Metabolic syndrome in Finnish women 7 years after a gestational diabetes prevention trial

Gestational diabetes mellitus and development of intergenerational non-alcoholic fatty liver disease (NAFLD) after delivery: a systematic review and meta-analysis

Background

It is known that gestational diabetes mellitus (GDM)-complicated pregnancies could affect maternal cardiometabolic health after delivery, resulting in hepatic dysfunction and a heightened risk of developing non-alcoholic fatty liver disease (NAFLD). Hence, this study aims to summarise existing literature on the impact of GDM on NAFLD in mothers and investigate the intergenerational impact on NAFLD in offspring.

Methods

Using 4 databases (PubMed, Embase, Web of Science and Scopus) between January 1980 and December 2023, randomized controlled trials and observational studies that assessed the effect of maternal GDM on intergenerational liver outcomes were extracted and analysed using random-effects meta-analysis to investigate the effect of GDM on NAFLD in mothers and offspring. Pooled odds ratio (OR) was calculated using hazards ratio (HR), relative risk (RR), or OR reported from each study, with corresponding 95% confidence intervals (CI), and statistical heterogeneity was assessed with the Cochran Q-test and I2 statistic, with two-sided p values. The study protocol was pre-registered on PROSPERO (CRD42023392428).

Findings

Twenty studies pertaining to mothers and offspring met the inclusion criteria and 12 papers were included further for meta-analysis on intergenerational NAFLD development. Compared with mothers without a history of GDM, mothers with a history of GDM had a 50% increased risk of developing NAFLD (OR 1.50; 95% CI: 1.21-1.87, over a follow-up period of 16 months-25 years. Similarly, compared with offspring born to non-GDM-complicated pregnancies, offspring born to GDM-complicated pregnancies displayed an approximately two-fold elevated risk of NAFLD development (2.14; 1.57-2.92), over a follow-up period of 1-17.8 years.

Interpretation

This systematic review and meta-analysis suggests that both mothers and offspring from GDM-complicated pregnancies exhibit a greater risk to develop NAFLD. These findings underline the importance of early monitoring of liver function and prompt intervention of NAFLD in both generations from GDM-complicated pregnancies.

Funding

No funding was available for this research.

Machine learning analysis for the association between breast feeding and metabolic syndrome in women

This cross-sectional study aimed to develop and validate population-based machine learning models for examining the association between breastfeeding and metabolic syndrome in women. The artificial neural network, the decision tree, logistic regression, the Naïve Bayes, the random forest and the support vector machine were developed and validated to predict metabolic syndrome in women. Data came from 30,204 women, who aged 20 years or more and participated in the Korean National Health and Nutrition Examination Surveys 2010-2019. The dependent variable was metabolic syndrome. The 86 independent variables included demographic/socioeconomic determinants, cardiovascular disease, breastfeeding duration and other medical/obstetric information. The random forest had the best performance in terms of the area under the receiver-operating-characteristic curve, e.g., 90.7%. According to random forest variable importance, the top predictors of metabolic syndrome included body mass index (0.1032), medication for hypertension (0.0552), hypertension (0.0499), cardiovascular disease (0.0453), age (0.0437) and breastfeeding duration (0.0191). Breastfeeding duration is a major predictor of metabolic syndrome for women together with body mass index, diagnosis and medication for hypertension, cardiovascular disease and age.

Genetics and Epigenetics: Implications for the Life Course of Gestational Diabetes

