Abstract
Background:
Age, smoking, sleep duration, sleep quality, and obesity are risk factors that can affect the amount of sperm concentration, morphology, and motility. The aim of this study is to assess the lifestyle effects: of age, smoking, sleep duration, sleep quality, and obesity on the amount of concentration, morphology, and motility of sperm.
Materials and Methods:
The study utilized an analytical observational approach with a cross-sectional design. The study subjects comprised 70 male partners of infertile couples admitted to the Sekar Fertility Clinic at the Dr. Moewardi General Hospital between March and August 2022. The study assessed variables including age, body mass index (BMI), smoking status, sleep duration, sleep quality, sperm concentration, sperm morphology, and sperm motility. Furthermore, the data were analyzed using univariate, bivariate, and multivariate methods with SPSS 25 software.
Results:
The research findings demonstrate that obesity is significantly associated with abnormal sperm concentration [odds ratio (OR)=40.07, confidence interval (CI)=3.90-411.67, P=0.002]. Furthermore, moderate or heavy smoking is significantly associated with abnormal sperm concentration (OR=17.45, CI=1.83-166.15, P=0.013) and sleep quality with severe disorders (OR=5.73, CI=1.12-29.21, P=0.036). Moreover, obesity is significantly associated with abnormal sperm motility (OR=12.97, CI=2.66-63.15, P=0.002), while moderate or heavy smoking (OR=5.89, CI=1.23- 28.20, P=0.026) and poor sleep duration (OR=6.21, CI=1.43-26.92, P=0.015) also exhibit significant associations with abnormal sperm motility. However, no significant findings were observed regarding sperm morphology.
Conclusion:
The findings of this study indicate that obesity, moderate or heavy smoking, and sleep quality have statistically significant effects on sperm concentration, while obesity, moderate or heavy smoking, and sleep duration have statistically significant effects on sperm motility. However, no statistically significant influence was observed on sperm morphology. Further research with larger sample sizes and more diverse populations is needed to validate these findings and explore other potential factors that may impact male fertility.
Keywords: Morphology, Motility, Obesity, Smoking, Sperm
Introduction
Infertility is a prevalent reproductive health issue affecting approximately 15% of couples worldwide. The male factor accounts for 20 to 70% of infertility cases, with male infertility rates ranging from 2.5 to 12% of the male population globally (1, 2). Lifestyle factors, such as smoking, alcohol consumption, drug use, obesity, sleep disorders, psychological stress, diet, and caffeine consumption, have been demonstrated to influence sperm quality (3, 4). Smoking, for example, is responsible for approximately 15% of infertility cases worldwide, with men contributing 50-60% due to the high risk of male germ cell damage leading to mutations in spermatogenesis (5, 6). Long-term smoking can increase leukocyte levels, resulting in the production of reactive oxygen species (ROS) during sperm development. ROS can harm sperm DNA and the plasma membranes of spermatozoa that are susceptible to damage from high levels of polyunsaturated fatty acids (7).
Although research on the relationship between sleep quality and infertility is limited, some studies have shown a correlation between sleep duration and quality and sperm quality in men. Poor sleep quality, difficulty falling asleep, and short sleep duration have been linked to decreased sperm volume and motility (8). Liu et al. (9) examined 981 healthy men and found that short sleep duration was associated with reduced sperm count and motility. Similarly, Chen et al. (10) reported that healthy men who slept for 7.5-8.5 hours per day had higher sperm count and total sperm motility. Conversely, men with poor sleep quality experienced an 8.0% decrease in total sperm count, total motility, and progressive motility, as determined by a Pittsburgh Sleep Quality Index (PSQI) screening (7). In addition, obesity has been identified as a detrimental factor in male fertility, affecting 400 million individuals worldwide (11). Studies have reported that obesity can alter semen parameters, resulting in decreased testicular volume, impaired spermatogenesis, and decreased semen quality (12, 13). Although several studies have explored this issue (14, 15), the link between obesity and male infertility still requires further investigation.
Age is another crucial risk factor, as men over 30 typically have lower sperm volume, motility, and concentration (16). As individuals age, they experience increased oxidative stress in the body, resulting in elevated lipid peroxidation and the formation of ROS in mitochondria (17). Nevertheless, the specific impacts of age, obesity, smoking, sleep duration, and sleep quality on sperm concentration, morphology, and motility remain uncertain. This study examined how age, obesity, smoking, sleep duration, and sleep quality affect sperm concentration, morphology, and motility.
