Table 3.
Source | Exposure assessment | Outcome measured | Confounders | Statistical analysis | Main faindings | Limitations | Strengths |
---|---|---|---|---|---|---|---|
Santi, et al. 2016 [25] | PM10 (μg/m3) | Volume, concentration (× 106/mL), total number, typical forms (%), atypical forms (%), progressive motility (%), non-progressive motility (%), total motility (%), leucocytes | Temperature, humidity | Bivariate and multivariate logistic regression models | PM2.5 was directly related to total sperm number (p = 0.001); PM10 was directly related to semen volume (p < 0.001) and typical forms (p < 0.001), inversely related to atypical forms (p < 0.001) | No information about smoking; Daily PM exposure registered through the monitoring network of the quality of the air for the province of Madena; the relationship between environmental PM and semen quality was evaluated irrespective of the life-style and risk factors of each men | The cohort is highly representative of the entire population; Choosing the coldest season of the year in this area (the possible negative influence of high ambient temp. on sperm quality was excluded); |
PM2.5 (μg/m3) | |||||||
Wu, et al. 2016 [27] | PM10 (μg/m3) | Concentration(×106/mL), sperm count, total motility (%), progressive motility (%), | Age, BMI, ethnic, education, smoking, drinking, abstinence, season, average ambient temperature | Multivariate linear mixed models | PM2.5 was inversely associated with sperm concentration (β = −0.20; (95%CI: − 0.34, − 0.07) and sperm count (β = − 0.22; 95%CI: − 0.35, − 0.08); PM10 was inversely associated with sperm concentration and count (p < 0.05) | The used of ambient PM exposures as a proxy for individual exposures; No investigation of the association between exposure and sperm morphology; the results cannot be directly generalized to populations in which PM exposure levels are too low; Participants from infertility clinic | Big sample size; A wide concentration range of PM exposure; the use of IDW interpolation to more precisely estimate individual PM exposure; the non-linear exposure-response relationships |
PM2.5 (μg/m3) | |||||||
Radwan, et al. 2016 [23] | PM10 | Concentration (× 106/mL), motility (%), sperm with abnormal morphology (%), DFI(%), HDS(%), CASA parameters: VSL, VCL, LIN; FSH, E2, T | Age, smoking, temperature (men from 90 days), past disease, time of sexual abstinence, season | Multivariate linear regression | Exposure to air pollutants (PM10, PM2,5, SO2, NOx, CO) increased the abnormalities in sperm morphology (p = 0.0002, p = 0.0001, p = 0.0001, p = 0.01, p = 0.0001, respectively); Negative association were found between air pollutants and testosterone levels (p < 0.05); There were a positive associations between PM10 and PM2,5 and HDS (p = 0.002, p = 0.0001, respectively) | participants from an infertility clinic; single semen sample; exposure levels assessed by considering the ZIP code of each participants; | Assessment of many different semen parameters, reproductive hormones levels and sperm chromatin structure; detailed questionnaire information allowed for control confounding factors in the analysis; cotinine measured in saliva to verified smoking status; |
PM2.5 | |||||||
SO2 | |||||||
CO | |||||||
NOx | |||||||
Jurewicz, et al. 2015 [34] | PM10 (μg/m3) | Sperm aneuploidy, sperm concentration (×106/mL), total motility (%), abnormal morphology (%) | Age, smoking, drinking, temperature, season, past disease, abstinence interval, distance from monitoring station, concentration, motility, morphology, PM10, SO2 | multivariate analysis | There was a positive association between exposure to PM2.5 and disomy Y (p = 0.001), sex chromosome disomy (p = 0.05), disomy of chromosome 21 (p = 0.03); xposure to PM10 was associated with disomy 21 (p = 0.02) | Exposure levels assessed by considering the ZIP code of each participants; participants from an infertility clinic; single semen sample; | Many confounders included to the analysis; cotinine measured in saliva to verified smoking status; detailed questionnaire information allowed for control confounding factors in the analysis, |
PM2.5 (μg/m3) | |||||||
O3 (μg/m3) | |||||||
SO2 (μg/m3) | |||||||
CO (μg/m3) | |||||||
NOx (μg/m3) | |||||||
