Association between body mass index and semen quality in infertile men: a cross-sectional study of 28 167 patients.

Infertility is defined as “a condition in which unprotected, regular sexual intercourse fails to result in conception over a period of 12 months or more”. 1 It has emerged as a significant global health concern, affecting approximately 15% of couples of reproductive age. 2 In China, particularly following the relaxation of the two-child policy, prevalence has risen to 25%. 3 Research indicates that male factors contribute to 40%–50% of infertility cases, 1 with roughly 20%–30% attributable solely to the male partner. 2 4 According to the 2019 Global Burden of Disease (GBD) Study, approximately 56 million men worldwide are affected by infertility, representing a 76.9% increase since 1990. 5 The age-standardized prevalence per 100 000 population is 1402.98 (95% uncertainty interval [UI]: 792.24–2242.45), reflecting a 19% rise since 1990. 5 Semen quality is a direct determinant of male fertility 6 and semen analysis remains the gold standard for its assessment. 7 Normal sperm parameters closely linked to fertility include sperm count, semen volume, sperm concentration, and sperm motility. 7 Semen abnormalities not only contribute to male infertility but are also associated with serious conditions such as testicular cancer, 8 9 diabetes, 10 and cardiovascular disease. 10 Current evidence indicates that factors including psychological stress, 11 environmental pollution, 12 13 and lifestyle choices, 14 15 16 are significantly associated with reduced semen quality, though further studies are required to elucidate the underlying mechanisms. Over the recent decades, obesity prevalence has risen steadily, coinciding with declines in semen quality and male fertility indices. 17 This parallel trend has generated increasing epidemiological interest, and a substantial body of evidence now supports a strong inverse relationship between elevated BMI and semen quality. For example, an observational study in Wuhan, China, identified significant associations between overweight status and reduced semen volume, total sperm count, and total motile sperm count. 18 Similarly, a meta-analysis of 50 studies confirmed that higher BMI is associated with poorer semen quality. 19 Although a few studies have reported no significant association between BMI and semen parameters, these findings are generally limited by small sample sizes or focus on specific subpopulations, such as sperm donors. 20 21 22 Despite the overall consistency of evidence, studies exploring the relationship between BMI and semen quality, specifically in clinical populations of infertile men, remain limited. Therefore, we conducted a cross-sectional study analyzing clinical data from 28 167 infertile men who underwent initial semen collection prior to assisted reproductive treatment (ART). The study aimed to investigate associations between BMI and semen quality parameters and to identify potential BMI thresholds linked to alterations in semen quality.

XC, PFQ, and JZS conceived and designed the study. LG and XJF were responsible for data collection and organization. JC, XYL, and YSH verified data accuracy. XC and LG performed the data analysis. XC drafted the manuscript, and PFQ and JZS critically revised it. All authors contributed to the work and read and approved the final manuscript.

