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Impact of postpartum weight change on metabolic syndrome and its components among women with recent gestational diabetes mellitus

Abstract

Background

While postpartum weight changes may affect the levels of metabolic parameters, the direct effects of weight changes in the postpartum period on changes in the prevalence rates of metabolic syndrome and its components remain unstudied. This study aimed to investigate the effects of postpartum weight changes between 6 weeks and 6 months on changes in the prevalence rates of metabolic syndrome and its components in women who have recently experienced gestational diabetes mellitus.

Methods

This prospective cohort study included 171 postpartum women with recent gestational diabetes mellitus, who underwent serial weight and metabolic risk factor assessments at 6 weeks and 6 months postpartum. Weight changes between these time points were classified as weight loss (> 2 kg), weight stability (± 2 kg), or weight gain (> 2 kg). Metabolic syndrome comprised the following metabolic risk factors: large waist circumference, elevated blood pressure, elevated fasting plasma glucose levels, high triglyceride levels, and low high-density lipoprotein cholesterol levels.

Results

Of the 171 women in our cohort, 30 women (17.5%) lost > 2 kg of body weight, while 85 (49.7%) maintained a stable weight and 56 (32.8%) gained > 2 kg. The weight loss group experienced significant changes in the prevalence rates of the following metabolic risk factors compared to the weight stability and weight gain groups: large waist circumference (% change: − 26.7 vs − 5.9 vs 5.4, respectively; p = 0.004), elevated fasting plasma glucose levels (% change: − 3.4 vs 18.9 vs 26.8, respectively; p = 0.022), and high triglyceride levels (% change: − 30.0 vs 0 vs − 7.2, respectively; p = 0.024). A significantly greater decrease in the prevalence of metabolic syndrome was also found in the weight loss group than in the other two groups (% change: − 20.0 vs 11.8 vs 14.2, respectively; p = 0.002).

Conclusions

Weight changes from 6 weeks to 6 months postpartum significantly altered the prevalence rates of metabolic syndrome and its components in women with recent gestational diabetes mellitus. Early postpartum weight loss can reverse metabolic risk factors and reduce the prevalence of metabolic syndrome.

Trial registration

Thai Clinical Trials Registry: Registration no. TCTR20200903001. Date of registration: September 3, 2020. Date of initial participant enrolment: September 7, 2020.

Plain language summary

Metabolic syndrome (MetS) is a frequent diagnosis with consequences for the occurrence of cardiovascular diseases. Women with gestational diabetes mellitus (GDM) are especially vulnerable to the development of MetS. In this study, we investigated how postpartum weight changes, specifically between 6 weeks and 6 months postpartum, impact MetS and its components in women who have recently experienced GDM. The results of our study showed that women who lost > 2 kg of body weight between 6 weeks and 6 months postpartum had significant decreases in the prevalence rates of metabolic risk factors, leading to a lower prevalence of MetS, compared to women who maintained a stable weight (± 2 kg) or gained > 2 kg. Our findings suggest that such weight loss is beneficial for preventing MetS; thus, strategies should be developed to support women with GDM in achieving postpartum weight loss. These strategies may include personalized dietary counseling, exercise programs, and behavioral support tailored to the specific needs and challenges faced by this population.

Peer Review reports

Background

Metabolic syndrome (MetS) has emerged as a global epidemic in recent decades [1], with variations in the prevalence across different ages, sexes, and ethnicities [2, 3]. Among women of reproductive age, the incidence rates of MetS and its components appear to be on the rise in recent years [4]. MetS encompasses a collection of metabolic risk factors, including abdominal obesity, elevated blood pressure (BP), elevated fasting plasma glucose (FPG) levels, high triglyceride (TG) levels, and low high-density lipoprotein cholesterol (HDL-C) levels [5, 6]. As an important risk factor for type 2 diabetes mellitus (T2DM) and cardiovascular diseases [7, 8], MetS warrants special attention.

Gestational diabetes mellitus (GDM) is a common medical complication of pregnancy. Compared to pregnant women without GDM, those with GDM often exhibit an elevated body mass index, BP, and TG level, along with a lower HDL-C level [9,10,11]. Furthermore, these metabolic risk factors have been observed to persist and even worsen in the postpartum period among women who have experienced GDM [12,13,14,15,16]. This persistence of metabolic abnormalities contributes to a higher prevalence of postpartum MetS in women with GDM compared to normoglycemic pregnant women [15, 16].

