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Research Article

Determinants of preeclampsia and eclampsia among women delivering in county hospitals in Nairobi, Kenya

[version 1; peer review: 2 not approved]
Gorbee G. Logan
https://orcid.org/0000-0002-3667-4213
1, Peter K. Njoroge2, Lambert O. Nyabola3, Marshal M. Mweu
https://orcid.org/0000-0002-2497-2424
4
Gorbee G. Logan
https://orcid.org/0000-0002-3667-4213
1, Peter K. Njoroge2, Lambert O. Nyabola3, Marshal M. Mweu
https://orcid.org/0000-0002-2497-2424
4
PUBLISHED 18 Mar 2020
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Abstract

Background: Preeclampsia is defined as the onset of a new episode of high blood pressure in a woman usually after 20 weeks gestation plus proteinuria, whereas eclampsia is defined as generalized seizures in a pregnant woman who generally has preeclampsia criteria. Preeclampsia and eclampsia are hypertensive disorders of pregnancy and thus, among the top causes of maternal death worldwide. The objective of this study was to investigate risk factors for preeclampsia/eclampsia.
Methods: This was a hospital-based unmatched case-control study carried out among women of reproductive age (15-49 years) who have given birth at Nairobi County Hospitals and admitted to the postnatal ward July-September 2019 with a sample size of 352 participants (88 cases and 264 controls). All cases were selected, while controls were simple random sampled, as per eligibility criteria. Information or data were gathered using a structured interviewer-administered questionnaire and data abstraction tool. Descriptive analysis was carried out, where, categorical variables were presented in percentages or proportions, whereas; continuous variables were presented in means, standard deviations, and range. This was followed by a bivariable mixed-effect logistic regression analysis and a multivariable mixed-effect logistic regression analysis using the significant variables from bivariable analysis.
Results: Of all the 88 cases enrolled in the study 5 (5.68%) had eclampsia and 83 (94.32%) had preeclampsia. There was a significant association between personal history of hypertension (AOR=7.1; 95% CI: 2.6-19.3, p=0.001), Occupation as a housewife (AOR=3.1; 95% CI: 1.1-8.8, p=0.034), nulliparity (AOR=7.5; 95% CI: 1.5-37.5, p=0.015) ,  primiparity (AOR=2.1; 95% CI: 1.1-4.2, p=0.031), advanced maternal age 35-49 years (AOR=5.9; 95% CI: 1.1-33.3, p=0.042), and the occurrence of preeclampsia/eclampsia.
Conclusions: The following conclusions were made regarding the study findings: Personal history of hypertension, older/advanced maternal age (35-49 years), occupation, and parity were factors significantly associated with preeclampsia/eclampsia.

Keywords

Preeclampsia, Eclampsia, Determinants

Corresponding authors: Gorbee G. Logan, Peter K. Njoroge, Lambert O. Nyabola, Marshal M. Mweu
Competing interests: No competing interests were disclosed.
Grant information: This research project was supported by the Government of Liberia, Republic of Liberia scholarship (Ref No. MOH/GOL/EBT/DMA/2784/17).
The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Copyright:  © 2020 Logan GG et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
How to cite: Logan GG, Njoroge PK, Nyabola LO and Mweu MM. Determinants of preeclampsia and eclampsia among women delivering in county hospitals in Nairobi, Kenya [version 1; peer review: 2 not approved]. F1000Research 2020, 9:192 (https://doi.org/10.12688/f1000research.21684.1) First published: 18 Mar 2020, 9:192 (https://doi.org/10.12688/f1000research.21684.1) Latest published: 18 Mar 2020, 9:192 (https://doi.org/10.12688/f1000research.21684.1)

Introduction

Preeclampsia affects 2–10% of pregnant women globally and eclampsia 0.03–0.05%1. However, the overall prevalence of preeclampsia according to studies varies from 4.5% to 23%2. Preeclampsia affects about 4% of pregnancies in the United States of America3. In Kenya, the incidence of preeclampsia is about 0.3%4 while the prevalence is 6.1%5. Similarly in Ethiopia, the prevalence of preeclampsia is about 5%6. In Nigeria, the prevalence of preeclampsia ranges between 2 and 16.7%7.

The maternal mortality ratio in Sub-Saharan Africa is estimated to be 510 maternal deaths per 100,00 live births8. Maternal and fetal complications in addition to maternal and fetal mortality are much greater in mothers with pre-eclampsia and eclampsia than those without2. Preeclampsia is the second top cause of maternal death globally, which may lead to grave maternal complications (stroke, eclampsia, and organ failure), and poor perinatal outcome for the fetus and infant especially intrauterine development restriction, low birth weight, and stillbirth9. Preeclampsia develops in 20% of first pregnancies and entails more than 40% of premature birth resulting from treatment2. About 98% of maternal, fetal, and neonatal death related to preeclampsia and eclampsia occur in low-income countries, with much of this mortality in South Asia and Sub-Saharan Africa10. Preeclampsia also accounts for increasing maternal & perinatal/infant mortality, and it is a major cause of maternal mortality 15–20% in developed countries11.

