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Insulin Resistance Syndrome in Women with Prior History of Gestational Diabetes Mellitus

Department of Community Health (A.V.), Brown Medical School, Providence, Rhode Island 02912; Department of Pediatrics (C.M.B.), Division of Endocrinology and Metabolism, Rhode Island Hospital, Brown Medical School, Providence, Rhode Island 02903; and Department of Pediatrics (R.T., B.R.V.), Women and Infants’ Hospital, Brown Medical School, Providence, Rhode Island 02905

Address all correspondence and requests for reprints to: Betty R. Vohr, M.D., Women and Infants’ Hospital, 101 Dudley Street, Providence, Rhode Island 02905. E-mail: . bvohr{at}wihri.org

Abstract

The purpose of this study was to determine the prevalence of insulin resistance syndrome (IRS) and the risk factors for developing IRS among women with a history of gestational diabetes mellitus (GDM), compared with controls over 11 postdelivery years. Assessments of 106 women with a prior history of GDM and 101 controls were done on six occasions from 4–11 yr after delivery. Tests included glucose, insulin, lipids, blood pressure, and body measurements. The risk of IRS was analyzed by Cox regression. The results were that 27.2% of GDM and 8.2% of controls developed IRS by 11 yr after delivery. The hazard of developing IRS was 5.6 times (95% confidence interval = 2.6–12.3) among women with prepregnant obesity (body mass index >27.3 kg/m²), compared with women without prepregnant obesity and 4.4 times (95% confidence interval = 1.7–11.1) in women with a history of GDM, compared with controls. At 11 yr after delivery, the cumulative hazard for developing IRS in the next 2 yr was 26 times higher among GDM with prepregnant obesity, compared with controls without prepregnant obesity. We concluded that obesity and GDM in a prior pregnancy are significant risk factors for developing IRS over time. Early detection of markers of IRS is vital for possible prevention of type 2 diabetes and cardiovascular adverse events in women.

B INSULIN RESISTANCE syndrome (IRS), also termed syndrome X, is a distinctive constellation of risk factors for developing type 2 diabetes mellitus (DM) and cardiovascular disease (CVD) in later life. The syndrome’s hallmarks (1, 2, 3, 4) are glucose intolerance; hyperinsulinemia; a characteristic dyslipidemia; obesity, in particular with central fat distribution; and hypertension. Other features include increased prothrombic and antifibrinolytic factors. The risk factors comprising the diagnosis of IRS do not occur in isolation; instead, they interact synergistically to produce adverse cardiovascular and metabolic outcomes or early death (5, 6, 7, 8). Rigorous biochemical criteria for the diagnosis of IRS have not yet been adopted, primarily because no single standardized laboratory test indicates IRS or the severity thereof. Not surprisingly, there are racial, ethnic, gender, and age differences in the prevalence of IRS, just as there are in the prevalence of obesity, DM, and CVD (9, 10, 11). Increasing age is known to increase the risk of IRS (4).

The clinical definition of insulin resistance is the impaired ability of insulin (either endogenous or exogenous) to lower blood glucose levels. Insulin resistance results from defects in insulin responsiveness in muscle, fat, and liver. In the chain of complex genetic and environmental influences, insulin resistance is suspected to be an early metabolic abnormality that precedes the development of hyperinsulinemia, hyperglycemia, hyperlipidemia, overt type 2 diabetes, and coronary heart disease (7, 12, 13, 14, 15). There is evidence from metabolic studies in women with previous gestational DM (GDM) that insulin resistance precedes the development of an abnormal glucose profile by several months to years after delivery (16, 17). As early as 1984, O’Sullivan (18) had found that women with previous GDM were at greater risk for hypertension, hyperlipidemia, electrocardiographic abnormalities, and mortality. In 1996 Meyers-Seifer and Vohr (19) investigated lipid levels in women with previous GDM at 5–6 yr post partum. Their study demonstrated that mean total cholesterol (TC), triglycerides (TGs), low-density lipoprotein (LDL), glucose, and systolic blood pressure (BP) were significantly higher among the GDM women, compared with normoglycemic controls. Given the evidence from various epidemiological and metabolic studies for common etiologies and risk factors for both DM and CVD, GDM in a prior pregnancy may be considered a possible marker or risk factor for IRS in later life.

