Abstract
Extensive studies have identified potential adverse effects on semen quality of obesity, based on body mass index, but the association between body fat distribution, a more relevant indicator for obesity, and semen quality remains less clear. We conducted a longitudinal study of 4304 sperm donors from the Guangdong Provincial Human Sperm Bank (Guangzhou, China) during 2017–2021. A body composition analyzer was used to measure total and local body fat percentage for each participant. Generalized estimating equations were employed to assess the association between body fat percentage and sperm count, motility, and morphology. We estimated that each 10% increase in total body fat percentage (estimated change [95% confidence interval, 95% CI]) was significantly associated with a 0.18 × 106 (0.09 × 106–0.27 × 106) ml and 12.21 × 106 (4.52 × 106–19.91 × 106) reduction in semen volume and total sperm count, respectively. Categorical analyses and exposure-response curves showed that the association of body fat distribution with semen volume and total sperm count was stronger at higher body fat percentages. In addition, the association still held among normal weight and overweight participants. We observed similar associations for upper limb, trunk, and lower limb body fact distributions. In conclusion, we found that a higher body fat distribution was significantly associated with lower semen quality (especially semen volume) even in men with a normal weight. These findings provide useful clues in exploring body fat as a risk factor for semen quality decline and add to evidence for improving semen quality for those who are expected to conceive.
Keywords: body fat distribution, obesity, semen quality, sperm donation volunteer
INTRODUCTION
Over the past few decades, there has been a trend in declining human semen quality, prompting widespread concerns about male reproductive health. A meta-analysis concluded that total sperm count in Western countries had decreased by over 50% from 1973 to 2011,1 in line with numerous studies documenting a sustained decline in semen quality.2,3 According to recent statistics, approximately 186 million people worldwide suffer from infertility, with around 15% of couples of reproductive age being affected.4,5 An estimated 30%–50% of cases of low fertility or infertility in couples worldwide are attributable to male factors.6,7,8 Clinical infertility is diagnosed when a couple fails to conceive after 12 months of unprotected intercourse, with semen quality serving as a crucial indicator of male reproductive health.9 Impairment of male reproductive health has emerged as a significant global public health concern, making it crucial to investigate the underlying modifiable risk factors.
Obesity has been linked with a decline in semen quality, as indicated by previous studies in extensive animal and epidemiological studies.10,11,12,13,14 However, most epidemiological studies have explored the association between obesity and semen quality using body mass index (BMI) as a measure of obesity.15,16 As BMI does not directly measure body fat, it may introduce bias in assessing the association of obesity with semen quality.17 Body fat distribution refers to the distribution of fat in different parts of the human body and is typically linked to various adverse health outcomes and reproductive system health.18,19 Body fat percentage (BFP) is a crucial indicator for assessing body fat distribution and identifying obesity, which is considered more accurate than BMI.17,20,21 Previous studies have reported that from 80% to 90% of the body fat is subcutaneous fat tissue, which is primarily distributed in the abdomen, upper back, buttocks, and thigh areas.22
To date, only a limited number of studies have investigated the association between body fat distribution and semen quality, and the results are inconclusive. For example, in studies of the general male population, there was no significant correlation between BFP and sperm concentration, total and progressive sperm motility, or normal sperm morphology.23 On the contrary, another study reported that a higher BFP was associated with lower semen volume and total sperm motility.24 In addition, most studies did not explore the dose–response relationship between BFP and semen quality. The association of localized fat percentages including upper limb, trunk, and lower limb with male semen quality is yet to be investigated. Therefore, we embarked on an extensive longitudinal investigation with Chinese volunteer sperm donors to evaluate systematically the dose–response relationship between the distribution of body fat and the quality of semen.
PARTICIPANTS AND METHODS
Study participants
We included 4673 volunteer sperm donors who were 20–45 years old and intended to donate spermatozoa at the Guangdong Provincial Human Sperm Bank (Guangzhou, China) between July 27, 2017, and December 31, 2021. No eligible donors had any reproductive system, serious genetic or infectious diseases, and their height exceeded 168 cm. Volunteers who had not resided at their current address for at least 6 months (n = 2), did not provide essential personal information (n = 9), lacked analytical data on body composition (n = 109), or were unable to provide a usable semen sample (n = 249) were excluded. We ultimately included 4304 participants and obtained 16 507 semen samples in the analysis. Our study received approval from the Ethics Committee of the School of Public Health, Sun Yat-sen University (Guangzhou, China; Approval No. 2019-071), with a waiver of informed consent. The data were routinely collected by clinical practitioners and used anonymously by the investigators.
BFP measurement
BFP was measured once for each participant after enrollment in this study as baseline data. Body measurements for each participant were conducted between 8:00 a.m. and 1:00 p.m. The multifrequency bioelectrical impedance analysis (InBody770; InBody Co., Ltd., Seoul, South Korea) was used to measure body fat indicators, including the lean and fat mass of the left arm, right arm, trunk, left leg, and right leg. Total BFP (%) and local fat percentage (%) were used to reflect body fat distribution. Local fat percentages including the upper limb, trunk, and lower limb were calculated from the following formulae. Total BFP (%) = total body mass/total weight × 100%. Upper limb fat percentage (%) = (fat mass of the left arm + fat mass of the right arm)/upper limb weight × 100%. Trunk fat percentage (%) = fat mass of the trunk/trunk weight × 100%. Lower limb fat percentage (%) = (fat mass of the left leg + fat mass of the right leg)/lower limb weight × 100%. In the above equation, “total body mass” refers to the total weight of an individual’s body, which includes all components such as water, fat, bone, muscle, and other tissues.