This single-center, cross-sectional study was conducted at the Assisted Reproduction Center of Northwest Women’s and Children’s Hospital (Xi’an, China). The study was approved by the Ethics Committee of Northwest Women’s and Children’s Hospital (Approval No. 2022007), which waived the requirement for informed consent. Baseline demographic data and semen quality parameters were extracted from the electronic medical record system of Assisted Reproduction Center of Northwest Women’s and Children’s Hospital. Prior to semen collection, all participants underwent standardized medical examinations to assess secondary sexual characteristics, and height and weight were measured. BMI was calculated as weight divided by the square of height (kg m -2 ). BMI was categorized as follows: underweight (<18.5 kg m −2 ), normal weight (18.5–24.9 kg m −2 ), overweight (25–29.9 kg m −2 ), and obese (≥30 kg m −2 ). This study included male infertile patients who underwent initial semen collection and analysis prior to ART at Northwest Women’s and Children’s Hospital between January 2019 and December 2023. The inclusion criteria of patients were as follows: (1) aged 20–40 years; (2) with primary or secondary infertility, defined as failure to conceive after ≥12 months of regular, unprotected intercourse; (3) with normal secondary sexual characteristics and no pathological changes in reproductive organs or accessory structures (testes, epididymis, and accessory gonads) confirmed by physical examination; (4) who have not taken any medications, dietary supplements, or traditional Chinese herbal remedies intend to improve semen quality in the past 6 months; (5) with no systemic or serious organic diseases; (6) with no history of prolonged exposure to radiation, toxic substances, or drug abuse; and (7) with no history of sexually transmitted or infectious diseases. The exclusion criteria of patients were as follows: (1) with prior conditions affecting sperm quality, including cryptorchidism, varicocele, orchitis, vasectomy, testicular trauma, or a family history of hereditary diseases; (2) with sexual dysfunction, ejaculatory disorders, retrograde ejaculation, or loss of sperm samples during collection; (3) with chromosomal or genetic abnormalities; or (4) with missing BMI data. Only the first semen analysis was included; for patients with multiple analyses, subsequent samples were excluded. Participants were instructed to abstain from sexual activity for 3–7 days, wash the genital area after urination, and collect semen via masturbation into sterilized, dry measuring cups. Semen volume was measured using the weighing method (assuming a semen density of 1 g ml −1 ). Samples were incubated in a 37°C water bath for 20–60 min to allow complete liquefaction. Sperm concentration and motility were assessed using a computer-assisted semen analyzer following the guidelines outlined in the WHO Laboratory Manual for the Examination and Processing of Human Semen (5 th edition). 23 The primary outcome was a composite measure of semen quality, defined according to the 5 th -percentile lower reference limits for key parameters in the WHO Laboratory Manual for the Examination and Processing of Human Semen (6 th edition). 24 The composite outcome required all of the following criteria: semen volume ≥1.4 ml, sperm concentration ≥16 × 10 6 ml −1 , total sperm count ≥39 × 10 6 per ejaculate, progressive motility ≥30%, and total motility ≥42%. Individual semen parameters included semen volume, sperm concentration, total sperm count, progressive motility, progressive motile sperm count, total motility, and total motile sperm count. Total motility was calculated as the sum of progressive and non-progressive motility. Progressive motile sperm count was derived by multiplying sperm concentration by the percentage of progressive motility, while total motile sperm count was calculated by multiplying sperm concentration by total motility. Continuous variables were presented as mean ± standard deviation (s.d.) and categorical variables as frequencies and percentages. Group comparisons for normally distributed continuous variables were performed using analysis of variance (ANOVA) and the Kruskal–Wallis H test or Mann–Whitney U test was applied for non-normally distributed variables. Categorical variables were analyzed using the Chi-square test, with exact Pearson Chi-square applied when assumptions were not met. Associations between BMI and semen parameters were analyzed using multiple regression, treating BMI as both a continuous and categorical variable. Smoothed curve fitting was performed using a generalized additive model, and threshold effect analysis identified BMI cut-offs influencing semen parameters. Participants were stratified by age to assess interaction effects. Trend tests were conducted by treating categorical BMI variables as continuous. Confounders were selected based on correlation with outcomes or if their inclusion altered effect estimates by >10%, including age, smoking status, alcohol consumption, season of semen collection, abstinence time, and testicular volumes. To further exclude potential confounding by reproductive hormones and validate robustness, sensitivity analyses were conducted in 6603 patients with complete data on follicle-stimulating hormone (FSH), luteinizing hormone (LH), and testosterone (T). Regression models were additionally adjusted for these hormones. All analyses were performed using EmpowerStats ( www.empowerstats.com ; X&Y Solutions, Boston, MA, USA) and R software ( http://www.r-project.org ). A two-sided P < 0.05 was considered statistically significant.

