Abstract
Male preconception lifestyle factors, such as smoking, alcohol consumption, and body mass index, may affect semen quality, but their dose-dependent and nonlinear effects remain unclear. We retrospectively analyzed 3336 men attending the Department of Andrology, West China Second University Hospital, Sichuan University (Chengdu, China) between January 2019 and June 2023 and collected their demographic information, lifestyle behaviors, and semen parameters. Associations were examined using multivariable regression models with natural cubic splines, with adjustment for age, abstinence period, and season. Smoking showed a clear dose-dependent adverse effect on semen quality as shown by a decline in sperm concentrations, total sperm count, and sperm motility in men who smoked more than 20 cigarettes each day or for longer than 10 years. Former drinkers showed limited improvement in sperm motility. The body mass index showed complex nonlinear associations with semen volume and sperm morphology, and some parameters peaked in mildly overweight men, while obesity remained associated with impaired semen quality. These findings highlight the substantial role of lifestyle factors in male reproductive health during the preconception period and emphasize the importance of smoking cessation and weight management. Even modest changes in body weight may meaningfully improve semen parameters, supporting targeted lifestyle guidance in preconception care.
Keywords: body mass index, drinking, male preconception, semen quality, smoking
INTRODUCTION
Male reproductive health is a major concern in global public health and clinical practice. Male factors account for approximately 30%–50% of infertility cases.1 Semen quality is a key indicator of male fertility potential. A rigorous and comprehensive meta-analysis reported a decline in sperm concentration and total sperm count in Chinese men between 1981 and 2019.2 Similar trends have been observed in European3 and African4 populations, and this global decline appears to have accelerated in the 21st century.5
The decline in semen quality is multifactorial, involving age, lifestyle factors (e.g., smoking and excessive alcohol consumption), environmental exposures, and genital tract infections of bacterial or viral origin.6,7,8,9,10,11 Some studies have shown that modifiable key factors, including smoking, excessive alcohol consumption, and body mass index (BMI), may affect semen quality. An abnormal BMI has been identified as a potential risk factor for impaired semen quality. Previous studies have suggested that obesity is associated with reduced sperm motility, abnormal morphology, and hormonal imbalance.12,13 However, findings from these studies are inconsistent, with study reporting no significant association between elevated BMI and semen quality.14 Smoking, a common unhealthy lifestyle behavior, is widely recognized to be associated with altered sperm DNA methylation, increased DNA fragmentation, and reduced sperm motility,15,16 but the magnitude of the effect according to the smoking dose and duration remains uncertain. The effect of alcohol consumption is even more controversial. A study have suggested a negative association between alcohol consumption and semen quality,17 whereas others showed no significant relationship.18 The modifiable key factors, including smoking, excessive alcohol consumption, and BMI, considerably affect semen quality and may inform preconception guidance for men.
Most studies focused on infertile men or the general population, and limited research targeted men in the preconception period. Compared with other groups, men in the preconception stage are generally healthier and are planning to conceive in the near future, making their lifestyle behaviors highly modifiable. This period represents a critical window for affecting semen quality and fertility potential, as well as an optimal opportunity to implement health interventions to improve the pregnancy outcomes. Preconception health management is a critical component of safeguarding reproductive health and promoting pregnancy outcomes.19 However, evidence-based lifestyle intervention strategies for male reproductive health remain scarce in China.
Therefore, to address the need for clearer evidence on lifestyle effects during preconception care, this study integrated semen analysis and lifestyle data from men attending preconception clinics to assess the effects of smoking, alcohol consumption, and BMI on semen quality. The findings from this study are intended to support clinical counseling and guide health recommendations for men planning conception.
PARTICIPANTS AND METHODS
Study population
This retrospective, cross-sectional study enrolled men seeking preconception consultations at the Department of Andrology, West China Second University Hospital, Sichuan University (Chengdu, China) between January 2019 and June 2023. A total of 3837 men attended preconception evaluations during this period. Eligible participants were aged 18 years or older and had completed at least one standardized semen analysis and sperm morphology assessment, with complete data on BMI, smoking status, drinking status, and duration of abstinence. After excluding individuals with missing key variables (BMI or semen parameters), 3364 participants remained. Participants with an abstinence period of less than 48 h or more than 7 days were further excluded.
The study cohort consisted exclusively of men without any prior diagnosis of male infertility. In routine clinical practice, individuals with a known history or confirmed diagnosis of conditions affecting semen quality, such as cryptorchidism, varicocele, vas deferens obstruction, infertility, teratozoospermia, asthenozoospermia, or oligozoospermia, or those with severe systemic diseases are managed in separate clinical pathways. Therefore, these individuals were excluded in the preconception cohort (Supplementary Figure 1 (161.9KB, tif) ).
Ethical approval
This retrospective study was conducted in accordance with the ethical standards of the Declaration of Helsinki and was approved by the Medical Ethics Committee of West China Second University Hospital, Sichuan University (Approval No. WCSUH-SCU IRB 2024-036). The requirement for informed consent was waived because the study involved the analysis of fully anonymized data collected from routine clinical practice and posed no more than minimal risk to participants.
The original datasets generated and analyzed during this study contain sensitive personal health information and are not publicly available. Anonymized datasets are available from the corresponding author upon reasonable request. All requests are subject to institutional ethics committee approval to ensure compliance with data protection regulations.
Data collection
Standardized medical history interviews and physical examinations were conducted by certified reproductive and andrology specialists for all men attending the andrology clinic. The clinical records were entered into the electronic medical record system of West China Second University Hospital, Sichuan University. The collected data included demographic characteristics, history of reproductive system diseases, and smoking and drinking behaviors. Additionally, information on other parameters, including smoking and alcohol consumption, was collected via online questionnaires. All information was stored in the hospital information system for subsequent analysis.
Semen examination
A semen analysis was conducted in a certified andrology laboratory. The participants were instructed to abstain from ejaculation for 2–7 days before sample collection. Semen samples were obtained via masturbation in a designated collection room, without the use of saliva or lubricants. Semen volume, color, and viscosity were recorded. After complete liquefaction in a 37°C water bath, sperm concentration and the total sperm count were evaluated using light microscopy. In this study, semen collection and analysis followed the 6th edition of World Health Organization (WHO) manual.20,21 Sperm morphology was assessed using Papanicolaou staining with standard staining protocols, and a morphological analysis was performed using a fully automated sperm morphology analyzer (Chengdu Pu Hua Software Co., Ltd., Chengdu, China). Sperm concentration and motility were measured using a Makler Counting chamber (Sefi Medical Instruments, Haifa, Israel) and computer-assisted sperm analysis system (Beijing Sui Jia Software Co., Ltd., Beijing, China). Sperm viability was evaluated using the eosin–nigrosin staining method. The presence and number of round cells (if any) were also recorded. All procedures followed the 6th edition of WHO manual20,21 with rigorous quality assurance and control procedures in place.