Covariates
We obtained demographic and clinical information on the study participants from the electronic medical records in the sperm bank, including age, race, education level, height, BMI, semen collection date, season, and abstinence period, which were routinely collected by sperm bank staff. Weight was measured with the InBody 770 body composition analyzer. From previous studies,15,25,26,27,28 the covariates included age, race (Han Chinese or other), education level (undergraduate or higher, college, or high school or less), BMI, semen collection season, and abstinence period (<4 days, 4–5 days, or ≥6 days). BMI (kg m−2) was calculated and categorized according to the World Health Organization (WHO) standards as normal weight (18.5–24.9 kg m−2), underweight (<18.5 kg m−2), overweight (25.0–29.9 kg m−2), and obese (≥30.0 kg m−2). Semen collection season was categorized as spring (March to May), summer (June to August), autumn (September to November), and winter (December to February of the following year).
Semen analysis
During the screening phase for sperm donation, each participant provided 1 to 3 semen samples for analysis. Participants who met the sperm donation requirements proceeded to the formal sperm donation process (donating 3 to 15 times). Each participant underwent a standardized semen analysis, according to the 5th edition of WHO Laboratory Manual for the Examination and Processing of Human Semen.29 Participants were directed to ejaculate into a sterile plastic specimen container within a private room designated for semen collection. The semen samples were then placed in a 37°C incubator and left to liquefy for 30 min. Qualified technicians examined the semen samples, which were processed in a single laboratory by standardized protocols. The volume of the semen was assessed from its weight. After loading semen sample into a blood cell counting chamber, sperm concentration, nonprogressive motility, and progressive motility were examined in a phase contrast microscope (Carl Zeiss Axio Lab.A1; Carl Zeiss, Oberkochen, Germany). Semen quality parameters were measured in duplicate, and the average values were used to reduce measurement errors. Study outcomes included semen volume (ml), sperm concentration (×106 ml−1), total sperm count (×106), progressive motility (%), total motility (%), and normal forms (%). Total sperm count and motility were obtained by multiplying semen volume by sperm concentration and summing nonprogressive motility and progressive motility, respectively. We strictly implemented quality control measures during the data collection, organization, and analysis processes.29,30
Statistical analyses
We utilized frequency and composition percentages to describe body fat distribution characteristics. As most participants had multiple semen analysis results, we employed the generalized estimating equation (GEE) with a random effect to explore the association of body fat distribution with semen quality. GEE was proposed by Liang and Zeger in 1986, which is an extension of the generalized linear model and has been widely used for statistical analysis of longitudinal data and other types of repeated measurements.31 The GEE analysis is an iterative process, where the regression coefficients are estimated using the quasi-likelihood method. The model is formulated as follows:
where Yit represents the semen quality parameter of individual i at time point t, which is a continuous variable. β0 represents the intercept. Xitj represents the covariate j of individual i at time point t. β1j represents the regression coefficient of covariate j. J represents the number of covariates. CORRit represents the working correlation structure. εit represents the error of individual i at time point t.
We assumed that the correlation between any two semen quality analysis results of the study participants was equal. The working correlation structure, CORRit was set as an exchangeable correlation structure. The model results are presented as the changes in semen quality indicators, along with their corresponding 95% confidence intervals (CIs), for each 10% increase in total BFP or local fat percentage. We conducted a categorical analysis by dividing the total BFP and local fat percentage into four levels based on quartiles: Q1, Q2, and Q3, with Q4 being the highest. Taking Q1 as the reference, we calculated the changes in semen quality parameters and their 95% CI for total BFP and local fat percentage in the Q2, Q3, and Q4 categories. By including the median of total BFP and local fat percentage in each quartile as a continuous variable, we tested the presence of a linear trend on the model. Furthermore, we included the total BFP and local fat percentage as natural cubic splines (with 3 degrees of freedom) in the model to depict the dose–response relationship. We conducted likelihood ratio tests (LRT) to examine if the dose–response relationships departed from linearity.
We stratified the study participants into categories on the basis of the WHO classification criteria for BMI (normal weight, underweight, overweight, and obese) and constructed models from generalized estimating equations for each stratum. The categorical analysis was to explore if the stratification variable (BMI) had an effect modification on the associations between total BFP, local fat percentage, and various indicators of semen quality. The R software (version 4.3.1; The R Foundation, Vienna, Austria) was used for all data analyses. A two-sided P < 0.05 was considered statistically significant.
RESULTS
We included 4304 participants, with a mean age of 25.7 (standard deviation [s.d.]: 5.5) years, who provided 16 507 semen samples for analysis. The general characteristics of the participants showed similar distribution patterns across total BFP quartiles (Table 1). The mean total BFP was 19.8% (s.d.: 7.0%; Supplementary Table 1). The distribution of upper limb, trunk, and lower limb fat percentage was similar to total BFP (Supplementary Table 1). According to the results of Spearman’s correlation analysis, there was a high correlation between different body fat percentages (Supplementary Table 2). The mean semen volume, sperm concentration, total sperm count, total motility, progressive motility, and normal forms of the participants were 3.9 (s.d.: 1.6) ml, 75.2 × 106 (s.d.: 32.6 × 106) ml−1, 283.6 × 106 (s.d.: 146.3 × 106), 59.1% (s.d.: 11.0%), 56.7% (s.d.: 11.1%), and 13.7% (s.d.: 6.8%), respectively (Table 2). The distribution of semen quality parameters was similar across total BFP quartiles.
Table 1.
