Objective
Women who develop preeclampsia have a higher risk of future cardiovascular disease and diabetes compared to women who have uncomplicated pregnancies. We hypothesized that women with prior preeclampsia would have increased visceral adiposity that would be a major determinant of their metabolic and cardiovascular risk factors.
Study Design
We compared intraabdominal fat (IAF) area, insulin sensitivity index ( S I ), fasting lipids, low-density lipoprotein relative flotation rate, and brachial artery flow-mediated dilatation in 49 women with prior preeclampsia and 22 controls who were at least 8 months postpartum and matched for age, parity, body mass index, and months postpartum. Women were eligible if they did not smoke tobacco, use hormonal contraception, have chronic hypertension, or have a history of gestational diabetes.
Results
The groups were similar for age (mean ± SD: prior preeclampsia 33.4 ± 6.6 vs control 34.6 ± 4.3 years), parity (median: 1 for both), body mass index (26.7 ± 5.9 vs 24.0 ± 7.3 kg/m 2 ), and months postpartum (median [25th-75th percentile]: 16 [13-38] vs 16.5 [13-25]). There were no significant differences in IAF area and S I . Despite this, women with preeclampsia had lower high-density lipoprotein (46.0 ± 10.7 vs 51.3 ± 9.3 mg/dL; P < .05), smaller/denser low-density lipoprotein relative flotation rate (0.276 ± 0.022 vs 0.289 ± 0.016; P = .02), higher systolic (114.6 ± 10.9 vs 102.3 ± 7.5 mm Hg) and diastolic (67.6 ± 7.5 vs 60.9 ± 3.6 mm Hg; P < .001) blood pressures, and impaired flow-mediated dilatation (4.5 [2-6.7] vs 8.8 [4.5-9.1] percent change, P < .05) compared to controls. In a subgroup analysis, women with nonsevere preeclampsia (n = 17) had increased IAF (98.3 [60.1-122.2]) vs 63.1 [40.1-70.7] cm 2 ; P = .02) and decreased S I (4.18 [2.43-5.25] vs 5.5 [3.9-8.3] × 10 -5 min -1 /pmol/L; P = .035) compared to the controls, whereas women with severe preeclampsia (n = 32) were not different for IAF and S I . IAF was negatively associated with S I and positively associated with cardiovascular risk factors even after adjusting for the matching variables and total body fat.
Conclusion
Women with prior preeclampsia have an atherogenic lipid profile and endothelial dysfunction compared to matched control subjects despite having similar adiposity and insulin sensitivity, suggesting that there are mechanisms separate from obesity and insulin resistance that lead to their cardiovascular risk factors. Visceral adiposity may have a role in contributing to these risk factors in the subgroup of women who have preeclampsia without severe features.
Women who develop preeclampsia are more likely to be obese, be insulin resistant, have an atherogenic lipoprotein phenotype, and have markers of endothelial dysfunction. Although the clinical manifestations of preeclampsia resolve postpartum, women have abnormalities remote from delivery including lower insulin sensitivity, higher blood pressures, an atherogenic lipoprotein phenotype, and endothelial dysfunction. The persistence of these abnormalities suggests that they have an underlying condition, presumably the metabolic syndrome. Indeed, recent studies have shown that the metabolic syndrome is more common in women with a history of preeclampsia and that they have an increased risk of developing complications associated with the metabolic syndrome such as cardiovascular disease and diabetes mellitus.
We and other investigators have demonstrated in other populations that visceral adiposity is a significant determinant of the metabolic syndrome and its features including decreased insulin sensitivity and ß-cell function, impaired glucose tolerance, elevated blood pressure, and dyslipidemia. Visceral fat is metabolically active as a source of free fatty acids and adipokines, such as adiponectin, tumor necrosis factor (TNF)-α, and plasminogen activator inhibitor (PAI)-1 ; many of these factors have been shown to be elevated in women with preeclampsia, but the studies that measured these factors in women with preeclampsia did not quantify visceral adiposity. Our group was specifically interested in evaluating the role that visceral adiposity and insulin resistance play in contributing to cardiovascular risk factors in women with a history of preeclampsia. We hypothesized that visceral adiposity would be a major determinant of their metabolic and cardiovascular risk factors.
