Medicine
®
OBSERVATIONAL STUDY
Lifestyles Associated With Human Semen Quality: Results From MARHCS Cohort Study in Chongqing, China Huan Yang, PhD, Qing Chen, PhD, Niya Zhou, MMS, Lei Sun, PhD, Huaqiong Bao, MMS, Lu Tan, MAgr, Hongqiang Chen, BSc, Guowei Zhang, PhD, Xi Ling, BE, Linping Huang, MPH, Lianbing Li, MD, Mingfu Ma, MD, Hao Yang, MD, Xiaogang Wang, BSc, Peng Zou, BSc, Kaige Peng, PhD, Kaijun Liu, PhD, Taixiu Liu, BSc, Zhihong Cui, PhD, Jinyi Liu, PhD, Lin Ao, PhD, Ziyuan Zhou, PhD, and Jia Cao, PhD
Abstract: Decline of semen quality in past decades is suggested to be potentially associated with environmental and sociopsychobehavioral factors, but data from population-based cohort studies is limited. The male reproductive health in Chongqing College students (MARHCS) study was established in June 2013 as a perspective cohort study that recruited voluntary male healthy college students from 3 universities in Chongqing. The primary objectives of the MARHCS study are to investigate the associations of male reproductive health in young adults with sociopsychobehavioral factors, as well as changes of environmental exposure due to the relocation from rural campus (in University Town) to metro-campus (in central downtown). A 93-item questionnaire was used to collect sociopsychobehavioral information in manner of interviewer–interviewing, and blood, urine and semen samples were collected at the same time. The study was initiated with 796 healthy young men screened from 872 participants, with a median age of 20. About 81.8% of this population met the WHO 2010 criteria on semen quality given to the 6 routine parameters. Decreases of 12.7%, 19.8%, and 17.0%, and decreases of 7.7%, 17.6%, and 14.7% in total sperm count and sperm concentration, respectively, were found to be associated with the tertiles of accumulated smoking amount. Fried food consumption (1–2 times/ wk or 3 times/wk vs nonconsumers) was found to be associated with Editor: Vijayaprasad Gopichandran. Received: March 23, 2015; revised: May 20, 2015; accepted: June 22, 2015. From the Institute of Toxicology (HuanY, QC, NZ, LS, LT, HC, GZ, LH, XW, PZ, KP, KL, TL, ZC, JL, LA, JC), College of Preventive Medicine, Third Military Medical University; The Key Laboratory of Birth Defects and Reproductive Health of National Health and Family Planning Commission (Chongqing Population and Family Planning Science and Technology Research Institute) (HB, LL, MM, HaoY); and Department of Environmental Hygiene (ZZ), College of Preventive Medicine, Third Military Medical University, Chongqing, P.R. China. Correspondence: Jia Cao, Institute of Toxicology, College of Preventive Medicine, Third Military Medical University, Chongqing 400038, P.R. China (e-mail: [email protected]). Ziyuan Zhou, Department of Environmental Hygiene, College of Preventive Medicine, Third Military Medical University, Chongqing, P.R. China (e-mail: [email protected]). HuanY and QC contributed equally to this work. This work was supported by the State Key Project 81130051 supported by the National Natural Science Foundation of China, the National Scientific and Technological Support Program (2013B112B02), and the Youth Project 81202276 supported by the National Natural Science Foundation of China. The authors have no conflicts of interest to disclose. Copyright # 2015 Wolters Kluwer Health, Inc. All rights reserved. This is an open access article distributed under the Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0, where it is permissible to download, share and reproduce the work in any medium, provided it is properly cited. The work cannot be changed in any way or used commercially. ISSN: 0025-7974 DOI: 10.1097/MD.0000000000001166
Medicine
Volume 94, Number 28, July 2015
decreased total sperm count (10.2% or 24.5%) and sperm concentration (13.7% or 17.2%), respectively. Coffee consumption was found to be associated with increased progressive and nonprogressive motility of 8.9% or 15.4% for subjects consuming 1–2 cups/wk or 3 cups/wk of coffee, respectively. Cola consumption appeared an association with decreased semen volume at 4.1% or 12.5% for 1–2 bottles/wk or 3 bottles/wk. A cohort to investigate the effects of environmental/sociopsychobehavioral factors act on semen quality was successfully set up. We found smoking, coffee/cola/fried foods consumption to be significantly associated with semen quality from the baseline investigation. (Medicine 94(28):e1166) Abbreviations: ANCOVA = analysis of covariance, BMI = body mass index, CASA = computer-aided sperm analysis, IM = immotility, MARHCS = male reproductive health in Chongqing College students, NP = nonprogressive, PAEs = phthalic acid esters, PAHs = polyaromatic hydrocarbons, PR = progressive, WHO = World Health Organization.
INTRODUCTION
A
pproximately 10% of couples suffer from infertility worldwide,1 and half of them are due to male factors.2 Semen analysis is important for examining male fertility potential.3 Carlsen et al4 summarized semen quality change between 1938 and 1990 and found the dramatic decline in general populations across continents, although the results are being debated afterward.5 Current studies are mostly cross-sectional, some of them mainly recruited participants from infertility clinic patients or sperm bank donators, the season of sampling, methods used in semen analysis, and the participants’ age varied among or within studies, and the results remain controversial.6–18 Our previous study found only 38.9% of healthy male volunteers in Chongqing area met with all 6 semen parameters6 according to World Health Organization (WHO) 1999 criteria,19 although this rate can reach 62.0% as recalculated according to WHO recommendations (5th edition, WHO, Switzerland)20; it still suggests that the current semen quality, at least in Chongqing males, requires higher public health concern. Although some genetic and pathological factors for male infertility have been confirmed,21,22 in general population, accumulating evidence,11,23– 28 including our previous studies,29–33 linked semen quality to environmental factors, among which persistent organic pollutants/endocrine disrupters, and electronic magnetic field exposures are extensively reported25,29,32,34–44; sociopsychobehavioral factors were also suggested to be associated with semen parameters.18,30,31,40,45–47 Moreover, age is extensively associated with semen quality,48,49 other factors www.md-journal.com |
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Medicine
Yang et al
such as season, geographic variation, lifestyles, methods used in semen analysis, may also modify the results. A general population-based longitudinal cohort study is necessary for illustrating the roles of environmental pollutants exposure and sociopsychobehavioral factors in semen quality alternation. Based on this, we carried out a cohort study (Figure 1) on male reproductive health in Chongqing College students with environmental exposure change on purpose of comparing semen parameters before and after the campuses relocation; assessing the effects of sociopsychobehavioral factors on semen quality; evaluating the effects of environmental pollutants, mainly polyaromatic hydrocarbons (PAHs) and phthalic acid esters (PAEs), on semen quality.
