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Background <p>The relationship between lipid metabolism and female infertility remains incompletely understood. The Atherogenic Index of Plasma (AIP) has emerged as a valuable marker of metabolic dysfunction, yet its association with infertility risk has not been systematically investigated in a large population-based study.</p> Methods <p>Data from 3,454 reproductive-aged women were analyzed using the National Health and Nutrition Examination Survey (NHANES) (2013–2018). Statistical analyses incorporated NHANES sampling weights. The association between AIP and infertility was examined using weighted logistic regression models with progressive adjustment for demographic and lifestyle factors (age, race, education, poverty income ratio, smoking, alcohol consumption, BMI, and diabetes status). Restricted cubic spline and threshold effect analyses (a statistical approach to identify inflection points where the strength of association changes) were performed to explore potential non-linear relationships and inflection points.</p> Results <p>Higher AIP levels were independently associated with increased infertility risk (adjusted OR = 2.292, 95% CI: 1.414–3.714, <i>P</i> = 0.001). This association demonstrated significant age modification, with stronger effects observed in women under 30 years (OR = 5.258, 95% CI: 2.054–13.455, <i>P</i> = 0.001). Exploratory threshold effect analysis suggested a potential inflection point at AIP = -0.076, below which the association was particularly pronounced (OR = 4.365, 95% CI: 2.002–9.863, <i>P</i> &lt; 0.001), though the likelihood ratio test did not reach conventional statistical significance (<i>P</i> = 0.074).</p> Conclusion <p>AIP shows promise as a biomarker for female infertility risk assessment, particularly in younger women. The identified AIP threshold of -0.076 is preliminary and hypothesis-generating, requiring external validation before clinical implementation. These findings suggest potential utility for risk stratification and warrant further prospective investigation to establish its clinical utility.</p>

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Threshold effects of atherogenic index of plasma on female infertility risk: evidence from NHANES 2013–2018

  • 期刊论文

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  • 发表日期：

    2025年11月19日

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  • Hongtao Zhu,
  • Luqiong Gong,
  • Huihua Yan

摘要

Background

The relationship between lipid metabolism and female infertility remains incompletely understood. The Atherogenic Index of Plasma (AIP) has emerged as a valuable marker of metabolic dysfunction, yet its association with infertility risk has not been systematically investigated in a large population-based study.

Methods

Data from 3,454 reproductive-aged women were analyzed using the National Health and Nutrition Examination Survey (NHANES) (2013–2018). Statistical analyses incorporated NHANES sampling weights. The association between AIP and infertility was examined using weighted logistic regression models with progressive adjustment for demographic and lifestyle factors (age, race, education, poverty income ratio, smoking, alcohol consumption, BMI, and diabetes status). Restricted cubic spline and threshold effect analyses (a statistical approach to identify inflection points where the strength of association changes) were performed to explore potential non-linear relationships and inflection points.

Results

Higher AIP levels were independently associated with increased infertility risk (adjusted OR = 2.292, 95% CI: 1.414–3.714, P = 0.001). This association demonstrated significant age modification, with stronger effects observed in women under 30 years (OR = 5.258, 95% CI: 2.054–13.455, P = 0.001). Exploratory threshold effect analysis suggested a potential inflection point at AIP = -0.076, below which the association was particularly pronounced (OR = 4.365, 95% CI: 2.002–9.863, P < 0.001), though the likelihood ratio test did not reach conventional statistical significance (P = 0.074).

Conclusion

AIP shows promise as a biomarker for female infertility risk assessment, particularly in younger women. The identified AIP threshold of -0.076 is preliminary and hypothesis-generating, requiring external validation before clinical implementation. These findings suggest potential utility for risk stratification and warrant further prospective investigation to establish its clinical utility.