Radwan, et al. 2015 [35] | 1 PAH metabolite in urine (1-OHP) | Sperm aneuploidy, sperm concentration (× 106/mL), total motility (%), normal sperm morphology (%), | Abstinence, age, smoking, season, past disease, | Multivariate analysis | Positive associations between level of 1-OHP in urine and total sex-chromosome disomy (p = 0.03); An increase in the frequency of disomy 18 was related to the level of 1-OHP in urine (p = 0.03) | participants from an infertility clinic; single semen sample; one biomarker of PAHs exposure- 1-hydroksypyrene (1-OHP) | cotinine measured in saliva to verified smoking status; detailed questionnaire information allowed for control confounding factors in the analysis, |
Zhou, et al. 2014 [21] | PM10 (μg/m3) | Volume, concentration (×106/mL), progressive motility (%), total motility, morphology (normal forms %), CASA sperm motility parameters (VCL, VSL, VAP, BCF, ALH, LIN, STR) | Age, education, smoking, drinking, BMI, abstinence, season, | Multivariate regression models | PM10, SO2, NO2 were negatively associated with a normal sperm morphology percentage (p < 0.001); there were inverse associations between sperm VCL and VSL value and PM10, SO2, NO2 (p < 0.001); PM10 was positively associated with sperm concentration (p = 0.031) | Used of monitoring data for the study sites to measure ambient air pollution; the measurement and prediction of PM10, SO2, NO2 exposure were performed outside; the used only a single semen sample | Big sample size; Exposure to air pollutants in both urban and rural areas; The use of mean concentration of each pollutant during the 90 days before sampling; Many confounders including to the analyses |
SO2 (μg/m3) | |||||||
NO2 (μg/m3) | |||||||
Jurewicz, et al. 2013 [24] | 1 PAH metabolite in urine (1-OHP) | Volume, concentration (×106/mL), motility (%), atypical sperm (%),static sperm (%), DFI (%), CASA parameters: VAP, VSL, VCL, BCF, ALH, | Age, smoking, past disease, season, sexual abstinence, | Multivariate regression models | A positive associations were observed between the level of 1-OHP in urine and sperm neck abnormalities (p = 0.001) and a negative between the semen volume (p = 0.014), %motility (p = 0.0001) and %static sperm (p = 0.018); | Participants from an infertility clinic; single urine and semen sample; one biomarker of PAHs exposure- 1-hydroksypyrene (1-OHP) | cotinine measured in saliva to verified smoking status; detailed questionnaire information allowed for control confounding factors in the analysis, |
Song, et al. 2013 [22] | 16 PAHs in blood | Concentration (× 106/mL), volume, motility (grade A, grade B, grade C) | – | The Pearson correlation analysis | Significant correlations between PAHs in blood and semen motility were observed (p < 0.01) | Small sample size; participants from infertility clinic; No investigation of the association between PAH exposure and semen morphology; | 16 PAH metabolites as a biomarkers of exposure to PAH; |
Han, et al. 2011 [31] | 4 PAH metabolites in urine | Apoptotic marker (Annexin V−/PI− spermatozoa %, Annexin V+/PI− spermatozoa %, PI+ spermatozoa %, comet parameters (tail%, tail length, TDM) | Age, BMI, abstinence, smoking, drinking, grilled and smoked foods ingestions | Multivariate regression models | 2-OHNa levels were associated with increased comet parameters including tail% (β = 13.26% per log unit 2-OHNa; 95%CI: 7.97–18.55), tail length (β = 12.25; 95%CI: 0.01–24.52) and tail distribution (β = 7.55; 95%CI: 1.28–18.83); 1-OHP was associated with increased tail% (β = 5.32; 95%CI: 0.47–10.17); urinary PAH metabolites were associated with decreased vital Annexin V negative sperm count; | Single urine sample; the use of biomarkers didn’t allow for determination of primary exposure sources; | Urinary PAH metabolites as biomarkers of PAH exposure; Assessing 4 metabolites individually; Participants recruited only during the winter when air pollution is higher); many confounders including in the analyses; |
1-OHP | |||||||
9-OHPh | |||||||
2-OHFIu | |||||||
2-OHNa | |||||||