Materials and Methods
Study design
The study employed an analytical observational approach with a cross-sectional design. The study included 70 male partners of infertile couples admitted to the Sekar Fertility Clinic at the Dr. Moewardi General Hospital between March and August 2022. The sample comprised patients who underwent male infertility diagnosis at the Sekar Fertility Clinic, Dr. Moewardi. According to WHO 2010, sperm parameters are normal if sperm concentration ≥15×106/mL, total sperm count ≥39×106, progressive motility ≥32%, and morphology ≥4%. Normozoospermia [total sperm count or concentration of spermatozoa, and percentages of progressively motile (PR) and morphology normal spermatozoa, equal to or above the lower reference limits], oligozoospermia (total sperm count or concentration of spermatozoa below the lower reference limit), asthenozoospermia (percentage of PR spermatozoa below the lower reference limit), teratozoospermia (percentage of morphology normal spermatozoa below the lower reference limit) (18). The inclusion criteria were as follows: i. Male patients whose sperm was evaluated by a team of fertility doctors, ii. Abstinence from intercourse for 2-7 days, iii. Ejaculated semen volume of at least 1.5 ml, and iv. Normozoospermia, oligozoospermia, asthenozoospermia, or teratozoospermia. The exclusion criteria were: i. Inability to provide sperm on the day of collection, ii. Varicocele, iii. Endocrine disorders, such as hypogonadism, and iv. Alcoholism (defined as alcohol consumption up to two drinks per day) (19), mental stress, poor diet, and coffee consumption (more than 800mg per day) (20). The sampling method utilized purposive sampling techniques with inclusion and exclusion criteria to obtain representative subjects. To calculate the number of samples required, the following formula was used:
Where:
p: Estimated proportion (prevalence) of the dependent variable in the population
q: 1-p
d: Delta, the desired margin of error on both sides of the proportion (10%)
Z1-α/2: Statistic Z (where the desired confidence interval is 95%)
n: Number of samples
We observed research subjects comprising 53 young adults (aged 25-37 years) and 17 middle adults (aged 37-49 years). Smoking among the research subjects was categorized as mild addiction in 48 participants, moderate addiction in 21 participants, and severe addiction in only 1. Body Mass Index (BMI) among the research subjects was classified as non-obese (≥18.5-29.9) in 49 participants and obese (≥30) in 21 participants. Sleep duration was assessed, with 34 participants experiencing a moderate disorder (6-7 hours), 8 participants having a good sleep duration (7-9 hours), and 28 participants having poor sleep duration (<6 hours). Sleep quality was divided into moderate disorder in 26 participants, severe disorder in 20 participants, and mild disorder in 24 participants. The sperm analysis resulted in the classification of participants into different groups: asthenozoospermia (2 participants), normozoospermic (28 participants), teratozoospermia (15 participants), astheno-teratozoospermia (6 participants), oligoasthenozoospermia (2 participants), oligoteratozoospermia (5 participants), and oligo-asthenoteratozoospermia (12 participants). Research variable: The independent variables were age, smoking, sleep duration, and sleep quality, while the dependent variable was sperm total concentration, morphology, and motility.
Chemicals and media
The sperm concentration was measured using an Ortho- Toluidine reagent (Sigma-Aldrich, USA). For sperm morphology staining, peripheral Morfologi Darah Tepi (MDT) (Segara Husada Mandiri Jakarta, Indonesia) was used. The observation was carried out using a light microscope (Olympus CX 33, Japan) with immersion oil from Olympus Corp., Japan.
Variable operational definition
Age is classified as young adults aged 25 to 36 and middle adults aged 37 to 49 (21).
Obesity is a condition characterized by an abnormal increase in body fat (22). Patients with a BMI <30 kg/m2 were classified as non-obese (including normal weight and overweight groups), while those with a BMI ≥30 kg/m2 were classified as obese.
The heaviness of the smoking index (HVI) (19) was used to measure smoking. Patients with a score of 0-2 were classified as belonging to the light cigarette group, while those with scores of 3-6 were classified as belonging to the moderate/heavy smoking group.
Based on the American Academy of Sleeping Medicine and Research Society (AASM) in 2015 (23), patients with a sleep duration of fewer than 6 hours were classified as having poor sleep duration, while those with a sleep duration of 6 hours or more were classified as having good or moderate sleep duration.
Sleep quality was measured using the PSQI (24). Patients with a PSQI score of 14 or lower were classified as having a mild or moderate sleep disorder, while those with a PSQI score of 15 or higher were classified as having a severe sleep disorder.
The sperm count is considered low if it is less than 15 million per milliliter or the total sperm count is less than 39 million per ejaculate (25). The measurement was done using the WHO criteria examination method (2010). In this study, concentrations of less than 15 million per milliliter were categorized as abnormal, while concentrations of more than 15 million per milliliter were classified as normal. The concentration was calculated after undergoing liquefaction within 30 minutes after ejaculation, with dilution 20 times using the Ortho-Toluidine reagent (Sigma-Aldrich, USA).
Abnormal sperm morphology was defined as less than 4%, while normal morphology was defined as 4% or higher. Normal sperm morphology has an ovalshaped head and an acrosome covering 40-70% of the head area. The sperm has a neck, midpiece, and no tail abnormalities or cytoplasmic droplets exceeding 50% of the sperm head size. The reagent for sperm morphological staining used was Morfologi Darah Tepi (MDT) dye (Segara Husada Mandiri Jakarta, Indonesia). Observations were made using a light microscope (Olympus CX 33, Jepang) at a magnification of 1000 times with immersion oil (Olympus Corp., Jepang). At least 200 spermatozoa were observed in each replica. The number of abnormal and normal spermatozoa was calculated and compared with the total number of spermatozoa observed in units of a percent (%) (18).
