FormalPara Key Summary Points

Why carry out this study?

Women with previous gestational diabetes are at higher risk of postpartum dyslipidemia, irrespective of glucose tolerance status.

Therefore, we aimed our study at investigating the prevalence of postpartum dyslipidemia and estimating the risk of postpartum dyslipidemia based on metabolic pregnancy parameters in normoglycemic women with previous gestational diabetes.

What was learned from this study?

Our results suggested a rather high occurrence of postpartum dyslipidemia in normoglycemic women with previous gestational diabetes.

We defined mid-term metabolic predictors for postpartum dyslipidemia in normoglycemic women with previous gestational diabetes.

Moreover, based on the mid-term pregnancy predictors, we developed the ALOHa-G score as a simple tool to identify normoglycemic women with previous gestational diabetes at high risk of postpartum dyslipidemia in clinical settings.

Introduction

It is known that women with gestational diabetes (GD) are at high risk of developing metabolic diseases such as prediabetes or diabetes, dyslipidemia, and cardiovascular disease (CVD) in later life [1,2,3]. Also, current evidence suggests that postpartum dyslipidemia is much more common in women with previous GD (pGD), who have a 1.4- to 1.8-fold increased risk compared to their peers [3].

Simultaneously, it has been shown that age, weight, and lipid status during pregnancy are associated with the risk of postpartum dyslipidemia [4,5,6]. On the other hand, dyslipidemia during pregnancy is a common physiological phenomenon, especially after mid-trimester, since increased levels of lipids are essential for fetus development [7]. A growing number of studies are exploring the normal range of elevation of pregnancy lipids as well as their influence on pregnancy outcomes and future metabolic diseases after delivery [8]. Furthermore, only a limited number of studies have evaluated risk factors for postpartum dyslipidemia, particularly in normoglycemic women with pGD, who are even more underestimated in clinical settings [4, 9].

In this regard, there is a need for early detection of women with GD who are at risk of developing postpartum dyslipidemia, even in pregnancy, as well as a simple tool/score which could facilitate the estimation of postpartum dyslipidemia risk among normoglycemic women with pGD, focusing on their cardiometabolic risk.

In that context, our study was aimed at investigating the prevalence of postpartum dyslipidemia in normoglycemic women with pGD early after delivery, and identifying women at high risk for developing postpartum dyslipidemia based on mid-term pregnancy metabolic parameters.

Methods

Research Design

We initially included 254 singleton pregnant women with GD who were diagnosed according to IADPSG/WHO criteria [10] and were treated only by lifestyle modification (Fig. 1). In the 1–6 months after delivery, all women were retested by 2 h oral glucose tolerance test (OGTT), and 107 were excluded because of prediabetes or diabetes according to ADA criteria [11]. Afterwards, 147 women with previous GD and normal glucose tolerance (NGT) after delivery were divided into two groups: group A (n = 63) with postpartum dyslipidemia, and group B (n = 85) without dyslipidemia. The diagnosis of postpartum dyslipidemia was made according to the Third Report of the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III) Final Report (NCEP-ATP III) [12] if at least one of the defined thresholds was met: TC level ≥ 6.22 mmol/L, TG level ≥ 2.26 mmol/L, LDL-C level ≥ 4.14 mmol/L, and HDL-C level ≤ 1.04 mmol/L. Women were treated at the Department for Metabolic Disorders, Intensive Treatment and Cell Therapy in Diabetes, Clinic for Endocrinology, Diabetes and Metabolic Disease, University Clinical Center of Serbia from 1 January 2017 until 31 December 2021. During pregnancy, 2 h OGTT was performed between the 24th and the 28th week of gestation (timeline for screening for GD), and fasting plasma glucose (FPG), HbA1c, and lipid parameters were collected in the same timeframe. Within 1–6 months (a wide timeline for postpartum screening for dysglycemia) after delivery, the 75 g 2 h OGTT was repeated, as well as a blood analysis of lipid parameters. The study was designed as an observational cohort study.

Fig. 1
figure 1

Research design

Full size image

ç

Inclusion Criteria

  1. 1.

    GD according to IADPSG/WHO criteria [10], where at least one of the glucose values from a 75 g 2 h OGTT is equal to or exceeds the following thresholds: FPG, 5.1 mmol/L; 1 h plasma glucose (PG), 10.0 mmol/L; 2 h PG, 8.5 mmol/L

  2. 2.

    NGT 1–6 months after delivery, as confirmed by 75 gr 2 h OGTT, where the glucose values were between defined thresholds: FPG was less than 5.6 mmol/L and 2h PG less than 7.8 [12].

Exclusion Criteria

  1. 1.

    Pregnancy obtained from assisted reproductive technologies

  2. 2.

    Previous thyroid and/or hepatic disorder

  3. 3.