METHODS Study Design Chinese universities/colleges are encountering space shortage due to fast development; local government usually assign specific lands in suburban or rural areas to set up new campuses.50 Chongqing city set up its new University Town in Huxi town, a rural area far away from downtown. Better air quality index and deep processed water can be found in the University Town when compared with the urban area.51 Most specialties in Chongqing’s universities/colleges split their courses into elementary and professional phases, deploy the elementary courses in University Town during the first 2 years, and the professionals in urban old campuses during the last 2 years, leading to the students relocation from rural to urban campus to finish all courses, whereas the students from other specialties, such as Computer Science, Art, etc., will stay in the University Town till graduation. Relocated students will consequently experience environmental exposure changes naturally. This particular environmental exposure change due to campus relocation offered us an opportunity to carry out this study. The baseline investigation was carried out in June 2013, at the end of August 2013, the fall semester began in universities/ colleges, most of the participants moved to urban campuses in
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Shapingba district whereas the rest remained in the University Town, no more relocation would happen to either group before graduation. All eligible volunteers, moved or not, were invited to the baseline investigation. This study was approved by the Ethics Committees of Third Military Medical University, and signed informed consent was obtained from each participant. Taking seasonal affection and change of environmental exposures into consideration, the first follow-up was performed in June 2014 with a 10-month interval (September 2013 to June 2014) covering 3 whole cycles of spermatogenesis, which may reduce possible delayed effects of environmental exposures, as well as the seasonal differences. The second follow-up is scheduled to be carried out in June 2015.
Study Population According to the semen parameters in Chongqing general population from our previous study,6 and on the consideration of perhaps 20% of failure in follow-up and another 20% of failure in semen sample collection, we calculated the sample size with NCSS PASS 2008, suggesting that a sample size of 646 would enable explanation of biological differences and their associations to environmental or sociopsychobehavioral factors with a statistical power of 0.9 and significant level of 0.05. Since April 2013, all male sophomores in University Town received our propaganda on illustrating this study. Online registration was opened to all male sophomores till the number of registered volunteers reached the expected sample size. In June 2013, those who met all the 3 criteria were included: >18 years old; 2 to 7 days of abstinent; and second-grade college students studying in University Town. An individual would be excluded if he met any of the following criteria: history of urologist diagnosed inflammation of urogenital system; history of epididymitis; history of testicular injury; treatment history of varicocele; history of incomplete orchiocatabasis; or any of the following was detected by the urologist at the physical examination stage during the investigation: absence of prominentia laryngea; absence of pubes; abnormal breast; abnormal penis; absence of testis; epididymal knob, or varicocele.
FIGURE 1. Flow chart of the design for the whole study and including/excluding process. The overall design and including/excluding process of the whole cohort study. Seventy-six patients were excluded because of the disease history of the following: 4 of urinary disease, 3 of incomplete orchiocatabasis, 2 of diabetes, 4 of tuberculosis, 4 of inguinal hernia, 2 of testicular injury, and 17 of inflammation in urogenital system.
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Medicine
Volume 94, Number 28, July 2015
Lifestyles and Semen Quality: The MARHCS Study
TABLE 1. Subjects and Items Included in the Lifestyle-Behavioral Questionnaire Subjects
Items
Demographics (6 items)