Materials and Methods
Study design
This was a cross-sectional study comparing body fat distribution, insulin sensitivity, β-cell function, fasting lipids, hepatic lipase activity, and endothelial function between postpartum women who had either an uncomplicated pregnancy (control group) or a history of preeclampsia (prior preeclampsia group). The study was approved by the University of Washington Institutional Review Board prior to initiation. All subjects provided written informed consent to participate.
Subjects
Subjects were recruited by advertisement in the greater Seattle area and underwent a screening visit that included a history and physical examination with a fasting blood draw. Women were eligible if they were at least 8 months postpartum and premenopausal. They were excluded if they smoked tobacco, used hormonal contraception or medications that would impact glucose metabolism or lipids/lipoproteins, were pregnant, or had a fasting plasma glucose ≥110 mg/dL, an abnormal complete blood cell count, liver transaminases ≥1.5 × normal, a serum creatinine ≥1.4 mg/dL, a history of chronic hypertension, diabetes, renal disease, autoimmune disease, fetal anomalies or aneuploidy, or multifetal gestation. All women underwent screening for gestational diabetes as a part of standard practice in our region and had normal results on either the 1-hour oral glucose challenge test or 3-hour oral glucose tolerance test. Women diagnosed with gestational diabetes in any pregnancy were excluded.
Women in the prior preeclampsia group had medical record documentation of the following criteria for preeclampsia: systolic blood pressure ≥140 mm Hg or diastolic blood pressure ≥90 mm Hg on 2 occasions 6 hours apart and persistent 1+ proteinuria (between 30-100 mg/dL) on random urine samples or total protein ≥300 mg/24-hour urine collection. Women in the prior preeclampsia group were further characterized by whether they had features of severe preeclampsia: elevated transaminases, thrombocytopenia, severe blood pressure elevation (systolic ≥160 mm Hg or diastolic blood pressure ≥110 mm Hg), renal insufficiency, and neurological symptoms. Women in the control group delivered their babies at ≥39 weeks’ gestation and had normal blood pressures documented throughout their prenatal course, labor and delivery, and postpartum. The 2 groups were matched for age (within 5 years), body mass index (BMI) (within 2.5 kg/m 2 ), time since delivery (within 4 weeks), and parity (within 1 delivery).
Measurements
Study procedures were performed on 2 consecutive days during the subjects’ follicular phase of the menstrual cycle at the University of Washington General Clinical Research Center. Study participants were instructed to avoid exercise or strenuous activity 24 hours prior to the visit. Dietary assessments were not performed.
Anthropometrics and body fat distribution and composition
BMI (kg/m 2 ) was calculated from the average of 3 weight and height measurements. Waist circumference was measured in the standing position at the level midway between the lateral lower rib margin and the iliac crest. To determine total and regional body fat and lean content, dual-energy x-ray absorptiometry (DEXA) was performed on the general clinical research center. A computed tomography (CT) scan was performed in the department of radiology to quantify intraabdominal fat (IAF) and subcutaneous fat (SCF) areas. A single observer who was blinded to group assignment made the DEXA and CT measurements. The coefficient of variation (CV) for the DEXA scan measurement of total fat mass is 1.67% (personal communication with Danielle Yancey, Bachelor of Science in Exercise Science, Research Scientist and Exercise Physiologist in the Nutrition Research and Body Composition Core at the University of Washington Medical Center, March 4, 2014). The CV for the SCF and visceral fat areas for the same scan on 10 separate days is 1.5%.