Statistical analyses
BMI was calculated as weight (kg) divided by the square of height (m2). According to the WHO criteria,22 BMI was categorized as underweight (<18.5 kg m−2), normal weight (18.5–24.9 kg m−2), overweight (25.0–29.9 kg m−2), and obese (≥30.0 kg m−2). To assess the robustness of our findings, we also conducted a sensitivity analysis by grouping BMI according to the following Chinese standards:23 underweight (<18.5 kg m−2), normal weight (18.5–23.9 kg m−2), overweight (24.0–27.9 kg m−2), and obese (≥28.0 kg m−2). Most semen parameters followed an approximately log-normal distribution. Therefore, all continuous variables were log-transformed before the analysis.
In univariate analysis, continuous variables are presented as the median (interquartile range [IQR]). Intergroup differences were assessed using the Kruskal–Wallis test. Post hoc pairwise comparisons were conducted with Dunn’s test, and the Bonferroni method was applied to adjust for multiple testing. Multivariable generalized linear models (GLMs) were used to evaluate the associations between modifiable risk factors (smoking, alcohol consumption, and BMI) and semen parameters. To assess potential nonlinear dose–response relationships between BMI and semen quality, natural cubic spline functions were incorporated into the models. In the subgroup of current smokers, additional GLMs were constructed to assess the effects of the smoking duration and daily cigarette consumption on semen parameters. Natural cubic splines were applied to examine potential nonlinear associations.
All analyses were performed using R version 4.3.2 (R Foundation for Statistical Computing, Vienna, Austria). All tests were two-sided and P < 0.05 was considered statistically significant.
RESULTS
A total of 3336 male participants who underwent preconception health examinations were included in this study (Table 1). The median age of the study population was 31 (IQR: 29–34) years, and the median abstinence period was 4 (IQR: 3–5) days. Smoking and alcohol consumption were relatively common in this population; 35.4% were current smokers and 68.9% were current drinkers. According to the BMI classification, the majority (61.1%) of the participants had a normal weight, followed by overweight (32.7%). The timing of semen collection among the participants was relatively evenly distributed across the four seasons.
Table 1.
Demographic and semen parameters of men undergoing evaluation of preconception (n=3336)
| Characteristics | Value |
|---|---|
| Age (year), median (IQR) | 31 (29–34) |
| Abstinence period (day), median (IQR) | 4 (3–5) |
| Smoking status, n (%) | |
| Never | 1832 (54.9) |
| Former | 323 (9.7) |
| Current | 1181 (35.4) |
| Drinking status, n (%) | |
| Never | 852 (25.5) |
| Former | 185 (5.5) |
| Current | 2299 (68.9) |
| BMI group, n (%) | |
| Underweight | 83 (2.5) |
| Normal | 2037 (61.1) |
| Overweight | 1092 (32.7) |
| Obese | 124 (3.7) |
| Season, n (%) | |
| Winter (December, January, and February) | 776 (23.3) |
| Spring (March, April, and May) | 1192 (35.7) |
| Summer (June, July, and August) | 647 (19.4) |
| Autumn (September, October, and November) | 721 (21.6) |
| Conventional semen parameters | |
| Semen volume (ml), median (IQR) | 3.4 (2.6–4.5) |
| Sperm concentration (106 ml−1), median (IQR) | 62.5 (33.2–103.5) |
| Total sperm number (106), median (IQR) | 211.7 (110.9–356.3) |
| Total motility (%), median (IQR) | 62.0 (47.0–74.0) |
| Round cell (106 ml−1), median (IQR) | 0.3 (0.2–0.5) |
| PR (%), median (IQR) | 57.0 (41.0–57.0) |
| A (%), median (IQR) | 37.0 (24.0–48.0) |
| B (%), median (IQR) | 17.0 (12.0–23.0) |
| C (%), median (IQR) | 4.0 (2.0–6.0) |
| D (%), median (IQR) | 36.0 (24.0–51.0) |
| Motility | |
| VCL (µm s−1), median (IQR) | 40.1 (27.7–52.4) |
| VSL (µm s−1), median (IQR) | 21.1 (14.2–28.3) |
| ALH (µm s−1), median (IQR) | 3.3 (2.3–4.2) |
| LIN (%), median (IQR) | 52.6 (46.3–58.6) |
| STR (%), median (IQR) | 75.5 (69.8–80.4) |
| VAP (µm s−1), median (IQR) | 28.3 (19.4–37.0) |
| BCF (time s−1), median (IQR) | 9.8 (7.1–12.0) |
| Morphology (%), median (IQR) | |
| PNSC | 6.6 (3.7–10.1) |
| PDSC | 92.9 (89.0–95.9) |
| PHDSC | 92.9 (88.9–95.9) |
| PNIDSC | 7.8 (5.0–11.1) |
| PTDSC | 5.4 (3.3–8.3) |
BMI was categorized using the following the WHO criteria:22 underweight (<18.5 kg m−2), normal weight (18.5–24.9 kg m−2), overweight (25.0–29.9 kg m−2), and obese (≥30.0 kg m−2). IQR: interquartile range; PR: sperm progressive motility; A: rapid forward movement; B: slow forward movement; C: non-forward movement; D: stationary; VCL: curvilinear velocity; VSL: straight-line velocity; ALH: amplitude of lateral head displacement; LIN: linearity; STR: straightness ratio; VAP: average path velocity; BCF: beat cross frequency; PNSC: percentage of normal sperm count; PDSC: percentage of defective sperm count; PHDSC: percentage of sperm count with head defects; PNIDSC: percentage of neck and interrupted defective sperm count; PTDSC: percentage of spermatozoa with tail defects; BMI: body mass index; WHO: World Health Organization
We used the Kruskal–Wallis test to compare semen parameters across the groups defined by smoking status, alcohol consumption, and BMI categories. Significant differences in these variables were observed between the groups (all P < 0.05; Supplementary Table 1–4). Current and former smokers had a significantly lower total sperm count than never smokers (Bonferroni-adjusted P = 0.007 and P = 0.022, respectively). The proportion of grade D sperm was significantly lower in current smokers than that in never smokers (adjusted P = 0.003). Furthermore, current smokers showed a general decline in several sperm morphology indicators, including the percentage of defective sperm count, percentage of sperm count with head defects, percentage of neck and interrupted defective sperm count, and percentage of spermatozoa with tail defects (all adjusted P < 0.05). No significant associations were observed between the smoking status and sperm motility (P = 0.074). Current and never drinkers showed higher sperm vitality, motility, and percentage of morphologically normal spermatozoa than former drinkers (all adjusted P < 0.05). Overweight men showed a significantly higher percentage of normal sperm count (PNSC) than those with a normal BMI (adjusted P = 0.016; Supplementary Table 5).
