.82 to 1.28) |
| Rich | 86 (36.9) | 147 (63.1) | 1 | 1 |
| Gravidity | ||||
| 1 | 127 (42.6) | 171 (57.4) | 0.81 (0.91 to 1.96) | 0.84 (0.72 to 1.97) |
| 2–3 | 154 (52.4) | 140 (47.6) | 0.96 (0.80 to 1.15) | 0.95 (0.81 to 1.11) |
| ≥4 | 79 (57.2) | 59 (42.8) | 1 | 1 |
| Mode of delivery | ||||
| Spontaneous vaginal delivery | 205 (51.5) | 193 (48.5) | 0.89 (0.77 to 1.04) | 0.12 (0.78 to 1.16) |
| Caesarean section | 143 (46.3) | 166 (53.7) | 1.01 (0.67 to 1.561) | 1.32 (0.85 to 2.34) |
| Vacuum assisted delivery | 12 (52.2) | 11 (47.8) | 1 | 1 |
| Gestational age at admission (week) | ||||
| <34 | 113 (58.2) | 81 (41.8) | 1.11 (0.97 to 1.28) | 1.15* (1.03 to 1.28) |
| 34–47 | 247 (46.1) | 289 (53.9) | 1 | 1 |
| Maternal ICU admission | ||||
| Yes | 4 (80) | 1 (20) | 1.67**(1.16 to 2.41) | 1.22 (0.75 to 3.19) |
| No | 356 (49.1) | 369 (50.9) | 1 | 1 |
| Women without severe feature of pre-eclampsia | ||||
| Yes | 159 (66.8) | 79 (33.2) | 1.67*** (1.39 to 1.93) | 1.39*** (1.21 to 1.56) |
| No | 201 (40.9) | 291 (59.1) | 1 | 1 |
| Women with severe feature of pre-eclampsia | ||||
| Yes | 99 (79.2) | 26 (20.8) | 1.58*** (1.25 to 1.85) | 1.46*** (1.38 to 2.77) |
| No | 261 (43.1) | 344 (56.9) | 1 | 1 |
| Eclampsia | ||||
| Yes | 32 (82.1) | 7 (17.9) | 1.61*** (1.38 to 1.92) | 1.34 (0.41 to 1.83) |
| No | 328 (47.5) | 363 (52.5) | 1 | 1 |
| Systolic blood pressure (mm Hg) | ||||
| <140 | 136 (37.1) | 231 (62.9) | 1 | 1 |
| 140–159 | 162 (62.3) | 98 (37.7) | 1.55*** (1.35 to 1.85) | 1.37*** (1.19 to 1.59) |
| ≥160 | 62 (60.2) | 41 (39.8) | 1.60*** (1.33 to 1.92) | 1.34** (1.13 to 1.58) |
| Diastolic blood pressure (mm Hg) | ||||
| <90 | 136 (37.1) | 231 (62.9) | 1 | 1 |
| 90–109 | 180 (62.3) | 109 (37.7) | 1.68*** (1.43 to 1.97) | 1.12 (0.21 to 2.03) |
| ≥110 | 44 (59.5) | 30 (40.5) | 1.60*** (1.27 to 2.02) | 1.43 (0.96 to 2.43) |
| Magnesium sulfate treatment | ||||
| Yes | 74 (43.8) | 95 (56.2) | 0.65*** (0.57 to 0.74) | 0.56 (0.36 to 1.23) |
| No | 286(51) | 275(49) | 1 | 1 |
| Antihypertensive drug treatment | ||||
| Yes | 124 (33.5) | 178 (49.4) | 0.64*** (0.56 to 0.73) | 0.84 (0.40 to 1.75) |
| No | 246 (66.5) | 182 (50.6) | 1 | 1 |
| Dexamethasone treatment | ||||
| Yes | 56 (48.7) | 59 (51.3) | 0.54 (0.34 to 1.81) | 0.45 (0.23 to 1.98) |
| No | 304 (49.4) | 311 (50.6) | 1 | 1 |
*P<0.05, **p<0.01, ***p<0.001.
ICU, intensive care unit; RR, relative risk.
