Risk factors of early and late onset pre-eclampsia

Authors


Reprint request to: Dr Vorapong Phupong, Department of Obstetrics and Gynecology, Faculty of Medicine, Chulalongkorn University, Rama IV Road, Pathumwan, Bangkok 10330, Thailand. Email: vorapong.p@chula.ac.th

Abstract

Aims

The aim of this study was to identify the differences in risk factors between early and late onset pre-eclampsia.

Material and Methods

A case–control study was carried out involving pregnancies with pre-eclampsia (152 early onset and 297 late onset) and 449 controls at King Chulalongkorn Memorial Hospital, Bangkok, Thailand between 1 January 2005 and 31 December 2010. The data were reviewed from antenatal and delivery records.

Results

Factors which were significantly associated with increased risk for both early and late onset pre-eclampsia were family history of diabetes mellitus, high pre-pregnancy body mass index ≥ 25 kg/m2 and weight gain ≥ 0.5 kg per week. History of chronic hypertension (odds ratio 4.4; 95% confidence interval 2.1–9.3) was significantly associated with increased risk for only early onset pre-eclampsia, while family history of chronic hypertension (odds ratio 18; 95% confidence interval 6–54) was significantly associated with increased risk for only late onset pre-eclampsia.

Conclusions

The risk factors that differ between early and late onset of pre-eclampsia were history of chronic hypertension and family history of chronic hypertension. Family history of diabetes mellitus, pre-pregnancy body mass index ≥ 25 kg/m2 and weight gain ≥ 0.5 kg per week were risk factors of both early and late onset pre-eclampsia. These risk factors are of value to obstetricians in identifying patients at risk for pre-eclampsia and in implementing primary prevention.

Introduction

Pre-eclampsia is a common obstetric complication. It is one of three common causes of maternal mortality in the world.[1] In severe cases, it causes multiple organ failures, which leads to maternal death. A high fetal morbidity and mortality rate is associated with prematurity, placental insufficiency and intrauterine growth restriction (IUGR), which result from this disorder.[2, 3] The exact cause of pre-eclampsia is still unknown. The impaired placentation is one possible cause.[4]

There are many studies that aim to evaluate risk factors of pre-eclampsia. Primigravida, previous pregnancy-induced hypertension, obesity, diabetes, hypertension and multiplicity are risk factors. Some factors are protective; one of these is cigarette smoking.[5] Some studies demonstrated higher morbidity and mortality from pre-eclampsia at an early gestational age than from that at a late stage.[2, 6-8] The early onset of this disorder causes severe morbidity in mothers and a higher preterm birth rate in fetuses.[7, 9]

The aim of this study is to find the difference in risk factors between early onset and late onset pre-eclampsia in the Thai population.

Methods

This was a case–control study conducted at the Department of Obstetrics and Gynecology, King Chulalongkorn Memorial Hospital, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand. The study was approved by the Institutional Review Board of the Faculty of Medicine, Chulalongkorn University.

The antenatal and delivery records of all pregnant women with gestational age of 20 weeks or more and estimate fetal weight of ≥500 g delivered (regardless of live birth or stillbirth) at King Chulalongkorn Memorial Hospital from 1 January 2005 to 31 December 2010 were reviewed. Exclusion criteria included abortion, hydatidiform mole, pregnancies complicated with chromosomal or structural anomalies and birth before arrival.

Data were divided into three groups (two case groups and one control group). Cases were diagnosed as mild pre-eclampsia, severe pre-eclampsia, eclampsia, or superimposed pre-eclampsia. Cases were divided into two subgroups, early onset and late onset. Controls were normotensive pregnant women who delivered consecutively after pre-eclamptic pregnant women.

Data were collected regarding general information, pregnancy information, antenatal care, medical history, and pregnancy outcome.