The flowchart of participant enrollment is shown in Supplementary Figure 1 . A total of 28 167 male infertile patients were included: 580 underweight, 13 965 normal weight, 11 407 overweight, and 2215 obese. The underweight group had the lowest age (mean ± s.d.: 30.7 ± 3.4 years), whereas the overweight group had the highest (mean ± s.d.: 32.3 ± 3.6 years, P < 0.001). Across all BMI categories, over half of the participants reported current smoking (64.0% underweight, 73.4% normal weight, 72.7% overweight, and 66.6% obese, P < 0.001). The normal weight group showed the longest abstinence time (mean ± s.d.: 4.5 ± 2.1 days, P = 0.018). Bilateral testicular volume (mean ± s.d.) increased with BMI, peaking in the obese group (left volume: 15.4 ± 2.8 cm 3 , right volume: 15.4 ± 2.8 cm 3 , P < 0.001), as shown in Table 1 . Baseline characteristics of patients stratified by body mass index categories DOR: diminished ovarian reserve; s.d.: standard deviation Univariate analysis revealed significant differences in semen quality across BMI categories. Compared with the obese group, both normal weight and overweight groups had higher semen volume, sperm count, and progressive motile sperm count. The overweight group also showed higher progressive and total motility than the normal weight group and greater sperm concentration and total motile sperm count compared with the obese group (all P < 0.05; Table 2 ). Distribution of sperm quality parameters based on body mass index categories a This value compared with that in the obese group, P <0.05. b The value compared with that in the normal weight group, P <0.05. Composite outcome was defined as the simultaneous fulfillment of semen volume ≥1.4 ml, sperm concentration ≥16×10 6 ml −1 , total sperm count (per ejaculate) ≥39×10 6 , progressive motility ≥30%, and total motility ≥42%. s.d.: standard deviation After adjusting for potential confounders, multivariate regression analysis treating BMI as a continuous variable showed that each 1 kg m −2 increase in BMI was associated with decreases in semen volume (β = −0.01; 95% confidence interval [CI]: −0.02 to −0.01), total sperm count (β = −0.95; 95% CI: −1.48 to −0.41), progressive motile sperm count (β = −0.38; 95% CI: −0.67 to −0.09), and total motile sperm count (β = −0.41; 95% CI: −0.77 to −0.05). When BMI was treated categorically, increasing BMI was associated with downward trends in semen volume ( P for trend = 0.001), total sperm count ( P for trend = 0.001), and progressive motile sperm count ( P for trend = 0.030). Compared with normal weight group, the underweight group had lower total sperm count (β = −14.01; 95% CI: −27.25 to −0.76), while the overweight group had increased progressive motility (β = 0.49; 95% CI: 0.16 to 0.83). The obese group showed obvious reductions in the composite outcome of good semen quality (odds ratio [OR] = 0 .88; 95% CI: 0.79 to 0.97) and other semen parameters, including semen volume (β = −0.15, 95% CI: −0.23 to −0.08), sperm concentration (β = −3.05, 95% CI: −4.76 to −1.35), total sperm count (β = −19.34, 95% CI: −26.52 to −12.17), progressive motile sperm count (β = −7.98, 95% CI: −11.87 to −4.10), and total motile sperm count (β = −9.63, 95% CI: −14.51 to −4.75), as shown in Table 3 . Multivariable regression analysis for sperm quality parameters by body mass index * BMI characterized as a continuous variable. # Statistically significant ( P <0.05). a Composite outcome was defined as the simultaneous fulfillment of semen volume ≥1.4 ml, sperm concentration ≥16×10 6 ml −1 , total sperm count (per ejaculate) ≥39×10 6 , progressive motility ≥30%, and total motility ≥42%, the composite outcome is a categorical variable analyzed using multivariable logistic regression, with results presented as OR (95% CI). Multiple regression models were adjusted for variables including age, infertility factors, smoking status, alcohol status, season of semen collection, abstinence time, left testicular volume, and right testicular volume. P value for trend was derived by converting the BMI categories into ordinal variables within the multiple regression models. BMI: body mass index; CI: confidence interval; OR: odds ratio Adjusted smoothed curves ( Figure 1 ) indicated that semen volume decreased consistently with increasing BMI, whereas the composite outcome of good semen quality, sperm concentration, sperm count, progressive motility, progressive motile sperm count, total motility, and total motile sperm count showed an inverted U-shaped relationship. Threshold effect