Association of regional fat distribution indicators with infertility in women: insights from the 2013–2018 NHANES
Year: 2026
Type: article
Study design: Observational Study
Abstract: BACKGROUND: Female infertility is multifactorial, with adiposity and regional fat distribution hypothesized as contributors, though evidence using detailed fat measures is limited. This study aims to examine the association between fat distribution indicators and female infertility in a nationally representative sample. METHODS: This retrospective cross-sectional study analyzed NHANES 2013-2018 data from 2,531 women aged 20-45. Infertility was defined by self-reported difficulty conceiving ≥ 12 months or seeking fertility care. Exposures included body mass index (BMI) and DXA-based measures: total percent fat (TPF), android percent fat (APF), gynoid percent fat (GPF), android fat/gynoid fat ratio (AGR), visceral fat/total fat (VPF), subcutaneous fat/total fat (SPF), and visceral fat/subcutaneous fat ratio (VSR). Multivariable logistic regression was used to assess associations, and sensitivity analyses were performed to evaluate robustness. RESULTS: In multivariable-adjusted models, TPF, APF, AGR, and BMI were modestly associated with higher odds of infertility (TPF: OR = 1.02, 95%CI: 1.00-1.05; APF: OR = 1.03, 95%CI: 1.01-1.04; AGR: OR = 1.02, 95%CI: 1.01-1.03; BMI: OR = 1.02, 95%CI: 1.01-1.04). Smooth curve fitting suggested a generally monotonic positive pattern for these associations. Associations were broadly similar across subgroups, although some subgroup interactions were observed. CONCLUSION: In this analysis, TPF, APF, AGR, and BMI showed modest associations with infertility, which should not be interpreted causally. Although associations were generally consistent across subgroups, subgroup-specific heterogeneity cannot be excluded.
Source: Gynecological Endocrinology
Authors: Luming Chen, Fangxiang Mu, Tianyu He, Fang Wang
Institution: Lanzhou University Second Hospital
Language: English
Subfield: Reproductive Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: diamond
Funder: Lanzhou University
Award: G6001635068
OpenAlex ID: W7160698205