Frequently sampled intravenous glucose tolerance test
Following a 12-hour overnight fast, an insulin-modified frequently sampled intravenous glucose tolerance test (FSIGT) was performed to quantify the insulin sensitivity index ( S I ) using minimal model of glucose kinetics of Bergman et al. The acute insulin response to glucose was quantified as the incremental insulin response above baseline from 2-10 minutes following glucose administration. ß-cell function (the disposition index) was calculated by adjusting the acute insulin response to glucose for the prevailing S I .
Assays
All chemical analyses were performed on blood samples obtained after a 12-hour overnight fast and stored at –70°C. Plasma glucose levels were determined in duplicate using a glucose oxidase method (Beckman, Palo Alto, CA). Plasma immunoreactive insulin levels were measured in duplicate using a modification of the double antibody radioimmunoassay technique. Total, low-density lipoprotein (LDL), and high-density lipoprotein (HDL) cholesterol and triglyceride levels were determined by standardized methodologies at the Northwest Lipid Research Laboratories. LDL relative flotation rate (Rf), which characterizes LDL peak buoyancy, was determined by density gradient ultracentrifugation. Hepatic lipase activity, which leads to more atherogenic, smaller, denser LDL, was measured in plasma after heparin bolus.
Endothelial- and endothelial-independent vasodilation
Longitudinal images of the brachial artery were digitized from the video output of a standard clinical ultrasound scanner (HDI 3000 or HDI 5000; Philips Medical Systems, Bothell, WA) using a frame grabber on a personal computer under control of custom image capture software. A linear 5- to 12-MHz scanhead or a compact linear 5- to 10-MHz scanhead was used for the ultrasound imaging. Image acquisition was gated with an ECG signal so that all images were captured at end diastole and collected for every cardiac cycle. The baseline brachial artery diameter was measured over 1 minute after the subject had been at rest for 10 minutes. Reactive hyperemia was produced using a pneumatic tourniquet placed around the upper arm and inflated to 40 mm Hg greater than the subject’s systolic pressure for 4 minutes. The maximum diameter was obtained during a 2-minute interval following cuff release. Endothelial-dependent vasodilation (flow-mediated dilatation [FMD]) was calculated as the maximum diameter expressed as a percentage of the baseline measurement. Sublingual nitroglycerin 0.4 mg was given 15 minutes after cuff deflation. Images were collected between 2-10 minutes to obtain the maximum diameter. Endothelial-independent vasodilation (nitroglycerine-mediated dilatation) was calculated as the maximum diameter expressed as a percentage of the baseline diameter.
Sample size calculation
Sample sizes were calculated for S I based on published data for postpartum women who had preeclampsia (8.5 ± 2.3 × 10 −5 min −1 pmol/L −1 ) compared to controls (11.4 ± 4.3 × 10 −5 min −1 pmol/L −1 ). To detect a difference in S I , 38 women in the preeclampsia group and 19 in the control group were needed for 90% power at a .05 significance level.
Statistical analyses
Continuous variables are presented as mean ± SD or median with the 25th and 75th percentiles if not normally distributed. Categorical variables are presented as absolute number and percentages and compared using χ 2 or Fisher exact test. Linear regression analyses were used to assess the relationships between the independent variables and the continuous, dependent variables of interest. Group assignment was included as an indicator variable. In these models, we assessed whether the differences between the groups were independent of BMI and measures of adiposity. We also adjusted for potential confounding variables and the matching variables. Logarithmic transformation was performed as necessary to satisfy the statistical assumptions of linear regression. We performed a subgroup analysis after categorizing women with preeclampsia into 2 groups based on the presence or absence of severe features. In these models, group was entered as a factor variable to allow comparisons between the control and each preeclampsia group. All statistical analyses were 2-sided. Statistical significance was considered for P < .05. Statistical analyses were performed using STATA 13.0 for Windows (STATA Corp, College Station, TX).
