Abstract
Although the detrimental impact of abnormal body mass index (BMI) on semen quality is well established in the general population, studies exploring this relationship in infertile men remain limited. This study aimed to investigate the association between BMI and semen quality parameters and to identify potential BMI thresholds linked to altered semen quality. In this cross-sectional study, clinical records from 28 167 men evaluated for infertility prior to assisted reproductive treatment (ART) at Northwest Women’s and Children’s Hospital (Xi’an, China) between January 2019 and December 2023 were analyzed. Participants were categorized by BMI as underweight (<18.5 kg m−2), normal (18.5–24.9 kg m−2), overweight (25.0–29.9 kg m−2), and obese (≥30.0 kg m−2). Conventional semen analysis was performed according to World Health Organization (WHO) guidelines, and a composite measure of “good” semen quality was defined using established reference criteria. Multivariable regression, smoothed curve fitting, and threshold effect analyses were used to examine associations between BMI and semen parameters. Underweight men had lower sperm counts, whereas overweight men showed slightly higher progressive motility. Obese men demonstrated significant reductions in semen volume, sperm concentration, sperm count, motile sperm counts, and the likelihood of achieving good semen quality compared with men of normal weight. Smoothed curve fitting and threshold effect analyses revealed an inverted U-shaped relationship between BMI and overall semen quality, with improvement up to a BMI of 26.0 kg m−2, followed by a decline beyond this point. These findings suggest that maintaining a BMI between 18.5 kg m−2 and 26.0 kg m−2 may optimally support semen quality and reproductive potential in infertile men.
Keywords: assisted reproductive technology, body mass index, male infertility, obesity, semen quality
INTRODUCTION
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 fertility6 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.
PARTICIPANTS AND METHODS
Study design
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).
Study population
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.
Semen analysis
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 (5th edition).23
Definitions of outcomes
The primary outcome was a composite measure of semen quality, defined according to the 5th-percentile lower reference limits for key parameters in the WHO Laboratory Manual for the Examination and Processing of Human Semen (6th edition).24 The composite outcome required all of the following criteria: semen volume ≥1.4 ml, sperm concentration ≥16 × 106 ml−1, total sperm count ≥39 × 106 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.
Statistical analyses
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.
RESULTS
Baseline characteristics
The flowchart of participant enrollment is shown in Supplementary Figure 1 (85.6KB, tif) . 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 cm3, right volume: 15.4 ± 2.8 cm3, P < 0.001), as shown in Table 1.
Table 1.
Baseline characteristics of patients stratified by body mass index categories
| Characteristics | Underweight group (n=580) | Normal weight group (n=13 965) | Overweight group (n=11 407) | Obese group (n=2215) | P |
|---|---|---|---|---|---|
| Age (year), mean±s.d. | 30.7±3.4 | 32.1±3.6 | 32.3±3.6 | 31.9±3.7 | <0.001 |
| 21–30, n (%) | 292 (50.3) | 4780 (34.2) | 3658 (32.1) | 813 (36.7) | <0.001 |
| 31–40, n (%) | 288 (49.7) | 9185 (65.8) | 7749 (67.9) | 1402 (63.3) | |
| Infertility factors, n (%) | 0.147 | ||||
| Tubal disease | 266 (45.9) | 6163 (44.1) | 4985 (43.7) | 924 (41.7) | |
| Ovulatory disorder | 37 (6.4) | 1120 (8.0) | 907 (8.0) | 207 (9.4) | |
| Endometriosis | 15 (2.6) | 266 (1.9) | 249 (2.2) | 40 (1.8) | |
| DOR | 12 (2.1) | 254 (1.8) | 194 (1.7) | 38 (1.7) | |
| Multiple female factors | 61 (10.5) | 1486 (10.6) | 1229 (10.8) | 250 (11.9) | |
| Male factor | 51 (8.8) | 1286 (9.2) | 999 (8.8) | 210 (9.5) | |
| Bilateral factor | 39 (6.7) | 1390 (10.0) | 1179 (10.3) | 223 (10.1) | |
| Others | 99 (17.1) | 2000 (14.3) | 1665 (14.6) | 323 (14.6) | |
| Smoking status, n (%) | <0.001 | ||||
| Smoker | 372 (64.1) | 10 253 (73.4) | 8296 (72.7) | 1475 (66.6) | |
| Non-smoker | 208 (35.9) | 3712 (26.6) | 3111 (27.3) | 740 (33.4) | |
| Alcohol status, n (%) | 0.539 | ||||
| Non-drinker | 580 (100.0) | 13 955 (99.9) | 11 401 (99.9) | 2 215 (100.0) | |
| Drinker | 0 (0) | 10 (0.1) | 6 (0.1) | 0 (0) | |
| Season of semen collection, n (%) | 0.665 | ||||
| Spring | 217 (37.4) | 4695 (33.6) | 3765 (33.0) | 736 (33.2) | |
| Summer | 139 (24.0) | 3654 (26.2) | 2953 (25.9) | 573 (25.9) | |
| Autumn | 117 (20.2) | 2948 (21.1) | 2478 (21.7) | 481 (21.7) | |
| Winter | 107 (18.4) | 2668 (19.1) | 2211 (19.4) | 425 (19.2) | |
| Abstinence time (day), mean±s.d. | 4.4±1.8 | 4.5±2.1 | 4.5±2.1 | 4.45±1.9 | 0.018 |
| Left testicular volume (cm3), mean±s.d. | 14.3±1.7 | 14.6±2.0 | 15.0±2.4 | 15.4±2.8 | <0.001 |
| Right testicular volume (cm3), mean±s.d. | 14.3±1.7 | 14.6±2.0 | 15.0±2.4 | 15.4±2.8 | <0.001 |
DOR: diminished ovarian reserve; s.d.: standard deviation
Relationship between BMI and semen quality
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).
