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Article

Association Between Age at Menarche and Gestational Diabetes: A Retrospective Case–Control Study

by
Ximena Solis-Gómez
1,†,
Mónica Alethia Cureño-Díaz
2,†,
Maximiliano Olguín-Montiel
1,
Adriana Jiménez
3,
Erika Gómez-Zamora
4,
Ahidée Guadalupe Leyva-Lopez
5,
Yaneth Citlalli Orbe-Orihuela
6,
Miguel Trujillo-Martínez
7,
Ricardo Castrejón-Salgado
8 and
José Ángel Hernández-Mariano
3,*,†
1
School of Medicine, National Autonomous University of Mexico, Mexico City 04360, Mexico
2
Department of Institutional Intelligence in Oncological Health, National Institute of Cancerology, Mexico City 14080, Mexico
3
Department of Research, Hospital Juarez of Mexico, Mexico City 07760, Mexico
4
Department of Medical Management, Hospital Juarez of Mexico, Mexico City 07760, Mexico
5
Center for Population Health Research, National Institute of Public Health, Cuernavaca 62100, Mexico
6
Department of Chronic Infections and Cancer, Center for Research on Infectious Diseases, National Institute of Public Health, Cuernavaca 62100, Mexico
7
General Hospital with Family Medicine Unit Number 7, Mexican Social Security Institute, Cuautla 62740, Mexico
8
Planning and Institutional Liaison Coordination, Decentralized Administrative Operations Body, Mexican Social Security Institute, Cuautla 62000, Mexico
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Women 2025, 5(4), 43; https://doi.org/10.3390/women5040043
Submission received: 14 October 2025 / Revised: 3 November 2025 / Accepted: 10 November 2025 / Published: 13 November 2025
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Abstract

Early menarche has been recognized as an early-life marker of metabolic vulnerability, yet its link to gestational diabetes mellitus (GDM) remains unclear. We investigated this association in a retrospective case–control study of 71 cases and 355 controls from a tertiary hospital in Mexico City. Age at menarche was evaluated both in categories and using restricted cubic splines to capture potential non-linear trends. Mediation analysis explored the contribution of pregestational body mass index (BMI) to the relationship between variables. Women who experienced menarche before age 12 had more than twice the odds of developing GDM compared with those whose menarche occurred between 12 and 15 years (adjusted OR = 2.51, 95% CI 1.40–4.50). In contrast, late menarche showed a minor, non-significant increase in risk. The spline models revealed a subtle U-shaped pattern, suggesting that both very early and delayed pubertal timing may carry metabolic disadvantages. The mediation analysis showed that pregestational BMI accounted for only a minor share of this association. Overall, the findings indicate that early pubertal onset may influence glucose regulation during pregnancy through pathways beyond adiposity, highlighting early menarche as a valuable marker for identifying women at higher risk of GDM.

