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

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.

Early age at menarche is associated with an increased risk of preeclampsia and adverse neonatal outcomes: a 6‑year retrospective study

PURPOSE

Preeclampsia affects between 2 to 8% of pregnancies worldwide and is associated with significant adverse outcomes for both mothers and their offspring. The present study aims to investigate whether there is a correlation between early age at menarche and an increased risk of developing preeclampsia and experiencing adverse neonatal outcomes.

METHODS

The study involved a review of medical records of 4227 pregnant women who gave birth at The First Affiliated Hospital of Chengdu Medical College between January 2017 and December 2022. The collected data included demographic characteristics, clinical manifestations of preeclampsia, laboratory indicators, gestational complications, and neonatal outcomes. Pregnant women were categorized into four groups based on their age at menarche (≤ 12, 13, 14, and ≥ 15 years). Logistic regression analysis was conducted to calculate the odds ratios (ORs) and 95% confidence intervals (CIs) for the association between different menarche age groups and the risk of preeclampsia and adverse neonatal outcomes.

RESULTS

Pregnant women who had an age at menarche of ≤ 12 years had a higher risk of preeclampsia than women who had their menarche at 13, 14, and ≥ 15 years of age, with adjusted ORs (95% CIs) for preeclampsia of 1.00 (reference), 0.78 (0.45-0.91), 0.76 (0.59-0.88), and 0.73 (0.56-0.94), respectively. The predictive efficacy of age at menarche for preeclampsia was assessed with a sensitivity and specificity of 85.2% and 76.4%, respectively, and an AUC of 0.82. Moreover, infants born to women with an age at menarche of ≤ 12 years had a higher risk of adverse neonatal outcomes, including small for gestational age, preterm birth, low birth weight, neonatal respiratory distress syndrome, and neonatal intensive care unit admission.

CONCLUSION

Our findings suggest that an early age at menarche is associated with an increased risk of preeclampsia and adverse neonatal outcomes. This information could be useful for obstetricians to identify women at risk for preeclampsia early on and implement timely interventions to reduce the incidence of preeclampsia and associated adverse neonatal outcomes.

Growth in Infancy and Childhood and Age at Menarche in Five Low- or Middle-Income Countries: Consortium of Health Orientated Research in Transitional Societies (COHORTS)

BACKGROUND

Earlier age at menarche is associated with behavioral and noncommunicable disease risks. The influence of birth weight (BW) (intrauterine) and postnatal growth on age at menarche is not well studied in low- and middle-income countries (LMICs).

OBJECTIVE

Therefore, we investigated these associations in 5 LMIC birth cohorts.

METHODS

We analyzed data from Brazil, Guatemala, India, the Philippines, and South Africa (n = 3983). We derived stunting (< -2 SD scores) at 24 mo using the WHO child growth standards. We generated interaction terms with categorized BW and conditional weight (lighter < 0 or heavier ≥ 0), and height (shorter < 0 or taller ≥ 0) z-scores. We categorized early-, modal-, and late-onset menarche and used multilevel ordinal regression. We used multilevel linear regression on continuous age at menarche.

RESULTS

Mean age at menarche was 12.8 y (95% CI: 12.7 12.9). BW was not associated with age at menarche. Conditional height at 24 mo and mid-childhood (OR: 1.35; 95% CI: 1.27, 1.44 and 1.32; 1.25, 1.41, respectively) and conditional weight at 24 mo and mid-childhood (OR: 1.15; 1.08, 1.22 and 1.18; 1.11, 1.25, respectively) were associated with increased likelihood of early-onset menarche. Being heavier at birth and taller at 24 mo was associated with a 4-mo (95% CI: 0.8, 7.6) earlier age at menarche than being lighter at birth and shorter at 24 mo. Being heavier at birth but lighter in mid-childhood was associated with a 3-mo (95% CI: 0.8, 4.8) later age at menarche than being lighter at birth and mid-childhood. Age at menarche was 7 mo later in stunted than nonstunted girls.

CONCLUSION

Age at menarche is inversely related to relative weight gain but also to rapid linear growth among those born shorter but remained stunted, and those born taller and grew excessively. These findings do not deter the global health goal to reduce growth faltering but emphasize the potential adverse effects of an obesogenic environment on adolescent development.

Development and validation of risk prediction models for large for gestational age infants using logistic regression and two machine learning algorithms

BACKGROUND

Large for gestational age (LGA) is one of the adverse outcomes during pregnancy that endangers the life and health of mothers and offspring. We aimed to establish prediction models for LGA at late pregnancy.

METHODS

Data were obtained from an established Chinese pregnant women cohort of 1285 pregnant women. LGA was diagnosed as >90th percentile of birth weight distribution of Chinese corresponding to gestational age of the same-sex newborns. Women with gestational diabetes mellitus (GDM) were classified into three subtypes according to the indexes of insulin sensitivity and insulin secretion. Models were established by logistic regression and decision tree/random forest algorithms, and validated by the data.

