Age at menarche and the risk of gestational diabetes mellitus: a systematic review and meta-analysis

Early age at menarche and the risk of gestational diabetes mellitus: a cohort study

PURPOSE

To evaluate whether there is an association between age at menarche (AAM) and the risk of gestational diabetes mellitus (GDM).

METHODS

A retrospective cohort study was conducted, including 5390 pregnant women who were screened for GDM at Alexandra Hospital in Athens, Greece over a 15-year period (2000-2014). Maternal age, pre-pregnancy body mass index (BMI), height, family history of type 2 diabetes mellitus, parity, educational and smoking status, and AAM were recorded. The results were expressed as odds ratios (OR) with a 95% confidence interval (95% CI).

RESULTS

Pregnant women with GDM experienced earlier menarche compared to normoglycemic women (12.9 ± 1.5 vs 13.1 ± 1.6, p < 0.001, respectively). The OR for a woman with AAM <12 years to develop GDM was 1.08 (95% CI 1.03-1.14), while the OR to be obese was 1.70 (95% CI 1.50-1.90). The multivariate logistic regression analysis showed that AAM is a risk factor for GDM. However, that effect was lost after adjusting for BMI.

CONCLUSION

Early AAM may be associated with an increased risk of GDM. Therefore, it can be used to identify high-risk women and implement preconception interventions for GDM prevention. Future studies should be conducted to confirm these findings.

A retrospective cohort study on the influencing factors for macrosomia in singleton pregnancies

To explore the influencing factors of singletons with macrosomia, and to develop interventions for the prevention of macrosomia. A retrospective cohort study was conducted on 26,379 pregnant women who established the Maternal and Child Health Record and gave birth from January 1, 2019 to December 31, 2019 in a community health service center in Haidian district, Beijing. The study analyzed factors such as maternal age, ethnicity, education level, prepregnancy body mass index (BMI), parity, folic acid supplementation, gestational diabetes mellitus, gestational hyper, hypothyroidism in pregnancy (including subhypothyroidism), hyperthyroidism in pregnancy, and infant gender. Univariate analysis was performed using the χ2 test, and multivariate analysis was performed using non-conditional multivariate logistic regression analysis. Out of 26,379 live births, 5.8% (1522/26,379) were macrosomia and 94.2% (24,857/26,379) were non-macrosomia. Univariate analysis revealed that maternal age, prepregnancy BMI, education level, parity, hypothyroidism during pregnancy, and infant gender were identified as influencing factors for macrosomia (P < .05). Multivariate analysis showed that maternal age ≥ 35 years, education level of high school or below, pre-pregnancy BMI, hypothyroidism, male infant, and parity were all influencing factors for macrosomia (P < .05). Prepregnancy overweight or obesity, male infants, multiparity, and low education level are risk factors for macrosomia. Multiple factors can contribute to macrosomia, and therefore, maternal health care should be strengthened, and early interventions should be taken for the above-mentioned factors in the local area.

Age at Menarche Mediating Visceral Adipose Tissue's Influence on Pre-eclampsia: A Mendelian Randomization Study

CONTEXT

The association between visceral adipose tissue (VAT) and pre-eclampsia (PE) shows inconsistent results and the underlying mediator remains unknown.

OBJECTIVE

We aimed to explore the causal effect of VAT on PE risks and the mediation role of age at menarche (AAM) in explaining this relationship.

METHODS

Summary data for PE were obtained from the FinnGen genome-wide association study (3556 cases and 114 735 controls). For exposure data, 70 genetic variants associated with the predicted VAT in 161 149 European women from UK Biobank were used as instrumental variables. Inverse variance weighted and multiple sensitivity analyses were applied. We also conducted multivariable Mendelian randomization (MR) analyses to test the association between VAT-associated single-nucleotide variations and PE. Next, mediation analyses were performed to study whether the association between VAT and PE was mediated via AAM.