Gestational diabetes (GDM) is one of the most common complications of pregnancy, affecting as many as one in six pregnancies. It is associated with both short- and long-term adverse outcomes for the mother and fetus and has important implications for the life course of affected women. Advances in genetics and epigenetics have not only provided new insight into the pathophysiology of GDM but have also provided new approaches to identify women at high risk for progression to postpartum cardiometabolic disease. GDM and type 2 diabetes share similarities in their pathophysiology, suggesting that they also share similarities in their genetic architecture. Candidate gene and genome-wide association studies have identified susceptibility genes that are shared between GDM and type 2 diabetes. Despite these similarities, a much greater effect size for MTNR1B in GDM compared to type 2 diabetes and association of HKDC1, which encodes a hexokinase, with GDM but not type 2 diabetes suggest some differences in the genetic architecture of GDM. Genetic risk scores have shown some efficacy in identifying women with a history of GDM who will progress to type 2 diabetes. The association of epigenetic changes, including DNA methylation and circulating microRNAs, with GDM has also been examined. Targeted and epigenome-wide approaches have been used to identify DNA methylation in circulating blood cells collected during early, mid-, and late pregnancy that is associated with GDM. DNA methylation in early pregnancy had some ability to identify women who progressed to GDM, while DNA methylation in blood collected at 26-30 weeks gestation improved upon the ability of clinical factors alone to identify women at risk for progression to abnormal glucose tolerance post-partum. Finally, circulating microRNAs and long non-coding RNAs that are present in early or mid-pregnancy and associated with GDM have been identified. MicroRNAs have also proven efficacious in predicting both the development of GDM as well as its long-term cardiometabolic complications. Studies performed to date have demonstrated the potential for genetic and epigenetic technologies to impact clinical care, although much remains to be done.

DNA Methylation in Gestational Diabetes and its Predictive Value for Postpartum Glucose Disturbances

CONTEXT

DNA methylation in the diagnosis of gestational diabetes.

OBJECTIVE

To assess the value of DNA methylation in the diagnosis of gestational diabetes (GDM) and in the prediction of maternal postpartum glucose disturbances.

METHODS

Two-stage observational study performed between July 2006 and December 2010, at University Hospital. Forty-eight randomly selected pregnant women formed the discovery cohort (24 with GDM and 24 controls) and 252 pregnant women (94 with GDM and 158 controls) formed the replication cohort. GDM women were re-evaluated 4 years postpartum. The main outcome measures were GDM, type 2 diabetes or prediabetes at 4 years postpartum.

RESULTS

We identified 3 CpG sites related to LINC00917, TRAPPC9, and LEF1 that were differentially methylated in women with GDM and abnormal glucose tolerance; and sites associated with LINC00917 and TRAPPC9 were independently associated with an abnormal glucose tolerance status 4 years postpartum after controlling for clinical variables. Moreover, the site associated with LINC00917 and the combination of the 3 sites had the highest predictive values.

CONCLUSION

Our results suggest that some of these sites may be implicated in the development of GDM and postpartum abnormal glucose tolerance.

Prolactin and Maternal Metabolism in Women With a Recent GDM Pregnancy and Links to Future T2D: The SWIFT Study

CONTEXT

Prolactin is a multifaceted hormone known to regulate lactation. In women with gestational diabetes mellitus (GDM) history, intensive lactation has been associated with lower relative risk of future type 2 diabetes (T2D). However, the role of prolactin in T2D development and maternal metabolism in women with a recent GDM pregnancy has not been ascertained.

OBJECTIVE

We examined the relationships among prolactin, future T2D risk, and key clinical and metabolic parameters.

METHODS

We utilized a prospective GDM research cohort (the SWIFT study) and followed T2D onset by performing 2-hour 75-g research oral glucose tolerance test (OGTT) at study baseline (6-9 weeks postpartum) and again annually for 2 years, and also by retrieving clinical diagnoses of T2D from 2 years through 10 years of follow up from electronic medical records. Targeted metabolomics and lipidomics were applied on fasting plasma samples collected at study baseline from 2-hour 75-g research OGTTs in a nested case-control study (100 future incident T2D cases vs 100 no T2D controls).