Discussion
In this study, more adverse perinatal outcomes occurred among women with pre-eclampsia compared with normotensive women after controlling for confounders. Perinatal death, stillbirth, small for gestational age, preterm birth, birth asphyxia and low birth weight were higher in the pre-eclampsia group compared with the normotensive group. We identified significant risk factors for adverse perinatal outcomes such as women with severe feature of pre-eclampsia and women who were admitted to the hospital at <34 weeks.
A higher adverse perinatal outcome was observed in the pre-eclampsia group compared with the normotensive group. This finding was similar to another study conducted in southwest Ethiopia in 2021, which found that a higher rate of adverse perinatal outcomes was observed among women with HDPs (64.1%) compared with normotensive women (32.8%).27 This finding was lower than the finding of a study conducted in Tigray Ethiopia in 2020 (66.4% vs 22.2%).20 A reduction in the utilisation gaps of ANC practice is needed to end preventable deaths of newborns.28 Women who had not had ANC attendance were three times more likely to have unfavourable perinatal outcomes as compared with women who had attended ANC.14
A higher perinatal death rate was reported in the pre-eclampsia group compared with the normotensive group. This finding was consistent with another study conducted in southwest Ethiopia in 2021, which found that a higher perinatal death rate occurred in women with HDPs (21.2%) compared with normotensive women (6.2%).27 This finding of this study was also lower than a study conducted in Ethiopia in 2020 (15.0% vs 2.5%).20 Women who attended at least one ANC were found to have a 58% lower risk of perinatal mortality as compared with women who did not receive any ANC follow-up in Ethiopia.29
A higher stillbirth rate was observed in the pre-eclampsia group compared with the normotensive group. This finding was slightly lower than the findings of another study conducted in Ghana in 2015, which found that a higher stillbirth rate was observed among women with pre-eclampsia (6.2%) compared with normotensive women (1.3%).30 Similarly, this finding was lower than the finding of a study conducted in Multicounty survey in 2014 (6.4% vs 1.9%).31 Women who attended at least one ANC session were found to have a 66% lower risk of stillbirth rate as compared with mothers who did not receive any ANC follow-up in Ethiopia.29
A higher small for gestational age rate was observed in the pre-eclampsia group compared with the normotensive group. This finding was higher than another study conducted in Ghana in 2015, which found that a small for gestational age rate was observed among more women with pre-eclampsia (14.3%) compared with normotensive women (2.3%)30 and in Southwest Ethiopia in 2021 (9.3% vs 2.3%).27 This finding was lower than the finding of another study conducted in Ethiopia in 2020 (36.7% vs 10.7%).20 Early detection and management of pre-eclampsia may reduce small for gestational age rate among newborns.
A higher preterm birth rate was observed in the pre-eclampsia group compared with the normotensive group. This finding was lower than a study conducted in Ethiopia, which found that a higher preterm birth rate was observed among women with pregnancy-induced hypertension (PIH) (40.8%) compared with normotensive women (5.6%).20 This finding was also lower than the findings of a study conducted in southwest Ethiopia in 2021 (39.4% vs 10.6%).27 Furthermore, this finding was slightly lower than a study conducted in Haiti in 2019 (27.9% vs 9.9%).32 The difference in incidence of preterm birth across the studies might be due to the difference in quality of ANC services and the difference in guidelines used for the management of pre-eclampsia.
