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Association between current relative fat mass and history of female infertility based on the NHANES survey
Dong Liu1,2, Xiaoyan Luo1,2, Kunyan Zhou3,4
1Department of Obstetrics and Gynecology, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China.
Abstract:
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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