Beneficial effect of residential greenness on sperm quality and the role of air pollution: A multicenter population-based study.

BACKGROUND: Poor sperm quality is a major cause of male infertility. However, evidence remains scarce on how greenness affects male sperm quality. OBJECTIVES: To assess the associations of residential greenness with male sperm quality and the modification effect of air pollution exposure on the relationship. METHODS: A total of 78,742 samples from 33,184 sperm donors from 6 regions across China during 2014-2020 were included and analyzed. Individual residential greenness exposures of study subjects were estimated using the Normalized Difference Vegetation Index (NDVI) during the entire (0-90 lag days) and two key stages (0-37, and 34-77 lag days) of sperm development. Contemporaneous personal exposure levels to air pollutants were estimated using a spatio-temporal deep learning method. Linear mixed models were employed to assess the impact of greenspace in relation to sperm quality. The modification effect of air pollution on the greenspace-sperm quality relationship was also estimated. RESULTS: Per IQR increment in NDVI exposure throughout spermatogenesis were statistically associated with increasing sperm count by 0.0122 (95 % CI: 0.0007, 0.0237), progressive motility by 0.0162 (95 % CI: 0.0045, 0.0280), and total motility by 0.0147 (95 % CI: 0.0014, 0.0281), respectively. Similar results were observed when the model added air pollutants (PM1, PM2.5 or O3) for adjustment. Additionally, specific air pollutants, including PM1, PM2.5, and O3, were found to modify this association. Notably, the protective effects of greenness exposure were more pronounced at higher concentrations of PM1 and PM2.5 and lower concentrations of O3 (all Pinteraction < 0.05). Statistically significant positive effects of NDVI were observed on sperm motility in early spermatogenesis and sperm count in late spermatogenesis. CONCLUSIONS: Exposure to residential greenness may have beneficial effects on sperm quality and air pollution modifies their relationship. These findings highlight the importance of adopting adaptable urban greenspace planning and policies to safeguard male fertility against environmental factors.

Effects of temperature anomaly on sperm quality: A multi-center study of 33,234 men.

Backgrounds: Global fertility rates continue to decline and sperm quality is a prime factor affecting male fertility. Both extreme cold and heat have been demonstrated to be associated with decreased sperm quality, but no epidemiological studies have considered human adaptation to long-term temperature. Our aim was to conduct a multi-center retrospective cohort study to investigate exposure-response relationship between temperature anomaly (TA) that deviate from long-term climate patterns and sperm quality. Methods: A total of 78,952 semen samples measured in 33,234 donors from 6 provincial human sperm banks in China were collected. This study considered heat and cold acclimatization to prolonged exposure in humans and explored the exposure-response relationship between TAs and sperm quality parameters (sperm concentrations, sperm count, progressive motility, progressive sperm count, total motility and total motile sperm count) during the hot and cold seasons, respectively. Linear mixed models and generalized linear models were built separately for specific centers to pool in a meta-analysis to obtain the pooled effect of TA on sperm quality, considering repeated measurements data structure and spatial heterogeneity. Results: We identified an inverted U-shaped exposure-response relationship between TA and sperm quality during the hot season. Significant negative effect of anomalous cold on sperm quality during the hot season was found after additional adjustment for Body mass index, marital status and childbearing history. The heat-related TA in hot season was significantly negatively associated with sperm concentration, progressive sperm count and total motile sperm count (all P-values<0.05). After adjusting the relative humidity, the cold-related TA in cold season was negatively associated with the sperm total motility (P-values<0.05). Conclusions: Our results suggest both heat-related and cold-related TAs are associated with decreased sperm quality. The findings highlight the importance of reducing exposure to anomalous temperatures to protect male fertility.

Exposure to Fine Particulate Matter Constituents and Human Semen Quality Decline: A Multicenter Study.