RESULTS

A total of 139 newborns were diagnosed as LGA after birth. The area under the curve (AUC) for the training set is 0.760 (95% confidence interval [CI] 0.706-0.815), and 0.748 (95% CI 0.659-0.837) for the internal validation set of the logistic regression model, which consisted of eight commonly used clinical indicators (including lipid profile) and GDM subtypes. For the prediction models established by the two machine learning algorithms, which included all the variables, the training set and the internal validation set had AUCs of 0.813 (95% CI 0.786-0.839) and 0.779 (95% CI 0.735-0.824) for the decision tree model, and 0.854 (95% CI 0.831-0.877) and 0.808 (95% CI 0.766-0.850) for the random forest model.

CONCLUSION

We established and validated three LGA risk prediction models to screen out the pregnant women with high risk of LGA at the early stage of the third trimester, which showed good prediction power and could guide early prevention strategies.

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.

Development and Validation of Risk Prediction Models for Gestational Diabetes Mellitus Using Four Different Methods

Gestational diabetes mellitus (GDM), a common perinatal disease, is related to increased risks of maternal and neonatal adverse perinatal outcomes. We aimed to establish GDM risk prediction models that can be widely used in the first trimester using four different methods, including a score-scaled model derived from a meta-analysis using 42 studies, a logistic regression model, and two machine learning models (decision tree and random forest algorithms). The score-scaled model (seven variables) was established via a meta-analysis and a stratified cohort of 1075 Chinese pregnant women from the Northwest Women's and Children's Hospital (NWCH) and showed an area under the curve (AUC) of 0.772. The logistic regression model (seven variables) was established and validated using the above cohort and showed AUCs of 0.799 and 0.834 for the training and validation sets, respectively. Another two models were established using the decision tree (DT) and random forest (RF) algorithms and showed corresponding AUCs of 0.825 and 0.823 for the training set, and 0.816 and 0.827 for the validation set. The validation of the developed models suggested good performance in a cohort derived from another period. The score-scaled GDM prediction model, the logistic regression GDM prediction model, and the two machine learning GDM prediction models could be employed to identify pregnant women with a high risk of GDM using common clinical indicators, and interventions can be sought promptly.

Association between Age at Menarche and Metabolic Syndrome in Southwest Iran: A Population-Based Case-Control Study

BACKGROUND

Age at menarche affects women's health outcomes and could be a risk factor for some diseases, such as metabolic syndrome (MetS). We assessed the association between age at menarche and MetS components in women aged 35-70 in Hoveyzeh, southwest Iran.

STUDY DESIGN

A case-control study.

METHODS

This case-control study was conducted on 5830 women aged 35-70 years in the Hoveyzeh cohort study (HCS), a part of the PERSIAN cohort study, from 2016-2018. The case group included women with MetS, while the controls were women without MetS. The MetS is determined based on standard NCEP-ATP III criteria. Data from demographic, socioeconomic, and reproductive history were gathered face-to-face through trained interviews. Moreover, laboratory, anthropometrics, and blood pressure measurements were assayed for participants. Multiple logistic regression was used to estimate the association between age at menarche and MetS, with adjustment for potential confounding variables.

RESULTS

The mean age at menarche was 12.60 ± 1.76 years old. Urban and rural women differed in age at menarche (12.58 ± 1.71 and 12.63 ± 1.83 years, respectively). The study revealed a statistically significant relationship between MetS and menarche age. The odds of developing MetS were 14% higher in women with menstrual age ≤ 11 years than in other groups.

CONCLUSION

As evidenced by the results of this study, the odds of having MetS were higher in women whose menarche age was ≤ 11 years. Furthermore, the association between MetS components and age groups at menarche was statistically significant.

A cross-sectional study to develop an early risk prediction tool for gestational diabetes mellitus for antenatal women diagnosed with this condition based on their characteristics and past obstetric history

Background

In India, the prevalence of gestational diabetes mellitus (GDM) is estimated to be 10%-14.3%, which is higher than in Western countries. Out of 10 pregnancies, one is associated with diabetes, and 90% of them are GDM. GDM influences not only maternal complications but also neonatal complications. Moreover, women with GDM and their children are at increased risk of developing type-2 diabetes later.

Method and Material

A cross-sectional study was conducted on 220 patients to develop an early risk prediction tool for GDM for antenatal women diagnosed with this condition based on their characteristics and past obstetric history.

Results

The mean age (in years) of patients in the study was 27.69 ± 5.07. One hundred and twenty-six patients (57.27%) had a family history of DM in their first relatives. Eighty-three (58.86%) patients had a history of complications in a previous pregnancy.

Conclusion

The early risk predictor tool with age, prepregnancy, body mass index (BMI), family history of DM, gravidity, past history of menstrual cycle, and complications in a previous pregnancy was easy to operate, and all predictors were easily obtained in the first trimester in primary healthcare centers.