Results
There were no differences between the groups in the matching variables, frequencies of exercise, or first-degree relatives with type 2 diabetes mellitus, obesity, hypertension, and cardiovascular disease ( Table 1 ). The majority (65.3%) of the women in the prior preeclampsia group had severe features; 46.9% delivered <36 weeks’ gestation.
| Characteristic | Prior preeclampsia (n = 49) | Controls (n = 22) | P value |
|---|---|---|---|
| Age, y | 33.4 ± 6.6 | 34.6 ± 4.3 | .4 |
| Primiparous, n (%) | 29 (59.2) | 11 (50.0) | .7 |
| BMI, kg/m 2 | 26.7 ± 5.9 | 24.0 ± 7.3 | .1 |
| Months postpartum | 16 [13–38] | 16.5 [13–25] | .8 |
| Race, n (%) | |||
| Caucasian | 35 (71.4) | 15 (68.2) | .9 |
| Other | 8 (16.3) | 3 (13.6) | |
| Unknown | 6 (12.2) | 4 (18.2) | |
| Exercise, n (%) | 28 (57.1) | 16 (72.7) | .5 |
| Family history, n (%) | |||
| Type 2 diabetes mellitus | 13 (26.5) | 6 (27.3) | .9 |
| Obesity | 19 (38.8) | 7 (31.8) | .4 |
| Hypertension | 25 (51.0) | 10 (45.5) | .5 |
| Preeclampsia | 7 (14.3) | 1 (4.5) | .2 |
| Coronary artery disease | 2 (4.1) | 1 (4.5) | 1.0 |
| Cerebrovascular disease | 9 (18.4) | 2 (9.1) | .3 |
In contrast to our hypothesis, women with prior preeclampsia did not have greater adiposity as compared to the controls ( Table 2 ). In linear regression models containing the matching variables, only BMI was significantly associated with waist circumference (coefficient 0.0084 ± 0.0009; P < .001), percent body fat (coefficient 0.9508 ± 0.1343; P < .001), IAF area (coefficient 0.0245 ± 0.0032; P < .001), and SCF area (coefficient 0.0296 ± 0.0037; P < .001). Consistent with the women having similar body fat distributions, we found no significant differences in S I ( Table 2 ). When total body fat, IAF area, and SCF area were added to the model, IAF area was an independent predictor of S I (coefficient –0.000042 ± 0.000013; P = .002), whereas SCF area, total body fat, and BMI were not.
| Demographic | Prior preeclampsia (n = 49) | Controls (n = 22) | P value |
|---|---|---|---|
| Total body fat, g | 26,411.1 ± 11,874.8 | 28,315.9 ± 12,715.7 | .6 |
| Percent total fat | 38.0 ± 9.5 | 37.3 ± 9.3 | .8 |
| Trunk/total body fat | 50 ± 6.4 | 50 ± 4.5 | .8 |
| Percent total lean | 60.1 [56.7–68.8] | 63.6 [53.8–69.2] | 1.0 |
| Waist circumference, cm | 84.7 ± 15 | 81.0 ± 11.2 | .3 |
| IAF area, cm 2 | 60.1 [39.6–90.9] | 63.1 [40.1–70.7] | .7 |
| SCF area, cm 2 | 282.9 [172.7–426.1] | 226.9 [177.3–425.6] | .5 |
| IAF/SCF | 0.228 [0.211–0.274] | 0.247 [0.166–0.302] | .9 |
| Fasting glucose, mg/dL | 87.3 [84.7–92.6] | 88.6 [84.8–92.2] | .7 |
| S I , ×10 −5 min −1 /pmol/L | 4.4 [3.2–6.8] | 5.5 [3.9–8.3] | .1 |
| AIRg, pmol/L | 358.6 [242.2–474.8] | 340.5 [219.4–528.2] | 1.0 |
| DI, min −1 | 0.0159 [0.0094–0.0211] | 0.0195 [0.0121–0.0292] | .2 |
Women with prior preeclampsia had higher blood pressures than controls ( Table 3 ) even after adjusting for exercise and family history ( P < .001 and P = .001, respectively). In models containing the matching variables, prior preeclampsia (coefficient 10.5 ± 2.5; P < .001) and BMI (coefficient 0.534 ± 0.180; P = .004) were the significant predictors of systolic blood pressure. When total body fat, IAF area, and SCF area were added to the model, only prior preeclampsia (coefficient 10.5 ± 2.5; P < .001) independently predicted systolic blood pressure. Prior preeclampsia was the only predictor of diastolic blood pressure (coefficient 6.02 ± 1.71; P = .001). Women with prior preeclampsia also had less FMD compared to controls ( Table 3 ). The association remained significant (coefficient –0.212 ± 0.102; P = .04) after adjusting for the matching variables. There were no significant associations between these variables, total body fat, IAF and SCF area, and FMD.