1. Introduction

Gestational diabetes mellitus (GDM) is defined as a state of hyperglycemia that appears or is first recognized during pregnancy, typically diagnosed between 24 and 28 weeks of gestation through screening and confirmatory testing [1]. This disorder represents one of the most frequent metabolic complications of pregnancy and has significant implications for both maternal and neonatal health [2]. In mothers, GDM is associated with increased risk of preeclampsia, preterm delivery, and future development of type 2 diabetes [3]; in the offspring, it increases the likelihood of macrosomia, neonatal hypoglycemia, autism, and later obesity [4,5,6,7].
The prevalence of GDM varies considerably depending on diagnostic criteria and population characteristics. Globally, between 7.1% and 27.6% pregnancies are affected [8]; across the Americas, the estimated prevalence ranges from 8.5% to 14.2% [8,9]. In Mexico, although precise national data are limited, studies have estimated rates ranging from 6% to 13% [10,11]. These figures highlight the magnitude of the problem and underscore the need to identify factors that could inform prevention and support timely diagnosis.
Traditional metabolic risk factors, such as a high body mass index, family history of diabetes, and advanced maternal age, are well-established [12].
However, increasing attention has been directed toward early reproductive factors, particularly the timing of menarche. Menarche is considered early if it occurs before age 12 and late if it occurs after age 15 [13,14]. Early menarche has been consistently associated with obesity, insulin resistance, and type 2 diabetes in adulthood, suggesting that it may also predispose women to gestational diabetes [15,16,17]. Biologically, earlier pubertal onset entails longer cumulative exposure to estrogens and progesterone, which promotes adiposity and insulin resistance. These endocrine–metabolic mechanisms may increase susceptibility to glucose intolerance during pregnancy, whereas late menarche may reflect nutritional or endocrine factors that also influence metabolic health [18].
Despite the biological plausibility of these mechanisms, epidemiological evidence remains inconsistent. Several studies have reported that early menarche is associated with increased insulin resistance and an increased risk of type 2 diabetes in adulthood [16,19,20,21,22]. However, other investigations have found no significant associations between early menarche and glucose intolerance or diabetes [23,24]. In contrast, one study reported a U-shaped relationship, with a higher diabetes risk among women with both early and late menarche [25]. On the other hand, evidence linking age at menarche to GDM is even more limited and less consistent. Some studies suggest that women with early menarche are more likely to develop GDM [26,27,28], whereas others have not confirmed this association [28,29]. Moreover, a curvilinear relationship has been described, with increased risk of GDM observed among women with both early and late menarche [30]. In Latin America, this relationship has been scarcely explored. To our knowledge, no studies in Mexico have examined this association, despite a generational decline in the age at menarche and a growing prevalence of GDM, which represents an emerging public health concern. Understanding whether age at menarche serves as an early reproductive marker of GDM susceptibility could enable the early identification of women at risk and support tailored screening, preconception counseling, and lifestyle interventions. Therefore, we aimed to investigate the relationship between age at menarche and GDM among Mexican women.

2. Results

Table 1 summarizes participants’ baseline characteristics. The median age was 25 years (interquartile range 10 years). Most women were married or living with a partner (92.0%) and had completed lower secondary education (50.6%). The median monthly household income was 459 units (IQR 74.0). Nearly half (47.4%) had one or two previous births, and 10.3% reported a history of gestational diabetes. Current alcohol and tobacco use were reported by 6.8% and 12.0% of participants, respectively. A family history of diabetes was present in 26.3% of participants. Regarding reproductive history, most women (60.6%) reported menarche between 12 and 15 years of age, 29.3% before 12 years, and 10.1% after 15 years.
