Associations between Routine Systemic Biochemical Indices and Semen Quality: A Cross-Sectional Study in Men Undergoing Health Examination

Associations between Routine Systemic Biochemical Indices and Semen Quality: A Cross-Sectional Study in Men Undergoing Health Examination | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Associations between Routine Systemic Biochemical Indices and Semen Quality: A Cross-Sectional Study in Men Undergoing Health Examination Xihuan Ren, Lin Ni, Yun Fu, Gang An, Xiangqun Fan, Dianliang Lin This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8982176/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract Background To evaluate associations between routinely measured systemic biochemical indices and semen quality parameters in a real-world health-check population. Methods This cross-sectional observational study included 264 men aged 21–60 years who underwent standardized health examinations, including semen analysis and comprehensive biochemical testing. Semen parameters were evaluated according to WHO reference limits (2010 edition), and all outcomes were analyzed as continuous variables. Biochemical indices were categorized into predefined domains reflecting metabolic status, oxidative/antioxidant balance, and electrolyte–osmotic homeostasis. Associations were assessed using correlation analyses with false discovery rate (FDR) adjustment to control for multiple testing. Results Weak inverse correlations were observed between semen volume or motility and age, BMI, diastolic blood pressure, glucose, and triglycerides. Serum magnesium showed a modest positive association with progressive motility, and unconjugated bilirubin was positively associated with normal morphology. Serum globulin levels demonstrated a small positive correlation with normal morphology. Serum osmolality exhibited consistent associations with DNA fragmentation index (DFI), high DNA stainability (HDS), and morphology. Most effect sizes were small, and associations not surviving FDR adjustment were interpreted as exploratory. Conclusion In this health-check population, routine systemic biochemical indices showed modest correlations with semen parameters. Given the cross-sectional design, findings should be interpreted as associative rather than causal. These results are hypothesis-generating and warrant longitudinal validation to clarify temporal relationships and biological mechanisms. Health sciences/Biomarkers Health sciences/Diseases Health sciences/Medical research Biological sciences/Physiology Semen quality Male reproductive health Cross-sectional study Systemic biomarkers Metabolic status Osmolality Figures Figure 1 Figure 2 Figure 3 1. Introduction Male infertility and reduced semen quality have become major global public health problems. [ 1 , 2 ] Epidemiologic summaries indicate that sperm concentration, motility, and morphology among men of reproductive age have decreased globally consistently. [ 2 , 3 ] The falling sperm counts and concentration have since been replicated by European and American studies. [ 1 , 4 , 5 ] A recent systematic review and meta-analysis (1973–2018) have estimated that the mean sperm count of men worldwide has declined more than 50% in the past 50 years, with the decline accelerating since the turn of the 21st century. [ 2 , 5 ] Multiple regions in China also reported a stunning deterioration of young men's semen quality from 2001 to 2015. [ 6 ] Accumulating epidemiological evidence suggests a temporal decline in several semen quality parameters across different regions, although the magnitude and consistency of this trend remain subject to methodological debate. Given that spermatogenesis is regulated by a complex interplay of endocrine signaling, metabolic homeostasis, oxidative balance, and immune regulation, understanding systemic correlates of semen quality has become increasingly relevant from both clinical and public health perspectives. [ 1 ] Rather than focusing exclusively on overt reproductive disorders, identifying physiological markers associated with variation in semen parameters within the general population may help contextualize male reproductive health within broader systemic processes. Several studies have extensively demonstrated that common cardiovascular and metabolic diseases (e.g., dyslipidemia, obesity, hyperglycemia, and high blood pressure) are linked to the loss of sperm quality. Obesity, impaired glucose regulation, and chronic low-grade inflammation have been associated with alterations in endocrine signaling and increased oxidative stress. These systemic disturbances may influence the testicular microenvironment, mitochondrial activity in spermatozoa, and chromatin stability. However, most existing evidence derives from selected clinical populations, and the extent to which routine metabolic indicators reflect subtle variation in semen parameters within generally healthy populations remains unclear. [ 7 , 8 ] Recent evidence indicates that an increase in body mass index and fasting glucose has a direct correlation to decreased motile sperm and increased sperm DNA fragmentation. [ 9 , 10 ] Dyslipidemia, including high low-density lipoprotein cholesterol (LDL-C) and apolipoprotein B, has strong correlations with sperm dysfunction. The lipids may injure mitochondria and produce reactive oxygen species (ROS) and thus disable the motility and chromatin integrity of the sperm. [ 3 , 11 ] Emerging evidence has suggested potential associations between certain micronutrient and antioxidant-related markers—such as magnesium and bilirubin—and semen parameters. Magnesium is involved in ATP-dependent cellular processes and mitochondrial function, while bilirubin possesses endogenous antioxidant properties. These biological roles provide a theoretical basis for potential relationships with sperm motility and chromatin integrity; however, direct mechanistic pathways linking circulating concentrations of these markers to semen quality remain to be fully elucidated. [ 12 , 13 ] This pattern is consistent with magnesium’s known roles in ATP production, maintaining mitochondrial function, and reducing inflammation. [ 14 ] Analogously, bilirubin too, once thought in the past simply as a marker of liver function, was discovered by research to be strongly positively related to semen volume and motility. [ 15 ] These observations may reflect bilirubin’s antioxidant properties, which may be associated with reduced oxidative damage to sperm DNA. They also broaden our understanding of male reproductive health by suggesting that even mild metabolic or biochemical disturbances can influence fertility. Quality of semen has been a universal concern traditionally and has been hypothesized to have many causes including environmental contamination and lifestyle modifications (e.g., daily use of cigarette or heavy alcohol consumption). [ 16 ] Although numerous studies have examined individual metabolic or inflammatory factors in relation to male fertility, relatively few investigations have systematically evaluated a broad panel of routinely measured biochemical indices within a standardized health-check setting. Importantly, most prior research has focused on predefined hypotheses involving specific pathways (e.g., obesity, diabetes, oxidative stress), whereas less attention has been given to exploratory pattern detection across comprehensive clinical biomarker profiles. Second, few large multivariable studies in preventive health-check populations have systematically evaluated the associations between routine metabolic, biochemical, and antioxidant parameters and semen quality, highlighting the need for broader exploratory analyses. Accordingly, the present study was designed as a biologically stratified, hypothesis-generating cross-sectional analysis aimed at identifying patterns of association between routine health-check indices and semen parameters in a real-world clinical population. Rather than testing a single predefined mechanistic hypothesis, we predefined three biologically grounded domains—(1) metabolic status, (2) oxidative/antioxidant balance, and (3) electrolyte–osmotic homeostasis—and examined whether systemic biochemical indicators within these domains demonstrate statistically detectable correlations with semen quality measures. Indices not directly mapping onto these domains were analyzed in an exploratory manner. Specifically, the primary aim of this study was to evaluate whether routinely measured systemic biochemical indices are statistically associated with semen quality parameters in a standardized health-check population. The objective was not to establish causal relationships, but to characterize potential associative signals that may inform future longitudinal or mechanistic studies. Given the cross-sectional design and the multiplicity of evaluated indices, findings within the three predefined biological domains were interpreted in the context of their underlying physiological rationale, whereas remaining associations were treated as exploratory signals requiring further validation. 2. Materials and Methods 2.1 Study Design and Participants This cross-sectional study enrolled men aged 21–60 years who completed routine health examinations—including full biochemical testing and semen analysis—at a tertiary medical center between January 2023 and December 2024. Inclusion required a complete physical examination record and successful completion of semen analysis on the same day. Exclusion (by protocol) included: past history of epididymal/testicular surgery, currently undergoing fertility treatment, serious chronic illness, or inadequate semen sample for analysis (e.g., incomplete collection, contamination). After applying inclusion and exclusion criteria and excluding records with missing core variables, 264 men were included in the final analysis. To address methodological rigor, we additionally evaluated whether the sample size was adequate for detecting clinically meaningful correlations. As this was an analysis of available health check-up data, a formal a priori sample size calculation was not performed. A post-hoc power analysis indicated that with 264 participants, the study had approximately 80% power (α = 0.05, two-tailed) to detect Pearson correlation coefficients of |r| ≥ 0.17. This should be considered when interpreting weaker correlations. Given that more than 40 biochemical variables were examined, many observed correlations below this threshold (e.g., |r|<0.10) should be interpreted cautiously as they may represent weak associations with limited biological relevance. This limitation was considered in the interpretation of results and further highlighted in the Discussion. Because the study involved retrospective analysis of routinely collected clinical data, no experimental interventions or comparisons were performed. 2.2 Laboratory and Clinical Measurements Upon morning visit, every participant received a standard health examination procedure. Following verification by a nurse that the participant had fasted for a minimum of 8 hours, the participant's height and weight were measured and BMI determined as a ratio of weight (kg) to height squared (m²). Following a five-minute sitting rest, the participant was measured for blood pressure employing an automatic sphygmomanometer: SBP and DBP, each in duplicate and the mean was taken for analysis purposes. Hypertension was diagnosed as SBP ≥ 140 mmHg, DBP ≥ 90 mmHg, or a history of diagnosed earlier. Fasting venous blood samples were drawn and analyzed in the hospital’s central laboratory using a Roche Cobas 8000 system. General metabolic testing included measurements of fasting glucose, total cholesterol, triglycerides, HDL-C, LDL-C, ApoA-1, and ApoB. Each of these was done by enzymatic methods or immunoturbidimetric assay, as directed by manufacturer's protocols. To provide a more complete biochemical profile for comparison with semen quality, we also analyzed stored blood samples. These included electrolytes (sodium, potassium, chloride, calcium, phosphorus, and magnesium), liver enzymes (ALT, AST, GGT, ALP), serum protein (total protein, albumin, globulin, and A/G ratio), bilirubin metabolism markers, renal function markers (urea, creatinine, uric acid), and lipid and glycemic indices. Concurrently, renal function tests like urea, creatinine, and uric acid and acid-base status markers like combining capacity of carbon dioxide, calculated anion gap, and serum osmolality, also were run in the same analyzer under strict internal and external quality control protocols. All biochemical analyses were performed within approximately 2 hours after venipuncture under standardized laboratory quality control procedures to minimize pre-analytical variation. 2.3 Semen Analysis Semen samples were collected after 2–7 days of sexual abstinence. Semen analysis was performed according to the World Health Organization (WHO) 2010 guidelines. DNA fragmentation index (DFI) and high DNA stainability (HDS) were assessed using the sperm chromatin structure assay (SCSA). All SCSA procedures, including sample processing, staining, and flow cytometric analysis, were conducted according to the standard protocol described by Greenberg et al. [ 17 ] For semen quality, we followed WHO reference criteria, using the WHO lower reference limits (sperm concentration ≥ 15×10⁶/mL, progressive motility ≥ 32%, total motility ≥ 40%, and normal morphology ≥ 4%) as comparative thresholds. Semen volume, percentage non-progressive motility, percentage immotile sperm, DNA fragmentation index (DFI), and high DNA stainability (HDS) were utilized as continuous outcome measures. For subgroup summaries, participants were classified as having semen parameters within WHO reference limits versus having ≥ 1 parameter below the WHO lower reference limit; these categories are used for descriptive purposes and do not imply diagnostic “normal/abnormal” labeling. For correlation analysis, each of the semen variables was treated as an independent continuous variable. 2.4 Statistical Analysis All statistical analyses were performed using R (version 4.3.1) and cross-validated in SPSS (version 26.0) to ensure computational consistency. Continuous variables were summarized as mean ± standard deviation (SD). Normality of continuous variables was assessed using the Shapiro–Wilk test prior to selection of parametric or non-parametric statistical methods. Group comparisons were conducted using appropriate parametric or non-parametric tests according to data distribution. Associations between semen parameters and clinical or biochemical indices were evaluated using Pearson or Spearman correlation analyses as appropriate, and correlation coefficients were reported together with two-sided P values. Given the evaluation of multiple biochemical variables—primarily categorized into the three predefined biological domains (metabolic status, oxidative/antioxidant balance, and electrolyte–osmotic homeostasis), with additional indices analyzed exploratorily—multiplicity was addressed using the Benjamini–Hochberg procedure to control the false discovery rate (FDR). For each semen parameter, P-values derived from the corresponding set of hypothesis tests were adjusted, and results were considered statistically significant at an FDR-adjusted P < 0.05. To minimize the risk of chance findings from extensive correlation screening, results that did not meet FDR significance were explicitly treated as exploratory and were interpreted in conjunction with effect sizes and biological plausibility rather than nominal P-values alone. 2.5 Ethical Considerations This study was approved by the Ethics Committee of Fujian Maternity and Child Health Hospital (Approval No. 2024KY077). The requirement for individual informed consent was waived for this retrospective analysis, as confirmed by the ethics committee, due to the use of anonymized data obtained from routine health check-ups. 3. Results 3.1.1 Baseline Characteristics and Between-Group Difference Table 1 lists the baseline clinical and biochemical characteristics of the participants. Among the 264 men included in the final analysis, 194 (73.5%) demonstrated semen parameters within the WHO reference ranges, and 70 (26.5%) exhibited at least one parameter below the lower reference limit. As expected, men in the below-reference-limit group had worse semen outcomes across all major measures, including concentration, motility, morphology, DFI, and HDS. These results support the internal consistency of the semen quality measures and confirm that our classification criteria were appropriate (Fig. 1 ). Table 1 Baseline characteristics of men with and without WHO-defined low semen quality Variable Within-reference-limits Group (n = 194, Mean ± SD) Below-reference-limit Group (n = 70, Mean ± SD) P -value Cohen's d Semen Volume 3.69 ± 1.38 3.45 ± 1.62 0.050 0.161 Sperm Concentration 48.54 ± 24.21 33.64 ± 25.81 < 0.001 0.61 Progressive Motility(%) 51.19 ± 11.37 32.28 ± 12.15 < 0.001 1.629 Non-progressive Motility(%) 4.24 ± 2.49 6.57 ± 6.91 0.035 -0.568 Immotile Sperm(%) 44.54 ± 11.45 60.86 ± 13.40 < 0.001 -1.354 Total Motility(%) 55.62 ± 11.50 39.56 ± 14.21 < 0.001 1.364 Normal Morphology(%) 12.11 ± 6.29 8.76 ± 4.79 < 0.001 0.553 DFI(%) 15.05 ± 7.85 23.91 ± 12.28 < 0.001 -0.979 HDS(%) 5.71 ± 4.18 6.90 ± 4.25 0.017 -0.276 Magnesium 0.895 ± 0.073 0.877 ± 0.053 0.080 0.266 GGT 43.546 ± 37.714 34.765 ± 21.818 0.124 0.256 LDL Cholesterol 3.315 ± 0.908 3.119 ± 0.865 0.308 0.218 LDH 173.133 ± 32.596 166.755 ± 26.94 0.177 0.204 Chloride 104.504 ± 1.933 103.79 ± 2.074 0.014 0.362 Age 31.326 ± 4.4 32.246 ± 6.556 0.761 -0.182 Height 173.728 ± 5.804 172.758 ± 6.32 0.266 0.163 Creatinine 75.81 ± 12.986 73.901 ± 9.817 0.488 0.156 Osmolality 279.055 ± 3.362 278.587 ± 3.004 0.283 0.143 BMI 25.278 ± 3.572 25.765 ± 4.081 0.642 -0.131 AST 24.641 ± 15.019 22.901 ± 8.725 0.725 0.127 Sodium 139.658 ± 1.625 139.449 ± 1.675 0.611 0.127 Notes: Data are presented as mean ± SD. P -values were calculated using independent t-test or Mann–Whitney U test as appropriate. Cohen’s d indicates effect size (small ≥ 0.2, medium ≥ 0.5, large ≥ 0.8). Abbreviations: BMI, body mass index; AST, aspartate aminotransferase; GGT, gamma-glutamyl transferase; LDL, low-density lipoprotein; LDH, lactate dehydrogenase; DFI, DNA fragmentation index; HDS, high DNA stainability. 3.1.2 Comparison of Physical Examination Indices Difference Analysis The comparison of routine clinical and biochemical indices revealed that most variables did not differ significantly between groups. Anthropometric measurements such as age, height, and BMI were broadly similar, suggesting that general demographic characteristics were unlikely to account for the observed disparities in semen quality. For metabolic and liver-related markers such as fasting glucose, triglycerides, LDL-C, ALT, AST, and GGT, differences between groups were small and not statistically significant. Some indices exhibited slight directional trends consistent with patterns reported in earlier literature. To further characterize the nature of group differences, continuous semen parameters were compared in detail. Men in the below-reference-limit group showed noticeably higher proportions of immotile and non-progressive sperm, along with clearly elevated DFI levels (mean 23.9% vs. 15.1% in the within-reference-limits group), underscoring substantial impairment in both sperm motility and chromatin integrity. In contrast, the below-reference-limit group had lower semen volume and reduced progressive and total motility, as well as poorer morphology. Several of these differences showed medium to large effect sizes. These observations align with recognized clinical patterns of concurrent decline across multiple semen indices and support the internal validity of the dataset. Most biochemical markers did not differ significantly between the groups, although a few showed trends that were biologically reasonable. For example, serum magnesium showed a borderline lower mean level in the below-reference-limit group, consistent with its known physiological role in energy metabolism and sperm motility, though the difference did not reach statistical significance. Similarly, a few markers—such as HDL-cholesterol, triglycerides, and some liver enzymes—showed weak trends that were broadly in line with previous findings on metabolism and male fertility. Although these trends were small and should not be over-interpreted, they offer useful context for the multivariable analyses presented later. 