RESULTS

Decreasing prolactin quartiles were associated with increased future T2D risk (adjusted odds ratio 2.48; 95% CI, 0.81-7.58; P = 0.05). In women who maintained normoglycemia during the 10-year follow-up period, higher prolactin at baseline was associated with higher insulin sensitivity (P = 0.038) and HDL-cholesterol (P = 0.01), but lower BMI (P = 0.001) and leptin (P = 0.002). Remarkably, among women who developed future T2D, prolactin was not correlated with a favorable metabolic status (all P > 0.05). Metabolomics and lipidomics showed that lower circulating prolactin strongly correlated with a T2D-high risk lipid profile, with elevated circulating neutral lipids and lower concentrations of specific phospholipids/sphingolipids.

CONCLUSION

In women with recent GDM pregnancy, low circulating prolactin is associated with specific clinical and metabolic parameters and lipid metabolites linked to a high risk of developing T2D.

Effects of Probiotic Supplementation during Pregnancy on the Future Maternal Risk of Metabolic Syndrome

Probiotics are live microorganisms that induce health benefits in the host. Taking probiotics is generally safe and well tolerated by pregnant women and their children. Consumption of probiotics can result in both prophylactic and therapeutic effects. In healthy adult humans, the gut microbiome is stable at the level of the dominant taxa: Bacteroidetes, Firmicutes and Actinobacteria, and has a higher presence of Verrucomicrobia. During pregnancy, an increase in the number of Proteobacteria and Actinobacteria phyla and a decrease in the beneficial species Roseburia intestinalis and Faecalibacterium prausnitzii are observed. Pregnancy is a "window" to the mother's future health. The aim of this paper is to review studies assessing the potentially beneficial effects of probiotics in preventing the development of diseases that appear during pregnancy, which are currently considered as risk factors for the development of metabolic syndrome, and consequently, reducing the risk of developing maternal metabolic syndrome in the future. The use of probiotics in gestational diabetes mellitus, preeclampsia and excessive gestational weight gain is reviewed. Probiotics are a relatively new intervention that can prevent the development of these disorders during pregnancy, and thus, would reduce the risk of metabolic syndrome resulting from these disorders in the mother's future.

Effectiveness of a Nurse-Led Web-Based Health Management in Preventing Women With Gestational Diabetes From Developing Metabolic Syndrome

BACKGROUND

Women with gestational diabetes mellitus (GDM) are more likely to develop metabolic syndrome (MS). However, the effectiveness of web-based health management in preventing women at high risk of GDM from developing MS has rarely been studied.

PURPOSE

The aim of this study was to evaluate the longitudinal effects of nurse-led web-based health management on maternal anthropometric, metabolic measures, and neonatal outcomes.

METHODS

A randomized controlled trial was conducted from February 2017 to February 2018, in accordance with the Consolidated Standards of Reporting Trials guidelines. Data were collected from 112 pregnant women at high risk of GDM who had been screened from 984 potential participants in northern Taiwan. Participants were randomly assigned to the intervention group (n = 56) or the control group (n = 56). The intervention group received a 6-month nurse-led, web-based health management program as well as consultations conducted via the LINE mobile app. Anthropometric and metabolic measures were assessed at baseline (Time 0, prior to 28 weeks of gestation), Time 1 (36-40 weeks of gestation), and Time 2 (6-12 weeks of postpartum). Maternal and neonatal outcomes were assessed at delivery. Clinical trial was registered.

RESULTS

Analysis using the general estimating equation models found that anthropometric and metabolic measures were significantly better in the intervention group than the control group and varied with time. At Time 1, the levels of diastolic pressure (β = -4.981, p = .025) and triglyceride (TG; β = -33.69, p = .020) were significantly lower in the intervention group than the control group, and at Time 2, the incidence of MS in the intervention group was lower than that in the control group (χ2 = 6.022, p = .014). The number of newborns with low birth weight in the intervention group was lower than that in the control group (χ2 = 6.729, p = .012).

CONCLUSION/IMPLICATIONS FOR PRACTICE

This nurse-led, web-based health management was shown to be effective in improving MS outcomes and may play an important role and show feasible clinical value in changing the current pregnancy care model.