Women with gestational diabetes differed significantly from controls in several characteristics. They were, on average, older than women without the condition. A greater proportion of cases had one or two previous births, whereas nulliparity was more common among controls. The previous history of gestational diabetes was notably more frequent among cases. Early menarche was also more common among women with gestational diabetes, indicating an earlier onset of reproductive maturation in this group. Other sociodemographic and behavioral characteristics, including marital status, education level, income, alcohol or tobacco use, and family history of diabetes, showed no significant differences between groups.
In the unadjusted model, women who experienced menarche before age 12 had higher odds of GDM compared with those whose menarche occurred between 12 and 15 years (OR = 2.31; 95% CI 1.29–4.13). After adjustment for potential confounders, the association remained significant and of similar magnitude (adjusted OR = 2.51; 95% CI 1.40–4.50). The robustness of this association was supported by an E-value of 4.46 (E-value for the lower confidence limit, 2.15), indicating that an unmeasured confounder would need to be strongly associated with both the exposure and the outcome to fully explain the observed effect. Late menarche (after age 15) was not significantly associated with gestational diabetes in either model; thus, no E-value was estimated for this comparison (Table 2).
In sensitivity analyses, we assessed whether the association between age at menarche and GDM was consistent across alternative exposure categorizations. When age at menarche was reclassified into <11, 11–14, and >14 years, early menarche (<11 years) remained associated with higher odds of GDM compared with the reference group (adjusted OR = 1.64; 95% CI 0.75–3.60), whereas late menarche (>14 years) was not associated (adjusted OR = 0.93; 95% CI 0.44–1.94; Table S1). In a second sensitivity model using 12–13 years as the reference category and comparing it with earlier (≤11 years) and later (≥14 years) menarche (Table S2), women with menarche at ≤11 years had significantly higher odds of GDM (adjusted OR = 2.38; 95% CI 1.31–4.34; p = 0.005), whereas those with menarche at ≥14 years showed no association (adjusted OR = 1.21; 95% CI 0.58–2.51).
To further explore the shape of the association, we modeled age at menarche as a continuous exposure using restricted cubic splines (RCS). Using 13 years as the reference, the relationship between age at menarche and GDM followed a U-shaped pattern, with higher odds at very early ages (approximately 10–12 years), a minimum around 13–14 years, and a modest increase at later ages. The uncertainty widened toward the extremes of the distribution. When three knots were placed at the 10th, 50th, and 90th percentiles and centered at 13 years, the joint test of the nonlinear component was statistically significant (Wald χ2 (1) = 4.09, p = 0.043). A four-knot model using the 5th, 35th, 65th, and 95th percentiles yielded a similar curve and confirmed the presence of non-linearity (Wald χ2 (2) = 10.68, p = 0.0048), although confidence bands were wider at the tails. Model fit was comparable across linear, three-knot, and four-knot specifications, as indicated by both AIC and BIC. Considering parsimony and the greater stability of the confidence intervals, we display the three-knot curve as the main result (Figure 1) and include the four-knot model as a supplementary figure (Figure S1).
To evaluate whether adiposity-related pathways explained the association between age at menarche and gestational diabetes, mediation analyses were conducted separately for early and late menarche. Among women with menarche before age 12, the total effect on GDM was significant (OR = 2.19, 95% CI 1.29–3.73), and the direct effect remained statistically significant after adjustment (OR = 2.06, 95% CI 1.21–3.50). The indirect effect through pregestational BMI was small and non-significant (OR = 1.06, 95% CI 0.94–1.20), indicating that approximately 9.7% of the association was mediated (Panel A, Figure 2). In contrast, for women with menarche after age 15, neither the total (OR = 1.54, 95% CI 0.67–3.58) nor the direct effect (OR = 1.52, 95% CI 0.70–3.29) reached statistical significance, and no evidence of mediation was observed (indirect OR = 1.02, 95% CI 0.71–1.46; proportion mediated = 4.3%) (Panel B, Figure 2).

