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. 2023 Nov 23;20:173. doi: 10.1186/s12978-023-01718-5

Association of diet and lifestyle factors with semen quality in male partners of Chinese couples preparing for pregnancy

Hanran Mai 1,2,#, Junyi Ke 1,2,#, Zilin Zheng 1,2,#, Jieyi Luo 1,2, Miaomiao Li 1,2, Yanxia Qu 3, Fan Jiang 4, Simian Cai 5, Liandong Zuo 2,✉
PMCID: PMC10666430  PMID: 37996913

Abstract

Background

Semen quality significantly influences conception, and its preservation is crucial for couples seeking pregnancy. We investigated dietary and lifestyle risk factors impacting semen quality.

Methods

A total of 466 males from the Guangzhou Women and Children’s Medical Center’s pre-pregnancy consultation clinic were recruited between January 2021 and March 2023 for inclusion. Semen analysis was performed, and diet and lifestyle data were gathered via questionnaire. Logistic regression was utilized to examine the link between diet, lifestyle variables, and semen quality.

Results

Smoking worsened progressive sperm motility (38.0% vs. 36.0%, t = 2.262; P = 0.049). Alcohol consumption impaired progressive motility (40.5 ± 17.8% vs. 34.7 ± 16.1%, t = 3.396; P < 0.001) and total motility (56.0% vs. 64.0%; P = 0.001). Using plastic beverage bottles for oil or seasonings lowered sperm concentrations (40.4% vs. 59.0% vs. 65.5%; P = 0.032). A sweet diet correlated with higher total sperm motility (55.0% vs. 60.0%, 62.0% vs. 63.2%; P = 0.017). Higher milk product intake improved sperm concentration (41.6106 vs. 63.7106 vs. 66.1*106; P = 0.021) and motility (54.5% vs. 56.0% vs. 63.0%; P = 0.033). More frequent egg consumption increased semen volume (3.1 mL vs. 3.8 mL vs. 4.0 mL; P = 0.038). Roughage intake enhanced sperm concentration (160.8106 vs. 224.6106; P = 0.027), and adequate sleep improved progressive sperm motility rate (35.4% ± 18.2% vs. 40.2 ± 16.3%, F = 3.747; P = 0.024) and total motility (52.7% vs. 61.5%; P = 0.013). The regression model showed that using plastic containers for condiments was a protective factor for semen volume (OR: 0.12; CI 0.03–0.55; P = 0.006), sperm concentration (OR: 0.001, CI 0.00–0.30; P = 0.012), and count (OR: 0.12, CI 0.03–0.48; P = 0.003). Milk and egg consumption were also protective for semen volume (OR: 0.18, CI 0.06–0.51; P = 0.001 and OR: 0.11, CI 0.03–0.55; P = 0.006, respectively), while sufficient sleep benefitted total sperm motility (OR: 0.47, CI 0.24–0.95; P = 0.034).

Conclusions

Smoking and drinking, type of condiment container, diet preference, sleep duration, and milk, roughage, and egg consumption may reduce semen quality.

Keywords: Semen quality, Male fertility, Diet factors, Lifestyle factors

Background

Couples who fail to conceive after 12 months of regular unprotected sexual activity are defined as infertile. In China, infertility has risen from approximately 12% to 18% as a result of improvements in education levels and quality of life, as well as changes in the concept of childbearing, and delays in the age of marriage and pregnancy [1]. Studies have shown that semen quality in adult males has been declining globally and has stabilized at low levels in recent decades [2]. Although the underlying causes of declining semen quality are the focus of current research, poor dietary habits and lifestyles may go some way to explain these trends. Therefore, there is an urgent need to identify the risk factors associated with infertility to help couples to restore their fertility.

Infertility affects both males and females. According to Sengupta P et al., male factors cause infertility in up to 40% of couples [3]. In clinical and scientific work, semen parameters, including semen volume, sperm concentration, sperm count, sperm progressive motility, and total motility, are often used as indicators to assess male fertility [4]. Spermatogenesis is a dynamically changing physiological process [5], which is easily influenced by lifestyle and diet. A review by Ostojic pointed out that creatine is a potential supplement for couples preparing for pregnancy, while another review indicated that the intake of myo-inositol is an effective supplement for sperm quality [6]. The muscles of animals, such as beef and pork, are rich in creatine and myo-inositol, which are difficult to obtain. Herbal foodstuffs such as onions, garlic, and carrots contain numerous nutrients that have positive effects on testosterone production and improve semen quality. Overall, a varied and balanced diet is important for maintaining good semen quality [7].

Unhealthy lifestyle is another unavoidable aspect of semen quality. Indeed, there is a consensus about moderate exercise as a positive factor for semen quality [8–10]. This may be because men who undertake moderate exercise have higher metabolic levels and better body shape, which are protective against obesity—a negative factor for semen quality [11]. Moderate abstinence has also been reported to be a positive factor for semen volume, total motility, and sperm concerntration [12]. Additionally, the World Health Organization (WHO) advised that patients should have 3–7 days of abstinence before collecting samples for semen analysis [13]. Furthermore, a study from Ghana showed that sitting for a long time and smoking were both related to lower sperm count [14].

Lifestyle and dietary factors have been shown to impact semen quality. Nevertheless, given the myriad of potential influences in lifestyle and diet, numerous factors remain unexamined in their relation to semen quality. Also, given that the confounding factors are vast, relevant studies are still needed to clarify which factors are affecting the human sperm quality. To investigate unknown life forms and environmental determinants of semen quality, and partially validate other studies' findings, we developed three questionnaires focusing on demographic traits, dietary patterns, and lifestyle factor exposures, tailored to the living habits of the Chinese population.

Based on our fertility cohort, more than 466 couples were enrolled between June 2020 and July 2021. We collected the couples’ essential information and completed diet as well as lifestyle factor questionnaires to verify the effects of certain lifestyles and diet factor on semen, explore more lifestyle and dietary factors related to semen quality, and guide couples in healthy pregnancy preparation and promote sexual reproductive health.

Methods

Study population

We enrolled couples from the pre-pregnancy consultation clinic of the Guangzhou Women and Children’s Medical Center in Guangzhou, China, who were invited to participate in a prospective cohort study that focused on whether lifestyle and dietary factors influenced fertility. After normalizing the female partners’ confounding factors and excluding male partners who had a medical history of systemic diseases and infertility-related diseases (including varicocele, cryptorchidism, and azoospermia), a total of 466 couples were included in this study between January 2021 and March 2023. Male partners aged 30–42 years completed three questionnaires relating to lifestyle, diet, and demographic information. All of the couples were East Asian.

Physical examination and semen analysis

Physical examinations and semen analysis were performed on the same day. The testicles and scrotum of each participant were examined to exclude patients with varicocele or other reproductive organ abnormalities.

The participants were required to abstain from sex for 3–7 days before semen analysis and physical examination. Semen samples were collected in a sterile semen container following masturbation and placed in a 37 °C incubator for 30 min to liquefy. After liquefaction, semen analysis was performed using computer-aided sperm analysis (CASA, SuiJia Software, Beijing, China) to evaluate the semen pH, volume, concentration, count, progressive motility, and total motility. All operations and reference values for semen parameters were in accordance with the latest guidelines of the WHO [13].

Our laboratory regularly conducts quality control screening to ensure the quality of semen analysis results.

Diet and lifestyle questionnaires

Based on the living habits of people in China, we designed two individual questionnaires to assess participants’ diet and lifestyle exposures. We also designed elaborate questions for factors related to low semen quality, such as smoking [15, 16], alcohol consumption [17, 18], and duration of sleep [19, 20]. We also designed additional questions based on the participants’ demographic characteristics. All of the study questionnaires used choice questions.

Ethics statement

The study was approved by the Ethics Review Committee of Guangzhou Women and Children’s Medical Center. Written informed consent was obtained from all of the participants.