Impact of missing outcome data in meta-analyses of lifestyle interventions during pregnancy to reduce postpartum weight retention: An overview of systematic reviews with meta-analyses and additional sensitivity analyses

High risk of bias associated with missing outcome data (MOD) in meta-analyses (MAs) of the effects of lifestyle interventions during pregnancy on postpartum weight retention (PPWR) casts doubt on whether such interventions can be relied upon as truly effective. This systematic overview of three MAs (19 RCTs), each with high MOD rates in the subset of RCTs included, examined how MOD were addressed in the estimation of summary intervention effects. All MAs reported beneficial and statistically significant intervention effects estimated based on complete case analyses, deemed valid if MOD was missing at random (MAR). Therefore, we conducted sensitivity analyses using pattern mixture models and informative missingness parameters (describing how the outcome in the missing participants may be related to the outcome in the completers), to ascertain the robustness of the estimates to reasonable deviations from the MAR assumption. In plausible scenarios where the response in intervention group participants with versus without MOD was worse (by just 0.5 kg), effect estimates were attenuated in all MAs and no longer statistically significant in two MAs. Statistical significance was retained when all 19 RCTs identified across MAs were examined together in a broader meta-analysis: -0.63 kg (95%CI -0.17, -0.08), but the clinical relevancy of effects of this magnitude remains unclear.

Intensive lactation among women with recent gestational diabetes significantly alters the early postpartum circulating lipid profile: the SWIFT study

BACKGROUND

Women with a history of gestational diabetes mellitus (GDM) have a 7-fold higher risk of developing type 2 diabetes (T2D). It is estimated that 20-50% of women with GDM history will progress to T2D within 10 years after delivery. Intensive lactation could be negatively associated with this risk, but the mechanisms behind a protective effect remain unknown.

METHODS

In this study, we utilized a prospective GDM cohort of 1010 women without T2D at 6-9 weeks postpartum (study baseline) and tested for T2D onset up to 8 years post-baseline (n=980). Targeted metabolic profiling was performed on fasting plasma samples collected at both baseline and follow-up (1-2 years post-baseline) during research exams in a subset of 350 women (216 intensive breastfeeding, IBF vs. 134 intensive formula feeding or mixed feeding, IFF/Mixed). The relationship between lactation intensity and circulating metabolites at both baseline and follow-up were evaluated to discover underlying metabolic responses of lactation and to explore the link between these metabolites and T2D risk.

RESULTS

We observed that lactation intensity was strongly associated with decreased glycerolipids (TAGs/DAGs) and increased phospholipids/sphingolipids at baseline. This lipid profile suggested decreased lipogenesis caused by a shift away from the glycerolipid metabolism pathway towards the phospholipid/sphingolipid metabolism pathway as a component of the mechanism underlying the benefits of lactation. Longitudinal analysis demonstrated that this favorable lipid profile was transient and diminished at 1-2 years postpartum, coinciding with the cessation of lactation. Importantly, when stratifying these 350 women by future T2D status during the follow-up (171 future T2D vs. 179 no T2D), we discovered that lactation induced robust lipid changes only in women who did not develop incident T2D. Subsequently, we identified a cluster of metabolites that strongly associated with future T2D risk from which we developed a predictive metabolic signature with a discriminating power (AUC) of 0.78, superior to common clinical variables (i.e., fasting glucose, AUC 0.56 or 2-h glucose, AUC 0.62).

CONCLUSIONS

In this study, we show that intensive lactation significantly alters the circulating lipid profile at early postpartum and that women who do not respond metabolically to lactation are more likely to develop T2D. We also discovered a 10-analyte metabolic signature capable of predicting future onset of T2D in IBF women. Our findings provide novel insight into how lactation affects maternal metabolism and its link to future diabetes onset.

TRIAL REGISTRATION

ClinicalTrials.gov NCT01967030 .

