ArticleFrontiers in nutrition2025
Does abnormal weight affect sperm quality? A case-control study based on bioelectrical impedance analysis.
Article in Frontiers in nutrition, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- Metals/Metalloids Profile in Seminal Plasma/Serum of Patients with Asthenozoospermia/Oligozoospermia: Correlation with Semen Quality.Biological trace element research · 2026Article
- Article
- A modular, mechanism-informed biomarker panel for asthenozoospermia based on integrative sperm proteomics.Frontiers in endocrinology · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: 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. Objective: 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. Methods: 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, Results: 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). Conclusion: 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.
Indexed as
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.