Statistical analysis

The Shapiro–Wilk test was used to assess the normality of the data. None of the semen quality parameters were normal except for progressive motility (%). Normally distributed data are presented as the mean ± standard deviation, whereas other data are presented as the median (25th and 75th percentiles). Associations among semen quality parameters, diet, and lifestyle factors were evaluated. The Mann–Whitney U-test and Kruskal–Wallis H test were used for data with a non-normal distribution, and ANOVA was used for normally distributed data.

To further explore the association between semen quality and environmental and occupational factors, binomial logistic regression was applied to detect independent predictors that significantly affected semen quality, and the following confounders were adjusted for in the analysis: education [21], BMI [22] and age [23]. Statistical significance was set at P < 0.05. Statistical analyses were performed using SPSS version 26.0 (SPSS Inc., Chicago, IL, USA).

Result

Characteristics of the study population

As shown in Table 1, we enrolled 466 males of reproductive age, with a mean age of 37.53 ± 5.75 years. Every participant had a stable job and was willing to accept follow-up services. Our study included individuals with varying degrees of education.

Table 1.

General characteristics of the study population (n = 466)

Variables N (%) or mean ± SD
Age, years 36.53 ± 5.75
Nationality, n (%)
 Han nationality 456 (97.94)
 Other 10 (2.06)
Education, n (%)
 Primary school and below 13 (2.72)
 Junior high school 67 (14.36)
 High school 165 (35.40)
 College or university degree 197 (42.33)
 A master’s degree 22 (4.70)
 PhD 2 (0.50)
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Semen quality

The results showed that the median (25th, 75th percentiles) semen pH, volume, concentration, count, and total motility were 7.3 (7.2–7.5), 3.6 (2.5–5.0) mL, 63.6 (38.3–100.0) * 106/mL, 213.7 (121.8–422.0) * 106/mL, and 58.0 (42.0–73.0)%, respectively. Additionally, the mean ± SD progressive sperm motility was 36.4% ± 16.8% (Table 2).

Table 2.

Summary of semen parameters of males

Variables Statistics
Semen volume(ml), Median (25th, 75th percentiles) 3.6 (2.5–5.0)
Sperm progressive motility (%), Mean ± SD 36.0 (23.0–49.0)
Total motility (%), Median (25th, 75th percentiles) 58.0 (42.0–73.0)
Sperm concentration (106 mL−1), Median (25th, 75th percentiles) 63.6 (38.3–100.0)
Sperm count (106 mL−1), Median (25th, 75th percentiles) 213.7 (121.8–422.0)
pH value, Median (25th, 75th percentiles) 7.3 (7.2–7.5)
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Association between diet and lifestyle factors with semen quality

As mentioned above, none of the semen parameters fit a normal distribution except for progressive motility (%). The Mann–Whitney U-test and Kruskal–Wallis H test were applied for all skewness distribution semen parameter data analyses. Analysis of variance (ANOVA) was applied to analyze normally distributed semen measurements. Our results suggested that smoking (38.0% vs. 36.0%, for no and yes, respectively; t = 2.262; P = 0.049) and alcohol consumption (64.0% vs. 56.0% for no and yes, respectively; P = 0.001) decreased the progressive sperm motility, while alcohol consumption significantly decreases the total sperm motility (40.5% ± 17.8% vs. 34.7% ± 16.1% for no and yes, respectively; t = 3.396; P < 0.001). The frequency of using plastic beverage bottles as containers for cooking oil and condiments was a negative factor for sperm concentration (65.5 * 106/mL vs. 59.0 * 106/mL vs. 40.4 * 106/mL for never, occasionally, and often, respectively; P = 0.032). According to our results, taste preference was also related to total sperm motility (55.0% vs. 63.2% vs. 62.0% vs. 60.0% for partial light, partial sweet, partial salty, and partial greasy, respectively; P = 0.017). Moreover, the frequency of eating roughage was a positive factor for the total sperm count (224.6 * 106 vs. 160.8 * 106 for occasionally and basically do not; P = 0.042), while the frequency of consuming milk and dairy products was beneficial to the total sperm motility (63.0% vs. 56.0% vs. 54.5% for every day, occasionally, and basically do not, respectively; P = 0.021) and sperm concentration (66.1 * 106/mL vs. 63.7 * 106/mL vs. 41.6 * 106/mL for every day, occasionally, and basically do not, respectively; P = 0.033). Our results suggested that eating eggs constantly may contribute to increased semen volume (4.0 mL vs. 3.8 mL vs. 3.1 mL for every day, occasionally, and basically do not, respectively). Moreover, sufficient sleep was vital to total sperm motility (61.5% vs. 57.0% vs. 52.7% for do not feel sleepy, feel sleepy occasionally, and often feel sleepy; P = 0.013) and progressive sperm motility (40.2% ± 16.3% vs. 35.2% ± 16.5% vs. 35.4% ± 18.2% for do not feel sleepy, feel sleepy occasionally, and often feel sleepy; F = 3.747; P = 0.024). We also found that several factors significantly affected the semen pH value, but there was no significant change in the pH value, The difference in significance and the statistical analyses that were conducted to obtain these results are unclear. According to the WHO guidelines, a pH value > 7.2 and < 7.8 is normal for a healthy man, and none of the study participants showed abnormal pH values [13]. Therefore, further research is needed to determine whether lifestyle and dietary factors can affect semen pH (Tables 3 and 4).

Table 3.