A higher birth asphyxia rate was reported in the pre-eclampsia group compared with the normotensive group. This finding was higher than the finding of another study conducted in Ethiopia in 2020, particularly in the Tigray region, which found that the birth asphyxia rate was higher among women with PIH (39.6%) compared with normotensive women (10.9%).20 This finding was slightly higher than the birth asphyxia rate reported (10.7%), compared with the study conducted in North West Ethiopia in 2018 (10.1%).9 Monitoring the fetus for signs of asphyxia, usually by assessing the fetal heart rate either during prenatal care for fetuses at risk or during labour, can determine which fetuses are at risk of stillbirth.33
A higher low birthweight rate was observed in the pre-eclampsia group compared with the normotensive group. This finding was higher than findings of the Multicounty Survey in 2014, which found that a higher low birth weight rate was reported among women with pre-eclampsia (26.1%) compared with normotensive women (9.4%)31 and a study conducted in southwestern Ethiopia in 2021, which found that a higher low birth weight rate was observed among women with HDP (39.8% vs 12.7%).27 This finding was lower than the findings of another study conducted in Ghana in 2015 (46.2% vs 6.8%).30 One study in Ethiopia found that women who did not attend ANC follow-up were three times more likely to deliver low birth weight babies compared with those who had at least one ANC follow-up.34
Women with severe features of pre-eclampsia had a higher risk for adverse perinatal outcomes compared with women without severe features of pre-eclampsia. A study from Brazil in 2018 found that in terms of pre-eclampsia with severity, severe pre-eclampsia was associated with birth weight <2500 g in 59% of cases, and mild PE was associated with birth weight ≥2500 g in 85.5% of cases.1 In 2015, one study from India found that those women with severe pre-eclampsia had a higher perinatal mortality when compared with those with mild pre-eclampsia.35
Women who were admitted to a hospital at <34 weeks had a higher risk of adverse perinatal outcomes compared with women who were admitted between 34 and 37 weeks. This finding was similar to another study conducted in Ethiopia in 2020 that patients with early onset of pre-eclampsia without severe feature were 25.9 times more likely to develop perinatal complication as compared with late-onset pre-eclampsia after 34 weeks.16 These increased perinatal complications might be explained by the progression of pre-eclampsia to severe diseases in those women who developed pre-eclampsia before 34 weeks, which is associated with high preterm birth.36
Limitations of the study
One limitation could be recall bias linked to gestational age, which was calculated based on the women’s recall of their last menstrual period. However, women who could not remember the approximate gestational age were given an ultrasound scan. Social desirability could have been present because data were collected in face-to-face interviews, which could have led to socially acceptable answers. This study is not generalisable as it was limited to one region of the country, and it was limited to women who received hospital care. It also only measured short-term morbidity in infants, so it did not assess the risk of pre-eclampsia on later mortality, growth, neurodevelopment or other important health outcomes. One strength that could be linked to this study was based on a prospective cohort, which minimised the risk of selection and recall bias.
Conclusion
In this study, more adverse perinatal outcomes occurred among women with pre-eclampsia after controlling for confounders. Early detection and management of pre-eclampsia may improve maternal and infant outcomes. We identified significant risk factors for adverse perinatal outcomes as women with severe features of pre-eclampsia, those admitted to hospital at <34 weeks, women without severe features of pre-eclampsia, maternal age, women with no formal education or with only primary school education, and women with high systolic BP. This paper highlights the significantly elevated perinatal risks associated with pre-eclampsia, especially when it has severe features.
Supplementary Material
Acknowledgments
We thank University of Gondar, Institute of Public Health, College of Medicine and Health Sciences for providing us the opportunity to conduct this study. We also thank supervisors for reviewing and editing the report of this PhD project. We thank Dorothy L. Southern for her critical review of this paper and for her support in editing and training in scientific writing. We also thank study participants who participated in this study.
Footnotes
Contributors: This study was carried outby all authors collaboratively. BJ, MA and KAG contributed to conceptualising and designing the study, curating and analysing data and writing the first draft. Also, BJ, MA, TA and KAG managed the investigation, literature searches, methodology review, writing and contributed to data collection; BJ, MA, TA and KAG contributed to the manuscript review, resource, preparation and editing. All the authors read and agreed to the final manuscript. BJ accepts full responsibility for the work and/or the conduct of the study, had access to the data, and controlled the decision to publish.
Funding: The current study was funded by a grant with R.No: (O/V/P/RCS/044/2019 on March 2019) from the University of Gondar, Ethiopia.
Competing interests: None declared.
Patient and public involvement: Patients and/or the public were involved in the design, or conduct, or reporting, or dissemination plans of this research. Refer to the Methods section for further details.
Provenance and peer review: Not commissioned; externally peer reviewed.
Data availability statement
Data are available on reasonable request.
Ethics statements
Patient consent for publication
Consent obtained directly from patient(s)
Ethics approval
This study was reviewed and ethically approved by the Institutional Review Board of the University of Gondar R.No: (O/V/P/RCS/044/2019 in March 2019). Participants gave informed consent to participate in the study before taking part.