Given that abdominal obesity, as indicated by a large waist circumference (WC), is a common metabolic risk factor found after GDM [13], early postpartum weight loss may help improve a large WC and other metabolic risk factors, thereby reducing the risk of MetS. Several studies have reported significant effects of postpartum weight changes on changes in the levels of metabolic parameters such as WC, FPG, and TG in women with recent GDM [17,18,19]. However, no study has explored the direct effects of postpartum weight changes on changes in the prevalence rates of MetS and its components in this population.

To address this gap, we designed a longitudinal study to follow women with recent GDM after childbirth, assessing how postpartum weight changes were associated with alterations in MetS and its components over time. By examining such associations, insights can be gained into the potential benefits of weight management interventions in this population. Such findings can inform clinical practice and public health strategies aimed at reducing the long-term metabolic risks associated with GDM.

The objective of this study was to investigate the impact of weight changes occurring between 6 weeks and 6 months postpartum on changes in the prevalence rates of MetS and its components among women with recent GDM.

Methods

Study design and study population

This prospective cohort study was conducted between September 7, 2020, and July 31, 2023, as part of a study exploring strategies to improve the metabolic health of postpartum women with a history of GDM. The study protocol was approved by the Vajira Institutional Review Board (approval no. 017/2563) and performed in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines. The protocol was registered with the Thai Clinical Trials Registry (registration no. TCTR20200903001).

The study population included women aged ≥ 18 years with recent GDM who delivered a live infant at the Faculty of Medicine Vajira Hospital, Bangkok, Thailand, between September 7, 2020, and January 31, 2023. Inclusion criteria were women who underwent antenatal care and GDM screening at the hospital. The exclusion criteria were pregnancy during the 6 months of study involvement, loss to follow-up, and refusal to participate.

Sample size

Given that no study has directly explored the effects of postpartum weight changes on changes in the prevalence rates of MetS and its components among women with a history of GDM, the sample size was calculated based on data from a previous study that explored the effects of weight changes between 3 and 12 months on changes in the levels of metabolic parameters in this population [17]. Based on the findings that changes in WC among women in the weight loss, weight stability, and weight gain groups were − 5.4 ± 5.1 cm, − 1.8 ± 4.6 cm, and 1.4 ± 4.6 cm, respectively, the sample size was calculated using the data on WC changes in the weight stability and weight gain groups because this yielded the largest sample. With 80% power at a two-sided significance level of 0.05, at least 99 participants were required (33 each with weight loss, weight stability, and weight gain). Allowing for a dropout rate of 25%, the total sample size required was 132 (44 in each group).

Institutional practices for GDM screening and diagnosis

The institutional practices for GDM screening and diagnosis have been described in detail in our previous work [20]. In brief, we followed the standard recommendation that all pregnant women undergo GDM screening using a 50-g glucose challenge test, followed by a 100-g oral glucose tolerance test (OGTT) using the Carpenter and Coustan criteria if the screening result was abnormal [21]. Blood samples were collected by phlebotomists and sent to the hospital laboratory. The initial management of women with GDM consists of dietary and lifestyle modifications, followed by insulin therapy if fasting or postprandial plasma glucose levels remain high despite dietary management [21].

After delivery, all women with GDM are scheduled for a postpartum checkup and T2DM screening using a 75-g, 2-h OGTT at 6 weeks postpartum [22].

Participant recruitment and follow-up

Consecutive women with pregnancies complicated by GDM, who delivered between September 7, 2020, and January 31, 2023, were approached by a researcher at the postnatal ward on the second day after delivery. These women received a study outline and were invited to participate in the study. All interested women were screened for eligibility. Written informed consent was obtained from all eligible women before the beginning of the study.

At enrollment, the clinical characteristics of the participants were collected from their medical records. These included age, weight, parity, family history of diabetes mellitus, severity of GDM, and gestational age at delivery. Participants were scheduled for serial assessments of weight and metabolic risk factors at 6 weeks and 6 months postpartum.