Metabolic syndrome in women with previous gestational diabetes

To evaluate the incidence and timing of the diagnosis of metabolic syndrome in a cohort of Danish women after a pregnancy with gestational diabetes (GDM) to estimate the optimum time for preventative actions in relation to metabolic syndrome (MetS). In this follow-up study, 435 women were included from a consecutive cohort with prior history of GDM. Data on dyslipidemia, hypertension and other cardiovascular disorders (CVD) were extracted from the electronic patient journal. Any antidiabetic, cardiovascular and cholesterol-lowering medicine was ascertained in the national prescription database. Similarly, any blood test taken was evaluated. We defined a patient having MetS if the criteria of the WHO based definition of diabetes or impaired glucose regulation were met. Further, we added as alternative for glucose intolerance, a glycosylated hemoglobin (HbA1c) > 44 mmol/mol or the former level ≥ 6.5%. Further, dyslipidemia, lipid lowering medications, BMI > 30 kg/m² or antihypertensive treatment were used. For MetS outcome, diagnosis or medication for CVD was registered. All women were followed for median 5.7 years (range 0; 9). The incidence of MetS was 28%. Thirteen percent of these qualified already within one year after pregnancy for the diagnosis of MetS. Postpartum MetS was detected after a median of 3 years (range 0; 7 years); further, 36 (8%) had been diagnosed with manifest diabetes after pregnancy. The diagnosis of postpartum MetS was strongly associated with the prevalence of manifest diabetes. Six years after pregnancy the rate of metabolic syndrome was more than tripled (25 vs. 89%, no DM vs manifest DM, RR: 6.7; 95% CI 2.7–17, p < 0.001). At 40 years the MetS rate nearly tripled if manifest DM was diagnosed (26 vs. 78%, no DM vs. manifest DM, RR: 3.3, 95% CI 1.8–6, p < 0.001). We found that GDM and later on manifest DM in women increase the risk of metabolic syndrome. There seems to be a window of opportunity before the early thirties where it would be especially beneficial to begin preventive efforts in women with GDM.

Metabolic syndrome and its associated factors in Ethiopia: A systematic review and meta-analysis

INTRODUCTION

Metabolic syndrome (MetS) is a common complex entity that has emerged as a worldwide epidemic and major public health concern. The incidence of MetS often parallels the incidence of obesity and it is even worst among people living with comorbidities like; HIV/AIDS, hypertension, and mental illness. Therefore, there was an urgent need to summarize the extent and risk factors of MetS in Ethiopia.

METHODOLOGY

This systematic review was conducted according to the PRISMA guideline to investigate the prevalence of MetS and contributing factors. English language-based databases (PubMed, Cumulative Index to Nursing and Allied Health Literature, EMBASE, and Cochrane library) were exhaustively searched to identify studies related to the prevalence of MetS. A random-effects model was employed to estimate the pooled prevalence of MetS, and it was computed using STATA 16.0 software. Heterogeneity analysis was reported using I2.

RESULT

A total of 25 studies with 21,431 study participants were included for this systematic review and meta-analysis. The pooled prevalence of MetS was 30.0% (95% CI: 24.0-36.0%, I2 = 99.19%, p < 0.001) with a high degree of heterogeneity across studies. Subgroup analysis with the target population showed that metabolic syndrome was most prevalent among type II diabetic 56% (95% CI: 47 - 64) and hypertensive patients 44% (95% CI: 35 - 53). Increased age, female gender, being overweight and obese, having a high educational level and income, physical inactivity, and being on treatment of chronic diseases like, diabetes mellitus, hypertension and HIV/AIDS were the most frequently reported risk factors of MetS regardless of the study population.

CONCLUSION

The prevalence of the MetS is high and rising in Ethiopia. Therefore, the preventative strategy should be considered to reduce the risk of morbidity or mortality related to metabolic syndrome.