Sperm motility was observed after sperm liquefaction occurred within 30 minutes of ejaculation. The sperm was stirred until homogeneous, and 10 μl of cement was dripped onto a glass object, flattened, and covered with a cover glass with a chamber height of 20 μm. The sample was allowed to stand for 60 seconds before observation. The observation was done using a light microscope (Olympus CX 33, Jepang) with 200 or 400 magnification. At least 200 spermatozoa were counted per replicate, and observations were calculated and categorized in units of a percent (%) (18): Progressive motility (PR)- active, straight or large circular movement; nonprogressive motility (NP) - all movements except progressive, rotating in place, moving in place, or tail movement only; immotility (IM) - no movement. Motility was considered normal if the progressive motility (PR) was greater than 32% of the total sperm motility (PR+NP) was greater than 40% (25). In this study, motility was considered normal if the value was greater than 40%, while values less than 40% were classified as abnormal.
Research preparation stage
The preparation stage included obtaining ethical clearance and research letters, preparing tools and materials, ensuring that sperm samples met the inclusion and exclusion criteria, preparing sperm preparation tools, and assessing total sperm concentration and sperm motility.
Sperm sampling
The stages of sperm sampling are as follows (26): Firstly, sperm samples are collected in a designated room close to the laboratory to minimize temperature stress. Secondly, a sperm sample is taken after a minimum of 2 days and a maximum of 7 days of abstinence from sexual activity. Patients should be given clear instructions both verbally and in writing, and a report book should be filled out with patient information, such as their name, date of birth, medical record number, period of abstinence, date and time of specimen collection, the integrity of the specimen, presence or absence of problems with collection, and the time interval between removing the sample and the start of sperm analysis. Thirdly, patients are instructed to masturbate and collect the semen sample obtained during ejaculation into a clean container with a wide opening made of glass or plastic. Fourthly, the sample container is stored between 20°C and 37°C for 10 minutes to avoid sudden temperature changes and then labeled with the patient's name, chart number, and the date and time the sample was collected. Finally, the sample container is placed in a 37°C incubator and allowed to liquefy for 5 minutes. If the initial sample is incomplete, it is recommended to provide a second sample after abstaining from sexual activity for 2-7 days.
The sperm preparation method uses the swim-up method by adding 1 ml of semen liquid to a 15 ml sterile centrifugation tube and then adding 1.2 ml of supplement media. After that, the tube is placed at an angle of 45° and incubated at 37°C for about 45 minutes. After that, the tube is returned to its original position, then taken 1 ml of the top of the media (which contains sperm with the highest motility) and mixed with 1.5-2.0 ml of supplement media. Next, centrifugation at 300-400 g power is carried out for 5 minutes, and the supernatant is removed. Resuspend the sperm pellet in a 0.5 ml SpermRinse (Vitrolife, Sweden) to evaluate sperm concentration, total motility, and progressive motility (18).
Statistical analysis
The collected data was analyzed using bivariate analysis Chi-square test to identify significant correlations. Multivariate analysis was conducted using logistic regression analysis if any significant correlations were found. The extent of risk from age, smoking, sleep duration, and sleep quality to concentration, morphology, and motility was determined using odds ratio (OR) testing. The statistical analysis was performed using SPSS 25 edition software (SPSS Inc., Chicago, IL, USA). The significance level was set at P<0.05, corresponding to a 95% confidence level.
Ethical clearance
Ethical clearance was approved by the Health Research Ethics Committee of Dr. Moewardi General Hospital (number 324/III/HREC/2022). All participants agreed to inform consent.
Results
Table 1 describes the subject’s characteristics and includes information about several variables observed in the subject, including the number of subjects and their percentages.
Table 2 above shows a relationship between middle adults and abnormal sperm concentration (OR=4.29, CI=1.34-13.71, P=0.015), obesity and abnormal sperm concentration (OR=6.83, CI=2.16-21.56, P=0.001), moderate or heavy smoking and abnormal sperm concentration (OR=6.00, CI=1.93-18.60, P=0.001), poor sleep duration and abnormal sperm concentration (OR=3.19, CI=1.09-9.33, P=0.031), sleep quality with severe disorder and abnormal sperm concentration (OR=7.87, CI=2.44-25.40, P≤0.001).
Table 1.
Characteristics subjects
|
| ||
|---|---|---|
| Variable | n (%) | |
|
| ||
| Age (Y) | ||
| Middle adult (37-49) | 17 (24.3) | |
| Young adult (25-36) | 53 (75.7) | |
| BMI (kg/m2) | ||
| Obesity (≥30) | 21 (30) | |
| Non obesity (≥18.5-29.9) | 49 (70) | |
| Smoking | ||
| Moderate or heavy | 22 (31.4) | |
| Light | 48 (68.6) | |
| Sleep duration (hours) | ||
| Poor (<6) | 28 (40) | |
| Good (7-9) or moderate (6-7) | 42 (60) | |
| Sleep quality | ||
| Severe disorder | 20 (28.6) | |
| Mild or moderate disorder | 50 (71.4) | |
| Sperm analysis | ||
| Astenozoospermia | 2 (2.86) | |
| Normozoospermia | 28 (40.00) | |
| Teratozoospermia | 15 (21.43) | |
| Asteno-teratozoospermia | 6 (8.57) | |
| Oligo-astenozoospermia | 2 (2.86) | |
| Oligo-teratozoospermia | 5 (7.14) | |
| Oligo-asteno-Teratozoospermia | 12 (17.14) | |
|
| ||
BMI; Body mass index.