Preeclampsia and eclampsia are among the hypertensive disorders of pregnancy. About 13% of maternal mortality globally is due to hypertensive disorders of pregnancy and the number is even higher in developing countries with an estimate between 20–80% in Africa and Latin America1.

Many risk factors have been associated with preeclampsia/eclampsia2. Nevertheless, a full account of the risk factors of preeclampsia/eclampsia has not been well established in the Kenyan population4. Therefore, this study was conducted to investigate some risk factors of preeclampsia/eclampsia namely; socio-demographic, reproductive and obstetric, clinical, behavioral and family history-related factors, with a view of informing policy, creating awareness, and formulating strategies to improve antenatal care and delivery services among women of reproductive age in Kenya.

Methods

Study design and setting

This was a hospital-based unmatched case-control study carried out at Nairobi County Hospitals’ postnatal ward. This study design was chosen because it is appropriate for identifying risk factors associated with pre-eclampsia/eclampsia, which are latent conditions among gravid women.

This study was carried out at Mbagathi District Hospital (Kibra), Mama Lucy Kibaki Hospital (Embakasi Central), and Pumwani Maternity Hospital (Kamukunji) in Nairobi County, Kenya; with a catchment population of 4.6 million people, 58% of which are slum dwellers. These are public county hospitals offering primary, secondary, and tertiary health care services to Nairobi residents and neighboring counties such as Kajiado, Kiambu and Machakos counties.

Study population and eligibility of participants

The study population was women of reproductive age (15–49 years) who have given birth at Nairobi County Hospitals and admitted to the postnatal ward from July–September, 2019. The controls and cases were selected from the study population-based outlined criteria for eligibility. A postnatal ward mother that met/satisfied the definition of a case or control and consented to participation was included. Those aged less than 18 years old were included in the study, but both the parent/guardian and patient were required to sign consent and assent forms, respectively. A postnatal ward mother that did not meet the definition of a case or control was excluded from the study.

Case definition and recruitment

A case was defined as a woman of reproductive age (15–49 years) admitted in postnatal wards having been diagnosed of preeclampsia (high blood pressure during pregnancy, ≥140/90 mmHg, plus proteinuria ≥300 mg/24 hours or ≥ 1+ dipstick) or eclampsia (high blood pressure during pregnancy, proteinuria plus generalized seizures) at Nairobi County Hospitals July- September, 2019. All cases that met the case definition were selected during the study period, July-September 2019, to obtain the required sample of 88 cases and the response rate was 100%. Thus, each case was selected after the physician (medical officer or consultant obstetrician/gynecologist) had made a diagnosis (preeclampsia/eclampsia) and client admitted to the postnatal ward.

Control definition and recruitment

Control was defined as a woman of reproductive age (15–49 years) admitted to the postnatal ward without preeclampsia/eclampsia at Nairobi County Hospitals from July-September 2019. Controls were simple randomly sampled from a list of women admitted to each of the three hospitals' post-natal ward without preeclampsia/eclampsia which was recruited at the time of selection of the cases. A total of three controls for each case were selected by the time of selection to cases. The sampling frame was updated as per deliveries taking place in study hospitals from July-September 2019.

Sample size determination

The sample size of 352 participants (264 controls & 88 cases) was determined as specified by Kelsey, Jennifer, and others12 for case-control studies as follow:

n1=(Zα+Zβ)2p¯q¯(r+1)r(p1−p2)2,p1=p2OR1+p2(OR−1)

p¯=p1+rp2r+1,q¯=1−p¯

n2=rn1

N1=(1.96+0.84)2(0.462887323)(0.537112677)(3+1)3(0.591549295−0.42)2=88.3or88(cases)

N2=rn1Totalsamplesize=n1+n2=88+264=352=3(88)=264(controls)

Since the outcome is rare in the Kenyan population, the ratio of 3 controls to 1 case was used in calculating the sample size but still maintains the statistical power of the study; N1 is the number of cases and N2 is the number of controls. Furthermore, P1 is the proportion of cases exposed thus, was the proportion of women with pre-eclampsia/eclampsia that attend less than four antenatal clinic (ANC) visits; P2 is the proportion of controls exposed and this was the proportion of women without pre-eclampsia/eclampsia that attends less than four ANC visit, that was set at 42%13; Zα (1.96) and Zβ (-0.84) were the required values specifying the two-tailed confidence interval (95%) and statistical power (80%) desired respectively. The odds for attending less than four ANC visits-preeclampsia/eclampsia association was been set at 2 (universally acceptable) and r=3, is the ratio of controls to cases. Given these figures, the desired sample size of 352 participants (88 cases and 264 controls) was computed.

Study variables

The dependent variable was pre-eclampsia/eclampsia status measured as a binary categorical variable. The independent variables of interest were maternal age, education, residence, marital status, occupation, ethnicity, religion, maternal age, age at first marriage, age at first pregnancy, number of antenatal care visit, time/trimester of first ANC visit, gravidity, parity, child sex, anaemia in pregnancy, urinary tract infection (UTI) in pregnancy, alcohol use, tobacco use, family history of hypertension, family history of diabetes, personal history of diabetes, personal history of hypertension, and use of traditional treatment or medicine. All of these explanatory variables were more or less potential confounders and a determination of which one is a confounder was made during analysis. A pretested structured interview questionnaire was used to collect primary data from postnatal mothers and a data abstraction tool was also used to collect some secondary data, both available as Extended data14.