Table 2.
Distribution of sperm quality parameters based on body mass index categories
| Characteristic | Underweight group (n=580) | Normal weight group (n=13 965) | Overweight group (n=11 407) | Obese group (n=2215) | P |
|---|---|---|---|---|---|
| Composite outcome, n (%) | 375 (64.7) | 9099 (65.2) | 7541 (66.1) | 1417 (64.0) | 0.170 |
| Semen volume (ml), mean±s.d. | 3.8±1.6 | 3.9±1.6a | 3.8±1.8a | 3.7±1.6 | <0.001 |
| Sperm concentration (106 ml−1), mean±s.d. | 53.9±39.3 | 56.8±38.3 | 57.6±39.6a | 54.9±37.5 | 0.005 |
| Sperm count (106 per ejaculate), mean±s.d. | 194.3±143.9 | 210.4±156.0a | 211.1±174.9a | 195.7±150.7 | <0.001 |
| Progressive motility (%), mean±s.d. | 43.2±17.2 | 42.9±16.2 | 43.6±16.3b | 43.2±16.3 | 0.022 |
| Progressive motile sperm count (106 per ejaculate), mean±s.d. | 93.4±86.2 | 97.5±85.6a | 99.0±85.6a | 92.2±84.1 | 0.006 |
| Total sperm motility (%), mean±s.d. | 48.3±19.2 | 48.1±17.9 | 48.8±18.0b | 48.2±18.1 | 0.033 |
| Total motile sperm count (106 per ejaculate), mean±s.d. | 106.2±106.9 | 110.9±104.5 | 112.9±120.5a | 104.4±101.5 | 0.006 |
aThis value compared with that in the obese group, P<0.05. bThe 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 ≥16×106 ml−1, total sperm count (per ejaculate) ≥39×106, 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.
Table 3.
Multivariable regression analysis for sperm quality parameters by body mass index
| Outcome | BMI * (kg m −2 ), β (95% CI) | Normal weight group | Underweight group, β (95% CI) | Overweight group, β (95% CI) | Obese group, β (95% CI) | P value for trend |
|---|---|---|---|---|---|---|
| Composite outcomea | 0.99 (0.99 to 1.00) | Reference | 0.94 (0.78 to 1.13) | 1.01 (0.95 to 1.06) | 0.88 (0.79 to 0.97)# | 0.196 |
| Semen volume | −0.01 (−0.02 to−0.01)# | Reference | −0.09 (−0.23 to 0.04) | −0.04 (−0.08 to 0) | −0.15 (−0.23 to −0.08)# | 0.001 |
| Sperm concentration | −0.08 (−0.20 to 0.05) | Reference | −2.03 (−5.18 to 1.11) | −0.06 (−1.00 to 0.88) | −3.05 (−4.76 to −1.35)# | 0.051 |
| Sperm count | −0.95 (−1.48 to −0.41)# | Reference | −14.01 (−27.25 to −0.76)# | −1.82 (−5.77 to 2.13) | −19.34 (−26.52 to −12.17)# | 0.001 |
| Progressive motility | 0.01 (−0.04 to 0.06) | Reference | 0.03 (−1.24 to 1.30) | 0.49 (0.16 to 0.83)# | −0.20 (−0.88 to 0.49) | 0.461 |
| Progressive motile sperm count | −0.38 (−0.67 to −0.09)# | Reference | −4.05 (−11.23 to 3.12) | 0.20 (−1.94 to 2.34) | −7.98 (−11.87 to −4.10)# | 0.030 |
| Total sperm motility | 0.00 (−0.06 to 0.06) | Reference | −0.07 (−1.48 to 1.33) | 0.33 (−0.09 to 0.75) | −0.44 (−1.20 to 0.33) | 0.834 |
| Total motile sperm count | −0.41 (−0.77 to −0.05)# | Reference | −5.07 (−14.07 to 3.93) | 0.48 (−2.20 to 3.17) | −9.63 (−14.51 to −4.75)# | 0.051 |
*BMI characterized as a continuous variable. #Statistically significant (P<0.05). aComposite outcome was defined as the simultaneous fulfillment of semen volume ≥1.4 ml, sperm concentration ≥16×106 ml−1, total sperm count (per ejaculate) ≥39×106, 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
Generalized additive model
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).
Figure 1.
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.
Table 4.
Threshold effects of body mass index on sperm quality parameters using piece-wise linear regression
| Outcome | One-line linear regression model, β (95% CI) | Cut-off value ( K; kg m −2 ) | <K, β (95% CI) | >K, β (95% CI) | Log-likelihood ratio test |
|---|---|---|---|---|---|
| Composite outcomea | 0.99 (0.99 to 1.00) | 26.0 | 1.01 (1.00 to 1.02) | 0.97 (0.96 to 0.99) | 0.002 |
| Semen volume | −0.01 (−0.02 to−0.01) | 30.8 | −0.01 (−0.01 to 0) | −0.05 (−0.08 to −0.03) | 0.002 |
| Sperm concentration | −0.03 (−0.15 to 0.09) | 24.7 | 0.59 (0.32 to 0.86) | −0.45 (−0.66 to −0.25) | <0.001 |
| Sperm count | −0.76 (−1.29 to−0.24) | 25.5 | 1.60 (0.62 to 2.57) | −3.20 (−4.19 to −2.20) | <0.001 |
| Progressive motility | 0.04 (0 to 0.09) | 26.0 | 0.12 (0.04 to 0.20) | −0.17 (−0.28 to −0.07) | <0.001 |
| Progressive motile sperm count | −0.26 (−0.54 to 0.02) | 26.0 | 0.73 (0.25 to 1.21) | −1.53 (−2.11 to −0.96) | <0.001 |
| Total sperm motility | 0.04 (−0.01 to 0.09) | 25.5 | 0.15 (0.06 to 0.24) | −0.22 (−0.34 to −0.11) | <0.001 |
| Total motile sperm count | −0.28 (−0.63 to 0.08) | 26.0 | 0.93 (0.32 to 1.54) | −1.83 (−2.55 to −1.10) | <0.001 |
aComposite outcome was defined as the simultaneous fulfillment of semen volume ≥1.4 ml, sperm concentration ≥16×106 ml−1, total sperm count (per ejaculate) ≥39×106, 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
Effect of age stratification on the relationship between BMI and sperm quality
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).