Mild pre-eclampsia was defined as a blood pressure of at least 140/90 mmHg, measured on two occasions at least 6 h apart, with proteinuria of at least 300 mg/24 h or at least 1+ on urine dipstick test. Both elevated blood pressure and proteinuria occurred for the first time after gestational age of 20 weeks.[10] Severe pre-eclampsia was defined on the basis of pre-eclampsia with one or more of the following: blood pressure of at least 160/110 mmHg, proteinuria of at least 5 g/24 h or at least 3+ on urine dipstick test, serum creatinine >1.2 mg/dL, platelet count <100 000/μL, microangiopathic hemolysis (increased lactate dehydrogenase), elevated serum transaminase level (aspartate aminotransferase or alanine aminotransferase), persistent headache or other cerebral or visual disturbance, persistent epigastric pain, pulmonary edema, or intrauterine growth restriction.[10] Eclampsia was defined as seizures that cannot be attributed to other causes in women with pre-eclampsia.[10] Superimposed pre-eclampsia was defined as a new onset of proteinuria of at least 300 mg/24 h in hypertensive women but no proteinuria prior to 20 weeks' gestation, or a sudden increase in proteinuria or blood pressure in women with hypertension and proteinuria before 20 weeks' gestation.[10] The onset of pre-eclampsia was divided into early and late onset; early onset was gestational age less than 34 weeks, and late onset was gestational age of 34 weeks or more.[7, 9] Gestational age was calculated from the time elapsed since the first day of the last menstrual period, or calculated from first-trimester ultrasonography if the last menstrual period was uncertain.

Sample size calculation was based on the risk factors based on a previous study.[11] Body mass index was the risk factor that gave the largest sample size in the early onset group: 152 women. Multifetal pregnancy was the risk factor that gave the largest sample size in the late onset group: 297 women. The samples in the control group were equal to all women in both case groups: 449 women. These samples were enough to detect a statistical difference (α = 0.05 and β = 0.1).

The following risk factors were evaluated: age, parity, gestational age, multifetal pregnancies, blood pressure at first visit, height, pre-pregnancy weight, body mass index (underweight: body mass index [BMI] < 20 kg/m2; normal: BMI 20–24.9 kg/m2; overweight: BMI 25.0–29.9 kg/m2; obese: BMI ≥ 30 kg/m2), weight gain per week (calculated by bodyweight at last visit minus pregestational weight and divided by gestational week at last visit), medical illness and family history (hypertension, diabetes, and renal disease), drug allergy, medication, previous history of pre-eclampsia, history of gestational hypertension, infant's sex, Apgar scores, maternal and fetal complications.

Statistical analysis

Data were presented as mean ± standard deviation and percentage. anova with post-hoc analysis (Fisher's least-significant difference) and Kruskal–Wallis were used for continuous variables. The χ2-test and Fisher's exact test were used for categorical variables.

Risk factors were compared between each pre-eclampsia group and the controls in univariate analysis. Then, multivariate logistic regression analysis was used to evaluate the association of risk factors with each pre-eclampsia group. The risk factors that were significant on the univariate analysis were entered into a multivariate regression analysis. Adjusted odds ratio (OR) with 95% confidence interval (CI) was calculated. A P-value < 0.05 was considered statistically significant.

Results

There were a total of 449 consecutive cases with pre-eclampsia. They were divided into 152 women in early onset pre-eclampsia and 297 women in late onset pre-eclampsia and 449 controls.

Demographic characteristics are shown in Table 1. Mean maternal age and proportion of multiparity were significantly higher in the early onset pre-eclampsia group than in controls. The pregestational weight and weight gain per week were significantly higher in both the early and late onset pre-eclampsia groups than in controls. The total weight gain was significantly higher in the late onset pre-eclampsia group than in controls.

Table 1. Demographic characteristics of study population
CharacteristicControl (n = 449)Early onset (n = 152)P-valueLate onset (n = 297)P-value
Age (years)28.5 ± 6.631.6 ± 6.4<0.00129.4 ± 6.80.076
Nulliparity206(45.9%)52(34.2%)0.012146(49.2%)0.380
Previous abortion101(22.5%)44(28.9%)0.10864(21.5%)0.760
Previous preterm delivery13(2.9%)00.04600.002
Pregestational bodyweight(kg)54.9 ± 10.957.9 ± 14.00.01259.2 ± 14.0<0.001
Total weight gain(kg)14.0 ± 5.513.7 ± 5.30.616.1 ± 5.9<0.001
Weight gain per week(kg)0.37 ± 0.140.45 ± 0.19<0.0010.44 ± 0.16<0.001

Perinatal characteristics are shown in Table 2. The proportion of preterm deliveries and cesarean sections were significantly higher in both the early and late onset pre-eclampsia groups than in controls. The control group did not represent a normal population in our institution. The preterm birth rate appeared to be high in the controls. The reasons for this may be as follows: (i) our institution is a tertiary care hospital, and thus, there were a high number of complicated cases that needed preterm delivery; and (ii) coincidentally, controls were recruited from normotensive pregnant women who delivered consecutively after pre-eclamptic pregnant women. The proportion of Apgar scores below 7 at 1 and 5 min were significantly higher in the early onset pre-eclampsia group than in controls. Neonatal birthweight in the early onset pre-eclampsia group was significantly less than in controls.