At 6 weeks postpartum, data on breastfeeding practices were collected from the participants upon their postpartum visit. Physical examinations, including measurements of weight, WC, and BP, were performed by a nurse who had been trained to ensure standard and accurate measurements. The body weight was measured without shoes and with light clothing using the Tanita Model WB-3000 digital scale (Tanita Corporation, Tokyo, Japan). WC was measured in the horizontal plane midway between the lowest ribs and the iliac crest with the participants in a standing position. After 10 min of rest, the BP was recorded to the closest 2 mmHg using the Nova-Presameter Desk mercury sphygmomanometer (Rudolf Riester GmbH, Jungingen, Germany) with the arm supported at heart level. Three separate BP readings were taken at 1-min intervals. The average of the last two readings was used for the analysis.

Venous blood samples were drawn to determine FPG, fasting lipid, and 2-h postprandial glucose (PG) levels. Fasting lipids included total cholesterol, TG, low-density lipoprotein cholesterol, and HDL-C levels. If participants were diagnosed with T2DM, MetS, or both, they were referred to an endocrinologist for further management.

At 6 months postpartum, the same data were collected for all participants. Blood samples were collected to determine FPG, fasting hemoglobin A1c (HbA1c), and fasting lipid levels.

Laboratory measurements

All blood samples for FPG, HbA1c, and lipid analyses were collected in the morning after overnight fasting for 12 h and sent to the hospital’s laboratory. A standard 75-g OGTT was performed to measure 2-h PG levels. Plasma glucose and lipid levels were measured using the automated analyzer Cobas c503 (Roche Diagnostics, Mannheim, Germany). HbA1c levels were measured using a Cobas c513 analyzer (Roche Diagnostics).

All devices were calibrated in-house daily and annually using external validation. Our laboratory has received National Glycohemoglobin Standardization Program certification for HbA1c assays and is traceable to the Diabetes Control and Complications Trial reference method. The HbA1c and blood chemistry analyses were approved by the Randox International Quality Assessment Scheme.

Stratification of participants, outcome assessment, and definitions

We stratified participants into three groups according to weight changes from 6 weeks to 6 months postpartum: weight loss (> 2 kg), weight stability (± 2 kg), and weight gain (> 2 kg) [17]. The outcome measures included changes in the prevalence rates of MetS and its components.

The presence of MetS was established using the joint interim statement of the International Diabetes Federation Task Force on Epidemiology and Prevention [5]. MetS was defined as the presence of three or more of the following five metabolic components: large WC (≥ 80 cm), elevated BP (systolic BP ≥ 130 mmHg, diastolic BP ≥ 85 mmHg, or both, or treatment with antihypertensive drugs), elevated FPG levels (≥ 100 mg/dL, or treatment with antidiabetic medications), high TG levels (≥ 150 mg/dL, or treatment with drugs for elevated TG levels), and low HDL-C levels (< 50 mg/dL, or drug treatment for reduced HDL-C levels). Those with FPG levels ≥ 126 mg/dL, 2-h PG levels ≥ 200 mg/dL, or HbA1c levels ≥ 6.5% were diagnosed as having T2DM [23].

Statistical analyses

All analyses were performed using IBM SPSS Statistics for Windows, Version 28.0 (IBM Corporation, Armonk, NY, USA). Categorical variables are presented as numbers and percentages and were compared using the chi-squared test. Continuous variables are described as means and standard deviations. Differences in the means of continuous variables between the three groups were analyzed using a one-way analysis of variance. When the overall analysis was significant, intergroup comparisons were made using the least significant difference method as a post-hoc test.

Changes in the means of variables over time (between 6 weeks and 6 months postpartum) within each group were analyzed using paired t-tests. The differences in changes between the three groups were analyzed using a one-way analysis of covariance, controlling for weight at 6 weeks postpartum and exclusive breastfeeding at 6 months postpartum, which were previously identified as factors affecting the prevalence of MetS or metabolic risk factors [17, 24]. Changes in the prevalence rates of MetS and its components over time within a group were calculated using McNemar’s test. The differences in changes between the three groups were compared using the chi-squared test. Statistical significance was defined as a two-sided p < 0.05.

Results

The study flow diagram, which is in line with the STROBE statement, is shown in Fig. 1. Of the 220 enrolled participants, 49 were excluded due to loss to follow-up before completing 6 months of participation in the study. There were no significant differences in delivery characteristics between participants who completed the study and those who were lost to follow-up (all p > 0.05). The 171 participants finally included were stratified into three groups: weight loss (> 2 kg; n = 30), weight stability (± 2 kg; n = 85), and weight gain (> 2 kg; n = 56).