Supplementary Table 1.
Comparison of semen parameters according to the smoking status (Kruskal–Wallis test)
| Variables | Smoking status | P | ||
|---|---|---|---|---|
|
| ||||
| Never (n=1832) | Former (n=323) | Current (n=1181) | ||
| Standard | ||||
| Semen volume (ml) | 3.5 (2.7–4.5) | 3.4 (2.6–4.5) | 3.4 (2.6–4.4) | 0.089 |
| Sperm concentration (106/ml) | 64.2 (35.8–105.8)a | 54.7 (29.3–93.0)a | 61.6 (30.7–101.0)a | 0.025 |
| Total sperm number (106) | 219.5 (120.0–371.6)a | 196.8 (101.6–332.0)a | 199.2 (101.3–345.3)a | 0.001 |
| Total motility (%) | 61.5 (46.0–74.0) | 60.0 (44.0–74.0) | 64.0 (48.0–75.0) | 0.074 |
| Round cell (106/ml) | 0.3 (0.2–0.5) | 0.3 (0.2–0.5) | 0.3 (0.2–0.5) | 0.918 |
| PR (%) | 56.0 (41.0–69.0) | 56.0 (39.0–69.0) | 58.0 (43.0–70.0) | 0.095 |
| A (%) | 37.0 (24.0–48.0) | 35.0 (23.0–48.0) | 38.0 (25.0–49.0) | 0.227 |
| B (%) | 17.0 (12.0–23.0) | 17.0 (12.0–22.0) | 17.0 (12.0–23.0) | 0.482 |
| C (%) | 4.0 (2.0–6.0) | 4.0 (2.0–6.0) | 4.0 (2.0–6.0) | 0.835 |
| D (%) | 37.0 (25.0–51.0)a | 37.0 (23.0–53.0)a | 34.0 (23.0–48.0)a | 0.004 |
| Motility | ||||
| VCL (µm/s) | 39.6 (27.5–51.7) | 38.3 (26.2–51.3) | 41.4 (28.8–53.9) | 0.071 |
| VSL (µm/s) | 21.1 (14.3–28.3) | 20.4 (13.7–27.8) | 21.6 (14.45–28.7) | 0.176 |
| ALH (µm/s) | 3.2 (2.3–4.1) | 3.2 (2.2–4.0) | 3.3 (2.34–4.2) | 0.139 |
| LIN (%) | 52.7 (46.4–58.8) | 53.0 (45.6–59.1) | 52.2 (46.1–58.2) | 0.286 |
| STR (%) | 75.6 (70.1–80.5) | 75.6 (69.6–80.5) | 75.1 (69.23–80.3) | 0.230 |
| VAP (µm/s) | 27.8 (19.3–36.8) | 26.9 (18.5–36.7) | 28.9 (19.78–37.8) | 0.114 |
| BCF (times/s) | 9.8 (7.0–11.9) | 9.3 (6.7–11.8) | 9.9 (7.4–12.0) | 0.211 |
| Morphological | ||||
| PNSC (%) | 6.6 (3.9–10.0) | 6.2 (2.9–9.6) | 6.8 (3.5–10.5) | 0.090 |
| PDSC (%) | 93.0 (89.3–95.8)a | 93.2 (89.6–96.6)a | 92.8 (88.2–95.7)a | 0.027 |
| PHDSC (%) | 92.9 (89.3–95.8)a | 93.1 (89.5–96.6)a | 92.6 (88.1–95.7)a | 0.036 |
| PNIDSC (%) | 8.0 (5.3–11.2)a | 7.7 (5.3–10.9)a | 7.4 (64.7–11.0)a | 0.031 |
| PTDSC (%) | 5.8 (3.5–8.4)a | 5.7 (3.3–8.4)a | 4.9 (2.9–8.0)a | <0.001 |
aP<0.05 by the Kruskal–Wallis test. Data are presented as the median (IQR). PR: sperm progressive motility sperm; A: rapid forward movement; B: slow forward movement; C: non-forward movement; D: stationary; VCL: curvilinear velocity; VSL: straight-line velocity; ALH: amplitude of lateral head displacement; LIN: linearity; STR: straightness ratio; VAP: average path velocity; BCF: beat cross frequency; PNSC: percentage of normal sperm count; PDSC: percentage of defective sperm count; PHDSC: percentage of sperm count with head defects; PNIDSC: percentage of neck and interrupted defective sperm count; PTDSC: percentage of spermatozoa with tail defects; IQR: interquartile range
Supplementary Table 4.
