Does abnormal weight affect sperm quality? A case-control study based on bioelectrical impedance analysis

Weight gain can lead to metabolic, circulatory, and systemic changes. Obesity has been confirmed to induce various physical and mental illnesses. The relationship between abnormal weight and male fertility has become a research focus, although the findings regarding their correlation remain controversial.

A case-control study based on bioelectrical impedance analysis was conducted to evaluate the correlation between abnormal body weight and sperm quality and to confirm the degree of impact of abnormal body weight on sperm quality.

A retrospective analysis was conducted of 137 men who underwent fertility assessment at the Guangdong Provincial Reproductive Science Institute (Guangdong Provincial Fertility Hospital) between April 2024 and April 2025. Sperm parameters, body composition parameters, age, height, and other relevant information were extracted and analyzed. One hundred and thirty-seven males were divided into three groups according to their sperm quality: normal sperm group (Group A, n = 29), oligoasthenozoospermia group (Group B, n = 58), and azoospermia group (Group C, n = 50). According to the presence of sperm, they were divided into two groups: sperm group (AA group, n = 87) and azoospermia group (BB group, n = 50). The differences between these groups were compared, and the inherent connections and patterns between the indicators were explored through Pearson correlation analysis and partial correlation analysis; to determine the correlation between weight and sperm quality; and to evaluate the influence of weight on sperm quality.

The body composition parameters of the different sperm count groups (A, B, and C) were similar and showed no differences. However, there were certain differences in age, height, weight, protein (P), minerals (M), InBody score (IBS), percent body fat (PBF), total body water (TBW), intracellular water (ICW), body fat mass (BFM), body cell mass (BCM), soft lean mass (SLM), and skeletal muscle mass (SMM) between groups AA and BB. They did not follow a linear distribution, and the KMO and Bartlett sphericity tests suggested that they followed a spherical distribution (KMO = 0.775, sig = 0.000), which was related to the presence of sperm. Factor analysis revealed that weight, PBF, height, age, and IBS were the five key influencing factors. After combining height and weight factors, we found the age, IBS, and PBF were more decisive and sensitive than body mass index (BMI).

Body composition has a certain impact on sperm quality, especially age, IBS, and PBF, which may be more accurate than BMI. Bioelectrical impedance analysis could effectively assist in the judgment and has the potential to predict sperm parameters.