Table 2. Perinatal characteristics
CharacteristicControl (n = 449)Early onset (n = 152)P-valueLate onset (n = 297)P-value
Gestational age at delivery (weeks)37.0 ± 3.730.5 ± 3.3<0.00136.8 ± 2.20.313
Preterm delivery129(28.7%)152(100%)<0.001155(52.2%)<0.001
Birthweight(g)2791.2 ± 782.11472.6 ± 547.3<0.0012690.3 ± 617.30.052
Birthweight < 2500 gram164(36.5%)147(96.7%)<0.00198(33%)0.323
Cesarean delivery78(17.4%)144(94.7%)<0.001147(49.5%)<0.001
Apgar scores at 1 min < 714(3.1%)56(36.8%)<0.00117(5.7%)0.080
Apgar scores at 5 min < 71(0.2%)17(11.2%)<0.0013(1%)0.306

From univariate analysis, maternal age ≥ 35 years, pre-pregnancy BMI 25–29.9 kg/m2, weight gain ≥ 0.5 kg per week, female infant, calcium intake, family history of diabetes mellitus (DM), and family history of hypertension were significantly associated with increased risk of both early and late onset pre-eclampsia. Multiparity, chronic hypertension, pregestational DM or gestational DM, history of pre-eclampsia in previous pregnancy, history of hemolysis, and elevated liver enzyme and low platelet (HELLP) in previous pregnancy were significantly associated with increased risk of early onset pre-eclampsia only. There was no risk factor significantly associated with increased risk of late onset pre-eclampsia only. Gestational age at first antenatal care ≥ 27 weeks and pre-pregnancy BMI < 20 kg/m2 were significantly associated with decreased risk of both early and late onset pre-eclampsia. Gestational age at first antenatal care 14–26 weeks and maternal weight gain < 0.2 kg per week were significantly associated with decreased risk of late onset pre-eclampsia only.

Table 3 shows the results of multivariate logistic regression analysis. Risk factors which were significantly associated with increased risk of both early and late onset pre-eclampsia were family history of DM, pre-pregnancy BMI 25–29.9 kg/m2, pre-pregnancy BMI ≥30 kg/m2 and weight gain ≥ 0.5 kg per week. History of chronic hypertension (OR 4.4; 95% CI 2.1–9.3) was significantly associated with increased risk of early onset pre-eclampsia only. Family history of chronic hypertension (OR 18; 95% CI 6–54) was significantly associated with increased risk of late onset pre-eclampsia only. Pre-pregnancy BMI < 20 kg/m2 was a significant protective factor for both early and late onset pre-eclampsia. Maternal weight gain < 0.2 kg per week was a significant protective factor for early onset pre-eclampsia only.

Table 3. Results of multivariate logistic regression analysis
Risk factorsEarly onsetLate onset
Adjusted OR (95% CI)Adjusted OR (95% CI)
  1. CI,confidence interval; OR,odds ratio.
History of chronic hypertension4.4(2.1,9.3)
Family history of hypertension18(6,54)
Family history of diabetes2.5(1.1,5.6)2.7(1.6,4.4)
Pre-pregnancy body mass index 25–29.9 kg/m23.5(1.3,8.9)2.1(1.2,3.7)
Pre-pregnancy body mass index ≥ 30 kg/m216.2(4.5,58.3)5.8(2.8,11.9)
Pre-pregnancy body mass index < 20 kg/m20.5(0.3,0.8)
Weight gain < 0.2 kg/week0.3(0.1,0.9)
Weight gain ≥ 0.5 kg/week2.1(1.2,3.7)1.9(1.3,2.8)

Discussion

This study shows that risk factors that differ between early and late onset pre-eclampsia were a history of chronic hypertension and family history of chronic hypertension. History of chronic hypertension was significantly associated with increased risk of early onset pre-eclampsia only, while family history of chronic hypertension was significantly associated with increased risk of late onset pre-eclampsia only.