RESULTS

In univariable MR analysis, higher volume of VAT was associated with the advancement of AAM and increased PE risk (beta = -0.33; 95% CI, -0.49 to -0.16 for AAM; odds ratio 1.65, 95% CI, 1.23 to 2.20 for PE). After adjusting for waist circumference, waist to hip ratio, and hip circumference, the multivariable MR results presented the consistent positive causality of VAT on PE. Two-step MR analysis proved an estimated 14.3% of the positive effect of VAT on PE was mediated by AAM.

CONCLUSION

Our findings provided evidence of the causal relationship between VAT and PE and proved VAT could accelerate AAM and then contribute to the risk of incident PE.

Mendelian randomization identifies age at menarche as an independent causal effect factor for gestational diabetes mellitus

AIMS

The relationship between age at menarche (AAM) and gestational diabetes mellitus (GDM) risk is still inconclusive. This Mendelian randomization (MR) analysis was used to assess systematically the causal relationship between AAM and GDM risk in human beings.

MATERIALS AND METHODS

Single-nucleotide polymorphisms associated with AAM, oestradiol levels, sex hormone-binding globulin (SHBG) levels and bioavailable testosterone (BioT) levels were screened via the genome-wide association study enrolling individuals of European descent. Summary-level data for GDM (123 579 individuals) were extracted from the UK Biobank. An inverse-variance-weighted method was used for the primary MR analysis. Sensitivity analyses were examined via MR-Egger regression, heterogeneity tests, pleiotropy tests and leave-one-out tests. The directionality that exposure causes the outcome was verified using the MR-Steiger test.

RESULTS

Genetically predicted early AAM was found to have a causal positive association with a higher risk of GDM (odds ratio = 0.798, 95% confidence interval = 0.649-0.980, p = .031). In the multivariable MR analysis adjusted for oestradiol, SHBG and BioT levels, the causal association between AAM and GDM risk remained (odds ratio = 0.651, 95% confidence interval = 0.481-0.881, p = .006). A 1-SD increase in SHBG or BioT levels was significantly associated with a 41.4% decrease or 20.8% increase in the overall GDM risk (p = 3.71E-05 and .040), respectively. However, after controlling for AAM, oestradiol levels and BioT levels by multivariable MR analysis, there was no direct causal effect of SHBG levels on GDM risk (p = .084). Similarly, after adjusting for AAM, oestradiol levels and SHBG levels by multivariable MR analysis, there was no direct causal effect of BioT levels on the risk of GDM (p = .533). In addition, no direct causal association was identified between oestradiol levels and GDM risk in univariable MR analysis or multivariable MR analysis.

CONCLUSION

Genetic variants predisposing individuals to early AAM were independently associated with higher GDM risk. Further research is required to understand the mechanisms underlying this putative causative association. In addition, AAM may be helpful in clinical practice to identify women at risk for GDM; pregnant women who are young for menarche may need to take precautions before GDM develops.

Long-term health outcomes of early menarche in women: an umbrella review

BACKGROUND

There is limited comprehensive evidence on the potential association between early menarche and subsequent health outcomes.

AIM

To evaluate the existing evidence for the association of early menarche with later health outcomes and assesse the strength and validity of the evidence for these associations.

DESIGN

Umbrella review.

METHODS

We searched PubMed, Web of Science, Embase, CINAHL, Cochrane Database of Systematic Reviews and Google Scholar, and manually screened retrieved references to find systematic reviews and meta-analyses from inception to July 2021. Early menarche was defined by taking into account ethnicity and birth year, and the outcomes were long-term consequences in adulthood.