Steroids, steroid associated substances and gestational diabetes mellitus

As gestational diabetes mellitus (GDM) is both a frequent and serious complication, steroid levels in pregnancy are extremely elevated and their role in pregnancy is crucial, this review focuses on the role of steroids and related substances in the GDM pathophysiology. Low SHBG levels are associated with insulin resistance and hyperinsulinemia, while also predicting a predisposition to GDM. Other relevant agents are placental hormones such as kisspeptin and CRH, playing also an important role beyond pregnancy, but which are synthesized here in smaller amounts in the hypothalamus. These hormones affect both the course of pregnancy as well as the synthesis of pregnancy steroids and may also be involved in the GDM pathophysiology. Steroids, whose biosynthesis is mainly provided by the fetal adrenal glands, placenta, maternal adrenal glands, and both maternal and fetal livers, are also synthesized in limited amounts directly in the pancreas and may influence the development of GDM. These substances involve the sulfated Δ5 steroids primarily acting via modulating different ion channels and influencing the development of GDM in different directions, mostly diabetogenic progesterone and predominantly anti-diabetic estradiol acting both in genomic and non-genomic way, androgens associated with IR and hyperinsulinemia, neuroactive steroids affecting the pituitary functioning, and cortisol whose production is stimulated by CRH but which suppresses its pro-inflammatory effects. Due to the complex actions of steroids, studies assessing their predominant effect and studies assessing their predictive values for estimating predisposition to GDM are needed.

Age at menarche and risk of adverse obstetric outcomes during the first childbirth in Japan: The Japan Environment and Children's Study

AIM

Age at menarche is used as a risk indicator of gestational diabetes mellitus, preterm birth, and fetal growth. However, little is known regarding the age impact on obstetric outcomes among nulliparous women. This study investigated whether menarche age was correlated with obstetric outcomes among nulliparous women.

METHODS

We analyzed the data obtained for 37 645 singleton pregnancies between 2011 and 2014 in the Japan Environment and Children's Study. Age at menarche was categorized into the ≤9-, 10-, 11-, 12-, 13-, 14-, and ≥15-year-old groups (n = 363, 3155, 8390, 11 164, 6713, 5446, and 2414, respectively). We calculated the relative risk for cases of preterm birth <37 weeks, low birthweight <2500 g, small for gestational age, early and late-onset hypertension disorders of pregnancy, and early- and late-diagnosed (diagnosed < or ≧ 24 weeks) gestational diabetes mellitus using a reference of 12 years at menarche.

RESULTS

Women with an age at menarche ≤9 years showed an increased incidence of developing early-diagnosed gestational diabetes mellitus (relative risk: 2.42; 95% confidence interval: 1.05-5.60). A high body mass index before pregnancy increased the risk of developing gestational diabetes mellitus.

CONCLUSIONS

Age at menarche helped in assessing the risk of early-diagnosed gestational diabetes mellitus among nulliparous women. Future studies are needed to clarify the underlying mechanisms. This study is the first to use data from the largest prospective birth cohort study of Japan and to investigate the relationship between menarche age and obstetric outcomes among nulliparous women.

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.

The levelling-off of the secular trend of age at menarche among Italian girls

OBJECTIVE

The main aim of this study was to verify whether the secular trend stopped in Italy by comparing the results of a 1990-2000 birth cohort versus a 1980-1990 birth cohort of Italian young women. The results were used to speculate about age at menarche as adaptive response to non-genetic factors.

METHODS

In 2016, a study was set on 413, 18-to-26 year-old women (1990-2000 birth cohort) attending two Italian Universities by web-based, self-reported questionnaires. Previously in 2000, a research including 3,783 high school female students (1980-1990 birth cohort) was led. The age at menarche distribution was performed by Kaplan-Meier analysis. The comparison between the findings of the two birth cohorts was performed by Wilcoxon sum-rank test. Mixed models analysis was applied to evaluate the effect of cohort and socio-economic status on age at menarche.

RESULTS

1990-2000 cohort's age at menarche median was 12.44y (95%CI 12.37; 12.59y). There was no significant difference with age at menarche of the previous cohort (p = 0.56). Consistently, the advance of age at menarche in comparison to the mothers' one was not significantly different between the two cohorts (-0.27y±0.10y vs -0.25y±0.03y, p = 0.33). The socio-economic level was not significantly associated with menarcheal age.

CONCLUSIONS

The findings of this study confirm that, like in other developed countries, the advance of age at menarche has stopped in Italy, consistently with the stop of the improvement of socio-economic conditions. Further studies are needed to explore the differential effect of each non-genetic factor to outline future scenarios of human sexual maturation.

TRIAL REGISTRATION

the Comitato Etico per la Sperimentazione Clinica (CESC) della Provincia di Padova of the Veneto Region (Italy), n°3993/U16/16.