There is a lack of data, especially from longitudinal investigations, for identifying characteristics of women who are at risk for IRS. To our knowledge, no studies have been performed to determine the prevalence of IRS among women with a history of GDM. In view of the serious metabolic and clinical implications of IRS, the purpose of our study was to determine the risk of developing IRS over time for women with a history of GDM, compared with controls. Our hypothesis was that women with a history of GDM and prepregnant obesity (PPO), defined as body mass index (BMI) 27.3 kg/m² or more, would be at increased risk of IRS.

Design and Methods

Study sample

All pregnant women attending Women and Infants’ Hospital were screened for GDM under a universal screening program, Diabetes in Pregnancy, instituted in 1982. Under this program, women were screened at 24–28 wk of gestation, and a diagnosis of GDM was made based on a screen test of a 1-h serum glucose greater than 7.1 mmol/liter after a 50-g oral glucose load, followed by two abnormal values in a 100-g oral glucose tolerance test. Women with documented GDM who fulfilled the Carpenter and Coustan (20) modification of the National Diabetes Data Group criteria were asked to participate. Women who had a 1-h 50-g screening blood glucose less than 7.1 mmol/liter were enrolled as controls. A detailed description of this study population and recruitment strategy has been reported (21). The Institutional Review Board of Women and Infants’ Hospital of Rhode Island approved the study. Informed consent was obtained from women 4 yr after delivery.

For the longitudinal follow-up study, a project research nurse contacted women with GDM and controls, matched for large-for-gestational-age (LGA) and appropriate-for-gestational-age offspring, at 4 yr after the delivery of a full-term healthy infant. A total of 106 women with GDM and 101 control women consented to participate. Recruitment for the follow-up study was completed in May 1995.

Measurements and techniques

Assessments were performed at 4, 5, 6, 7, 9, and 11 yr after delivery. Information on history of smoking, family history of adverse CVD and DM in the first-degree relatives and socioeconomic status (SES) of the family was obtained. The biochemical testing included plasma glucose and insulin (postprandial levels at 4, 5, 6, and 7 yr). However, at 9 and 11 yr, levels were fasting. At the 6-, 7-, 9-, and 11-yr visit, TC, TG, LDL, and high-density lipoprotein (HDL) levels were tested. Blood glucose was measured using a glucose analyzer (Yellow Springs Instruments, Yellow Springs, OH) by the glucose oxidase method. For the first four visits, women fasted overnight and were given a mixed carbohydrate breakfast containing 50–56.5 g carbohydrate, 4.4–9.9 g protein, and 8.1–13.2 g fat (kcal range 326–346) between 0730 and 0800 h. Blood was drawn 2 h postprandially. For the 9- and 11-yr visits, women fasted overnight and had blood drawn at 0800–0830 h. Serum insulin levels were determined by a double-antibody RIA, which used a recombinant human insulin standard and I¹²⁵ monoiodinated insulin (Diagnostic Products, Los Angeles, CA). The coefficient of variation was 8.1%. TC was measured by hydrolyzing all cholesterol esters to cholesterol, which was then measured spectrophotometrically at 500 nm after couple enzyme reactions catalyzed by cholesterol oxidase and peroxidase (Sigma, St. Louis, MO). The coefficient of variation was 1.3%. TGs were determined using enzymatic hydrolysis to FFAs and glycerol (Sigma). The coefficient of variation was 1.3%. To measure HDL cholesterol, very low density lipoproteins and LDL were separated from HDL by selective precipitation using phototungstic acid and magnesium chloride. The cholesterol concentration in the HDL fraction was then assayed by the enzymatic method described above for cholesterol. The coefficient of variation was 2.8%.

Biometric and anthropometric testing included measurements of BP, height, weight, waist and hip circumference, and four sc skinfold measurements including triceps, subscapular, abdominal, and suprailiac. Height was measured with a permanently affixed stadiometer. All four skinfolds were measured with a Lange skinfold caliper (Cambridge Scientific Industries, Inc., Cambridge, MD) according to standard techniques. Women wore only undergarments for the measurements of waist and hip circumferences. Waist circumference was taken horizontally at the level of the narrowest part of the torso in the standing position. Hip circumference was taken horizontally at the maximum extension of the buttocks. Two measures were obtained for each assessment and averaged. A DINAMAPP vital signs monitor was used to accurately, noninvasively, and automatically measure systolic and diastolic BP. The mean of at least two measurements taken under relaxed conditions was used. The DINAMAPP was recalibrated for accuracy on a weekly basis. The BMI (kilograms per square meter), the sum of four skinfolds (triceps, subscapular, abdominal, and suprailiac), and the waist/hip ratio were computed at each follow-up visit.