Comparison of semen parameters according to Chinese body mass index categories (Kruskal–Wallis test)
| Variables | BMI group (Chinese categories) | P | |||
|---|---|---|---|---|---|
|
| |||||
| Underweight (n=83) | Normal (n=1589) | Overweight (n=1309) | Obese (n=355) | ||
| Standard | |||||
| Semen volume (ml) | 3.2 (2.5–4.4)a | 3.5 (2.7–4.6)a | 3.4 (2.6–4.3)a | 3.2 (2.4–4.2)a | <0.001 |
| Sperm concentration (106/ml) | 66.0 (34.8–102.9) | 61.9 (33.1–104.0) | 63.4 (32.7–104.7) | 61.4 (35.0–99.5) | 0.951 |
| Total sperm number (106) | 205.5 (98.3–331.8) | 214.5 (112.1–371.1) | 212.4 (112.4–352.0) | 202.3 (104.7–321.5) | 0.345 |
| Total motility (%) | 65.0 (49.0–74.0) | 61.0 (46.0–74.0) | 63.0 (47.0–74.0) | 63.0 (48.5–74.0) | 0.411 |
| Round cell (106/ml) | 0.4 (0.2–0.6) | 0.3 (0.2–0.5) | 0.3 (0.2–0.5) | 0.3 (0.2–0.5) | 0.085 |
| PR (%) | 58.0 (42.0–68.0) | 56.0 (41.0–69.0) | 57.0 (42.0–69.0) | 59.0 (43.0–69.0) | 0.400 |
| A (%) | 38.0 (24.0–49.0) | 36.0 (24.0–48.0) | 37.0 (24.0–48.0) | 37.0 (26.0–49.0) | 0.293 |
| B (%) | 18.0 (13.0–21.0) | 17.0 (12.0–23.0) | 17.0 (12.0–23.0) | 17.0 (13.0–23.0) | 0.754 |
| C (%) | 5.0 (2.5–8.0) | 4.0 (2.0–6.0) | 4.0 (2.0–6.0) | 4.0 (2.0–7.0) | 0.401 |
| D (%) | 32.0 (25.0–47.0) | 37.0 (24.0–51.0) | 35.0 (24.0–50.0) | 35.0 (24.0–49.5) | 0.309 |
| Motility | |||||
| VCL (µm/s) | 41.9 (27.2–50.8) | 39.4 (27.1–51.9) | 40.3 (28.0–52.7) | 40.5 (29.3–53.1) | 0.499 |
| VSL (µm/s) | 21.6 (14.8–27.1) | 20.6 (13.8–28.1) | 21.5 (14.5–28.7) | 21.9 (14.9–28.4) | 0.263 |
| ALH (µm/s) | 3.2 (2.3–4.0) | 3.3 (2.3–4.2) | 3.3 (2.3–4.2) | 3.3 (2.5–4.2) | 0.805 |
| LIN (%) | 51.5 (46.4–57.9) | 52.4 (46.1–58.5) | 52.8 (46.6–58.8) | 52.4 (46.0–59.2) | 0.414 |
| STR (%) | 74.2 (70.9–78.5) | 75.3 (69.5–80.4) | 75.8 (70.1–80.3) | 75.7 (70.0–81.3) | 0.435 |
| VAP (µm/s) | 28.7 (18.8–35.5) | 27.7 (19.1–37.0) | 28.7 (19.5–37.4) | 28.8 (20.5–36.7) | 0.347 |
| BCF (times/s) | 9.8 (7.7–11.5) | 9.6 (7.0–12.0) | 10.0 (7.1–12.0) | 9.8 (7.7–11.9) | 0.438 |
| Morphological | |||||
| PNSC (%) | 5.9 (3.0–10.1) | 6.4 (3.5–9.9) | 6.8 (3.7–10.4) | 7.0 (4.3–10.4) | 0.059 |
| PDSC (%) | 93.8 (88.2–96.3) | 93.1 (89.3–96.0) | 92.8 (88.7–95.8) | 92.6 (88.9–95.4) | 0.193 |
| PHDSC (%) | 93.6 (88.2–96.4) | 93.1 (89.2–96.0) | 92.7 (88.5–95.7) | 92.6 (88.9–95.5) | 0.171 |
| PNIDSC (%) | 7.5 (4.9–11.1) | 7.9 (5.0–11.2) | 7.7 (5.0–10.9) | 7.9 (5.2–11.1) | 0.786 |
| PTDSC (%) | 5.7 (3.3–7.9) | 5.4 (3.2–8.4) | 5.4 (3.4–8.2) | 5.5 (3.4–8.3) | 0.997 |
aP<0.05 by the Kruskal–Wallis test. Data are presented as the median (IQR). PR: sperm progressive motility sperm; A: rapid forward movement; B: slow forward movement; C: non-forward movement; D: stationary; VCL: curvilinear velocity; VSL: straight-line velocity; ALH: amplitude of lateral head displacement; LIN: linearity; STR: straightness ratio; VAP: average path velocity; BCF: beat cross frequency; PNSC: percentage of normal sperm count; PDSC: percentage of defective sperm count; PHDSC: percentage of sperm count with head defects; PNIDSC: percentage of neck and interrupted defective sperm count; PTDSC: percentage of spermatozoa with tail defects; IQR: interquartile range; BMI: body mass index
Supplementary Table 5.
Groupwise comparisons of semen quality according to smoking, drinking, and body mass index categories
| Variables | Group 1 | Group 2 | Z | P unadjusted | P adjusted |
|---|---|---|---|---|---|
| PTDSC | Current smoker | Never smoker | −4.612 | <0.001 | <0.001 |
| D | Current smoker | Never smoker | −3.247 | 0.001 | 0.003 |
| Total sperm number | Current smoker | Never smoker | −3.039 | 0.002 | 0.007 |
| Total sperm number | Former smoker | Never smoker | −2.677 | 0.007 | 0.022 |
| PNIDSC | Current smoker | Never smoker | −2.615 | 0.008 | 0.0267 |
| PDSC | Current smoker | Former smoker | −2.431 | 0.015 | 0.045 |
| PNSC | Current drinker | Former drinker | 4.634 | <0.001 | <0.001 |
| PDSC | Current drinker | Former drinker | −4.397 | <0.001 | <0.001 |
| PNSC | Former drinker | Never drinker | −4.262 | <0.001 | <0.001 |
| ALH | Current drinker | Former drinker | 4.231 | <0.001 | <0.001 |
| PHDSC | Current drinker | Former drinker | −4.213 | <0.001 | <0.001 |
| VCL | Current drinker | Former drinker | 4.130 | <0.001 | <0.001 |
| VAP | Current drinker | Former drinker | 3.845 | <0.001 | <0.001 |
| PDSC | Former drinker | Never drinker | 3.636 | <0.001 | <0.001 |
| PHDSC | Former drinker | Never drinker | 3.539 | <0.001 | 0.001 |
| VSL | Current drinker | Former drinker | 3.489 | <0.001 | 0.001 |
| Total motility | Current drinker | Former drinker | 3.362 | <0.001 | 0.002 |
| PR | Current drinker | Former drinker | 3.318 | <0.001 | 0.002 |
| VCL | Former drinker | Never drinker | −3.104 | 0.001 | 0.005 |
| ALH | Former drinker | Never drinker | −2.953 | 0.003 | 0.009 |
| VAP | Former drinker | Never drinker | −2.948 | 0.003 | 0.009 |
| BCF | Current drinker | Former drinker | 2.928 | 0.003 | 0.010 |
| VSL | Former drinker | Never drinker | −2.831 | 0.004 | 0.013 |
| D | Current drinker | Former drinker | −2.767 | 0.005 | 0.016 |
| A | Current drinker | Former drinker | 2.755 | 0.005 | 0.017 |
| Total motility | Former drinker | Never drinker | −2.618 | 0.008 | 0.026 |
| BCF | Former drinker | Never drinker | −2.533 | 0.011 | 0.033 |
| PR | Former drinker | Never drinker | −2.487 | 0.012 | 0.038 |
| B | Current drinker | Former drinker | 2.452 | 0.014 | 0.042 |
| PNSC | Normal weight | Overweight | −2.993 | 0.002 | 0.016 |
| Semen volume | Normal weight | Obese | 4.008 | <0.001 | <0.001 |
| Semen volume | Obese | Overweight | −2.996 | 0.002 | 0.016 |
P adjusted indicates Bonferroni-adjusted P values. Statistical significance was defined as P adjusted <0.05. PR: sperm progressive motility sperm; A: rapid forward movement; B: slow forward movement; C: non-forward movement; D: stationary; VCL: curvilinear velocity; VSL: straight-line velocity; ALH: amplitude of lateral head displacement; LIN: linearity; STR: straightness ratio; VAP: average path velocity; BCF: beat cross frequency; PNSC: percentage of normal sperm count; PDSC: percentage of defective sperm count; PHDSC: percentage of sperm count with head defects; PNIDSC: percentage of neck and interrupted defective sperm count; PTDSC: percentage of spermatozoa with tail defects
Supplementary Table 2.