Description of semen parameters in different dietary intake

Characteristic N Semen volume(ml) Progressive motility (%) Total motility (%) Sperm concentration(106/ml) Sperm count (106/ml) pH value
Median (25th, 75th) Effect size Median (25th, 75th) Effect size Median (25th, 75th) Effect size Median (25th, 75th) Effect size Median (25th, 75th) Effect size Median (25th, 75th) Effect size
Drinking
 Yes 135 3.6 (2.5–5.0) − 0.016 40.0 (25.0–54.0) 0.347 56.0 (40.0–71.0) 0.379 61.8 (37.8–98.7) 0.057 209.5 (121.9–389.6) 0.061 7.3 (7.2–7.5) 0.039
 No 327 3.5 (2.6–5.0) 33.5 (18.3–48.8)* 64.0 (49.0–79.0)* 68.0 (41.3–104.8) 246.0 (119.3–477.4) 7.3 (7.2–7.5)
Frequency of alcohol consumption
 Often 14 5.0 (4.2–6.1) 0.446 38.5 (29.8–54.3) − 0.021 66.5 (36.5–77.9) − 0.131 70.2 (40.2–105.5) − 0.128 355.0 (148.1–580.7) 0.155 7.4 (7.2–7.6) 0.081
 Occasionally 126 3.4 (2.6–5.0) 41.0 (25.0–55.5) 62.9 (49.0–79.0) 68.5 (40.7–110.3) 242.4 (113.9–489.7) 7.2 (7.2–7.5)
 Never 68 3.6 (2.5–6.0) 33.0 (18.5–47.5) 60.0 (40.2–74.8) 65.1 (50.7–105.5) 261.0 (159.8–472.6) 7.3 (7.2–7.5)
 Less 8 2.2 (1.9–4.5) 30.0 (17.5–45.3) 45.4 (35.5–64.1) 55.4 (27.1–77.5) 153.3 (46.2–285.4) 7.2 (7.1–7.5)
Types of regular drinking
 Beer 51 4.1 (3.2–5.6) 0.026 43.0 (25.8–57.0) 0.017 67.0 (51.0–78.0) 0.023 73.6 (41.3–96.9) 0.014 294.4 (118.6–572.4) 0.014 7.2 (7.2–7.5) 0.003
 Liquor 27 4.2 (3.2–6.0)* 41.0 (25.0–48.0) 61.2 (52.0–74.4) 72.9 (35.9–151.3) 305.7 (160.8–560.2) 7.2 (7.2–7.5)
 Wine 31 3.1 (2.2–4.0) 38.0 (21.0–53.0) 55.0 (37.0–72.0) 66.6 (42.3–128.0) 189.6 (96.1–433.1) 7.2 (7.2–7.5)
 Miscellaneous 34 3.1 (2.2–4.7) 37.0 (23.5–58.3) 67.5 (48.6–86.1) 72.6 (42.8–117.1) 221.7 (128.1–418.5) 7.3 (7.2–7.5)
 Other 50 3.6 (2.5–6.1) 34.0 (19.0–47.0) 56.9 (33.8–71.0) 63.8 (38.6–104.8) 264.2 (114.4–523.1) 7.3 (7.2–7.5)
The consumption of alcohol everyday
 Less than 100 mL per day 152 3.5 (2.5–5.3) 0.045 38.0 (24.0–52.0) 0.025 61.0 (47.8–74.0) 0.049 66.7 (41.5–108.8) 0.016 259.5 (119.3–500.8) 0.035 7.3 (7.2–7.5) 0.007
 100–250 mL per day 12 4.8 (2.6–6.0) 39.5 (24.5–54.8) 64.0 (38.8–81.6) 82.2 (49.6–128.9) 372.5 (136.5–544.0) 7.3 (7.2–7.5)
 More than 250 mL per day 10 4.8 (2.8–6.3) 45.5 (29.5–58.5) 67.0 (43.3–84.4) 50.1 (39.2–95.2) 172.7 (123.2–616.3) 7.4 (7.2–7.6)
 0 mL per day 6 3.5 (2.3–4.9) 38.5 (15.0–56.5) 53.5 (34.7–82.5) 72.6 (40.2–113.7) 253.4 (133.4–500.5) 7.2 (7.2–7.5)
 Daily water intake
  Below 500 mL 55 3.5 (2.5–4.6) 0.009 44.0 (28.3–56.8) 0.008 66.0 (39.5–79.0) 0.003 71.6 (42.6–129.0) 0.005 245.2 (132.2–522.4) 0.002 7.2 (7.2–7.5) 0.001
  500–2500 mL 360 3.6 (2.5–5.0) 38.0 (24.0–52.0) 58.0 (42.9–72.4) 62.5 (38.0–98.0) 209.1 (111.9–400.9) 7.3 (7.2–7.5)
  More than 2500 mL 47 4.2 (2.8–6.0) 35.5 (19.0–52.0) 55.0 (35.0–68.0) 62.1 (39.1–96.6) 211.2 (133.1–484.7) 7.3 (7.2–7.7)
Types of drinking water for outdoor activities
 Mineral water 219 3.6 (2.5–5.0) 0.008 42.0 (25.0–53.0) 0.002 59.0 (42.0–72.9) 0.010 70.4 (41.5–98.2) 0.008 219.3 (129.1–414.5) 0.005 7.3 (7.2–7.5) 0.001
 Pure water 77 3.5 (2.8–5.7) 40.0 (20.0–53.0) 56.0 (41.5–73.1) 55.5 (27.3–102.1) 203.8 (105.6–413.0) 7.2 (7.2–7.5)
 Tap water (boiled water) 109 3.7 (2.5–5.4) 38.5 (22.8–48.0) 56.0 (42.1–72.0) 59.0 (37.5–106.0) 222.2 (112.3–419.9) 7.3 (7.2–7.5)
 Tea 20 4.0 (2.2–6.0) 41.0 (23.0–56.0) 62.5 (41.4–74.5) 96.9 (40.8–145.0) 307.9 (142.6–578.6) 7.3 (7.2–7.5)
 Beverage 37 3.6 (2.8–4.8) 36.0 (20.5–45.0) 60.0 (40.7–75.0) 51.8 (38.2–86.1) 181.7 (130.8–424.5) 7.3 (7.2–7.5)
Beverages that often consumed
 Pure juice 37 3.5 (2.3–5.6) 0.005 44.0 (31.0–56.0) 0.001 64.1 (44.0–79.5) 0.001 65.8 (39.2–96.8) − 0.002 202.5 (130.0–517.9) 0.005 7.5 (7.2–7.6) 0.006
 Non-carbonated sugar-sweetened beverages 37 3.8 (3.1–4.3) 37.0 (26.8–42.3) 50.0 (35.5–66.7) 52.4 (36.6–97.6) 181.7 (135.5–347.5) 7.3 (7.2–7.5)
 Coffee 18 3.4 (2.6–4.2) 39.5 (29.5–55.8) 59.1 (46.6–69.7) 65.6 (27.7–102.9) 240.7 (96.1–397.5) 7.3 (7.2–7.7)
 Carbonated drinks 89 4.0 (3.0–5.6) 36.0 (22.0–54.8) 61.0 (43.5–75.5) 67.4 (33.4–93.3) 240.2 (132.7–541.3) 7.3 (7.2–7.5)
 Hardly drink 281 3.5 (2.5–5.0) 40.0 (24.0–52.0) 57.9 (41.5–72.3) 61.8 (39.9–106.7) 213.9 (115.1–415.7) 7.2 (7.2–7.5)
Number of drinks purchased in a week
 ≤ 3 bottles 407 3.5 (2.5–5.0) 0.011 39.5 (23.8–52.3) 0.012 58.0 (42.0–73.0) 0.012 63.7 (38.3–99.9) 0.003 213.9 (120.4–416.9) 0.005 7.3 (7.2–7.5) 0.009
 4–6 bottles 43 4.0 (3.2–5.0) 40.0 (24.8–54.0) 58.0 (44.0–75.0) 64.2 (39.8–114.0) 233.6 (143.5–569.9) 7.3 (7.2–7.5)
 7–9 bottles 6 3.8 (1.4–4.7) 29.5 (22.0-) 61.0 (33.4–70.5) 49.1 (25.0–79.7) 120.2 (72.0–318.7) 7.5 (7.2–7.5)
 ≥ 10 bottles 6 3.3 (2.6–4.7) 32.0 (24.5–48.0) 45.0 (29.5–67.2) 56.0 (37.9–140.5) 209.1 (122.4–418.1) 7.4 (7.2–7.7)
Use plastic beverage bottles for cooking oil, condiments, etc
 Never 301 3.5 (2.5–5.0) 0.004 40.0 (25.0–53.0) 0.004 59.0 (43.5–72.3) 0.007 65.5 (41.4–104.7)* 0.010 222.2 (129.6–421.2) 0.004 7.2 (7.2–7.5) 0.001
 Occasionally 149 3.8 (2.5–5.3) 38.5 (21.5–52.3) 56.0 (42.0–74.1) 59.0 (33.4–96.1) 203.8 (106.8–430.3) 7.3 (7.2–7.5)
 Often 12 3.2 (2.1–6.1) 34.5 (10.3–42.3) 38.7 (34.4–56.3) 40.4 (21.9–73.2) 130.7 (50.8–403.8) 7.4 (7.2–7.7)
Dietary preference
 Light 270 3.8 (2.5–5.0) 0.008 37.0 (24.0–52.3) 0.012 55.0 (39.0–71.0) 0.021 61.6 (36.6–102.0) 0.004 224.6 (116.3–403.0) 0.002 7.3 (7.2–7.5) 0.007
