Abstract
BACKGROUND: Infertility is a growing global challenge that affects millions of people, and various factors influence female reproductive health. This study examined the association between inflammatory indicators, nutritional status, metabolic conditions, and infertility. METHODS: This cross-sectional study was part of the National Health and Nutrition Examination Survey (NHANES) and included women aged 18-45 years between 2013 and 2018. Weighted binary logistic regression was used to investigate independent relationships between inflammatory indicators, nutritional status, metabolic conditions, and infertility. Subsequently, a nomogram risk prediction model was developed along with subgroup analyses. RESULTS: Among the 1,250 women analyzed, the overall infertility prevalence was 12.3%. Multivariate logistic regression analyses identified marital status, systemic immune inflammation index (SII), body mass index (BMI), nutritional risk index (NRI), and metabolic syndrome (MetS) as independent risk factors for infertility. A nomogram prediction model was constructed based on the independent risk factors, and the area under the ROC curve of the model was 0.703. The calibration and decision curves showed that the model had good calibration and net benefits. Based on the nomogram prediction model, the total risk scores for infertility were calculated and divided into tertiles. The infertility risk was 4.5% in tertile 1, 9.3% in tertile 2, and 22.1% in tertile 3. Both the crude and adjusted models and subgroup analyses confirmed this positive correlation. CONCLUSIONS: Inflammatory, nutritional, and metabolic factors are significantly associated with infertility in women. The reproductive capacity of women of childbearing age can be enhanced by reducing inflammation, optimizing nutrition, and managing metabolic conditions, thereby reducing the risk of infertility.