Table 2.
Bivariate analysis examining the association between risk factors such as age, obesity, smoking, sleep duration, and sleep quality on sperm concentration
|
| ||||||
|---|---|---|---|---|---|---|
| Variable | Concentration | OR | (95% CI) | P value | ||
| Abnormal | Normal | |||||
|
| ||||||
| Ageb (Y) | ||||||
| Middle adult | 9 (45.0) | 8 (16.0) | 4.29 | (1.34-13.71) | 0.015* | |
| Young adult | 11 (55.0) | 42 (84.0) | ||||
| BMIa (kg/m2) | ||||||
| Obesity | 12 (60.0) | 9 (18.0) | 6.83 | (2.16-21.56) | 0.001* | |
| Non obesity | 8 (40.0) | 41 (82.0) | ||||
| Smokinga | ||||||
| Moderate or heavy | 12 (60.0) | 10 (20.0) | 6.00 | (1.93-18.60) | 0.001* | |
| Light | 8 (40.0) | 40 (80.0) | ||||
| Sleep durationa | ||||||
| Poor | 12 (60.0) | 16 (32.0) | 3.19 | (1.09-9.33) | 0.031* | |
| Good or moderate | 8 (40.0) | 34 (68.0) | ||||
| Sleep qualitya | ||||||
| Severe disorder | 12 (60.0) | 8 (16.0) | 7.87 | (2.44-25.40) | <0.001* | |
| Mild or moderate disorder | 8 (40.0) | 42 (84.0) | ||||
|
| ||||||
Data are presented as n (%). a; Chi-Square test (is the correct statistical test for categorical data presented in a cross-tabulation), b; Fisher Exact test (is an adjustment for Chisquare when there is a cell with an expected value less than 5 in the cross-tabulation), *; Significant P<0.05, BMI; Body mass index, CI; Confidence interval, and OR; Odds ratio.
Table 3 above demonstrates a correlation between moderate or heavy smoking and abnormal sperm morphology (OR=3.15, CI=1.05-9.43, P=0.036). It also indicates a correlation between poor sleep duration and abnormal sperm morphology (OR=3.33, CI=1.20-9.27, P=0.019). Furthermore, there is an association between sleep quality with severe disorder and abnormal sperm morphology (OR=3.52, CI=1.11- 11.17, P=0.028). However, no relationship was found between age and obesity with abnormal sperm morphology, with P>0.05.
Table 3.
Bivariate analysis examining the association between risk factors such as age, obesity, smoking, sleep duration, and sleep quality on sperm morphology
|
| ||||||
|---|---|---|---|---|---|---|
| Variable | Morphology | OR | 95% CI | P value | ||
| Abnormal | Normal | |||||
|
| ||||||
| Ageb (Y) | ||||||
| Middle adult | 11 (28.9) | 6 (18.8) | 1.76 | (0.57-5.47) | 0.322 | |
| Young adult | 27 (71.1) | 26 (81.3) | ||||
| BMIa (Kg/m2) | ||||||
| Obesity | 12 (31.6) | 9 (28.1) | 1.18 | (0.42-3.30) | 0.753 | |
| Non obesity | 26 (68.4) | 23 (71.9) | ||||
| Smokinga | ||||||
| Moderate or heavy | 16 (42.1) | 6 (18.8) | 3.15 | (1.05-9.43) | 0.036* | |
| Light | 22 (57.9) | 26 (81.3) | ||||
| Sleep durationa | ||||||
| Poor | 20 (52.6) | 8 (25.0) | 3.33 | (1.20-9.27) | 0.019* | |
| Good or moderate | 18 (47.4) | 24 (75.0) | ||||
| Sleep qualitya | ||||||
| Severe disorder | 15 (39.5) | 5 (15.6) | 3.522 | (1.11-11.17) | 0.028* | |
| Mild or moderate disorder | 23 (60.5) | 27 (84.4) | ||||
|
| ||||||
Data are presented as n (%). a; Chi-Square test (is the correct statistical test for categorical data presented in a cross-tabulation), b; Fisher Exact test (is an adjustment for Chisquare when there is a cell with an expected value less than 5 in the cross-tabulation), *; Significant P<0.05, BMI; Body mass index, CI; Confidence interval, and OR; Odds ratio.
Table 4 above shows a relationship between middle adults and abnormal sperm motility (OR=3.46, CI=1.11- 10.82, P=0.028), obesity and abnormal sperm motility (OR=5.20, CI=1.71-15.76, P=0.002), moderate or heavy smoking and abnormal sperm motility (OR=4.56, CI=1.53-13.57, P=0.005), poor sleep duration and sperm motility (OR=5.77, CI=1.92-17.33, P=0.001) sleep quality with severe disorder and abnormal sperm motility (OR= 4.33, CI=1.43-13.10, P=0.007).
Based on Table 5, the results of the multivariate analysis showed a Negelkerke R2 of 0.614, indicating that 61.4% of the variance in sperm concentration data can be explained by independent variables (age, smoking, sleep duration, sleep quality, and obesity). The remaining 38.6% is influenced by other variables outside the model. Obesity is the dominant factor significantly affecting abnormal sperm concentration (OR=40.07, CI=3.90-411.67, P=0.002). Smoking is also a dominant factor significantly affecting sperm concentration (OR=17.45, CI=1.83-166.15, P=0.013). Sleep quality with severe disorders is another dominant factor significantly affecting sperm concentration (OR=5.73, CI=1.12- 29.21, P=0.036). However, middle adults and poor sleep duration are not dominant factors affecting abnormal sperm concentration with P>0.05.