Long-Term IoT-Based Maternal Monitoring: System Design and Evaluation

Pregnancy is a unique time when many mothers gain awareness of their lifestyle and its impacts on the fetus. High-quality care during pregnancy is needed to identify possible complications early and ensure the mother’s and her unborn baby’s health and well-being. Different studies have thus far proposed maternal health monitoring systems. However, they are designed for a specific health problem or are limited to questionnaires and short-term data collection methods. Moreover, the requirements and challenges have not been evaluated in long-term studies. Maternal health necessitates a comprehensive framework enabling continuous monitoring of pregnant women. In this paper, we present an Internet-of-Things (IoT)-based system to provide ubiquitous maternal health monitoring during pregnancy and postpartum. The system consists of various data collectors to track the mother’s condition, including stress, sleep, and physical activity. We carried out the full system implementation and conducted a real human subject study on pregnant women in Southwestern Finland. We then evaluated the system’s feasibility, energy efficiency, and data reliability. Our results show that the implemented system is feasible in terms of system usage during nine months. We also indicate the smartwatch, used in our study, has acceptable energy efficiency in long-term monitoring and is able to collect reliable photoplethysmography data. Finally, we discuss the integration of the presented system with the current healthcare system.

Increased Visceral Adipose Tissue Without Weight Retention at 59 Weeks Postpartum

OBJECTIVE

This study aimed to determine whether controlling maternal gestational weight gain (GWG) influences adipose tissue distribution at 1 year postpartum.

METHODS

Women with overweight or obesity (n = 210, BMI ≥ 25 or ≥ 30) were randomized to a lifestyle intervention (LI) designed to control GWG or to usual obstetrical care (UC). Measures included anthropometry, whole-body magnetic resonance imaging for visceral (VAT), intermuscular, and subcutaneous adipose tissue, and cardiometabolic risk factors in pregnancy (15 and 35 weeks) and after delivery (15 and 59 weeks).

RESULTS

Baseline (15 weeks) characteristics were similar (mean [SD]: age, 33.8 [4.3] years; weight, 81.9 [13.7] kg; BMI, 30.4 [4.5]; gestational age at randomization, 14.9 [0.8] weeks). LI had less GWG (1.79 kg; P = 0.003) and subcutaneous adipose tissue gain at 35 weeks gestation (P < 0.01). UC postpartum weight (2.92 kg) was higher at 15 weeks but not different from baseline or LI at 59 weeks postpartum. Postpartum VAT increased from baseline in LI by 0.23 kg at 15 weeks and 0.55 kg at 59 weeks; in UC, it increased by 0.34 kg at 15 and 59 weeks. Intermuscular adipose tissue remained elevated in LI (0.22 kg) at 59 weeks. VAT was associated with several cardiometabolic risk factors at 59 weeks.

CONCLUSIONS

Despite no weight retention at 59 weeks postpartum, women had increased VAT by ~30%. Postpartum modifiable behaviors are warranted to lower the risk of VAT retention.

Metabolic syndrome in pregnancy and postpartum: prevalence and associated factors

OBJECTIVE

Evaluate the prevalence of metabolic syndrome (MS) and the main associated maternal factors in women without pre-gestational conditions, in early pregnancy and in the immediate postpartum.

METHODS

Two hundred pregnant women were evaluated at the 16th week of pregnancy, and 187 were reassessed postpartum. MS was diagnosed according to the criteria by the National Cholesterol Education Program Adult Treatment Panel III. In addition to the diagnostic criteria, anthropometric measures, blood pressure, metabolic profile, and visceral and subcutaneous fat thickness (by ultrasonography) were collected from the pregnant woman. The student's t-test was used to compare the prevalence of MS and its components in the 16th week and in the postpartum. Multiple logistic regression was performed to identify the principal factors associated with the syndrome.

RESULTS

The prevalence of the MS was 3.0% in early pregnancy and 9.7% postpartum (p=0.01). Following multiple logistic regression, the prepregnancy body mass index (BMI) (p=0.04) and high-density lipoprotein cholesterol (HDL-c) (p=0.02) remained associated with MS at 16 weeks, and triglyceride levels evaluated in postpartum (p<0.001) with MS in postpartum.