References
- 1.Anselmini M, Rodrigues LK, Balestrin B, et al. Perinatal outcome of hypertensive pregnant women is related to the severity of preeclampsia. Clin Biomed Res 2018;38:116–22. 10.4322/2357-9730.76514 [DOI] [Google Scholar]
- 2.Townsend R, O'Brien P, Khalil A. Current best practice in the management of hypertensive disorders in pregnancy. Integr Blood Press Control 2016;9:79–94. 10.2147/IBPC.S77344 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Mersha AG, Abegaz TM, Seid MA. Maternal and perinatal outcomes of hypertensive disorders of pregnancy in Ethiopia: systematic review and meta-analysis. BMC Pregnancy Childbirth 2019;19:458. 10.1186/s12884-019-2617-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Berhe AK, Kassa GM, Fekadu GA, et al. Prevalence of hypertensive disorders of pregnancy in Ethiopia: a systemic review and meta-analysis. BMC Pregnancy Childbirth 2018;18:34. 10.1186/s12884-018-1667-7 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Mini demographic and health survey report Ethiopia 2019.
- 6.Endalamaw A, Engeda EH, Ekubagewargies DT, et al. Low birth weight and its associated factors in Ethiopia: a systematic review and meta-analysis. Ital J Pediatr 2018;44:141. 10.1186/s13052-018-0586-6 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Mulatu T, Debella A, Feto T, et al. Determinants of stillbirth among women who gave birth at Hiwot Fana specialized university Hospital, eastern Ethiopia: a facility-based cross-sectional study. SAGE Open Med 2022;10:205031212210763–7. 10.1177/20503121221076370 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Getaneh T, Asres A, Hiyaru T, et al. Adverse perinatal outcomes and its associated factors among adult and advanced maternal age pregnancy in Northwest Ethiopia. Sci Rep 2021;11:14072. 10.1038/s41598-021-93613-x [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Melese MF, Badi MB, Aynalem GL. Perinatal outcomes of severe preeclampsia/eclampsia and associated factors among mothers admitted in Amhara region referral hospitals, North West Ethiopia, 2018. BMC Res Notes 2019;12:147. 10.1186/s13104-019-4161-z [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.National Strategy for Newborn and Child Survival . Maternal and child health Directorate federal Ministry of health in Ethiopia, 2015. [Google Scholar]
- 11.Minstry of Health Ethiopia . Health sector transformation plan II HSTP II 2020/21-2024/25, 2021. [Google Scholar]
- 12.National antenatal care guideline in Ethiopia, 2022. Available: https://e-library.moh.gov.et/library/wp-content/uploads/2022/03/Anc-Guideline_Feb-24-2022.pdf
- 13.Wakgar N, Dulla D, Daka D. Maternal near misses and death in southern Ethiopia: a retrospective study. Ethiopian Journal of Reproductive Health 2019;11:17–25. [Google Scholar]
- 14.Asseffa NA, Demissie BW. Perinatal outcomes of hypertensive disorders in pregnancy at a referral Hospital, southern Ethiopia. PLoS One 2019;14:e0213240. 10.1371/journal.pone.0213240 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Deneke YS, Afework MF, Tessema TT, et al. Cause, magnitude and contributing factors for maternal death in selected hospitals in SNNPR between 2007/2008 and 2009/2010.