Table 4.
Bivariate analysis examining the association between risk factors such as age, obesity, smoking, sleep duration, and sleep quality on sperm motility
|
| ||||||
|---|---|---|---|---|---|---|
| Variable | Motility | OR | 95% CI | P value | ||
| Abnormal | Normal | |||||
|
| ||||||
| Ageb (Y) | ||||||
| Middle adult | 9 (40.9) | 8 (16.7) | 3.46 | (1.11-10.82) | 0.028* | |
| Young adult | 13 (59.1) | 40 (83.3) | ||||
| BMIa (kg/m2) | ||||||
| Obesity | 12 (54.5) | 9 (18.8) | 5.20 | (1.71-15.76) | 0.002* | |
| Non obesity | 10 (45.5) | 39 (81.3) | ||||
| Smokinga | ||||||
| Moderate or heavy | 12 (54.5) | 10 (20.8) | 4.56 | (1.53-13.57) | 0.005* | |
| Light | 10 (45.5) | 38 (79.2) | ||||
| Sleep durationa | ||||||
| Poor | 15 (68.2) | 13 (27.1) | 5.77 | (1.92-17.33) | 0.001* | |
| Good or moderate | 7 (31.8) | 35 (72.9) | ||||
| Sleep qualitya | ||||||
| Severe disorder | 11 (50.0) | 9 (18.8) | 4.33 | (1.43-13.10) | 0.007* | |
| Mild or moderate disorder | 11 (50.0) | 39 (81.3) | ||||
|
| ||||||
Data are presented as n (%). a; Chi-Square test (is the correct statistical test for categorical data presented in a cross-tabulation), b; Fisher Exact test (is an adjustment for Chisquare when there is a cell with an expected value less than 5 in the cross-tabulation), *; Significant P<0.05, BMI; Body mass index, CI; Confidence interval, and OR; Odds ratio.
Additionally, Negelkerke’s R2 was 0.117, indicating that 11.7% of the variance in sperm morphological data can be explained by the independent variables (age, smoking, sleep duration, sleep quality, and obesity), while the remaining 88.3% is influenced by other variables outside the model. Middle adults, obesity, moderate or heavy smoking, poor sleep duration, and sleep quality with severe disorders are not dominant factors influencing abnormal sperm morphology with P>0.05.
Furthermore, Negelkerke’s R2 was 0.511, which means that 51.1% of sperm motility data variance can be explained by independent variables (age, smoking, sleep duration, sleep quality, and obesity), while the remaining 48.9% is influenced by other variables outside the model. Obesity is the dominant factor significantly affecting abnormal sperm motility (OR=12.97, CI=2.66-63.15, P=0.002). Moderate or heavy smoking was the dominant factor significantly affecting abnormal sperm motility (OR=5.89, CI=1.23- 28.20, P=0.026). Poor sleep duration was the dominant factor significantly affecting sperm motility (OR= 6.21, CI=1.43-26.92, P=0.015). Meanwhile, middle adults and sleep quality with severe disorders are not dominant factors affecting abnormal sperm motility (P>0.05).
Table 5.
Multivariate analysis investigating the associations between risk factors of age, obesity, smoking, sleep duration, and sleep quality on sperm concentration, morphology, and motility
|
| |||||||||
|---|---|---|---|---|---|---|---|---|---|
| Risk factor | Sperm concentration | Sperm morphology | Sperm motility | ||||||
| OR | 95% CI | P value | OR | 95% CI | P value | OR | 95% CI | P value | |
|
| |||||||||
| Age (Y, middle adults) | 3.44 | (0.66-17.83) | 0.142 | 1.11 | (0.30- 4.00) | 0.877 | 2.54 | (0.56-11.54) | 0.227 |
| Obesity | 40.07 | (3.90-411.67) | 0.002* | 1.16 | (0.38- 3.56) | 0.796 | 12.97 | (2.66-63.15) | 0.002* |
| Smoking (moderate or heavy) | 17.45 | (1.83-166.15) | 0.013* | 2.39 | (0.70- 8.17) | 0.163 | 5.89 | (1.23-28.20) | 0.026* |
| Sleep duration (poor) | 1.76 | (0.35-8.75) | 0.486 | 2.28 | (0.72- 7.18) | 0.160 | 6.21 | (1.43-26.92) | 0.015* |
| Sleep quality (severe disorder) | 5.73 | (1.12-29.21) | 0.036* | 1.93 | (0.51- 7.27) | 0.331 | 1.40 | (0.33-5.98) | 0.651 |
|
| |||||||||
Multiple logistic regression analysis. *; Significant P<0.05, CI; Confidence interval, and OR; Odds ratio.
Discussion
This study states that age does not significantly affect sperm concentration, motility, and morphology. However, some studies indicate a correlation between aging and structural and functional changes in the sexual organs and endocrine system, indirectly impacting sperm parameters and fertility (17, 27). Other studies also suggest that aging may lead to a decline in semen parameters (16, 28). The aging process involves unavoidable physiological changes in the body, and some of these changes affect reproductive organs, including a decrease in reproductive capacity (17).
