Association between atherogenic index of plasma and infertility: a cross-sectional study based on U.S. women

A wealth of evidence indicates that dyslipidemia is associated with endothelial dysfunction, oxidative stress, and inflammation, each of which can impair reproductive function and lead to infertility. The Atherogenic Index of Plasma (AIP) is an innovative lipid biomarker that combines the triglyceride to high-density lipoprotein cholesterol (HDL-C) ratio, providing a more in-depth evaluation of lipid metabolism. This biomarker synthesizes discrete lipid disruptions into a single value, surpassing isolated lipid indicators' diagnostic value. The primary goal of our study was to explore the link between AIP and the incidence of infertility.

Data from the National Health and Nutrition Examination Survey (NHANES) spanning 2013-2018 were subjected to cross-sectional examination. The AIP is determined through the logarithmic transformation (base 10) of the triglyceride-to-HDL-C ratio. To uncover the connection between AIP and infertility, a suite of analytical techniques was employed, encompassing weighted multiple logistic regression, stratified analyses, spline curve modeling, and determination of cutoff values.

Among the 1,191 participants, with a weighted mean age of 31.89 years, 12.09% were diagnosed as infertile. The multivariate-adjusted odds ratios for infertility occurrence across the AIP quartiles were 1.00 (reference), 1.96 (95% CI: 1.10-3.49), 2.62 (95% CI: 1.48-4.63), and 2.38 (95% CI: 1.31-4.32), respectively. Subgroup examinations suggest that the association between AIP and infertility remains robust and is not substantially altered by factors including age, marital status, economic status, tobacco use, alcohol intake, and body mass index. Curve fitting and threshold analyses have indicated a positive nonlinear relationship between AIP and infertility, as well as a relatively stable incidence of infertility within the AIP range from -0.21 to 0.22.

Incorporating an assessment of AIP into the clinical evaluation could potentially refine the accuracy of risk estimation for infertility patients.