Exposure to fine particulate matter (PM < 2.5 µm in diameter [PM2.5]) may accelerate human sperm quality decline, although research on this association is limited. Our objective was to investigate the relationship between exposure to the chemical constituents of PM2.5 air pollution and decreased sperm quality and to further explore the exposure-response relationship. We conducted a multicenter population-based cohort study including 78,952 semen samples from 33,234 donors at 6 provincial human sperm banks (covering central, northern, southern, eastern, and southwestern parts of China) between 2014 and 2020. Daily exposure to PM2.5 chemical composition was estimated using a deep learning model integrating a density ground-based measure network at a 1 km resolution. Linear mixed models with subject- and center-specific intercepts were used to quantify the harmful impacts of PM2.5 constituents on semen quality and explore their exposure-response relationships. Per interquartile range (IQR) increase in PM2.5 exposure levels during spermatogenesis was significantly associated with decreased sperm concentration, progressive motility, and total motility. For PM2.5 constituents, per IQR increment in Cl- (ß: -0.02, 95% CI: [-0.03, -0.00]) and NO3- (ß: -0.05, 95% CI: [-0.08, -0.02]) exposure was negatively associated with sperm count, while NH4+ (ß: -0.03, 95% CI: [-0.06, -0.00]) was significantly linked to decreased progressive motility. These results suggest that exposure to PM2.5 chemical constituents may adversely affect human sperm quality, highlighting the urgent need to reduce PM2.5 exposure.

Sperm quality decline associated with gaseous pollutant exposure: Evidence from a large cohort multicenter study.

BACKGROUND: Poor sperm quality is a prevalent cause of male infertility, and the association between gaseous ambient air pollutants exposure and semen quality remains unclear. OBJECTIVES: To examine the relationship between gaseous air pollution exposure with semen quality in a large-scale and multi-center study. METHODS: We analyzed 78,952 samples corresponding to 33,234 study subjects from 2014 to 2020. The high-resolution grid pollution dataset was used to estimate personal exposures to CO, SO2, NO2 and O3 across entire stage of semen formation and three crucial stages. The linear mixed models were performed to evaluate the relationships. RESULTS: The results showed that sperm count was inversely related to SO2 exposure (-0.0070, -0.0128 to -0.0011). Decreased sperm concentration was associated with SO2 (-0.0083, -0.0142 to -0.0024), NO2 (-0.0162, -0.0320 to -0.0005) and O3 (-0.0306, -0.0480 to -0.0133) during 0-90 lag days, respectively. Additionally, we observed significant decline of PR and total motility with SO2 exposure. Similar trends were observed for SO2 and CO exposure during 3 key periods. CONCLUSIONS: Our findings suggest that exposure to gaseous air pollutants may have negative impacts on sperm quality. These findings highlight the importance that critical periods of sperm development should be considered when implementing protective measures.

Dengue transmission dynamics prediction by combining metapopulation networks and Kalman filter algorithm.

Predicting the specific magnitude and the temporal peak of the epidemic of individual local outbreaks is critical for infectious disease control. Previous studies have indicated that significant differences in spatial transmission and epidemic magnitude of dengue were influenced by multiple factors, such as mosquito population density, climatic conditions, and population movement patterns. However, there is a lack of studies that combine the above factors to explain their complex nonlinear relationships in dengue transmission and generate accurate predictions. Therefore, to study the complex spatial diffusion of dengue, this research combined the above factors and developed a network model for spatiotemporal transmission prediction of dengue fever using metapopulation networks based on human mobility. For improving the prediction accuracy of the epidemic model, the ensemble adjusted Kalman filter (EAKF), a data assimilation algorithm, was used to iteratively assimilate the observed case data and adjust the model and parameters. Our study demonstrated that the metapopulation network-EAKF system provided accurate predictions for city-level dengue transmission trajectories in retrospective forecasts of 12 cities in Guangdong province, China. Specifically, the system accurately predicts local dengue outbreak magnitude and the temporal peak of the epidemic up to 10 wk in advance. In addition, the system predicted the peak time, peak intensity, and total number of dengue cases more accurately than isolated city-specific forecasts. The general metapopulation assimilation framework presented in our study provides a methodological foundation for establishing an accurate system with finer temporal and spatial resolution for retrospectively forecasting the magnitude and temporal peak of dengue fever outbreaks. These forecasts based on the proposed method can be interoperated to better support intervention decisions and inform the public of potential risks of disease transmission.

The size of the susceptible pool differentiates climate effects on seasonal epidemics of bacillary dysentery.