- 16.Belay Tolu L, Yigezu E, Urgie T, et al. Maternal and perinatal outcome of preeclampsia without severe feature among pregnant women managed at a tertiary referral hospital in urban Ethiopia. PLoS One 2020;15:e0230638. 10.1371/journal.pone.0230638 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.MOH . Obstetrics management protocol for hospitals. Ethiopia, 2021. [Google Scholar]
- 18.The International Society for the Study of Hypertension in Pregnancy:The hypertensive disorders of pregnancy: ISSHP classification, diagnosis & management recommendations for international practice (Pregnancy Hypertension), 2018. Available: http://www.isshp.org/guidelines.ISSHP [DOI] [PubMed]
- 19.Child growth standards. Available: https://www.who.int/tools/child-growth-standards
- 20.Berhe AK, Ilesanmi AO, Aimakhu CO, et al. Effect of pregnancy induced hypertension on adverse perinatal outcomes in Tigray regional state, Ethiopia: a prospective cohort study. BMC Pregnancy Childbirth 2020;20:7. 10.1186/s12884-019-2708-6 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Jikamo B, Adefris M, Azale T, et al. Cultural adaptation and validation of the Sidamic version of the world Health organization Quality-of-Life-Bref scale measuring the quality of life of women with severe preeclampsia in southern Ethiopia, 2020. Health Qual Life Outcomes 2021;19:239. 10.1186/s12955-021-01872-z [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Koo TK, Li MY, Terry Koo K K. A guideline of selecting and reporting intraclass correlation coefficients for reliability research. J Chiropr Med 2016;15:155–63. 10.1016/j.jcm.2016.02.012 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Chan LL, Idris N. Validity and reliability of the instrument using exploratory factor analysis and Cronbachâ'™s alpha. International Journal of Academic Research in Business and Social Sciences 2017;7. 10.6007/IJARBSS/v7-i10/3387 [DOI] [Google Scholar]
- 24.Hosmer DW, Lemeshow S. Applied logistic regression. New York: John Wiley & Sons, 1989. [Google Scholar]
- 25.David Garson G. Testing statistical assumptions, 2012: 44–5. http://www.statisticalassociates.com [Google Scholar]
- 26.Hansen AM. Goodness-Of-Fit tests for autoregressive logistic regression models and generalized linear mixed models 2012.
- 27.Jaleta DD, Gebremedhin T, Jebena MG. Perinatal outcomes of women with hypertensive disorders of pregnancy in Jimma medical center, Southwest Ethiopia: retrospective cohort study. PLoS One 2021;16:e0256520. 10.1371/journal.pone.0256520 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Shukla VV, Carlo WA. Review of the evidence for interventions to reduce perinatal mortality in low- and middle-income countries. Int J Pediatr Adolesc Med 2020;7:4–10. 10.1016/j.ijpam.2020.02.004 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Shiferaw K, Mengiste B, Gobena T, et al. The effect of antenatal care on perinatal outcomes in Ethiopia: a systematic review and meta-analysis. PLoS One 2021;16:e0245003. 10.1371/journal.pone.0245003 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 30.Browne JL, Vissers KM, Antwi E, et al. Perinatal outcomes after hypertensive disorders in pregnancy in a low resource setting. Trop Med Int Health 2015;20:1778–86. 10.1111/tmi.12606 [DOI] [PubMed] [Google Scholar]
- 31.Abalos E, Cuesta C, Carroli G, et al. Pre-Eclampsia, eclampsia and adverse maternal and perinatal outcomes: a secondary analysis of the world Health organization multicountry survey on maternal and newborn health. BJOG: Int J Obstet Gy 2014;121:14–24. 10.1111/1471-0528.12629 [DOI] [PubMed] [Google Scholar]
- 32.Bridwell M, Handzel E, Hynes M, et al. Hypertensive disorders in pregnancy and maternal and neonatal outcomes in Haiti: the importance of surveillance and data collection. BMC Pregnancy Childbirth 2019;19:208. 10.1186/s12884-019-2361-0 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Abalos E, Cuesta C, Grosso AL, et al. Global and regional estimates of preeclampsia and eclampsia: a systematic review. Eur J Obstet Gynecol Reprod Biol 2013;170:1–7. 10.1016/j.ejogrb.2013.05.005 [DOI] [PubMed] [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 2012;12:4. [PMC free article] [PubMed] [Google Scholar]
- 35.Aabidha PM, Cherian AG, Paul E, et al. Maternal and fetal outcome in pre-eclampsia in a secondary care hospital in South India. J Family Med Prim Care 2015;4:257-60. 10.4103/2249-4863.154669 [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Muhe LM, McClure EM, Nigussie AK, et al. Major causes of death in preterm infants in selected hospitals in Ethiopia (SIP): a prospective, cross-sectional, observational study. Lancet Glob Health 2019;7:e1130–8. 10.1016/S2214-109X(19)30220-7 [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.
Supplementary Materials
Data Availability Statement
Data are available on reasonable request.