Fig. 1
figure 1

STROBE flow diagram. GDM gestational diabetes mellitus, STROBE Strengthening the Reporting of Observational Studies in Epidemiology

Participant characteristics

The mean age and mean weight at delivery of the 171 included participants were 32.5 ± 5.9 years and 75.4 ± 14.2 kg, respectively. Approximately 15.8% (n = 27) of participants had class A2 GDM. The mean gestational age at delivery was 37.8 ± 1.4 weeks. The clinical characteristics of the participants in each weight change group are shown in Table 1.

Table 1 Clinical characteristics of participants in each weight change group

Changes in the levels of metabolic parameters

Changes in the levels of metabolic parameters over time within and between the groups are shown in Table 2. The weight loss group showed a significantly greater decrease in WCs and a significantly smaller increase in FPG levels than the other two groups. In addition, the weight loss group showed a significantly greater decrease in TG levels than the weight stability group. The weight stability group showed a significantly greater decrease in WCs than the weight gain group. The results of the one-way analysis of covariance showed that the weight at 6 weeks postpartum and exclusive breastfeeding at 6 months postpartum have no significant effect on changes in the metabolic parameter levels.

Table 2 Changes in metabolic parameters within and between groups

Changes in the prevalence rates of metabolic risk factors

At 6 weeks postpartum, a large WC (67.3%; n = 115) was the most commonly detected metabolic risk factor, followed by a high TG level (32.7%; n = 56), low HDL-C level (28.7%; n = 49), elevated BP (23.4%; n = 40), and elevated FPG level (15.8%; n = 27) levels.

At 6 months postpartum, the prevalence rates of these metabolic risk factors in the order of decreasing frequency were as follows: a large WC (61.4%; n = 105), low HDL-C level (37.4%; n = 64), elevated FPG level (33.3%; n = 57), high TG level (25.1%; n = 43), and elevated BP (18.1%; n = 31).

Changes in the prevalence rates of metabolic risk factors over time within and between the groups are summarized in Table 3. The weight loss group had significantly greater decreases in the prevalence rates of large WC and high TG level than the other two groups. The weight loss group also showed a significantly greater decrease in the prevalence of high TG levels than the weight stability group. The changes in the prevalence rates of the five metabolic risk factors were not significantly different between the weight stability and weight gain groups.

Table 3 Changes in the prevalence rates of metabolic syndrome and its components within and between groups

Changes in the prevalence of MetS

The weight loss group experienced a significantly greater decrease in the prevalence of MetS than the other two groups (Table 3). Changes in the prevalence of MetS between the weight stability and weight gain groups did not differ significantly.

Discussion

The main findings of this study were that postpartum women with recent GDM who lost > 2 kg of weight between 6 weeks and 6 months postpartum had significant improvements in metabolic parameters, leading to significantly lower rates of MetS and its components than those in women who maintained a stable weight (± 2 kg) or gained > 2 kg.

Our observation of a greater decrease in WCs and a smaller increase in FPG levels in the weight loss group than in the other two groups aligned with the results of previous studies, including women with recent GDM with a longer postpartum evaluation interval [17,18,19]. A study including 206 Australian women revealed significant improvements in WCs and TG levels among women who lost > 2 kg within 6 weeks to 12 months postpartum when compared to those whose weight remained stable or increased [17]. Another study involving 72 American women showed a significantly smaller increase in FPG levels in women who lost > 2 kg within 12 months postpartum than in those who maintained or gained weight [18]. Likewise, a study including 75 American women demonstrated significant correlations of weight changes between baseline (6 weeks postpartum) and 6 and 12 months postpartum with the changes in FPG and TG levels [19]. Although our study and those performed in Australia and the United States differed in terms of population characteristics (such as ethnicity and weight at delivery) and the postpartum time points at which weight changes were examined, the consistent results among these studies indicate that postpartum weight changes have the potential to impact metabolic parameters in women with a history of GDM.

To date, no study has explored how changes in postpartum weight affect the prevalence rates of MetS and its components, specifically in women with GDM. The results of our study showed that women who lost weight experienced significantly greater decreases in the prevalence rates of large WCs and high TG levels than those who maintained or gained weight. Among the two metabolic risk factors that significantly improved after weight loss, a greater reduction in the prevalence of large WCs was observed (from 66.7% to 40.0%, Δ: − 26.7%).