Characteristics of the study population by body fat distribution in Guangdong Province Human Sperm Bank, China (2017–2021)
| Variable | Total | Quartile of BFPa | |||
|---|---|---|---|---|---|
|
| |||||
| Q1 | Q2 | Q3 | Q4 | ||
| Semen analysis (n) | 16 507 | 4191 | 4096 | 4097 | 4123 |
| Participant (n) | 4304 | 1103 | 1041 | 1077 | 1083 |
| Age (year)b, n (%) | |||||
| ≤25 | 2520 (58.6) | 844 (76.5) | 649 (62.3) | 545 (50.6) | 482 (44.5) |
| >25 | 1784 (41.4) | 259 (23.5) | 392 (37.7) | 532 (49.4) | 601 (55.5) |
| Race, n (%) | |||||
| Han Chinese | 4166 (96.8) | 1080 (97.9) | 1005 (96.5) | 1043 (96.8) | 1038 (95.8) |
| Other | 138 (3.2) | 23 (2.1) | 36 (3.5) | 34 (3.2) | 45 (4.2) |
| Education, n (%) | |||||
| High school or less | 509 (11.8) | 147 (13.3) | 103 (9.9) | 119 (11.0) | 140 (12.9) |
| College | 1583 (36.8) | 422 (38.3) | 355 (34.1) | 370 (34.4) | 436 (40.3) |
| Undergraduate or higher | 2212 (51.4) | 534 (48.4) | 583 (56.0) | 588 (54.6) | 507 (46.8) |
| BMI (kg m−2)c, n (%) | |||||
| <18.5 | 437 (10.2) | 363 (32.9) | 63 (6.1) | 11 (1.0) | 0 (0) |
| 18.5–24.9 | 3029 (70.4) | 734 (66.5) | 951 (91.4) | 910 (84.5) | 434 (40.1) |
| 25–30 | 748 (17.4) | 6 (0.5) | 27 (2.6) | 155 (14.4) | 560 (51.7) |
| ≥30 | 90 (2.1) | 0 (0) | 0 (0) | 1 (0.1) | 89 (8.2) |
| Season, n (%) | |||||
| Spring | 1042 (24.2) | 307 (27.8) | 239 (23.0) | 254 (23.6) | 242 (22.3) |
| Summer | 1432 (33.3) | 382 (34.6) | 352 (33.8) | 321 (29.8) | 377 (34.8) |
| Autumn | 1217 (28.3) | 280 (25.4) | 315 (30.3) | 333 (30.9) | 289 (26.7) |
| Winter | 613 (14.2) | 134 (12.1) | 135 (13.0) | 169 (15.7) | 175 (16.2) |
| Abstinence (day), n (%) | |||||
| <4 | 896 (20.8) | 235 (21.3) | 203 (19.5) | 227 (21.1) | 231 (21.3) |
| 4–5 | 1983 (46.1) | 499 (45.2) | 465 (44.7) | 502 (46.6) | 517 (47.7) |
| ≥6 | 1425 (33.1) | 369 (33.5) | 373 (35.8) | 348 (32.3) | 335 (30.9) |
aBody fat distribution was categorized using the quartile: Q1 (2.9%–14.7%), Q2 (14.8%–19.2%), Q3 (19.3%–24.3%), and Q4 (24.4%–50.5%); bAge was categorized from mean of age. cBMI was categorized from the WHO criteria: underweight (<18.5 kg m−2), normal weight (18.5–24.9 kg m−2), overweight (25.0–29.9 kg m−2), and obesity (≥30.0 kg m−2). WHO: World Health Organization; BFP: body fat percentage; BMI: body mass index
Supplementary Table 1.
Distribution of body fat among the study subjects in Guangdong Province Human Sperm Bank (Guangzhou, China; 2017–2021)
| Variable | Mean (s.d.) | Media (IQR) | Q1 | Q2 | Q3 | Q4 |
|---|---|---|---|---|---|---|
| Total BFP (%) | 19.8 (7.0) | 19.2 (9.6) | 2.9–14.6 | 14.7–19.2 | 19.3–24.3 | 24.4–50.5 |
| Upper limb fat (%) | 21.0 (9.5) | 19.8 (12.9) | 2.3–14.1 | 14.2–19.7 | 19.8–27.0 | 27.1–69.2 |
| Trunk fat (%) | 21.2 (8.5) | 21.0 (12.2) | 0.4–14.9 | 15.0–20.9 | 21.0–27.1 | 27.2–48.4 |
| Lower limb fat (%) | 19.6 (5.8) | 19.0 (8.0) | 4.3–15.3 | 15.4–18.9 | 19.0–23.3 | 23.4–45.4 |
IQR: interquartile range; s.d.: standard deviation; BFP: body fat percentage; Q1: 0–25th; Q2: 25th–50th; Q3: 50th–75th; Q4: 75th–100th
Supplementary Table 2.
Spearman correlation among different body fat index
| Body fat index | Total body fat (%) | Upper limb fat (%) | Trunk fat (%) | Lower fat limb (%) |
|---|---|---|---|---|
| Total body fat (%) | / | 0.97 | 0.99 | 0.99 |
| Upper limb fat (%) | 0.97 | / | 0.95 | 0.98 |
| Trunk fat (%) | 0.99 | 0.95 | / | 0.98 |
| Lower fat limb (%) | 0.99 | 0.98 | 0.98 | / |
All correlation coefficients were significant. /: no value
Table 2.