Comparison of semen parameters according to the drinking status (Kruskal–Wallis test)
| Variables | Drinking status | P | ||
|---|---|---|---|---|
|
| ||||
| Never (n=852) | Former (n=185) | Current (n=2299) | ||
| Standard | ||||
| Semen volume (ml) | 3.4 (2.5–4.4) | 3.5 (2.8–4.4) | 3.4 (2.6–4.5) | 0.483 |
| Sperm concentration (106/ml) | 60.8 (33.9–100.2) | 56.7 (26.4–88.2) | 63.7 (33.6–105.2) | 0.135 |
| Total sperm number (106) | 201.5 (112.9–347.8) | 194.1 (93.6–345.9) | 216.0 (111.9–361.4) | 0.158 |
| Total motility (%) | 62.0 (46.0–73.0)a | 58.0 (39.0–71.0)a | 63.0 (47.0–75.0)a | 0.003 |
| Round cell (106/ml) | 0.3 (0.2–0.6) | 0.3 (0.2–0.5) | 0.3 (0.2–0.5) | 0.412 |
| PR (%) | 56.0 (41.0–68.0)a | 52.0 (34.0–64.0)a | 57.0 (42.0–70.0)a | 0.003 |
| A (%) | 37.0 (24.0–47.2)a | 34.0 (19.0–44.0)a | 37.0 (25.0–49.0)a | 0.022 |
| B (%) | 17.0 (12.0–22.0)a | 16.0 (11.0–21.0)a | 17.0 (12.0–23.0)a | 0.033 |
| C (%) | 4.0 (3.0–7.0) | 4.0 (2.0–6.0) | 4.0 (2.0–6.0) | 0.068 |
| D (%) | 37.0 (25.0–51.0)a | 40.0 (27.0–55.0)a | 35.0 (23.0–50.0)a | 0.008 |
| Motility | ||||
| VCL (µm/s) | 39.5 (27.5–50.7)a | 35.0 (22.0–47.2)a | 40.6 (28.4–53.6)a | <0.001 |
| VSL (µm/s) | 21.0 (14.4–27.8)a | 19.2 (12.3–26.3)a | 21.4 (14.6–28.8)a | 0.002 |
| ALH (µm/s) | 3.2 (2.23–4.1)a | 2.9 (1.8–3.8)a | 3.3 (2.4–4.2)a | <0.001 |
| LIN (%) | 52.9 (46.5–58.8) | 53.1 (45.2–59.2) | 52.5 (46.2–58.5) | 0.309 |
| STR (%) | 75.9 (70.4–80.4) | 76.1 (69.9–80.5) | 75.3 (69.6–80.4) | 0.370 |
| VAP (µm/s) | 27.9 (19.4–36.3)a | 25.6 (15.9–34.5)a | 28.5 (19.8–37.6)a | <0.001 |
| BCF (times/s) | 9.8 (7.1–11.9)a | 9.0 (6.0–11.5)a | 9.9 (7.2–12.0)a | 0.014 |
| Morphological | ||||
| PNSC (%) | 6.7 (3.9–9.9)a | 4.9 (2.5–8.2)a | 6.7 (3.8–10.4)a | <0.001 |
| PDSC (%) | 92.9 (89.4–95.8)a | 94.6 (90.5–97.0)a | 92.8 (88.7–95.7)a | <0.001 |
| PHDSC (%) | 92.8 (89.3–95.8)a | 94.6 (90.4–97.0)a | 92.8 (88.6–95.7)a | <0.001 |
| PNIDSC (%) | 8.2 (5.1–11.5) | 7.8 (5.5–10.8) | 7.7 (5.0–10.9) | 0.090 |
| PTDSC (%) | 5.8 (3.45–8.4) | 5.7 (3.4–8.5) | 5.4 (3.3–8.2) | 0.096 |
aP<0.05 by Kruskal–Wallis test. Data are presented as the median (IQR). PR: sperm progressive motility sperm; A: rapid forward movement; B: slow forward movement; C: non-forward movement; D: stationary; VCL: curvilinear velocity; VSL: straight-line velocity; ALH: amplitude of lateral head displacement; LIN: linearity; STR: straightness ratio; VAP: average path velocity; BCF: beat cross frequency; PNSC: percentage of normal sperm count; PDSC: percentage of defective sperm count; PHDSC: percentage of sperm count with head defects; PNIDSC: percentage of neck and interrupted defective sperm count; PTDSC: percentage of spermatozoa with tail defects; IQR: interquartile range
Supplementary Table 3.