Age, place of birth (county), race, duration of residence in the University Town, specialty, and affiliation. Parenthood of siblings, parents’ siblings, and grandparents’ siblings. History of chronic diseases: diabetes, tuberculosis, chronic respiratory diseases, pancreatic cystic fibrosis, nervous system disease. Surgical treatments: urethrostenosis, hypospadias, prostatectomy, bladder neck surgery, vasoligation, inguinal hernia surgery, surgery of hydrocele of tunica vaginalis, surgery of sympathetic nerve. Urinosexual diseases: infections, epididymal diseases, testicle injuries, varicocele, and undescended testicle, cystospermitis, prostatitis, sexually transmitted diseases. Medical care in recent 3 mo: fever >38.58C, any medications, or other diseases not mentioned earlier. Tight-fitting underwear, chemical fiber fabric underwear, hot shower, sauna, bicycle/motorcycle riding, sitting time, tobacco smoking, passive smoking, alcohol consumption, tea/coffee/soft drink consumptions, water consumption, container for drinking water and foods, fried/baked food consumption, physical activities. Usage of desktop/laptop, utilizing of Wi-Fi, usage of cellular phones, number of cellphones using in recent 3 mo, carriers of cellphones, presence of 3rd-generation function, duration of using cellphones, average time of closely ( 40) as systematically reviewed.18 Abstinent duration, sauna experience, smoking, coffee/cola drinking, and fried/baked foods consuming showed significant association with semen parameters (Table 2): first, longer abstinent duration was found to be positively associated with semen volume, sperm concentration, and total sperm count (P < 0.001), and negatively associated with PR (P < 0.01). Second, sauna experience was the only lifestyle that was associated with normal sperm morphology rate, a significantly higher normal sperm morphology rate (9.9%) was found in subjects with sauna experience when compared to that (8.3%) in those without it (P < 0.05); however, the low frequencies (usually 1 time in 3 months) may reduce the effects of high temperature on semen parameters, thus this result may be a coincidence. Third, smoking was found to be associated with decreased total sperm count (P < 0.05). Fourth, both coffee and cola drinking were found to be associated with increased PR (P < 0.01, P < 0.05, respectively); coffee drinking was also associated with increased PRþNP (P < 0.001) but cola drinking was associated with decreased semen volume and total sperm count (both P < 0.01). Fifth, both fried foods and baked foods consumption were observed to have negative associations with sperm concentration and total sperm count (all P < 0.01). Variables that were found to be associated with semen parameters were included in the multivariate analyses, after adjusting for age, tobacco and alcohol consumption, duration of abstinent, BMI, coffee/cola/fried food/baked foods consumption with a linear regression model, we still observed smoking, coffee/cola drinking, fried foods consumption to be associated with semen parameters: first, decreases of 12.7%, 19.8%, and 17.0%, and decreases of 7.7%, 17.6%, and 14.7% in total sperm count and sperm concentration, respectively, were found to be associated with the tertiles of accumulated smoking amount (Ptrend ¼ 0.012, 0.023, respectively; Figure 3A and B). Second, for frequencies of 1 to 2 times/wk or 3 times/wk, fried food consumption was found to be associated with decreased total sperm count (10.2% or 24.5%) and sperm concentration (13.7% or 17.2%), respectively (Ptrend ¼ 0.005, 0.008, respectively; Figure 3C and D). Third, coffee consumption was found to be positively associated with PRþNP, increase of 8.9% or 15.4% for subjects consuming 1 to 2 cups/wk or 3 cups/wk of coffee were found, respectively (Ptrend < 0.001, Figure 3E). Suggesting caffeine may be associated only with improved sperm motility, which is not accordant to a study carried out in western countries,55,56 the much lower level of coffee intake in the current population may partially explain the difference. Fourth, cola consumption appeared an association with decreased semen volume at 4.1% or 12.5% for 1 to 2 bottles/wk or 3 bottles/wk (Ptrend ¼ 0.024, Figure 3F). Copyright
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Volumey, mL
Sperm concentrationy, million/mL
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55 (29, 84) 56 (29, 81) 59 (22, NA) >0.05 59 56 56 53
188 (40, 621) 167 (34, 648) 198 (55, NA) >0.05 185 187 158 153
2015 Wolters Kluwer Health, Inc. All rights reserved.
(43, 693) (35, 548) (36, 618) (34, 608) >0.05 (31, 587) (40, 821) (38, 551) (41, 645) >0.05
162 210 188 170
198 197 167 188
55 54 57 56
55 57 59 60
55 59 57 54
(39, 626) (194, 744) (34, 614) (34, 607) >0.05
174 202 194 164
(31, 84) (18, 82) (32, 82) (28, 84) >0.05
(30, 83) (26, 85) (32, 87) (23, 88) >0.05
(71, 99) (67, 99) (67, 99) (55, 97) >0.05
90 87 90 89
89 90 90 92
88 90 90 88
(70, 98) (65, 99) (69, 99) (65, 99) >0.05
(67, 99) (68, 99) (64, 99) (61, 99) >0.05
(67. 99) (67, 99) (71, 99) (64, 99) >0.05
89 (67, 98) 90 (69, 99) 87 (64, 98) >0.05
91 89 88 82
89 (67, 99) 88 (65, 99) 91 (64, NA) >0.05
89 (67, 99) 88 (63, 98) >0.05
88 (65, 99)
Total motilityy, %
(4.4,16.0) (4.0,13.9) (3.5,14.7) (4.2,14.7) >0.05
8.0 8.2 8.4 8.5
9.4 9.2 8.3 8.5
9.5 8.7 8.4 7.8
(3.5, 14.7) (4.4, 13.9) (3.8, 14.2) (4.5, 14.0) >0.05
(4.0, 13.9) (4.4, 16.0) (4.0, 13.1) (4.2, 16.3) >0.05
(4.1, 14) (3.9, 13.6) (4, 14.8) (4, 12.2) >0.05
8.5 (4.2,13.9) 8.4 (4.0,14.8) 8.0 (4.3,13.9) >0.05
8.5 8.4 8.3 7.5
8.4 (4.0, 14.0) 8.2 (4.4, 13.5) 9.0 (3.3, NA) >0.05
8.4 (4.0, 14.0) 8.4 (4.5, 15.6) >0.05
8.4 (4.0, 14.0)
Normal sperm morphologyy, %