3. Discussion

In this study, we found that early menarche was significantly associated with an increased risk of gestational diabetes. This association persisted after adjustment for potential confounders, suggesting that early sexual maturation may represent an early-life marker of metabolic vulnerability. We observed that nearly one in three participants experienced menarche before age 12, a finding consistent with national data indicating a secular decline in the age at menarche among Mexican women [31]. Studies from different regions of Mexico have documented mean ages at menarche ranging from 11.3 to 12.0 years, consistent with the national downward trend and reinforcing the representativeness of our findings [31,32]. In recent decades, Mexico has also experienced some of the highest global rates of childhood and adolescent overweight and obesity [33]. Excess adiposity increases leptin and insulin levels, hormones that accelerate pubertal onset and may contribute to the rising prevalence of early menarche in this population [34].
Early menarche has been associated with long-term metabolic alterations that may predispose women to GDM. Accelerated pubertal timing is associated with greater lifetime exposure to estrogens and earlier adipose tissue accumulation, both of which contribute to the development of insulin resistance [18]. Consistent with our findings, previous studies conducted in several parts of the world have reported that early menarche is associated with an increased risk of metabolic syndrome, type 2 diabetes, and gestational diabetes in adulthood [15,16,17,35], suggesting that this relationship is not limited to specific ethnic or socioeconomic contexts. Women who experience menarche at younger ages tend to exhibit higher pregestational BMI, increased visceral fat deposition, and altered glucose metabolism even before pregnancy, indicating that metabolic programming may begin early in life [36].
In our study, the spline analyses revealed a modest U-shaped pattern, suggesting that both extremes of reproductive maturation could entail metabolic disadvantages. However, the association was strongest for early menarche. Biologically, this may reflect the dual impact of accelerated and delayed hypothalamic–pituitary–gonadal activation. Early activation promotes adipogenesis and chronic low-grade inflammation through leptin and insulin signaling, whereas delayed maturation may reflect underlying nutritional or endocrine disturbances that also impair insulin sensitivity [37,38,39]. Previous research has also identified an increased risk of type 2 diabetes and cardiovascular disease among women with late menarche, supporting the notion that delayed reproductive maturation may also signal adverse metabolic programming [25,30,40,41]. Moreover, similar U-shaped associations between age at menarche and metabolic outcomes have been described in other studies, one assessing type 2 diabetes [25]. Another study examining GDM [30] further supports the hypothesis that deviations from typical pubertal timing, whether early or late, may represent distinct pathways of metabolic dysregulation that contribute to glucose intolerance during pregnancy. In our study, however, the association between late menarche and GDM was not statistically significant, likely due to the smaller number of participants in this category. Taken together, these findings support the hypothesis that deviations from typical pubertal timing, whether early or late, may represent distinct pathways of metabolic dysregulation that contribute to glucose intolerance during pregnancy.
The robustness of these findings was confirmed in additional sensitivity analyses using alternative categorizations of menarcheal age. When age at menarche was reclassified into <11, 11–14, and >14 years, the direction of the association remained consistent, although precision decreased due to the smaller sample size in the youngest group. Similarly, when using 12–13 years as the reference category and comparing earlier (≤11 years) and later (≥14 years) menarche, the excess risk of GDM was again concentrated among women with menarche at ≤11 years. These results demonstrate that the association between early menarche and GDM is robust across alternative exposure categorizations.
In mediation analyses, pregestational BMI accounted for only a small, non-significant portion of the association between early menarche and gestational diabetes. This finding suggests that the excess risk associated with early pubertal timing operates primarily through direct pathways rather than being fully explained by pre-existing adiposity. Previous studies have also reported that adjusting for adult BMI attenuates but does not eliminate the association between early menarche and glucose intolerance or type 2 diabetes, supporting the notion that shared developmental mechanisms, such as early-life nutritional exposure, hormonal imprinting, and genetic susceptibility, may contribute to long-term metabolic risk [18,22]. Early menarche may also reflect a trajectory of accelerated biological aging, characterized by chronic low-grade inflammation, endothelial dysfunction, and early-onset insulin resistance. These processes could predispose women to impaired glucose regulation during pregnancy even in the absence of overt obesity [22,42,43,44]. Nevertheless, the lack of a significant indirect effect in our study could also reflect limited statistical power to detect minor mediation effects or imprecision in the measurement of pregestational weight, which may have attenuated the estimates. Despite these limitations, the direction and magnitude of the findings suggest that early menarche represents an independent marker of metabolic vulnerability.

Limitations

This study has some limitations that should be considered when interpreting the findings. First, although the age at menarche was obtained from clinical records, minor inaccuracies cannot be ruled out. However, recall of menarche age is highly reliable even many years after the event, and any potential error is likely to be non-differential. Second, pregestational weight was estimated indirectly by subtracting the self-reported gestational weight gain from the measured final pregnancy weight. This approach may have introduced some imprecision in estimating pregestational BMI and, consequently, attenuated the observed magnitude of the mediation effects. Given that any resulting error was likely random and unrelated to age at menarche or GDM status, its impact would most likely reflect non-differential misclassification, biasing the indirect effect toward the null. Thus, the modest and non-significant mediation observed may partly reflect this measurement imprecision rather than the absence of a proper pathway through adiposity, and should therefore be interpreted with caution. Third, the relatively small number of women with late menarche (approximately 10% of participants, n ≈ 43) may have limited the statistical power to detect significant associations in this group, leading to wider confidence intervals at the extremes of the spline curve. Because uncertainty naturally increases at both tails of the menarche-age distribution, these estimates should be interpreted with caution. However, the results of our sensitivity analyses, using alternative categorizations of age art menarche, <11, 11–14, >14 years and ≤11, 12–13, ≥14 years, showed consistent directions of association and similar point estimates, suggesting that the lack of significance in this subgroup likely reflects limited sample size rather than the absence of a true relationship. Fourth, although the analyses are adjusted for key sociodemographic and reproductive factors, residual confounding by unmeasured variables (i.e., childhood nutrition) cannot be excluded. However, the E-value analysis indicated that an unmeasured confounder would need to be strongly associated with both early menarche and gestational diabetes to fully explain the observed association, suggesting that residual confounding is unlikely to account for the findings. Fifth, because this was a case–control study, the temporal sequence between exposure and outcome could not be fully established, and the associations identified should not be interpreted as causal. Finally, because the study population was drawn from a single tertiary hospital that primarily serves women without social security coverage, socioeconomic characteristics may differ from those of the general obstetric population in Mexico. Patients attending this public referral center often experience limited access to preventive and preconception care, a higher prevalence of overweight and obesity, and greater exposure to adverse social determinants of health, such as food insecurity and reduced healthcare continuity. These factors could modify both the timing of menarche and the risk of gestational diabetes, potentially reinforcing the associations observed. Consequently, while the biological mechanisms linking pubertal timing and glucose regulation are unlikely to differ across populations, the magnitude of the associations should be interpreted in light of the socioeconomic profile of this cohort. Despite these limitations, the consistency of the observed patterns and the robustness analyses performed strengthen the internal validity and interpretability of our findings.