The findings of this study demonstrate that obesity significantly influences sperm concentration and motility. This finding is consistent with the study by Ramaraju et al. (29), which reported a decrease in sperm volume, count, concentration, and motility in obese men. A sedentary lifestyle and excessive calorie intake in obese men can disrupt their reproductive health in various ways. The effects of obesity and metabolic syndrome (MetS) involve complex pathophysiology. Chronic inflammation responses triggered by subclinical TH1 lymphocytes are present in obesity and MetS and can be found in various body systems such as visceral adipose tissue, brain (hypothalamus), muscles, blood vessels, heart, pancreas, testes, epididymis, prostate, and sperm. These inflammatory cytokines can interfere with the hypothalamic-pituitary-testicular axis, steroidogenesis (hypogonadotropic hypogonadism), and obesity also leads to other endocrine changes in humans, such as alterations in insulin production and regulation, sex-hormone-bindingglobulin (SHBG), leptin, and inhibin B (30). These hormonal changes can affect the testosterone-to-estrogen ratio and impact spermatogenesis. Hyperinsulinemia due to insulin resistance caused by obesity can lower SHBG production and promote the production of more biologically active estrogen through negative feedback on the hypothalamic-pituitary-gonadal (HPG) axis. SHBG serves as a homeostatic mechanism to maintain adequate testosterone levels. Obese men tend to have low serum testosterone levels (31).
The results of this study state that moderate or heavy smoking significantly affects sperm concentration and motility. This finding aligns with previous research by Joo et al. (32), which stated that heavy smoking (>20 cigarettes/day) is associated with a decrease in sperm count. Oxidative smoking-related stress is believed to affect acrosomal response and sperm performance. This oxidative stress can affect two mechanisms essential for fertilization and is believed to be the leading cause of DNA damage in sperm (33). Some hypothesized mechanisms include disturbances in spermatogenesis, ultrastructural abnormalities, apoptosis, and abnormal epigenetic modifications. However, some smokers still have normal sperm quality. Their sperm may show abnormal DNA methylation and non-coding RNA expression. Therefore, smoking can affect fertility by influencing epigenetic modifications in sperm chromatin damage without involving the volume, count, and motility of sperm as mediators (34). A study conducted by Kulaksiz et al. (35) indicated that quitting smoking has a positive impact on sperm concentration, semen volume, and total sperm count. Based on these findings, infertile patients are advised to quit smoking before undergoing treatment.
Furthermore, the results of this study stated that poor sleep duration (<6 hours) significantly impacted sperm motility, while severe sleep quality disturbances significantly affected sperm concentration. This finding aligns with previous research by Chen et al. (36), which stated that both short and long sleep durations and poor sleep quality are associated with poor sperm quality. A study by Liu et al. (9) also showed that short and long sleep durations and late-night sleep could reduce sperm count and motility through increased antisperm antibodies (ASA). Additionally, research by Du et al. (37) also shows a relationship between poor sleep and sperm quality. Although the mechanisms linking sleep duration, sleep quality, and sperm quality are still under investigation, it is suspected to be related to an increased risk of obesity, decreased testosterone levels, and enzymes associated with sperm apoptosis. Poor sleep quality is also linked to decreased serum testosterone levels and can damage Sertoli cells in the seminiferous tubules (36). In men with sleep disorders, there is an increased secretion of corticosteroids that can inhibit stimulation of the HPG axis. The HPG axis plays a crucial role in testosterone production, a hormone involved in sperm formation (38).
A limitation of this study is that the minimum sample size is disproportionate to the number of variables. Additionally, completing the questionnaire is subjective, which could result in biased implications of the study's results and depend on the respondent's or research subject's memory. Using the WHO 2010 guidelines for sperm analysis is another limitation of this study, as the latest WHO 2021 guidelines are not utilized.
Conclusion
The findings of this study indicate that obesity, moderate or heavy smoking, and sleep quality have statistically significant effects on sperm concentration, while obesity, moderate or heavy smoking, and sleep duration have statistically significant effects on sperm motility. However, no statistically significant influence was observed on sperm morphology. Further research with larger sample sizes and more diverse populations is needed to validate these findings and explore other potential factors that may impact male fertility.
Acknowledgments
We would like to thank Universitas Sebelas Maret for the financial support of Non Anggaran Pendapatan dan Belanja Negara (APBN) number: 254/UN27.22/ PT.01.03/2022.
Authors’ Contributions
U.R.B., L.O.P., M.P.; Conceptualization. U.R.B., L.O.P., E.M., T.P.; Data curation. U.R.B., A.A.R., M.P., A.L.; Formal analysis. U.R.B., E.M., T.P., A.A.R.; Funding acquisition. A.L., L.O.P., T.P., C.H.; Investigation. M.P., T.P., A.L., A.A.R.; Methodology. L.O.P., U.R.B., M.P.; Project administration. E.M., U.R.B., T.P., A.L.; Resources. E.M., A.A.R.; Software. T.P., A.L., C.H.; Supervision. U.R.B., M.P., A.L.; Validation. E.M., M.P., L.O.P.; Visualization. B.M., I.N.; Statistical analysis. U.R.B.; Writing-original draft. U.R.B., M.P., B.M., I.N.; Writing-review and Editing. All authors read and approved the final version of the manuscript.