Ethical considerations

The research was granted ethical clearance by Kenyatta National Hospital (KNH)-University of Nairobi (UON) Ethics and Research Committee (P426/05/2019) and the Nairobi City County Government - Public health division (Ref. No. NCC/HRD/HRM/11/904/JWN/2019). Furthermore, written consent was obtained from the participants after they were informed about the nature of the study.

Minimization of biases

Before starting data collection, six research assistants (two for each of the three health facilities) were trained on the sampling technique for cases and controls and standard interview skills to reduce systemic error and interview bias. Research assistants were also trained to get information such as the number of antenatal care (ANC) visits, time/trimester of first ANC visit from the patient medical record using data abstraction tool in an attempt to reduce recall bias. Misclassification bias which could affect both cases and controls was minimized by including cases and controls determined by the obstetrician.

Statistical analysis

The filled questionnaires were first checked for completeness then followed by the entry of data collected from the field into Microsoft Excel spreadsheets, cleaned, formatted, coded and audited for quality and consistency using Epi-info software before exporting the dataset to Stata -version 14.0 computer programming software. Descriptive analysis was carried out, where, categorical variables were presented in percentages or proportions, whereas, continuous variables were presented in means and standard deviations. This was followed by bivariable mixed-effect logistic regression analysis and a multivariable mixed-effect logistic regression analysis using the significant variables (p ≤0.20) from the bivariable analysis. A modified Hosmer-Lemeshow goodness-of-fit test was carried out; after which, variables with p≤0.05 were considered as factors associated with preeclampsia/eclampsia.

Results and discussion

Results

Socio-demographic characteristics of the study participants. The study participants were 352, of whom 88 were cases and 264 were controls. Among the cases, preeclampsia accounted for 83 (94.3%) and eclampsia 5 (5.7%). This was a multicenter study conducted in Pumwani Maternity Hospital which had 196 participants (55.7%), Mama Lucy Kibaki Hospital with 99 participants (28.1%) and Mbagathi District Hospital with 57 participants (16.2%). The distribution of study participants by study hospital is presented in Table 1; individual-level responses to questionnaire items are available as Underlying data

Table 1. Distribution of study participants by study hospital.

Study hospitalControls (n=264),
n (%)		Cases (n=88),
n (%)		Total, n (%)
Mama Lucy Kibaki 74 (28.0)25 (28.4)99 (28.1)
Mbagathi District43 (16.3)14 (15.9)57 (16.2)
Pumwanity maternity147 (55.7)49 (55.7)196 (55.7)

The mean maternal age of the study participants was 26.1 years (SD=5.5); the mean maternal age of controls being 26.1 years with a standard deviation 5.3 years (range: 18–41 years) and the mean maternal age of cases being 27.6 years with 5.9 standard deviation (range: 17–42). About 81% of cases and 83% of controls were mothers aged between 20 and 34 years old. Among the controls and cases, 71 (26.9%) and 23 (26.1%) had primary-level education, respectively, whereas 140 (53.0%) of the controls and 40 (45.5%) of cases had a secondary level of education. In terms of marital status, 80.7% of cases and 80.7% of controls were married. The majority of cases 49 (55.7%) and controls 114 (43.2%) had an occupation as housewife.

Concerning the county of residence, 247 (93.6%) of controls and 86 (97.7%) of cases were residents of Nairobi County. Mothers of Kenyan ethnicity accounted for 258 (97.7%) of controls and 86 (97.7%) of cases whereas, those of non-Kenyan ethnicity were 2 (2.3%) of cases and 6 (2.3%) of controls. Among the cases and controls, 97.7% and 97.0% were Christians respectively; whereas Muslim mothers represented 8 (3.0%) controls and 2 (2.3%) of cases. The socio-demographic factors of the study population are presented in Table 2.

Table 2. Socio-demographic characteristics of the respondents.

VariableCases, n (%)Controls, n (%)Total, n (%)
Education Level
   No education1 (1.1)1 (0.4)2 (0.6)
   Primary education23 (26.1)71 (26.9)94 (26.7)
   Secondary education40 (45.5)140 (53.0)180 (51.1)
   Tertiary education24 (27.3)52 (19.7)76 (21.6)
Maternal Age
   <204 (4.55)19 (7.2)23 (6.5)
   20–3471 (80.7)220 (83.3)291 (82.7)
   35–4913 (14.8)25 (9.5)38 (10.8)
Marital status
   Married71 (80.7)213 (80.7)284 (80.7)
   Separated0 (0.0)4 (1.5)4 (1.1)
   Single16 (18.2)45 (17.1)61 (17.3)
   widowed1 (1.1)2 (0.8)3 (0.9)
Occupation
   Salaried employee10 (11.4)26 (10.0)36 (10.2)
   Housewife49 (55.7)114 (43.2)163 (46.3)
   Merchant/business22 (25.0)91 (34.5)113 (32.1)
   Other occupation7 (8.0)33 (12.1)40 (11.4)
County of residence
   Nairobi86 (97.7)247 (93.6)333 (94.6)
   Other counties2 (2.3)17 (6.4)19 (5.4)
Specific place of
residence
   Urban/estate42 (47.7)143 (54.2)185 (52.6)
   Rural0 (0.0)8 (3.0)8 (2.3)
   Informal settlement46 (52.3)113 (42.8)159 (45.2)
Ethnicity
   Kenyan86 (97.7)258 (97.7)344 (97.7)
   Non-Kenyan2 (2.3)6 (2.3)8 (2.3)
Religion
   Christian86 (97.7)256 (97.0)342 (97.2)
   Muslim2 (2.3)8 (3.0)10 (2.8)