RESULTS

Thirteen reviews encompassing 283 original articles and over 6.8 million participants from 39 countries across 5 continents were included. In categorical outcomes, early menarche was associated with metabolic syndrome (n = 37 543 pooled adjusted relative risk [aRR] 1.56, 95% confidence interval (CI) 1.33, 1.83; high certainty [Hi]), endometrial cancer (n = 874 188, aRR 1.40, 95% CI 1.17, 1.68; Hi), type 2 diabetes mellitus/impaired glucose tolerance (n = 1 185 444, aRR 1.30, 95% CI 1.19, 1.42; Hi), breast cancer (n = 103 574, aRR 1.19, 95% CI 1.06, 1.33; Hi), death from all causes (n = 152 747, aRR 1.11, 95% CI 1.03, 1.19; Hi), obesity (n = 54 006, aRR 1.68, 95% CI 1.53, 1.84; moderate certainty [Mod]), gestational diabetes mellitus (n = 48 535, aRR 1.32, 95% CI 1.09, 1.58; Mod), hypertension (n = 1 682 689, aRR 1.24, 95% CI 1.20, 1.29; Mod), endometriosis (n = 885 390, aRR 1.22, 95% CI 1.09, 1.37; Mod), ovarian cancer (n = 1 022 451, aRR 1.17, 95% CI 1.04, 1.31; Mod) and asthma (n = 22 859, aRR 1.31, 95% CI 1.09, 1.57; low certainty [Lo]). For continuous outcomes, early menarche was associated with increased body mass index (BMI) in adults ≥40 years of age (n = 121 943, adjusted pooled standardized mean difference [aSMD] 0.30, 95% CI 0.28, 0.32; Mod), BMI in adults <40 years of age (n = 124 728, aSMD 0.39, 95% CI 0.36, 0.43; Mod), serum fasting insulin level (n = 17 020, aSMD 0.52, 95% CI 0.48, 0.57; Mod) and homeostatic model assessment of insulin resistance (n = 7925, aSMD 0.27, 95% CI 0.19, 0.35; Mod).

CONCLUSION

We found varied levels of evidence for the association between early menarche and the development of subsequent health problems. Our results recommend that physicians should pay attention to these associations, as early menarche can be a potential indicator of metabolic disorders and female-specific cancer and cause death in women.

Age at menarche: risk factor for gestational diabetes

This study examines the relationship between the age at menarche and gestational diabetes mellitus (GDM). This retrospective study included subjects who were diagnosed with GDM at a pregnancy polyclinic in Kocaeli, Turkey between 2014 and 2018. The mean ages at menarche were 12.6 and 13.03 years in the GDM group and control group, respectively. The analysis results showed that pre-pregnancy cycle duration, age at menarche and pre-pregnancy BMI are statistically significant in terms of the development of gestational diabetes. (p < .05).In our study showed that the risk of GDM was found to be 2.3 times higher in pregnant women with a menarche age of <12 years. If the pre-pregnancy BMI value is more than 25 kg/cm², the risk of GDM was found to be approximately 2 times higher. The study indicated that age at menarche, cycle duration, and BMI were risk factors for GDM. IMPACT STATEMENTWhat is already known on this subject? GDM has a lasting health impact on both the mother and the foetus. While several risk factors have previously been identified for GDM such as family history, obesity, advanced maternal age, significant gaps remain in our understanding of the risk factor and pathogenesis. Recent studies suggested that earlier menarche was significantly associated with an increased risk of GDM.What do the results of this study add? There might be ethnic differences on the relationship between the GDM and menarche age. There is no study examining the relationship between the age of menarche and GDM in Turkey. In presented study, we determined the risk factors of GDM including the age of menarche, cycle duration and BMI.What are the implications of these findings for clinical practice and / or further research? Therefore, a comprehensive evaluation of the menstrual history by healthcare professionals is important for future pregnancy risks. It is important to understand risk factors for GDM and to establish preventive strategies among high-risk populations. In addition, this study will shed light on future epidemiological and cohort studies.