Table 5.
Multivariate regression analysis examining the relationship between age-stratified body mass index and sperm quality parameters
| Outcome | ≤30 years, β (95% CI) | >30 years, β (95% CI) | P value for interaction | |
|---|---|---|---|---|
| Composite outcomea | BMI* | 1.00 (0.99, 1.01) | 0.99 (0.98, 1.00) | 0.571 |
| Normal | Reference | Reference | 0.289 | |
| Underweight | 0.87 (0.65, 1.17) | 0.97 (0.73, 1.28) | ||
| Overweight | 1.00 (0.90, 1.12) | 1.03 (0.96, 1.11) | ||
| Obese | 1.05 (0.86, 1.27) | 0.84 (0.73, 0.96)# | ||
| P for trend | 0.494 | 0.283 | ||
| Semen volume | BMI* | -0.02 (-0.02, -0.01)# | -0.01 (-0.02, 0)# | 0.370 |
| Normal | Reference | Reference | 0.832 | |
| Underweight | -0.03 (-0.23, 0.16) | -0.15 (-0.34, 0.05) | ||
| Overweight | -0.04 (-0.11, 0.04) | -0.04 (-0.09, 0.01) | ||
| Obese | -0.15 (-0.27, -0.02)# | -0.15 (-0.25, -0.06)# | ||
| P for trend | 0.046 | 0.010 | ||
| Sperm concentration | BMI* | 0.08 (-0.12, 0.28) | -0.10 (-0.26, 0.06) | 0.149 |
| Normal | Reference | Reference | 0.508 | |
| Underweight | -0.57 (-4.85, 3.72) | -3.54 (-7.87, 0.79) | ||
| Overweight | 0.97 (-0.59, 2.54) | -0.31 (-1.43, 0.80) | ||
| Obese | -1.13 (-3.84, 1.58) | -3.43 (-5.51, -1.34)# | ||
| P for trend | 0.810 | 0.052 | ||
| Sperm count | BMI* | -0.60 (-1.40, 0.21) | -0.92 (-1.59, -0.24)# | 0.548 |
| Normal | Reference | Reference | 0.699 | |
| Underweight | -8.14 (-25.73, 9.45) | -19.48 (-36.06, 0.91) | ||
| Overweight | 1.12 (-5.32, 7.56) | -2.54 (-7.33, 2.25) | ||
| Obese | -12.75 (-23.88, -1.62)# | -20.55 (-29.48, -11.62)# | ||
| P for trend | 0.339 | 0.003 | ||
| Progressive motility | BMI* | 0.09 (-0.02, 0.16) | 0.01 (-0.04, 0.07) | 0.194 |
| Normal | Reference | Reference | 0.609 | |
| Underweight | 0.07 (-1.51, 1.66) | -0.06 (-1.64, 1.52) | ||
| Overweight | 0.60 (0.02, 1.18)# | 0.43 (0.03, 0.84)# | ||
| Obese | 0.93 (-0.08, 1.93) | -0.28 (-1.04, 0.48) | ||
| P for trend | 0.020 | 0.418 | ||
| Progressive motile sperm count | BMI* | -0.11 (-0.57, 0.35) | -0.38 (-0.74, -0.03)# | 0.366 |
| Normal | Reference | Reference | 0.777 | |
| Underweight | -2.19 (-12.17, 7.78) | -5.66 (-15.33, 4.01) | ||
| Overweight | 1.45 (-2.20, 5.10) | 0.06 (-2.43, 2.56) | ||
| Obese | -3.81 (-10.12, 2.51) | -8.70 (-13.35, -4.05)# | ||
| P for trend | 0.855 | 0.045 | ||
| Total sperm motility | BMI* | 0.10 (0.02, 0.18)# | 0.00 (-0.06, 0.07) | 0.180 |
| Normal | Reference | Reference | 0.218 | |
| Underweight | -0.09 (-1.85, 1.67) | -0.15 (-1.90, 1.59) | ||
| Overweight | 0.42 (-0.23, 1.06) | 0.50 (0.05, 0.95)# | ||
| Obese | 1.01 (-0.11, 2.12) | -0.65 (-1.49, 0.19) | ||
| P for trend | 0.052 | 0.721 | ||
| Total motile sperm count | BMI* | -0.15 (-0.71, 0.42) | -0.39 (-0.84, 0.06) | 0.557 |
| Normal | Reference | Reference | 0.602 | |
| Underweight | -3.51 (-15.84, 8.82) | -6.62 (-18.98, 5.75) | ||
| Overweight | 0.76 (-3.76, 5.28) | 0.91 (-2.28, 4.09) | ||
| Obese | -4.18 (-11.99, 3.62) | -10.90 (-16.85, -4.96)# | ||
| P for trend | 0.765 | 0.092 | ||
*BMI is characterized as a continuous variable. #Statistically significant (P<0.05). aComposite outcome was defined as the simultaneous fulfillment of semen volume ≥1.4 ml, sperm concentration ≥16×106 ml−1, total sperm count (per ejaculate) ≥39×106, 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
Sensitivity analysis
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).
Supplementary Table 1.