Distribution of semen parameters among the participants in Guangdong Province Human Sperm Bank, China (2017–2021)
| Semen quality parameter | Value, mean (s.d.) | Quartile of BFP | |||
|---|---|---|---|---|---|
|
| |||||
| Q1 | Q2 | Q3 | Q4 | ||
| Semen volume (ml) | 4.0 (1.7) | 4.1 (1.7) | 4.1 (1.7) | 4.0 (1.7) | 3.8 (1.7) |
| Sperm concentration (×106 ml−1) | 66.5 (34.6) | 67.0 (34.3) | 65.4 (33.3) | 66.3 (35.2) | 67.1 (35.4) |
| Total sperm count (×106) | 257.4 (161.5) | 264.0 (162.2) | 251.6 (159.2) | 258.6 (163.2) | 245.5 (161.0) |
| Total sperm motility (%) | 56.1 (12.35) | 55.9 (11.9) | 55.9 (12.8) | 55.9 (12.7) | 56.7 (12.0) |
| Progressive sperm motility (%) | 53.7 (12.4) | 53.5 (11.9) | 53.5 (12.9) | 53.5 (12.7) | 54.3 (12.1) |
| Normal forms (%) | 12.7 (6.7) | 12.4 (6.5) | 12.7 (6.7) | 12.8 (6.7) | 12.8 (6.9) |
BFP: body fat percentage; s.d.: standard deviation
In dose–response analyses, we estimated that each 10% increase of total BFP was significantly associated with a 0.18 (95% CI: 0.09–0.27) ml and 12.21 × 106 (95% CI: 4.52 × 106–19.91 × 106) reduction in semen volume and total sperm count, respectively (Table 3). The categorical analyses showed a significantly decreasing trend of semen volume and total sperm count across BFP quartiles (both P for linear trend <0.05), though the associations were only significant for the Q4 of BFP. The results showed that there was a nonlinear correlation between BFP and semen quality parameter. The dose–response curve gave a similar trend that the semen volume and total sperm count remained unchanged at lower BFP but decreased significantly at higher BFP (Figure 1). The dose–response analyses for upper limb, trunk, and lower limb fat percentage yielded very similar results (Table 3 and Supplementary Figure 1 (312.2KB, tif) ). No significant associations for sperm motility or morphology were observed.
Table 3.
Estimated change (95% CI) of semen quality parameters associated with body fat percentage
| Semen quality parameter | Per 10% increase | Quartile of BFP, estimated change (95% CI) | ||||
|---|---|---|---|---|---|---|
|
| ||||||
| Q1 | Q2 | Q3 | Q4 | Plinear trend | ||
| Total BFP | ||||||
| Semen volume (ml) | -0.18 (-0.27, -0.09)* | Reference | -0.02 (-0.11, 0.16) | -0.10 (-0.24, 0.04) | -0.24 (-0.41, -0.07)* | 0.002 |
| Sperm concentration (×106 ml-1) | 0.28 (-1.75, 1.80) | Reference | -1.08 (-3.69, 1.53) | -0.84 (-3.54, 1.87) | -0.83 (-4.08, 2.41) | 0.66 |
| Total sperm count (×106) | -12.21 (-19.91, -4.52)* | Reference | -1.42 (-12.98, 10.14) | -7.98 (-19.99, 4.03) | -20.06 (-34.46, -5.67)* | 0.004 |
| Total sperm motility (%) | 0.24 (-0.35, 0.82) | Reference | -0.03 (-0.93, 0.87) | 0.02 (-0.9, 0.95) | 0.35 (-0.71, 1.42) | 0.52 |
| Progressive sperm motility (%) | 0.21 (-0.38, 0.80) | Reference | -0.02 (-0.93, 0.88) | 0.00 (-0.92, 0.92) | 0.31 (-0.75, 1.38) | 0.58 |
| Normal forms (%) | 0.03 (-0.36, 0.42) | Reference | 0.23 (-0.35, 0.82) | 0.24 (-0.37, 0.85) | 0.06 (-0.65, 0.77) | 0.85 |
| Upper limb fat | ||||||
| Semen volume (ml) | -0.12 (-0.19, -0.06)* | Reference | -0.05 (-0.18, 0.09) | -0.06 (-0.19, 0.07) | -0.24 (-0.4, -0.09)* | <0.001 |
| Sperm concentration (×106 ml-1) | -0.35 (-1.57, 0.87) | Reference | 0.12 (-2.49, 2.73) | -0.36 (-2.87, 2.14) | -1.09 (-4.16, 1.99) | 0.56 |
| Total sperm count (×106) | -10.46 (-15.77, -5.15)* | Reference | -1.36 (-13.06, 10.33) | -3.86 (-15.01, 7.30) | -22.51 (-35.87, -9.16)* | <0.001 |
| Total sperm motility (%) | 0.10 (-0.30, 0.50) | Reference | -0.2 (-1.08, 0.68) | 0.19 (-0.65, 1.04) | 0.29 (-0.7, 1.29) | 0.50 |
| Progressive sperm motility (%) | 0.08 (-0.32, 0.48) | Reference | -0.16 (-1.05, 0.72) | 0.02 (-0.65, 1.04) | 0.26 (-0.73, 1.26) | 0.55 |
| Normal forms (%) | -0.02 (-0.29, 0.25) | Reference | 0.05 (-0.54, 0.65) | -0.02 (-0.58, 0.53) | 0.03 (-0.64, 0.7) | 0.96 |
| Trunk fat | ||||||
| Semen volume (ml) | -0.13 (-0.20, -0.05)* | Reference | 0.00 (-0.14, 0.14) | -0.07 (-0.21, 0.07) | -0.25 (-0.42, -0.07)* | 0.004 |
| Sperm concentration (×106 ml-1) | 0.13 (-1.37, 1.63) | Reference | -0.14 (-2.81, 2.53) | -0.79 (-3.54, 1.96) | 0.23 (-3.15, 3.60) | 0.92 |
| Total sperm count (×106) | -8.32 (-14.84, -1.80)* | Reference | 0.39 (-11.45, 12.23) | -6.94 (-19.04, 5.15) | -17.32 (-32.33, -2.31)* | 0.01 |
| Total sperm motility (%) | 0.23 (-0.27, 0.73) | Reference | 0.10 (-0.83, 1.02) | 0.20 (-0.73, 1.13) | 0.27 (-0.83, 1.38) | 0.64 |
| Progressive sperm motility (%) | 0.22 (-0.28, 0.72) | Reference | 0.10 (-0.83, 1.03) | 0.18 (-0.75, 1.12) | 0.24 (-0.86, 1.35) | 0.68 |
| Normal forms (%) | 0.02 (-0.35, 0.32) | Reference | 0.04 (-0.56, 0.63) | 0.21 (-0.4, 0.82) | -0.15 (-0.89, 0.59) | 0.84 |