Hammoud, et al. 2010 [20] | PM2.5 (μg/m3) | Motility, concentration (×106/mL), morphology (normal forms %) | Temperature, season | Multivariate regression models | PM2.5 was negatively associated with sperm motility 2 months and 3 months following the recording of the PM2.5 values (p = 0.010 and p = 0.044, respectively) | Participants from andrology laboratory; occupational exposure didn’t include in the analysis | Repeated semen samples; big sample size; The analyses of daily levels of PM2.5 over the 5 years; |
Hansen, et al. 2010 [19] | O3 (ppb) | Concentration (× 106/mL), count, morphology (normal forms %), abnormal morphology (%), abnormal head (%), abnormal midsection (%), abnormal tail (%), cytoplasmic droplets (%), CMA (%), DFI (%) | Age, abstinence, education levels, smoking, season, temperature | Multivariate regression models | Exposures to O3 or PM2.5 at least below the current National Ambient Air Quality Standards were not associated with decrements in sperm outcomes. | Small sample size; single semen sample; | Many confounders including in the analysis; |
PM2.5 (μg/m3) | |||||||
Xia, et al. 2009a [28] | 4 PAH metabolites in urine | Volume, concentration (×106/mL), sperm number per ejaculum, sperm motility | Age, abstinence time, | Logistic regression analysis | Men with higher urinary concentrations of 1-OHP, 2-OHP and Sum PAH metabolites were more likely to have idiopathic male infertility (p for trend = 0.034) | Single semen sample; No investigation of the association between PAH exposure and semen morphology; | Big sample size; Urinary PAH metabolites as biomarkers of PAH exposure; men with idiopathic infertility were divided into ‘normal’ and ‘abnormal’ semen quality group |
1-N | |||||||
2-N | |||||||
1-OHP | |||||||
2-OHF | |||||||
Xia, et al. 2009b [29] | 4 PAH metabolites in urine | Volume, concentration (× 106/mL), sperm number per ejaculum, sperm motility | No information-based on abstract | No information-based on abstract | Men with higher 1-OHP (assessed as quintiles) were likely to have below-reference sperm concentration and sperm number per ejaculum. | No information-based on abstract | No information-based on abstract |
1-N | |||||||
2-N | |||||||
1-OHP | |||||||
2-OHF | |||||||
Rubes, et al. 2007 [32] | SO2 (μg/m3) | %DFI GSTM1 genotype |
Smoking | Mixed models | Association between GSTM1 null genotype and increased %DFI (beta = 0.309; 95% CI: 0.129, 0.489). Furthermore, GSTM1 null men also showed higher %DFI in response to exposure to intermittent high air pollution (beta = 0.487; 95% CI: 0.243, 0.731) | Small sample size; Single semen sample; only one confounder included to the analysis; |
Novel evidence for a gene-environment interaction between GSTM1 and air pollution; |
NOX (μg/m3) | |||||||
PM10 (μg/m3) | |||||||
PAH (ng/m3) | |||||||
Sokol, et al. 2006 [18] | O3 (ppb) | Concentration (×106/mL), motility (×106) | Temperature, seasonality, age of donation, date of birth | Linear mixed-effects model | Negative association between ozone and sperm concentration (p < 0.01); | Small sample size; No investigation of the association between air pollution exposure and semen morphology; | Repeated semen samples; |
NO2 (ppb) | |||||||
CO (ppm) | |||||||
PM10 (μg/m3) | |||||||
Rubes, et al. 2005 [26] | SO2 (μg/m3) | Count, concentration (× 106/mL), volume, motility (%), normal sperm head morphology (%), normal morphology (%), straight line velocity, curvilinear velocity, linearity, DFI% | Smoking, drinking, caffeine, abstinence, fever, briefs, | Mixed models for repeated measures | Significant association between high air pollution and %DFI (β = 0.19; 95%CI: 0.02–0.36); Other semen measures were not associated with air pollution; | Small sample size; | Urine sample were assayed for cotinine to confirm self-reported smoking status; Blood sample was collected for analysis of lead, mercury and cadmium as an indication of possible exposure to metals; Air pollution categorized as low and high; semen samples classify as a “winter” or “summer” sample |
NOx (μg/m3) | |||||||
PM10 (μg/m3) | |||||||
PAH (ng/ m3) | |||||||