Gestational Diabetes and Risk Assessment of Adverse Perinatal Outcomes and Newborns Early Motoric Development

Background and Objectives: The aim of this study was to analyze the presence of gestational diabetes mellitus (GDM) on maternal and fetal perinatal parameters, as well to evaluate the influence of GDM on neonatal early motoric development. Materials and Methods: In this prospective study, we evaluated 203 eligible participants that were admitted to obstetrics department for a labor. GDM was assessed by evaluation of maternal parameters, fetal parameters, as well its impact on infants early motoric development (Alberta Infant Motor Scale-AIMS). Results: Presence of GDM was significantly positively associated with: pre-pregnancy weight, obesity degree, weight at delivery, gestational weight gain (GWG), body mass index (BMI) at delivery, GWG and increased pre-pregnancy BMI, glucose levels in mother's venous blood after the delivery, positive family history for cardiovascular disease, pregnancy-related hypertension, congenital thrombophilia, drug use in pregnancy, large for gestational age (LGA), mode of delivery (Cesarean section and instrumental delivery). Likewise, GDM association was detected for tested ultrasound parameters (biparietal diameter (BPD), head circumference (HC), abdominal circumference (AC), femoral length (FL)), length at birth, birth weight, newborn's head circumference, newborn's chest circumference, AIMS supination and pronation at three months, AIMS supination, pronation, sitting and standing at six months. Only Amniotic Fluid Index and AIMS supination at three months of infant's age remained significantly associated in multivariate regression model. Conclusions: The presence of significant positive association of numerous tested parameters in our study on perinatal outcomes and early motoric development, points to the necessity of establishing appropriate clinical decision-making strategies for all pregnant woman at risk and emphasize the importance of providing adequate glycaemia control options and further regular follow ups during the pregnancy.

Identifying environmental exposure profiles associated with timing of menarche: A two-step machine learning approach to examine multiple environmental exposures

BACKGROUND

Variation in the timing of menarche has been linked with adverse health outcomes in later life. There is evidence that exposure to hormonally active agents (or endocrine disrupting chemicals; EDCs) during childhood may play a role in accelerating or delaying menarche. The goal of this study was to generate hypotheses on the relationship between exposure to multiple EDCs and timing of menarche by applying a two-stage machine learning approach.

METHODS

We used data from the National Health and Nutrition Examination Survey (NHANES) for years 2005-2008. Data were analyzed for 229 female participants 12-16 years of age who had blood and urine biomarker measures of 41 environmental exposures, all with >70% above limit of detection, in seven classes of chemicals. We modeled risk for earlier menarche (<12 years of age vs older) with exposure biomarkers. We applied a two-stage approach consisting of a random forest (RF) to identify important exposure combinations associated with timing of menarche followed by multivariable modified Poisson regression to quantify associations between exposure profiles ("combinations") and timing of menarche.

RESULTS

RF identified urinary concentrations of monoethylhexyl phthalate (MEHP) as the most important feature in partitioning girls into homogenous subgroups followed by bisphenol A (BPA) and 2,4-dichlorophenol (2,4-DCP). In this first stage, we identified 11 distinct exposure biomarker profiles, containing five different classes of EDCs associated with earlier menarche. MEHP appeared in all 11 exposure biomarker profiles and phenols appeared in five. Using these profiles in the second-stage of analysis, we found a relationship between lower MEHP and earlier menarche (MEHP ≤ 2.36 ng/mL vs >2.36 ng/mL: adjusted PR = 1.36, 95% CI: 1.02, 1.80). Combinations of lower MEHP with benzophenone-3, 2,4-DCP, and BPA had similar associations with earlier menarche, though slightly weaker in those smaller subgroups. For girls not having lower MEHP, exposure profiles included other biomarkers (BPA, enterodiol, monobenzyl phthalate, triclosan, and 1-hydroxypyrene); these showed largely null associations in the second-stage analysis. Adjustment for covariates did not materially change the estimates or CIs of these models. We observed weak or null effect estimates for some exposure biomarker profiles and relevant profiles consisted of no more than two EDCs, possibly due to small sample sizes in subgroups.