    Known familiar hyperlipoproteinemia

  4. 4.

    Antihyperglycemic treatment including oral drugs (metformin) or insulin during previous pregnancy and/or 6 months after delivery

  5. 5.

    Corticosteroid treatment during pregnancy and/or 6 months after delivery.

Measurements

Body mass index (BMI) preconception was calculated according to the equation BMI = weight (kg)/height (m2), and self-reported data on weight and height were obtained by an experienced interviewer. We also recorded perception of financial status (self-reported as bad, average, or good), education level (secondary school or university), as well as urban or suburban community, obtained through an interview.

HbA1c was measured using a commercial test reagent (SEBIA, Lisses, France).

FPG and PG values during the 2 h OGTT were obtained by the glucose oxidase method using a Beckman glucose analyzer (Beckman Instruments Inc., Fullerton, CA, USA).

Serum lipid levels (total cholesterol, HDL-c and triglycerides) were analyzed enzymatically using a commercial kit [Boehringer Mannheim GmbH (Roche Diagnostics), Mannheim, Germany], while LDL-c was calculated by the standard Friedewald formula.

Compliance with Ethics Guidelines

This investigation was done in accordance with national regulations as well as the Declaration of Helsinki of 1964, and its later amendments. All participants were extensively informed about the study, including the collection and publishing of data, before giving informed consent. The study was approved by the Ethics Committee of the Faculty of Medicine, University of Belgrade (reference number 1322/X-26).

Data Analysis

The descriptive statistics, including means, medians, standard deviations, and percentiles for numerical variables and numbers and percentages for categorical variables, were used to characterize the study sample. The Kolmogorov–Smirnov and Shapiro–Wilk tests were used to test the normality of the distribution. Student’s t test or the Mann–Whitney U test was used for numerical data to evaluate the differences between group A and group B, whereas associations between categorical data were evaluated using the Pearson chi-square test. Univariate logistic regression analysis was performed on previously calculated cutoff values for selected variables to determine factors related to postpartum dyslipidemia as the dependent variable. Results were expressed as corresponding 95% confidence intervals (CIs). Model discrimination performance was tested by means of sensitivity, specificity, and positive and negative predictive values. The C statistic, representing the area under the receiver operating characteristic curve, was used for overall assessment of the predictive model. In order to enhance the development of our risk prediction scoring system, we used the TRIPOD checklist. TRIPOD is an evidence-based minimum set of recommendations for reporting prediction modeling studies in biomedical sciences [13]. In all analyses, the level of statistical significance was set at p ≤ 0.05. SPSS version 25 statistical software (Chicago, USA) was used for the statistical analysis.

Results

Characteristics of the Study Population Preconception

The baseline characteristics of normoglycemic women with pGD are shown in Table 1. Whereas 42.8% of normoglycemic women with pGD had dyslipidemia (group A, n = 63), 57.2% had lipid values in the normal range based on lipid parameters measured after delivery (group B, n = 84) (Table 1, Fig. 2).

Table 1 Baseline characteristics in normoglycemic women with pGD: comparison between groups (group A vs. B) based on the presence of postpartum dyslipidemia
Full size table
Fig. 2
figure 2

Lipid abnormalities of women with pGD and postpartum dyslipidemia. Percentages of women with pGD who had TC levels ≥ 6.22 mmol/L, TG levels ≥ 2.26 mmol/L, LDL-C levels ≥ 4.14 mmol/L, and HDL-C levels ≤ 1.04 mmol/L are shown

Full size image

Analyzing age at the time of conception, we found that the women with postpartum dyslipidemia (group A) were significantly older than the women in group B (p < 0.001). Also, group A had significantly higher BMIs than group B (p < 0.001) preconception (Table 1).

Glycemic and Lipid Parameters in Mid-term Pregnancy

With regard to glucose tolerance parameters, although both groups had FPG and HbA1c levels in the normal range when measured in mid-term pregnancy, we detected that women in group A had significantly higher FPG and HbA1c in comparison to group B (p < 0.001, respectively) (Table 1).

Simultaneously, we found that TC, LDL-c, and TG during mid-term pregnancy were higher in group A in comparison to group B (p < 0.001, respectively), while HDL-c in group A was comparable to that in group B (p = 0.998) (Table 1).