The socio-demographic factors associated with preeclampsia/eclampsia. The socio-demographic factors hypothesized to significantly associate with preeclampsia/eclampsia include maternal age, maternal level of education, marital status, maternal occupation, maternal county of residence, and religion.

Compared to mothers aged less than 20 years, mothers 20–34 years of age were 1.5 times more likely to suffer preeclampsia/eclampsia (OR=1.5, 95% CI=0.5-4.7, p=0.451) whereas mothers aged 35–49 years were 2.5 times more likely to experience preeclampsia/eclampsia than mothers aged less than 20 years (OR=2.5, 95% CI=0.7-8.8, p=0.163).

Postnatal mothers from government/private occupation were 1.8 times more likely to suffer from preeclampsia/eclampsia than those from other occupations (OR=1.8, 95% CI=0.6-5.4, p=0.286) whereas those that have an occupation as housewives were 2.0 times more likely to develop preeclampsia/eclampsia than other occupations. Similarly, mothers that have merchant/business occupation were more likely to develop preeclampsia/eclampsia than other occupations (OR=1.1, 95% CI=0.5-2.9, p=0.789).

Postnatal mothers from Nairobi County were at increased risk of preeclampsia/eclampsia compared to those from other counties (OR=3.0, 95% CI=0.7-13.1, p=0.152). The associations between socio-demographic factors and preeclampsia/eclampsia are summarized in Table 3.

Table 3. Association between socio-demographic factors and preeclampsia/eclampsia.

VariableCases, n (%)Controls, n (%)χ2Crude OR (95% CI)p-value
Age group  
   <204 (4.6)19 (7.2)2.44Ref 
   20–3471 (80.7)220 (83.3)1.5 (0.5-4.7)0.451
   35–4913 (14.8)25 (9.5)2.5 (0.7-8.8)0.163
Education Level  
Up to Primary24 (27.3)72 (27.3)2.47Ref 
   Secondary40 (45.5)140 (53.0)0.9 (0.5-1.5)0.603
   Tertiary24 (27.3)52 (19.7)1.4 (0.7-2.7)0.34
Marital Status  
   Married71 (80.7)213 (80.7)0.462 (0.2-16.9)0.524
   Separated/Widowed1 (1.1)6 (2.3)Ref 
   Single16 (18.2)45 (17.1)2.1 (0.2-19.1)0.498
Occupation  
   Salaried employee10 (11.4)26 (9.9)5.341.8 (0.6-5.4)0.286
   House Wife49 (55.7)114 (43.2)2.0 (0.8-4.9)0.116
   Merchant/Business22 (25.0)91 (34.5)1.1 (0.5-2.9)0.789
   Others7 (8.0)33 (12.5)Ref 
County of Residence  
   Nairobi86 (97.7)247 (93.6)2.053.0 (0.7-13.1)0.152
   Other County2 (2.3)17 (6.4)Ref 
Specific Place of Residence  
   Informal/Rural Settlement46 (52.3)121 (45.8)1.09Ref 
   Urban/Estate42 (47.7)143 (54.2)1.3 (0.8-2.1)0.295
Religion  
   Christians86 (97.7)256 (97.0)0.140.7 (0.2-3.6)0.712
   Muslims2 (2.3)8 (3.0)Ref

The reproductive and obstetric factors associated with preeclampsia/eclampsia

We hypothesized that reproductive and obstetrics factors likely associated with preeclampsia/eclampsia were maternal age, age at first marriage, age at first pregnancy, number of ANC visits, time/trimester of first ANC visit, gravidity, parity, and child-Sex.

Nulliparous mothers were 4.8 times more likely to suffer from preeclampsia/eclampsia than multiparous mothers (OR=4.8, 95% CI=1.0-22.4, p=0.045) whereas primiparous mothers were 1.4 times more likely to develop preeclampsia/eclampsia than those that were multiparous (OR=1.4, 95% CI=0.9-2.3, p=0.187). Nulliparous mothers, though, were at increased risk of suffering preeclampsia/eclampsia; however, the association was not statistically significant in that the 95% confidence included 1 despite a p-value of 0.045 (OR=4.8, 95% CI=1.0-22.4, p=0.045). Therefore, there was no significant association between parity and development of preeclampsia and or eclampsia. Compared to mothers aged 20 years and above, teenage mothers were 30% less likely to develop preeclampsia/eclampsia (OR=0.7, 95% CI=0.4-1.3, p=0.199).