CONCLUSION

A two-stage approach incorporating machine learning was able to identify interpretable combinations of biomarkers in relation to timing of menarche; these should be further explored in prospective studies. Machine learning methods can serve as a valuable tool to identify patterns within data and generate hypotheses that can be investigated within future, targeted analyses.

Longitudinal 15-year follow-up of women with former early puberty: abnormal metabolic profiles not associated with earlier age at onset of puberty, but associated with obesity

BACKGROUND

In 2011, we described 104 girls who were diagnosed as early puberty (EP) during 2003-2005. In 2019-2020, the former EP women had been followed up 14 years after attaining their final height.

OBJECTIVE

To determine the reproductive function and metabolic profiles of former EP women.

STUDY DESIGN

Fifty-seven former EP women were evaluated for reproductive function and examined for health status. Blood samples were obtained for metabolic profiles of glucose, lipids and insulin, and testosterone levels.

RESULTS

In 2020, the average age of the study women was 22.9 ± 1.7 years. The average height was 156.7 ± 5.6 cm. The average weight had increased from 52.5 ± 7.8 kg in 2011 to 58.5 ± 11.1 kg in 2020 and average body mass index (BMI) from 21.4 ± 2.9 to 23.8 ± 4.0 kg/m². Obesity (BMI>25 kg/m²) was found in 8.8% (five participants) in 2011 and had increased to 22.8% (13 participants) in 2020. Most participants (79%) had regular menstrual cycle. Of the 17 married women, 4 (23.5%) had 1-2 children. Dividing the participants into obese and nonobese groups, the average fasting plasma glucose, lipid profiles, and testosterone levels were similar in both groups. However, the average systolic blood pressure and the serum insulin levels and HOMA-IR assessments were significantly higher in the obese group than in the nonobese group.

CONCLUSION

The former EP women had normal menstruation and reproductive function. The former EP women with average BMI at the follow-up had normal metabolic profiles while those who later became obese had significantly higher systolic blood pressure, serum insulin, and HOMA-IR assessments.

Risk Factors Screening for Gestational Diabetes Mellitus Heterogeneity in Chinese Pregnant Women: A Case-Control Study

PURPOSE

To study the risk factors of gestational diabetes mellitus (GDM) heterogeneity, and to evaluate the correlation between the risk factors and obesity.

METHODS

We performed a case-control study of 452 women with GDM and 516 women with normal glucose tolerance (NGT) at the first and second trimester. We defined GDM women as GDM-resistance subtype, GDM-dysfunction subtype, and GDM-mixed subtype, according to their simultaneous insulin-release test with predominant insulin-sensitivity defect, insulin-secretion defect, or both defects.

RESULTS

We found that higher maternal age, family history of diabetes, the elevated level of fasting blood glucose in the first trimester (≥5.1 mmol/L) were risk factors of all GDM subtypes. Pre-pregnancy overweight/obesity and the increased gestational weight gain (GWG) in the first-trimester are risk factors of the GDM-resistance subtype. Indicators including younger age at first menstruation, the elevated levels of alanine aminotransferase (ALT), total bile acid (TBA), triglyceride (TG), and the decreased level of high-density lipoprotein cholesterol (HDL-C) are risk factors of the GDM-resistance subtype. However, the associations between those risk factors and GDM-resistance subtype attenuated after adjusted by pre-pregnancy body mass index (pre-BMI) and gestational weight gain (GWG) in the first trimester. Nonalcoholic fatty liver disease (NAFLD) and the improved level of TG are independent risk factors for the GDM-resistance subtype and the GDM-mixed subtype, respectively.

CONCLUSION

Women with GDM exhibited heterogeneity based on glycemic physiology and their risk factors are not all the same. Some obesity-related risk factors are specific to the GDM-resistance subtype, which are mediated by pre-pregnancy overweight/obesity and the elevated GWG the first-trimester.

Relationship between age at menarche and chromosome numerical abnormalities in chorionic villus among missed abortions: A cross-sectional study of 459 women in China

AIMS

To assess the relationship between age at menarche and the numerical abnormalities of chorionic villi chromosomes in patients with missed abortion.