References
- 1.Harlev A, Agarwal A, Gunes SO, Shetty A, du Plessis SS. Smoking and male infertility: an evidence-based review. World J Mens Health. 2015;33(3):143–160. doi: 10.5534/wjmh.2015.33.3.143. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Nouri M, Abdollahi N, Leilami K, Shirani M. The relationship between plant-based diet index and semen parameters of men with infertility: a cross-sectional study. Int J Fertil Steril. 2022;16(4):310–319. doi: 10.22074/IJFS.2021.538675.1184. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Durairajanayagam D. Lifestyle causes of male infertility. Arab J Urol. 2018;16(1):10–20. doi: 10.1016/j.aju.2017.12.004. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Pacey AA. Environmental and lifestyle factors associated with sperm DNA damage. Hum Fertil (Camb) 2010;13(4):189–193. doi: 10.3109/14647273.2010.531883. [DOI] [PubMed] [Google Scholar]
- 5.Parameswari R, Sridharan TB. Cigarette smoking and its toxicological overview on human male fertility—a prospective review. Toxin Rev. 2019;40(3):145–161. [Google Scholar]
- 6.Sharma R, Harlev A, Agarwal A, Esteves SC. Cigarette smoking and semen quality: a new meta-analysis examining the effect of the 2010 world health organization laboratory methods for the examination of human semen. Eur Urol. 2016;70(4):635–645. doi: 10.1016/j.eururo.2016.04.010. [DOI] [PubMed] [Google Scholar]
- 7.Evans EPP, Scholten JTM, Mzyk A, Reyes-San-Martin C, Llumbet AE, Hamoh T, et al. Male subfertility and oxidative stress. Redox Biol. 2021;46:102071–102071. doi: 10.1016/j.redox.2021.102071. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Viganò P, Chiaffarino F, Bonzi V, Salonia A, Ricci E, Papaleo E, et al. Sleep disturbances and semen quality in an Italian cross sectional study. Basic Clin Androl. 2017;27:16–16. doi: 10.1186/s12610-017-0060-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Liu MM, Liu L, Chen L, Yin XJ, Liu H, Zhang YH, et al. Sleep deprivation and late bedtime impair sperm health through increasing antisperm antibody production: a prospective study of 981 healthy men. Med Sci Monit. 2017;23:1842–1848. doi: 10.12659/MSM.900101. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Chen Q, Yang H, Zhou N, Sun L, Bao H, Tan L, et al. Inverse U-shaped association between sleep duration and semen quality: longitudinal observational study (MARHCS) in Chongqing, China. Sleep. 2016;39(1):79–86. doi: 10.5665/sleep.5322. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Chaudhuri GR, Das A, Kesh SB, Bhattacharya K, Dutta S, Sengupta P, et al. Obesity and male infertility: multifaceted reproductive disruption. Middle East Fertil Soc J. 2022;27(8):1–12. [Google Scholar]
- 12.MacDonald AA, Herbison GP, Showell M, Farquhar CM. The impact of body mass index on semen parameters and reproductive hormones in human males: a systematic review with meta-analysis. Hum Reprod Update. 2009;16(3):293–311. doi: 10.1093/humupd/dmp047. [DOI] [PubMed] [Google Scholar]
- 13.Katib A. Mechanisms linking obesity to male infertility. Cent European J Urol. 2015;68(1):79–85. doi: 10.5173/ceju.2015.01.435. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 14.Liu Y, Ding Z. Obesity, a serious etiologic factor for male subfertility in modern society. Reproduction. 2017;154(4):R123–R131. doi: 10.1530/REP-17-0161. [DOI] [PubMed] [Google Scholar]
- 15.Palmer NO, Bakos HW, Fullston T, Lane M. Impact of obesity on male fertility, sperm function and molecular composition. Spermatogenesis. 2012;2(4):253–263. doi: 10.4161/spmg.21362. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Pino V, Sanz A, Valdés N, Crosby J, Mackenna A. The effects of aging on semen parameters and sperm DNA fragmentation. JBRA Assist Reprod. 2020;24(1):82–86. doi: 10.5935/1518-0557.20190058. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Gunes S, Hekim GN, Arslan MA, Asci R. Effects of aging on the male reproductive system. J Assist Reprod Genet. 2016;33(4):441–454. doi: 10.1007/s10815-016-0663-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.World Health Organization. WHO laboratory manual for the examination and processing of human semen. 5th ed. Geneva: World Health Organization; 2010. pp. 1–271. [Google Scholar]
- 19.Van Heertum K, Rossi B. Alcohol and fertility: how much is too much? Fertil Res Pract. 2017;3:10–10. doi: 10.1186/s40738-017-0037-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Jensen TK, Swan SH, Skakkebæk NE, Rasmussen S, Jørgensen N. Caffeine intake and semen quality in a population of 2,554 young danish men. Am J Epidemiol. 2010;171(8):883–891. doi: 10.1093/aje/kwq007. [DOI] [PubMed] [Google Scholar]