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(29, 83) (27, 81) (32, 84) (28, 86) >0.05
58 (30, 83) 57 (32, 84) 53 (27, 80) 0.05
183 (37, 619) 193 (40, 751) >0.05
(49, 613) (38, 637) (33, 705) (14, 580) >0.05
55 (29, 83)
Progressive motiley, %
184 (38, 627)
Total sperm county, million
Population (n ¼ 794) 3.4 (1.5, 6.7) 54 (14, 194) Race Han (n ¼ 661) 3.4 (1.5, 6.7) 53 (13, 182) 3.2 (1.6, 6.6) 55 (17, 215) Others (other 19 racesz, n ¼ 133) P for trend >0.05 >0.05 Age (with a median of 20 years, 5th and 95th percentile of 19 and 23 years old) 18–20 (477) 3.5 (1.5, 6.6) 54 (13, 192) 21–23 (303) 3.3 (1.6, 6.7) 51 (14, 210) >23 (14) 3.6 (1.5, NA) 64 (16, NA) P for trend >0.05 >0.05 BMIz (with a median of 20.9, 5th and 95th percentile of 17.8 and 26.3) 26.9 (n ¼ 31) 2.9 (1.0, 6.0) 47 (7.5, 233) P for trend >0.05 >0.05 Abstinent duration, d 2–3 (n ¼ 317) 3.1 (1.5, 6.4) 47 (11, 174) 4–5 (n ¼ 259) 3.5 (1.5, 6.4) 57 (16, 163) 6–7 (n ¼ 218) 3.7 (1.8, 7.0) 61 (19, 232) P for trend 0.05 Hot shower Never (n ¼ 146) 3.3 (1.5, 6.4) 55 (13, 201) 2 times/wk (n ¼ 301) 3.3 (1.5, 6.7) 54 (15, 206) P for trend >0.05 >0.05
Variables
TABLE 2. Basic Characteristics and Univariate Correlations Between Semen Parameters and Lifestyles
Medicine Lifestyles and Semen Quality: The MARHCS Study
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6
Sauna experience No (n ¼ 770) Yes (n ¼ 24) P for trend Bicycle riding Never (n ¼ 412) 0.05 209 (40, 761) 175 (37, 593) 154 (35, 505)
54 (13, 200) 55 (14, 183) 52 (21, 226) >0.05 57 (15, 211) 52 (14, 184) 56 (11, 158)
3.4 (1.6, 6.8) 3.1 (1.4, 5.9) 3.6 (1.5, 7.4) >0.05 3.6 (1.7, 6.6) 3.4 (1.5, 6.9) 3.1 (1.4, 5.9)
(30, 87) (27, 83) (31, 83) (34, 84) >0.05
#
54 (28, 80) 57 (30, 84) 71 (28, 91)
(67, 99) (63, 99) (67, 99) (65, 99) >0.05
88 (67, 98) 90 (69, 99) 89 (64, 100)
88 (67, 98) 91 (66, 99) 92 (76, 100) 0.05
89 (65, 99) 82 (52, NA) 90 (70, 99) >0.05
89 (67, 99) 86 (64, 99) 90 (70, 99) >0.05
87 88 88 90
89 (67, 99) 86 (61, 99) >0.05
87 (65, 99) 91 (68, 99) 84 (67, 99) >0.05
88 (65, 99) 88 (49, 98) >0.05
Total motilityy, %
(4.4, 14.9) (4.0, 14.4) (4.4, 13.9) (3.5, 13.9) >0.05
8.5 (4.4, 13.5) 8.4 (3.9, 15.0) 7.9 (4.3, 13.9)
8.3 (4.0, 13.9) 8.7 (4.5, 14.8) 7.7 (3.9, 13.0) >0.05
8.3 (4.0, 14.0) 8.5 (4.4, 13.9) 8.4 (4.0, 14.5) >0.05
8.3 (4.0, 13.7) 5.9 (2.5, NA) 8.5 (4.3, 14.4) >0.05
8.4 (4.0, 14.0) 7.5 (4.1, 12.0) 8.5 (4.0, 14.7) >0.05
8.3 8.4 8.4 8.5
8.4 (4.0, 13.9) 8.6 (3.3, 17.9) >0.05
8.5 (4.0, 14.2) 7.9 (4.0, 13.5) 8.5 (4.7, 14) >0.05
8.3 (4.0, 14.0) 9.9 (4.4, 17.9) 0.05
56 (28, 83) 52 (25, 84) 57 (34, 84) >0.05
55 56 54 59
56 (29, 83) 51 (23, 84) >0.05
54 (28, 83) 58 (30, 84) 51 (28, 83) >0.05
56 (29, 83) 57 (19, 81) >0.05
Progressive motiley, %
Medicine
184 (37, 621) 162 (29, 523) 195 (43, 762) >0.05
54 (14, 200) 50 (10, 138) 57 (17, 228) >0.05
3.4 (1.5, 6.6) 3.2 (1.5, 6.9) 3.6 (1.8, 6.9) >0.05
184 (37, 690) 208 (13, NA) 182 (40, 590) >0.05
192 (40, 654) 186 (26, 834) 155 (33, 567) 0.05
54 (13, 209) 62 (5.8, NA) 53 (15, 164) >0.05
55 (28, 203) 48 (11, 178) 50 (10, 170) >0.05
192 188 178 193
184 (38, 630) 181 (41, 590) >0.05
175 (35, 692) 194 (38, 563) 184 (41, 708) >0.05
184 (38, 621) 185 (36, 881) >0.05
Total sperm county, million
3.4 (1.5, 6.7) 3.8 (0.7, NA) 3.4 (1.6, 6.8) >0.05
3.4 (1.5, 6.8) 3.6 (1.6, 7.4) 3.4 (1.5, 5.8) >0.05
(13, 212) (13, 190) (16, 184) (10, 256) >0.05
51 (14, 189) 56 (12, 173) 57 (16, 243) >0.05
3.4 (1.6, 6.8) 3.4 (1.5, 6.7) 3.0 (1.6, 6.7) >0.05
(1.4, 6.0) (1.6, 6.8) (1.5, 6.7) (1.7, 6.8) >0.05
53 (14, 195) 75 (22, 210) >0.05
Sperm concentrationy, million/mL
3.4 (1.6, 6.7) 3.4 (0.9, 7.0) >0.05
Volumey, mL
Yang et al Volume 94, Number 28, July 2015
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57 (15, 200) 50 (12, 209) 42 (16, 157) 0.05
190 (37, 636) 145 (38, 536) 161 (55, NA) 0.05
56 (29, 83) 56 (29, 84) 57 (34, 84) >0.05
56 (28, 83) 55 (30, 83) 65 (26, 91) >0.05
88 (65, 99) 88 (68, 99) 88 (71, NA) >0.05
90 (67, 99) 88 (67, 99) 89 (69, 98) >0.05
89 (67, 99) 88 (67, 99) 91 (60, 100) >0.05
8.4 (4.0, 14.1) 8.1 (4.0, 13.2) 9.7 (3.5, NA) >0.05
8.5 (4.0, 14.6) 8.0 (4.0, 13.8) 8.5 (4.0, 14.5) >0.05
8.5 (4.0, 14.1) 8.3 (4.5, 13.5) 7.9 (4.0, 14.4) >0.05
>0.05
BMI ¼ body mass index, NA ¼ not available. Two subjects failed to report lifestyles, data from 794 subjects is presented. y Results are presented as median with 5th and 95th percentile. Mann–Whitney U or Jonckheere–Terpstra test was deployed to compare medians between or among groups in each variable. Results in bold characters indicate the variable to be significantly different between/among groups. z The 19 races are Tujia (n ¼ 29), Miao (n ¼ 12), Hazak (n ¼ 10), and other 82 from 16 races including Yi, Zhuang, Dong, Qilao, Meng, Bai, Zang, Chuanqing, Dai, Hui, Kirgiz, Man, She, Shui, Uygur, and Yao. § One subject failed to report chemical fiber underwear use, 1 failed to report alcohol drinking, 2 failed to report motorcycle riding, and 2 failed to report time of keeping seated.