ROC Analysis of Significant Variables

Finally, we used ROC to determine the optimal cutoffs for selected variables which remained significant after comparing groups. In that context, the predictive accuracy of age at conception for detecting dyslipidemia after delivery among normoglycemic women with pGD showed a sensitivity of 74.6%, specificity of 71.4%, PPV of 66.2%, and NPV of 78.9% for a cutoff of 35 years (AUC 0.814, p < 0.001). In addition, the predictive accuracy of preconception BMI for detecting dyslipidemia after delivery had a sensitivity of 56.5%, specificity of 23.8%, PPV of 35.4%, and NPV of 42.6% for a cutoff of 26.4 kg/m2 (AUC 0.665, p = 0.001). Also, FPG in pregnancy with a cutoff of 4.8 mmol/L (AUC 0.703, p < 0.001) showed a sensitivity of 71.4%, specificity of 94.5%, PPV of 91.8%, and NPV of 79.3% for detecting dyslipidemia after delivery, and HbA1c with a cutoff of 5.2% (AUC 0.763, p < 0.001) showed a sensitivity of 71.4%, specificity of 82.1%, PPV of 75%, and NPV of 79.3%. According to our results, the optimal cutoff for LDL-c in pregnancy to predict dyslipidemia after delivery among normoglycemic women with pGD was 3.9 mmol/L (AUC 0.709, p < 0.001), which led to a sensitivity of 84.1%, specificity of 52.1%, PPV of 52.1%, and NPV of 84.1%, while the cutoff for TG was 2.7 mmol/L (AUC 0.660, p = 0.005), which gave a sensitivity of 64.3%, specificity of 59.2%, PPV of 48.2%, and NPV of 73.7%.

Developing the ALOHa-G Score

When univariate regression analysis was used with the previously calculated optimal cutoff values for the six selected variables [age at conception, BMI in preconception, FPG and HbA1c, lipid parameters (LDL-c and TG)], a significant difference was found (Table 2). Moreover, the predictive accuracy of these six variables was examined using ROC analysis [AUC 0.931, SE 0.021, p < 0.001, 95% CI (0.890–0.972)] (Fig. 3), and, based on the significant predictors, we developed ALOHa-G (an acronym for Age, Lipids, Overweight, HbA1c, fasting plasma Glucose). Each of the six selected variables were assigned 1 score point as they all had comparable levels of significance (Table 3). The risk estimation score (ALOHa-G score) for detecting dyslipidemia after delivery among normoglycemic women with pGD ranges from 0 to 6 points. Moreover, a total score ≤ 2 reflects a low risk, a total score of 3 reflects a medium risk, whereas a total score ≥ 4 represents a high risk for dyslipidemia after delivery among normoglycemic women with pGD (Table 4).

Table 2 Logistic regression model with postpartum dyslipidemia as the dependent variable
Full size table
Fig. 3
figure 3

Predictive accuracy of the ALOHa-G score for detecting postpartum dyslipidemia among normoglycemic women with pGD

Full size image
Table 3 ALOHa-G score: selected variable cutoffs and relative score points
Full size table
Table 4 Risk estimation of postpartum dyslipidemia among normoglycemic women with pGD based on total ALOHa-G score
Full size table

Using the ALOHa-G score to predict the development of dyslipidemia after delivery in our sample, we found that the proportion of the women in group B who were at high risk for the development of dyslipidemia was only around 5%, while the corresponding proportion of group A was significantly higher (around 62%) (p < 0.001). Similarly, according to the ALOHa-G score, 81% of the women in group B had a low risk for postpartum dyslipidemia, in contrast to less than 5% of the women in group A (p < 0.001) (Fig. 4).

Fig. 4
figure 4

Risk estimation of postpartum dyslipidemia among normoglycemic women with pGD using the ALOHa-G score (p < 0.001, chi-square)

Full size image

Discussion

In our observational cohort study, we found that a notable percentage of normoglycemic women with pGD had dyslipidemia during the half-year period after delivery. Furthermore, normoglycemic women with pGD and dyslipidemia after delivery were older and overweight at the time of conception and had higher values of glycemic and lipid parameters in mid-pregnancy compared to those without dyslipidemia. Simultaneously, using calculated cutoff values for significant predictors, we developed the ALOHa-G score to estimate the risk of dyslipidemia in normoglycemic women with pGD after delivery.

Previous studies showed that the prevalence of postpartum dyslipidemia varies from 38.5 to 52% depending on the period of observation after delivery [3, 4, 9]. The majority of these studies detected both dyslipidemia and prediabetes or diabetes, which are common residual metabolic disorders in women with pGD [14]. One of the studies showed that 60% of the detected postpartum dyslipidemia occurred in women with normal glucose tolerance [4]. Furthermore, the rationale for including only normoglycemic women with pGD in our study was to define risk factors for postpartum dyslipidemia in this population, who may be mistakenly considered to be “normal” in the context of future cardiometabolic risk. Also, our results are almost in line with the previously noted prevalence of postpartum dyslipidemia in women with pGD.

However, there is limited evidence on the prevalence and predictors of dyslipidemia after delivery among normoglycemic women with pGD [4]. Moreover, the results with respect to GD as a risk factor for postpartum dyslipidemia are conflicting, especially after adjusting for potential confounders such as age and BMI [15]. A recent study defined 35 years as a cutoff for postpartum dyslipidemia in women with pGD [4], which was also defined as a predictor in our study. Previously recognized risk factors for dyslipidemia, such as overweight status, were also confirmed in our results [4, 15].