- 21.Dyussenbayev A. Age periods of human life. Adv Soc Sci Res J. 2017;4(6):258–263. [Google Scholar]
- 22.Casadei K, Kiel J. StatPearls. Treasure Island (FL): StatPearls Publishing; 2024. Anthropometric Measurement. Available from: http://wwwncbinlmnihgov/books/NBK537315/ (26 Sep 2022) [Google Scholar]
- 23.Consensus Conference Panel, Watson NF, Badr MS, Belenky G, Bliwise DL, Buxton OM, et al. Joint consensus statement of the american academy of sleep medicine and sleep research society on the recommended amount of sleep for a healthy adult: methodology and discussion. Sleep. 2015;38(8):1161–1183. doi: 10.5665/sleep.4886. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Buysse DJ, III CFR, Monk TH, Berman SR, Kupfer DJ. The pittsburgh sleep quality index: a new instrument for psychiatric practice and research. Psychiatry Res. 1989;28(2):193–213. doi: 10.1016/0165-1781(89)90047-4. [DOI] [PubMed] [Google Scholar]
- 25.Cao XW, Lin K, Li CY, Yuan CW. A review of WHO laboratory manual for the examination and processing of human semen (5th edition) Zhonghua Nan Ke Xue. 2011;17(12):1059–1063. [PubMed] [Google Scholar]
- 26.Boitrelle F, Shah R, Saleh R, Henkel R, Kandil H, Chung E, et al. The sixth edition of the WHO manual for human semen analysis: a critical review and SWOT analysis. Life (Basel) 2021;11(12):1368–1368. doi: 10.3390/life11121368. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Johnson SL, Dunleavy J, Gemmell NJ, Nakagawa S. Consistent age-dependent declines in human semen quality: a systematic review and meta-analysis. Ageing Res Rev. 2015;19:22–33. doi: 10.1016/j.arr.2014.10.007. [DOI] [PubMed] [Google Scholar]
- 28.Oliveira JBA, Petersen CG, Mauri AL, Vagnini LD, Baruff RLR, Franco JG. The effects of age on sperm quality: an evaluation of 1,500 semen samples. JBRA Assist Reprod. 2014;18(2):34–41. doi: 10.5935/1518-0557.20140002. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 29.Ramaraju GA, Teppala S, Prathigudupu K, Kalagara M, Thota S, Kota M, et al. Association between obesity and sperm quality. Andrologia. 2018;50(3):1–12. doi: 10.1111/and.12888. [DOI] [PubMed] [Google Scholar]
- 30.Leisegang K, Henkel R, Agarwal A. Obesity and metabolic syndrome associated with systemic inflammation and the impact on the male reproductive system. Am J Reprod Immunol. 2019;82(5):e13178–e13178. doi: 10.1111/aji.13178. [DOI] [PubMed] [Google Scholar]
- 31.Davidson LM, Millar K, Jones C, Fatum M, Coward K. Deleterious effects of obesity upon the hormonal and molecular mechanisms controlling spermatogenesis and male fertility. Hum Fertil (Camb) 2015;18(3):184–193. doi: 10.3109/14647273.2015.1070438. [DOI] [PubMed] [Google Scholar]
- 32.Joo KJ, Kwon YW, Myung SC, Kim TH. The effects of smoking and alcohol intake on sperm quality: Light and transmission electron microscopy findings. J Int Med Res. 2012;40(6):2327–2335. doi: 10.1177/030006051204000631. [DOI] [PubMed] [Google Scholar]
- 33.Corona G, Sansone A, Pallotti F, Ferlin A, Pivonello R, Isidori AM, et al. People smoke for nicotine, but lose sexual and reproductive health for tar: a narrative review on the effect of cigarette smoking on male sexuality and reproduction. J Endocrinol Invest. 2020;43(10):1391–1408. doi: 10.1007/s40618-020-01257-x. [DOI] [PubMed] [Google Scholar]
- 34.Tang Q, Pan F, Wu X, Nichols CE, Wang X, Xia Y, et al. Semen quality and cigarette smoking in a cohort of healthy fertile men. Environ Epidemiol. 2019;3(4):e055–e055. doi: 10.1097/EE9.0000000000000055. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 35.Kulaksiz D, Toprak T, Tokat E, Yilmaz M, Ramazanoglu MA, Garayev A, et al. Sperm concentration and semen volume increase after smoking cessation in infertile men. Int J Impot Res. 2022;34(6):614–619. doi: 10.1038/s41443-022-00605-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 36.Chen HG, Sun B, Chen YJ, Chavarro JE, Hu SH, Xiong CL, et al. Sleep duration and quality in relation to semen quality in healthy men screened as potential sperm donors. Environ Int. 2020;135:105368–105368. doi: 10.1016/j.envint.2019.105368. [DOI] [PubMed] [Google Scholar]
- 37.Du CQ, Yang YY, Chen J, Feng L, Lin WQ. Association between sleep quality and semen parameters and reproductive hormones: a cross-sectional study in Zhejiang, China. Nat Sci Sleep. 2020;12:11–18. doi: 10.2147/NSS.S235136. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 38.Lateef OM, Akintubosun MO. Sleep and reproductive health. J Circadian Rhythms. 2020;18(1):1–1. doi: 10.5334/jcr.190. [DOI] [PMC free article] [PubMed] [Google Scholar]