OBJECTIVES: At present, some studies have pointed out several possible climate drivers of bacillary dysentery. However, there is a complex nonlinear interaction between climate drivers and susceptible population in the spread of diseases, which makes it challenging to detect climate drivers at the size of susceptible population. METHODS: By using empirical dynamic modeling (EDM), the climate drivers of bacillary dysentery dynamic were explored in China's five temperature zones. RESULTS: We verified the availability of climate drivers and susceptible population size on bacillary dysentery, and used this information for bacillary dysentery dynamic prediction. Moreover, we found that their respective effects increased with the increase of temperature and relative humidity, and their states (temperature and relative humidity) were different when they reached their maximum effects, and the negative effect between the effect of temperature and disease incidence increased with the change of temperature zone (from temperate zone to warm temperate zone to subtropical zone) and the climate driving effect of the temperate zone (warm temperate zone) was greater than that of the colder (temperate zone) and warmer (subtropics) zones. When we viewed from single temperature zone, the climatic effect arose only when the size of the susceptible pool was large. CONCLUSIONS: These results provide empirical evidence that the climate factors on bacillary dysentery are nonlinear, complex but dependent on the size of susceptible populations and different climate scenarios.

Impacts of traffic-related particulate matter pollution on semen quality: A retrospective cohort study relying on the random forest model in a megacity of South China.

BACKGROUND: Emerging evidence shows the detrimental impacts of particulate matter (PM) on poor semen quality. High-resolution estimates of PM concentrations are conducive to evaluating accurate associations between traffic-related PM exposure and semen quality. METHODS: In this study, we firstly developed a random forest model incorporating meteorological factors, land-use information, traffic-related variables, and other spatiotemporal predictors to estimate daily traffic-related PM concentrations, including PM2.5, PM10, and PM1. Then we enrolled 1310 semen donors corresponding to 4912 semen samples during the study period from January 1, 2019, and December 31, 2019 in Guangzhou city, China. Linear mixed models were employed to associate individual exposures to traffic-related PM during the entire (0-90 lag days) and key periods (0-37 and 34-77 lag days) with semen quality parameters, including sperm concentration, sperm count, progressive motility and total motility. RESULTS: The results showed that decreased sperm concentration was associated with PM10 exposures (ß: -0.21, 95 % CI: -0.35, -0.07), sperm count was inversely related to both PM2.5 (ß: -0.19, 95 % CI: -0.35, -0.02) and PM10 (ß: -0.19, 95 % CI: -0.33, -0.05) during the 0-90 days lag exposure window. Besides, PM2.5 and PM10 might diminish sperm concentration by mainly affecting the late phase of sperm development (0-37 lag days). Stratified analyses suggested that PBF and drinking seemed to modify the associations between PM exposure and sperm motility. We did not observe any significant associations of PM1 exposures with semen parameters. CONCLUSION: Our results indicate that exposure to traffic-related PM2.5 and PM10 pollution throughout spermatogenesis may adversely affect semen quality, especially sperm concentration and count. The findings provided more evidence for the negative associations between traffic-related PM exposure and semen quality, highlighting the necessity to reduce ambient air pollution through environmental policy.

Effect of ambient temperature variability on sperm quality: A retrospective population-based cohort study.

BACKGROUNDS: Abnormal sperm quality in men is one of the common causes of infertility. Both ambient temperature and extreme heat exposure have been shown to be associated with sperm quality, but there is no epidemiological evidence for the effect of ambient temperature variability. Our aim was to investigate the association between ambient temperature variability exposure and a decline in sperm quality at different stages of sperm development. METHODS: A total of 4912 semen samples collected from the Guangdong Human Sperm Bank between 1 January 2019 and 31 December 2019 were analyzed. We selected three exposure periods: the full-stage (0-90 lag days), early-stage (34-77 lag days) and late-stage (0-37 lag days) of sperm development, and then calculated the standard deviation of daily temperature (TVSD), the maximum day-to-day temperature difference (TVDmax) and the mean day-to-day temperature difference (TVDmean) for the three exposure periods. A linear mixed model was used to explore the exposure response relationship between temperature variability exposure and sperm quality indicators (including sperm concentration, sperm count and sperm motility). RESULTS: There was a significant negative association of decreased sperm count with the exposure to temperature variability during 0-90 days prior to sperm collection. (TVDmax: -0.041; -0.063, -0.019; TVDmean: -0.237; -0.386, -0.088; TVSD: -0.103; -0.196, -0.011). We observed a significant association between the decline in sperm concentration, sperm count and per 1 °C increase in TVDmean during early spermatogenesis. No significant association of temperature variability with sperm motility was found. CONCLUSIONS: The results indicate that exposure to temperature variability during the entire period of sperm development is significantly associated with a decline in sperm counts. We found that mean day-to-day temperature differences had a detrimental effect on sperm counts in the early-stage. Our findings provide a scientific basis for public health policy and further mechanistic studies.