 Partial sweet 38 3.8 (2.5–5.5) 33.0 (22.3–51.3) 63.2 (42.0–72.4)* 63.2 (37.0–135.3) 280.9 (130.8–591.0) 7.2 (7.2–7.5)
 Partial salty 107 3.6 (2.7–5.0) 44.0 (26.0–54.0) 62.0 (47.8–77.0) 66.1 (42.6–96.6) 211.7 (129.5–429.4) 7.2 (7.2–7.5)
 Partial greasy 47 3.2 (2.4–4.6) 40.5 (28.3–53.0) 60.0 (51.0–79.0) 57.5 (35.9–88.1) 179.3 (97.9–442.4) 7.3 (7.2–7.7)
Eat pickled foods
 Never 25 4.0 (2.4–6.2) 0.060 36.0 (20.3–53.0) 0.001 61.0 (42.6–74.0) 0.001 65.1 (46.1–87.8) 0.000 249.2 (149.8–386.1) 0.006 7.2 (7.2–7.5) 0.004
 Occasionally 421 3.6 (2.5–5.0) 39.0 (24.0–52.0) 58.0 (42.0–72.3) 63.7 (38.6–99.9) 218.4 (120.5–425.1) 7.3 (7.2–7.5)
 Often 15 3.0 (2.0–4.0) 32.0 (20.0–67.0) 50.0 (21.0–87.1) 58.2 (27.2–104.0) 163.0 (90.3–332.8) 7.2 (7.2–7.5)
 Almost every day 1 – – – – – –
Eat fried food
 Never 18 4.7 (2.8–6.4) 0.009 51.0 (21.3–56.8) 0.000 67.5 (38.5–79.7) 0.001 74.1 (50.3–130.4) 0.001 328.6 (181.7–432.1) 0.003 7.2 (7.2–7.3) 0.012
 Occasionally 430 3.5 (2.5–5.0) 39.0 (24.0–52.0) 58.0 (42.0–72.2) 62.3 (37.8–99.7) 205.5 (119.3–417.5) 7.3 (7.2–7.5)
 Often 14 4.5 (2.2–6.7) 39.5 (34.0–48.3) 55.2 (50.3–70.1) 73.7 (44.2–96.9) 314.7 (121.8–487.9) 7.5 (7.2–7.7)
Daily meal plan
 Mainly meat 48 3.5 (2.7–5.9) 0.000 51.0 (21.3–56.8) 0.007 61.5 (46.9–80.9) 0.011 71.7 (44.6–118.4) 0.005 295.9 (126.0–610.3) 0.006 7.2 (7.2–7.5) 0.022
 Half meat and half vegetable 378 3.6 (2.5–5.0) 39.0 (24.0–52.0) 58.0 (42.0–72.0) 62.4 (37.9–99.0) 211.5 (120.1–397.2) 7.3 (7.2–7.5)
 Mainly vegetarian 36 4.3 (2.5–5.3) 39.5 (34.0–48.3) 54.7 (38.1–69.3) 61.0 (41.6–91.2) 221.5 (128.3–399.0) 7.2 (7.2–7.3)
Frequency of eating whole grains
 Occasionally 421 3.6 (2.5–5.0) 0.247 39.5 (23.3–52.8) 0.019 58.0 (42.0–73.0) 0.003 65.0 (39.1–101.0) 0.203 224.6 (125.9–425.1) 0.176 7.3 (7.2–7.5) 0.061
 Basically don’t 41 3.4 (2.6–5.0) 39.0 (25.0–50.0) 55.0 (40.1–73.1) 50.3 (33.3–90.1) 160.8 (97.9–361.1) 7.2 (7.2–7.5)
Frequency of eating soy products
 Every day 16 3.5 (2.2–5.0) 0.002 38.5 (17.5–56.3) 0.000 51.1 (42.2–80.7) 0.000 51.6 (23.3–103.4) 0.003 170.6 (97.6–263.9) 0.003 7.3 (7.2–7.7) 0.000
 Occasionally 430 3.6 (2.5–5.0) 39.5 (24.0–52.0) 58.6 (42.0–73.0) 62.8 (38.3–98.6) 214.4 (123.8–423.0) 7.3 (7.2–7.5)
 Basically don't 16 3.2 (2.1–5.0) 25.0 (24.0-) 52.4 (42.7–71.0) 104.2 (61.5–127.3) 366.1 (119.2–525.3) 7.2 (7.2–7.7)
Consumption of milk and dairy products
 Every day 89 3.4 (2.5–5.0) 0.003 41.0 (21.3–55.3) 0.005 63.0 (48.9–78.0)* 0.017 66.1 (45.7–103.2)* 0.009 218.4 (145.9–378.2) 0.009 7.2 (7.2–7.5) 0.008
 Occasionally 351 3.8 (2.5–5.0) 38.0 (24.0–50.3) 56.0 (41.0–71.0) 63.7 (37.9–100.8) 224.5 (119.3–433.1) 7.3 (7.2–7.5)
 Basically don’t 22 4.0 (2.1–5.1) 44.0 (20.0–59.5) 54.5 (31.8–81.5) 41.6 (27.9–67.0) 126.3 (78.5–316.0) 7.3 (7.2–7.5)
Frequency of eating eggs
 Every day 86 4.0 (3.1–5.0)* 0.014 42.0 (24.0–56.0) 0.010 56.5 (42.5–74.4) 0.007 61.5 (40.7–108.9) 0.002 189.3 (100.8–342.4) 0.005 7.2 (7.2–7.5) 0.005
 Occasionally 369 3.8 (2.7–5.0) 39.0 (24.3–52.0) 58.9 (42.0–73.0) 64.0 (38.3–99.2) 228.9 (126.2–432.1) 7.3 (7.2–7.5)
 Basically don't 7 3.1 (2.1–5.0) 20.0 (7.0–41.3) 39.0 (36.0–55.6) 42.2 (24.3–97.2) 211.2 (61.9–388.9) 7.3 (7.2–7.5)
Which part of the egg do you eat
 Whole egg 408 3.5 (2.5–5.0) 0.004 38.5 (23.8–52.0) 0.008 57.9 (42.0–72.4) 0.012 61.5 (38.2–98.4) 0.008 205.5 (119.9–402.9) 0.012 7.3 (7.2–7.5) 0.003
 Remove the yolks 52 4.1 (3.3–5.9) 40.0 (27.0–52.0) 64.2 (43.0–73.4) 81.9 (40.7–112.5) 296.8 (127.9–527.1) 7.3 (7.2–7.5)
 Basically don’t 2 4.1 (4.0-.) 57.5 (57.0-) 90.5 (88.0-.) 107.6 (84.6-.) 434.7 (346.9-.)
Frequency of eating animal food (pork, beef, lamb)
 Every day 278 3.5 (2.5–5.0) 0.006 40.0 (24.0–53.0) 0.002 58.0 (42.0–73.9) 0.001 59.9 (35.0–99.0) 0.005 201.9 (106.3–388.1) 0.009 7.2 (7.2–7.5) 0.005
 Occasionally 180 3.8 (2.5–5.3) 38.0 (22.3–52.0) 59.0 (42.5–72.0) 66.8 (41.4–106.8) 240.0 (131.6–452.5) 7.3 (7.2–7.5)
 Basically don’t 4 5.1 (2.8–8.8) 40.3 (22.4–52.0) 51.5 (46.3–56.8) 48.9 (42.5–58.2) 229.8 (142.2–420.1) 7.3 (7.2–7.5)
Vegetarian
 Yes, but there is a corresponding daily intake of egg and milk 200 3.8 (2.6–5.1) 0.003 41.0 (22.3–52.0) 0.001 56.9 (44.0–72.0) 0.007 64.1 (39.0–102.1) 0.006 217.1 (123.2–392.8) 0.004 7.3 (7.2–7.5) 0.008
 No, I like to eat meat, especially fatty meat 248 3.5 (2.5–5.0) 38.0 (25.0–54.0) 59.0 (42.0–74.8) 61.1 (38.0–97.1) 210.4 (115.3–454.7) 7.3 (7.2–7.5)
 Yes, completely vegetarian 14 3.7 (2.3–5.6) 39.5 (23.0–54.3) 54.5 (34.8–62.0) 102.9 (63.6–129.7) 375.7 (180.2–536.2) 7.2 (7.2–7.3)
Frequency of eating animal viscera (liver, kidney, stomach, intestine)
 Basically don’t 64 3.6 (2.4–5.5) 0.113 38.0 (28.5–51.0) − 0.001 57.8 (42.9–73.9) − 0.143 63.2 (43.2–100.9) 0.013 218.5 (131.1–418.1) 0.096 7.3 (7.2–7.6) 0.042
 Occasionally 398 3.6 (2.5–5.0) 40.0 (23.0–53.0) 58.0 (42.0–72.9) 63.6 (37.9–99.8) 212.8 (120.1–423.3) 7.3 (7.2–7.5)
Frequency of eating dark colored vegetables such as yellow, red and purple
 Often 184 4.0 (2.5–5.0) 0.003 40.0 (23.0–53.0) 0.001 58.0 (43.7–73.0) 0.002 66.8 (40.9–107.7) 0.012 245.6 (133.1–459.5)* 0.016 7.3 (7.2–7.5) 0.002
 Occasionally 274 3.5 (2.5–5.0) 39.0 (24.0–52.0) 58.3 (40.4–72.9) 57.8 (36.5–92.9) 186.3 (101.0–367.6) 7.3 (7.2–7.5)
 Basically don’t 4 2.6 (2.2–8.2) 39.0 (22.1–52.0) 46.0 (34.5–70.3) 105.7 (38.5–184.1) 243.8 (98.6–1546.4) 7.1 (6.9–7.8)
Open in a new tab