Comparison of semen parameters according to who body mass index categories (Kruskal–Wallis test)
| Variables | BMI group (WHO categories) | P | |||
|---|---|---|---|---|---|
|
| |||||
| Underweight (n=83) | Normal (n=2037) | Overweight (n=1092) | Obese (n=124) | ||
| Standard | |||||
| Semen volume (ml) | 3.2 (2.5–4.4)a | 3.5 (2.7–4.6)a | 3.4 (2.6–4.2)a | 3.1 (2.2–4.4)a | 0.007 |
| Sperm concentration (106/ml) | 66.0 (34.8–102.9) | 61.9 (32.7–103.5) | 63.6 (34.2–105.4) | 59.5 (35.4–94.9) | 0.806 |
| Total sperm number (106) | 205.5 (98.3–331.8) | 214.7 (111.0–369.4) | 204.8 (111.6–348.8) | 198.8 (107.0–296.7) | 0.521 |
| Total motility (%) | 65.0 (49.0–74.0) | 62.0 (46.0–74.0) | 63.0 (47.7–74.0) | 63.5 (47.7–75.0) | 0.232 |
| Round cell (106/ml) | 0.4 (0.2–0.6)a | 0.3 (0.2–0.5)a | 0.3 (0.2–0.5)a | 0.3 (0.2–0.5)a | 0.039 |
| PR (%) | 58.0 (42.0–68.0) | 56.0 (41.0–69.0) | 58.0 (43.0–70.0) | 59.0 (42.0–69.0) | 0.270 |
| A (%) | 38.0 (24.0–49.0) | 36.0 (24.0–48.0) | 38.0 (25.0–48.2) | 36.0 (24.7–51.0) | 0.288 |
| B (%) | 18.0 (13.0–21.0) | 17.0 (12.0–23.0) | 17.0 (12.0–23.0) | 17.0 (14.0–23.2) | 0.614 |
| C (%) | 5.0 (2.8–8.0) | 4.0 (2.0–6.0) | 4 (2.0–6.0) | 4.0 (2.0–7.0) | 0.256 |
| D (%) | 32.0 (25–47.0) | 36.0 (24.0–51.0) | 35.0 (24.0–50.0) | 34.0 (23.7–51.0) | 0.400 |
| Motility | |||||
| VCL (µm/s) | 41.9 (27.2–50.8) | 39.5 (27.2–52.1) | 40.7 (28.5–52.6) | 41.3 (30.6–53.7) | 0.448 |
| VSL (µm/s) | 21.6 (14.8–27.1) | 20.8 (13.8–28.3) | 21.7 (14.7–28.6) | 22.4 (14.6–29.2) | 0.304 |
| ALH (µm/s) | 3.2 (2.3–4.0) | 3.2 (2.3–4.2) | 3.3 (2.4–4.2) | 3.3 (2.5–4.2) | 0.625 |
| LIN (%) | 51.5 (46.4–57.9) | 52.5 (46.1–58.4) | 52.7 (47.0–59.0) | 52.8 (45.7–59.8) | 0.465 |
| STR (%) | 74.2 (70.9–78.5) | 75.5 (69.6–80.3) | 75.7 (70.2–80.6) | 75.2 (68.6–81.3) | 0.463 |
| VAP (µm/s) | 28.7 (18.8–35.5) | 27.8 (19.1–37.0) | 28.8 (20.0–37.1) | 29.1 (20.0–37.6) | 0.327 |
| BCF (times/s) | 9.8 (7.7–11.5) | 9.7 (6.9–12.0) | 10.0 (7.4–12.0) | 9.8 (7.6–11.9) | 0.369 |
| Morphological | |||||
| PNSC (%) | 5.9 (3.0–10.1)a | 6.4 (3.4–9.9)a | 6.9 (3.9–10.6)a | 6.8 (4.3–10.2)a | 0.014 |
| PDSC (%) | 93.8 (88.2–96.3) | 93.0 (89.3–96.0) | 92.7 (88.5–95.5) | 93.0 (89.3–95.5) | 0.152 |
| PHDSC (%) | 93.6 (88.2–96.4) | 93.0 (89.2–96.0) | 92.6 (88.4–95.5) | 93.0 (89.3–95.5) | 0.112 |
| PNIDSC (%) | 7.5 (4.9–11.1) | 7.8 (5.0–11.0) | 7.8 (5.2–11.3) | 7.7 (4.4–10.6) | 0.919 |
| PTDSC (%) | 5.7 (3.3–7.9) | 5.4 (3.0–8.3) | 5.4 (3.3–8.2) | 6.1 (3.7–8.8) | 0.581 |
aP<0.05 by the Kruskal–Wallis test. Data are presented as the median (IQR). PR: sperm progressive motility sperm; A: rapid forward movement; B: slow forward movement; C: non-forward movement; D: stationary; VCL: curvilinear velocity; VSL: straight-line velocity; ALH: amplitude of lateral head displacement; LIN: linearity; STR: straightness ratio; VAP: average path velocity; BCF: beat cross frequency; PNSC: percentage of normal sperm count; PDSC: percentage of defective sperm count; PHDSC: percentage of sperm count with head defects; PNIDSC: percentage of neck and interrupted defective sperm count; PTDSC: percentage of spermatozoa with tail defects; IQR: interquartile range; BMI: body mass index; WHO: World Health Organization
Multivariable GLMs are shown in Figure 1. Lifestyle factors showed distinct associations with semen quality. Current smokers showed a significantly lower semen volume (P = 0.015), sperm concentration (P = 0.010), and total sperm count (P = 0.001) than never smokers. Additionally, current smokers showed lower motility parameters, such as linearity and the straightness ratio, than never smokers (both P < 0.05). Moreover, former drinkers showed significantly impaired sperm motility compared with never drinkers, including the amplitude of lateral head displacement, straight-line velocity, average path velocity, beat cross frequency, and curvilinear velocity (all P < 0.05). Additionally, former drinkers also had a lower proportion of grade A sperm (P = 0.049) and a lower PNSC (P < 0.001). Interestingly, overweight men demonstrated better sperm quality, as shown by a higher proportion of grade A sperm (P = 0.019) and greater PNSC (P = 0.003), than those with a normal weight. Overweight men also had improved motility indices compared with those with a normal weight (P < 0.05; Figure 1a). Older age and longer abstinence were associated with variation in semen quality, while autumn samples showed a higher proportion of grade C sperm compared with winter (all P < 0.05; Figure 1b).