4. Materials and Methods

4.1. Design and Study Population

We conducted an analytic case–control study based on a retrospective review of medical records from pregnant women attended at a tertiary care hospital in Mexico City between January and December 2024. The institution provides specialized medical care to individuals without social security coverage.
The study population included women aged 18 to 45 years with singleton pregnancies and complete clinical information regarding age at menarche and GDM status. Women with pregestational diabetes, multiple gestations, or incomplete medical records were excluded from the analysis. GDM was defined according to the American Diabetes Association criteria and identified by an oral glucose tolerance test performed between 24 and 28 weeks of gestation. Controls were pregnant women without GDM during the same period, selected from the same hospital population, and matched to cases at a 1:5 ratio by the four months of care. A total of 71 cases and 355 controls were included in the final analytic sample (Figure S2).

4.2. Study Variables

The dependent variable was the presence of GDM, as documented in clinical records and diagnosed according to the American Diabetes Association (ADA) criteria (2024). The primary independent variable was age at menarche, expressed in years and analyzed both as a continuous variable and as categorical groups: early (<12 years), average (12–14 years), and late (>14 years).
Covariates included sociodemographic factors (maternal age, marital status, education level, and monthly family income), obstetric characteristics (parity and history of miscarriage), and clinical and behavioral factors (family history of diabetes, alcohol consumption, and tobacco use). Because pregestational body mass index (BMI) was not systematically recorded, we estimated pregestational weight by subtracting the self-reported total gestational weight gain from the final maternal weight recorded at the end of pregnancy. This estimate served as a proxy for maternal nutritional status before conception and has been applied in retrospective studies when complete pregestational data are unavailable. Alcohol consumption and tobacco use were coded as dichotomous variables (yes/no) based on documentation in the clinical records.

4.3. Data Collection

Data were collected retrospectively through a systematic review of paper-based clinical records, as the hospital does not have an electronic medical record system. Authorization was obtained from the Clinical Records Department to access the files of pregnant women attended at a tertiary care hospital in Mexico City between January and December 2024. To ensure the reliability of the selection process, an independent evaluation of 15% of the records (n = 64) was conducted before applying the exclusion criteria. Interobserver agreement was assessed using Cohen’s kappa coefficient, yielding a value of 0.85, which indicated substantial agreement among reviewers.