Compared to mothers whose first antenatal care visit was in the first trimester of pregnancy, mothers whose first antenatal care visit was in the second and third trimesters were at reduced risk of preeclampsia/eclampsia (OR=0.8, 95% CI=0.5-1.4, p=0.473 and OR=0.5, 95% CI=0.2-1.4, p=0.191). Mothers whose age at first marriage was <20 years old were 10% less likely to develop preeclampsia/eclampsia than those that were ≥20 years old (OR=0.9, 95% CI=0.5-1.6, p=0.659) whereas mothers whose age at first pregnancy was <20 years old were 0.7 times more likely to develop preeclampsia/eclampsia than those that were ≥20 years old (OR=0.7, 95% CI=0.4-1.3, p=0.199). The associations between reproductive and obstetric factors and preeclampsia/eclampsia are summarized in Table 4.

Table 4. Association between reproductive and obstetric factors and preeclampsia/ eclampsia.

VariableCases, n (%)Controls, n (%)χ2Crude OR (95% CI)p-value
Age at First Marriage  
   <2019 (26.4)64 (29.1)0.190.9 (0.5-1.6)0.659
   ≥2053 (73.6)156 (70.9)Ref 
Age at First Pregnancy  
   <2024 (27.3)89 (33.7)1.250.7 (0.4-1.3)0.199
   ≥2064 (72.7)175 (66.3)Ref 
Number of ANC Visits  
   <439 (44.3)106 (40.2)0.471.2 (0.7-1.9)0.492
   ≥449 (55.7)158 (59.9)Ref 
Time/Trimester First ANC Visit 
   Up to First trimester29 (33.0)73 (27.7)1.78Ref 
   Second trimester53 (60.2)162 (61.4)0.8 (0.5-1.4)0.473
   Third Trimester6 (6.8)29 (11.0)0.5 (0.2-1.4)0.191
Gravidity  
   Primigravida37 (42.1)99 (37.5)0.57Ref 
   Multigravida51 (58.0)165 (62.5)0.8 (0.5-1.4)0.449
Parity  
   Nulliparous4 (4.6)3 (1.1)5.084.8 (1.0-22.4) 0.045
   Primiparous42 (47.7)109 (41.3)1.4 (0.9-2.3)0.187
   Multiparous42 (47.7)152 (57.6)Ref 
Child Sex  
   Male41 (46.6)138 (52.3)1.310.5 (0.1-2.2)0.35
   Female44 (50.0)121 (45.8)0.6 (0.1-2.6)0.505
   Multi-sex3 (3.4)5 (1.9)Ref

The clinical factors associated with preeclampsia/eclampsia

Anemia and urinary tract infections in pregnancy were hypothesized to relate significantly with the occurrence of preeclampsia and eclampsia. Compared to mothers with a normal number of pus cells (0–5 hpf) on admission for delivery, mothers with mild-moderate and severe UTI (6–10 hpf and >10 hpf) in pregnancy on admission were 1.7 times more likely to develop preeclampsia/eclampsia (OR=1.7, 95% CI=0.4-7.0, p=0.454). Mothers with mild-moderate and severe levels (7-10.9 g/dl and <7 g/dl) of anemia on admission for delivery were 0.9 times as likely to suffer from preeclampsia/eclampsia than those with normal hemoglobin level (≥11 g/dl); (OR=0.9, 95% CI=0.5-1.6, p=0.625). Associations between clinical factors and preeclampsia/eclampsia are presented in Table 5.

Table 5. Association between clinical factors and preeclampsia/eclampsia status.

VariableCases, n (%)Controls, n (%)χ2Crude OR (95% CI)p-value
Pus cells count on admission for delivery  
Normal3 (23.1)18 (34.0)0.56Ref 
Mild-moderate and severe UTI in pregnancy 10 (76.9)35 (66.0)1.7 (0.4-7.0)0.454
Haemoglobin level on admission for delivery  
Normal67 (77.9)189 (75.3)0.24Ref 
Mild-Moderate and severe level of anaemia 19 (22.1)62 (24.7)0.9 (0.5-1.6)0.625

The behavioural and family history-related factors associated with preeclampsia/eclampsia

Further, the relationships between alcohol use, tobacco use, traditional treatment use, diabetes, and hypertension with preeclampsia/eclampsia were assessed. History of diabetes and hypertension were personal and family history.

Postnatal mothers who used tobacco were 3.9 times more likely to develop preeclampsia/eclampsia than those who did not use tobacco (OR=3.9, 95% CI=1.0-14.9, p=0.046). Postnatal mothers who used tobacco were at increased risk of suffering preeclampsia/eclampsia; however, the association was not statistically significant in that the 95% confidence included 1 despite a p-value of 0.046 (OR=3.9, 95% CI=1.0-14.9, p=0.046). On the other hand, mothers with a personal history of hypertension were 6.3 times more likely to suffer from preeclampsia/eclampsia than those without a personal history of hypertension (OR=6.3, 95% CI=2.7-14.8, p=0.001). In addition, there was a significant association between personal history of hypertension and development of preeclampsia/eclampsia (p<0.001). The associations between behavioural and family history-related factors and preeclampsia/eclampsia are presented in Table 6.