Moreover, we found that weight loss during the early postpartum period reduced the prevalence of MetS. The MetS prevalence decreased significantly from 36.7% at 6 weeks postpartum to 16.7% at 6 months postpartum in women who lost weight. Conversely, women with weight stability or weight gain exhibited an increase in MetS rates (from 14.1% to 25.9% and from 30.4% to 44.6%, respectively).

Our findings were consistent with those of a previous study conducted in Iran [13], which also identified a large WC as the most prevalent metabolic risk factor at 6 weeks postpartum among women with recent GDM. In contrast, a study including an American population revealed that low HDL-C levels were more common than a large WC among early postpartum women with a history of GDM [25]. These different findings may be attributed to the diverse definitions of large WCs or differences in body build among the populations studied. Our study and the study performed in Iran defined a large WC as ≥ 80 cm, whereas the study performed in the United States defined a large WC as ≥ 88 cm. Given that WC is a surrogate clinical measure of visceral adiposity, which predisposes individuals to MetS and subsequent T2DM and cardiovascular diseases, preventive measures to reduce a large WC are paramount.

Our findings underscore the metabolic implications of weight changes in the first 6 months after delivery in patients with GDM and highlight the benefits of > 2 kg postpartum weight loss in women with recent GDM. At present, there are no specific recommendations on the timing of MetS screening commencement following GDM or on the continuation of follow-up processes. The results of our study may be used to establish practice guidelines for the early detection of metabolic risk factors and MetS in women with a history of GDM. Special attention should be paid to those with weight stability or weight gain between 6 weeks and 6 months postpartum, who comprised 82.5% of this population.

Further research is needed to confirm the metabolic benefits of weight loss over a longer duration, beyond the first 6 months postpartum. Considering that postpartum women face several barriers to lifestyle modifications in terms of time constraints, childcare demands, and lack of motivation [26], interventional studies that include strategies to address these barriers should be considered to promote weight loss in the early postpartum period in women with recent GDM.

A strength of this study is its prospective serial evaluation of metabolic risk factors. In addition, the data collection procedures were standardized and reliable. All blood samples were tested using standardized assays in a single certified laboratory. Additionally, this study added new evidence that improvements in metabolic parameters resulting from weight loss in the early postpartum period could lead to subsequent decreases in the prevalence rates of MetS and its components among women with recent GDM.

Nevertheless, this study had some limitations. First, the relatively small number of women with weight loss of > 2 kg may have limited our ability to detect subtle differences in the extent and prevalence rates of some metabolic risk factors. A larger sample size would have provided more statistical power and potentially yielded more robust results. Second, this study was conducted at a specific hospital in Thailand and focused on a specific population of postpartum women with recent GDM. Therefore, the generalizability of the findings to other populations or settings may be limited. The results may not be applicable to women with different demographic characteristics or healthcare systems. Third, we excluded women who were lost to follow-up, which may have introduced selection bias. This omission could affect the representativeness of the sample and potentially influence the study's results. Fourth, our study defined a large WC as ≥ 80 cm, which may not be consistent with other definitions used in different populations or settings. This variation in defining metabolic risk factors could impact the comparability of the findings across studies and limit the generalizability of the results. Finally, this study focused on weight changes and metabolic parameters within the first 6 months postpartum. However, the long-term effects of weight loss on metabolic improvements beyond this timeframe remain unknown. It would be valuable to investigate whether the observed benefits persist or change over a longer duration.

Conclusions

Weight changes from 6 weeks to 6 months postpartum had a significant impact on the prevalence rates of MetS and its components in women with a history of GDM. Early postpartum weight loss reversed metabolic risk factors and possibly reduced the prevalence of MetS. Given the increasing prevalence of MetS among women of reproductive age and the availability of risk-reducing strategies, we propose that all postpartum women with GDM should undergo screening for metabolic risk factors, alongside screening for T2DM.

Availability of data and materials

The datasets used and analyzed in this study are available from the corresponding author upon reasonable request.