55 (15, 201) 51 (12, 200) 57 (18, 134) >0.05
3.4 (1.6, 6.6) 3.6 (1.5, 6.8) 3.2 (1.4, 6.2) >0.05
®
OBSERVATIONAL STUDY
Lifestyles Associated With Human Semen Quality: Results From MARHCS Cohort Study in Chongqing, China Huan Yang, PhD, Qing Chen, PhD, Niya Zhou, MMS, Lei Sun, PhD, Huaqiong Bao, MMS, Lu Tan, MAgr, Hongqiang Chen, BSc, Guowei Zhang, PhD, Xi Ling, BE, Linping Huang, MPH, Lianbing Li, MD, Mingfu Ma, MD, Hao Yang, MD, Xiaogang Wang, BSc, Peng Zou, BSc, Kaige Peng, PhD, Kaijun Liu, PhD, Taixiu Liu, BSc, Zhihong Cui, PhD, Jinyi Liu, PhD, Lin Ao, PhD, Ziyuan Zhou, PhD, and Jia Cao, PhD
Abstract: Decline of semen quality in past decades is suggested to be potentially associated with environmental and sociopsychobehavioral factors, but data from population-based cohort studies is limited. The male reproductive health in Chongqing College students (MARHCS) study was established in June 2013 as a perspective cohort study that recruited voluntary male healthy college students from 3 universities in Chongqing. The primary objectives of the MARHCS study are to investigate the associations of male reproductive health in young adults with sociopsychobehavioral factors, as well as changes of environmental exposure due to the relocation from rural campus (in University Town) to metro-campus (in central downtown). A 93-item questionnaire was used to collect sociopsychobehavioral information in manner of interviewer–interviewing, and blood, urine and semen samples were collected at the same time. The study was initiated with 796 healthy young men screened from 872 participants, with a median age of 20. About 81.8% of this population met the WHO 2010 criteria on semen quality given to the 6 routine parameters. Decreases of 12.7%, 19.8%, and 17.0%, and decreases of 7.7%, 17.6%, and 14.7% in total sperm count and sperm concentration, respectively, were found to be associated with the tertiles of accumulated smoking amount. Fried food consumption (1–2 times/ wk or 3 times/wk vs nonconsumers) was found to be associated with Editor: Vijayaprasad Gopichandran. Received: March 23, 2015; revised: May 20, 2015; accepted: June 22, 2015. From the Institute of Toxicology (HuanY, QC, NZ, LS, LT, HC, GZ, LH, XW, PZ, KP, KL, TL, ZC, JL, LA, JC), College of Preventive Medicine, Third Military Medical University; The Key Laboratory of Birth Defects and Reproductive Health of National Health and Family Planning Commission (Chongqing Population and Family Planning Science and Technology Research Institute) (HB, LL, MM, HaoY); and Department of Environmental Hygiene (ZZ), College of Preventive Medicine, Third Military Medical University, Chongqing, P.R. China. Correspondence: Jia Cao, Institute of Toxicology, College of Preventive Medicine, Third Military Medical University, Chongqing 400038, P.R. China (e-mail: [email protected]). Ziyuan Zhou, Department of Environmental Hygiene, College of Preventive Medicine, Third Military Medical University, Chongqing, P.R. China (e-mail: [email protected]). HuanY and QC contributed equally to this work. This work was supported by the State Key Project 81130051 supported by the National Natural Science Foundation of China, the National Scientific and Technological Support Program (2013B112B02), and the Youth Project 81202276 supported by the National Natural Science Foundation of China. The authors have no conflicts of interest to disclose. Copyright # 2015 Wolters Kluwer Health, Inc. All rights reserved. This is an open access article distributed under the Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0, where it is permissible to download, share and reproduce the work in any medium, provided it is properly cited. The work cannot be changed in any way or used commercially. ISSN: 0025-7974 DOI: 10.1097/MD.0000000000001166
Medicine
Volume 94, Number 28, July 2015
decreased total sperm count (10.2% or 24.5%) and sperm concentration (13.7% or 17.2%), respectively. Coffee consumption was found to be associated with increased progressive and nonprogressive motility of 8.9% or 15.4% for subjects consuming 1–2 cups/wk or 3 cups/wk of coffee, respectively. Cola consumption appeared an association with decreased semen volume at 4.1% or 12.5% for 1–2 bottles/wk or 3 bottles/wk. A cohort to investigate the effects of environmental/sociopsychobehavioral factors act on semen quality was successfully set up. We found smoking, coffee/cola/fried foods consumption to be significantly associated with semen quality from the baseline investigation. (Medicine 94(28):e1166) Abbreviations: ANCOVA = analysis of covariance, BMI = body mass index, CASA = computer-aided sperm analysis, IM = immotility, MARHCS = male reproductive health in Chongqing College students, NP = nonprogressive, PAEs = phthalic acid esters, PAHs = polyaromatic hydrocarbons, PR = progressive, WHO = World Health Organization.
INTRODUCTION
A
pproximately 10% of couples suffer from infertility worldwide,1 and half of them are due to male factors.2 Semen analysis is important for examining male fertility potential.3 Carlsen et al4 summarized semen quality change between 1938 and 1990 and found the dramatic decline in general populations across continents, although the results are being debated afterward.5 Current studies are mostly cross-sectional, some of them mainly recruited participants from infertility clinic patients or sperm bank donators, the season of sampling, methods used in semen analysis, and the participants’ age varied among or within studies, and the results remain controversial.6–18 Our previous study found only 38.9% of healthy male volunteers in Chongqing area met with all 6 semen parameters6 according to World Health Organization (WHO) 1999 criteria,19 although this rate can reach 62.0% as recalculated according to WHO recommendations (5th edition, WHO, Switzerland)20; it still suggests that the current semen quality, at least in Chongqing males, requires higher public health concern. Although some genetic and pathological factors for male infertility have been confirmed,21,22 in general population, accumulating evidence,11,23– 28 including our previous studies,29–33 linked semen quality to environmental factors, among which persistent organic pollutants/endocrine disrupters, and electronic magnetic field exposures are extensively reported25,29,32,34–44; sociopsychobehavioral factors were also suggested to be associated with semen parameters.18,30,31,40,45–47 Moreover, age is extensively associated with semen quality,48,49 other factors www.md-journal.com |
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Medicine
Yang et al
such as season, geographic variation, lifestyles, methods used in semen analysis, may also modify the results. A general population-based longitudinal cohort study is necessary for illustrating the roles of environmental pollutants exposure and sociopsychobehavioral factors in semen quality alternation. Based on this, we carried out a cohort study (Figure 1) on male reproductive health in Chongqing College students with environmental exposure change on purpose of comparing semen parameters before and after the campuses relocation; assessing the effects of sociopsychobehavioral factors on semen quality; evaluating the effects of environmental pollutants, mainly polyaromatic hydrocarbons (PAHs) and phthalic acid esters (PAEs), on semen quality.