analysis identified BMI cut-offs for each semen parameter: 26.0 kg m −2 for the composite outcome, 30.8 kg m −2 for semen volume, 24.7 kg m −2 for sperm concentration, 25.5 kg m −2 for sperm count, 26.0 kg m −2 for progressive motility, 26.0 kg m −2 for progressive motile sperm count, 25.5 kg m −2 for total motility, and 26.0 kg m −2 for total motile sperm count. Log-likelihood ratio tests confirmed significant differences for all segmented linear models (all P < 0.05; Table 4 ) . The smoothed plot of the relationship between BMI and sperm quality parameters. Relationship between BMI and ( a ) the composite outcome of good semen quality, ( b ) semen volume, ( c ) sperm concentration, ( d ) total sperm count, ( e ) progressive motility, ( f ) progressive motile sperm count, ( g ) total motility, and ( h ) total motile sperm count. All regression models were adjusted for age, infertility factors, smoking status, alcohol consumption, season of semen collection, abstinence time, and left and right testicular volumes. BMI was treated as a continuous variable. BMI: body mass index. Threshold effects of body mass index on sperm quality parameters using piece-wise linear regression a Composite outcome was defined as the simultaneous fulfillment of semen volume ≥1.4 ml, sperm concentration ≥16×10 6 ml −1 , total sperm count (per ejaculate) ≥39×10 6 , progressive motility ≥30%, and total motility ≥42%, the composite outcome is a categorical variable analyzed using multivariable logistic regression, with results presented as OR (95% CI). BMI is characterized as a continuous variable. Multiple regression models were adjusted for variables including age, infertility factors, smoking status, alcohol status, season of semen collection, abstinence time, left testicular volume, and right testicular volume. BMI: body mass index; CI: confidence interval; OR: odds ratio To further explore the impact of BMI on semen quality across different age groups, age stratification analyses were conducted. Across all age groups, semen volume decreased significantly with increasing BMI ( P for trend < 0.05). The normal weight group had lower progressive motility than the overweight group, but higher semen volume and total sperm count than the obese group. Among men aged 20–30 years, increasing BMI was associated with decreased total motility. In men aged 31–40 years, the overweight group had higher total motility than the normal weight group, whereas the obese group showed significant reductions in the composite outcome, sperm concentration, progressive motile sperm count, and total motile sperm count. No significant interaction between BMI and age was observed (all P for interaction > 0.05; Table 5 ). Multivariate regression analysis examining the relationship between age-stratified body mass index and sperm quality parameters * BMI is characterized as a continuous variable. # Statistically significant ( P <0.05). a Composite outcome was defined as the simultaneous fulfillment of semen volume ≥1.4 ml, sperm concentration ≥16×10 6 ml −1 , total sperm count (per ejaculate) ≥39×10 6 , progressive motility ≥30%, and total motility ≥42%, the composite outcome is a categorical variable analyzed using multivariable logistic regression, with results presented as OR (95% CI). Multiple regression models were adjusted for variables including infertility factors, smoking status, alcohol status, season of semen collection, abstinence time, left testicular volume, and right testicular volume. P value for trend was derived by converting the BMI categories into ordinal variables within the multiple regression models. BMI: body mass index; CI: confidence interval; OR: odds ratio To assess the robustness of our findings, sensitivity analyses were conducted in a subset of 6603 infertile men with complete hormone data. Baseline characteristics, such as age, smoking and alcohol consumption, and bilateral testicular volumes, were similar to those of the overall cohort ( Table 1 ). However, the proportion of male factor infertility was higher in this hormone-complete subgroup ( P = 0.014), and the underweight group had the highest proportion of semen collections during spring ( P < 0.001). With increasing BMI, FSH levels progressively increased, T levels declined, and LH levels were the highest in the obese group (all P < 0.001; Supplementary Table 1 ). Baseline characteristics of patients stratified by body mass index categories DOR: diminished ovarian reserve; s.d.: standard deviation; BMI: body mass index; FSH: follicle-stimulating