| Characteristic | Prior preeclampsia (n = 49) | Controls (n = 22) | P value |
|---|---|---|---|
| Systolic BP, mm Hg | 114.6 ± 10.9 | 102.3 ± 7.5 | < .001 |
| Diastolic BP, mm Hg | 67.6 ± 7.5 | 60.9 ± 3.6 | < .001 |
| FMD (% change) | 4.5 [2–6.7] | 8.8 [4.5–9.1] | < .05 |
| NMD (% change) | 19.4 [16.4–23] | 22.5 [16.8–26.3] | .2 |
| Total cholesterol, mg/dL | 166.0 ± 30.0 | 169.6 ± 41.4 | .7 |
| HDL cholesterol, mg/dL | 46.0 ± 10.7 | 51.3 ± 9.3 | < .05 |
| Triglycerides, mg/dL | 69 [52–100] | 55 [45–80] | .2 |
| LDL cholesterol, mg/dL | 104 [84–123] | 103 [83–114] | .6 |
| LDL peak buoyancy (Rf) | 0.276 ± 0.022 | 0.289 ± 0.016 | .02 |
| Hepatic lipase activity, nmol/mL/min | 308 [224–393] | 243 [217–286] | .04 |
Women with prior preeclampsia had a more atherogenic lipoprotein phenotype as compared to controls ( Table 3 ). In the multivariate regression model, IAF area (coefficient –0.0013 ± 0.0005; P = .016) independently predicted HDL levels, but BMI, total body fat, SCF area, and prior preeclampsia did not. Women with prior preeclampsia had increased hepatic lipase activity and lower LDL Rf compared to controls. In the multivariate regression models, IAF area (coefficient –0.0000419 ± 0.0000106; P < .001) significantly predicted smaller, denser LDL; whereas prior preeclampsia (coefficient –0.0098 ± 0.005; P = .055) and the matching variables, total body fat, and SCF area did not.
In our subgroup analysis, women with nonsevere preeclampsia were more obese and had a central fat distribution; elevated triglycerides; smaller, denser LDL; and lower HDL levels compared to women with severe preeclampsia and controls ( Table 4 ). Women with nonsevere preeclampsia also had significantly lower S I , higher blood pressures, and elevated hepatic lipase activity compared to controls. In contrast, women with severe preeclampsia were not significantly different from controls with the exception of having higher blood pressures. After adjusting for BMI, the differences between the groups were no longer statistically significant for S I , IAF and SCF areas, triglycerides, and hepatic lipase. However, systolic (coefficient 12.4 ± 3.3; P < .001) and diastolic (coefficient 6.0 ± 2.2; P = .008) blood pressures, HDL levels (coefficient –0.0730 ± 0.0298; P = .02), and LDL Rf (coefficient –0.0191 ± 0.0067; P = .005) remained significantly different between the groups. In multivariate regression models, IAF area significantly predicted S I (coefficient –0.000042 ± 0.000014; P = .003), HDL levels (coefficient –0.0012 ± 0.0005; P = .036), and LDL Rf (coefficient –0.0000346 ± 0.0000109; P = .001), whereas BMI, total body fat, and SCF area did not.