| Lower limb fat | ||||||
| Semen volume (ml) | -0.24 (-0.35, -0.13)* | Reference | -0.03 (-0.17, 0.1) | -0.05 (-0.19, 0.09) | -0.29 (-0.45, -0.13)* | <0.001 |
| Sperm concentration (×106 ml-1) | -0.19 (-2.30, 1.91) | Reference | -1.12 (-3.7, 1.47) | -1.26 (-3.95, 1.43) | -1.05 (-4.25, 2.14) | 0.49 |
| Total sperm count (×106) | -16.73 (-25.80, -7.67)* | Reference | -2.96 (-14.42, 8.49) | -6.56 (-18.43, 5.31) | -23.91 (-37.76, -10.06)* | <0.001 |
| Total sperm motility (%) | 0.17 (-0.52, 0.86) | Reference | -0.13 (-1.01, 0.76) | 0.09 (-0.81, 0.99) | 0.09 (-0.95, 1.13) | 0.86 |
| Progressive sperm motility (%) | 0.14 (-0.56, 0.83) | Reference | -0.13 (-1.02, 0.76) | 0.09 (-0.82, 0.99) | 0.04 (-1.00, 1.08) | 0.92 |
| Normal forms (%) | 0.07 (-0.39, 0.53) | Reference | 0.25 (-0.33, 0.84) | 0.05 (-0.54, 0.65) | 0.15 (-0.54, 0.85) | 0.82 |
*P<0.05. The regression coefficient and 95% CI were calculated using generalized estimating equation models, adjusting for age, race (Han Chinese or other), education level (undergraduate or higher, college, or high school or less), BMI, abstinence period (<4 days, 4–5 days, or ≥6 days), and semen collection season (spring, summer, autumn, or winter). BMI: body mass index; CI: confidence interval; BFP: body fat percentage
Figure 1.
Dose–response curve for the association of total BFP with semen quality. The body fat distribution was included as a natural cubic spline function in the GEE, adjusting for age, race (Han Chinese or other), education level (undergraduate or higher, college, or high school or less), BMI, abstinence period (<4 days, 4–5 days, or ≥6 days), and semen collection season (spring, summer, autumn, or winter). BFP: body fat percentage; BMI: body mass index; GEE: generalized estimating equation model.
In the stratified analysis according to BMI, we observed that BFP, upper limb, trunk, and lower limb fat percentage remained significantly associated with a decrease in sperm count and semen volume in participants with a normal BMI (all P < 0.05; Supplementary Table 3). For overweight participants, both total BFP and local fat percentages showed negative associations with semen volume and total sperm count (all P < 0.05; Figure 2). No significant associations between BFP and sperm motility or morphology were observed in stratified analyses (Supplementary Figure 2 (148.8KB, tif) ). In the analysis stratified by age, we observed that BFP, upper limb, trunk, and lower limb fat percentage remained significantly associated with decreased sperm count and semen volume in all age groups (all P < 0.05; Supplementary Table 3). No significant differences between the results of different age groups were observed in the stratified analysis by age (Supplementary Table 4).
Supplementary Table 3.
Estimated change (95% confidence interval) of semen quality parameter values associated with body fat percentage, stratified by body mass index
| Semen quality parameter | BMIa | |||
|---|---|---|---|---|
|
| ||||
| Normal weight | Underweight | Overweight | Obese | |
| Total body fat | ||||
| Semen volume (ml) | -0.14 (-0.24, -0.04)* | 0.05 (-0.45, -0.34) | -0.44 (-0.65, -0.22)* | -0.14 (-0.59, 0.32) |
| Sperm concentration (×106 ml-1) | -0.02 (-2.04, 2.00) | -3.07 (-10.81, 4.67) | 1.45 (-2.89, 5.79) | -8.34 (-25.5, 8.82) |
| Total sperm count (×106) | -8.9 (-17.67, -0.14,)* | -7.64 (-42.25, 26.97) | -29.08 (-48.48, -9.68)* | -30.51 (-95.60, 34.59) |
| Total sperm motility (%) | 0.2 (-0.48, 0.87) | -0.14 (-2.98, 2.70) | 0.44 (-0.97, 1.85) | 0.48 (-3.74, 4.70) |
| Progressive sperm motility (%) | 0.17 (-0.51, 0.85) | -0.13 (-2.96, 2.69) | 0.42 ( -1.00, 1.83) | 0.54 (-3.74, 4.83) |
| Normal forms (%) | -0.01 (-0.46, 0.44) | -0.63 (-2.42, 1.17) | 0.41 (-0.54, 1.36) | 0.20 (-2.89, 3.30) |
| Upper limb fat | ||||
| Semen volume (ml) | -0.09 (-0.17, -0.02)* | -0.04 (-0.23, 0.30) | -0.28 (-0.41, -0.15)* | -0.07 (-0.37, 0.23) |
| Sperm concentration (×106 ml-1) | -0.40 (-1.82, 1.01) | -2.48 (-7.85, 2.89) | 0.55 (-2.17, 3.28) | -4.22 (-14.87, 6.44) |
| Total sperm count (×106) | -8.15 (-14.33, -1.98)* | -8.33 (-31.62, 14.87) | -19.96 (-32.21, -7,71)* | -17.47 (-58.92, 23.97) |
| Total sperm motility (%) | 0.05 (-0.42, 0.52) | 0.17 (-1.65, 1.99) | 0.21 (-0.67, 1.10) | -0.58 (-2.02, 3.19) |
| Progressive sperm motility (%) | 0.02 (-0.45, 0.49) | 0.21 (-1.61, 2.02) | 0.20 (-0.69, 1,09) | 0.62 (-2.04, 3.28) |
| Normal forms (%) | -0.09 (-0.40, 0.23) | -0.05 (-1.73, 0.72) | 0.33 (-0.27, 0.92) | 0.30 (-1.68, 2.29) |
| Trunk fat | ||||
| Semen volume (ml) | -0.10 (-0.19, -0.01)* | 0.11 (-0.18, 0.40)* | -0.45 (-0.66, -0.23)* | -0.23 (-0.79, -0.33)* |