hormone; LH: luteinizing hormone After adjusting for FSH, LH, and T, multivariate regression analysis showed that each 1 kg m −2 increase in BMI was associated with significant reductions in the composite outcome of good semen quality, sperm concentration, total sperm count, progressive motile sperm count, and total motile sperm count. Compared with the normal-weight group, the underweight group showed significantly lower sperm count and total motility, whereas the obese group had significantly lower values across all semen parameters ( Supplementary Table 2 ). Age-stratified analyses indicated that these associations were most pronounced in men aged 31–40 years, with higher BMI associated with reduced sperm concentration and progressive motile sperm count. In this age group, the overweight group showed lower sperm concentration and total sperm count, while obese men exhibited marked reductions in semen volume, sperm concentration, total sperm count, progressive motile sperm count, and total motile sperm count ( Supplementary Table 3 ). These results were consistent with the primary analysis, confirming the robustness of our findings. Multivariable regression analysis for sperm quality parameters by body mass index * BMI is characterized as a continuous variable. # Statistically significant ( P <0.05). a Composite outcome was defined as the simultaneous fulfillment of semen volume ≥1.4 ml, sperm concentration ≥16×10 6 ml −1 , total sperm count (per ejaculate) ≥39×10 6 , progressive motility ≥30%, and total motility ≥42%, the composite outcome is a categorical variable analyzed using multivariable logistic regression, with results presented as OR (95% CI). Multiple regression models were adjusted for variables including age, infertility factors, smoking status, alcohol status, season of semen collection, abstinence time, left testicular volume, right testicular volume, testosterone, FSH, LH, and testosterone. P values for trend were derived by converting the BMI categories into ordinal variables within the multiple regression models. BMI: body mass index; CI: confidence interval; OR: odds ratio; FSH: follicle-stimulating hormone; LH: luteinizing hormone Multivariate regression analysis examining the relationship between age-stratified body mass index and sperm quality parameters * BMI is characterized as a continuous variable. # Statistically significant ( P <0.05). a Composite outcome was defined as the simultaneous fulfillment of semen volume ≥1.4 ml, sperm concentration ≥16×10 6 ml −1 , total sperm count (per ejaculate) ≥39×10 6 , progressive motility ≥30%, and total motility ≥42%, the composite outcome is a categorical variable analyzed using multivariable logistic regression, with results presented as OR (95% CI). Multiple regression models were adjusted for variables including age, infertility factors, smoking status, alcohol status, season of semen collection, abstinence time, left testicular volume, right testicular volume, testosterone, FSH, LH, and testosterone. P values for trend were derived by converting the BMI categories into ordinal variables within the multiple regression models. BMI: body mass index; CI: confidence interval; OR: odds ratio; FSH: follicle-stimulating hormone; LH: luteinizing hormone

In this cross-sectional study of infertile men, we explored the relationship between BMI and semen quality, revealing an inverted U-shaped association. Underweight men had significantly lower total sperm counts, overweight men exhibited modestly improved progressive motility, and obese men showed marked reductions in the composite outcome of good semen quality, semen volume, sperm concentration, total sperm count, progressive motile sperm count, and total motile sperm count. Age-stratified analyses indicated that these associations were most pronounced in men aged 31–40 years. Threshold effect analysis identified a critical BMI range of 24.7–26.0 kg m −2 , above which most semen parameters and the composite outcome declined significantly. Our findings are broadly consistent with prior literature demonstrating the negative impact of elevated BMI on semen quality. Meta-analyses have reported significant inverse associations between overweight/obesity and semen volume, total sperm count, sperm concentration, and motility. 25 26 A retrospective cohort study of 2384 infertile Chinese men reported similar conclusions. 