Advanced maternal age and infertility: The role of biological aging, lifestyle, and biomarkers

Infertility in women of advanced maternal age is often attributed to chronological aging, yet the contribution of biological aging and immunometabolic dysregulation remains unclear. This cross-sectional study analyzed nationally representative data from the 2021-2023 National Health and Nutrition Examination Survey, including 895 women aged 35-49 years with complete reproductive, lifestyle, and biomarker data. Self-reported infertility was defined as a history of attempting pregnancy for at least one year without success. Biological age was estimated using standardized metabolic and inflammatory biomarkers, including C-reactive protein and glycemic indices. Multivariable logistic regression, unsupervised clustering, and machine learning-based partial dependence analyses were applied to characterize age-dependent immunometabolic associations with infertility. Biological age closely paralleled chronological age and did not differ significantly between women reporting infertility and those not reporting infertility (p = 0.38). However, women reporting infertility exhibited a broader upper-tail distribution of biological age, suggesting a subgroup with elevated immunometabolic burden. Clustering identified four distinct immunometabolic phenotypes, with infertility prevalence ranging from 7.4% to 21.4%, highest in the phenotype characterized by elevated systemic inflammation. Machine learning analyses revealed nonlinear and age-specific associations between body mass index, inflammatory markers, and infertility risk, particularly among women aged 40-44 years, patterns not detected using conventional regression models. These findings suggest that infertility in advanced maternal age is not uniformly associated with accelerated biological aging but reflects heterogeneous immunometabolic pathways, particularly those related to systemic inflammation. Integration of inflammatory biomarkers with advanced analytic modeling may improve individualized risk stratification and understanding of age-related infertility.