| Sperm concentration (×106 ml-1) | 0.12 (-1.53, 1.78) | -2.15 (-7.90, 3.61) | 1.52 (-2.94, 5.98) | -11.02 (-34.28, 12.24) |
| Total sperm count (×106) | -6.03 (-13.31, 1.15) | -0.58 (-26.48, 25.33) | -29.61 (-49.93, -9.29)* | -44.79 (-132.22, -42.64) |
| Total sperm motility (%) | 0.19 (-0.37, 0.75) | -0.05 (-2.14, 2.03) | 0.48 (-0.98, 1.93) | 0.63 (-4.68, 5.95) |
| Progressive sperm motility (%) | 0.18 (-0.38, 0.74) | -0.03 (-2.11, 2.05) | 0.45 (-1.01, 1.90) | 0.71 (-4.69, 6.12) |
| Normal forms (%) | -0.04 (-0.41, 0.32) | -0.56 (-1.90, 0.79) | 0.48 (-0.49, 1.45) | 0.72 (-3.26, 4.71) |
| Lower fat limb | ||||
| Semen volume (ml) | -0.19 (-0.31, -0.07)* | -0.04 (-0.55, 0.45) | -0.49 (-0.73, -0.25)* | -0.40 (-11.82, 0.40) |
| Sperm concentration (×106 ml-1) | -0.09 (-2.50, 2.32) | -3.79 (-13.50, 5.92) | 1.05 (-3.81, 5.91) | -11.23 (-30.34, 7.90) |
| Total sperm count (×106) | -12.29 (-22.73, -1.85)* | -15.16 (-57.25, -26.94)* | -34.44 (-55.97, -12.92)* | -45.05 (-119.01, -28.91) |
| Total sperm motility (%) | 0.13 (-0.67, 0.93) | -0.54 (-4.12, 3.04) | 0.33 (-1.24, 1.91) | 1.39 (-3.46, 6.23) |
| Progressive sperm motility (%) | 0.09 (-0.71, 0.89) | -0.54 (-4.11, 3.02) | 0.31 (-1.26, 1.89) | 1.41 (-3.54, 6.36) |
| Normal forms (%) | 0.01 (-0.53, 0.54) | -0.51 (-2.70, 1.68) | 0.47 (-0.57, 1.52) | 0.40 (-2.96, 3.67) |
*P<0.05; aBMI was categorized using the WHO criteria: underweight (<18.5 kg m−2), normal weight (18.5–24.9 kg m−2), overweight (25.0–29.9 kg m−2), and obesity (≥30.0 kg m−2). The regression coefficient and 95% CI were calculated using generalized estimating equation models, adjusting for age, race, education level, abstinence period, and semen collection season. CI: confidence interval; BFP: body fat percentage; BMI: body mass index; WHO: World Health Organization
Figure 2.
Stratified analysis error bar plot by BMI. BMI was categorized using the WHO criteria: underweight (<18.5kg m−2), normal weight (18.5–24.9 kg m−2), overweight (25.0–29.9 kg m−2), and obesity (≥30.0kg m−2). Stratified BFP according to BMI. Each stratification was modeled using GEE. The estimated change in semen quality and 95% CI of each index of semen quality was calculated for each 10% increase in total BFP and local fat percentage in different stratified populations. BFP: body fat percentage; BMI: body mass index; GEE: generalized estimating equation model; WHO: World Health Organization; CI: confidence intervals.
Supplementary Table 4.
Estimated change (95% confidence interval) of semen quality parameters associated with body fat percentage, stratified by age
| Semen quality parameter | Age | P | |
|---|---|---|---|
|
| |||
| ≤25 years | >25 years | ||
| Total body fat | |||
| Semen volume (ml) | -0.16 (-0.28, -0.05)* | -0.21 (-0.35, -0.07)* | 0.63 |
| Sperm concentration (×106 ml-1) | -0.20 (-2.45, 2.04) | 0.38 (-2.50, 3.27) | 0.75 |
| Total sperm count (×106) | -11.95 (-21.77, -2.14)* | -12.53 (-24.82, -0.24)* | 0.94 |
| Total sperm motility (%) | 0.14 (-0.61, 0.89) | 0.31 (-0.63, 1.25) | 0.79 |
| Progressive sperm motility (%) | 0.09 (-0.65, 0.84) | 0.33 (-0.62, 1.28) | 0.70 |
| Normal forms (%) | -0.07 (-0.59, 0.45) | 0.09 (-0.51. 0.69) | 0.70 |
| Upper limb fat | |||
| Semen volume (ml) | -0.12 (-0.20, -0.04)* | -0.13 (-0.22, -0.04)* | 0.92 |
| Sperm concentration (×106 ml-1) | -0.04 (-1.96, 1.12) | -0.23 (-0.22, 1.74) | 0.88 |
| Total sperm count (×106) | -10.55 (-17.38, -3.73)* | -10.37 (-18.76, -1.98)* | 0.97 |
| Total sperm motility (%) | 0.04 (-0.47, 0.55) | 0.14 (-0.50, 0.78) | 0.81 |
| Progressive sperm motility (%) | 0.01 (-0.51, 0.51) | 0.15 (-0.49, 0.79) | 0.72 |
| Normal forms (%) | -0.09 (-0.45, 0.27) | 0.03 (-0.37, 0.44) | 0.66 |
| Trunk fat | |||
| Semen volume (ml) | -0.11 (-0.21, -0.01)* | -0.16 (-0.28, -0.03)* | 0.55 |
| Sperm concentration (×106 ml-1) | -0.17 (-2.03, 1.68) | 0.64 (-1.88, 3.15) | 0.61 |
| Total sperm count (×106) | -8.49 (-16.65, -0.33)* | -8.31 (-19.07, 2.46) | 0.98 |
| Total sperm motility (%) | 0.12 (-0.51, 0.75) | 0.34 (-0.48, 1.17) | 0.68 |
| Progressive sperm motility (%) | 0.09 (-0.54, 0.71) | 0.36 (-0.47, 1.20) | 0.60 |
| Normal forms (%) | -0.10 (-0.52, 0.33) | -0.05 (-0.47, 0.58) | 0.67 |
| Lower fat limb | |||
| Semen volume (ml) | -0.22 (-0.36, -0.08)* | -0.28 (-0.45, -0.12)* | 0.56 |
| Sperm concentration (×106 ml-1) | -0.50 (-3.15, 2.16) | 0.25 (-3.16, 3.67) | 0.73 |
| Total sperm count (×106) | -16.24 (-27.82, -4.66)* | -17.70 (-32.19, -3.21)* | 0.88 |
| Total sperm motility (%) | 0.06 (-0.82, 0.94) | 0.25 (-0.86, 1.35) | 0.80 |
| Progressive sperm motility (%) | -0.01 (-0.88, 0.87) | 0.27 (-0.84, 1.39) | 0.70 |