Table 6. Association between behavioral and family history-related factors and preeclampsia/eclampsia.

VariableCases, n (%)Controls, n (%)χ2Crude OR (95% CI)p-value
Alcohol Use  
   YES8 (9.1)17 (6.4)0.71.5 (0.6-3.5)0.404
    NO80 (90.9)247 (93.6)Ref 
Tobacco use  
   YES5 (5.7)4 (1.5)43.9 (1.0-14.9) 0.046
   NO83 (94.3)260 (98.5)Ref 
Personal history of hypertension  
   YES16 (18.2)9 (3.4)17.696.3 (2.7-14.8) <0.001
   NO72 (81.8)255 (96.6)Ref 
Family history of hypertension  
   YES19 (21.6)36 (13.6)3.121.7 (0.9-3.2)0.078
   NO69 (78.4)228 (86.4)Ref 
Family history of diabetes  
   YES4 (4.6)21 (8.0)1.130.6 (0.2-1.7)0.287
   NO84 (95.5)243 (92.1)Ref 
Traditional Treatment use  
   YES4 (4.5)16 (6.1)0.280.7 (0.2-2.3)0.596
   NO84 (95.5)248 (93.9)Ref

Multivariable mixed-effect logistic regression on risk factors for preeclampsia/eclampsia. A multivariable mixed-effect logistic regression model was used to determine the effect of various socio-demographic, reproductive and obstetric, clinical, behavioral and family history-related factors. Only variables that reached p ≤0.2 from the bivariable analysis were moved forward for multivariable analysis. Those variables that are of interest from previous studies were also moved forward for multivariable analysis despite not meeting the stated threshold requirement.

From the best model, mothers with advanced age 35–49 years were 5.9 times more likely to develop preeclampsia/eclampsia when compared to those aged less than 20 years (AOR=5.9, 95% CI=1.1-33.3, p=0.042). Mothers who had an occupation as housewife were significantly more likely to suffer from preeclampsia/eclampsia compared to those with other occupations (AOR = 3.1; 95% CI: 1.1-8.8, p=0.034).

Mothers that had less than four ANC visits were 1.8 times more likely to suffer preeclampsia/eclampsia; however, the association was not statistically significant in that the 95% confidence included 1 despite a p-value of 0.041 (AOR=1.8, 95% CI=1.0-3.3, p=0.041). Compared to mothers who were multiparous, nulliparous and primiparous were significantly associated with increased risk of developing preeclampsia/eclampsia (AOR=7.5, 95% CI=1.5-37.5, p=0.015) and (AOR=2.1, 95% CI=1.1-4.2, p=0.031) respectively.

Mothers with preeclampsia/eclampsia were 7.1 times more likely to have personal history of hypertension comparing to their counterparts (AOR=7.1, 95% CI=2.6-19.3, p=0.001). The associations between risk factors and preeclampsia/eclampsia are presented in Table 7.

Table 7. Risk factors of preeclampsia/eclampsia.

VariableCases, n (%)Controls, n (%)Adjusted OR (95% CI)p-value
Age group
   <204 (4.6)19 (7.2)Ref
   20–3471 (80.7)220 (83.3)2.2 (0.5-8.8)0.28
   35–4913 (14.8)25 (9.5)5.9 (1.1-33.3) 0.042
Occupation
   Salaried employee10 (11.4)26 (9.9)2.1 (0.6-7.5)0.241
   Housewife49 (55.7)114 (43.2)3.1 (1.1-8.8) 0.034
   Merchant/Business22 (25.0)91 (34.5)1.5 (0.5-4.6)0.469
   Others7 (8.0)33 (12.5)Ref
County of residence
   Nairobi86 (97.7)247 (93.6)2.6 (0.6-12.4)0.224
   Other Counties2 (2.3)17 (6.4)Ref
Age at first pregnancy
   <2024 (27.3)89 (33.7)1.05 (0.5-2.1)0.902
   ≥2064 (72.7)175 (66.3)Ref
Number of ANC visits
   <439 (44.3)106 (40.2)1.8 (1.0-3.3) 0.041
   ≥449 (55.7)158 (59.9)Ref
Time/trimester first ANC visit
   Up to First trimester29 (33.0)73 (27.7)Ref
   Second trimester53 (60.2)162 (61.4)0.9 (05-1.7)0.74
   Third Trimester6 (6.8)29 (11.0)0.5 (0.1-1.6)0.214
Parity
   Nulliparous4 (4.6)3 (1.1)7.5 (1.5-37.5) 0.015
   Primiparous42 (47.7)109 (41.3)2.1 (1.1-4.2) 0.031
   Multiparous42 (47.7)152 (57.6)Ref
Haemoglobin level on admission for delivery
   Normal67 (77.9)189 (75.3)Ref
   Mid-Moderate level anaemia and
severe		19 (22.1)62 (24.7)0.9 (0.5-1.9)0.968
Tobacco use
   YES8 (9.1)17 (6.4)1.7 (0.4-7.8)0.518
   NO80 (90.9)247 (93.6)Ref
Personal history of hypertension
   YES16 (18.2)9 (3.4)7.1 (2.6-19.3) <0.001
   NO72 (81.8)255 (96.6)Ref
Family history of hypertension
   YES4 (4.6)21 (8.0)1.2 (0.6-2.5)0.633
   NO84 (95.4)243 (92.0)Ref