CONCLUSION

The frequency of the MS was high in the immediate postpartum. The factors associated were prepregnancy BMI and HDL-c at the 16th week, as well as triglyceride levels postpartum.

Diabetes after pregnancy prevention trials: Systematic review for core outcome set development

Diabetes prevention intervention studies in women with previous gestational diabetes have increased, but no consensus exists on core outcomes to support comparisons and synthesis of findings. We aimed to systematically catalogue outcomes in diabetes after pregnancy prevention interventions with the goal of developing a core outcome set. Embase, Medline, Cochrane Library, Cochrane Pregnancy and Childbirth Trials Register, and CINAHL were searched from inception to October 2017. Post‐partum lifestyle and diabetes screening intervention studies in women with previous gestational diabetes and/or their families were eligible. No limits were placed on intervention type, duration, or location. Two authors independently screened and performed data extraction on outcomes, measurement tools, and relevant study characteristics. We analysed data from 38 studies (29 randomised controlled trials and 9 pre–post intervention evaluations) comprising 12,509 participants. Most publications (80%) occurred between the years 2012 and 2017. Among 172 outcomes, we identified 36 outcome groups and classified them under three domains: health status (body weight, body composition, diabetes risk, cardiometabolic risk, diabetes development, mental health, pregnancy outcomes, and fitness), health behaviours (dietary, physical activity, diabetes screening, behaviour change, and breastfeeding), and intervention processes (implementation). The health status domain contained the most commonly reported outcomes, but measurement tools were very heterogeneous.

Despite the recent explosion in diabetes after pregnancy prevention studies, large variation in outcomes and measurement methods exists. Research is needed to define a core outcome set to standardise diabetes after pregnancy prevention interventions. The core outcome set should engage a wide group of stakeholders to identify impactful indicators for future trials.

Duration of reproductive years and time since menopause were associated with metabolic syndrome in postmenopausal parous women of Chinese ancestry

OBJECTIVE

Although duration of reproductive years and time since menopause were previously implicated in the metabolic syndrome, the evidence is more limited. Few of the previous studies were able to take into account related reproductive variables simultaneously. The aim of the present study was to explore the influence of these two reproductive factors on the prevalence of metabolic syndrome in postmenopausal parous women from Southeast China.

METHODS

In all, 1,536 postmenopausal parous women were recruited. Self-reported information about reproductive status, including age at menarche, age at menopause, number of children, prepregnancy body weight, and oral contraceptive use, was collected, and duration of reproductive years and time since menopause were calculated. Clinical parameters related with metabolic syndrome were also measured.

RESULTS

Longer duration of reproductive years was significantly related with increased presence of the metabolic syndrome (odds ratio [OR] 1.570, 95% confidence interval [CI] 1.091, 2.259 for tertile 2 group; OR 1.850, 95% CI 1.163, 2.944 for tertile 3 group; P for trend = 0.010). Women with more than 20 years since menopause were more likely to experience metabolic syndrome (OR 2.422, 95% CI 1.109, 5.286, P = 0.026) and elevated blood pressure (OR 3.239, 95% CI 1.406, 7.458, P = 0.006) when compared with those with less than 10 years since menopause.

CONCLUSIONS

Longer duration of reproductive years and time since menopause were associated with higher prevalence of metabolic syndrome in postmenopausal parous women from Southeast China.

Long-term effects of a preconception lifestyle intervention on cardiometabolic health of overweight and obese women

Background

The global prevalence of obesity in women keeps increasing. The preconception period may be a window of opportunity to improve lifestyle, reduce obesity and improve cardiometabolic health. This study assessed the effect of a preconception lifestyle intervention on long-term cardiometabolic health in two randomized controlled trials (RCTs).

Methods

Participants of the LIFEstyle and RADIEL preconception lifestyle intervention studies with a baseline body mass index (BMI) ≥29 kg/m² were eligible for this follow-up study. Both studies randomized between a lifestyle intervention targeting physical activity, diet and behaviour modification or usual care. We assessed cardiometabolic health 6 years after randomization.