| Normal forms (%) | -0.06 (-0.67, 0.55) | 0.18 (-0.52, 0.88) | 0.61 |
*P<0.05. The regression coefficient and 95% CI were calculated from generalized estimating equation models, adjusting for BMI, race, education level, abstinence period, and semen collection season. CI: confidence interval; BFP: body fat percentage; BMI: body mass index
DISCUSSION
In this large longitudinal study involving 4304 sperm donors in South China, we found that total BFP and local fat percentages were consistently associated with a reduction in semen volume and total sperm count, but not sperm concentration, sperm motility, or sperm morphology. These associations tended to be nonlinear, as the semen volume and total sperm count only decreased significantly at higher BFPs. Furthermore, these associations still held in participants with a normal BMI.
Numerous studies have explored the influence of obesity on male reproductive health. These studies primarily utilized waist-to-hip ratio and BMI as indicators of male obesity and reported that abnormal BMI (including underweight, overweight, and obesity) and higher waist-to-hip ratio were associated with reduced semen quality.16,28,32,33,34 Our previous study using BMI as an indicator also identified a significant association of underweight and overweight with a decline in semen quality.15 Although BMI is the most commonly used indicator for diagnosing obesity, accumulating evidence suggests that it cannot differentiate between muscle and fat distribution and can lead to an overestimation of obesity in individuals with higher muscle mass and an underestimation of obesity in individuals with lower muscle mass.24 A meta-analysis reported that using conventional BMI reference values for diagnosing obesity carried a high degree of specificity, but a low level of sensitivity.35 As such, it cannot identify nearly half of the obese population with excessive BFPs. For individuals with a normal BMI but excessive BFP, known as “normal weight obesity” or “hidden obesity”, health issues such as metabolic disorders may arise due to excessive body fat.36,37 Therefore, BFP can be more relevant in assessing the link between obesity and semen quality.
From published research, it is observed that central obesity is correlated with decreased semen volume, total sperm count, total motile sperm count, and total progressively motile sperm count, along with a higher probability of reduced semen volume.38 These findings align with our study’s; however, the obesity indices utilized differ from those in our research. A few studies have investigated the link between BFP and the quality of semen. A cross-sectional study surveyed 260 reproductive-age Estonian men, with an average age of 31 years old, revealing a negative association between BFP and levels of total testosterone and sex hormone-binding globulin. Among the participants with a BFP >23.4%, a negative association was found between BFP and both total sperm count and semen volume.39 Similar results were found in our study among participants with a BFP exceeding 24.4%; however, compared with our research, the Estonian cross-sectional study had fewer participants and less detailed body fat distribution data, potentially lacking sufficient power to detect any association between localized body fat and semen quality. A study conducted among couples undergoing in vitro fertilization in the USA found that men with a BFP FPund that men with a ted among cocount, but no difference was observed in total motile sperm count among different BMI groups.24 Our study results only indicated an association between increased BFP and decreased sperm count, but not sperm motility. Notably, we found that even in men with a normal BMI, increased BFP remains associated with decreased sperm quantity, suggesting the potential value of BFP in identifying reduced total sperm count.
Contrary to our study, some studies have failed to observe such significant associations. A study based on 7941 healthy men did not find a relationship between BFP and semen quality.23 Moreover, a study involving 100 men in Poland similarly found no significant associations between BFP and any sperm parameters.40 The inconsistency of findings among previous studies and our study can be explained by the difference in population characteristics and exposure assessment. In summary, the influence of body fat on semen quality in our study aligned with findings from several previous studies, especially regarding the decrease in sperm count. However, additional studies are still necessary to confirm these findings.