METHODS

Unexplained miscarriage patients were admitted to an outpatient clinic in Tianjin Central Hospital of Gynecology Obstetrics, China. Embryonic villi tissues were collected aseptically after curettage. Chromosome analysis was performed subsequently using multiplex ligation-dependent probe amplification method.

RESULTS

Among 459 cases of missed abortion, chromosome numerical abnormalities were found in 231 cases (50.33%). Autosomal trisomy occurs most frequently, with 16-trisomy being most common. Patients (age more than 35 years old) had more frequent miscarriages compared with those who were less than 35 years old. However, there was no statistically significant difference in chromosome numerical abnormalities. In addition, compared with patients less than 30 years old, women with age ≥ 30 years old had higher abortions frequency (P = 0.002), and the proportion of chromosome numeric abnormalities increased (P = 0.000). The number of patients with abnormal chromosomes is higher among patients whose age of menarche are less than 12 years old than that of patients whose age of menarche was over 12 years old (P = 0.003).

CONCLUSION

Chromosome numerical abnormalities are important cause of missed abortion. The incidence of chromosome numeric abnormalities increases among patients ≥30 years old. Besides, age of menarche is an important risk factor for chromosome numerical abnormalities.

Age at menarche and clinical outcomes following medically assisted reproduction (MAR): a cohort study

Medically assisted reproduction (MAR) technologies have advanced rapidly, but in contrast to the specificity of modern approaches, they provide limited effectiveness in the management of the infertile couple. The purpose of this study was to assess the possible relationship between age at menarche and MAR outcomes of clinical pregnancy, live birth and the adverse incident of miscarriage, and to determine the offspring sex ratio according to age at menarche. In a cohort of 254 infertile couples who underwent 426 IVF/ICSI cycles, statistical analysis was performed by applying Student's t-test, chi-square test, and logistic regression models, adequately in the respective parameters and outcomes. The results indicated a strong association of age at menarche with the outcomes of clinical pregnancy (p = .0007) and live birth (p < .0001), especially by applying a threshold of 12 years in the first occurrence of menstruation (p = .0019 for clinical pregnancy, p < .0001 for live birth), also demonstrating a negative effect for earlier menarche that acts in parallel with the increasing age of the woman. Calculation of sex ratio demonstrated a tendency towards female offspring close to the age at menarche of 12 years. Age at menarche could serve as a surrogate parameter for reproductive potential towards personalized management of infertility.

Age at menarche and risk of gestational diabetes mellitus: a population-based study in Xiamen, China

Background

It has been reported that earlier age at menarche is associated with a higher risk for type 2 diabetes mellitus. However, the relationship between age at menarche and gestational diabetes mellitus is inconsistent across studies. We hypothesized that an earlier age at menarche would predict the gestational diabetes mellitus risk.

Methods

This was a population-based, retrospective cohort study of 70,041 women aged 18 to 53 years old, conducted between 2011 and 2018. The subjects were recruited from the Medical Birth Registry in Xiamen, China. Age at menarche was categorized as 8–12, 13, 14, 15, 16–19 years old. Logistic regression analysis and spline analysis was used to assess the risk of the menarche age group for gestational diabetes mellitus. Linear regression analysis was performed to evaluate independent associations between age at menarche and fasting plasma glucose and blood glucose 1 hour and 2 hours after a 75-g of glucose load between 24 and 28 weeks’ gestation.

Results

The overall prevalence of GDM was 17.6%. After adjustment for family history of diabetes, earlier age at menarche (8–12, and 13 years old) was associated with increased odds for GDM (OR, 1.08; 95% CI, 1.02–1.15, and OR, 1.07; 95% CI, 1.03–1.14, respectively) compared with average age at menarche (14 years old). With further adjustment for pre-pregnancy body mass index, blood pressure, educational level, age at delivery, and hepatitis B surface antigen status, this association was attenuated (OR, 0.93, and OR, 1.02, respectively). Multivariable-adjusted spline regression models showed a linear dose-response association between age at menarche and GDM (P for nonlinearity, 0.203; P for linearity, 0.006). On linear regression analysis, earlier age at menarche was significantly associated with increased blood glucose one and 2 hours after a glucose load but not with the fasting plasma glucose.