METHODS Study Design Chinese universities/colleges are encountering space shortage due to fast development; local government usually assign specific lands in suburban or rural areas to set up new campuses.50 Chongqing city set up its new University Town in Huxi town, a rural area far away from downtown. Better air quality index and deep processed water can be found in the University Town when compared with the urban area.51 Most specialties in Chongqing’s universities/colleges split their courses into elementary and professional phases, deploy the elementary courses in University Town during the first 2 years, and the professionals in urban old campuses during the last 2 years, leading to the students relocation from rural to urban campus to finish all courses, whereas the students from other specialties, such as Computer Science, Art, etc., will stay in the University Town till graduation. Relocated students will consequently experience environmental exposure changes naturally. This particular environmental exposure change due to campus relocation offered us an opportunity to carry out this study. The baseline investigation was carried out in June 2013, at the end of August 2013, the fall semester began in universities/ colleges, most of the participants moved to urban campuses in
Volume 94, Number 28, July 2015
Shapingba district whereas the rest remained in the University Town, no more relocation would happen to either group before graduation. All eligible volunteers, moved or not, were invited to the baseline investigation. This study was approved by the Ethics Committees of Third Military Medical University, and signed informed consent was obtained from each participant. Taking seasonal affection and change of environmental exposures into consideration, the first follow-up was performed in June 2014 with a 10-month interval (September 2013 to June 2014) covering 3 whole cycles of spermatogenesis, which may reduce possible delayed effects of environmental exposures, as well as the seasonal differences. The second follow-up is scheduled to be carried out in June 2015.
Study Population According to the semen parameters in Chongqing general population from our previous study,6 and on the consideration of perhaps 20% of failure in follow-up and another 20% of failure in semen sample collection, we calculated the sample size with NCSS PASS 2008, suggesting that a sample size of 646 would enable explanation of biological differences and their associations to environmental or sociopsychobehavioral factors with a statistical power of 0.9 and significant level of 0.05. Since April 2013, all male sophomores in University Town received our propaganda on illustrating this study. Online registration was opened to all male sophomores till the number of registered volunteers reached the expected sample size. In June 2013, those who met all the 3 criteria were included: >18 years old; 2 to 7 days of abstinent; and second-grade college students studying in University Town. An individual would be excluded if he met any of the following criteria: history of urologist diagnosed inflammation of urogenital system; history of epididymitis; history of testicular injury; treatment history of varicocele; history of incomplete orchiocatabasis; or any of the following was detected by the urologist at the physical examination stage during the investigation: absence of prominentia laryngea; absence of pubes; abnormal breast; abnormal penis; absence of testis; epididymal knob, or varicocele.
FIGURE 1. Flow chart of the design for the whole study and including/excluding process. The overall design and including/excluding process of the whole cohort study. Seventy-six patients were excluded because of the disease history of the following: 4 of urinary disease, 3 of incomplete orchiocatabasis, 2 of diabetes, 4 of tuberculosis, 4 of inguinal hernia, 2 of testicular injury, and 17 of inflammation in urogenital system.
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Medicine
Volume 94, Number 28, July 2015
Lifestyles and Semen Quality: The MARHCS Study
TABLE 1. Subjects and Items Included in the Lifestyle-Behavioral Questionnaire Subjects
Items
Demographics (6 items)
Age, place of birth (county), race, duration of residence in the University Town, specialty, and affiliation. Parenthood of siblings, parents’ siblings, and grandparents’ siblings. History of chronic diseases: diabetes, tuberculosis, chronic respiratory diseases, pancreatic cystic fibrosis, nervous system disease. Surgical treatments: urethrostenosis, hypospadias, prostatectomy, bladder neck surgery, vasoligation, inguinal hernia surgery, surgery of hydrocele of tunica vaginalis, surgery of sympathetic nerve. Urinosexual diseases: infections, epididymal diseases, testicle injuries, varicocele, and undescended testicle, cystospermitis, prostatitis, sexually transmitted diseases. Medical care in recent 3 mo: fever >38.58C, any medications, or other