The value of semen volume, progressive motility, sperm concentration, sperm count, total motility, pH value represent median (25th, 75th percentiles). *P < 0.05

Table 4.

Description of semen parameters in different lifestyle

Characteristic N Semen volume(ml) Progressive motility (%) Total motility (%) Sperm concentration(106/ml) Sperm count (106/ml) pH value
Median (25th, 75th) Effect size Median (25th, 75th) Effect size Median (25th, 75th) Effect size Median (25th, 75th) Effect size Median (25th, 75th) Effect size Median (25th, 75th) Effect size
Smoking
 Yes 47 3.6 (2.5–5.0) 0.080 36.0 (22.0–48.0) − 0.271 57.0 (42.0–72.0) − 0.37 62.4 (38.3–99.8) − 0.069 213.9 (121.6–408.1) − 0.06 7.3 (7.2–7.5) 0.119
 No 415 3.9 (3.0–4.6) 37.0 (27.0–57.3)* 67.0 (49.5–79.0) 72.9 (41.3–111.7) 236.3 (131.0–484.2) 7.2 (7.2–7.5)
Losing weight or want to lose weight
 No need to lose weight 252 3.5 (2.5–5.0) 0.002 26.5 (19.3–48.0) 0.000 57.0 (42.0–72.0) 0.000 61.0 (38.0–98.1) 0.003 202.0 (118.8–388.6) 0.003 7.3 (7.2–7.5) 0.000
 Want to lose weight 168 3.8 (2.7–5.2) 38.0 (25.0–48.5) 58.8 (41.4–73.4) 66.4 (36.4–107.1) 243.9 (130.8–473.0) 7.2 (7.2–7.5)
 Losing weight 42 3.6 (2.4–5.5) 36.0 (23.0–52.0) 58.0 (42.2–72.9) 62.7 (43.5–105.9) 224.6 (140.2–473.9) 7.3 (7.2–7.6)
The way to lose weight
 Go on a diet 68 3.7 (2.7–5.0) 0.048 32.5 (20.3–46.0) 0.009 55.0 (37.5–69.1) 0.015 60.8 (34.2–87.7) 0.016 197.3 (130.8–344.9) 0.017 7.2 (7.2–7.5) 0.028
 Sports 131 3.5 (2.4–5.0) 38.0 (23.3–50.8) 58.9 (42.2–74.2) 64.2 (36.5–107.4) 228.5 (110.7–481.3) 7.3 (7.2–7.5)
 Take diet pills 2 4.4 (3.5-.) 49.5 (47.0-) 71.5 (71.0-.) 54.6 (42.4-.) 229.1 (224.5-.) 7.4 (7.2-.)
 Eat weight loss health products (weight loss tea, meal replacement powder, etc.) 8 3.6 (1.1–4.6) 37.0 (22.3–47.8) 51.5 (41.5–68.5) 56.2 (39.7–86.1) 132.7 (77.6–333.2) 7.2 (7.2–7.6)
 Weight loss device 2 4.4 (2.7-.) 35.0 (21.0-) 64.0 (48.0-.) 106.5 (100.0-.) 473.9 (270.1-.) 7.7 (7.6-.)
 Other 41 4.6 (3.0–6.5) 38.0 (22.8–44.8) 57.0 (41.5–72.1) 64.2 (35.9–110.0) 332.4 (142.8–658.7) 7.5 (7.2–7.6)
Duration of weight loss
 Less than 3 months 200 3.7 (2.5–5.3) 0.005 36.0 (22.0–49.0) 0.005 58.0 (41.0–72.4) 0.002 64.6 (39.0–97.1) 0.012 235.5 (129.7–464.4) 0.007 7.2 (7.2–7.5) 0.009
 3–6 months 24 3.5 (2.0–4.6) 42.5 (25.0–52.8) 60.0 (37.1–79.8) 62.6 (34.6–108.4) 166.3 (133.7–334.2) 7.4 (7.2–7.5)
 6–12 months 5 3.6 (2.7–7.6) 41.0 (17.0–41.5) 58.0 (37.1–66.7) 35.2 (25.6–46.1) 149.6 (80.4–289.0) 7.5 (7.0–7.8)
 More than 12 months 17 3.8 (2.4–5.6) 30.0 (25.0–51.5) 54.0 (46.6–70.5) 97.9 (32.3–139.1) 270.1 (76.8–681.2) 7.5 (7.2–7.7)
The average amount of sleep per day
 More than 8 h 49 4.0 (3.0–5.2) 0.000 36.0 (28.0–52.0) 0.002 59.0 (41.5–72.0) 0.001 65.5 (44.4–122.5) 0.014 272.5 (147.5–523.7) 0.017 7.3 (7.2–7.5) 0.002
 Less than 6 h 22 3.6 (3.0–5.3) 36.0 (26.5–48.5) 58.7 (34.8–75.0) 42.5 (24.7–82.5) 159.9 (104.7–252.9) 7.3 (7.2–7.5)
 6–8 h 391 3.5 (2.5–5.0) 36.0 (21.5–49.0) 58.0 (42.0–73.0) 63.9 (38.3–99.7) 211.7 (121.9–423.5) 7.3 (7.2–7.5)
The average time spent on phones in bed before going to bed each day
 Under half an hour 161 3.7 (2.5–5.4) 0.011 34.0 (20.5–48.0) 0.009 58.0 (40.0–73.3) 0.012 58.3 (39.9–98.5) 0.010 211.2 (121.3–389.4) 0.006 7.2 (7.2–7.5) 0.017
 Half an hour to an hour 191 3.4 (2.5–5.0) 40.5 (25.0–52.0) 59.5 (45.1–75.0) 69.7 (41.3–108.2) 224.6 (125.4–433.0) 7.3 (7.2–7.5)
 1–2 h 80 4.0 (2.6–6.0) 33.5 (21.3–46.5) 58.0 (42.5–69.0) 65.4 (36.5–99.7) 262.7 (127.3–503.3) 7.4 (7.2–7.6)
 More than 2 h 30 3.7 (3.1–4.5) 34.0 (22.0–42.0) 52.0 (35.8–69.3) 43.8 (27.7–67.6) 158.2 (87.3–329.5) 7.4 (7.2–7.7)*
Sleep time at night
 Before 22:00 39 4.6 (2.8–6.3) 0.016 42.5 (27.0–55.0) 0.018 63.0 (45.0–71.0) 0.014 81.0 (36.9–108.2) 0.021 355.2 (129.5–560.2) 0.027 7.4 (7.2–7.5) 0.003
 22:00 to 24:00 320 3.6 (2.5–5.0) 33.0 (20.3–45.8) 56.5 (41.4–72.0) 62.0 (40.6–93.7) 213.7 (121.8–400.9) 7.3 (7.2–7.5)
 After 24:00 100 3.4 (2.5–5.0) 42.0 (28.0–52.5) 59.5 (44.2–80.0) 65.2 (34.3–111.2) 209.1 (118.5–430.6) 7.2 (7.2–7.5)
 All night long 3 5.0 (3.8-.) 42.5 (28.0–55.0) 35.0 (25.0-.) 28.5 (24.4-.) 146.3 (108.1-.) 7.5 (7.3-.)
Difficulty falling asleep (can not fall asleep within 30 min)
 No 168 3.5 (2.3–5.0) 0.005 39.0 (22.0–52.0) 0.005 61.1 (44.2–75.3) 0.010 60.7 (37.8–95.7) 0.007 191.6 (112.2–367.6) 0.012 7.3 (7.2–7.5)* 0.024
 Occasionally 241 3.8 (2.7–5.0) 35.5 (24.3–47.0) 56.0 (42.0–71.0) 63.5 (38.9–103.1) 224.6 (125.2–428.1) 7.3 (7.2–7.5)
 Often 53 3.8 (2.5–5.7) 32.0 (16.0–50.0) 54.0 (35.5–75.0) 67.4 (42.3–97.4) 240.6 (160.5–444.7) 7.2 (7.0–7.3)
Going to toilet at night and interfere with sleep