Baseline characteristics of patients stratified by body mass index categories
| Characteristic | Underweight group (n=140) | Normal group (n=3430) | Overweight group (n=2537) | Obese group (n=496) | P |
|---|---|---|---|---|---|
| Age (years), mean±s.d. | 30.2±3.4 | 31.9±3.7 | 31.9±3.7 | 31.8±3.8 | <0.001 |
| 21–30, n (%) | 81 (57.9) | 1332 (38.8) | 957 (37.7) | 196 (39.5) | <0.001 |
| 31–40, n (%) | 59 (42.1) | 2098 (61.2) | 1580 (62.3) | 300 (60.5) | |
| Infertility factors, n (%) | 0.014 | ||||
| Tubal disease | 47 (33.5) | 1358 (39.6) | 989 (39.0) | 171 (34.5) | |
| Ovulatory disorder | 6 (4.3) | 279 (8.1) | 209 (8.2) | 54 (10.9) | |
| Endometriosis | 3 (2.1) | 46 (1.3) | 50 (2.0) | 9 (1.8) | |
| DOR | 0 (0) | 35 (1.0) | 5 (0.2) | 6 (1.2) | |
| Multiple female factors | 20 (14.3) | 420 (12.2) | 280 (11.0) | 49 (9.9) | |
| Male factor | 34 (24.3) | 621 (18.1) | 455 (17.9) | 104 (21.0) | |
| Bilateral factor | 18 (12.9) | 398 (11.6) | 307 (12.1) | 56 (11.3) | |
| Others | 12 (8.6) | 273 (8.0) | 242 (9.5) | 47 (9.5) | |
| Smoking status, n (%) | <0.001 | ||||
| Smoker | 90 (64.3) | 2517 (73.4) | 1943 (76.6) | 336 (67.7) | |
| Non-smoker | 50 (35.7) | 913 (26.6) | 594 (23.4) | 160 (32.3) | |
| Alcohol status, n (%) | 0.851 | ||||
| Non-drinker | 140 (100.0) | 3427 (99.9) | 2534 (99.9) | 496 (100.0) | |
| Drinker | 0 (0.0) | 3 (0.1) | 3 (0.1) | 0 (0.0) | |
| Season of semen collection, n (%) | <0.001 | ||||
| Spring | 57 (40.7) | 1271 (37.1) | 794 (31.3) | 175 (35.3) | |
| Summer | 19 (13.6) | 770 (22.5) | 615 (24.2) | 102 (20.6) | |
| Autumn | 27 (19.3) | 566 (16.5) | 604 (23.8) | 89 (17.9) | |
| Winter | 37 (26.4) | 823 (24.0) | 524 (20.7) | 130 (26.2) | |
| Abstinence time (day), mean±s.d. | 4.5±1.5 | 4.6±2.6 | 4.5±1.7 | 4.6±2.3 | 0.302 |
| Left testicular volume (cm3), mean±s.d. | 14.1±1.7 | 14.5±1.9 | 14.9±2.2 | 15.4±2.9 | <0.001 |
| Right testicular volume (cm3), mean±s.d. | 14.0±1.7 | 14.5±1.9 | 14.9±2.2 | 15.4±2.9 | <0.001 |
| FSH (mIU m−1), mean±s.d. | 6.01±1.6 | 7.4±3.0 | 7.8±3.8 | 7.7±2.6 | <0.001 |
| LH (IU l−1), mean±s.d. | 4.5±0.9 | 4.6±1.5 | 4.4±1.6 | 4.6±1.3 | <0.001 |
| Testosterone (ng dl−1), mean±s.d. | 369.1±104.1 | 362.9±77.67 | 302.2±69.2 | 275.0±59.2 | <0.001 |
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.
Supplementary Table 2.
Multivariable regression analysis for sperm quality parameters by body mass index
| Outcome | BMI* (kg m−2),β/OR (95% CI) | Normal weight group | Underweight group, β /OR (95% CI) | Overweight group, β /OR (95% CI) | Obese group, β /OR (95% CI) | P for trend |
|---|---|---|---|---|---|---|
| Composite outcomea | 0.98 (0.97 to 0.99)# | Reference | 0.83 (0.59 to 1.17) | 0.92 (0.82 to 1.03) | 0.79 (0.64 to 0.96)# | 0.052 |
| Semen volume | −0.01 (−0.02 to 0.01) | Reference | −0.12 (−0.39 to 0.15) | 0.02 (−0.07 to 0.11) | −0.13 (−0.29 to 0.03) | 0.606 |
| Sperm concentration | −0.26 (−0.51 to−0.01)# | Reference | −4.51 (−10.30 to 1.28) | −1.55 (−3.45 to 0.34) | −4.69 (−8.06 to−1.33)# | 0.030 |
| Sperm count | −1.54 (−2.58 to−0.51)# | Reference | −26.35 (−49.93 to −2.78)# | −7.43 (−15.14 to 0.27) | −26.32 (−40.03 to −12.62)# | 0.005 |
| Progressive motility | −0.04 (−0.19 to 0.10) | Reference | −3.22 (−6.52 to 0.08) | 0.02 (−1.05 to 1.10) | −2.13 (−4.05 to −0.21)# | 0.445 |
| Progressive motile sperm count | −0.60 (−1.17 to −0.03)# | Reference | −12.65 (−25.68 to 0.39) | −2.61 (−6.87 to 1.65) | −11.55 (−19.13 to −3.98)# | 0.047 |
| Total sperm motility | −0.09 (−0.25 to 0.06) | Reference | −3.68 (−7.24 to −0.12)# | −0.80 (−1.96 to 0.37) | −2.16 (−4.23 to −0.09)# | 0.163 |
| Total motile sperm count | −0.81 (−1.46 to −0.15)# | Reference | −14.85 (−29.78 to 0.08) | −4.89 (−9.77 to 0.01) | −12.19 (−20.87 to −3.50)# | 0.026 |
*BMI is characterized as a continuous variable. #Statistically significant (P<0.05). aComposite outcome was defined as the simultaneous fulfillment of semen volume ≥1.4 ml, sperm concentration ≥16×106 ml−1, total sperm count (per ejaculate) ≥39×106, 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
Supplementary Table 3.