Conclusions

As expected, early age at menarche was found to be associated with an increased risk of gestational diabetes mellitus. However, this association may be mediated by potential confounding factors other than age. An additional finding was that earlier menarche was significantly related with elevated pregnancy glucose concentrations after a glucose load.

Age at menarche and the future risk of gestational diabetes: a systematic review and dose response meta-analysis

Published studies show an inconsistent association between age at menarche and the subsequent risk of developing gestational diabetes mellitus when pregnant. This systematic review and meta-analysis was performed to clarify any trends in this association in published observational population studies. We searched online databases for relevant studies, entered into them up until June 21st 2017. Five eligible studies were found and a pooled random effects dose response meta-analysis of results from these was conducted. This included coverage of 58,133 pregnancies, from which 3,035 women developed gestational diabetes. There was evidence of a non-linear association between age at menarche and gestational diabetes (overall p = 1.4 × 10^-8; p for non-linearity = 2.4 × 10^-4), along with evidence of relatively low heterogeneity (I² = 25.5%). The largest predicted risk of gestational diabetes was associated with having a low age at menarche; the mean (95% confidence interval) risk relative to that associated with menarche at age 13 years being: 9 years 2.0 (1.6, 2.4), 10 years 1.6 (1.4, 1.9), 11 years 1.3 (1.2, 1.4), 12 years 1.1 (1.1, 1.1), 13 years was the reference, 14 years 1.0 (1.0, 1.0), 15 years 1.1 (0.9, 1.2), 16 years 1.1 (0.9, 1.4). There was evidence of potential publication bias, such that the maximal true relative risk of gestational diabetes, associated with an age at menarche of 9 years, may be closer to 1.6 than 2. Nevertheless, the curvilinear relationship between age at menarche and the future risk of gestational diabetes in pregnancy appears robust.

The association between age at menarche and later risk of gestational diabetes is mediated by insulin resistance

AIMS

Associations have been reported between age at menarche and the later risk of gestational diabetes. However, it is not known whether these associations reflect differences in insulin sensitivity and/or pancreatic β-cell function in pregnancy.

METHODS

We examined this question in women enrolled in the prospective Cambridge Baby Growth Study who recalled their age at menarche in questionnaires during pregnancy. Polynomial logistic and linear regression models were used to relate menarche timing to the risk of gestational diabetes, both unadjusted and adjusted for the Homeostasis Model Assessments of insulin resistance (HOMA IR) and pancreatic β-cell function (HOMA B) at week 28 of pregnancy.

RESULTS

Age at menarche showed a U-shaped association with gestational diabetes risk (linear term: p = 9.5 × 10^-4; quadratic term: p = 1.0 × 10^-3; n = 889; overall model p = 8.1 × 10^-3). Age at menarche showed a negative linear association with insulin resistance (HOMA IR: β = -0.13, p = 5.2 × 10^-4, n = 771), which explained the relationship between age at menarche and gestational diabetes risk (adjusted linear term going from p = 0.03-0.08; adjusted quadratic term going from p = 0.04-0.08; n = 771). Age at menarche also showed a negative linear association with β-cell function (HOMA B: β = -0.11, p = 2.8 × 10^-3, n = 771) but this did not attenuate the relationship between age at menarche and gestational diabetes (adjusted linear term p = 0.02; adjusted quadratic term p = 0.03, n = 771).

CONCLUSIONS

These results suggest that the associations between age at menarche and risk of gestational diabetes and raised pregnancy glucose concentrations may be mediated by insulin resistance.