diseases not mentioned earlier. Tight-fitting underwear, chemical fiber fabric underwear, hot shower, sauna, bicycle/motorcycle riding, sitting time, tobacco smoking, passive smoking, alcohol consumption, tea/coffee/soft drink consumptions, water consumption, container for drinking water and foods, fried/baked food consumption, physical activities. Usage of desktop/laptop, utilizing of Wi-Fi, usage of cellular phones, number of cellphones using in recent 3 mo, carriers of cellphones, presence of 3rd-generation function, duration of using cellphones, average time of closely ( 40) as systematically reviewed.18 Abstinent duration, sauna experience, smoking, coffee/cola drinking, and fried/baked foods consuming showed significant association with semen parameters (Table 2): first, longer abstinent duration was found to be positively associated with semen volume, sperm concentration, and total sperm count (P < 0.001), and negatively associated with PR (P < 0.01). Second, sauna experience was the only lifestyle that was associated with normal sperm morphology rate, a significantly higher normal sperm morphology rate (9.9%) was found in subjects with sauna experience when compared to that (8.3%) in those without it (P < 0.05); however, the low frequencies (usually 1 time in 3 months) may reduce the effects of high temperature on semen parameters, thus this result may be a coincidence. Third, smoking was found to be associated with decreased total sperm count (P < 0.05). Fourth, both coffee and cola drinking were found to be associated with increased PR (P < 0.01, P < 0.05, respectively); coffee drinking was also associated with increased PRþNP (P < 0.001) but cola drinking was associated with decreased semen volume and total sperm count (both P < 0.01). Fifth, both fried foods and baked foods consumption were observed to have negative associations with sperm concentration and total sperm count (all P < 0.01). Variables that were found to be associated with semen parameters were included in the multivariate analyses, after adjusting for age, tobacco and alcohol consumption, duration of abstinent, BMI, coffee/cola/fried food/baked foods consumption with a linear regression model, we still observed smoking, coffee/cola drinking, fried foods consumption to be associated with semen parameters: first, decreases of 12.7%, 19.8%, and 17.0%, and decreases of 7.7%, 17.6%, and 14.7% in total sperm count and sperm concentration, respectively, were found to be associated with the tertiles of accumulated smoking amount (Ptrend ¼ 0.012, 0.023, respectively; Figure 3A and B). Second, for frequencies of 1 to 2 times/wk or 3 times/wk, fried food consumption was found to be associated with decreased total sperm count (10.2% or 24.5%) and sperm concentration (13.7% or 17.2%), respectively (Ptrend ¼ 0.005, 0.008, respectively; Figure 3C and D). Third, coffee consumption was found to be positively associated with PRþNP, increase of 8.9% or 15.4% for subjects consuming 1 to 2 cups/wk or 3 cups/wk of coffee were found, respectively (Ptrend < 0.001, Figure 3E). Suggesting caffeine may be associated only with improved sperm motility, which is not accordant to a study carried out in western countries,55,56 the much lower level of coffee intake in the current population may partially explain the difference. Fourth, cola consumption appeared an association with decreased semen volume at 4.1% or 12.5% for 1 to 2 bottles/wk or 3 bottles/wk (Ptrend ¼ 0.024, Figure 3F). Copyright
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Volumey, mL
Sperm concentrationy, million/mL
#
55 (29, 84) 56 (29, 81) 59 (22, NA) >0.05 59 56 56 53
188 (40, 621) 167 (34, 648) 198 (55, NA) >0.05 185 187 158 153
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(43, 693) (35, 548) (36, 618) (34, 608) >0.05 (31, 587) (40, 821) (38, 551) (41, 645) >0.05
162 210 188 170
198 197 167 188
55 54 57 56
55 57 59 60
55 59 57 54
(39, 626) (194, 744) (34, 614) (34, 607) >0.05
174 202 194 164
(31, 84) (18, 82) (32, 82) (28, 84) >0.05
(30, 83) (26, 85) (32, 87) (23, 88) >0.05
(71, 99) (67, 99) (67, 99) (55, 97) >0.05
90 87 90 89
89 90 90 92
88 90 90 88
(70, 98) (65, 99) (69, 99) (65, 99) >0.05
(67, 99) (68, 99) (64, 99) (61, 99) >0.05
(67. 99) (67, 99) (71, 99) (64, 99) >0.05
89 (67, 98) 90 (69, 99) 87 (64, 98) >0.05
91 89 88 82
89 (67, 99) 88 (65, 99) 91 (64, NA) >0.05
89 (67, 99) 88 (63, 98) >0.05
88 (65, 99)
Total motilityy, %
(4.4,16.0) (4.0,13.9) (3.5,14.7) (4.2,14.7) >0.05
8.0 8.2 8.4 8.5
9.4 9.2 8.3 8.5
9.5 8.7 8.4 7.8
(3.5, 14.7) (4.4, 13.9) (3.8, 14.2) (4.5, 14.0) >0.05
(4.0, 13.9) (4.4, 16.0) (4.0, 13.1) (4.2, 16.3) >0.05
(4.1, 14) (3.9, 13.6) (4, 14.8) (4, 12.2) >0.05
8.5 (4.2,13.9) 8.4 (4.0,14.8) 8.0 (4.3,13.9) >0.05
8.5 8.4 8.3 7.5
8.4 (4.0, 14.0) 8.2 (4.4, 13.5) 9.0 (3.3, NA) >0.05
8.4 (4.0, 14.0) 8.4 (4.5, 15.6) >0.05
8.4 (4.0, 14.0)
Normal sperm morphologyy, %
Volume 94, Number 28, July 2015
(29, 83) (27, 81) (32, 84) (28, 86) >0.05