3.2 Association between Demographic Traits, Basic Physical Measures and Semen Parameters We subsequently compared correlations of demographic characteristic of participants (age) to uncomplicated physical measures (weight, height, BMI, SBP, DBP) and indices of semen quality. (Figure 3) 3.2.1 Age Age had a weak but significant inverse association with most of the semen quality parameters. Precisely, age was inversely connected to semen volume (r = -0.166, P < 0.01), which indicated a tendency toward a declining volume of ejaculate with increasing age. Age was positively correlated with sperm DNA fragmentation index (DFI) (r = 0.167, P < 0.01), indicating that older individuals tended to have higher levels of sperm DNA fragmentation. Age was inversely connected very weakly to the percentage of sperm concentration (r =0.119), progressively motile sperm (r =-0.052) and total motility (r =-0.083), but was positively connected to the percentage of immotile sperm (r =0.081). Taken together, these findings suggest that even within this relatively young cohort, age may have a small adverse effect on semen volume, motility, and DNA integrity. Age, in relation to other clinical parameters, was inversely related to serum calcium (r = -0.252, P < 0.001), and to the total protein (r = -0.181, P < 0.001), and to albumin (r = -0.212, P < 0.001) but positively to fasting glucose (r = 0.258, P < 0.001). Data are likely to show age-dependent changes in metabolism, however there are not known specific intervening mechanisms how these have impacts on semen quality. 3.2.2 Blood Pressure Semen parameters likewise presented weak inverse correlations with levels of blood pressure. Remarkably, higher DBP correlated significantly with declining semen volume (r = -0.171, P = 0.005). That is, individuals with relatively higher blood pressure had a lesser ejaculate volume. Although this relationship has been weak, it has physiological plausibility: hypertension may impair vascular endothelial function at a systemic level, which may be associated with reduced blood supply to accessory glands such as the prostate and seminal vesicles, potentially reflecting reduced secretory output and lower semen volume [23] . In fact, one large study has identified that hypertensive men have significantly lower mean semen volume and poorer sperm motility than normotensive men [23] . We discovered in our study that there was only a weak correlation between DBP and semen volume; there was no correlation between systolic blood pressure and semen parameters. This may be because most subjects had normal or slightly elevated blood pressure, which made its visible impact precluded. Of note is the fact that DBP was significantly correlated with GGT (r = 0.261, P < 0.001), total protein (r = 0.249, P < 0.001), and globulin (r = 0.239, P < 0.001). Because these markers reflect liver function and inflammation, data suggest that cardiovascular or metabolic conditions might affect reproductive health through several indirect pathways. This pattern hints at a link between cardiovascular status and male fertility. Conditions such as hypertension may gradually influence semen parameters over time. 3.2.3 Height, Weight, and BMI Height is weakly associated with parameters such as sperm concentration and motility. Weight and BMI were highly collinear (r = 0.886, P < 0.001). These both had negative correlations with semen volume (weight: r = -0.055; BMI: r = -0.115), the negative correlation of the latter being slightly stronger. Unfortunately, it did not reach statistical significance. Weight and BMI also showed weak negative correlations with progressive motility (weight: r = -0.032; BMI: r = -0.087) and with total motility (weight: r = -0.041; BMI: r = -0.076), and weak positive correlations with the proportion of immotile sperm (weight: r = 0.037; BMI: r = 0.078). Although our sample size was modest, we noticed a small trend suggesting that higher BMI might be linked to reduced semen volume and total motility. This trend is consistent with findings from previous large-scale studies. Because weight and BMI were also related to several metabolic and liver enzyme markers, their influence on semen quality may operate through broader metabolic mechanisms. [18] For example, BMI was also highly positively correlated with alanine aminotransferase (ALT, r = 0.496, P < 0.001), aspartate aminotransferase (AST, r = 0.350, P < 0.001), gamma-glutamyl transferase (GGT, r = 0.374, P < 0.001), uric acid (r = 0.361, P < 0.001), triglycerides (r = 0.400, P < 0.001), and fasting glucose (r = 0.235, P < 0.05). Conversely, BMI was strongly inversely related to the ratio of AST/ALT (r = -0.465, P < 0.001) and HDL cholesterol (r = -0.428, P < 0.001). They suggest that BMI as a sign of central metabolic health in our patients has effects on metabolic and liver function, and has an indirect impact on semen quality. 3.3 Association between Electrolyte and Acid-Base Balance Indices and Semen Parameters 3.3.1 Potassium, Sodium, Chloride Potassium, and chloride serum levels and sodium each possessed very weak associations with all indices of semen quality (concentration, motility, morphology, DFI, HDS), each having absolute correlation coefficients < -0.1 and no direct significant correlations. This indicates that in physiological ranges, serum electrolyte changes likely have little direct impact upon semen quality. 3.3.2 Calcium, Magnesium, Phosphate Calcium was very weakly positively related to semen volume (r = 0.072), sperm concentration (r = 0.087), and normal morphology rate (r = 0.142, P < 0.001). Magnesium was also extremely weakly directly related to semen parameters. Again, however, magnesium was positively related to percentage progressively motile sperm (r = 0.210, P < 0.001). Despite the small coefficient, this would suggest that perhaps there is a very weak positive impact of magnesium on motility of sperm. There was no significant relation we could identify between phosphorus (as serum phosphate) and the semen parameters. 3.3.3 Combining Capacity of CO 2 and Anion CO 2 combining capacity (indicator of acid-base status) was significantly and positively (r = 0.196, P < 0.001) correlated with normal morphology. CO2 combining capacity was strongly and inversely correlated with the anion gap (r = -0.523, P < 0.001), consistent with expected physiological relationships. However, the anion gap was inversely correlated with normal morphology (r = -0.142, P < 0.05). A high anion gap could indicate the accumulation of metabolic acidosis or a surplus of unmeasured anions; its inverse correlation with normal morphology may be an important finding that warrants further attention. 3.4 Relationship between Indices of Renal Function and Semen Parameters The renal function indices (urea, creatinine, uric acid, urea-to-creatinine ratio) demonstrated poor correlations (|r| < 0.1) between the major semen parameters (sperm motility, morphology, sperm concentration). It implies that, in our population, variations of renal function in the ordinary range are not related to semen quality in any obvious direct manner.Uric acid is more connected to metabolic markers. Uric acid was highly correlated with weight (r = 0.355, P < 0.001), BMI (r = 0.361, P < 0.001), ALT (r = 0.177, P < 0.05), AST (r = 0.181, P < 0.05), and triglycerides (r = 0.332, P < 0.001). It implies that uric acid has a larger role as an element of the metabolic syndrome spectrum, as opposed to an autonomous identifier of renal function, and it influences, in an indirect manner, reproductive outcome along the metabolic routes. 3.5 Association between Liver Enzyme Indices and Semen Parameters For liver enzymes, pre-treatment AST or ALT levels did not exhibit significant correlations with semen parameters. But ALT and AST also exhibited significant correlations with weight, BMI, triglycerides, and other metabolic parameters (explained above, ALT vs BMI r = 0.496). AST/ALT ratio was significantly and inversely correlated with weight (r = -0.426, P < 0.001) and BMI (r = -0.465, P < 0.001), and positively correlated with progressive motility (r = 0.125, P < 0.05) and total motility (r = 0.121, P < 0.05). AST/ALT ratio decreased in non-alcoholic fatty liver disease (NAFLD); liver damage due to fatty liver (present as decreased AST/ALT ratio) may be implicated in sperm motility defect. It may be an indirect impact via systemic metabolic disorder and oxidative stress. Gamma-glutamyl transferase (GGT) was strongly related to DBP (r = 0.261, P < 0.001), weight (r = 0.344, P < 0.001), BMI (r = 0.374, P < 0.001), triglycerides (r = 0.534, P < 0.001), as well as fasting glucose (r = 0.150, P < 0.05), and each further validates the application of GGT as a marker for metabolic disease. GGT was directly but weakly related to semen parameters; alkaline phosphatase had poor correlations. 3.6 Protein Metabolism and Nutrition Indices versus Semen Parameters 3.6.1 Total Protein, Albumin, Globulin, A/G Ratio There was a significant and positive correlation between rate of normal morphology and total protein (r = 0.165, P < 0.05). There was highly significant positive correlation between calcium and total protein (r = 0.510, P < 0.001), which indicates interrelationship between markers of nutrition and biochemical status. Albumin was weakly negatively correlated by itself with normal morphology (r = -0.052), and albumin-to-globulin ratio (A/G ratio) was negatively correlated with normal morphology (r = -0.193, P < 0.05). A decreased A/G ratio will likely imply chronic inflammation or liver disease; its negative correlation with normal sperm morphology may perhaps imply that systemic inflammatory state can exert an undesirable effect on spermatogenesis. Globulin, in contrast, was positively related to normal morphology (r = 0.197, P < 0.001). Globulin is a key component of immunoproteins, and the positive relation of globulin to sperm morphology is a curious finding. It may plausibly suggest that there must be some degree of immunocyte function to preserve the testicular microenvironment, or may relate to one of the components of the seminal plasma which carries immunoglobulins. Speculative explanations, both, and other work must be performed prior to the etiologic factors being certain. 3.7 Association of Bilirubin Metabolism and Semen Importantly, we first identified a positive correlation between the pattern of unconjugated bilirubin and semen quality parameters. In particular, we observed that high concentrations of unconjugated bilirubin possessed an incrementally increasing level of normal sperm morphology (r = 0.117, nominal P < 0.05 (did not remain significant after FDR correction). As a natural antioxidant, a higher level of bilirubin may have countered the impact of oxidative stress and, therefore, spared sperm morphology. Bilirubin was nonsignificantly and weakly related to the other semen parameters (e.g., sperm motility and concentration). 3.8 Association between Glycemic and Lipid Metabolic Indices and Semen Parameters 3.8.1 Fasting Glucose Fasting glucose in the bloodstream was inversely related to semen volume (r = -0.068, P < 0.05). It was also (weak) negatively related to progressive motility (r = -0.082, P < 0.05) and to complete motility (r = -0.122, P < 0.05). Based on these findings, it can be concluded that at nondiabetic level, elevated glucose in the bloodstream may have a very minimal harmful effect on motility of sperm. Although the magnitude of these relations is low, direction conforms to evidence that diabetic men have deficient semen parameters. [19] 3.8.2 Lipid Profile Triglycerides were inversely correlated with semen volume (r = -0.144, P < 0.05), and strongly with BMI, liver enzymes, and other measures of metabolism (as reported already, above). We found that in men with high levels of triglycerides, percentage progressively motile sperm (r = -0.085) and total motility (r = -0.080) are slightly reduced; in our patient group, these reductions, although statistically significant, were slender in degree. Elevated levels of cholesterol and triglycerides have been found to have a detrimental impact on sperm motility. [20] Total cholesterol had weak positive correlations with semen parameters. Total cholesterol had strong, positive correlations with apolipoprotein B (ApoB, r = 0.880, P < 0.001) and LDL-C (r = 0.843, P < 0.001), the latter being an atherogenic lipid of first importance.Apolipoprotein A-1 was strongly positively correlated with HDL-C (r = 0.876, P < 0.001), as would be predicted for its role as the chief apolipoprotein of HDL. ApoA-1 was not significantly directly correlated with semen parameters but was inversely correlated with HDS (r = -0.112, P < 0.01). HDL-C was positively correlated with volume of semen (r = 0.109, P < 0.05). This is an unusual positive correlation between a marker of the lipid profile and semen quality, the mechanism is unclear; it may be secondary to the antioxidant and anti-inflammatory effects of HDL.LDL cholesterol was highly collinear with total cholesterol and ApoB, and had very poor direct correlations with semen parameters. 3.9 Relationship between Cardiac Enzyme Profile and Other Indices and Semen Characteristics Lactate dehydrogenase (LDH) was highly correlated with DBP (r = 0.245, P < 0.001), BMI (r = 0.289, P < 0.001), ALT (r = 0.394, P < 0.001), and AST (r = 0.436, P < 0.001),which is Consistent with physiological function. On the other hand, LDH was very weakly correlated directly with semen parameters. LDH is an important glycolytic enzyme and it is found highly in tissues like skeletal muscle, myocardium, and testes; therefore, its variation has more to do with metabolic factors than with semen quality per se. Creatine kinase and its isoenzymes also demonstrated equally poor correlations with semen parameters. However, we noted that osmotic pressure was positively correlated with normal sperm morphology (r = 0.171, P < 0.05) and the DNA fragmentation index (DFI; r = 0.187, P < 0.05), and negatively correlated with high DNA stainability (HDS; r = −0.171, P < 0.05). These correlations may reflect the effects of a hypotonic environment, which may be associated with sperm swelling and deformity, reduced motility, and disruption of the plasma membrane. 4. Discussion In this cross-sectional analysis of 264 men undergoing routine health screening, we evaluated correlations between semen parameters and systemic biochemical indices categorized into predefined biological domains. Overall, associations were modest in magnitude, and most effect sizes were small, suggesting subtle rather than clinically pronounced relationships. 4.1 Semen Parameter Internal Consistency Other than the expected internal consistency among semen parameters, one notable observation in our dataset was the preliminary signal involving serum chloride showed a nominally significant difference ( P = 0.0139) before multiple testing correction. However, after FDR adjustment, this difference was no longer statistically significant. While this precludes a definitive conclusion, the observed directional trend may warrant further investigation in larger cohorts. Chloride is known to participate in cellular osmoregulation and membrane stability in general physiological contexts. [21] However, in the context of the present cross-sectional analysis, our findings should not be interpreted as evidence of a direct mechanistic effect of chloride on sperm function. Rather, the observed association may reflect broader systemic physiological states that warrant further mechanistic exploration. Given the limited sample size and modest effect size observed, this finding remains exploratory and requires validation in larger cohorts. 4.2. Age and Blood Pressure Weak Associations with Fertility Age showed low negative correlations with semen volume and positive with DFI, as would be predicted by the general view that with age, reproductive function slowly deteriorates. Blood pressure-diastolic pressure, in particular-showed inverse correlations with semen volume and no strong correlation with basic semen parameters of concentration, motility, and morphology. This suggests that, per se, pressure in the bloodstream is unlikely to be a cause of reduced semen quality. Blood pressure may reflect broader cardiovascular and metabolic status. However, the present data do not allow inference regarding specific intermediary mechanisms linking vascular parameters to semen quality. 4.3 Intermediate role of BMI in the Metabolic Syndrome Network Because the correlations of BMI with semen parameters were in general quite weak in this study, none of the observed associations reached a clinically meaningful magnitude. While metabolic dysfunction has been clearly aligned with male reproductive impairment in the literature, results from this investigation indicate that BMI in and of itself may not be a key determinant of semen quality among a generally healthy screening population. [18] Here, BMI related more strongly to metabolic markers such as ALT, AST, GGT, triglycerides, and uric acid, suggesting that BMI may reflect metabolic status rather than directly mediate impaired spermatogenesis. [22] In this cohort, BMI showed only weak associations with semen parameters, indicating that adiposity alone may not be a dominant correlate of semen variation within a generally healthy screening population. 4.4 Magnesium and Bilirubin: Potential Protective Associations Magnesium is recognized as a cofactor in numerous metabolic processes, including ATP-related pathways and mitochondrial function. [23] Nevertheless, the associations observed in this study do not establish a causal link between serum magnesium levels and sperm metabolism, and should be interpreted as exploratory correlations requiring experimental validation. Previous studies have reported correlations between serum magnesium and sperm motility; however, whether circulating magnesium levels reflect seminal plasma concentrations remains uncertain. Wong et al. determined that seminal plasma concentrations of magnesium are highly correlated to sperm number and motility and hypothesized that magnesium has effects upon sperm flagellar movement and ATP synthesis. [24] Several animal studies have suggested that magnesium deficiency is associated with altered male reproductive function. [25] Although magnesium participates in ATP-related cellular processes, the modest correlation observed here does not justify clinical recommendations regarding supplementation. The clinical relevance of circulating magnesium concentrations for semen quality remains uncertain and requires prospective validation. [26] During the last decades, many investigations have been carried out to determine whether antioxidant supplementation is able to enhance semen quality. [27] Spermatozoa are rich in polyunsaturated fatty acids and are very sensitive to ROS. High levels of ROS may promote lipid peroxidation and DNA fragmentation, thus impairing sperm function. [28] In physiological conditions, seminal plasma contains a variety of antioxidants including vitamin C, vitamin E, glutathione, superoxide dismutase, etc. which neutralize ROS. [29] Bilirubin is an endogenous antioxidant that is associated with modulation of oxidative stress. [30] In our study, total bilirubin was correlated with normal sperm morphology; however, its functional relevance to sperm chromatin integrity remains to be clarified. Intuitively, moderate levels of bilirubin may be associated with reduced oxidative stress in tissues such as the testes against oxidative damage while very high levels of bilirubin may become pathologic and interfere with ROS signaling across sperm capacitation. [13,27,31] These findings should be interpreted cautiously and do not establish a basis for therapeutic intervention. Further studies incorporating direct oxidative stress measurements are required to determine whether circulating bilirubin levels have functional relevance for sperm biology. 