27 Although obesity was associated with reduced semen parameters in our study, threshold analysis indicated that a mildly elevated BMI (<26 kg m −2 ) was associated with modestly higher sperm motility. Several factors may explain these discrepancies. Previous meta-analyses generally did not stratify by fertility status, whereas some cohort studies of infertile men lacked adjustments for testicular volume and reproductive hormones and were limited by smaller sample sizes. In contrast, our study analyzed infertile men undergoing pre-ART semen evaluation and rigorously adjusted for these confounders using multivariable regression. Body composition may also influence reproductive outcomes. 28 Men classified as “metabolically healthy overweight” may maintain or even improve sperm motility through healthier lifestyle behaviors, including higher physical activity and balanced diets. Patients preparing for assisted reproduction are often more attentive to such interventions, potentially explaining the motility advantage in those with mildly elevated BMI. This may also account for reports of no significant associations between overweight/obesity and semen quality in some studies. 20 21 22 Research on underweight status and semen quality is limited. Two recent studies, one of 3966 sperm donors and another of 990 men from the general population, consistently reported that underweight men had lower sperm concentration and total sperm count. 18 29 Consistent with these findings, the present study also identified a negative association between underweight and total sperm count, though sperm concentration was not significantly affected, likely due to the small proportion of underweight men in the Chinese infertile population. Previous studies often used restricted cubic spline (RCS) models to characterize nonlinear BMI-semen relationships. Ma et al . 18 identified an inflection point at 21.6 kg m −2 in 3966 healthy sperm donors and Wang et al . 30 reported a threshold of 22.4 kg m −2 in 715 participants. In contrast, our study of 28 167 infertile men revealed a critical BMI range of 24.7–26.0 kg m −2 . Differences likely reflect study populations and methodology: prior cohorts focused on healthy donors with BMI distributions concentrated in the normal range, whereas our sample encompassed broader BMI values and infertility-related heterogeneity. Additionally, RCS models generate smooth curves requiring visual or derivative-based identification of inflection points, whereas threshold effect analysis uses piecewise regression to optimize and define BMI cutoffs, more precisely delineating the transition from “beneficial overweight” to deleterious obesity. Age-stratified analyses showed that elevated BMI exerted the greatest negative impact on semen quality among men aged 31–40 years, consistent with a retrospective study of 71 623 infertile men demonstrating that advancing age exacerbates declines in total sperm count and progressive motility. 31 Similarly, Ramírez et al . 32 reported synergistic detrimental effects of older age, alcohol use, and unhealthy weight on multiple semen parameters. The stronger BMI-semen quality association in older men likely reflects cumulative exposure to obesity-related metabolic and endocrine disturbances that progressively impair spermatogenesis and sperm function. Younger men may not have experienced sufficient duration of excess adiposity for these effects to manifest clearly. The pathophysiological mechanisms linking abnormal BMI to impaired semen quality remain incompletely understood. Obesity disrupts hypothalamic–pituitary–gonadal (HPG) axis function 33 and alters sex hormone regulation. 33 34 35 36 Insulin resistance lowers sex hormone-binding globulin via hyperinsulinemia and impairs Sertoli and Leydig cell function, 37 38 reducing semen volume, sperm count, and maturation. Obesity also enhances inflammatory signaling ( e.g ., nuclear factor kappa-B and Jun N-terminal kinase) and oxidative stress in genital tissues. 39 40 Excess adiposity and immune activation generate reactive oxygen species (ROS) that peroxidize sperm membrane polyunsaturated fatty acids (PUFAs), including docosahexaenoic acid (DHA), reducing membrane fluidity and motility. 40 ROS-induced lipid peroxidation and DNA fragmentation further compromise mitochondrial function, lowering adenosine triphosphate (ATP) production and sperm viability. 41 A double-blind, placebo-controlled trial by Busetto et al . 42 found that antioxidant supplementation improved sperm concentration, total count, and motility overall, but men with BMI >25 kg m −2 experienced substantially smaller gains, highlighting the impact of ROS-mediated damage in obese individuals. Unsaturated fatty acids play a pivotal role in male fertility. 