Multivariate regression analysis examining the relationship between age-stratified body mass index and sperm quality parameters
| Outcome | ≤30 year, β /OR (95% CI) | >30 years, β /OR (95% CI) | P value for interaction |
|---|---|---|---|
| Composite outcomea | |||
| BMI* | 0.98 (0.95 to 1.02) | 0.98 (0.95 to 1.00) | 0.268 |
| Normal weight | Reference | Reference | 0.634 |
| Underweight | 0.97 (0.53 to 1.79) | 1.51 (0.74 to 3.09) | |
| Overweight | 0.98 (0.76 to 1.26) | 0.92 (0.76 to 1.10) | |
| Obese | 0.86 (0.56 to 1.33) | 0.78 (0.56 to 1.08) | |
| P for trend | 0.625 | 0.069 | |
| Volume | |||
| BMI* | −0.00 (−0.02 to 0.01) | −0.00 (−0.02 to 0.01) | 0.971 |
| Normal weight | Reference | Reference | 0.269 |
| Underweight | −0.13 (−0.49 to 0.23) | −0.15 (−0.57 to 0.27) | |
| Overweight | −0.07 (−0.22 to 0.07) | 0.11 (−0.01 to 0.22) | |
| Obese | −0.10 (−0.35 to 0.15) | −0.14 (−0.35 to 0.07)# | |
| P for trend | 0.424 | 0.729 | |
| Concentration | |||
| BMI* | 0.01 (−0.32 to 0.34) | −0.51 (−0.82 to−0.21)# | 0.051 |
| Normal weight | Reference | Reference | 0.391 |
| Underweight | 1.86 (−4.61 to 8.33) | −3.51 (−11.47 to 4.45) | |
| Overweight | 0.41 (−2.16 to 2.98) | −3.17 (−5.36 to −0.98)# | |
| Obese | −1.40 (−5.91 to 3.10) | −6.02 (−9.97 to −2.08)# | |
| P for trend | 0.654 | 0.001 | |
| Count | |||
| BMI* | −0.61 (−1.99 to 0.77) | −2.44 (−3.69 to−1.19) | 0.083 |
| Normal weight | Reference | Reference | 0.755 |
| Underweight | 0.99 (−26.17 to 28.15) | −25.34 (−57.93 to 7.24) | |
| Overweight | −5.33 (−16.10 to 5.44) | −9.51 (−18.48 to −0.55)# | |
| Obese | −14.61 (−33.51 to 4.28) | −31.19 (−47.34 to −15.05)# | |
| P for trend | 0.122 | 0.002 | |
| Progressive motility | |||
| BMI* | 0.01 (−0.15 to 0.17) | 0.07 (−0.08 to 0.21) | 0.846 |
| Normal weight | Reference | Reference | 0.984 |
| Underweight | 0.29 (−2.88 to 3.46) | −1.14 (−4.84 to 2.56) | |
| Overweight | 0.34 (−0.92 to 1.60) | 0.64 (−0.37 to 1.66) | |
| Obese | 0.01 (−2.20 to 2.22) | −0.94 (−2.77 to 0.89) | |
| P for trend | 0.824 | 0.838 | |
| Progressive motile sperm count | |||
| BMI* | −0.36 (−1.13 to 0.42) | −0.72 (−1.38 to−0.07)# | 0.427 |
| Normal weight | Reference | Reference | 0.653 |
| Underweight | 3.17 (−12.05 to 18.39) | −12.82 (−30.01 to 4.37) | |
| Overweight | −3.39 (−9.43 to 2.65) | −1.53 (−6.26 to 3.20) | |
| Obese | −7.67 (−18.26 to 2.91) | −10.63 (−19.14 to−2.11)# | |
| P for trend | 0.092 | 0.129 | |
| Total motility | |||
| BMI* | 0.02 (−0.16 to 0.19) | −0.02 (−0.17 to 0.13) | 0.499 |
| Normal weight | Reference | Reference | 0.976 |
| Underweight | −0.40 (−3.82 to 3.03) | −0.59 (−4.59 to 3.41) | |
| Overweight | −0.11 (−1.47 to 1.25) | −0.37 (−1.47 to 0.73) | |
| Obese | 0.59 (−1.81 to 2.98) | −1.18 (−3.16 to 0.80) | |
| P for trend | 0.752 | 0.295 | |
| Total motile sperm count | |||
| BMI* | −0.45 (−1.34 to 0.45) | −1.02 (−1.79 to−0.25) | 0.334 |
| Normal weight | Reference | Reference | 0.766 |
| Underweight | 1.82 (−15.78 to 19.42) | −14.11 (−34.19 to 5.97) | |
| Overweight | −5.11 (−12.10 to 1.88) | −4.22 (−9.75 to 1.31) | |
| Obese | −7.27 (−19.54 to 5.01) | −11.64 (−21.59 to −1.69)# | |
| P for trend | 0.107 | 0.055 |
*BMI is characterized as a continuous variable. #Statistically significant (P<0.05). aComposite outcome was defined as the simultaneous fulfillment of semen volume ≥1.4 ml, sperm concentration ≥16×106 ml−1, total sperm count (per ejaculate) ≥39×106, 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
DISCUSSION
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 function33 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.
CONCLUSIONS
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.
AUTHOR CONTRIBUTIONS
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.