58 (30, 83) 57 (32, 84) 53 (27, 80) 0.05
183 (37, 619) 193 (40, 751) >0.05
(49, 613) (38, 637) (33, 705) (14, 580) >0.05
55 (29, 83)
Progressive motiley, %
184 (38, 627)
Total sperm county, million
Population (n ¼ 794) 3.4 (1.5, 6.7) 54 (14, 194) Race Han (n ¼ 661) 3.4 (1.5, 6.7) 53 (13, 182) 3.2 (1.6, 6.6) 55 (17, 215) Others (other 19 racesz, n ¼ 133) P for trend >0.05 >0.05 Age (with a median of 20 years, 5th and 95th percentile of 19 and 23 years old) 18–20 (477) 3.5 (1.5, 6.6) 54 (13, 192) 21–23 (303) 3.3 (1.6, 6.7) 51 (14, 210) >23 (14) 3.6 (1.5, NA) 64 (16, NA) P for trend >0.05 >0.05 BMIz (with a median of 20.9, 5th and 95th percentile of 17.8 and 26.3) 26.9 (n ¼ 31) 2.9 (1.0, 6.0) 47 (7.5, 233) P for trend >0.05 >0.05 Abstinent duration, d 2–3 (n ¼ 317) 3.1 (1.5, 6.4) 47 (11, 174) 4–5 (n ¼ 259) 3.5 (1.5, 6.4) 57 (16, 163) 6–7 (n ¼ 218) 3.7 (1.8, 7.0) 61 (19, 232) P for trend 0.05 Hot shower Never (n ¼ 146) 3.3 (1.5, 6.4) 55 (13, 201) 2 times/wk (n ¼ 301) 3.3 (1.5, 6.7) 54 (15, 206) P for trend >0.05 >0.05
Variables
TABLE 2. Basic Characteristics and Univariate Correlations Between Semen Parameters and Lifestyles
Medicine Lifestyles and Semen Quality: The MARHCS Study
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6
Sauna experience No (n ¼ 770) Yes (n ¼ 24) P for trend Bicycle riding Never (n ¼ 412) 0.05 209 (40, 761) 175 (37, 593) 154 (35, 505)
54 (13, 200) 55 (14, 183) 52 (21, 226) >0.05 57 (15, 211) 52 (14, 184) 56 (11, 158)
3.4 (1.6, 6.8) 3.1 (1.4, 5.9) 3.6 (1.5, 7.4) >0.05 3.6 (1.7, 6.6) 3.4 (1.5, 6.9) 3.1 (1.4, 5.9)
(30, 87) (27, 83) (31, 83) (34, 84) >0.05
#
54 (28, 80) 57 (30, 84) 71 (28, 91)
(67, 99) (63, 99) (67, 99) (65, 99) >0.05
88 (67, 98) 90 (69, 99) 89 (64, 100)
88 (67, 98) 91 (66, 99) 92 (76, 100) 0.05
89 (65, 99) 82 (52, NA) 90 (70, 99) >0.05
89 (67, 99) 86 (64, 99) 90 (70, 99) >0.05
87 88 88 90
89 (67, 99) 86 (61, 99) >0.05
87 (65, 99) 91 (68, 99) 84 (67, 99) >0.05
88 (65, 99) 88 (49, 98) >0.05
Total motilityy, %
(4.4, 14.9) (4.0, 14.4) (4.4, 13.9) (3.5, 13.9) >0.05
8.5 (4.4, 13.5) 8.4 (3.9, 15.0) 7.9 (4.3, 13.9)
8.3 (4.0, 13.9) 8.7 (4.5, 14.8) 7.7 (3.9, 13.0) >0.05
8.3 (4.0, 14.0) 8.5 (4.4, 13.9) 8.4 (4.0, 14.5) >0.05
8.3 (4.0, 13.7) 5.9 (2.5, NA) 8.5 (4.3, 14.4) >0.05
8.4 (4.0, 14.0) 7.5 (4.1, 12.0) 8.5 (4.0, 14.7) >0.05
8.3 8.4 8.4 8.5
8.4 (4.0, 13.9) 8.6 (3.3, 17.9) >0.05
8.5 (4.0, 14.2) 7.9 (4.0, 13.5) 8.5 (4.7, 14) >0.05
8.3 (4.0, 14.0) 9.9 (4.4, 17.9) 0.05
56 (28, 83) 52 (25, 84) 57 (34, 84) >0.05
55 56 54 59
56 (29, 83) 51 (23, 84) >0.05
54 (28, 83) 58 (30, 84) 51 (28, 83) >0.05
56 (29, 83) 57 (19, 81) >0.05
Progressive motiley, %
Medicine
184 (37, 621) 162 (29, 523) 195 (43, 762) >0.05
54 (14, 200) 50 (10, 138) 57 (17, 228) >0.05
3.4 (1.5, 6.6) 3.2 (1.5, 6.9) 3.6 (1.8, 6.9) >0.05
184 (37, 690) 208 (13, NA) 182 (40, 590) >0.05
192 (40, 654) 186 (26, 834) 155 (33, 567) 0.05
54 (13, 209) 62 (5.8, NA) 53 (15, 164) >0.05
55 (28, 203) 48 (11, 178) 50 (10, 170) >0.05
192 188 178 193
184 (38, 630) 181 (41, 590) >0.05
175 (35, 692) 194 (38, 563) 184 (41, 708) >0.05
184 (38, 621) 185 (36, 881) >0.05
Total sperm county, million
3.4 (1.5, 6.7) 3.8 (0.7, NA) 3.4 (1.6, 6.8) >0.05
3.4 (1.5, 6.8) 3.6 (1.6, 7.4) 3.4 (1.5, 5.8) >0.05
(13, 212) (13, 190) (16, 184) (10, 256) >0.05
51 (14, 189) 56 (12, 173) 57 (16, 243) >0.05
3.4 (1.6, 6.8) 3.4 (1.5, 6.7) 3.0 (1.6, 6.7) >0.05
(1.4, 6.0) (1.6, 6.8) (1.5, 6.7) (1.7, 6.8) >0.05
53 (14, 195) 75 (22, 210) >0.05
Sperm concentrationy, million/mL
3.4 (1.6, 6.7) 3.4 (0.9, 7.0) >0.05
Volumey, mL
Yang et al Volume 94, Number 28, July 2015
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57 (15, 200) 50 (12, 209) 42 (16, 157) 0.05
190 (37, 636) 145 (38, 536) 161 (55, NA) 0.05
56 (29, 83) 56 (29, 84) 57 (34, 84) >0.05
56 (28, 83) 55 (30, 83) 65 (26, 91) >0.05
88 (65, 99) 88 (68, 99) 88 (71, NA) >0.05
90 (67, 99) 88 (67, 99) 89 (69, 98) >0.05
89 (67, 99) 88 (67, 99) 91 (60, 100) >0.05
8.4 (4.0, 14.1) 8.1 (4.0, 13.2) 9.7 (3.5, NA) >0.05
8.5 (4.0, 14.6) 8.0 (4.0, 13.8) 8.5 (4.0, 14.5) >0.05
8.5 (4.0, 14.1) 8.3 (4.5, 13.5) 7.9 (4.0, 14.4) >0.05
>0.05
BMI ¼ body mass index, NA ¼ not available. Two subjects failed to report lifestyles, data from 794 subjects is presented. y Results are presented as median with 5th and 95th percentile. Mann–Whitney U or Jonckheere–Terpstra test was deployed to compare medians between or among groups in each variable. Results in bold characters indicate the variable to be significantly different between/among groups. z The 19 races are Tujia (n ¼ 29), Miao (n ¼ 12), Hazak (n ¼ 10), and other 82 from 16 races including Yi, Zhuang, Dong, Qilao, Meng, Bai, Zang, Chuanqing, Dai, Hui, Kirgiz, Man, She, Shui, Uygur, and Yao. § One subject failed to report chemical fiber underwear use, 1 failed to report alcohol drinking, 2 failed to report motorcycle riding, and 2 failed to report time of keeping seated.
55 (15, 201) 51 (12, 200) 57 (18, 134) >0.05
3.4 (1.6, 6.6) 3.6 (1.5, 6.8) 3.2 (1.4, 6.2) >0.05