 No 215 3.5 (2.5–5.0) 0.000 38.0 (23.3–48.0) 0.005 59.0 (44.0–73.0) 0.002 59.0 (36.6–93.7) 0.006 196.4 (121.6–402.8) 0.008 7.3 (7.2–7.5) 0.009
 Occasionally 209 3.6 (2.5–5.0) 32.0 (20.0–49.0) 58.0 (39.9–73.1) 65.8 (40.9–109.5) 236.6 (119.7–456.1) 7.2 (7.2–7.5)
 Often 38 3.6 (2.8–5.1) 40.0 (32.0–52.0) 55.6 (47.8–67.3) 62.0 (40.9–89.9) 255.3 (170.2–333.1) 7.3 (7.2–7.6)
Shortness of breath that interferes with sleep
 No 380 3.6 (2.5–5.0) 0.001 37.0 (24.3–49.0) 0.005 59.0 (43.9–73.2) 0.006 62.0 (38.3–98.1) 0.009 205.5 (119.6–403.4) 0.007 7.3 (7.2–7.5) 0.000
 Occasionally 79 3.5 (2.3–5.2) 34.0 (19.0–50.0) 54.0 (37.0–70.0) 67.4 (36.1–128.0) 249.2 (131.0–512.1) 7.3 (7.2–7.5)
 Often 3 4.8 (2.0-.) 36.0 (11.0-) 54.0 (34.0-.) 54.4 (46.6-.) 333.8 (93.3-.) 7.4 (7.2-.)
Coughing or snoring loudly that interferes with sleep
 No 309 3.5 (2.5–5.0) 0.008 37.0 (24.0–49.8) 0.001 58.0 (44.0–73.0) 0.000 59.5 (38.0–98.3) 0.005 201.3 (117.2–387.9) 0.008 7.2 (7.2–7.5) 0.006
 Occasionally 137 4.0 (2.6–5.9) 35.0 (21.0–51.0) 59.0 (41.5–73.0) 69.7 (40.2–115.9) 243.5 (138.3–538.6) 7.3 (7.2–7.5)
 Often 16 4.2 (3.3–5.0) 36.0 (14.0–39.0) 44.5 (26.7–58.4) 61.0 (38.6–118.0) 238.1 (124.9–477.1) 7.3 (7.2–7.5)
Feeling cold during sleeping interferes with sleep
 No 268 3.5 (2.5–5.0) 0.005 36.0 (22.0–48.0) 0.004 58.0 (41.0–73.6) 0.003 59.2 (39.0–98.7) 0.002 203.1 (120.7–388.7) 0.003 7.3 (7.2–7.5) 0.005
 Occasionally 183 4.0 (2.7–5.6) 36.5 (23.0–51.3) 58.0 (42.0–73.0) 66.6 (38.3–107.4) 237.7 (127.3–475.5) 7.3 (7.2–7.5)
 Often 11 3.5 (2.0–5.0) 43.0 (36.0-) 59.0 (53.0–71.3) 65.1 (29.3–93.3) 183.5 (86.1–403.6) 7.2 (7.2–7.7)
Feeling hot while sleeping interferes with sleep
 No 236 3.5 (2.5–5.0) 0.015 38.0 (25.0–49.0) 0.002 59.0 (42.4–73.6) 0.001 65.1 (40.9–101.0) 0.006 225.4 (126.3–425.8) 0.024 7.3 (7.2–7.5) 0.001
 Occasionally 216 4.0 (2.8–5.0) 36.0 (21.3–48.8) 57.0 (42.0–71.0) 61.1 (32.9–97.2) 206.8 (116.4–413.4) 7.3 (7.2–7.5)
 Often 10 3.8 (2.5–7.1) 37.0 (16.3–61.0) 67.6 (28.8–86.9) 80.7 (43.7–123.9) 371.0 (135.5–742.4) 7.3 (7.2–7.5)
Pain and discomfort during sleeping can interfere with sleep
 No 319 3.5 (2.5–5.0) 0.008 37.0 (25.0–49.0) 0.004 58.0 (42.9–72.0) 0.002 63.0 (38.3–97.2) 0.011 204.0 (119.3–387.8) 0.004 7.3 (7.2–7.5) 0.014
 Occasionally 134 4.1 (2.7–6.0) 36.0 (20.3–51.5) 57.5 (39.7–75.0) 64.0 (38.2–121.7) 249.2 (130.1–523.0) 7.3 (7.2–7.5)
 Often 9 4.0 (2.0–5.7) 16.0 (4.0-) 59.0 (35.2–68.9) 53.3 (39.0–84.0) 183.5 (103.3–384.0) 7.3 (7.1–7.6)
Wake up time in workday (nearly a month)
 Before 6:00 30 4.1 (3.1–6.0) 0.000 36.0 (25.5–50.0) 0.001 60.0 (35.0–73.0) 0.000 78.8 (39.1–134.0) 0.031 377.4 (151.9–564.8) 0.049 7.2 (7.2–7.5) 0.000
 6:00–8:00 380 3.6 (2.5–5.0) 36.0 (22.0–48.0) 58.0 (42.0–72.8) 60.7 (38.3–96.8) 210.4 (117.4–392.8) 7.3 (7.2–7.5)
 8:00–10:00 40 3.4 (2.4–5.0) 38.0 (22.5–51.0) 54.8 (45.2–72.8) 75.2 (37.9–136.4) 235.7 (125.6–506.4) 7.5 (7.2–7.7)
 After 10:00 12 3.4 (2.2–5.8) 49.5 (34.3–57.8) 70.8 (37.0–81.2) 61.0 (38.8–121.4) 198.8 (139.9–368.0) 7.2 (7.1–7.7)
Use of hypnotic drugs (nearly a month)
 No 452 3.6 (2.5–5.0) − 0.101 36.0 (22.0–49.0) 0.247 58.0 (42.0–72.8) ##### 63.3 (38.3–99.5) − 0.238 214.4 (121.8–418.6) − 0.56 7.3 (7.2–7.5) − 0.013
 Occasionally 10 4.0 (2.5–5.8) 38.0 (14.8–51.8) 67.0 (43.9–76.5) 103.5 (34.5–171.0) 202.6 (126.0–1038.7) 7.3 (7.0–7.5)
Feel sleepy (nearly a month)
 No 106 3.4 (2.5–5.0) 0.004 41.0 (26.5–53.0)* 0.016 61.5 (48.8–77.3)* 0.02 75.5 (43.5–120.0) 0.007 237.0 (130.3–467.9) 0.004 7.5 (7.2–7.7)* 0.02
 Occasionally 282 3.9 (2.7–5.1) 36.0 (21.8–49.0) 57.0 (40.8–72.0) 62.1 (35.8–98.4) 218.9 (114.7–420.1) 7.3 (7.2–7.5)
 Often 74 3.5 (2.1–5.0) 34.0 (20.0–47.5) 52.7 (38.3–69.1) 59.4 (40.3–91.1) 187.0 (115.7–359.1) 7.2 (7.2–7.5)
The length of a daily nap
 Don't nap 60 3.8 (2.5–5.3) 0.002 41.0 (13.5–48.0) 0.000 55.5 (39.1–71.0) 0.003 57.1 (35.4–104.8) 0.001 219.7 (122.0–399.4) 0.000 7.3 (7.2–7.7)* 0.007
 Occasionally a nap 185 3.9 (2.8–5.0) 36.0 (24.0–49.0) 57.0 (41.0–72.0) 65.1 (41.0–99.0) 222.2 (128.9–449.2) 7.3 (7.2–7.5)
 Often a nap 217 3.5 (2.5–5.1) 36.0 (22.8–49.3) 59.0 (44.0–74.3) 61.8 (38.6–100.1) 204.0 (116.6–409.0) 7.2 (7.2–7.5)
Participate in sports activities
 Never 106 4.0 (2.5–5.2) 0.004 36.5 (21.8–47.0) 0.004 54.5 (39.9–70.3) 0.002 69.1 (42.2–108.1) 0.003 255.3 (131.9–476.2) 0.010 7.3 (7.2–7.5) 0.003
 Occasionally 316 3.5 (2.5–5.0) 36.5 (22.0–50.0) 59.0 (42.0–73.9) 62.8 (36.5–99.5) 200.3 (118.3–400.9) 7.2 (7.2–7.5)
 Often 40 4.0 (2.6–5.6) 31.5 (20.8–49.0) 58.7 (49.1–73.4) 54.2 (37.4–91.3) 225.4 (114.1–400.1) 7.4 (7.2–7.5)
Open in a new tab