Results

In the LIFEstyle study (n = 111) and RADIEL study (n = 39), no statistically significant differences between the intervention and control groups were found for body composition, blood pressure, arterial stiffness, fasting glucose, homeostasis model assessment of insulin resistance, HbA1c, lipids and high sensitive C-reactive protein levels 6 years after randomization. Participants of the LIFEstyle study who successfully lost ≥5% bodyweight or reached a BMI <29 kg/m² during the intervention (n = 22, [44%]) had lower weight (−8.1 kg; 99% CI [−16.6 to −0.9]), BMI (−3.3 kg/m²; [−6.5 to −0.8]), waist circumference (−8.2 cm; [−15.3 to −1.3]), fasting glucose (−0.5 mmol/L; [−1.1 to −0.0]), HbA1c (−4.1 mmol/mol; [−9.1 to −0.8]), and higher HDL-C (0.3 mmol/L; [0.1–0.5]) compared with controls.

Conclusion

We found no evidence of improved cardiometabolic health 6 years after a preconception lifestyle intervention among overweight and obese women in two RCTs. Women who successfully lost weight during the intervention had better cardiometabolic health 6 years later, emphasizing the potential of successful preconception lifestyle improvement.

Do lifestyle interventions during pregnancy have the potential to reduce long-term postpartum weight retention? A systematic review and meta-analysis

Reducing postpartum weight retention is a promising strategy for addressing the rising prevalence of overweight and obesity in women. This systematic review and meta-analysis explored whether lifestyle interventions during pregnancy have the potential to reduce weight retention at 4 months postpartum and beyond. A search of five electronic databases for randomized controlled trials comparing the effect of weight-related lifestyle interventions beginning in pregnancy on postpartum weight retention to standard prenatal care groups was performed. Postpartum weight retention data was synthesized in a random-effects meta-analysis. Data from 14 studies of 7116 participants showed that the intervention group retained statistically significant less weight than the control group (weighted mean difference: -0.73 kg, 95% CI: -1.32 to -0.14, P = 0.015). Subgroup analysis showed this effect to be largest in studies with follow-ups from 4 to 6 months (weighted mean difference: -1.32 kg, 95% CI: -2.11 to -0.53, P = 0.001), but it remained significant until 12 months postpartum (weighted mean difference: -0.68 kg, 95% CI: -1.28 to -0.09, P = 0.023). In studies of women with a body mass index above 25.0 kg/m² , no significant intervention effect was observed. More high-quality studies with a follow-up beyond 12 months postpartum are needed.

The Emerging Role of Biomarkers in the Diagnosis of Gestational Diabetes Mellitus

Gestational diabetes mellitus (GDM) is a common complication of pregnancy; its rising incidence is a result of increased maternal obesity and older maternal age together with altered diagnostic criteria identifying a greater proportion of pregnant women with GDM. Its consequences are far-reaching, associated with poorer maternal and neonatal outcomes compared to non-GDM pregnancies, and GDM has implications for metabolic health in both mother and offspring. Objective markers to identify women at high risk for the development of GDM are useful to target therapy and potentially prevent its development. Established clinical risk factors for GDM include overweight/obesity, age, ethnicity, and family history of diabetes, though they lack specificity for its development. The addition of biomarkers to predictive models of GDM may improve the ability to identify women at risk of GDM prior to its development. These biomarkers reflect the pathophysiologic mechanisms of GDM involving insulin resistance, chronic inflammation, and altered placental function. In addition, the role of epigenetic changes in GDM pathogenesis highlights the complex interplay between genetic and environmental factors, potentially offering further refinement of the prediction of GDM risk. In this review, we will discuss the clinical challenges associated with the diagnosis of GDM and its current pathophysiologic basis, giving rise to potential biomarkers that may aid in its identification. While not yet validated for clinical use, we explore the possible clinical role of biomarkers in the future. We also explore novel diagnostic tools, including high throughput methodologies, that may have potential future application in the identification of women with GDM.