COMPETING INTERESTS
All authors declare no competing interests.
Flow chart of patient inclusion. BMI: body mass index.
ACKNOWLEDGMENTS
We thank the staff of Northwest Women’s and Children’s Hospital for their support in data collection, and we are grateful to all participants for their contributions to this study. This work was supported in part by the National Natural Science Foundation of China (grant No. 82103924) and the Key Research and Development Program of Shaanxi Province (grant No. 2024SF-YBXM-238, No. 2023-ZDLSF-48, and No. 2022ZDLSF02-11).
Supplementary Information is linked to the online version of the paper on the Asian Journal of Andrology website.
REFERENCES
- 1.Eisenberg ML, Esteves SC, Lamb DJ, Hotaling JM, Giwercman A, et al. Male infertility. Nat Rev Dis Primers. 2023;9:49. doi: 10.1038/s41572-023-00459-w. [DOI] [PubMed] [Google Scholar]
- 2.Vander Borght M, Wyns C. Fertility and infertility: definition and epidemiology. Clin Biochem. 2018;62:2–10. doi: 10.1016/j.clinbiochem.2018.03.012. [DOI] [PubMed] [Google Scholar]
- 3.Zhou Z, Zheng D, Wu H, Li R, Xu S, et al. Epidemiology of infertility in China: a population-based study. BJOG. 2018;125:432–41. doi: 10.1111/1471-0528.14966. [DOI] [PubMed] [Google Scholar]
- 4.Diaz P, Dullea A, Chu KY, Zizzo J, Loloi J, et al. Future of male infertility evaluation and treatment: brief review of emerging technology. Urology. 2022;169:9–16. doi: 10.1016/j.urology.2022.06.036. [DOI] [PubMed] [Google Scholar]
- 5.Huang B, Wang Z, Kong Y, Jin M, Ma L. Global, regional and national burden of male infertility in 204 countries and territories between 1990 and 2019: an analysis of global burden of disease study. BMC Public Health. 2023;23:2195. doi: 10.1186/s12889-023-16793-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Levine H, Jørgensen N, Martino-Andrade A, Mendiola J, Weksler-Derri D, et al. Temporal trends in sperm count: a systematic review and meta-regression analysis. Hum Reprod Update. 2017;23:646–59. doi: 10.1093/humupd/dmx022. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Boitrelle F, Shah R, Saleh R, Henkel R, Kandil H, et al. The sixth edition of the WHO manual for human semen analysis: a critical review and SWOT analysis. Life (Basel) 2021;11:1368. doi: 10.3390/life11121368. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Raman JD, Nobert CF, Goldstein M. Increased incidence of testicular cancer in men presenting with infertility and abnormal semen analysis. J Urol. 2005;174:1819–22. doi: 10.1097/01.ju.0000177491.98461.aa. discussion 22. [DOI] [PubMed] [Google Scholar]
- 9.Pape J, Fernando J, Megaritis D, Weidlinger S, Vidal A, et al. Oncological treatments have limited effects on the fertility prognosis in testicular cancer: a systematic review and meta-analysis. Andrology. 2024;13:731–46. doi: 10.1111/andr.13741. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Latif T, Kold Jensen T, Mehlsen J, Holmboe SA, Brinth L, et al. semen quality as a predictor of subsequent morbidity: a Danish cohort study of 4,712 men with long-term follow-up. Am J Epidemiol. 2017;186:910–7. doi: 10.1093/aje/kwx067. [DOI] [PubMed] [Google Scholar]
- 11.Zou P, Wang X, Sun L, Chen Q, Yang H, et al. Semen quality in Chinese college students: associations with depression and physical activity in a cross-sectional study. Psychosom Med. 2018;80:564–72. doi: 10.1097/PSY.0000000000000595. [DOI] [PubMed] [Google Scholar]
- 12.Zhang Y, Wei J, Liu C, Cao W, Zhang Z, et al. Association between ambient PM1 and semen quality: a cross-sectional study of 27,854 men in China. Environ Int. 2023;175:107919. doi: 10.1016/j.envint.2023.107919. [DOI] [PubMed] [Google Scholar]
- 13.Skakkebæk NE, Lindahl-Jacobsen R, Levine H, Andersson AM, Jørgensen N, et al. Environmental factors in declining human fertility. Nat Rev Endocrinol. 2022;18:139–57. doi: 10.1038/s41574-021-00598-8. [DOI] [PubMed] [Google Scholar]
- 14.Jensen TK, Swan S, Jørgensen N, Toppari J, Redmon B, et al. Alcohol and male reproductive health: a cross-sectional study of 8344 healthy men from Europe and the USA. Hum Reprod. 2014;29:1801–9. doi: 10.1093/humrep/deu118. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Petre GC, Francini-Pesenti F, Di Nisio A, De Toni L, Grande G, et al. Observational cross-sectional study on mediterranean diet and sperm parameters. Nutrients. 2023;15:4989. doi: 10.3390/nu15234989. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Salas-Huetos A, Bulló M, Salas-Salvadó J. Dietary patterns, foods and nutrients in male fertility parameters and fecundability: a systematic review of observational studies. Hum Reprod Update. 2017;23:371–89. doi: 10.1093/humupd/dmx006. [DOI] [PubMed] [Google Scholar]
- 17.Cannarella R, Crafa A, Curto R, Condorelli RA, La Vignera S, et al. Obesity and male fertility disorders. Mol Aspects Med. 2024;97:101273. doi: 10.1016/j.mam.2024.101273. [DOI] [PubMed] [Google Scholar]
- 18.Ma J, Wu L, Zhou Y, Zhang H, Xiong C, et al. Association between BMI and semen quality: an observational study of 3966 sperm donors. Hum Reprod. 2019;34:155–62. doi: 10.1093/humrep/dey328. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Li Y, Lin Y, Ou C, Xu R, Liu T, et al. Association between body mass index and semen quality: a systematic review and meta-analysis. Int J Obes (Lond) 2024;48:1383–401. doi: 10.1038/s41366-024-01580-w. [DOI] [PubMed] [Google Scholar]