4.4. Statistical Analysis

We summarized participants’ characteristics using descriptive statistics. Categorical variables were expressed as frequencies and percentages. In contrast, continuous variables were described using medians and interquartile ranges (IQRs) because they were non-normal, as determined by the Shapiro–Wilk test. Comparisons between cases and controls were performed using Pearson’s chi-square test for categorical variables and the Mann–Whitney U test for continuous variables.
We estimated odds ratios (ORs) and 95% confidence intervals (CIs) for the association between age at menarche and GDM using logistic regression models. To evaluate potential dose–response relationships, we obtained p-values for trend by modeling the median value of each menarcheal age category (<12, 12–14, and >14 years) as a continuous variable.
As part of the sensitivity analyses, we assessed the robustness of the association to alternative functional forms of the exposure. First, we reclassified age at menarche into <11, 11–14, and >14 years to examine whether a narrower definition of early puberty altered the estimates. Second, because previous studies on menarcheal timing and metabolic outcomes have used single-year categories centered around the modal ages (≤11, 12–13 years [reference], and ≥14 years) to better capture non-linear patterns [26] we fitted an additional conditional logistic regression model using this three-level specification. Both sensitivity models used the same matching structure and covariate adjustment as the main analysis.
In addition, we modeled age at menarche as a continuous exposure using restricted cubic splines (RCS). Our primary sensitivity specification used three knots at the 10th, 50th, and 90th percentiles, centered at 13 years; non-linearity was assessed with Wald tests of the non-linear spline term (s). We also fit an alternative four-knot specification (5th, 35th, 65th, and 95th percentiles) as a robustness check. The overall shape was similar, but confidence bands were wider at the tails, so we present the three-knot curve as the main sensitivity display.
Because previous evidence suggests that age at menarche may influence body weight and that maternal weight is a well-established predictor of GDM, we conducted a mediation analysis to assess whether estimated pregestational weight mediated this association. This analysis was performed using the “mediate” command in Stata, which implements the counterfactual causal mediation framework. Logistic regression was specified for the outcome (GDM), and linear regression was used for the mediator (estimated pregestational weight). We estimated the natural direct and indirect effects with their 95% CIs and calculated the proportion mediated to quantify the extent to which pregestational weight explained the total association. Because the “mediate” command requires a dichotomous exposure, we ran two independent mediation models: one comparing women with early menarche (<12 years) with the reference group (12–14 years), and another comparing women with late menarche (>15 years) with the same reference group.
All models were adjusted for confounding factors. The selection of confounders was guided by directed acyclic graphs (DAGs) [45,46]. The minimum adjustment set was maternal age, educational level, and monthly family income. (Figure S3). To assess the potential impact of unmeasured confounding, we calculated E-values for the observed associations between age at menarche and GDM. The E-value represents the minimum strength of association that an unmeasured confounder would need to have with both the exposure and the outcome, conditional on the measured covariates, to account for the observed effect estimates fully [47].
Statistical significance for logistic regression models and hypothesis tests was determined using a p-value threshold of <0.05. All analyses were conducted using Stata statistical software, version 19.5 (StataCorp, College Station, TX, USA).

5. Conclusions

Early menarche was associated with a higher risk of gestational diabetes. Mediation analyses indicated that pregestational adiposity explained only a small and non-significant proportion of this association, suggesting that early pubertal timing may influence gestational glucose regulation through additional biological pathways beyond adiposity. These findings support the concept of early menarche as a marker of metabolic vulnerability in early life. Recognizing this reproductive milestone as a potential risk indicator could help identify women who might benefit from targeted preventive strategies before and during pregnancy. Future research should confirm these results in larger and more diverse populations and further explore the mechanisms linking pubertal timing to metabolic health in pregnancy.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/women5040043/s1, Figure S1. Spline curve of age at menarche and gestational diabetes mellitus (four-knot model); Figure S2. Flow diagram of participant selection for the case–control study on age at menarche and gestational diabetes mellitus; Figure S3. Directed acyclic graph (DAG) for the association between age at menarche and gestational diabetes mellitus, with pregestational body mass as mediator; Table S1. Sensitivity analysis of the association between age at menarche and gestational diabetes using alternative categorical definitions of age at menarche (<11, 11–14, and >14 years); Table S2. Sensitivity analysis of the association between age at menarche and gestational diabetes using 12–13 years as the reference category (≤11, 12–13, and ≥14 years).