Abbreviations

BP:

Blood pressure

FPG:

Fasting plasma glucose

GDM:

Gestational diabetes mellitus

HbA1c:

Hemoglobin A1c

HDL-C:

High-density lipoprotein cholesterol

MetS:

Metabolic syndrome

OGTT:

Oral glucose tolerance test

PG:

Postprandial glucose

STROBE:

Strengthening the Reporting of Observational Studies in Epidemiology

T2DM:

Type 2 diabetes mellitus

TG:

Triglycerides

WC:

Waist circumference

References

  1. Saklayen MG. The global epidemic of the metabolic syndrome. Curr Hypertens Rep. 2018;20:12.

    Article  PubMed  PubMed Central  Google Scholar 

  2. Kuk JL, Ardern CI. Age and sex differences in the clustering of metabolic syndrome factors: association with mortality risk. Diabetes Care. 2010;33:2457–61.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Grundy SM, Neeland IJ, Turer AT, Vega GL. Ethnic and gender susceptibility to metabolic risk. Metab Syndr Relat Disord. 2014;12:110–6.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Ramos RG, Olden K. The prevalence of metabolic syndrome among US women of childbearing age. Am J Public Health. 2008;98:1122–7.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Alberti KG, Eckel RH, Grundy SM, Zimmet PZ, Cleeman JI, Donato KA, et al. Harmonizing the metabolic syndrome: a joint interim statement of the International Diabetes Federation Task Force on Epidemiology and Prevention; National Heart, Lung, and Blood Institute; American Heart Association; World Heart Federation; International Atherosclerosis Society; and International Association for the Study of Obesity. Circulation. 2009;120:1640–5.

    Article  CAS  PubMed  Google Scholar 

  6. Silva V, Stanton KR, Grande AJ. Harmonizing the diagnosis of metabolic syndrome–focusing on abdominal obesity. Metab Syndr Relat Disord. 2013;11:102–8.

    Article  PubMed  Google Scholar 

  7. Wilson PW, D’Agostino RB, Parise H, Sullivan L, Meigs JB. Metabolic syndrome as a precursor of cardiovascular disease and type 2 diabetes mellitus. Circulation. 2005;112:3066–72.

    Article  CAS  PubMed  Google Scholar 

  8. Lee EY, Han K, Kim DH, Park YM, Kwon HS, Yoon KH, et al. Exposure-weighted scoring for metabolic syndrome and the risk of myocardial infarction and stroke: a nationwide population-based study. Cardiovasc Diabetol. 2020;19:153.

    Article  PubMed  PubMed Central  Google Scholar 

  9. Benhalima K, Van Crombrugge P, Moyson C, Verhaeghe J, Vandeginste S, Verlaenen H, et al. Characteristics and pregnancy outcomes across gestational diabetes mellitus subtypes based on insulin resistance. Diabetologia. 2019;62:2118–28.

    Article  CAS  PubMed  Google Scholar 

  10. Birukov A, Glintborg D, Schulze MB, Jensen TK, Kuxhaus O, Andersen LB, et al. Elevated blood pressure in pregnant women with gestational diabetes according to the WHO criteria: importance of overweight. J Hypertens. 2022;40:1614–23.

    Article  CAS  PubMed  Google Scholar 

  11. Ryckman KK, Spracklen CN, Smith CJ, Robinson JG, Saftlas AF. Maternal lipid levels during pregnancy and gestational diabetes: a systematic review and meta-analysis. BJOG. 2015;122:643–51.

    Article  CAS  PubMed  Google Scholar 

  12. Ko GT, Chan JC, Tsang LW, Li CY, Cockram CS. Glucose intolerance and other cardiovascular risk factors in chinese women with a history of gestational diabetes mellitus. Aust N Z J Obstet Gynaecol. 1999;39:478–83.

    Article  CAS  PubMed  Google Scholar 

  13. Nouhjah S, Shahbazian H, Shahbazian N, Jahanfar S, Jahanshahi A, Cheraghian B, et al. Early postpartum metabolic syndrome in women with or without gestational diabetes: results from life after gestational diabetes Ahvaz cohort study. Diabetes Metab Syndr. 2018;12:317–23.

    Article  PubMed  Google Scholar 

  14. Retnakaran R, Qi Y, Connelly PW, Sermer M, Zinman B, Hanley AJ. Glucose intolerance in pregnancy and postpartum risk of metabolic syndrome in young women. J Clin Endocrinol Metab. 2010;95:670–7.

    Article  CAS  PubMed  Google Scholar 

  15. Shen Y, Li W, Leng J, Zhang S, Liu H, Li W, et al. High risk of metabolic syndrome after delivery in pregnancies complicated by gestational diabetes. Diabetes Res Clin Pract. 2019;150:219–26.