- 20.Duits FH, van Wely M, van der Veen F, Gianotten J. Healthy overweight male partners of subfertile couples should not worry about their semen quality. Fertil Steril. 2010;94:1356–9. doi: 10.1016/j.fertnstert.2009.05.075. [DOI] [PubMed] [Google Scholar]
- 21.Lu JC, Jing J, Dai JY, Zhao AZ, Yao Q, et al. Body mass index, waist-to-hip ratio, waist circumference and waist-to-height ratio cannot predict male semen quality: a report of 1231 subfertile Chinese men. Andrologia. 2015;47:1047–54. doi: 10.1111/and.12376. [DOI] [PubMed] [Google Scholar]
- 22.MacDonald AA, Herbison GP, Showell M, Farquhar CM. The impact of body mass index on semen parameters and reproductive hormones in human males: a systematic review with meta-analysis. Hum Reprod Update. 2010;16:293–311. doi: 10.1093/humupd/dmp047. [DOI] [PubMed] [Google Scholar]
- 23.World Health Organization. WHO Laboratory Manual for The Examination and Processing of Human Semen. 5th ed. Geneva: World Health Organization; 2010. [Google Scholar]
- 24.World Health Organization. WHO Laboratory Manual for The Examination and Processing of Human Semen. 6th ed. Geneva: World Health Organization; 2021. [Google Scholar]
- 25.Salas-Huetos A, Maghsoumi-Norouzabad L, James ER, Carrell DT, Aston KI, et al. Male adiposity, sperm parameters and reproductive hormones: an updated systematic review and collaborative meta-analysis. Obes Rev. 2021;22:e13082. doi: 10.1111/obr.13082. [DOI] [PubMed] [Google Scholar]
- 26.Santi D, Lotti F, Sparano C, Rastrelli G, Isidori AM, et al. Does an increase in adipose tissue ‘weight’ affect male fertility? A systematic review and meta-analysis based on semen analysis performed using the WHO 2010 criteria. Andrology. 2024;12:123–36. doi: 10.1111/andr.13460. [DOI] [PubMed] [Google Scholar]
- 27.Wang EY, Huang Y, Du QY, Yao GD, Sun YP. Body mass index effects sperm quality: a retrospective study in Northern China. Asian J Androl. 2017;19:234–7. doi: 10.4103/1008-682X.169996. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Barone B, Amicuzi U, Massanova M, Napolitano L, Reccia P, et al. The correlation between body mass index and prostate volume: a retrospective analysis of pre and postoperative measurements in prostate cancer patients. Prostate. 2025;85:433–42. doi: 10.1002/pros.24845. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Qin DD, Yuan W, Zhou WJ, Cui YQ, Wu JQ, et al. Do reproductive hormones explain the association between body mass index and semen quality? Asian J Androl. 2007;9:827–34. doi: 10.1111/j.1745-7262.2007.00268.x. [DOI] [PubMed] [Google Scholar]
- 30.Wang S, Wu B, Wang C, Ke Z, Xiang P, et al. Influence of body mass index and waist-hip ratio on male semen parameters in infertile men in the real world: a retrospective study. Front Endocrinol (Lausanne) 2023;14:1148715. doi: 10.3389/fendo.2023.1148715. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 31.Li WN, Jia MM, Peng YQ, Ding R, Fan LQ, et al. Semen quality pattern and age threshold: a retrospective cross-sectional study of 71,623 infertile men in China, between 2011 and 2017. Reprod Biol Endocrinol. 2019;17:107. doi: 10.1186/s12958-019-0551-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 32.Ramírez N, Estofán G, Tissera A, Molina R, Luque EM, et al. Do aging, drinking, and having unhealthy weight have a synergistic impact on semen quality? J Assist Reprod Genet. 2021;38:2985–94. doi: 10.1007/s10815-021-02274-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 33.Pauli EM, Legro RS, Demers LM, Kunselman AR, Dodson WC, et al. Diminished paternity and gonadal function with increasing obesity in men. Fertil Steril. 2008;90:346–51. doi: 10.1016/j.fertnstert.2007.06.046. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 34.Hammoud AO, Wilde N, Gibson M, Parks A, Carrell DT, et al. Male obesity and alteration in sperm parameters. Fertil Steril. 2008;90:2222–5. doi: 10.1016/j.fertnstert.2007.10.011. [DOI] [PubMed] [Google Scholar]
- 35.Håkonsen LB, Thulstrup AM, Aggerholm AS, Olsen J, Bonde JP, et al. Does weight loss improve semen quality and reproductive hormones? Results from a cohort of severely obese men. Reprod Health. 2011;8:24. doi: 10.1186/1742-4755-8-24. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Ma JX, Wang B, Li HS, Jiang XJ, Yu J, et al. Association between obesity-associated markers and semen quality parameters and serum reproductive hormones in Chinese infertile men. Reprod Biol Endocrinol. 2020;18:95. doi: 10.1186/s12958-020-00652-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 37.Barbagallo F, Condorelli RA, Mongioì LM, Cannarella R, Cimino L, et al. Molecular mechanisms underlying the relationship between obesity and male infertility. Metabolites. 2021;11:840. doi: 10.3390/metabo11120840. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38.Darand M, Salimi Z, Ghorbani M, Sadeghi N, Babaie S, et al. Obesity is associated with quality of sperm parameters in men with infertility: a cross-sectional study. Reprod Health. 