4.5 Influence of Serum Protein Indices in Relation to Semen Quality In the present study, serum protein indices-total protein, albumin-to-globulin ratio (A/G ratio), and globulin-exhibited small but significant correlations with sperm morphology. Total protein and globulin revealed weak but statistically significant positive correlations with the percentage of morphologically normal spermatozoa. Though the effect sizes were small, these associations may reflect systemic protein status without establishing a direct relationship with spermatogenesis. One hypothesis concerns the functional composition of the globulin fraction. [32] Globulin represents a heterogeneous mixture of proteins, including immunoglobulins, hormone-binding proteins - such as sex hormone-binding globulin, SHBG - and nutrient transport proteins, including transferrin. [33] A number of these constituent proteins have recognized roles in male reproductive physiology. Thus, SHBG is essential to the regulation of circulating testosterone bioavailability; reduced levels of SHBG commonly occur in men with metabolic syndrome and have been linked with impaired sperm morphology. [34] Similarly, transferrin is involved in the transport of trace elements, including iron, which are required for normal testicular function and spermatogenesis. [35] Although the current study did not measure these subfractions directly, the positive association of globulin with sperm morphology observed may reflect, at least indirectly, the biological activity of these proteins. By contrast, the inverse correlation between the A/G ratio and normal morphology may indicate physiological relevance, since disturbances in the relative distribution of albumin and globulin as reflected by a lower A/G ratio may reflect systemic inflammatory or metabolic alterations. [36] However, the present findings do not allow inference regarding downstream testicular oxidative stress or spermatogenic impairment, and such mechanistic pathways remain speculative without direct biological assessment. However, these interpretations remain purely speculative given the cross-sectional nature of the study and lack of direct inflammatory or hormonal measurements. Indeed, additional studies combining detailed immunologic and endocrine evaluations will be required to conclude whether serum protein patterns can serve as early biomarkers of subtle reproductive impairment. 4.6 Potential Role of Systemic Osmolality in Sperm Function. Serum osmolality emerged as one of the more consistently associated biochemical markers in this study, with convergent correlations within multiple semen parameters. Higher osmolality was positively associated with DFI and, intriguingly, also with the percentage of normal morphology, while showing a negative correlation with HDS. Although these associations were moderate, the internal consistency may suggest a potential relationship between systemic osmotic balance and sperm chromatin integrity. Osmotic stress is a well-recognized driver of cellular dysfunction, with particular relevance in tissues with high metabolic demands, including the testes and epididymis. [37] Experimental studies suggest that hyperosmotic stress can influence cellular homeostasis and oxidative balance. In the present observational dataset, however, serum osmolality represents a systemic measurement and cannot be assumed to directly translate into testicular microenvironmental conditions. Therefore, the associations reported here should not be interpreted as evidence of osmotic stress–induced sperm damage, but rather as signals warranting further mechanistic investigation. Previous experimental studies in animal models have indicated that sperm subjected to hyperosmotic conditions exhibit increased superoxide production, lipid peroxidation, and decreased fertilization potential. [37] The positive association of serum osmolality with DFI in the present study may be biologically plausible; however, mechanistic pathways cannot be inferred from the current design. High osmolality may reflect systemic dehydration or metabolic disturbances, although their relevance to oxidative stress in the male reproductive tract was not directly assessed in this study. [38] The corresponding negative correlation with HDS-a marker of chromatin immaturity-may indicate a shift toward DNA fragmentation in response to osmotic challenge. In contrast, the mild positive association with normal morphology may reflect complex biological variability, and speculative mechanisms should be interpreted cautiously. [32] Importantly, osmolality is a commonly measured biochemical parameter in the clinical setting, and yet its possible implications for male reproductive health have been poorly noted. While serum osmolality demonstrated consistent correlations with selected semen parameters, these observations remain associative and should not be interpreted as establishing biomarker utility without longitudinal confirmation. Causality requires further investigation in prospective studies to clarify whether systemic osmotic status is associated with sperm chromatin integrity. 4.7 Limitations and Prospects This was a cross-sectional survey and, as such, cannot offer any basis for inferences about causality. The sample size was relatively small and, especially for subgroup analysis, power was small. Given the number of biochemical indices evaluated, we applied Benjamini–Hochberg false discovery rate adjustment to limit type I error inflation. Associations that did not remain significant after correction were treated as exploratory. Even among statistically significant findings, effect sizes were modest, and results should be interpreted as hypothesis-generating rather than confirmatory. Although several statistically significant correlations were identified, most effect sizes were small (|r| < 0.25), indicating limited clinical relevance at the individual level. In addition, residual confounding cannot be excluded, as detailed lifestyle variables, environmental exposures, and dietary factors were not systematically captured. In addition, recruitment from a health-check population may introduce selection bias, potentially limiting generalizability to broader community settings. 5. Conclusion This cross-sectional analysis among 264 men undergoing routine health examinations offers new insights into the subtle biochemical determinants of semen quality. First, impaired semen quality was characterized by a simultaneous reduction in sperm concentration, motility, morphology, and DNA integrity, thus reaffirming that comprehensive semen assessment is required for evaluating male reproductive potential. Among more than forty routine biochemical indices evaluated, serum chloride showed an exploratory association with semen quality parameters that did not remain statistically significant after FDR correction. Although it did not remain significant after FDR adjustment, its possible implication in reproductive physiology may warrant further investigation in adequately powered longitudinal studies. Third, the study points out protein metabolism indices, in particular globulin and albumin-to-globulin ratio, as potential markers of sperm morphologic integrity. Although effect sizes were modest, these associations raise the possibility that systemic protein distribution and transport-related pathways may reflect subtle aspects of spermatogenic function. Fourth, serum osmolality showed consistent correlations with various semen parameters, such as DFI and HDS, indicating a potential role of systemic osmotic status in the modulation of sperm chromatin stability. Since osmolality is an easily clinically accessible parameter, it may represent a potential biomarker requiring further validation in longitudinal studies. Finally, the traditional metabolic risk factors of BMI, glucose and lipid levels were only weakly associated with semen quality in this relatively healthy population, suggesting their influence may be indirect or evident only in more metabolically impaired cohorts. Taken together, these findings indicate modest correlations between selected systemic biochemical indices and semen parameters in a health-check population. Given the cross-sectional design and small effect sizes, these associations should not be interpreted as causal and require confirmation in longitudinal and mechanistic studies before clinical application is considered. The primary contribution of this study lies in identifying patterns within routinely collected clinical data that may inform future targeted research in male reproductive epidemiology. Abbreviations Abbreviation Full Term A/G ratio Albumin-to-globulin ratio ALP Alkaline phosphatase ALT Alanine aminotransferase ApoA-1 Apolipoprotein A-1 ApoB Apolipoprotein B AST Aspartate aminotransferase BMI Body mass index CO2 Carbon dioxide DBP Diastolic blood pressure DFI DNA fragmentation index GGT Gamma-glutamyl transferase HDS High DNA Stainability HDL-C High-density lipoprotein cholesterol IQR Interquartile range LDH Lactate dehydrogenase LDL-C Low-density lipoprotein cholesterol NAFLD Non-alcoholic fatty liver disease ROS Reactive oxygen species SBP Systolic blood pressure SCSA Sperm chromatin structure assay SHBG Sex hormone-binding globulin Declarations Ethics approval and consent to participate This study was approved by the Ethics Committee of Fujian Maternity and Child Health Hospital (Approval No. 2024KY077). All procedures were conducted in accordance with the ethical standards of the institutional research committee and with the 1964 Declaration of Helsinki and its later amendments. The requirement for individual informed consent was waived due to the retrospective and anonymized nature of the data analysis, as confirmed by the ethics committee. Consent for publication Not applicable. All data presented in this manuscript are anonymized and do not contain any identifiable information of individual participants. Availability of data and materials The datasets generated and/or analyzed during the current study contain potentially identifiable information and are therefore not publicly available. De-identified data may be made available from the corresponding author upon reasonable request and subject to approval by the Ethics Committee of Fujian Maternity and Child Health Hospital. Competing interests The authors declare that they have no competing interests. Funding This work was supported by the Natural Science Foundation of Fujian Province (Grant No. 2024J011060). The funding body had no role in the design of the study; in the collection, analysis, or interpretation of data; or in the writing of the manuscript. Authors’ contributions XR and LN contributed equally to conceptualization, methodology, formal analysis, and writing of the original draft. YF contributed to data curation and validation. GA contributed to software development and investigation. XF and DL contributed equally to supervision, project administration, funding acquisition, and manuscript review and editing. All authors read and approved the final manuscript. Acknowledgements Not applicable. References Cipriani, S. et al. Trend of change of sperm count and concentration over the last two decades: A systematic review and meta-regression analysis. Andrology 11 (6), 997–1008. 10.1111/andr.13396 (2023). Epub 2023 Feb 7. Levine, H. et al. Temporal trends in sperm count: a systematic review and meta-regression analysis of samples collected globally in the 20th and 21st centuries. Hum. Reprod. Update . 29 (2), 157–176. 10.1093/humupd/dmac035 (2023). Dutta, S., Sengupta, P., Slama, P. & Roychoudhury, S. Oxidative Stress, Testicular Inflammatory Pathways, and Male Reproduction. Int. J. Mol. Sci. 22 (18), 10043. 10.3390/ijms221810043 (2021). Lassen, E., Pacey, A., Skytte, A. B. & Montgomerie, R. Recent decline in sperm motility among donor candidates at a sperm bank in Denmark. Hum. Reprod. 39 (8), 1618–1627. 10.1093/humrep/deae115 (2024). Luo, X., Yin, C., Shi, Y., Du, C. & Pan, X. Global trends in semen quality of young men: a systematic review and regression analysis. J. Assist. Reprod. Genet. 40 (8), 1807–1816. 10.1007/s10815-023-02859-z (2023). Epub 2023 Jun 19. Huang, C. et al. Decline in semen quality among 30,636 young Chinese men from 2001 to 2015. Fertil. Steril. 107 (1), 83–88e2. 10.1016/j.fertnstert.2016.09.035 (2017). Epub 2016 Oct 25. Service, C. A., Puri, D., Al Azzawi, S., Hsieh, T. C. & Patel, D. P. The impact of obesity and metabolic health on male fertility: a systematic review. Fertil. Steril. 120 (6), 1098–1111. 10.1016/j.fertnstert.2023.10.017 (2023). Epub 2023 Oct 14. Blaurock, J., Grunewald, S. & Engel, K. M. Intra-individual variability of the human seminal plasma metabolome. Asian J. Androl. 27 (5), 586–591. 10.4103/aja2024110 (2025). Epub 2025 Feb 28. Xia, P. et al. Macrophage-Related Testicular Inflammation in Individuals with Idiopathic Non-Obstructive Azoospermia: A Single-Cell Analysis. Int. J. Mol. Sci. 24 (10), 8819. 10.3390/ijms24108819 (2023). Liu, J. C. et al. Myd88 Signaling Is Involved in the Inflammatory Response in LPS-Induced Mouse Epididymitis and Bone-Marrow-Derived Dendritic Cells. Int. J. Mol. Sci. 24 (9), 7838. 10.3390/ijms24097838 (2023). Ferramosca, A. & Zara, V. Diet and Male Fertility: The Impact of Nutrients and Antioxidants on Sperm Energetic Metabolism. Int. J. Mol. Sci. 23 (5), 2542. 10.3390/ijms23052542 (2022). Shi, X. et al. Associations between blood metal/ metalloid concentration and human semen quality and sperm function: A cross-sectional study in Hong Kong. J. Trace Elem. Med. Biol. 65 , 126735. 10.1016/j.jtemb.2021.126735 (2021). Epub 2021 Feb 23. Chen, Y. Y. & Chen, W. L. Serum Bilirubin and Sperm Quality in Adult Population. Toxics 10 (6), 295. 10.3390/toxics10060295 (2022). Liu, M. & Dudley, S. C. Jr Beyond Ion Homeostasis: Hypomagnesemia, Transient Receptor Potential Melastatin Channel 7, Mitochondrial Function, and Inflammation. Nutrients 15 (18), 3920. 10.3390/nu15183920 (2023). Nguyen, N. D., Le, M. T., Tran, N. Q. T., Nguyen, Q. H. V. & Cao, T. N. Micronutrient supplements as antioxidants in improving sperm quality and reducing DNA fragmentation. Basic. Clin. Androl. 33 (1), 23. 10.1186/s12610-023-00197-9 (2023). Johnson, T. A. et al. Non-Targeted Analysis of Environmental Contaminants and Their Associations with Semen Health Factors in Men from New York City. Environ. Health (Wash) . 3 (2), 164–176. 10.1021/envhealth.4c00165 (2024). Greenberg, D. R. et al. The association of hypertension and antihypertensive medications on semen parameters among men presenting for fertility evaluation. Andrology 13 (8), 2083–2090. 10.1111/andr.70010 (2025). Epub 2025 Feb 6. Ji, F. et al. BMI is associated with sperm quality and sex hormones in men: a meta-analysis. Front. Endocrinol. (Lausanne) . 16 , 1714019. 10.3389/fendo.2025.1714019 (2025). Zhang, W., Tong, L., Jin, B. & Sun, D. Diabetic testicular dysfunction and spermatogenesis impairment: mechanisms and therapeutic prospects. Front. Endocrinol. (Lausanne) . 16 , 1653975. 10.3389/fendo.2025.1653975 (2025). Płaczkowska, S., Rodak, K., Kmieciak, A., Gilowska, I. & Kratz, E. M. Exploring correlations: Human seminal plasma and blood serum biochemistry in relation to semen quality. PLoS One . 19 (6), e0305861. 10.1371/journal.pone.0305861 (2024). Raut, S. K. et al. Chloride ions in health and disease. Biosci. Rep. 44 (5), BSR20240029. 10.1042/BSR20240029 (2024). Zhang, T. et al. Disrupted spermatogenesis in a metabolic syndrome model: the role of vitamin A metabolism in the gut-testis axis. Gut 71 (1), 78–87. 10.1136/gutjnl-2020-323347 (2022). Epub 2021 Jan 27. Kröse, J. L. & de Baaij, J. H. F. Magnesium biology. Nephrol Dial Transplant. ;39(12):1965–1975. (2024). 10.1093/ndt/gfae134 . Erratum in: Nephrol Dial Transplant. 2025;40(6):1261. doi: 10.1093/ndt/gfae219. Wong, W. Y. et al. The impact of calcium, magnesium, zinc, and copper in blood and seminal plasma on semen parameters in men. Reprod. Toxicol. 15 (2), 131–136. 10.1016/s0890-6238(01)00113-7 (2001 Mar-Apr). Alvarez, J. G. et al. Ethanol accelerates acrosomal loss in human spermatozoa. J. Androl. 9 (6), 357–366. 10.1002/j.1939-4640.1988.tb01065.x (1988 Nov-Dec). Verma, H. & Garg, R. Evaluation of synergistic combination comprising magnesium orotate, menaquinone-7, and cholecalciferol for management of type 2 diabetes and dyslipidemia. Magnes Res. 33 (4), 88–105. 10.1684/mrh.2020.0472 (2020). Showell, M. G., Brown, J., Yazdani, A., Stankiewicz, M. T. & Hart, R. J. Antioxidants for male subfertility. Cochrane Database Syst Rev. ;(1):CD007411. (2011). 10.1002/14651858.CD007411.pub2 . Update in: Cochrane Database Syst Rev. 2014;(12):CD007411. doi: 10.1002/14651858.CD007411.pub3. Wang, Y., Fu, X. & Li, H. Mechanisms of oxidative stress-induced sperm dysfunction. Front. Endocrinol. (Lausanne) . 16 , 1520835. 10.3389/fendo.2025.1520835 (2025). Aitken, R. J. et al. A Comparative Analysis of the Antioxidant Profiles Generated by the RoXstaTM System for Diverse Biological Fluids Highlights the Powerful Protective Role of Human Seminal Plasma. Antioxid. (Basel) . 14 (1), 90. 10.3390/antiox14010090 (2025). Čepelak, I., Dodig, S. & Pavić, I. Bilirubin - new insights into an old molecule. Biochem. Med. (Zagreb) . 35 (2), 020501. 10.11613/BM.2025.020501 (2025). Epub 2025 Apr 15. Henkel, R., Sandhu, I. S. & Agarwal, A. The excessive use of antioxidant therapy: A possible cause of male infertility? Andrologia. ;51(1):e13162. (2019). 10.1111/and.13162 . Epub 2018 Sep 26. Potiris, A. et al. From Inflammation to Infertility: How Oxidative Stress and Infections Disrupt Male Reproductive Health. Metabolites 15 (4), 267. 10.3390/metabo15040267 (2025). Palani, A. & Alahmar, A. Impact of oxidative stress on semen parameters in normozoospermic infertile men: a case–control study. Afr. J. Urol. 26 , 50. https://doi.org/10.1186/s12301-020-00061-6 (2020). Martins, A. D., Majzoub, A. & Agawal, A. Metabolic Syndrome and Male Fertility. World J. Mens Health . 37 (2), 113–127. 10.5534/wjmh.180055 (2019). Epub 2018 Oct 22. Almadaly, E. A. et al. Fertility-associated biochemical components in seminal plasma and serum of buffalo (Bubalus bubalis) bulls. Front. Vet. Sci. 9 , 1043379. 