The value of semen volume, progressive motility, sperm concentration, sperm count, total motility, pH value represent median (25th, 75th percentiles). *P < 0.05

Independent predictors of low semen quality by binomial logistic regression analysis

Table 5 and Fig. 1 show the results of binomial logistic analysis. Abnormal semen quality parameters were defined by the guidelines of the WHO [13]. After adjusting for education state, we observed that not using plastic beverage bottles for cooking oil and condiments was a positive factor for semen volume (odds ratio [OR]: 0.12; 95% confidence interval [CI] 0.03–0.55; P = 0.006), sperm concentration (OR: 0.001; 95% CI 0.00–0.30; P = 0.012), and total sperm count (OR: 0.12; 95% CI 0.03–0.48; P = 0.003). Moreover, consuming milk and dairy products (OR: 0.11; 95% CI 0.09–0.97; P = 0.044) contributed to increased semen volume, while eggs intake may contribute to reductions in semen volume (OR: 9.41; 95% CI 1.55–57.27; P = 0.015). Finally, getting a sufficient amount of sleep was a positive factor for total sperm motility (OR: 0.47; 95% CI 0.24–0.95; P = 0.034).

Table 5.

Binomial regression model to explore the relationship between lifestyle and dietary intake and semen quality

Characteristic Semen volume Total motility Progressive motility Sperm concentration Sperm count pH value
(< 1.5 ml vs ≥ 1.5 ml) (< 40% vs ≥ 40%) (< 32% vs ≥ 32%) (< 15 × 106/ml vs ≥ 15 × 106/ml) (< 39 × 106 vs ≥ 39 × 106) (< 7.2vs ≥ 7.2)
OR(95%CI) P R2 OR(95%CI) P R2 OR(95%CI) P R2 OR(95%CI) P R2 OR(95%CI) P R2 OR(95%CI) P R2
Smoking 9.06 (0.64–128.28) 0.103 0.326 0.85 (0.28–2.60) 0.771 0.208 0.87 (0.39–1.95) 0.735 0.049 14.44 (0.13–1619.17) 0.267 0.561 4.04 (0.29–56.36) 0.300 0.313 0.69 (0.21–2.32) 0.55 0.128
Drinking 4.27 (0.45–40.73) 0.207 0.45 (0.17–1.20) 0.111 0.92 (0.41–2.05) 0.830 3.46 (0.08–155.40) 0.522 1.45 (0.22–9.49) 0.701 0.98 (0.30–3.21) 0.968
Types of regular drinking 1.36 (0.77–2.41) 0.294 0.80 (0.59–1.08) 0.146 0.97 (0.77–1.22) 0.792 1.23 (0.43–3.47) 0.698 0.93 (0.52–1.65) 0.793 1.00 (0.71–1.41) 0.993
Won’t use plastic beverage bottles as containers 0.12 (0.03–0.55) 0.006* 0.53 (0.27–1.05) 0.067 0.89 (0.51–1.56) 0.685 0.00 (0.00–0.30) 0.012* 0.12 (0.03–0.48) 0.003* 0.86 (0.37–1.99) 0.721
Dietary preference 1.43 (0.69–2.97) 0.34 1.36 (0.89–2.09) 0.155 1.02 (0.77–1.37) 0.874 0.72 (0.22–2.35) 0.587 1.32 (0.58–2.98) 0.51 0.95 (0.61–1.47) 0.819
Have the habit of eating fried food 0.04 (0.00–1.30) 0.071 1.73 (0.35–8.46) 0.5 1.16 (0.34–3.94) 0.818 12.42 (0.00–2434424.12) 0.685 0.98 (0.02–58.68) 0.994 1.55 (0.28–8.77) 0.618
Consumption of milk and dairy products 0.11 (0.02–0.83) 0.032* 0.60 (0.24–1.50) 0.274 1.08 (0.54–2.17) 0.819 0.24 (0.02–3.86) 0.315 0.32 (0.05–2.00) 0.221 2.50 (0.93–6.70) 0.069
Frequency of eating eggs 9.41 (1.55–57.27) 0.015* 1.32 (0.43–3.99) 0.626 1.11 (0.52–2.37) 0.789 12.37 (0.49–311.32) 0.126 6.70 (0.92–49.07) 0.061 1.92 (0.68–5.44) 0.219
Frequency of eating dark colour vegetables such as yellow, red and purple 2.10 (0.45–9.76) 0.342 1.35 (0.59–3.07) 0.477 0.93 (0.48–1.79) 0.822 1.88 (0.06–61.60) 0.723 2.91 (0.53–15.93) 0.219 1.72 (0.66–4.50) 0.272
The average number of hours spent on phones on bed before going to sleep each day 1.03 (0.39–2.74) 0.947 0.99 (0.62–1.58) 0.965 1.39 (0.95–2.02) 0.088 1.27 (0.24–6.75) 0.78 1.22 (0.47–3.18) 0.681 1.15 (0.67–1.97) 0.606
Difficulty falling asleep 1.83 (0.56–5.99) 0.318 0.74 (0.41–1.35) 0.329 0.83 (0.52–1.31) 0.417 0.22 (0.04–1.29) 0.093 0.36 (0.11–1.13) 0.079 0.56 (0.29–1.08) 0.082
Getting enough sleep 1.48 (0.44–5.06) 0.529 0.47 (0.24–0.95) 0.034* 0.66 (0.39–1.11) 0.116 1.26 (0.11–14.29) 0.855 1.25 (0.31–5.06) 0.753 0.76 (0.35–1.63) 0.477
The length of a daily nap 2.93 (0.89–9.62) 0.077 1.19 (0.66–2.14) 0.572 0.94 (0.59–1.48) 0.774 14.95 (0.89–250.03) 0.06 2.11 (0.55–8.15) 0.279 1.17 (0.59–2.32) 0.664
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*P < 0.05

Fig. 1.