An earlier study indicated HbA1c as a significant predictor for postpartum dyslipidemia irrespective of glucose tolerance status [4]. A previous study that aimed to identify the cardiovascular risk profile after delivery based on fasting glycemia tertiles in pregnancy showed an association between the highest tertile and postpartum dyslipidemia [16]. In our study, glycemic parameters, namely FPG and HbA1c in the mid-pregnancy trimester, were also singled out as important predictors for postpartum dyslipidemia among normoglycemic women with pGD.

The majority of studies have evaluated lipid parameters in women with GD predominantly in association with adverse pregnancy outcomes [17], neglecting the importance of dyslipidemia as a prominent risk factor for cardiovascular disease during the lifespan [18]. In addition, not only the occurrence of dyslipidemia but also the duration of exposure to dyslipidemia plays an important role in atherosclerosis [19], suggesting the need for identification from early postpartum on. In that context, our study was aimed at developing a simple tool to identify and facilitate timely intervention.

Previous data implied that disturbance of the lipid profile (namely total cholesterol, LDL-c, and triglycerides) during pregnancy might be associated with persistent postpartum dyslipidemia, while HDL-c did not influence postpartum dyslipidemia occurrence [20], which was also confirmed by our analysis.

Logistic univariate regression analysis clearly distinguished age, BMI before conception, FPG, HbA1c, LDL-c, and TG (using optimal cutoff values calculated beforehand) as predictors for postpartum dyslipidemia in normoglycemic women with pGD. Analyzing individual predictors separately, it is interesting to point out that the FPG cutoff in mid-pregnancy was even more strict than the one defined as a therapeutic goal for fasting glucose in pregnancy. The HbA1c cutoff for a high risk profile for postpartum dyslipidemia in normoglycemic women with pGD in our study was almost in agreement with previous findings [4]. According to our results, even in conditions where glycemic goals (FPG and HbA1c) are achieved, women with GD might be at risk for postpartum dyslipidemia after delivery, even when they are normoglycemic [4]. On the other hand, lipid parameters during mid-pregnancy should not be ignored due to a lack of therapeutic importance. Furthermore, pregnancy levels of LDL-c and TG were identified as predictors for postpartum dyslipidemia in women with GD [20], which is in line with our results.

Hence, using previously described predictors, we developed the ALOHa-G score and deliberately allocated equal contributions to each individual variable based on their levels of significance. Therefore, although some of the variables showed only moderate accuracy, we focused on analyzing the combination of selected predictors, which yielded respectable accuracy. Nevertheless, the risk score category (low, moderate, high) was influenced by the number of predictors present. In that context, more than 60% of normoglycemic women with pGD and postpartum dyslipidemia were in the high-risk category according to to ALOHa-G score. We did not find any other similar tool for predicting the presence of postpartum dyslipidemia among normoglycemic women with pGD based on metabolic mid-pregnancy variables. Therefore, our ALOHa-G risk score could be a simple tool for the early identification of a high risk profile for postpartum dyslipidemia among normoglycemic women with pGD in clinical settings.

Taking into account prior studies, it has not been clarified yet whether attaining normoglycemia can, on its own, ameliorate CV risk in pGD, or whether there are other contributing factors, such as dyslipidemia [21, 22]. Therefore, current recommendations suggest not only screening for postpartum glucose intolerance [23], but also determining the lipid profile after delivery in women with pGD [24]. However, we wanted to highlight the importance of diagnosing postpartum dyslipidemia in women with pGD independently of glucose tolerance status.

Limitations

Our study, which aimed to identify a high risk profile for dyslipidemia after delivery in normoglycemic women with pGD, had several limitations. Firstly, we analyzed only lipid parameters in mid-pregnancy without taking into consideration the lipid continuum from preconception, through the pregnancy trimesters, and after delivery, and without analyzing different types of dyslipidemia. Also, we are aware of the observational study design, the small sample size for constructing the risk score, as well as the lack of mandatory validation using an independent cohort.

Conclusions

Our results suggest a rather high occurrence of postpartum dyslipidemia, even in normoglycemic women with previous gestational diabetes. Also, mid-pregnancy glycemic and lipid parameters in gestational diabetes together with BMI and age preconception were identified as predictors for postpartum dyslipidemia. Moreover, the investigated predictors were assessed for use as a platform to develop the ALOHa-G score, a tool for identifying a high risk profile for postpartum dyslipidemia. In general, detecting and further elucidating postpartum dyslipidemia in normoglycemic women with previous gestational diabetes may contribute to the clarification and potential prompt modification of a higher cardiovascular risk independent of glucose tolerance status after delivery.