10.3389/fvets.2022.1043379 (2023). Xiao, M. et al. High Systemic Inflammatory Protein Index Is Associated with Clinically Ineffective Reperfusion in Acute Anterior Circulation Ischemic Stroke Patients Undergoing Endovascular Treatment. Mol. Neurobiol. 61 (10), 7707–7716. 10.1007/s12035-024-04068-w (2024). Epub 2024 Mar 1. Joseph, A., Shur, B. D., Ko, C., Chambon, P. & Hess, R. A. Epididymal hypo-osmolality induces abnormal sperm morphology and function in the estrogen receptor alpha knockout mouse. Biol. Reprod. 82 (5), 958–967. 10.1095/biolreprod.109.080366 (2010). Epub 2010 Feb 3. Dutta, S., Sengupta, P., Slama, P. & Roychoudhury, S. Oxidative Stress, Testicular Inflammatory Pathways, and Male Reproduction. Int. J. Mol. Sci. 22 (18), 10043. 10.3390/ijms221810043 (2021). Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 13 May, 2026 Reviewers agreed at journal 11 May, 2026 Reviewers agreed at journal 11 May, 2026 Reviewers agreed at journal 10 May, 2026 Reviewers agreed at journal 05 May, 2026 Reviewers invited by journal 24 Apr, 2026 Editor invited by journal 08 Apr, 2026 Editor assigned by journal 27 Feb, 2026 Submission checks completed at journal 27 Feb, 2026 First submitted to journal 26 Feb, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8982176","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":634310297,"identity":"0546d180-03b8-4a05-9e4f-8ce51080e3ea","order_by":0,"name":"Xihuan Ren","email":"","orcid":"","institution":"Fujian Maternity and Child Health Hospital, College of Clinical Medicine for Obstetrics \u0026 Gynecology and Pediatrics, Fujian Medical University","correspondingAuthor":false,"prefix":"","firstName":"Xihuan","middleName":"","lastName":"Ren","suffix":""},{"id":634310300,"identity":"b451b00d-299c-42fd-81ba-204d04b97192","order_by":1,"name":"Lin Ni","email":"","orcid":"","institution":"Fujian Maternity and Child Health Hospital, College of Clinical Medicine for Obstetrics \u0026 Gynecology and Pediatrics, Fujian Medical University","correspondingAuthor":false,"prefix":"","firstName":"Lin","middleName":"","lastName":"Ni","suffix":""},{"id":634310309,"identity":"1be7fe32-947c-44d2-92d4-87ba547bb975","order_by":2,"name":"Yun Fu","email":"","orcid":"","institution":"Fujian Maternity and Child Health Hospital, College of Clinical Medicine for Obstetrics \u0026 Gynecology and Pediatrics, Fujian Medical University","correspondingAuthor":false,"prefix":"","firstName":"Yun","middleName":"","lastName":"Fu","suffix":""},{"id":634310312,"identity":"21709ee8-7f5b-46e0-b07d-473cbd05f18d","order_by":3,"name":"Gang An","email":"","orcid":"","institution":"Fujian Maternity and Child Health Hospital, College of Clinical Medicine for Obstetrics \u0026 Gynecology and Pediatrics, Fujian Medical University","correspondingAuthor":false,"prefix":"","firstName":"Gang","middleName":"","lastName":"An","suffix":""},{"id":634310313,"identity":"e3ad5780-70e0-4e9e-893c-52ff3ddd9625","order_by":4,"name":"Xiangqun Fan","email":"","orcid":"","institution":"Fujian Maternity and Child Health Hospital, College of Clinical Medicine for Obstetrics \u0026 Gynecology and Pediatrics, Fujian Medical University","correspondingAuthor":false,"prefix":"","firstName":"Xiangqun","middleName":"","lastName":"Fan","suffix":""},{"id":634310315,"identity":"b8c9f1ec-6456-4436-a082-443f5cb13b64","order_by":5,"name":"Dianliang Lin","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAmklEQVRIiWNgGAWjYFAC5gaJBxUScvIkaGFskEg4Y2Fs2ECSlsS2ikSGA8Rq0G1PbLyROE8igbGB+eGjG8RoMTvzsNkicZtEHjsDm7FxDlFabiS2SQC1FDM28LBJk6BljkRiwwHStDSQpAXkl4RjEsaGzUT75XjywRsfaurk5NmbHz4mSgsDQwKUZiZOObKWUTAKRsEoGAW4AADO3TH+K3TCXwAAAABJRU5ErkJggg==","orcid":"","institution":"Fujian Maternity and Child Health Hospital, College of Clinical Medicine for Obstetrics \u0026 Gynecology and Pediatrics, Fujian Medical University","correspondingAuthor":true,"prefix":"","firstName":"Dianliang","middleName":"","lastName":"Lin","suffix":""}],"badges":[],"createdAt":"2026-02-27 00:54:21","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8982176/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8982176/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":108532666,"identity":"a5366667-2399-4edf-9a02-05f9d68acfc2","added_by":"auto","created_at":"2026-05-05 16:15:59","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":173647,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eComparison of semen parameters by WHO reference status.\u003c/strong\u003e Box plots showing (A) semen volume, (B) sperm concentration, (C) progressive motility, (D) non-progressive motility, (E) immotile sperm, (F) total motility, (G) normal morphology, (H) DNA fragmentation index (DFI), (I) high DNA stainability (HDS), and (J) serum chloride. Central line: median; box: interquartile range (IQR); whiskers: 1.5×IQR; points: outliers. Nominal P values: *P \u0026lt; 0.05, **P \u0026lt; 0.01, ***P \u0026lt; 0.001 (unadjusted).\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8982176/v1/e2c6957675f876194c04b7e4.png"},{"id":108532667,"identity":"b6c0e449-f0eb-49ab-9628-e64497191c25","added_by":"auto","created_at":"2026-05-05 16:15:59","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":26153,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSerum chloride levels by WHO reference status. \u003c/strong\u003eBox plot showing serum chloride (mmol/L) distribution. Group definitions as in Figure 1. Central line: median; box: IQR; whiskers: 1.5×IQR. The nominal P value from t-test was 0.0139, but not significant after FDR correction.\u003c/p\u003e\n\u003cp\u003eSerum chloride was the only biochemical marker showing a statistically significant difference between groups in the initial analysis (\u003cem\u003eP\u003c/em\u003e = 0.0139)(Figure 2). However, after applying FDR correction for multiple comparisons, this difference was no longer statistically significant. Accordingly, we interpret chloride not as a clear discriminator between groups but as an exploratory finding that could be examined further in larger or more specific populations. Other electrolytes (magnesium, sodium, calcium, potassium) and renal function markers (creatinine, urea, uric acid) also exhibited minimal effect sizes (Cohen’s d \u0026lt; 0.30) and did not demonstrate meaningful group-level distinctions.\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8982176/v1/2d12dde0d87a2ce97482656a.png"},{"id":108803914,"identity":"8ea0b5f4-0115-49f2-ab1b-ff5c6986fcd7","added_by":"auto","created_at":"2026-05-08 15:10:45","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":321423,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eHeatmap of correlations among semen parameters, demographics, and biochemical indices. \u003c/strong\u003eThe heatmap displays pairwise correlation coefficients (Pearson/Spearman r) for 51 variables. Red: positive correlation; blue: negative correlation; color intensity reflects |r|. Variables are hierarchically clustered (Euclidean distance, complete linkage). Order (top to bottom, left to right): ApoA1, HDL‑C, direct bilirubin, total bilirubin, unconjugated bilirubin, AST/ALT ratio, A/G ratio, chloride, sodium, osmolality, immotile sperm, DFI, age, glucose, non‑progressive motility, HDS, CK, CK‑MB, LDH, ALT, AST, uric acid, weight, BMI, ALP, CK‑MB/CK ratio, anion gap, calcium, albumin, SBP, DBP, total protein, globulin, GGT, triglycerides, LDL‑C, total cholesterol, ApoB, magnesium, progressive motility, total motility, phosphorus, urea, urea/creatinine ratio, height, semen volume, sperm concentration, normal morphology, potassium, CO₂ combining power.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-8982176/v1/e7e955fc0edcf8cb367e97c9.png"},{"id":108976674,"identity":"6887a5cb-3e61-40e9-93be-78110a969846","added_by":"auto","created_at":"2026-05-11 11:27:55","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":934565,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8982176/v1/ea54ddf1-67a0-42dd-bd1f-74aaea7877a3.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Associations between Routine Systemic Biochemical Indices and Semen Quality: A Cross-Sectional Study in Men Undergoing Health Examination","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eMale infertility and reduced semen quality have become major global public health problems.\u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e Epidemiologic summaries indicate that sperm concentration, motility, and morphology among men of reproductive age have decreased globally consistently.\u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e The falling sperm counts and concentration have since been replicated by European and American studies.\u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e A recent systematic review and meta-analysis (1973\u0026ndash;2018) have estimated that the mean sperm count of men worldwide has declined more than 50% in the past 50 years, with the decline accelerating since the turn of the 21st century.\u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e Multiple regions in China also reported a stunning deterioration of young men's semen quality from 2001 to 2015.\u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e Accumulating epidemiological evidence suggests a temporal decline in several semen quality parameters across different regions, although the magnitude and consistency of this trend remain subject to methodological debate. Given that spermatogenesis is regulated by a complex interplay of endocrine signaling, metabolic homeostasis, oxidative balance, and immune regulation, understanding systemic correlates of semen quality has become increasingly relevant from both clinical and public health perspectives.\u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e Rather than focusing exclusively on overt reproductive disorders, identifying physiological markers associated with variation in semen parameters within the general population may help contextualize male reproductive health within broader systemic processes.\u003c/p\u003e \u003cp\u003eSeveral studies have extensively demonstrated that common cardiovascular and metabolic diseases (e.g., dyslipidemia, obesity, hyperglycemia, and high blood pressure) are linked to the loss of sperm quality. Obesity, impaired glucose regulation, and chronic low-grade inflammation have been associated with alterations in endocrine signaling and increased oxidative stress. These systemic disturbances may influence the testicular microenvironment, mitochondrial activity in spermatozoa, and chromatin stability. However, most existing evidence derives from selected clinical populations, and the extent to which routine metabolic indicators reflect subtle variation in semen parameters within generally healthy populations remains unclear.\u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e Recent evidence indicates that an increase in body mass index and fasting glucose has a direct correlation to decreased motile sperm and increased sperm DNA fragmentation.\u003csup\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eDyslipidemia, including high low-density lipoprotein cholesterol (LDL-C) and apolipoprotein B, has strong correlations with sperm dysfunction. The lipids may injure mitochondria and produce reactive oxygen species (ROS) and thus disable the motility and chromatin integrity of the sperm.\u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e Emerging evidence has suggested potential associations between certain micronutrient and antioxidant-related markers\u0026mdash;such as magnesium and bilirubin\u0026mdash;and semen parameters. Magnesium is involved in ATP-dependent cellular processes and mitochondrial function, while bilirubin possesses endogenous antioxidant properties. These biological roles provide a theoretical basis for potential relationships with sperm motility and chromatin integrity; however, direct mechanistic pathways linking circulating concentrations of these markers to semen quality remain to be fully elucidated.\u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/sup\u003e This pattern is consistent with magnesium\u0026rsquo;s known roles in ATP production, maintaining mitochondrial function, and reducing inflammation.\u003csup\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e Analogously, bilirubin too, once thought in the past simply as a marker of liver function, was discovered by research to be strongly positively related to semen volume and motility.\u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e These observations may reflect bilirubin\u0026rsquo;s antioxidant properties, which may be associated with reduced oxidative damage to sperm DNA. They also broaden our understanding of male reproductive health by suggesting that even mild metabolic or biochemical disturbances can influence fertility.\u003c/p\u003e \u003cp\u003eQuality of semen has been a universal concern traditionally and has been hypothesized to have many causes including environmental contamination and lifestyle modifications (e.g., daily use of cigarette or heavy alcohol consumption).\u003csup\u003e[\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e Although numerous studies have examined individual metabolic or inflammatory factors in relation to male fertility, relatively few investigations have systematically evaluated a broad panel of routinely measured biochemical indices within a standardized health-check setting. Importantly, most prior research has focused on predefined hypotheses involving specific pathways (e.g., obesity, diabetes, oxidative stress), whereas less attention has been given to exploratory pattern detection across comprehensive clinical biomarker profiles. Second, few large multivariable studies in preventive health-check populations have systematically evaluated the associations between routine metabolic, biochemical, and antioxidant parameters and semen quality, highlighting the need for broader exploratory analyses. Accordingly, the present study was designed as a biologically stratified, hypothesis-generating cross-sectional analysis aimed at identifying patterns of association between routine health-check indices and semen parameters in a real-world clinical population.\u003c/p\u003e \u003cp\u003eRather than testing a single predefined mechanistic hypothesis, we predefined three biologically grounded domains\u0026mdash;(1) metabolic status, (2) oxidative/antioxidant balance, and (3) electrolyte\u0026ndash;osmotic homeostasis\u0026mdash;and examined whether systemic biochemical indicators within these domains demonstrate statistically detectable correlations with semen quality measures. Indices not directly mapping onto these domains were analyzed in an exploratory manner. Specifically, the primary aim of this study was to evaluate whether routinely measured systemic biochemical indices are statistically associated with semen quality parameters in a standardized health-check population.\u003c/p\u003e \u003cp\u003eThe objective was not to establish causal relationships, but to characterize potential associative signals that may inform future longitudinal or mechanistic studies.\u003c/p\u003e \u003cp\u003eGiven the cross-sectional design and the multiplicity of evaluated indices, findings within the three predefined biological domains were interpreted in the context of their underlying physiological rationale, whereas remaining associations were treated as exploratory signals requiring further validation.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Study Design and Participants\u003c/h2\u003e \u003cp\u003eThis cross-sectional study enrolled men aged 21\u0026ndash;60 years who completed routine health examinations\u0026mdash;including full biochemical testing and semen analysis\u0026mdash;at a tertiary medical center between January 2023 and December 2024. Inclusion required a complete physical examination record and successful completion of semen analysis on the same day. Exclusion (by protocol) included: past history of epididymal/testicular surgery, currently undergoing fertility treatment, serious chronic illness, or inadequate semen sample for analysis (e.g., incomplete collection, contamination). After applying inclusion and exclusion criteria and excluding records with missing core variables, 264 men were included in the final analysis.\u003c/p\u003e \u003cp\u003eTo address methodological rigor, we additionally evaluated whether the sample size was adequate for detecting clinically meaningful correlations. As this was an analysis of available health check-up data, a formal a priori sample size calculation was not performed. A post-hoc power analysis indicated that with 264 participants, the study had approximately 80% power (α\u0026thinsp;=\u0026thinsp;0.05, two-tailed) to detect Pearson correlation coefficients of |r| \u0026ge; 0.17. This should be considered when interpreting weaker correlations. Given that more than 40 biochemical variables were examined, many observed correlations below this threshold (e.g., |r|\u0026lt;0.10) should be interpreted cautiously as they may represent weak associations with limited biological relevance. This limitation was considered in the interpretation of results and further highlighted in the Discussion. Because the study involved retrospective analysis of routinely collected clinical data, no experimental interventions or comparisons were performed.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Laboratory and Clinical Measurements\u003c/h2\u003e \u003cp\u003eUpon morning visit, every participant received a standard health examination procedure. Following verification by a nurse that the participant had fasted for a minimum of 8 hours, the participant's height and weight were measured and BMI determined as a ratio of weight (kg) to height squared (m\u0026sup2;). Following a five-minute sitting rest, the participant was measured for blood pressure employing an automatic sphygmomanometer: SBP and DBP, each in duplicate and the mean was taken for analysis purposes. Hypertension was diagnosed as SBP\u0026thinsp;\u0026ge;\u0026thinsp;140 mmHg, DBP\u0026thinsp;\u0026ge;\u0026thinsp;90 mmHg, or a history of diagnosed earlier.\u003c/p\u003e \u003cp\u003eFasting venous blood samples were drawn and analyzed in the hospital\u0026rsquo;s central laboratory using a Roche Cobas 8000 system. General metabolic testing included measurements of fasting glucose, total cholesterol, triglycerides, HDL-C, LDL-C, ApoA-1, and ApoB. Each of these was done by enzymatic methods or immunoturbidimetric assay, as directed by manufacturer's protocols.\u003c/p\u003e \u003cp\u003eTo provide a more complete biochemical profile for comparison with semen quality, we also analyzed stored blood samples. These included electrolytes (sodium, potassium, chloride, calcium, phosphorus, and magnesium), liver enzymes (ALT, AST, GGT, ALP), serum protein (total protein, albumin, globulin, and A/G ratio), bilirubin metabolism markers, renal function markers (urea, creatinine, uric acid), and lipid and glycemic indices. Concurrently, renal function tests like urea, creatinine, and uric acid and acid-base status markers like combining capacity of carbon dioxide, calculated anion gap, and serum osmolality, also were run in the same analyzer under strict internal and external quality control protocols. All biochemical analyses were performed within approximately 2 hours after venipuncture under standardized laboratory quality control procedures to minimize pre-analytical variation.