There has been only one study evaluating the risk factors of early and late onset of pre-eclampsia.[12] Fang et al. did not find any difference in risk factors between early and late onset pre-eclampsia.[12] This may be due to the small sample size of their study. There were only 29 cases of early onset and 121 cases of late onset pre-eclampsia. They found that pre-pregnancy body mass index >30 kg/m2 and failure to use prenatal care services were associated with increased risk of pre-eclampsia.[12] The difference between this study and that of Fang et al. may be due to the difference of methodology. This study recruited cases as early and late onset pre-eclampsia at the beginning of the study, while Fang et al. divided cases into early and late onset pre-eclampsia by subgroup analysis.

Poon et al.[13] developed prediction algorithms for hypertensive disorders based on multivariate analysis of factors from the maternal history and compared the estimated performance of such algorithms in the prediction of early pre-eclampsia, late pre-eclampsia and gestational hypertension. There were 37 cases with early pre-eclampsia, 128 with late pre-eclampsia, and 140 with gestational hypertension. They found that predictors of early pre-eclampsia were African race, chronic hypertension, prior pre-eclampsia and use of ovulation drugs. Predictors of late onset pre-eclampsia and gestational hypertension were increased maternal age and BMI, and family history or history of pre-eclampsia. The detection rates of early pre-eclampsia, late pre-eclampsia and gestational hypertension in screening by maternal factors were only 37.0, 28.9 and 20.7%, respectively, for a 5% false positive rate.

Nanjundan et al. evaluated risk factors for early onset severe pre-eclampsia and eclampsia.[14] They found that history of pre-eclampsia or eclampsia in a previous pregnancy, exposure to passive smoking, inadequate antenatal supervision, family history of hypertension in one or more first-degree relatives, living in a joint family, being overweight and lower socioeconomic status were associated with increased risk of early onset pre-eclampsia and eclampsia. The difference in these studies may be due to difference in the study population.

The results of the present study were similar to previous studies.[6, 7, 11] Overweight and obesity increased the risk of pre-eclampsia, which was explained by increase in triglyceride and free fatty acid levels. These lipid alterations can produce major factors leading to endothelial cell dysfunction in pre-eclampsia with increased circulating levels of lipid peroxides oxidative stress. This can lead to endothelial cell damage.[15-17] Maternal weight gain < 0.2 kg per week was a significant protective factor for early onset pre-eclampsia. Pre-pregnancy BMI < 20 kg/m2 was a significant protective factor for late onset pre-eclampsia. This is similar to the previous studies.[11, 18]

History of chronic hypertension was a significant risk factor for early onset pre-eclampsia in the present study. This is in agreement with previous studies that showed that chronic hypertension was a risk factor for pre-eclampsia.[8, 18] Family history of chronic hypertension was a significant risk factor for late onset pre-eclampsia in the present study. This is in agreement with previous studies.[19, 20]

In contrast to previous studies,[2, 6, 8] cigarette smoking and high calcium intake were not protective factors in our study. This may due to the relatively small number of cigarette smokers in the groups and because people in Thailand generally take a sufficient amount of calcium. However, we did not exactly evaluate the calcium intake in their food. We did not identify maternal age as a significant risk factor for early and late onset pre-eclampsia. This is consistent with previous studies.[14, 21]

Chronic hypertension can cause end-organ damage and vascular complications. This may be the reason why chronic hypertension is associated with early onset pre-eclampsia; however, family history of chronic hypertension is associated with late onset pre-eclampsia. This may be explained by a genetic predisposition. Vascular complications still do not occur in these cases.

The strength of the present study was the large number of cases in early and late onset pre-eclampsia. Thus, we could compare and indentify the difference in the risk factors between these groups. The limitation of this study was the small number of smokers and the small number of pregnant women who used calcium medication during pregnancy. Thus we could not assess the effect of these factors.

In conclusion, the risk factors differing between early and late onset pre-eclampsia were history of chronic hypertension and family history of chronic hypertension. Family history of DM, pre-pregnancy BMI ≥ 25 kg/m2 and weight gain ≥ 0.5 kg per week were risk factors of both early and late onset pre-eclampsia. These risk factors are valuable to obstetricians for identifying patients at risk for pre-eclampsia and for implementing primary prevention.

Disclosure

No author has any potential conflict of interest.

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