Figure 1.
Multivariable generalized linear model analysis in the overall population. (a) Significant effects of smoking, drinking, and BMI on semen parameters. (b) Significant effects of age, abstinence period, and season on semen parameters. Reference groups: never smokers, never drinkers, normal BMI, and winter season. PR: sperm progressive motility; A: rapid forward movement; B: slow forward movement; C: non-forward movement; D: stationary; VCL: curvilinear velocity; VSL: straight-line velocity; ALH: amplitude of lateral head displacement; LIN: linearity; STR: straightness ratio; VAP: average path velocity; BCF: beat cross frequency; PNSC: percentage of normal sperm count; PDSC: percentage of defective sperm count; PHDSC: percentage of sperm count with head defects; PNIDSC: percentage of neck and interrupted defective sperm count; PTDSC: percentage of spermatozoa with tail defects; OR: odds ratio; CI: confidence interval.
According to the Chinese BMI classification, the numbers of participants classified as underweight, normal weight, overweight, and obese were 83 (2.5%), 1589 (47.6%), 1309 (39.2%), and 355 (10.6%), respectively (Supplementary Table 6). Semen volume was lower in participants with obesity than that in those with normal weight and overweight (adjusted P < 0.05; Supplementary Table 5). However, participants with obesity showed slightly higher proportions of grade A sperm (P = 0.049), PNSC (P = 0.024), and beat cross frequency (P = 0.048) than participants with normal weight (Supplementary Figure 2 (49.3KB, tif) ).
Supplementary Table 6.
Descriptive analysis of Chinese body mass index groups
| BMI Chinese group | Value |
|---|---|
| Underweight | 83 (2.5) |
| Normal | 1589 (47.6) |
| Overweight | 1309 (39.2) |
| Obese | 355 (10.6) |
Data are presented as n (%). BMI was categorized using the following Chinese criteria: underweight (<18.5 kg/m2), normal weight (18.5–23.9 kg/m2), overweight (24–27.9 kg/m2), and obese (≥28 kg/m2). BMI: body mass index
Continuous BMI was nonlinearly associated with several semen quality parameters (P < 0.05; Figure 2a–2c). Biphasic M-shaped relationships were observed between BMI and semen volume and PNSC, and local maxima occurred at approximately 21.5 kg m−2 and 24.9 kg m−2, respectively. In contrast, BMI showed an inverse M-shaped association with the round cell count, which was characterized by an initial decline, a modest rebound at 21.5 kg m−2, a second decline at 24.9 kg m−2, and a subsequent monotonic increase beyond 30 kg m−2.
Figure 2.
Natural cubic spline analysis of the associations between body mass index (BMI) and semen parameters, including (a) semen volume, (b) percentage of normal sperm count (PNSC), and (c) round cell count, in the overall population.
Among current smokers, a stratified analysis was performed by categorizing the participants into two groups according to the smoking duration (>10 years and ≤10 years). The multivariable GLM analysis showed that men with a smoking history >10 years had significantly higher round cell counts in semen than those who smoked for ≤10 years (P = 0.035). There were no significant differences in other semen quality parameters between these two groups of smoking duration (all P > 0.05; Figure 3a). In the GLM analysis restricted to current smokers, overweight men showed significantly higher sperm motility parameters than normal weight men (P < 0.05), which was consistent with the pattern observed in the overall sample (Figure 3a). Finally, the directions of associations for age, abstinence period, and season of semen collection were consistent with those reported in the overall analysis (Figure 3b).
Figure 3.
Multivariable generalized linear model analysis in current smokers. (a) Significant effects of smoking, drinking, and BMI on semen parameters. (b) Significant effects of age, abstinence period, and season on semen parameters. Reference groups: never smokers, never drinkers, normal BMI, and winter season. PR: sperm progressive motility; A: rapid forward movement; B: slow forward movement; C: non-forward movement; D: stationary; VCL: curvilinear velocity; VSL: straight-line velocity; ALH: amplitude of lateral head displacement; LIN: linearity; STR: straightness ratio; VAP: average path velocity; BCF: beat cross frequency; PNSC: percentage of normal sperm count; PDSC: percentage of defective sperm count; PHDSC: percentage of sperm count with head defects; PNIDSC: percentage of neck and interrupted defective sperm count; PTDSC: percentage of spermatozoa with tail defects; OR: odds ratio; CI: confidence interval.
In contrast, the natural cubic spline function analysis showed more nuanced nonlinear associations between the smoking duration and semen quality (P < 0.05). The proportion of grade D sperm initially decreased when the smoking duration was ≤10 years, increased at approximately 15 years, and declined again at approximately 30 years. Semen volume showed a different pattern, with a steady decline when the smoking duration exceeded 15 years (Figure 4a and 4b). Moreover, the analysis of daily cigarette consumption showed a biphasic M-shaped association with the PNSC (P < 0.05), which was characterized by a sharp decline when consumption exceeded 20 cigarettes each day (Figure 4c).
Figure 4.
Natural cubic spline analysis of the associations between lifestyle factors and semen parameters of current smokers. (a) Association between smoking duration and percentage of stationary (D-grade) sperm. (b) Association between smoking duration and semen volume. (c) Association between cigarettes smoked per day and percentage of normal sperm count (PNSC). (d) association between body mass index (BMI) and percentage of non-forward motile (C-grade) sperm. (e) Association between BMI and PNSC.
Additionally, an inverse S-shaped relationship was observed between BMI and the proportion of grade C sperm, and the proportion of grade C sperm steadily increased after a slight decline when BMI exceeded 24.9 kg m−2. The association between continuous BMI and the PNSC was also consistent with that observed in the overall population (Figure 4d and 4e).
DISCUSSION
This study, which was based on a large-scale, cross-sectional population of men who underwent preconception outpatient examinations, systematically evaluated the effects of smoking, drinking, and BMI on semen quality.