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Semen Analysis\u003c/h2\u003e \u003cp\u003eSemen samples were collected after 2\u0026ndash;7 days of sexual abstinence. Semen analysis was performed according to the World Health Organization (WHO) 2010 guidelines. DNA fragmentation index (DFI) and high DNA stainability (HDS) were assessed using the sperm chromatin structure assay (SCSA). All SCSA procedures, including sample processing, staining, and flow cytometric analysis, were conducted according to the standard protocol described by Greenberg et al.\u003csup\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eFor semen quality, we followed WHO reference criteria, using the WHO lower reference limits (sperm concentration\u0026thinsp;\u0026ge;\u0026thinsp;15\u0026times;10⁶/mL, progressive motility\u0026thinsp;\u0026ge;\u0026thinsp;32%, total motility\u0026thinsp;\u0026ge;\u0026thinsp;40%, and normal morphology\u0026thinsp;\u0026ge;\u0026thinsp;4%) as comparative thresholds. Semen volume, percentage non-progressive motility, percentage immotile sperm, DNA fragmentation index (DFI), and high DNA stainability (HDS) were utilized as continuous outcome measures. For subgroup summaries, participants were classified as having semen parameters within WHO reference limits versus having\u0026thinsp;\u0026ge;\u0026thinsp;1 parameter below the WHO lower reference limit; these categories are used for descriptive purposes and do not imply diagnostic \u0026ldquo;normal/abnormal\u0026rdquo; labeling. For correlation analysis, each of the semen variables was treated as an independent continuous variable.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Statistical Analysis\u003c/h2\u003e \u003cp\u003eAll statistical analyses were performed using R (version 4.3.1) and cross-validated in SPSS (version 26.0) to ensure computational consistency. Continuous variables were summarized as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation (SD). Normality of continuous variables was assessed using the Shapiro\u0026ndash;Wilk test prior to selection of parametric or non-parametric statistical methods. Group comparisons were conducted using appropriate parametric or non-parametric tests according to data distribution. Associations between semen parameters and clinical or biochemical indices were evaluated using Pearson or Spearman correlation analyses as appropriate, and correlation coefficients were reported together with two-sided P values.\u003c/p\u003e \u003cp\u003eGiven the evaluation of multiple biochemical variables\u0026mdash;primarily categorized into the three predefined biological domains (metabolic status, oxidative/antioxidant balance, and electrolyte\u0026ndash;osmotic homeostasis), with additional indices analyzed exploratorily\u0026mdash;multiplicity was addressed using the Benjamini\u0026ndash;Hochberg procedure to control the false discovery rate (FDR). For each semen parameter, P-values derived from the corresponding set of hypothesis tests were adjusted, and results were considered statistically significant at an FDR-adjusted P\u0026thinsp;\u0026lt;\u0026thinsp;0.05. To minimize the risk of chance findings from extensive correlation screening, results that did not meet FDR significance were explicitly treated as exploratory and were interpreted in conjunction with effect sizes and biological plausibility rather than nominal P-values alone.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e2.5 Ethical Considerations\u003c/h2\u003e \u003cp\u003e This study was approved by the Ethics Committee of Fujian Maternity and Child Health Hospital (Approval No. 2024KY077). The requirement for individual informed consent was waived for this retrospective analysis, as confirmed by the ethics committee, due to the use of anonymized data obtained from routine health check-ups.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec9\" class=\"Section3\"\u003e \u003cdiv class=\"Heading\"\u003e3.1.1 Baseline Characteristics and Between-Group Difference\u003c/div\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e lists the baseline clinical and biochemical characteristics of the participants. Among the 264 men included in the final analysis, 194 (73.5%) demonstrated semen parameters within the WHO reference ranges, and 70 (26.5%) exhibited at least one parameter below the lower reference limit. As expected, men in the below-reference-limit group had worse semen outcomes across all major measures, including concentration, motility, morphology, DFI, and HDS. These results support the internal consistency of the semen quality measures and confirm that our classification criteria were appropriate (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline characteristics of men with and without WHO-defined low semen quality\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\"\u0026plusmn;\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eWithin-reference-limits Group (n\u0026thinsp;=\u0026thinsp;194, Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBelow-reference-limit Group (n\u0026thinsp;=\u0026thinsp;70, Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e-value\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCohen's d\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSemen Volume\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e3.69\u0026thinsp;\u0026plusmn;\u0026thinsp;1.38\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e3.45\u0026thinsp;\u0026plusmn;\u0026thinsp;1.62\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.050\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.161\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSperm Concentration\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e48.54\u0026thinsp;\u0026plusmn;\u0026thinsp;24.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e33.64\u0026thinsp;\u0026plusmn;\u0026thinsp;25.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.61\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eProgressive Motility(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e51.19\u0026thinsp;\u0026plusmn;\u0026thinsp;11.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e32.28\u0026thinsp;\u0026plusmn;\u0026thinsp;12.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.629\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon-progressive Motility(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e4.24\u0026thinsp;\u0026plusmn;\u0026thinsp;2.49\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e6.57\u0026thinsp;\u0026plusmn;\u0026thinsp;6.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.035\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.568\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eImmotile Sperm(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e44.54\u0026thinsp;\u0026plusmn;\u0026thinsp;11.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e60.86\u0026thinsp;\u0026plusmn;\u0026thinsp;13.40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-1.354\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal Motility(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e55.62\u0026thinsp;\u0026plusmn;\u0026thinsp;11.50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e39.56\u0026thinsp;\u0026plusmn;\u0026thinsp;14.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e1.364\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNormal Morphology(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e12.11\u0026thinsp;\u0026plusmn;\u0026thinsp;6.29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e8.76\u0026thinsp;\u0026plusmn;\u0026thinsp;4.79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.553\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDFI(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e15.05\u0026thinsp;\u0026plusmn;\u0026thinsp;7.85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e23.91\u0026thinsp;\u0026plusmn;\u0026thinsp;12.28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.979\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHDS(%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e5.71\u0026thinsp;\u0026plusmn;\u0026thinsp;4.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e6.90\u0026thinsp;\u0026plusmn;\u0026thinsp;4.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.276\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMagnesium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e0.895\u0026thinsp;\u0026plusmn;\u0026thinsp;0.073\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e0.877\u0026thinsp;\u0026plusmn;\u0026thinsp;0.053\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.080\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.266\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGGT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e43.546\u0026thinsp;\u0026plusmn;\u0026thinsp;37.714\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e34.765\u0026thinsp;\u0026plusmn;\u0026thinsp;21.818\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.124\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.256\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLDL Cholesterol\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e3.315\u0026thinsp;\u0026plusmn;\u0026thinsp;0.908\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e3.119\u0026thinsp;\u0026plusmn;\u0026thinsp;0.865\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.308\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.218\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLDH\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e173.133\u0026thinsp;\u0026plusmn;\u0026thinsp;32.596\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e166.755\u0026thinsp;\u0026plusmn;\u0026thinsp;26.94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.177\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.204\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eChloride\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e104.504\u0026thinsp;\u0026plusmn;\u0026thinsp;1.933\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e103.79\u0026thinsp;\u0026plusmn;\u0026thinsp;2.074\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.014\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.362\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e31.326\u0026thinsp;\u0026plusmn;\u0026thinsp;4.4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e32.246\u0026thinsp;\u0026plusmn;\u0026thinsp;6.556\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.761\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.182\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHeight\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e173.728\u0026thinsp;\u0026plusmn;\u0026thinsp;5.804\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e172.758\u0026thinsp;\u0026plusmn;\u0026thinsp;6.32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.266\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.163\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eCreatinine\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e75.81\u0026thinsp;\u0026plusmn;\u0026thinsp;12.986\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e73.901\u0026thinsp;\u0026plusmn;\u0026thinsp;9.817\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.488\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.156\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOsmolality\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e279.055\u0026thinsp;\u0026plusmn;\u0026thinsp;3.362\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e278.587\u0026thinsp;\u0026plusmn;\u0026thinsp;3.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.283\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.143\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e25.278\u0026thinsp;\u0026plusmn;\u0026thinsp;3.572\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e25.765\u0026thinsp;\u0026plusmn;\u0026thinsp;4.081\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.642\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e-0.131\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAST\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e24.641\u0026thinsp;\u0026plusmn;\u0026thinsp;15.019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e22.901\u0026thinsp;\u0026plusmn;\u0026thinsp;8.725\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.725\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.127\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSodium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c2\"\u003e \u003cp\u003e139.658\u0026thinsp;\u0026plusmn;\u0026thinsp;1.625\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\"\u0026plusmn;\" colname=\"c3\"\u003e \u003cp\u003e139.449\u0026thinsp;\u0026plusmn;\u0026thinsp;1.675\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.611\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e0.127\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eNotes: Data are presented as mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD. \u003cem\u003eP\u003c/em\u003e-values were calculated using independent t-test or Mann\u0026ndash;Whitney U test as appropriate. Cohen\u0026rsquo;s d indicates effect size (small\u0026thinsp;\u0026ge;\u0026thinsp;0.2, medium\u0026thinsp;\u0026ge;\u0026thinsp;0.5, large\u0026thinsp;\u0026ge;\u0026thinsp;0.8).\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\u003cp\u003eAbbreviations: BMI, body mass index; AST, aspartate aminotransferase; GGT, gamma-glutamyl transferase; LDL, low-density lipoprotein; LDH, lactate dehydrogenase; DFI, DNA fragmentation index; HDS, high DNA stainability.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.1.2 Comparison of Physical Examination Indices Difference Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe comparison of routine clinical and biochemical indices revealed that most variables did not differ significantly between groups. Anthropometric measurements such as age, height, and BMI were broadly similar, suggesting that general demographic characteristics were unlikely to account for the observed disparities in semen quality. For metabolic and liver-related markers such as fasting glucose, triglycerides, LDL-C, ALT, AST, and GGT, differences between groups were small and not statistically significant. Some indices exhibited slight directional trends consistent with patterns reported in earlier literature.\u003c/p\u003e\n\u003cp\u003eTo further characterize the nature of group differences, continuous semen parameters were compared in detail. Men in the below-reference-limit group showed noticeably higher proportions of immotile and non-progressive sperm, along with clearly elevated DFI levels (mean 23.9% vs. 15.1% in the within-reference-limits group), underscoring substantial impairment in both sperm motility and chromatin integrity. In contrast, the below-reference-limit group had lower semen volume and reduced progressive and total motility, as well as poorer morphology. Several of these differences showed medium to large effect sizes. These observations align with recognized clinical patterns of concurrent decline across multiple semen indices and support the internal validity of the dataset.\u003c/p\u003e\n\u003cp\u003eMost biochemical markers did not differ significantly between the groups, although a few showed trends that were biologically reasonable. For example, serum magnesium showed a borderline lower mean level in the below-reference-limit group, consistent with its known physiological role in energy metabolism and sperm motility, though the difference did not reach statistical significance. Similarly, a few markers\u0026mdash;such as HDL-cholesterol, triglycerides, and some liver enzymes\u0026mdash;showed weak trends that were broadly in line with previous findings on metabolism and male fertility. Although these trends were small and should not be over-interpreted, they offer useful context for the multivariable analyses presented later.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.2 Association between Demographic Traits, Basic Physical Measures and Semen Parameters\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe subsequently compared correlations of demographic characteristic of participants (age) to uncomplicated physical measures (weight, height, BMI, SBP, DBP) and indices of semen quality. (Figure 3)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.2.1 Age\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAge had a weak but significant inverse association with most of the semen quality parameters. Precisely, age was inversely connected to semen volume (r = -0.166, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01), which indicated a tendency toward a declining volume of ejaculate with increasing age. Age was positively correlated with sperm DNA fragmentation index (DFI) (r = 0.167, P \u0026lt; 0.01), indicating that older individuals tended to have higher levels of sperm DNA fragmentation. Age was inversely connected very weakly to the percentage of sperm concentration (r =0.119), progressively motile sperm (r =-0.052) and total motility (r =-0.083), but was positively connected to the percentage of immotile sperm (r =0.081). Taken together, these findings suggest that even within this relatively young cohort, age may have a small adverse effect on semen volume, motility, and DNA integrity.\u003c/p\u003e\n\u003cp\u003eAge, in relation to other clinical parameters, was inversely related to serum calcium (r = -0.252, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001), and to the total protein (r = -0.181, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001), and to albumin (r = -0.212, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001) but positively to fasting glucose (r = 0.258, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001). Data are likely to show age-dependent changes in metabolism, however there are not known specific intervening mechanisms how these have impacts on semen quality.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.2.2 Blood Pressure\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSemen parameters likewise presented weak inverse correlations with levels of blood pressure. Remarkably, higher DBP correlated significantly with declining semen volume (r = -0.171, \u003cem\u003eP\u003c/em\u003e = 0.005). That is, individuals with relatively higher blood pressure had a lesser ejaculate volume. Although this relationship has been weak, it has physiological plausibility: hypertension may impair vascular endothelial function at a systemic level, which may be associated with reduced blood supply to accessory glands such as the prostate and seminal vesicles, potentially reflecting reduced secretory output and lower semen volume\u003csup\u003e[23]\u003c/sup\u003e. In fact, one large study has identified that hypertensive men have significantly lower mean semen volume and poorer sperm motility than normotensive men\u003csup\u003e[23]\u003c/sup\u003e. We discovered in our study that there was only a weak correlation between DBP and semen volume; there was no correlation between systolic blood pressure and semen parameters. This may be because most subjects had normal or slightly elevated blood pressure, which made its visible impact precluded. Of note is the fact that DBP was significantly correlated with GGT (r = 0.261, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001), total protein (r = 0.249, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001), and globulin (r = 0.239, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001). Because these markers reflect liver function and inflammation, data suggest that cardiovascular or metabolic conditions might affect reproductive health through several indirect pathways. This pattern hints at a link between cardiovascular status and male fertility. Conditions such as hypertension may gradually influence semen parameters over time.