Sci Rep
Department of Obstetrics and Gynecology, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China.
Published: February 2025
Infertility is a significant global issue affecting millions of couples, and increased body fat is considered a major contributing factor. Traditional assessment methods, such as body mass index (BMI) and waist circumference (WC), are limited in accurately reflecting body fat composition. The relative fat mass (RFM) index, a newer tool, provides a more precise assessment of fat content, but its relationship with infertility remains unclear. This study aimed to investigate the correlation between relative fat mass and a history of infertility by analyzing data from the National Health and Nutrition Examination Survey (NHANES). The study included 3915 women aged 18 to 45 years. Infertility status was self-reported, and RFM was calculated using a specific formula. Logistic regression models were employed, adjusting for multiple covariates, to investigate the relationship between RFM and infertility. Women with a history of infertility had a significantly higher RFM when compared to those who were not infertile. Specifically, women in the highest RFM quartile had almost three-fold higher odds of history of infertility than those in the lowest quartile (odds ratio [OR]: 2.87; 95% confidence interval [CI]: 1.85-4.44). Subgroup analyses indicated a stronger association between RFM and a history of infertility; this relationship was predominantly observed in women under 35 years-of-age. Sensitivity analyses confirmed the robustness of these findings. Higher RFM is more likely to be associated with a history of infertility. While RFM provides a more accurate assessment of body fat distribution compared to BMI and WC, making it a valuable tool for evaluating infertility, further research is now needed to determine the impact of interventions based on RFM measurements.
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http://dx.doi.org/10.1038/s41598-025-89417-y | DOI Listing |
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Centre d'Assistance Médicale à la Procréation, Hôpital des Bluets, Paris, France.
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Hospital of Chengdu University of Traditional Chinese Medicine, Chengdu, China.
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Department of Health Information Management, School of Health Management and Information Sciences, Iran University of Medical Sciences, Tehran, Iran.
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Ahvaz Jundishapur University of Medical Sciences, Diabetes Research Center, Health Research Institute, Ahvaz, Iran.
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