ArticleEndocrine2024
Fat-free mass index is a feasible predictor of insulin resistance in women with polycystic ovary syndrome: Evidence from a cross-sectional study.
Article in Endocrine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 2 of them syntheses that pooled it.
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Who cites it
5 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- The accuracy of lipid accumulation product to predict metabolic syndrome in PCOS: a meta-analysis and comparative analysis with other indicators.Frontiers in endocrinology · 2026Pooled it
- Liver and cardiovascular outcomes in lean non-alcoholic fatty liver disease: an updated systematic review and meta-analysis of about 1 million individuals.Hepatology international · 2024Pooled it
- Analysis of the association between cytokine expression in the endometrial microenvironment and insulin resistance in polycystic ovary syndrome.Endocrine · 2026Article
- Dietary and Genetic Aspects of Polycystic Ovary Syndrome (PCOS) in Polish Women-Part I: Nutritional Status and Dietary Intake.Nutrients · 2025Article
- Associations of the fat-free mass index and the fat mass index with the risk of developing diabetes and prediabetes in US adults: a nationally representative cross-sectional study.Lipids in health and disease · 2024Article
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
backgroundInsulin resistance (IR) and adipose tissue amplify the metabolic and reproductive outcomes in women with polycystic ovary syndrome (PCOS). It has been widely discussed that body composition influences metabolic health. Still, limited studies were focused on the role of the fat-free mass index (FFMI) in assessing IR in PCOS women.
aimsWe aimed to explore the associations between FFMI/fat mass index (FMI) and IR in women with PCOS and assess the role of FFMI in predicting IR in women with PCOS.
methodsIn the current cross-sectional study, women with PCOS aged between 18 and 40 years were enrolled from October 2018 to July 2022. Baseline demographic information was obtained using standardized self-administered questionnaires. Anthropometric, biochemical, and hormonal information was measured and recorded by investigators. Pearson's correlation and multivariable logistical regression were used to analyze the associations of FFMI/FMI and IR. In addition, receiver operating characteristic (ROC) curves were implied to measure the predictive role of FFMI/FMI for IR in women with PCOS.
resultsA total of 371 women with PCOS, reproductive age (27.58 ± 4.89) were enrolled. PCOS women with IR have higher levels of triglyceride (TG), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-c), homeostatic model assessment of insulin resistance (HOMA-IR), FMI, and FFMI than that without IR. FMI (r = 0.492, p < 0.001) and FFMI (r = 0.527, p < 0.001) were positively associated with IR. After adjusting for potential confounders, FMI and FFMI were significantly associated with IR in PCOS women, and the OR was 1.385 (95%CI: 1.212-1.583) and 2.306 (95%CI: 1.675-3.174), respectively. Additionally, the FFMI (0.847, 95%CI: 0.784-0.888) has a larger area of ROC (AUC) than the FMI (0.836, 95%CI: 0.799-0.896), while there is no difference in predicting IR (95%CI: -0.18-0.41, p = 0.456).
conclusionThese results indicated that FFMI and FMI could significantly increase the risk of IR, both of which could be feasible predictors of IR in PCOS women.
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