Fig. 1

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Forest plot showing the effect of different diet and lifestyle on semen volume (A), progressive motility (B), total motility (C), sperm concentration (D), sperm count (E), pH value (F). Dots represent ORs. Error bars indicate 95% CIs

Discussion

In this cross-sectional study, we enrolled 466 couples who were attempting to conceive, and focused on the dietary and lifestyle factors that affect the fertility of male partners. Several independent factors have been found to correlate with semen quality, and some of those identified in the current study are supported by previous studies. Indeed, smoking and alcohol consumption have been associated with reduced sperm motility and are well-known factors that affect semen quality. A new systematic evaluation and meta-analysis of 5,865 men showed that smoking was associated with reduced sperm count and viability, with a more pronounced deterioration in semen quality observed in moderate and heavy smokers [24]. The effect of smoking on spermatogenesis may be explained by dual mechanisms. First, a reduction in T concentration in the testicular tissue due to impaired Leydig cell function may result in disturbed spermatogenesis, spermiogenesis, and epididymal function, which may explain the disturbances in sperm motility and morphological characteristics. Second, nicotine or catecholamines released during smoking can directly affect steroidogenesis and spermatogenesis [25]. In conclusion, smoking in men may affect their fertility by interfering with normal testicular steroid production and spermatogenesis due to stress-induced overactivity of the adrenal medulla and adrenal cortex. Furthermore, the association between chronic alcohol consumption and poor semen quality is mainly due to the development of oxidative stress and its genotoxic effects on hormonal regulation and DNA integrity, which in turn affect the health of the offspring [17]. Sleep quality is another factor that has been widely reported to be associated with semen quality, and has also been found to affect sperm motility [26]. Indeed, Chen et al. assessed the relationship between sleep quality and semen parameters in 842 healthy men, and found that poor sleep quality was associated with impaired semen parameters [27]. Moreover, in 2013, Jensen et al. reported an inverse relationship between sleep disturbance and sperm concentration, total count, and percentage of normal morphology in 953 healthy Danish men. These findings are consistent with our results [28]. Although living habits, such as diet preference and using plastic beverage bottles as containers for cooking oil, have been seldom reported by other researchers, we found close associations between them and semen quality. Moreover, improper spice containers can cause harmful substances in the plastic to leach into the spice, which can be absorbed by the body and lead to a reduction in semen quality, and even birth defects in offspring [29]. Indeed, a recent study by Xia indicated that microplastics (MP) have reproductive toxicity and transgenerational effects in aquatic species, with potential adverse effects on mammalian reproduction [30]. Besides, Jin et al. demonstrated that long-term exposure to PS-MPs at concentrations equivalent to environmental contamination resulted in impaired testicular tissue structure, reduced sperm quality, and decreased testosterone levels, leading to male reproductive toxicity in mice. Among them, the PS-MPs-induced decrease in testosterone levels was achieved through inhibition of the LH-mediated LHR/cAMP/PKA/StAR pathway [31]. Our results also suggested that food choice is vital to semen quality, with foods such as eggs and roughage being associated with changes in semen quality. However, these food preference factors and their association with semen quality have been rarely reported. We also noticed that the consumption of milk wasbeneficial to the total sperm motility and concentration; however, the classification of dairy products was unclear owing to the small sample size. The literature on the relationship between dairy products is inconclusive. Although some studies have suggested that dairy products may be a risk factor for poor semen parameters, others do not support this theory. In a case–control study comparing the dietary habits of men with oligozoospermia and normospermia, case subjects consumed higher amounts of whole milk products (yogurt, whole milk, cheese, and semi-fermented milk) and lower amounts of skim milk than control subjects [32]. Moreover, in an American cohort study, intake of low-fat dairy products was associated with higher sperm concentration and better motility [33]. Furthermore, in a study of young men engaged in physical labor, the intake of full-fat dairy products, especially cheese, was adversely associated with normal sperm morphological characteristics and progressive sperm motility [34]. However, in another study of men in a Dutch hospital, dairy intake was not associated with semen quality [35]. While most studies support the benefits of low-fat versus the harmful effects of full-fat dairy products, more studies, especially randomized trials, are needed to draw well-supported conclusions.

Semen quality is easily influenced by one’s own behavior and the environment [36, 37]. However, many factors cannot be studied and discussed simultaneously. By sorting the factors by group, we have the opportunity to analyze the effects of interrelated factors on semen quality and, in the future, it will be possible to combine different groups of factors before applying medical data, artificial intelligence, and machine learning to construct a mathematical model to evaluate male fertility. The results of this intuitive evaluation will assist doctors in pre-pregnancy clinics with selecting an appropriate solution for each case, and provide patients with a set of guidelines to follow to reduce their exposure to risk factors and consequently, restore their fertility. Avoiding exposure to high-risk factors before pregnancy will save couples preparing for pregnancy from expensive medical costs and provide a scientific basis for precise fertility interventions.

Originally, assisted reproductive technology (ART) was intended to help couples with organic diseases become pregnant. Since its first application, more than 300,000 infants have been born in China as a result of ART [38]. However, ART is frequently believed to be abused, with excessive medical treatments [39–41]. It has also been reported that ART may lead to higher risks of gestational diseases, hypertension, and other pregnancy-related diseases. Even after controlling for known risk factors, such as maternal age, weight, and poor lifestyle habits, ART is associated with a higher risk of adverse perinatal outcomes, such as placenta previa, premature abruption, antepartum hemorrhage, low amniotic fluid, cesarean delivery, preterm delivery, very low birth weight, low birth weight, and increased risk of perinatal mortality [42–45]. Therefore, if couples can successfully become pregnant naturally by avoiding exposure to risk factors, infertility treatments may be reserved for couples with the greatest need, preventing excessive application of ART and avoiding unnecessary ART expenses.

To achieve our expectations, we must recruit more couples with infertility concerns and expand the sample size for a more reliable result. In the meantime, to improve the accuracy of our results, we plan to modify our questionnaires according to the reflections of our patients.

Conclusions

Overall, our results demonstrated that drinking, smoking, using plastic bottles for condiment containers, dietary preference, sleep, and consumption of milk, egg, and roughage are related to semen quality. However, as our cohort was comparatively small, we plan to increase our sample size to verify our results. Additionally, the specific mechanisms by which risk factors, such as high fat, red meat, processed meat, refined grains, candy and sweet drinks, unhealthy eating patterns, and long periods of sedentary work condition, affect semen quality are still unknown and require further research [46].

Acknowledgements

We would like to thank the Clinical Biological Resource Bank of Guangzhou Women and Children’s Medical Center for curating clinical data.

Abbreviations

CASA

Computer-Aided Sperm Analysis

CI

Confidence Interval

OR

Odds Ratio

SD

Standard Deviation

WHO

World Health Organization

Author contributions

HM, JK and ZZ contributed equally to this study. Conceptualization: LZ, HM. Formal analysis: JK, JL. Funding acquisition: LZ, YQ. Investigation: LZ, HM. Methodology: ML. Project administration: LZ, HM. Resources: LZ. Software: JK, ZZ. Supervision: LZ. Validation: HM. Visualization: SC. Writing—original draft: HM. Writing—review & editing: YQ, FJ.

Funding

This study was funded by the Guangzhou Medical and Health Technology Projects (China, 20191A011021, 20191A011033 and 202206010100), the Guangdong Natural Science Foundation (China, 2019A1515012061), Guangzhou Science and Technology Program Key Projects (China,201904010486), and the Guangzhou Health Commission (China,20211A011034).

Availability of data and materials

All data generated or analyzed during this study are included in this published article.

Declarations

Ethics approval and consent to participate

The present study protocol was reviewed and approved by the Ethics Review Committee of the Guangzhou Women and Children's Medical Center (2016102416). All procedures followed were in accordance with the ethical standards of the responsible committee on human experimentation (institutional and national) and with the Helsinki Declaration of 1975, as revised in 2000. Informed consent was obtained from all patients for being included in the study.

Consent for publication

All authors have read and approved the final manuscript.

Competing interests

Hanran Mai, Junyi Ke, Zilin Zheng, Li Miaomiao, Jieyi Luo, Yanxia Qu, Fan Jiang, Simian Cai, Liandong Zuo declare that they have no conflict of interest.

Footnotes

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Hanran Mai, Junyi Ke and Zilin Zheng contributed equally to this study.

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