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.2.3 Height, Weight, and BMI\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHeight is weakly associated with parameters such as sperm concentration and motility. Weight and BMI were highly collinear (r = 0.886, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001). These both had negative correlations with semen volume (weight: r = -0.055; BMI: r = -0.115), the negative correlation of the latter being slightly stronger. Unfortunately, it did not reach statistical significance. Weight and BMI also showed weak negative correlations with progressive motility (weight: r = -0.032; BMI: r = -0.087) and with total motility (weight: r = -0.041; BMI: r = -0.076), and weak positive correlations with the proportion of immotile sperm (weight: r = 0.037; BMI: r = 0.078). Although our sample size was modest, we noticed a small trend suggesting that higher BMI might be linked to reduced semen volume and total motility. This trend is consistent with findings from previous large-scale studies. Because weight and BMI were also related to several metabolic and liver enzyme markers, their influence on semen quality may operate through broader metabolic mechanisms.\u003csup\u003e[18]\u003c/sup\u003e For example, BMI was also highly positively correlated with alanine aminotransferase (ALT, r = 0.496, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001), aspartate aminotransferase (AST, r = 0.350, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001), gamma-glutamyl transferase (GGT, r = 0.374, P \u0026lt; 0.001), uric acid (r = 0.361, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001), triglycerides (r = 0.400, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001), and fasting glucose (r = 0.235, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05). Conversely, BMI was strongly inversely related to the ratio of AST/ALT (r = -0.465, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001) and HDL cholesterol (r = -0.428, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001).\u003c/p\u003e\n\u003cp\u003eThey suggest that BMI as a sign of central metabolic health in our patients has effects on metabolic and liver function, and has an indirect impact on semen quality.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.3 Association between Electrolyte and Acid-Base Balance Indices and Semen Parameters\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.3.1 Potassium, Sodium, Chloride\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePotassium, and chloride serum levels and sodium each possessed very weak associations with all \u0026nbsp;indices of semen quality (concentration, motility, morphology, DFI, HDS), each having absolute correlation coefficients \u0026lt; -0.1 and no direct significant correlations. This indicates that in physiological ranges, serum electrolyte changes likely have little direct impact upon semen quality.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.3.2 Calcium, Magnesium, Phosphate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCalcium was very weakly positively related to semen volume (r = 0.072), sperm concentration (r = 0.087), and normal morphology rate (r = 0.142, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001). Magnesium was also extremely weakly directly related to semen parameters. Again, however, magnesium was positively related to percentage progressively motile sperm (r = 0.210, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001). Despite the small coefficient, this would suggest that perhaps there is a very weak positive impact of magnesium on motility of sperm. There was no significant relation we could identify between phosphorus (as serum phosphate) and the semen parameters.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.3.3 Combining Capacity of CO\u003csub\u003e2\u003c/sub\u003e and Anion\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCO\u003csub\u003e2\u003c/sub\u003e combining capacity (indicator of acid-base status) was significantly and positively (r = 0.196, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001) correlated with normal morphology. CO2 combining capacity was strongly and inversely correlated with the anion gap (r = -0.523, P \u0026lt; 0.001), consistent with expected physiological relationships. However, the anion gap was inversely correlated with normal morphology (r = -0.142, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05). A high anion gap could indicate the accumulation of metabolic acidosis or a surplus of unmeasured anions; its inverse correlation with normal morphology may be an important finding that warrants further attention.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.4 Relationship between Indices of Renal Function and Semen Parameters\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe renal function indices (urea, creatinine, uric acid, urea-to-creatinine ratio) demonstrated poor correlations (|r| \u0026lt; 0.1) between the major semen parameters (sperm motility, morphology, sperm concentration). It implies that, in our population, variations of renal function in the ordinary range are not related to semen quality in any obvious direct manner.Uric acid is more connected to metabolic markers. Uric acid was highly correlated with weight (r = 0.355, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001), BMI (r = 0.361, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001), ALT (r = 0.177, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05), AST (r = 0.181, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05), and triglycerides (r = 0.332, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001). It implies that uric acid has a larger role as an element of the metabolic syndrome spectrum, as opposed to an autonomous identifier of renal function, and it influences, in an indirect manner, reproductive outcome along the metabolic routes.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.5 Association between Liver Enzyme Indices and Semen Parameters\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFor liver enzymes, pre-treatment AST or ALT levels did not exhibit significant correlations with semen parameters. But ALT and AST also exhibited significant correlations with weight, BMI, triglycerides, and other metabolic parameters (explained above, ALT vs BMI r = 0.496). AST/ALT ratio was significantly and inversely correlated with weight (r = -0.426, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001) and BMI (r = -0.465, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001), and positively correlated with progressive motility (r = 0.125, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05) and total motility (r = 0.121, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05). AST/ALT ratio decreased in non-alcoholic fatty liver disease (NAFLD); liver damage due to fatty liver (present as decreased AST/ALT ratio) may be implicated in sperm motility defect. It may be an indirect impact via systemic metabolic disorder and oxidative stress.\u003c/p\u003e\n\u003cp\u003eGamma-glutamyl transferase (GGT) was strongly related to DBP (r = 0.261, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001), weight (r = 0.344, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001), BMI (r = 0.374, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001), triglycerides (r = 0.534, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001), as well as fasting glucose (r = 0.150, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05), and each further validates the application of GGT as a marker for metabolic disease. GGT was directly but weakly related to semen parameters; alkaline phosphatase had poor correlations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.6 Protein Metabolism and Nutrition Indices versus Semen Parameters\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.6.1 Total Protein, Albumin, Globulin, A/G Ratio\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThere was a significant and positive correlation between rate of normal morphology and total protein (r = 0.165, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05). There was highly significant positive correlation between calcium and total protein (r = 0.510, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001), which indicates interrelationship between markers of nutrition and biochemical status.\u003c/p\u003e\n\u003cp\u003eAlbumin was weakly negatively correlated by itself with normal morphology (r = -0.052), and albumin-to-globulin ratio (A/G ratio) was negatively correlated with normal morphology (r = -0.193, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05). A decreased A/G ratio will likely imply chronic inflammation or liver disease; its negative correlation with normal sperm morphology may perhaps imply that systemic inflammatory state can exert an undesirable effect on spermatogenesis.\u003c/p\u003e\n\u003cp\u003eGlobulin, in contrast, was positively related to normal morphology (r = 0.197, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001). Globulin is a key component of immunoproteins, and the positive relation of globulin to sperm morphology is a curious finding. It may plausibly suggest that there must be some degree of immunocyte function to preserve the testicular microenvironment, or may relate to one of the components of the seminal plasma which carries immunoglobulins. Speculative explanations, both, and other work must be performed prior to the etiologic factors being certain.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.7 Association of Bilirubin Metabolism and Semen\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eImportantly, we first identified a positive correlation between the pattern of unconjugated bilirubin and semen quality parameters. In particular, we observed that high concentrations of unconjugated bilirubin possessed an incrementally increasing level of normal sperm morphology (r = 0.117, nominal \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05 (did not remain significant after FDR correction). As a natural antioxidant, a higher level of bilirubin may have countered the impact of oxidative stress and, therefore, spared sperm morphology. Bilirubin was nonsignificantly and weakly related to the other semen parameters (e.g., sperm motility and concentration).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.8 Association between Glycemic and Lipid Metabolic Indices and Semen Parameters\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.8.1 Fasting Glucose\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFasting glucose in the bloodstream was inversely related to semen volume (r = -0.068, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05). It was also (weak) negatively related to progressive motility (r = -0.082, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05) and to complete motility (r = -0.122, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05). Based on these findings, it can be concluded that at nondiabetic level, elevated glucose in the bloodstream may have a very minimal harmful effect on motility of sperm. Although the magnitude of these relations is low, direction conforms to evidence that diabetic men have deficient semen parameters.\u003csup\u003e[19]\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.8.2 Lipid Profile\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTriglycerides were inversely correlated with semen volume (r = -0.144, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05), and strongly with BMI, liver enzymes, and other measures of metabolism (as reported already, above). We found that in men with high levels of triglycerides, percentage progressively motile sperm (r = -0.085) and total motility (r = -0.080) are slightly reduced; in our patient group, these reductions, although statistically significant, were slender in degree. Elevated levels of cholesterol and triglycerides have been found to have a detrimental impact on sperm motility.\u003csup\u003e[20]\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003eTotal cholesterol had weak positive correlations with semen parameters. Total cholesterol had strong, positive correlations with apolipoprotein B (ApoB, r = 0.880, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001) and LDL-C (r = 0.843, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001), the latter being an atherogenic lipid of first importance.Apolipoprotein A-1 was strongly positively correlated with HDL-C (r = 0.876, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001), as would be predicted for its role as the chief apolipoprotein of HDL. ApoA-1 was not significantly directly correlated with semen parameters but was inversely correlated with HDS (r = -0.112, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.01). HDL-C was positively correlated with volume of semen (r = 0.109, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05). This is an unusual positive correlation between a marker of the lipid profile and semen quality, the mechanism is unclear; it may be secondary to the antioxidant and anti-inflammatory effects of HDL.LDL cholesterol was highly collinear with total cholesterol and ApoB, and had very poor direct correlations with semen parameters.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e3.9 Relationship between Cardiac Enzyme Profile and Other Indices and Semen Characteristics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eLactate dehydrogenase (LDH) was highly correlated with DBP (r = 0.245, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001), BMI (r = 0.289, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001), ALT (r = 0.394, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001), and AST (r = 0.436, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.001),which is Consistent with physiological function. On the other hand, LDH was very weakly correlated directly with semen parameters. LDH is an important glycolytic enzyme and it is found highly in tissues like skeletal muscle, myocardium, and testes; therefore, its variation has more to do with metabolic factors than with semen quality per se. Creatine kinase and its isoenzymes also demonstrated equally poor correlations with semen parameters. However, we noted that osmotic pressure was positively correlated with normal sperm morphology (r = 0.171, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05) and the DNA fragmentation index (DFI; r = 0.187, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05), and negatively correlated with high DNA stainability (HDS; r = \u0026minus;0.171, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05). These correlations may reflect the effects of a hypotonic environment, which may be associated with sperm swelling and deformity, reduced motility, and disruption of the plasma membrane.\u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eIn this cross-sectional analysis of 264 men undergoing routine health screening, we evaluated correlations between semen parameters and systemic biochemical indices categorized into predefined biological domains. Overall, associations were modest in magnitude, and most effect sizes were small, suggesting subtle rather than clinically pronounced relationships.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.1 Semen Parameter Internal Consistency\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOther than the expected internal consistency among semen parameters, one notable observation in our dataset was the preliminary signal involving serum chloride showed a nominally significant difference (\u003cem\u003eP\u003c/em\u003e = 0.0139) before multiple testing correction. However, after FDR adjustment, this difference was no longer statistically significant. While this precludes a definitive conclusion, the observed directional trend may warrant further investigation in larger cohorts. Chloride is known to participate in cellular osmoregulation and membrane stability in general physiological contexts.\u003csup\u003e[21]\u003c/sup\u003e However, in the context of the present cross-sectional analysis, our findings should not be interpreted as evidence of a direct mechanistic effect of chloride on sperm function. Rather, the observed association may reflect broader systemic physiological states that warrant further mechanistic exploration. Given the limited sample size and modest effect size observed, this finding remains exploratory and requires validation in larger cohorts.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.2. Age and Blood Pressure Weak Associations with Fertility\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAge showed low negative correlations with semen volume and positive with DFI, as would be predicted by the general view that with age, reproductive function slowly deteriorates. Blood pressure-diastolic pressure, in particular-showed inverse correlations with semen volume and no strong correlation with basic semen parameters of concentration, motility, and morphology. This suggests that, per se, pressure in the bloodstream is unlikely to be a cause of reduced semen quality. Blood pressure may reflect broader cardiovascular and metabolic status. However, the present data do not allow inference regarding specific intermediary mechanisms linking vascular parameters to semen quality.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.3 Intermediate role of BMI in the Metabolic Syndrome Network\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBecause the correlations of BMI with semen parameters were in general quite weak in this study, none of the observed associations reached a clinically meaningful magnitude. While metabolic dysfunction has been clearly aligned with male reproductive impairment in the literature, results from this investigation indicate that BMI in and of itself may not be a key determinant of semen quality among a generally healthy screening population.\u003csup\u003e[18]\u003c/sup\u003e Here, BMI related more strongly to metabolic markers such as ALT, AST, GGT, triglycerides, and uric acid, suggesting that BMI may reflect metabolic status rather than directly mediate impaired spermatogenesis.\u003csup\u003e[22]\u003c/sup\u003e In this cohort, BMI showed only weak associations with semen parameters, indicating that adiposity alone may not be a dominant correlate of semen variation within a generally healthy screening population.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.4 Magnesium and Bilirubin: Potential Protective Associations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eMagnesium is recognized as a cofactor in numerous metabolic processes, including ATP-related pathways and mitochondrial function.\u003csup\u003e[23]\u003c/sup\u003e Nevertheless, the associations observed in this study do not establish a causal link between serum magnesium levels and sperm metabolism, and should be interpreted as exploratory correlations requiring experimental validation. Previous studies have reported correlations between serum magnesium and sperm motility; however, whether circulating magnesium levels reflect seminal plasma concentrations remains uncertain. Wong et al. determined that seminal plasma concentrations of magnesium are highly correlated to sperm number and motility and hypothesized that magnesium has effects upon sperm flagellar movement and ATP synthesis.\u003csup\u003e[24]\u003c/sup\u003e Several animal studies have suggested that magnesium deficiency is associated with altered male reproductive function.