2023;20:134. doi: 10.1186/s12978-023-01664-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 39.Fan W, Xu Y, Liu Y, Zhang Z, Lu L, et al. Obesity or overweight, a chronic inflammatory status in male reproductive system, leads to mice and human subfertility. Front Physiol. 2017;8:1117. doi: 10.3389/fphys.2017.01117. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 40.Wang Y, Fu X, Li H. Mechanisms of oxidative stress-induced sperm dysfunction. Front Endocrinol (Lausanne) 2025;16:1520835. doi: 10.3389/fendo.2025.1520835. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 41.Jing J, Peng Y, Fan W, Han S, Peng Q, et al. Obesity-induced oxidative stress and mitochondrial dysfunction negatively affect sperm quality. FEBS Open Bio. 2023;13:763–78. doi: 10.1002/2211-5463.13589. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 42.Busetto GM, Rodrigues BF, Virmani A, Checchia A, Ninivaggi A, et al. Antioxidant treatment for oligoasthenoteratozoospermia and varicocele: a DBPC trial to evaluate the impact of age and body mass index. Asian J Androl. 2024;26:239–44. doi: 10.4103/aja202381. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 43.Rodak K, Kratz EM. PUFAs and their derivatives as emerging players in diagnostics and treatment of male fertility disorders. Pharmaceuticals (Basel) 2023;16:723. doi: 10.3390/ph16050723. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 44.Lenzi A, Gandini L, Maresca V, Rago R, Sgrò P, et al. Fatty acid composition of spermatozoa and immature germ cells. Mol Hum Reprod. 2000;6:226–31. doi: 10.1093/molehr/6.3.226. [DOI] [PubMed] [Google Scholar]
- 45.Martínez-Soto JC, Domingo JC, Cordobilla B, Nicolás M, Fernández L, et al. Dietary supplementation with docosahexaenoic acid (DHA) improves seminal antioxidant status and decreases sperm DNA fragmentation. Syst Biol Reprod Med. 2016;62:387–95. doi: 10.1080/19396368.2016.1246623. [DOI] [PubMed] [Google Scholar]
- 46.Saether T, Tran TN, Rootwelt H, Grav HJ, Christophersen BO, et al. Essential fatty acid deficiency induces fatty acid desaturase expression in rat epididymis, but not in testis. Reproduction. 2007;133:467–77. doi: 10.1530/REP-06-00294. [DOI] [PubMed] [Google Scholar]
- 47.Zhang W, Cui Z, Shen D, Gao L, Li Q. Testosterone levels positively linked to muscle mass but not strength in adult males aged 20-59 years: a cross-sectional study. Front Physiol. 2025;16:1512268. doi: 10.3389/fphys.2025.1512268. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 48.Santos AM, Ferraz MR, Teixeira CV, Sampaio FJ, da Fonte Ramos C. Effects of undernutrition on serum and testicular testosterone levels and sexual function in adult rats. Horm Metab Res. 2004;36:27–33. doi: 10.1055/s-2004-814198. [DOI] [PubMed] [Google Scholar]
- 49.Abou Heif HM, Deif MM, Abdel Aziz HK. Effect of food restriction on ghrelin in adult male rats and its relation to male reproductive hormones. Andrologia. 2010;42:97–105. doi: 10.1111/j.1439-0272.2009.00962.x. [DOI] [PubMed] [Google Scholar]
- 50.Feldman HA, Longcope C, Derby CA, Johannes CB, Araujo AB, et al. Age trends in the level of serum testosterone and other hormones in middle-aged men: longitudinal results from the Massachusetts male aging study. J Clin Endocrinol Metab. 2002;87:589–98. doi: 10.1210/jcem.87.2.8201. [DOI] [PubMed] [Google Scholar]
- 51.Qi X, Guan Q, Zhang W, Huang X, Yu C. The time-dependent adverse effects of a high-fat diet on sperm parameters. Adv Clin Exp Med. 2023;32:889–900. doi: 10.17219/acem/159090. [DOI] [PubMed] [Google Scholar]
- 52.Lalrinzuali S, Khushboo M, Dinata R, Bhanushree B, Nisa N, et al. Long-term consumption of fermented pork fat-based diets differing in calorie, fat content, and fatty acid levels mediates oxidative stress, inflammation, redox imbalance, germ cell apoptosis, disruption of steroidogenesis, and testicular dysfunction in Wistar rats. Environ Sci Pollut Res Int. 2023;30:52446–71. doi: 10.1007/s11356-023-26018-0. [DOI] [PubMed] [Google Scholar]
- 53.Cavaliere G, Viggiano E, Trinchese G, De Filippo C, Messina A, et al. Long feeding high-fat diet induces hypothalamic oxidative stress and inflammation, and prolonged hypothalamic AMPK activation in rat animal model. Front Physiol. 2018;9:818. doi: 10.3389/fphys.2018.00818. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 54.Sepidarkish M, Maleki-Hajiagha A, Maroufizadeh S, Rezaeinejad M, Almasi-Hashiani A, et al. The effect of body mass index on sperm DNA fragmentation: a systematic review and meta-analysis. Int J Obes (Lond) 2020;44:549–58. doi: 10.1038/s41366-020-0524-8. [DOI] [PubMed] [Google Scholar]
- 55.Zhu G, Zhang Y, Dong J, Liu Y, Zhao F, et al. Association between body mass index and male sperm apoptosis and apoptosis-related factors. Diabetes Metab Syndr Obes. 2021;14:1043–51. doi: 10.2147/DMSO.S289923. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 56.Dupont C, Faure C, Sermondade N, Boubaya M, Eustache F, et al. Obesity leads to higher risk of sperm DNA damage in infertile patients. Asian J Androl. 2013;15:622–5. doi: 10.1038/aja.2013.65. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Flow chart of patient inclusion. BMI: body mass index.