Selevan, et al. 2000 [17] | PM10 (μg/m3) | Semen volume, concentration (×106/mL), total count, motility (%), total progressive, normal morphology (%), normal heads (%), VSL, VCL, LIN, sperm chromatin structure | Abstinence, wearing briefs, caffeine, high fever, work and hobbies with metal, work and hobbies with solvents, season | Multivariate regression models | Significant associations between medium air pollution and %motile sperm (β = −8.12; 95%CI: −12.95, −3.30); between medium air pollution and progressive motility (β = −0.15; 95%CI: −0.30, −0.01); Negative association between medium and high air pollution and %normal morphology (β = − 0.42; 95%CI: − 0.69, − 0.14 and β = − 0.84; 95%CI: − 1.15, − 0.53); High air pollution was associated with parameters of sperm motion – VSL, VCL, LIN (p < 0,005) | Single semen sample; Data about air pollution from the air monitoring program; | Air pollution categorized as low, medium and high; Many confounders included to the analysis |
SO2 (μg/m3) | |||||||
CO (mg/m3) | |||||||
NOx (μg/m3) | |||||||
Robbins, et al. 1999 [33] | SO2 | aneuploidy | Alcohol, caffeine intake, fever, laboratory variables | Poisson regression modeling | The sex chromosomal aneuploidy YY was associated with exposure to high air pollution IRR = 5.25, 95%CI: 2.5,11.0 | No information-based on abstract | No information-based on abstract |
Occupational exposure | |||||||
Calogero, et al. 2011 [37] | NOx (μg/m3) | LH, FSH, T, sperm concentration (×106/mL), total sperm count, total motility, progressive motility (%), normal form (%), sperm chromatin integrity; DFI (%) | Age, length of occupational exposure, smoking | Multivariate regression models; | Motorway tollgate workers had a significantly higher %spermatozoa with damage chromatin (p < 0.001) compared with controls, likewise the %spermatozoa with fragmented DNA; late sign of apoptosis was also significantly higher in tollgate workers (p < 0.001); sperm concentration, total sperm count, total and progressive motility, and normal form were significantly lower in tollgate workers compared with controls (p < 0.05) | Small sample size; | blood levels of MHb, SHb, COHb, Pb as a biological biomarkers of environmental pollution; the air pollution was measured with specific analyzers 24 h/day for 30 days during summer; |
SOx (μg/m3) | |||||||
Boggia, et al. 2009 [38] | NO2 (μg/m3) | FSH, LH, T, sperm count, motility, morphology, | Fuel combustion gases | Negative association between men occupationally exposed to NO2 and total motility (p < 0.05) | No individual estimations of exposure; | Cross-sectional design | |
Guven, et al. 2008 [36] | diesel | Concentration (×106/mL), motility, morphology | – | student’s t-test, Mann-Whitney U-test; | The differences regarding the abnormal sperm count and motility were significant between the study group and control group (p = 0.002 and p = 0.003, respectively); the ratio of sperm cells with normal morphology was significantly lower in the study group (p = 0.001) | Small sample size; No individual estimations of exposure; | Cross-sectional design |
De Rosa, et al. 2003 [39] | CO (mg/m3) | FSH, LH, T, sperm count, volume, motility, morphology, sperm membrane function, forward progression, sperm kinetics: VSL, VCL, LIN, ALH, | student’s t-test; linear regression analysis | Total motility, forward progression, functional test and sperm kinetic were significantly lower in tollgate workers vs. controls (p < 0.0001) | Small sample size; No individual estimations of exposure | blood levels of MHb, SHb, COHb, Pb, Zn as a biological biomarkers of environmental pollution; | |
NO (mg/m3) | |||||||
SO (μg/m3) | |||||||
Pb (μg/m3) |
PM10 particulate matter < 10 μm, PM2,5 particulate matter < 2,5 μm, O3 ozone, SOx sulphur oxides, CO carbon monoxide, NOx nitrogen oxides, PAH polycyclic aromatic hydrocarbons, 1-OHP 1-hydroxypyrene, Pb lead, Cd – cadmium, 1-N 1-hydroxynapthalene, 2-N 2-hydroxynapthalene, 1-OHP 1-hydroxypyrene, 2-OHF 2-hydroxyfluorene, VCL curvilinear velocity, VSL straight line velocity, VAP average path velocity, BCF beat cross frequency, ALH amplitude of lateral head displacements, %DFI percentage of sperm with fragmented DNA, %HDS high DNA stainability, LIN linearity, STR straightness, grade A sperm with progressive motility, grade B nonlinear motility, grade c non-progressive motility, TDM tail distributed moment, %CMA percentage of sperm chromatin maturity, LH luteinizing hormone, FSH follicle-stimulating hormone, T testosterone, E2 estradiol, MHb methahaemoglobin, SHb sulphahaemoglobin, COHb carboxyhaemoglobin, IDW interpolation inverse distance weighting (Shepard’s method)