\u003csup\u003e[25]\u003c/sup\u003e Although magnesium participates in ATP-related cellular processes, the modest correlation observed here does not justify clinical recommendations regarding supplementation. The clinical relevance of circulating magnesium concentrations for semen quality remains uncertain and requires prospective validation.\u003csup\u003e[26]\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003eDuring the last decades, many investigations have been carried out to determine whether antioxidant supplementation is able to enhance semen quality.\u003csup\u003e[27]\u003c/sup\u003e Spermatozoa are rich in polyunsaturated fatty acids and are very sensitive to ROS. High levels of ROS may promote lipid peroxidation and DNA fragmentation, thus impairing sperm function.\u003csup\u003e[28]\u003c/sup\u003e In physiological conditions, seminal plasma contains a variety of antioxidants including vitamin C, vitamin E, glutathione, superoxide dismutase, etc. which neutralize ROS.\u003csup\u003e[29]\u003c/sup\u003e Bilirubin is an endogenous antioxidant that is associated with modulation of oxidative stress.\u003csup\u003e[30]\u003c/sup\u003e In our study, total bilirubin was correlated with normal sperm morphology; however, its functional relevance to sperm chromatin integrity remains to be clarified. Intuitively, moderate levels of bilirubin may be associated with reduced oxidative stress in tissues such as the testes against oxidative damage while very high levels of bilirubin may become pathologic and interfere with ROS signaling across sperm capacitation.\u003csup\u003e[13,27,31]\u003c/sup\u003e These findings should be interpreted cautiously and do not establish a basis for therapeutic intervention. Further studies incorporating direct oxidative stress measurements are required to determine whether circulating bilirubin levels have functional relevance for sperm biology.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.5 Influence of Serum Protein Indices in Relation to Semen Quality\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn the present study, serum protein indices-total protein, albumin-to-globulin ratio (A/G ratio), and globulin-exhibited small but significant correlations with sperm morphology. Total protein and globulin revealed weak but statistically significant positive correlations with the percentage of morphologically normal spermatozoa. Though the effect sizes were small, these associations may reflect systemic protein status without establishing a direct relationship with spermatogenesis.\u003c/p\u003e\n\u003cp\u003eOne hypothesis concerns the functional composition of the globulin fraction.\u003csup\u003e[32]\u003c/sup\u003e Globulin represents a heterogeneous mixture of proteins, including immunoglobulins, hormone-binding proteins - such as sex hormone-binding globulin, SHBG - and nutrient transport proteins, including transferrin.\u003csup\u003e[33]\u003c/sup\u003e A number of these constituent proteins have recognized roles in male reproductive physiology. Thus, SHBG is essential to the regulation of circulating testosterone bioavailability; reduced levels of SHBG commonly occur in men with metabolic syndrome and have been linked with impaired sperm morphology.\u003csup\u003e[34]\u003c/sup\u003e Similarly, transferrin is involved in the transport of trace elements, including iron, which are required for normal testicular function and spermatogenesis.\u003csup\u003e[35]\u003c/sup\u003e Although the current study did not measure these subfractions directly, the positive association of globulin with sperm morphology observed may reflect, at least indirectly, the biological activity of these proteins.\u003c/p\u003e\n\u003cp\u003eBy contrast, the inverse correlation between the A/G ratio and normal morphology may indicate physiological relevance, since disturbances in the relative distribution of albumin and globulin as reflected by a lower A/G ratio may reflect systemic inflammatory or metabolic alterations.\u003csup\u003e[36]\u003c/sup\u003e However, the present findings do not allow inference regarding downstream testicular oxidative stress or spermatogenic impairment, and such mechanistic pathways remain speculative without direct biological assessment. However, these interpretations remain purely speculative given the cross-sectional nature of the study and lack of direct inflammatory or hormonal measurements. Indeed, additional studies combining detailed immunologic and endocrine evaluations will be required to conclude whether serum protein patterns can serve as early biomarkers of subtle reproductive impairment.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.6 Potential Role of Systemic Osmolality in Sperm Function.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSerum osmolality emerged as one of the more consistently associated biochemical markers in this study, with convergent correlations within multiple semen parameters. Higher osmolality was positively associated with DFI and, intriguingly, also with the percentage of normal morphology, while showing a negative correlation with HDS. Although these associations were moderate, the internal consistency may suggest a potential relationship between systemic osmotic balance and sperm chromatin integrity.\u003c/p\u003e\n\u003cp\u003eOsmotic stress is a well-recognized driver of cellular dysfunction, with particular relevance in tissues with high metabolic demands, including the testes and epididymis.\u003csup\u003e[37]\u003c/sup\u003e Experimental studies suggest that hyperosmotic stress can influence cellular homeostasis and oxidative balance. In the present observational dataset, however, serum osmolality represents a systemic measurement and cannot be assumed to directly translate into testicular microenvironmental conditions. Therefore, the associations reported here should not be interpreted as evidence of osmotic stress\u0026ndash;induced sperm damage, but rather as signals warranting further mechanistic investigation. Previous experimental studies in animal models have indicated that sperm subjected to hyperosmotic conditions exhibit increased superoxide production, lipid peroxidation, and decreased fertilization potential.\u003csup\u003e[37]\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003eThe positive association of serum osmolality with DFI in the present study may be biologically plausible; however, mechanistic pathways cannot be inferred from the current design. High osmolality may reflect systemic dehydration or metabolic disturbances, although their relevance to oxidative stress in the male reproductive tract was not directly assessed in this study.\u003csup\u003e[38]\u003c/sup\u003e The corresponding negative correlation with HDS-a marker of chromatin immaturity-may indicate a shift toward DNA fragmentation in response to osmotic challenge. In contrast, the mild positive association with normal morphology may reflect complex biological variability, and speculative mechanisms should be interpreted cautiously.\u003csup\u003e[32]\u003c/sup\u003e\u003c/p\u003e\n\u003cp\u003eImportantly, osmolality is a commonly measured biochemical parameter in the clinical setting, and yet its possible implications for male reproductive health have been poorly noted. While serum osmolality demonstrated consistent correlations with selected semen parameters, these observations remain associative and should not be interpreted as establishing biomarker utility without longitudinal confirmation. Causality requires further investigation in prospective studies to clarify whether systemic osmotic status is associated with sperm chromatin integrity.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e4.7 Limitations and Prospects\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis was a cross-sectional survey and, as such, cannot offer any basis for inferences about causality. The sample size was relatively small and, especially for subgroup analysis, power was small. Given the number of biochemical indices evaluated, we applied Benjamini\u0026ndash;Hochberg false discovery rate adjustment to limit type I error inflation. Associations that did not remain significant after correction were treated as exploratory. Even among statistically significant findings, effect sizes were modest, and results should be interpreted as hypothesis-generating rather than confirmatory. Although several statistically significant correlations were identified, most effect sizes were small (|r| \u0026lt; 0.25), indicating limited clinical relevance at the individual level. In addition, residual confounding cannot be excluded, as detailed lifestyle variables, environmental exposures, and dietary factors were not systematically captured. In addition, recruitment from a health-check population may introduce selection bias, potentially limiting generalizability to broader community settings.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eThis cross-sectional analysis among 264 men undergoing routine health examinations offers new insights into the subtle biochemical determinants of semen quality. First, impaired semen quality was characterized by a simultaneous reduction in sperm concentration, motility, morphology, and DNA integrity, thus reaffirming that comprehensive semen assessment is required for evaluating male reproductive potential.\u003c/p\u003e\n\u003cp\u003eAmong more than forty routine biochemical indices evaluated, serum chloride showed an exploratory association with semen quality parameters that did not remain statistically significant after FDR correction. Although it did not remain significant after FDR adjustment, its possible implication in reproductive physiology may warrant further investigation in adequately powered longitudinal studies.\u003c/p\u003e\n\u003cp\u003eThird, the study points out protein metabolism indices, in particular globulin and albumin-to-globulin ratio, as potential markers of sperm morphologic integrity. Although effect sizes were modest, these associations raise the possibility that systemic protein distribution and transport-related pathways may reflect subtle aspects of spermatogenic function.\u003c/p\u003e\n\u003cp\u003eFourth, serum osmolality showed consistent correlations with various semen parameters, such as DFI and HDS, indicating a potential role of systemic osmotic status in the modulation of sperm chromatin stability. Since osmolality is an easily clinically accessible parameter, it may represent a potential biomarker requiring further validation in longitudinal studies. Finally, the traditional metabolic risk factors of BMI, glucose and lipid levels were only weakly associated with semen quality in this relatively healthy population, suggesting their influence may be indirect or evident only in more metabolically impaired cohorts. Taken together, these findings indicate modest correlations between selected systemic biochemical indices and semen parameters in a health-check population. Given the cross-sectional design and small effect sizes, these associations should not be interpreted as causal and require confirmation in longitudinal and mechanistic studies before clinical application is considered. The primary contribution of this study lies in identifying patterns within routinely collected clinical data that may inform future targeted research in male reproductive epidemiology.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"456\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\" style=\"width: 140px;\"\u003e\n \u003cp\u003eAbbreviation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\" style=\"width: 316px;\"\u003e\n \u003cp\u003eFull Term\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eA/G ratio\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eAlbumin-to-globulin ratio\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eALP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eAlkaline phosphatase\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eALT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eAlanine aminotransferase\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eApoA-1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eApolipoprotein A-1\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eApoB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eApolipoprotein B\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eAST\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eAspartate aminotransferase\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eBMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eBody mass index\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eCO2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eCarbon dioxide\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eDBP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eDiastolic blood pressure\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eDFI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eDNA fragmentation index\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eGGT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eGamma-glutamyl transferase\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eHDS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eHigh DNA Stainability\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eHDL-C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eHigh-density lipoprotein cholesterol\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eIQR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eInterquartile range\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eLDH\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eLactate dehydrogenase\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eLDL-C\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eLow-density lipoprotein cholesterol\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eNAFLD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eNon-alcoholic fatty liver disease\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eROS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eReactive oxygen species\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eSBP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eSystolic blood pressure\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eSCSA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eSperm chromatin structure assay\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eSHBG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd nowrap=\"\"\u003e\n \u003cp\u003eSex hormone-binding globulin\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was approved by the Ethics Committee of Fujian Maternity and Child Health Hospital (Approval No. 2024KY077). All procedures were conducted in accordance with the ethical standards of the institutional research committee and with the 1964 Declaration of Helsinki and its later amendments. The requirement for individual informed consent was waived due to the retrospective and anonymized nature of the data analysis, as confirmed by the ethics committee.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable. All data presented in this manuscript are anonymized and do not contain any identifiable information of individual participants.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and/or analyzed during the current study contain potentially identifiable information and are therefore not publicly available. De-identified data may be made available from the corresponding author upon reasonable request and subject to approval by the Ethics Committee of Fujian Maternity and Child Health Hospital.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by the Natural Science Foundation of Fujian Province (Grant No. 2024J011060). The funding body had no role in the design of the study; in the collection, analysis, or interpretation of data; or in the writing of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eXR and LN contributed equally to conceptualization, methodology, formal analysis, and writing of the original draft. YF contributed to data curation and validation. GA contributed to software development and investigation. XF and DL contributed equally to supervision, project administration, funding acquisition, and manuscript review and editing. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eCipriani, S. et al. Trend of change of sperm count and concentration over the last two decades: A systematic review and meta-regression analysis. \u003cem\u003eAndrology\u003c/em\u003e \u003cb\u003e11\u003c/b\u003e (6), 997\u0026ndash;1008. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/andr.13396\u003c/span\u003e\u003cspan address=\"10.1111/andr.13396\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2023). Epub 2023 Feb 7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLevine, H. et al. Temporal trends in sperm count: a systematic review and meta-regression analysis of samples collected globally in the 20th and 21st centuries. \u003cem\u003eHum. Reprod. Update\u003c/em\u003e. \u003cb\u003e29\u003c/b\u003e (2), 157\u0026ndash;176. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/humupd/dmac035\u003c/span\u003e\u003cspan address=\"10.1093/humupd/dmac035\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2023).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDutta, S., Sengupta, P., Slama, P. \u0026amp; Roychoudhury, S. Oxidative Stress, Testicular Inflammatory Pathways, and Male Reproduction. \u003cem\u003eInt. J. Mol. Sci.\u003c/em\u003e \u003cb\u003e22\u003c/b\u003e (18), 10043. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/ijms221810043\u003c/span\u003e\u003cspan address=\"10.3390/ijms221810043\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2021).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLassen, E., Pacey, A., Skytte, A. B. \u0026amp; Montgomerie, R. Recent decline in sperm motility among donor candidates at a sperm bank in Denmark. \u003cem\u003eHum. Reprod.\u003c/em\u003e \u003cb\u003e39\u003c/b\u003e (8), 1618\u0026ndash;1627. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/humrep/deae115\u003c/span\u003e\u003cspan address=\"10.1093/humrep/deae115\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2024).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLuo, X., Yin, C., Shi, Y., Du, C. \u0026amp; Pan, X. Global trends in semen quality of young men: a systematic review and regression analysis. \u003cem\u003eJ. Assist. Reprod. Genet.\u003c/em\u003e \u003cb\u003e40\u003c/b\u003e (8), 1807\u0026ndash;1816. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s10815-023-02859-z\u003c/span\u003e\u003cspan address=\"10.1007/s10815-023-02859-z\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2023). Epub 2023 Jun 19.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHuang, C. et al. Decline in semen quality among 30,636 young Chinese men from 2001 to 2015. \u003cem\u003eFertil. Steril.\u003c/em\u003e \u003cb\u003e107\u003c/b\u003e (1), 83\u0026ndash;88e2. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.fertnstert.2016.09.035\u003c/span\u003e\u003cspan address=\"10.1016/j.fertnstert.2016.09.035\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2017). Epub 2016 Oct 25.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eService, C. A., Puri, D., Al Azzawi, S., Hsieh, T. C. \u0026amp; Patel, D. P. The impact of obesity and metabolic health on male fertility: a systematic review. \u003cem\u003eFertil. Steril.\u003c/em\u003e \u003cb\u003e120\u003c/b\u003e (6), 1098\u0026ndash;1111. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.fertnstert.2023.10.017\u003c/span\u003e\u003cspan address=\"10.1016/j.fertnstert.2023.10.017\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2023). Epub 2023 Oct 14.