Diagnosis of IRS

The diagnosis of IRS in our population was made using the criteria recommended by the Expert Panel on Detection, Evaluation and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel) (22), published in 2001 (Table 1). By their definition, a minimum of two of four listed criteria should be fulfilled to make a diagnosis of IRS.

To determine statistical power for detecting a difference in the hazard ratio (HR) between the GDM and control groups for developing IRS over 11 yr after delivery, we performed a post hoc power analysis using the Power and Precision software program (23). The log-rank survival power test technique was employed. Because lipids were first tested at the 6-yr postdelivery visit, that visit was treated as the baseline with follow-up visits at 7, 9, and 11 yr after delivery for the survival power test calculations. We assumed a minimum HR of 2 for developing IRS in the GDM group, compared with the control group. Furthermore, considering an attrition of 30% by the 11-yr postdelivery visit, the power (1-ß) to detect a significant HR of 2, 2.5, and 3 between the two groups with two-sided = 0.05 was 56.8%, 75.2%, and 95.3%, respectively.

SAS (version 6.12, SAS Institute, Cary, NC) and SPSS for windows (version 10.0, SPSS, Inc., Chicago, IL) statistical packages were used for analysis and plotting of graphs. Univariate analyses were performed using the independent sample t tests, ² analyses for proportions, and Fisher exact test. Multivariate analysis included the repeated-measures ANOVA and the semiparametric analysis, Cox regression for computing the hazard ratios. The purpose of the repeated-measures analysis was to determine differences between the GDM and control groups for biochemical and biometric parameters and to perform within-subject tests of trend over time.

Cox regression analysis (24) was performed to determine the risk of developing IRS from 6–11 postdelivery years in women who had GDM in a prior pregnancy, compared with non-GDM controls. In this analysis, we adjusted for the effects of prepregnancy BMI, women’s SES, and history of smoking (yes/no). The 6-yr postdelivery visit was considered as the baseline visit because lipids were first tested at this visit. Data were available for 166 women at the 6-yr postdelivery visit; 13 participants subsequently missed two or more consecutive follow-up visits. Therefore, they were excluded from this analysis. In the remaining data set of 153 women, including 79 GDM and 74 controls, 14 women (5 GDM and 9 control) had either a biochemical or biometric value missing, at random. We imputed those values by averaging two available sequential values, i.e. one before and one after the missing value in the data set. For example, the BP readings from 6- and 9-yr postdelivery visits were averaged to obtain the 7-yr postdelivery BP reading when missing. We also performed stratified Cox regression analysis for the obese and nonobese groups and for the GDM and control groups. The cumulative hazard (risk rate) for developing IRS at each follow-up visit from the 6- to 11-yr postdelivery visit was also computed. Cumulative hazard may be defined as the risk of occurrence of an event (i.e. IRS) at any follow-up visit. For example, if the HR for developing IRS at the 9-yr follow-up visit for a woman was computed as 0.3, then she would be expected to develop IRS 0.3 times in the next 2 yr. The reciprocal of the HR is the expected length of time until IRS could develop; that means the expected length of time before IRS develops = 1/0.3 x 2 (2-yr units) = 6.6 yr, given the risk of 0.3 at 9 postdelivery yr.

Obesity was defined as prepregnancy BMI greater than 27.3 kg/m². The Hollingshead 4 Factor Index consisting of maternal and paternal education and occupation was used to determine SES (25). The Hollingshead Index ranged from 17–66 in our population, in which an index of 17 corresponds to low SES and 66 to high SES. Data on current or past smoking were obtained at the 9- and 11-yr visits. Women who provided a history of being current or past smokers were categorized as smokers and all others as nonsmokers.