Discussion

Women with preeclampsia/eclampsia were more likely to be 35–49 years of age comparing to their counterparts (AOR=5.9, 95% CI=1.1-33.3, p=0.042). This was concurrent with other studies that showed an increased risk in a similar age group11,15,16. A study conducted in Iran has linked the obstetric danger of advanced maternal age to aging-mediated vascular damage2. This is because as a woman gets advanced age, she is more likely to develop heart/blood vessel related problems chiefly due to the steady failure of compliance of said vessels that are mainly linked with the ageing of uterine blood vessels and arterial firmness. Thus, the reason why preeclampsia/eclampsia is more likely in older women is biologically plausible.

The odds of developing preeclampsia/eclampsia were 3.1 times higher in postnatal mothers with occupation as housewife comparing to mothers with other occupations (AOR=3.1, 95% CI=1.1-8.8, p=0.034). The association between occupation as housewife and preeclampsia/eclampsia was statistically significant. A similar finding was obtained from a study done in Nigeria17. This could be due to stress-related factors arising from low socio-economic status and low wealth index.

According to the results of our study, women who were nulliparous or primiparous were at increased risk of developing preeclampsia/eclampsia than those who were multiparous. This was concurrent with several studies that found the same findings1,11,18. Several hypotheses have linked nulliparity to a maternal immune maladaptation2. This is for the reason that nulliparity is due to early trophoblastic invasion and how the mother reacts to it. The breakdown or malfunction of the normal invasion of trophoblastic cells leads to maladaptation of the coiled arterioles, which are linked to the causation of preeclampsia1.

Mothers that attended less than four ANC visits were at increased risk of developing preeclampsia/eclampsia when compared with those that attended four or more ANC visits. This is comparable to a study conducted in Nigeria17. Long-distance to access health facility, limited knowledge about antenatal care (ANC) services coupled with low socio-economic status could possibly be responsible for postnatal mothers not meeting the WHO recommended four or more ANC visits; a situation which could predispose mothers to obstetric complications such as preeclampsia and eclampsia. In this study however, the association between a number of ANC visits and the outcome (preeclampsia/eclampsia) was not statistically significant in that the 95% confidence included 1 despite a p-value of 0.041 (AOR = 1.8; 95% CI: 1.0-3.3, p=0.041).

The study results found out that anemia and UTI in pregnancy were not significantly associated with preeclampsia/eclampsia; however, this finding contradicts studies conducted in Egypt, Sudan, and by WHO19–21.

Women with personal history of hypertension were more likely to suffer from preeclampsia/eclampsia compared with their counterparts (AOR=7.1, 95% CI=2.6-19.3, p=0.001). A similar finding was found in a study conducted in Nigeria17. It is probable that lifestyle modifications/behavioral factors are the reason for influencing women to an increased threat of preeclampsia/eclampsia. For instance, mothers taking-in an unhealthy diet; eating food high in fats and carbohydrates could increase their triglyceride levels, narrowing blood flow, which may predispose them to develop hypertensive disorders in pregnancy.

Limitations of the study. This study had some limitations. First, not all admission for delivery had their hemoglobin level (337 out of 352 study participants) and urinary pus cells count (only 66 out of 352) recorded in the study hospitals, therefore; if this study was repeated in other facilities with better recording of lab results of maternal admission, then the findings could be different. Secondly, there might have been recall bias regarding some factors such as the specific traditional treatment use and purpose of using the said treatment. Lastly, the hospital-based approach included only women attending the study hospitals.

Conclusions

This study indicated that a personal history of hypertension, older/advanced maternal age (35–49 years), occupation, and parity (nulliparous/primiparous) were factors significantly associated with preeclampsia/eclampsia. In this study, only 66 out of 352 participants (18.8%) had their urinary pus cells recorded on admission for delivery and whether UTI in pregnancy is actually not associated with preeclampsia/eclampsia needs further investigation. Anemia in pregnancy was 10% less likely to develop preeclampsia/eclampsia.

Based on the study findings, this study makes the following recommendations to policymakers, county government, hospital management teams, and other relevant institutions:

  • 1. Health Workers in Maternal and Child Health units of health facilities should emphasize the risk factors for preeclampsia and/or eclampsia to pregnant and postnatal mothers during their health talks in the health facilities. These messages should be extended to other pregnant and postnatal mothers in the catchment areas of the health facilities through Community Health Workers.

  • 2. Maternity In-charges should ensure that urinary pus cell count and hemoglobin level for pregnant women are ordered and results recorded in the admission notes for delivery.

  • 3. That future studies should investigate the association between UTI in pregnancy and preeclampsia/eclampsia in a multi-county study.