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBlaurock, J., Grunewald, S. \u0026amp; Engel, K. M. Intra-individual variability of the human seminal plasma metabolome. \u003cem\u003eAsian J. Androl.\u003c/em\u003e \u003cb\u003e27\u003c/b\u003e (5), 586\u0026ndash;591. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.4103/aja2024110\u003c/span\u003e\u003cspan address=\"10.4103/aja2024110\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2025). Epub 2025 Feb 28.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXia, P. et al. Macrophage-Related Testicular Inflammation in Individuals with Idiopathic Non-Obstructive Azoospermia: A Single-Cell Analysis. \u003cem\u003eInt. J. Mol. Sci.\u003c/em\u003e \u003cb\u003e24\u003c/b\u003e (10), 8819. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/ijms24108819\u003c/span\u003e\u003cspan address=\"10.3390/ijms24108819\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2023).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu, J. C. et al. Myd88 Signaling Is Involved in the Inflammatory Response in LPS-Induced Mouse Epididymitis and Bone-Marrow-Derived Dendritic Cells. \u003cem\u003eInt. J. Mol. Sci.\u003c/em\u003e \u003cb\u003e24\u003c/b\u003e (9), 7838. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/ijms24097838\u003c/span\u003e\u003cspan address=\"10.3390/ijms24097838\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2023).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFerramosca, A. \u0026amp; Zara, V. Diet and Male Fertility: The Impact of Nutrients and Antioxidants on Sperm Energetic Metabolism. \u003cem\u003eInt. J. Mol. Sci.\u003c/em\u003e \u003cb\u003e23\u003c/b\u003e (5), 2542. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/ijms23052542\u003c/span\u003e\u003cspan address=\"10.3390/ijms23052542\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2022).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShi, X. et al. Associations between blood metal/ metalloid concentration and human semen quality and sperm function: A cross-sectional study in Hong Kong. \u003cem\u003eJ. Trace Elem. Med. Biol.\u003c/em\u003e \u003cb\u003e65\u003c/b\u003e, 126735. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.jtemb.2021.126735\u003c/span\u003e\u003cspan address=\"10.1016/j.jtemb.2021.126735\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2021). Epub 2021 Feb 23.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChen, Y. Y. \u0026amp; Chen, W. L. Serum Bilirubin and Sperm Quality in Adult Population. \u003cem\u003eToxics\u003c/em\u003e \u003cb\u003e10\u003c/b\u003e (6), 295. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/toxics10060295\u003c/span\u003e\u003cspan address=\"10.3390/toxics10060295\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2022).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLiu, M. \u0026amp; Dudley, S. C. Jr Beyond Ion Homeostasis: Hypomagnesemia, Transient Receptor Potential Melastatin Channel 7, Mitochondrial Function, and Inflammation. \u003cem\u003eNutrients\u003c/em\u003e \u003cb\u003e15\u003c/b\u003e (18), 3920. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/nu15183920\u003c/span\u003e\u003cspan address=\"10.3390/nu15183920\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2023).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNguyen, N. D., Le, M. T., Tran, N. Q. T., Nguyen, Q. H. V. \u0026amp; Cao, T. N. Micronutrient supplements as antioxidants in improving sperm quality and reducing DNA fragmentation. \u003cem\u003eBasic. Clin. Androl.\u003c/em\u003e \u003cb\u003e33\u003c/b\u003e (1), 23. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12610-023-00197-9\u003c/span\u003e\u003cspan address=\"10.1186/s12610-023-00197-9\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2023).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJohnson, T. A. et al. Non-Targeted Analysis of Environmental Contaminants and Their Associations with Semen Health Factors in Men from New York City. \u003cem\u003eEnviron. Health (Wash)\u003c/em\u003e. \u003cb\u003e3\u003c/b\u003e (2), 164\u0026ndash;176. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1021/envhealth.4c00165\u003c/span\u003e\u003cspan address=\"10.1021/envhealth.4c00165\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2024).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGreenberg, D. R. et al. The association of hypertension and antihypertensive medications on semen parameters among men presenting for fertility evaluation. \u003cem\u003eAndrology\u003c/em\u003e \u003cb\u003e13\u003c/b\u003e (8), 2083\u0026ndash;2090. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/andr.70010\u003c/span\u003e\u003cspan address=\"10.1111/andr.70010\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2025). Epub 2025 Feb 6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJi, F. et al. BMI is associated with sperm quality and sex hormones in men: a meta-analysis. \u003cem\u003eFront. Endocrinol. (Lausanne)\u003c/em\u003e. \u003cb\u003e16\u003c/b\u003e, 1714019. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fendo.2025.1714019\u003c/span\u003e\u003cspan address=\"10.3389/fendo.2025.1714019\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2025).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang, W., Tong, L., Jin, B. \u0026amp; Sun, D. Diabetic testicular dysfunction and spermatogenesis impairment: mechanisms and therapeutic prospects. \u003cem\u003eFront. Endocrinol. (Lausanne)\u003c/em\u003e. \u003cb\u003e16\u003c/b\u003e, 1653975. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fendo.2025.1653975\u003c/span\u003e\u003cspan address=\"10.3389/fendo.2025.1653975\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2025).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePłaczkowska, S., Rodak, K., Kmieciak, A., Gilowska, I. \u0026amp; Kratz, E. M. Exploring correlations: Human seminal plasma and blood serum biochemistry in relation to semen quality. \u003cem\u003ePLoS One\u003c/em\u003e. \u003cb\u003e19\u003c/b\u003e (6), e0305861. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1371/journal.pone.0305861\u003c/span\u003e\u003cspan address=\"10.1371/journal.pone.0305861\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2024).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRaut, S. K. et al. Chloride ions in health and disease. \u003cem\u003eBiosci. Rep.\u003c/em\u003e \u003cb\u003e44\u003c/b\u003e (5), BSR20240029. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1042/BSR20240029\u003c/span\u003e\u003cspan address=\"10.1042/BSR20240029\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2024).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang, T. et al. Disrupted spermatogenesis in a metabolic syndrome model: the role of vitamin A metabolism in the gut-testis axis. \u003cem\u003eGut\u003c/em\u003e \u003cb\u003e71\u003c/b\u003e (1), 78\u0026ndash;87. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1136/gutjnl-2020-323347\u003c/span\u003e\u003cspan address=\"10.1136/gutjnl-2020-323347\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2022). Epub 2021 Jan 27.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKr\u0026ouml;se, J. L. \u0026amp; de Baaij, J. H. F. Magnesium biology. Nephrol Dial Transplant. ;39(12):1965\u0026ndash;1975. (2024). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/ndt/gfae134\u003c/span\u003e\u003cspan address=\"10.1093/ndt/gfae134\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Erratum in: Nephrol Dial Transplant. 2025;40(6):1261. doi: 10.1093/ndt/gfae219.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWong, W. Y. et al. The impact of calcium, magnesium, zinc, and copper in blood and seminal plasma on semen parameters in men. \u003cem\u003eReprod. Toxicol.\u003c/em\u003e \u003cb\u003e15\u003c/b\u003e (2), 131\u0026ndash;136. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/s0890-6238(01)00113-7\u003c/span\u003e\u003cspan address=\"10.1016/s0890-6238(01)00113-7\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2001 Mar-Apr).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAlvarez, J. G. et al. Ethanol accelerates acrosomal loss in human spermatozoa. \u003cem\u003eJ. Androl.\u003c/em\u003e \u003cb\u003e9\u003c/b\u003e (6), 357\u0026ndash;366. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/j.1939-4640.1988.tb01065.x\u003c/span\u003e\u003cspan address=\"10.1002/j.1939-4640.1988.tb01065.x\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (1988 Nov-Dec).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVerma, H. \u0026amp; Garg, R. Evaluation of synergistic combination comprising magnesium orotate, menaquinone-7, and cholecalciferol for management of type 2 diabetes and dyslipidemia. \u003cem\u003eMagnes Res.\u003c/em\u003e \u003cb\u003e33\u003c/b\u003e (4), 88\u0026ndash;105. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1684/mrh.2020.0472\u003c/span\u003e\u003cspan address=\"10.1684/mrh.2020.0472\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2020).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShowell, M. G., Brown, J., Yazdani, A., Stankiewicz, M. T. \u0026amp; Hart, R. J. Antioxidants for male subfertility. Cochrane Database Syst Rev. ;(1):CD007411. (2011). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/14651858.CD007411.pub2\u003c/span\u003e\u003cspan address=\"10.1002/14651858.CD007411.pub2\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Update in: Cochrane Database Syst Rev. 2014;(12):CD007411. doi: 10.1002/14651858.CD007411.pub3.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWang, Y., Fu, X. \u0026amp; Li, H. Mechanisms of oxidative stress-induced sperm dysfunction. \u003cem\u003eFront. Endocrinol. (Lausanne)\u003c/em\u003e. \u003cb\u003e16\u003c/b\u003e, 1520835. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fendo.2025.1520835\u003c/span\u003e\u003cspan address=\"10.3389/fendo.2025.1520835\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2025).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAitken, R. J. et al. A Comparative Analysis of the Antioxidant Profiles Generated by the RoXstaTM System for Diverse Biological Fluids Highlights the Powerful Protective Role of Human Seminal Plasma. \u003cem\u003eAntioxid. (Basel)\u003c/em\u003e. \u003cb\u003e14\u003c/b\u003e (1), 90. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/antiox14010090\u003c/span\u003e\u003cspan address=\"10.3390/antiox14010090\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2025).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eČepelak, I., Dodig, S. \u0026amp; Pavić, I. Bilirubin - new insights into an old molecule. \u003cem\u003eBiochem. Med. (Zagreb)\u003c/em\u003e. \u003cb\u003e35\u003c/b\u003e (2), 020501. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.11613/BM.2025.020501\u003c/span\u003e\u003cspan address=\"10.11613/BM.2025.020501\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2025). Epub 2025 Apr 15.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHenkel, R., Sandhu, I. S. \u0026amp; Agarwal, A. The excessive use of antioxidant therapy: A possible cause of male infertility? Andrologia. ;51(1):e13162. (2019). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/and.13162\u003c/span\u003e\u003cspan address=\"10.1111/and.13162\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 2018 Sep 26.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePotiris, A. et al. From Inflammation to Infertility: How Oxidative Stress and Infections Disrupt Male Reproductive Health. \u003cem\u003eMetabolites\u003c/em\u003e \u003cb\u003e15\u003c/b\u003e (4), 267. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/metabo15040267\u003c/span\u003e\u003cspan address=\"10.3390/metabo15040267\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2025).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePalani, A. \u0026amp; Alahmar, A. Impact of oxidative stress on semen parameters in normozoospermic infertile men: a case\u0026ndash;control study. \u003cem\u003eAfr. J. Urol.\u003c/em\u003e \u003cb\u003e26\u003c/b\u003e, 50. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s12301-020-00061-6\u003c/span\u003e\u003cspan address=\"10.1186/s12301-020-00061-6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2020).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMartins, A. D., Majzoub, A. \u0026amp; Agawal, A. Metabolic Syndrome and Male Fertility. \u003cem\u003eWorld J. Mens Health\u003c/em\u003e. \u003cb\u003e37\u003c/b\u003e (2), 113\u0026ndash;127. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.5534/wjmh.180055\u003c/span\u003e\u003cspan address=\"10.5534/wjmh.180055\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2019). Epub 2018 Oct 22.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAlmadaly, E. A. et al. Fertility-associated biochemical components in seminal plasma and serum of buffalo (Bubalus bubalis) bulls. \u003cem\u003eFront. Vet. Sci.\u003c/em\u003e \u003cb\u003e9\u003c/b\u003e, 1043379. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3389/fvets.2022.1043379\u003c/span\u003e\u003cspan address=\"10.3389/fvets.2022.1043379\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2023).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eXiao, M. et al. High Systemic Inflammatory Protein Index Is Associated with Clinically Ineffective Reperfusion in Acute Anterior Circulation Ischemic Stroke Patients Undergoing Endovascular Treatment. \u003cem\u003eMol. Neurobiol.\u003c/em\u003e \u003cb\u003e61\u003c/b\u003e (10), 7707\u0026ndash;7716. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s12035-024-04068-w\u003c/span\u003e\u003cspan address=\"10.1007/s12035-024-04068-w\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2024). Epub 2024 Mar 1.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJoseph, A., Shur, B. D., Ko, C., Chambon, P. \u0026amp; Hess, R. A. Epididymal hypo-osmolality induces abnormal sperm morphology and function in the estrogen receptor alpha knockout mouse. \u003cem\u003eBiol. Reprod.\u003c/em\u003e \u003cb\u003e82\u003c/b\u003e (5), 958\u0026ndash;967. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1095/biolreprod.109.080366\u003c/span\u003e\u003cspan address=\"10.1095/biolreprod.109.080366\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2010). Epub 2010 Feb 3.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDutta, S., Sengupta, P., Slama, P. \u0026amp; Roychoudhury, S. Oxidative Stress, Testicular Inflammatory Pathways, and Male Reproduction. \u003cem\u003eInt. J. Mol. Sci.\u003c/em\u003e \u003cb\u003e22\u003c/b\u003e (18), 10043. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/ijms221810043\u003c/span\u003e\u003cspan address=\"10.3390/ijms221810043\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2021).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Semen quality, Male reproductive health, Cross-sectional study, Systemic biomarkers, Metabolic status, Osmolality","lastPublishedDoi":"10.21203/rs.3.rs-8982176/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8982176/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eTo evaluate associations between routinely measured systemic biochemical indices and semen quality parameters in a real-world health-check population.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis cross-sectional observational study included 264 men aged 21\u0026ndash;60 years who underwent standardized health examinations, including semen analysis and comprehensive biochemical testing. Semen parameters were evaluated according to WHO reference limits (2010 edition), and all outcomes were analyzed as continuous variables. Biochemical indices were categorized into predefined domains reflecting metabolic status, oxidative/antioxidant balance, and electrolyte\u0026ndash;osmotic homeostasis. Associations were assessed using correlation analyses with false discovery rate (FDR) adjustment to control for multiple testing.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eWeak inverse correlations were observed between semen volume or motility and age, BMI, diastolic blood pressure, glucose, and triglycerides. Serum magnesium showed a modest positive association with progressive motility, and unconjugated bilirubin was positively associated with normal morphology. Serum globulin levels demonstrated a small positive correlation with normal morphology. Serum osmolality exhibited consistent associations with DNA fragmentation index (DFI), high DNA stainability (HDS), and morphology. Most effect sizes were small, and associations not surviving FDR adjustment were interpreted as exploratory.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eIn this health-check population, routine systemic biochemical indices showed modest correlations with semen parameters. Given the cross-sectional design, findings should be interpreted as associative rather than causal. These results are hypothesis-generating and warrant longitudinal validation to clarify temporal relationships and biological mechanisms.\u003c/p\u003e","manuscriptTitle":"Associations between Routine Systemic Biochemical Indices and Semen Quality: A Cross-Sectional Study in Men Undergoing Health Examination","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-05 16:15:55","doi":"10.21203/rs.3.rs-8982176/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-05-13T04:36:55+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"271895771315534511800005160978935832955","date":"2026-05-11T16:49:35+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"147358343131272766387929382154748752344","date":"2026-05-11T06:49:15+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"128935121009852932988796814380673858249","date":"2026-05-10T15:43:26+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"162991834824330027922846516207441057191","date":"2026-05-05T12:39:49+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-24T17:05:30+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-04-08T17:27:40+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-02-27T12:26:42+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-02-27T12:22:13+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2026-02-27T00:47:30+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"2cd05861-c839-421b-9c03-9602e61a3bf6","owner":[],"postedDate":"May 5th, 2026","published":true,"recentEditorialEvents":[{"type":"editorInvitedReview","content":"","date":"2026-05-13T04:36:55+00:00","index":121,"fulltext":""},{"type":"reviewerAgreed","content":"271895771315534511800005160978935832955","date":"2026-05-11T16:49:35+00:00","index":120,"fulltext":""},{"type":"reviewerAgreed","content":"147358343131272766387929382154748752344","date":"2026-05-11T06:49:15+00:00","index":97,"fulltext":""},{"type":"reviewerAgreed","content":"128935121009852932988796814380673858249","date":"2026-05-10T15:43:26+00:00","index":96,"fulltext":""},{"type":"reviewerAgreed","content":"162991834824330027922846516207441057191","date":"2026-05-05T12:39:49+00:00","index":92,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":67505632,"name":"Health sciences/Biomarkers"},{"id":67505633,"name":"Health sciences/Diseases"},{"id":67505634,"name":"Health sciences/Medical research"},{"id":67505635,"name":"Biological sciences/Physiology"}],"tags":[],"updatedAt":"2026-05-05T16:15:55+00:00","versionOfRecord":[],"versionCreatedAt":"2026-05-05 16:15:55","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8982176","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8982176","identity":"rs-8982176","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}