Results

Baseline characteristics of the 207 women at the time of the index delivery, stratified by GDM vs. control status, are shown in Table 2. The GDM and control groups were comparable for women’s age at delivery, prepregnant BMI, SES, parity, weight gain during pregnancy, race/ethnicity, and family history of DM or CVD. Anthropometrics for the two study groups, from 4–11 yr after delivery, are shown in Table 3. The waist-hip ratio was significantly greater for GDM than controls at 5, 6, 7, and 9 yr after delivery. The sum of four skinfolds was significantly greater than that of the controls at 4, 5, and 6 yr after delivery. Repeated-measures analysis showed significant linear trend effects for BMI (P < 0.0001) and waist-hip ratio (P < 0.0001), significant quadratic trend effects for the sum of four skinfolds (P < 0.04) and significant between-group effects for the waist-hip ratio (P < 0.02) and the sum of four skinfolds (P < 0.03). Table 4 shows the mean values for systolic and diastolic BP and the number and percent of values above threshold at 4 to 11 yr. Systolic BP was significantly higher for the GDM group at 5, 6, 7, and 11 yr after delivery. However, repeated-measures analyses revealed a nonsignificant group effect at P = 0.06 for systolic BP.

In Cox regression, our aim was to determine the independent hazard (risk) attributed to GDM status, PPO, SES, and smoking history for developing IRS over 11 postdelivery yr. As shown in Table 7, women with PPO had a 5.6-fold increased risk, compared with women without PPO [95% confidence interval (CI) = 2.6–12.3; P < 0.001], and women with a prior history of GDM had a 4.4-fold increased risk, compared with controls (95% CI = 1.7–11.1; P = 0.002), for developing IRS over 11 postdelivery yr. Our analysis did not indicate any significant influence of women’s SES or smoking status on developing IRS.

View larger version (19K): [in this window] [in a new window]   Figure 1. A, Hazard function for IRS by prepregnant obesity status. The hatched line represents prepregnant BMI of 27 kg/m2 or more; the solid line represents prepregnant BMI of less than 27 kg/m2. B, Hazard function for IRS by study groups: GDM vs. control. The hatched line represents the GDM group; the solid line represents the control group.

View larger version (15K): [in this window] [in a new window]   Figure 2. A, Hazard function for IRS by prepregnant obesity status in the GDM group. The hatched line represents prepregnant BMI of 27 kg/m2 or more; the solid line represents prepregnant BMI of less than 27 kg/m2. B, Hazard function for IRS by prepregnant obesity status in the control group. The hatched line represents prepregnant BMI of 27 kg/m2 or more; the solid line represents prepregnant BMI of less than 27 kg/m2.

The present study assessed the impact of risk factors including PPO, a history of GDM, smoking, and SES on the development of IRS in a longitudinal cohort of women.

By 11 yr after delivery, the obesity (BMI >27.3 kg/m²) rates in both women with GDM and control women were high, 40% and 37%, respectively. Central obesity with a waist-hip ratio of 0.85 or more, however, was higher at each time point for women with GDM than controls and reached statistical significance at 5, 7, and 9 postdelivery yr, and repeated-measures analysis confirmed significant group effects. Prior studies (3, 26) have shown that an increased waist/hip ratio is associated with increased BP and TG levels and lower HDL cholesterol levels in nondiabetics. Waist/hip ratio of 0.85 or more is also one of the four categories of criteria identified to make a diagnosis of IRS (22).

Elevated BP is another well-established risk factor for both coronary artery disease and IRS (1, 27). One study has reported that half of all people with hypertension have IRS (27). In our study, the women with GDM had higher systolic BP than controls at 5, 6, 7, and 11 yr after delivery and a higher rate of elevated measurements (130 mm Hg) at 4, 6, and 11 yr. At 11 yr after delivery, the 30% rate of systolic hypertension for women with GDM was more than twice the 14% rate for controls.

Glucose and insulin are standard measurements for assessment of glucose intolerance and whole-body insulin. The glucose levels were consistently and significantly higher for women with GDM compared with controls at each study visit, from 4–11 yr after delivery. By 11 postdelivery yr, 22% of women with GDM were glucose intolerant, compared with 10% of controls. In addition, women with GDM were more likely to have a fasting value of 7.0 mmol/liter or more at 9 yr and 11 yr after delivery. This confirms that the GDM group is not only at an increased risk of IRS but also of one of its major sequelae, type 2 diabetes.