| Characteristic | Nonsevere preeclampsia (n = 17) | Severe preeclampsia (n = 32) | Controls (n = 22) | P value Nonsevere vs severe Control vs nonsevere Control vs severe |
|---|---|---|---|---|
| Age, y | 35.0 ± 7.5 | 32.5 ± 5.9 | 34.6 ± 4.3 | .2 |
| .7 | ||||
| .3 | ||||
| BMI, kg/m 2 | 29.6 [24.4–32.4] | 24.7 [20.9–27.5] | 24.0 ± 7.3 | .01 |
| .007 | ||||
| .4 | ||||
| Primiparous, n (%) | 11 (64.7) | 18 (56.3) | 11 (50.0) | .5 |
| .2 | ||||
| .8 | ||||
| Months postpartum | 15 [11–35] | 17.5 [13–39] | 16.5 [13–25] | .8 |
| .4 | ||||
| 1.0 | ||||
| Waist circumference, cm | 91.5 ± 16.2 | 81.1 ± 2.3 | 81.0 ± 11.2 | .02 |
| .02 | ||||
| .9 | ||||
| Total body fat, g | 33,632.8 ± 11,990.4 | 25,491.3 ± 12,345.6 | 26,140.7 ± 12,098.5 | .02 |
| .07 | ||||
| .8 | ||||
| Percent total fat | 40.7 ± 8.9 | 36.6 ± 9.7 | 37.3 ± 9.3 | .1 |
| .2 | ||||
| .9 | ||||
| IAF, cm 2 | 98.3 [60.1–122.2] | 56.4 [38.6–75.1] | 63.1 [40.1–70.7] | .004 |
| .02 | ||||
| .7 | ||||
| SCF, cm 2 | 389.2 [263.0–572.5] | 243.8 [148.2–367.9] | 226.9 [177.3–425.6] | .02 |
| .07 | ||||
| .8 | ||||
| S I , ×10 −5 min −1 /pmol/L | 4.18 [2.43–5.25] | 4.71 [3.59–7.28] | 5.5 [3.9–8.3] | .1 |
| .04 | ||||
| .5 | ||||
| DI, min −1 | 0.0153 [0.0072–0.0183] | 0.0169 [0.0099–0.0223] | 0.0195 [0.0121–0.0292] | .2 |
| .1 | ||||
| .5 | ||||
| Systolic BP, mm Hg | 117.7 ± 11.7 | 112.9 ± 10.3 | 102.3 ± 7.5 | .2 |
| < .001 | ||||
| < .001 | ||||
| Diastolic BP, mm Hg | 68.5 ± 7.5 | 67.0 ± 7.5 | 60.9 ± 3.6 | .5 |
| .001 | ||||
| .002 | ||||
| FMD (% change) | 4.5 [2.9–6.3] | 5.0 [1.6–7.2] | 8.8 [4.5–9.1] | .7 |
| .08 | ||||
| .1 | ||||
| Total cholesterol, mg/dL | 167.3 ± 33.5 | 165.3 ± 28.6 | 169.6 ± 41.4 | .7 |
| .8 | ||||
| .6 | ||||
| HDL cholesterol, mg/dL | 40.8 ± 7.5 | 48.7 ± 11.2 | 51.3 ± 9.3 | .01 |
| .001 | ||||
| .3 | ||||
| Triglycerides, mg/dL | 101 [69–134] | 63.5 [50.5–82.5] | 55 [45–80] | .02 |
| .02 | ||||
| .8 | ||||
| LDL cholesterol, mg/dL | 106 [91–123] | 98 [81–121.5] | 103 [83–114] | .5 |
| .5 | ||||
| .8 | ||||
| LDL peak buoyancy (Rf) | 0.266 ± 0.022 | 0.281 ± 0.021 | 0.289 ± 0.016 | .01 |
| .001 | ||||
| .2 | ||||
| Hepatic lipase activity, nmol/mL/min | 319 [237–444] | 286 [215.5–387.5] | 243 [217–286] | .3 |
| .045 | ||||
| .3 |
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