    Article  PubMed  PubMed Central  Google Scholar 

  16. Vilmi-Kerälä T, Palomäki O, Vainio M, Uotila J, Palomäki A. The risk of metabolic syndrome after gestational diabetes mellitus - a hospital-based cohort study. Diabetol Metab Syndr. 2015;7:43.

    Article  PubMed  PubMed Central  Google Scholar 

  17. Lim S, Versace VL, O’Reilly S, Janus E, Dunbar J. Weight change and cardiometabolic outcomes in postpartum women with history of gestational diabetes. Nutrients. 2019;11:922.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Ehrlich SF, Hedderson MM, Quesenberry CP Jr, Feng J, Brown SD, Crites Y, et al. Post-partum weight loss and glucose metabolism in women with gestational diabetes: the DEBI Study. Diabet Med. 2014;31:862–7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Nicklas JM, Rosner BA, Zera CA, Seely EW. Association between changes in postpartum weight and waist circumference and changes in cardiometabolic risk factors among women with recent gestational diabetes. Prev Chronic Dis. 2019;16:E47.

    Article  PubMed  PubMed Central  Google Scholar 

  20. Phaloprakarn C, Tangjitgamol S. Glucose levels during gestational diabetes pregnancy and the risk of developing postpartum diabetes or prediabetes. BMC Pregnancy Childbirth. 2022;22:22.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Committee on Practice Bulletins—Obstetrics. ACOG practice bulletin no. 190: gestational diabetes mellitus. Obstet Gynecol. 2018;131:e49–64.

    Article  Google Scholar 

  22. Phaloprakarn C, Suthasmalee S. Effect of prenatal counseling on postpartum follow-up and contraceptive use in women with gestational diabetes mellitus: a randomized controlled trial. Am J Obstet Gynecol MFM. 2023;5:101107.

    Article  PubMed  Google Scholar 

  23. American Diabetes Association Professional Practice Committee. 2. Classification and diagnosis of diabetes: standards of medical care in diabetes-2022. Diabetes Care. 2022;45(Suppl 1):S17–38.

    Article  Google Scholar 

  24. Yasuhi I, Soda T, Yamashita H, Urakawa A, Izumi M, Kugishima Y, et al. The effect of high-intensity breastfeeding on postpartum glucose tolerance in women with recent gestational diabetes. Int Breastfeed J. 2017;12:32.

    Article  PubMed  PubMed Central  Google Scholar 

  25. Sodhi NK, Nelson AL. Prevalence of glucose intolerance and metabolic syndrome within one year following delivery of a pregnancy complicated by gestational diabetes. Contracept Reprod Med. 2018;3:27.

    Article  PubMed  PubMed Central  Google Scholar 

  26. Nicklas JM, Zera CA, Seely EW, Abdul-Rahim ZS, Rudloff ND, Levkoff SE. Identifying postpartum intervention approaches to prevent type 2 diabetes in women with a history of gestational diabetes. BMC Pregnancy Childbirth. 2011;11:23.

    Article  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

The authors thank our laboratory staff for their support.

Funding

This work was supported by the Navamindradhiraj University Research Fund and the Faculty of Medicine Vajira Hospital, Navamindradhiraj University Research Fund. The funders played no role in the study design, data collection, data analysis, data interpretation, decision to publish, or manuscript writing.

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Authors

Contributions

CP, SS, and ST conceived the study. CP wrote the first draft of the manuscript. CP and SS acquired data. CP performed the statistical analyses. CP, SS, and ST interpreted the data and contributed to the revision of the manuscript. CP is the study guarantor, has full access to all data in the study, and takes responsibility for the integrity of the data and accuracy of the data analysis. All authors critically revised the manuscript and approved its final version.

Corresponding author

Correspondence to Chadakarn Phaloprakarn.

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Ethics approval and consent to participate

This study was approved by the Vajira Institution Review Board (approval no. 017/2563). The study was conducted in accordance with the principles of the Declaration of Helsinki. All participants agreed to participate in the study and provided written informed consent.

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Not applicable.

Competing interests

The authors declare no competing interests.

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Phaloprakarn, C., Suthasmalee, S. & Tangjitgamol, S. Impact of postpartum weight change on metabolic syndrome and its components among women with recent gestational diabetes mellitus. Reprod Health 21, 44 (2024). https://doi.org/10.1186/s12978-024-01783-4

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