Author Contributions

Conceptualization, J.Á.H.-M., X.S.-G. and M.A.C.-D.; methodology, J.Á.H.-M., X.S.-G. and M.A.C.-D.; software, J.Á.H.-M.; validation, J.Á.H.-M., M.A.C.-D., X.S.-G., A.J., A.G.L.-L., Y.C.O.-O., M.T.-M., E.G.-Z., M.O.-M. and R.C.-S.; formal analysis, J.Á.H.-M.; investigation, J.Á.H.-M., X.S.-G., E.G.-Z., A.J., M.O.-M. and M.A.C.-D.; resources, J.Á.H.-M. and M.A.C.-D.; data curation, J.Á.H.-M., A.J. and Y.C.O.-O.; writing—original draft preparation, J.Á.H.-M., writing—review and editing, X.S.-G., M.A.C.-D., A.J., E.G.-Z., A.G.L.-L., Y.C.O.-O., M.T.-M., M.O.-M. and R.C.-S.; visualization, X.S.-G., M.A.C.-D., E.G.-Z., A.J., A.G.L.-L., Y.C.O.-O., M.T.-M., J.Á.H.-M., M.O.-M. and R.C.-S.; supervision, J.Á.H.-M.; project administration, J.Á.H.-M. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

This research study was approved by Hospital Juarez of Mexico’s Ethics and Research Committee on 8 January 2025 (07824I).

Informed Consent Statement

Not applicable. This study was based on a retrospective review of patient medical records, and no direct involvement of human subjects or interventions was required.

Data Availability Statement

The data that support the findings of this study are openly available in Mendeley Data at doi: 10.17632/htd7rzxtj7.1; https://data.mendeley.com/drafts/fjw9mnnj4v (accessed on 10 October 2025).

Conflicts of Interest

The authors declare no conflicts of interest.

Abbreviations

The following abbreviations are used in this manuscript:
GDMGestational diabetes mellitus
OROdds ratio
CIConfidence interval
DAGDirected acyclic graphs
IQRInterquartile range