Data availability

Underlying data

Harvard Dataverse: Replication data for: Determinants of preeclampsia and eclampsia among women delivering in county hospitals in Nairobi, Kenya: https://doi.org/10.7910/DVN/BYFL3J14.

This project contains the following underlying data:

  • Logan preeclampsia dataset Final. (Study dataset)

  • Logan preeclampsia dofile Final2 (do file code for Determinants-Preeclampsia/ eclampsia identification).

Extended data

Harvard Dataverse: Replication data for: Determinants of preeclampsia and eclampsia among women delivering in county hospitals in Nairobi, Kenya: https://doi.org/10.7910/DVN/BYFL3J14.

This project contains the following extended data:

  • Logan Interview Questionnaire & Data Abstarction Tool. (Questionnaire and data abstraction tool used in this study.)

Data are available under the terms of the Creative Commons Zero "No rights reserved" data waiver (CC0 1.0 Public domain dedication).

Acknowledgments

We would like to acknowledge and thank the School of Public Health, College of Health Sciences/University of Nairobi for providing all assistance requested. Special thanks go to the members of the Kenyatta National Hospital-University of Nairobi Ethics and Research Committee and the Nairobi City County Government – Public Health Division for granting me the approval to conduct this research. We are indebted to the management and staff of Pumwani, Mama Lucy Kibaki and Mbagathi hospitals for allowing us to conduct this study within their facilities. Our appreciation goes to the Government of Liberia (GOL), the Republic of Liberia for funding this research and the entire study in Kenya.

Lastly, we wish to acknowledge and thank all the postnatal mothers who participated in this study. Their excitement and willingness to fill the questionnaires made the completion of this research an enjoyable experience. Furthermore, special thanks to the research assistants and data entry clerks who helped us in collecting and entering data.

References

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  • 3.  US Preventive Services Task Force, Bibbins-Domingo K, Grossman DC, et al.: Screening for Preeclampsia: US Preventive Services Task Force Recommendation Statement. JAMA. 2017; 317(16): 1661–1667. PubMed Abstract | Publisher Full Text
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  • 5.  Otieno DAN: FACTORS CONTIBUTING TO ADVERSE OUTCOMES OF PRE-ECLAMPSIA AMONG PREGNANT WOMEN ATTENDING ANTENATAL CLINICS IN KIBERA SLUMS, NAIROBI. 2012. Reference Source
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  • 7.  Osungbade KO, Ige OK: Public health perspectives of preeclampsia in developing countries: implication for health system strengthening. J Pregnancy. 2011; 2011: 481095. PubMed Abstract | Publisher Full Text | Free Full Text
  • 8.  Kirigia JM, Muthuri RD, Nabyonga-Orem J, et al.: Counting the cost of child mortality in the World Health Organization African region. BMC Public Health. 2015; 15(1): 1103. PubMed Abstract | Publisher Full Text | Free Full Text
  • 9.  US Preventive Services Task Force, Grossman DC, Bibbins-Domingo K, et al.: Behavioral Counseling to Promote a Healthful Diet and Physical Activity for Cardiovascular Disease Prevention in Adults Without Cardiovascular Risk Factors: US Preventive Services Task Force Recommendation Statement. JAMA. 2017; 318(2): 167–174. PubMed Abstract | Publisher Full Text
  • 10.  Goldenberg RL, Jones B, Griffin JB, et al.: Reducing maternal mortality from preeclampsia and eclampsia in low-resource countries--what should work? Acta Obstet Gynecol Scand. 2015; 94(2): 148–155. PubMed Abstract | Publisher Full Text
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  • 15.  Tessema GA, Tekeste A, Ayele TA: Preeclampsia and associated factors among pregnant women attending antenatal care in Dessie referral hospital, Northeast Ethiopia: a hospital-based study. BMC Pregnancy Childbirth. 2015; 15(1): 73. Publisher Full Text
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Logan GG, Njoroge PK, Nyabola LO and Mweu MM. Determinants of preeclampsia and eclampsia among women delivering in county hospitals in Nairobi, Kenya [version 1; peer review: 2 not approved]. F1000Research 2020, 9:192 (https://doi.org/10.12688/f1000research.21684.1)
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Reviewer Report 19 Oct 2021
Jussara Mayrink, Federal University of Minas Gerais, Minas Gerais, Brazil 
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https://doi.org/10.5256/f1000research.23904.r96070
Dear authors, there are some suggestions I have about your study: 

Abstract:
  •  Be careful with preeclampsia concept, which is not exclusively linked to proteinuria anymore. Methods section can be more concise and
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Ishag Adam, Faculty of Medicine, University of Khartoum, Khartoum, Sudan 
Not Approved
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https://doi.org/10.5256/f1000research.23904.r65550
The authors investigated an important topic “preeclampsia”. I have some points that need to be addressed.

Abstract:
  • No need to have details of statistic methods in the abstract.
     
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Adam I. Reviewer Report For: Determinants of preeclampsia and eclampsia among women delivering in county hospitals in Nairobi, Kenya [version 1; peer review: 2 not approved]. F1000Research 2020, 9:192 (https://doi.org/10.5256/f1000research.23904.r65550)
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