Although repeated-measures analyses revealed postprandial insulin levels were higher for women with GDM than controls and fasting values trended higher for women with GDM than controls at 9 and 11 yr, no significant differences in the fasting values were identified. Insulin resistance (IR) has previously been demonstrated in former gestational diabetic mothers months to 4 yr after delivery (28, 29, 30, 31). In individuals having IR, fasting and postprandial insulin concentrations may be elevated, even though plasma glucose levels appear normal or only slightly increased. Hyperinsulinemia represents a compensatory mechanism to maintain normoglycemia in the face of IR and may serve as a passive marker for IR (32). There are many methods of measuring whole-body IR, of which hyperinsulinemic euglycemic clamp is considered the gold standard (33). Previous studies report that among normoglycemic subjects, both fasting and postprandial insulin levels correlate highly with the gold standard values for IR (-0.5 to -0.74, P < 0.01), whereas in subjects with impaired glucose tolerance and noninsulin-dependent diabetes, only the fasting insulin level correlates with IR (-0.47, P < 0.05 and -0.48, P < 0.01) (32). Hence, fasting insulin may be considered a biomarker for whole-body IR in population studies. However, clamp studies and measurements of insulin levels in the blood are not indicative of specific site of IR, i.e. muscle vs. liver vs. fat. The ideal measurement of IR as a marker for IRS should include measures of tissue IR, which are currently difficult to measure in vivo and not readily available.

Dyslipidemia is a manifestation of IR and is characterized broadly by an elevation in LDL, very LDL, and TGs and a reduction in HDL cholesterol (15). By 11 yr after delivery, the women with GDM had significantly higher levels of TGs, TC, and LDL, compared with control women. Eighteen percent of women with GDM had TGs of 1.7 mmol/liter or more, compared with 2% controls, 42% percent of women with GDM had a cholesterol level greater than 5.2 mmol/liter, compared with 15% of controls, and 38% of women with GDM had LDL of 3.7 mmol/liter or more, compared with 12% of controls. Our findings differ from those of Kjos et al. (30) who found no difference in serum lipids in women with former GDM, compared with controls 36 months after delivery. We first assessed lipids 6 yr after delivery, at which time women with GDM had significantly higher TGs, TC, and LDL. Perhaps a later follow-up of the former GDM population in the Kjos study would reveal differences in the lipid profile.

The IRS rates increased significantly over the study period for both study groups. Using the Adult Treatment Panel II criteria, 27% of women with GDM and 8.2% of controls had IRS 11 yr after delivery, indicating a 3-fold higher rate of IRS for the women with GDM, compared with controls. In fact, the hazard function analysis, as shown in Fig. 2, A and B, revealed that control women without PPO had the lowest risk of developing IRS 11 yr after delivery. In comparison with controls without PPO, controls with PPO were 6.8 times more likely to develop IRS, and women with GDM without PPO were 4.8 times more likely to develop IRS. The greatest risk of developing IRS was women with GDM and a history of PPO. These women were 26 times more likely to develop IRS at 11 yr after delivery than controls without PPO. This strongly supports that, in addition to PPO, there is an additional independent increased risk of IRS among women with a history of GDM.

In summary, our data indicate that women with former GDM, especially women with a history of PPO, are at considerable increased risk of developing IRS. This finding has important clinical implications. Awareness of a subgroup of women at increased risk of developing IRS will alert providers of the need for regular monitoring and the initiation of interventions including dietary management, exercise, and medications to prevent long-term complications (34, 35).

Acknowledgments

We gratefully appreciate the assistance of Jane Healey, R.N., and Joanne Rainho, R.N., for completing the patient assessments and Nancy Gelardi for completing the biochemical analyses.

Footnotes

Abbreviations: BMI, Body mass index; BP, blood pressure; CI, confidence interval; CVD, cardiovascular disease; DM, diabetes mellitus; GDM, gestational diabetes mellitus; HDL, high-density lipoprotein; HR, hazard ratio; IR, insulin resistance; IRS, insulin resistance syndrome; LDL, low-density lipoprotein; LGA, large for gestational age; PPO, prepregnant obesity; SES, socioeconomic status; TC, total cholesterol; TG, triglyceride.

Received December 14, 2001.

Accepted April 8, 2002.

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