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Women 05 00043 g001
Figure 1. Restricted cubic spline of age at menarche (reference = 13 years) from conditional logistic regression of GDM, adjusted for maternal age, education, monthly family income, and family history of diabetes. Knots at the 10th, 50th, and 90th percentiles; odds ratios with 95% confidence bands. Abbreviations: OR, odds ratio; CI, confidence interval.
Figure 1. Restricted cubic spline of age at menarche (reference = 13 years) from conditional logistic regression of GDM, adjusted for maternal age, education, monthly family income, and family history of diabetes. Knots at the 10th, 50th, and 90th percentiles; odds ratios with 95% confidence bands. Abbreviations: OR, odds ratio; CI, confidence interval.
Women 05 00043 g001
Women 05 00043 g002
Figure 2. Mediation analysis of the association between age at menarche and gestational diabetes mellitus (GDM) through pregestational body mass index (BMI). Panel (A) illustrates the pathway for early menarche (<12 years), and Panel (B) illustrates the pathway for late menarche (>15 years). Abbreviations: OR, odds ratio; CI, confidence interval; BMI, body mass index.
Figure 2. Mediation analysis of the association between age at menarche and gestational diabetes mellitus (GDM) through pregestational body mass index (BMI). Panel (A) illustrates the pathway for early menarche (<12 years), and Panel (B) illustrates the pathway for late menarche (>15 years). Abbreviations: OR, odds ratio; CI, confidence interval; BMI, body mass index.
Women 05 00043 g002
Table 1. Selected characteristics of the study population.
Table 1. Selected characteristics of the study population.
Features Gestational Diabetes
n = 426Yes (Cases)
n = 71		No (Controls)
n = 355		p-Value a
Age (in years)
     Median (IQR)25 (10)30 (13)25 (10)0.001
Marital status, f (%)
     No partner34 (8.0)6 (8.5)28 (7.9)0.873
     With partner392 (92.0)65 (91.5)327 (92.1)
Education level, f (%)
     Primary education40 (9.4)7 (9.9)33 (9.3)0.138
     Lower secondary education215 (50.6)30 (42.3)185 (52.3)
     Upper secondary education89 (20.9)22 (31.0)67 (18.9)
     Tertiary education81 (19.1)12 (16.9)69 (19.5)
Monthly household income b
     Median (IQR)459 (74.0)442.3 (67.3)460.1 (74.8)0.218
Parity, f (%)
     Nulliparous172 (40.4)19 (26.6)153 (43.1)0.030
     1–2202 (47.4)43 (60.6)159 (44.8)
     ≥352 (12.2)9 (12.7)43 (12.1)
Previous gestational diabetes
     No382 (89.7)45 (63.4)337 (94.9)0.001
     Yes44 (10.3)26 (36.6)18 (5.1)
Alcohol consumption, f (%)
     No401 (94.1)68 (95.8)333 (93.8)0.519
     Yes25 (5.9)3 (12.0)22 (6.2)
Cigarette smoking, f (%)
     No375 (88.0)61 (85.9)314 (88.5)0.548
     Yes51 (12.0)10 (14.1)41 (11.5)
Family history of diabetes, f (%)
     No314 (73.7)53 (74.6)261 (73.5)0.844
     Yes112 (26.3)18 (25.4)94 (26.5)
Age of menarche, f (%)
     <12 years125 (29.3)30 (42.2)95 (26.8)0.021
     12–15 years258 (60.6)33 (46.5)225 (63.4)
     >15 years43 (10.1)8 (11.3)35 (9.8)
Abbreviations: IQR, interquartile range; f, frequency. a Categorical variables were compared using Pearson’s chi-squared or Fisher’s exact test, and medians with the Mann–Whitney U test. b American dollars.
Table 2. Odds ratios for the association between age at menarche and gestational diabetes.
Table 2. Odds ratios for the association between age at menarche and gestational diabetes.
Age at Menarche Gestational Diabetes
OR (CI 95%)p-ValueOR (CI 95%) ap-Value
12–15 yearsRef.-Ref.-
<12 years 2.31 (1.29, 4.13)0.0052.51 (1.40, 4.50)0.002
>15 years1.55 (0.69, 3.50)0.2861.84 (0.75, 4.49)0.179
Abbreviations: OR, odds ratio; CI, confidence interval. a All models were adjusted for age, education, monthly household income, family history of diabetes, parity.
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Solis-Gómez, X.; Cureño-Díaz, M.A.; Olguín-Montiel, M.; Jiménez, A.; Gómez-Zamora, E.; Leyva-Lopez, A.G.; Orbe-Orihuela, Y.C.; Trujillo-Martínez, M.; Castrejón-Salgado, R.; Hernández-Mariano, J.Á. Association Between Age at Menarche and Gestational Diabetes: A Retrospective Case–Control Study. Women 2025, 5, 43. https://doi.org/10.3390/women5040043

AMA Style

Solis-Gómez X, Cureño-Díaz MA, Olguín-Montiel M, Jiménez A, Gómez-Zamora E, Leyva-Lopez AG, Orbe-Orihuela YC, Trujillo-Martínez M, Castrejón-Salgado R, Hernández-Mariano JÁ. Association Between Age at Menarche and Gestational Diabetes: A Retrospective Case–Control Study. Women. 2025; 5(4):43. https://doi.org/10.3390/women5040043

Chicago/Turabian Style

Solis-Gómez, Ximena, Mónica Alethia Cureño-Díaz, Maximiliano Olguín-Montiel, Adriana Jiménez, Erika Gómez-Zamora, Ahidée Guadalupe Leyva-Lopez, Yaneth Citlalli Orbe-Orihuela, Miguel Trujillo-Martínez, Ricardo Castrejón-Salgado, and José Ángel Hernández-Mariano. 2025. "Association Between Age at Menarche and Gestational Diabetes: A Retrospective Case–Control Study" Women 5, no. 4: 43. https://doi.org/10.3390/women5040043

APA Style

Solis-Gómez, X., Cureño-Díaz, M. A., Olguín-Montiel, M., Jiménez, A., Gómez-Zamora, E., Leyva-Lopez, A. G., Orbe-Orihuela, Y. C., Trujillo-Martínez, M., Castrejón-Salgado, R., & Hernández-Mariano, J. Á. (2025). Association Between Age at Menarche and Gestational Diabetes: A Retrospective Case–Control Study. Women, 5(4), 43. https://doi.org/10.3390/women5040043

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