43 A mild increase in fat mass may elevate PUFA levels in sperm membranes, enhancing membrane fluidity, acrosome reaction, and flagellar motility. 44 PUFAs are taken up by Sertoli cells, passively or via CD36, to support energy metabolism and membrane remodeling, 45 46 optimizing spermatogenesis. Their antioxidant properties help maintain redox balance, mitigate ROS-induced lipid peroxidation and DNA damage, and preserve sperm membrane integrity, collectively improving sperm viability and motility. 45 Importantly, BMI does not differentiate between fat and muscle mass. Patients preparing for ART often adopt healthier lifestyles, including increased physical activity and balanced nutrition, which may increase muscle mass and elevate basal T levels, further supporting spermatogenesis and sperm motility. 47 In contrast, underweight status, reflecting malnutrition, disrupts reproductive hormone homeostasis. 48 49 Animal studies have shown that calorie restriction significantly reduces both serum and testicular T levels, 48 while prolonged food restriction lowers T, FSH, and LH levels in a duration-dependent manner. 49 In healthy men, T normally declines by approximately 1%–2% per year, 50 a process that may be accelerated by chronic obesity through persistent HPG axis dysfunction. Additionally, high-fat diets, common among obese individuals, induce cumulative sperm damage, with severity increasing over time. 51 Chronic high-fat intake disrupts testicular architecture, triggers oxidative stress, inflammation, and apoptosis, and impairs mitochondrial function, reducing ATP production. Collectively, these changes exacerbate metabolic dysregulation and compromise male reproductive function, ultimately resulting in significant declines in sperm quality. 51 52 53 This study has several strengths. First, this study combines smoothed curve fitting with threshold effect analysis to explore the turning point of BMI affecting semen quality. Second, the large sample size enhances the robustness of statistical analyses. Finally, the data were derived from routine clinical practice, minimizing observational bias. However, there were some limitations. First, the study population was restricted to infertile men aged 20–40 years to reduce age-related confounding; while the observed associations align with previous findings in non-infertile men, effect sizes may differ, limiting generalizability to younger or older populations. Second, although sensitivity analyses adjusted for reproductive hormones, baseline measurements of T, LH, and FSH were unavailable for all participants. Third, we examined only BMI and did not account for fat distribution. The role of waist circumference, as an indicator of central obesity, in independently influencing semen quality has not been addressed. Finally, sperm DNA fragmentation, an important functional parameter strongly associated with elevated BMI, was not evaluated. 54 55 56 Despite these limitations, our findings have important clinical implications. We identified an optimal BMI range of 18.5–26.0 kg m −2 associated with improved semen quality. This quantitative range may guide weight management counseling for infertile men and support personalized lifestyle interventions. Clinically, BMI should be measured at the initial visit. For patients with BMI >26.0 kg m −2 , multidisciplinary weight-loss programs are recommended to achieve ≤26.0 kg m −2 . For those with BMI <18.5 kg m −2 , nutritional support and a supervised weight-gain plan should aim to reach at least 18.5 kg m −2 . Because spermatogenesis requires 70–90 days, interventions should be sustained, with semen re-evaluation after a minimum of 3 months to assess response. These findings also lay the foundation for future studies integrating ART outcomes, including pregnancy and live birth rates, to evaluate the clinical benefits of BMI optimization in enhancing assisted reproductive success.

Our study demonstrated a threshold effect of BMI on semen quality, characterized by an inverted U-shaped relationship. Semen parameters improved with increasing BMI up to a threshold of 26.0 kg m −2 , beyond which further increases were associated with declines in semen quality. These findings suggest that maintaining a BMI within the range of 18.5–26.0 kg m −2 may help optimize reproductive potential in infertile men undergoing ART evaluation.

All authors declare no competing interests.

Flow chart of patient inclusion. BMI: body mass index.