We found that smoking had a significant negative effect on sperm concentrations, total sperm count, and multiple motility parameters. Daily cigarette consumption and the smoking duration showed clear dose–response relationships, with the most pronounced decline observed in men who smoked more than 20 cigarettes each day or in those with a smoking history exceeding 10 years. The detrimental effects of smoking on male reproductive health have been well documented.24,25 The present findings are partly consistent with a meta-analysis by Sharma et al.26 who found that smoking reduced the sperm count and motility. The underlying mechanisms of this finding may involve the toxic effects of nicotine,27 elevated carbon monoxide levels leading to decreased oxyhemoglobin concentrations, and impaired mitochondrial oxygen use in sperm. Smoking cessation has been shown to improve semen quality. In a previous study, sperm concentrations and semen volume increased 3 months after quitting smoking in infertile men.28 In another study, no significant difference in semen quality was observed between former smokers and never smokers,29 further supporting the importance of smoking cessation in improving male fertility.
In this study, the effects of alcohol consumption on male fertility were less than those of smoking. Former drinkers showed a reduction in several semen parameters, particularly sperm motility, whereas current drinkers were not significantly different from never drinkers. Among smokers, alcohol intake was not significantly associated with most semen parameters. A large-scale study involving 8344 men reported no significant association between recent alcohol intake and conventional semen parameters, but showed a linear relationship with testosterone concentration.30 This finding suggested that alcohol affects the hypothalamic–pituitary–gonadal axis through hepatic metabolism. Experimental studies have shown that ethanol exposure can reduce sperm motility, increase sperm mortality and apoptosis, and potentially cause long-term damage.31 Further evidence from murine models has indicated that chronic paternal alcohol consumption before conception reduces embryo survival and the pregnancy success rate in a dose–dependent manner.32 A meta-analysis also suggested that paternal alcohol intake affects offspring neurodevelopment and behavior through genetic and epigenetic mechanisms.33 Collectively, these findings indicate the importance of reducing or avoiding alcohol consumption during the preconception period.
Using a categorical analysis combined with natural cubic spline modeling, we precisely characterized the dose–response relationship between BMI and semen parameters. We found that semen volume significantly declined when BMI reached or exceeded 30.0 kg m−2, consistent with a previous study.34 Obesity was associated with reductions in sperm concentrations and the total count, as well as with increased morphological abnormalities.35,36 Potential mechanisms of these associations may include impaired hypothalamic–pituitary–testicular axis function,37,38 increased aromatase activity leading to elevated estrogen concentrations and suppression of the gonadal axis,39,40 and an elevated scrotal temperature accompanied by increased oxidative stress.41 Interventional studies have shown that weight loss through diet and exercise can increase sperm concentrations and total sperm count by 1.49-fold and 1.41-fold, respectively,42 suggesting that weight management improves semen quality in men with obesity.
Preconception health management not only helps optimize male reproductive function but also plays a critical role in reducing the incidence of infertility and improving overall population health. However, traditional preconception guidance has predominantly focused on women,43 with limited attention to men’s lifestyle factors. Our findings suggest that preconception interventions for men should incorporate the regulation of BMI, smoking cessation, and responsible alcohol consumption, forming a systematic lifestyle management strategy to enhance semen quality and reproductive potential.
This study has several strengths, including its large sample size and the use of real-world clinical data, providing findings of practical relevance for clinical practice. Additionally, we analyzed BMI using the WHO22 and China-specific23 classification systems. Under the WHO criteria, overweight men showed better sperm quality, including a higher proportion of grade A sperm, PNSC, and motility indices, than normal weight men. In contrast, using the Chinese criteria, men with obesity showed a lower semen volume but slightly higher proportions of grade A sperm, PNSC, and beat cross frequency than normal weight men. This discrepancy between these two systems is likely due to differences in the BMI thresholds of the systems, which may assign the same individual to different categories and thereby affect the observed associations. To minimize the effect of classification schemes, we further treated BMI as a continuous variable to assess its dose–response relationship with semen quality, which is an important strength of this study.
However, our study has several limitations. First, the cross-sectional and retrospective design of the study limits the ability to establish causal relationships and the temporal sequence between lifestyle factors and semen quality. Second, each participant provided only a single semen sample, which may not have adequately reflected individual variability. Drinking patterns were recorded only as categorical data because of practical limitations in clinical data collection (e.g., difficulties in accurately recalling alcohol intake levels and frequency). Future studies using repeated measurements and more detailed drinking data are expected to enhance the precision and depth of the analysis. Third, information on drug use, including anabolic–androgenic steroids, which suppress spermatogenesis,44 was not available. The lack of these data may have introduced additional unmeasured confounding. Finally, although participants with known reproductive disorders or severe systemic diseases were excluded, other unmeasured factors may still have affected semen quality. Future research should include multicenter, prospective studies to validate these findings, explore underlying mechanisms, and assess the actual effects of lifestyle interventions on male reproductive health.
In conclusion, this study shows that smoking has a dose–dependent adverse effect on sperm concentrations, the total sperm count, and sperm motility and suggests that sperm motility is also impaired in former drinkers. BMI shows a complex nonlinear association with semen quality, suggesting that simple categorical grouping may underestimate its effect. These findings indicate the importance of targeted preconception lifestyle interventions in men, particularly smoking cessation and weight management. By linking cumulative smoking exposure and BMI to multiple semen parameters, our study provides clinicians with quantitative evidence to guide individualized counseling and risk assessment. This evidence will allow reproductive specialists to offer more precise, evidence-based recommendations during fertility consultations, emphasizing early lifestyle modification rather than general advice. Such data-driven guidance may be particularly useful for men with unexplained infertility or those planning conception, enhancing the practical relevance of preconception care.
AUTHOR CONTRIBUTIONS
HLY and TTY contributed to the study design, data analysis, and drafting of the manuscript. RT assisted with the study design and data analysis. CZ and FY contributed to revising the manuscript. ZML and FPL participated in critical review of the manuscript. All authors read and approved the final manuscript.
COMPETING INTERESTS
All authors declare no competing interests.
Flowchart of the study design.
Significant effects of Chinese BMI groups on semen parameters. A: rapid forward movement; BCF: beat cross frequency; PNSC: percentage of normal sperm count.
ACKNOWLEDGMENTS
This study was supported by the Sichuan Science and Technology Program (No. 2024NSFSC0647), the Health Commission of Sichuan Province Medical Science and Technology Program (No. 24SYJS01), and the Key Project of Regional Joint Fund of National Natural Science Foundation of China (No. U23A20494).
Supplementary Information is linked to the online version of the paper on the Asian Journal of Andrology website.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Flowchart of the study design.
Significant effects of Chinese BMI groups on semen parameters. A: rapid forward movement; BCF: beat cross frequency; PNSC: percentage of normal sperm count.