Several possible biological mechanisms can link a higher BFP to semen quality decline. Because obesity is linked to both an augmentation in fat cell count and size, numerous suggested mechanisms regarding its influence on male fertility concentrate on the impact of adipose-derived hormones and adipokines associated with reproductive organs and hormones.22 For example, in men with excessive body fat, higher levels of estrogen have been observed,41 and studies in animal models have shown that elevated estrogen levels have a direct harmful effect on sperm production.42 The presence of estrogen receptors in the hypothalamus of men implies that estrogen could lower testosterone levels via a negative feedback mechanism, thereby affecting semen quality.18 Furthermore, there exists a robust positive correlation between serum leptin levels and BFP.43 Animal experiments have revealed that elevated leptin levels can adversely affect sperm and testosterone production in interstitial cells.44 In addition, the main effect of elevated BFP may be related to accessory gonadal function. A recent study has highlighted that excess body fat can lead to hormonal imbalances, especially decreased testosterone levels, which in turn affect the secretory function of the accessory gonads, thereby affecting semen volume and sperm count.45
Furthermore, environmental toxins and oxidative stress are also noteworthy. In obese men, the buildup of excessive fat in the scrotum along with environmental toxins found in the white adipose tissue encasing the scrotum could directly affect sperm generation within the testes. Oxidative stress likely plays a significant role in the interplay between body fat and male reproductive dysfunction. Mitochondria produce reactive oxygen species (ROS) as a byproduct of metabolic activity during sperm development; excessive ROS production, particularly in conditions of obesity or high-fat diets, has been well documented to cause lipid peroxidation, nucleic acid damage, and mitochondrial dysfunction. These effects primarily contribute to impaired sperm motility, abnormal morphology, and decreased sperm concentration.46,47 However, emerging research also suggests that oxidative stress may influence semen volume and sperm count by causing damage to the seminal vesicles or inducing apoptosis in spermatogenic cells.45 Studies in animal models have demonstrated that high-fat diets can lead to oxidative stress-induced impairments in both sperm count and semen volume, pointing to a broader impact of oxidative stress beyond traditional measures of sperm quality.48 Antioxidant therapies have shown promise in mitigating some of these effects, suggesting that the oxidative damage associated with increased adiposity can contribute to male reproductive dysfunction in multiple ways.49 Human and animal studies consistently indicate that men with higher body fat levels also have elevated oxidative stress responses, which can damage both the mitochondrial membrane and reproductive tissues, potentially affecting semen production and sperm quantity.
Our study has several strengths. First, the sample size was large, which can provide sufficient statistical power to evaluate the association between body fat distribution and semen quality. Second, it is the inaugural investigation to examine quantitatively the dose–response relationship of total BFP and local fat percentage with semen quality. Previous studies only compared variations in semen quality among men across different ranges of BFP qualitatively. Third, we utilized repeated measurements of semen analysis data to control for variability in semen parameter testing and included all repeated measures data in generalized estimating equation to assess the association between BFP and semen quality, taking into account the correlation among repeated measurements.
There are also some limitations in our study. First, we did not collect detailed information on the volunteers’ daily diet and exercise habits, which prevented us from controlling for the potential influence of these factors on semen quality. Second, we did not measure other indicators for semen quality including DNA fragmentation rate and relevant reproductive hormone levels, which can help further elucidate the association of BFP with semen quality indicators. Third, the generalizability of our research findings is limited, as the study participants were solely sourced from one sperm bank in China.
CONCLUSIONS
A higher level of total and local BFPs was significantly associated a reduction in semen volume and total sperm count, and these associations still hold in participants with a normal BMI. These findings contribute further evidence to the notion that obesity negatively impacts semen quality and emphasizes the needs to maintain an appropriate BFP for men whose partners expect to conceive. Further studies are necessary to clarify the causality between body fat distribution and semen quality, as well as to gain deeper insights into the underlying mechanisms.
AUTHOR CONTRIBUTIONS
YWL and XZZ designed this study and mainly revised the manuscript. YWL, XZZ, QLW, and GFY collected the data. SHL, QLW, and DL performed the statistical analysis and drafted the manuscript. GFY, YXL, WZ, RJX, XYD, LL, and SRW reviewed the manuscript and commented on it. All authors read and approved the final manuscript.
COMPETING INTERESTS
All authors declare no competing interests.
Dose–response curve for the association of local body fat distribution with semen quality. The body fat distribution is included as a natural cubic spline function in the GEE, adjusting for age, race, education level, BMI, semen collection season, and abstinence days. BFP: body fat percentage; BMI: body mass index; GEE: generalized estimating equation model.
Stratified analysis error bar plot by BMI. BMI was categorized using the WHO criteria: underweight (<18.5kg m−2), normal weight (18.5–24.9 kg m−2), overweight (25.0–29.9 kg m−2), and obesity (≥30.0kg m−2). Stratified body fat percentage according to BMI. Each stratification is modeled using GEE. The change in semen quality and 95% CI of each index of semen quality was calculated for each 10% increase in global fat rate and local fat rate in different stratified populations. The mid-point of the figure represents the semen quality parameter values associated with BFP, and the error bar length represents the 95% CI of the parameter values. BFP: body fat percentage; BMI: body mass index; GEE: generalized estimating equation model, CI: confidence interval.
ACKNOWLEDGMENTS
This work was supported by the Guangdong Natural Science Foundation (No. 2022A1515011705).
Supplementary Information is linked to the online version of the paper on the Asian Journal of Andrology website.
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Associated Data
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Supplementary Materials
Dose–response curve for the association of local body fat distribution with semen quality. The body fat distribution is included as a natural cubic spline function in the GEE, adjusting for age, race, education level, BMI, semen collection season, and abstinence days. BFP: body fat percentage; BMI: body mass index; GEE: generalized estimating equation model.
Stratified analysis error bar plot by BMI. BMI was categorized using the WHO criteria: underweight (<18.5kg m−2), normal weight (18.5–24.9 kg m−2), overweight (25.0–29.9 kg m−2), and obesity (≥30.0kg m−2). Stratified body fat percentage according to BMI. Each stratification is modeled using GEE. The change in semen quality and 95% CI of each index of semen quality was calculated for each 10% increase in global fat rate and local fat rate in different stratified populations. The mid-point of the figure represents the semen quality parameter values associated with BFP, and the error bar length represents the 95% CI of the parameter values. BFP: body fat percentage; BMI: body mass index; GEE: generalized estimating equation model, CI: confidence interval.