Background: Few epidemiological investigations have focused on the influence of environmental temperature on human sperm quality. Here, we evaluated the potential association between ambient temperature and human sperm quality in Wuhan, China, and examined the interactive effect of particulate matter (PM_2.5) and temperature. Methods: 1780 males who had been living in Wuhan for no less than three months and received semen analysis at the Department of Reproductive Medicine in Renmin Hospital of Wuhan University between April 8, 2013 and June 30, 2015 were recruited. Daily mean meteorological data and air pollution data (PM_2.5, O₃ and NO₂) in Wuhan between 2013 and 2015 were collected. A generalized linear model was used to explore the associations between ambient temperature and sperm quality (including sperm concentration, percentage of normal sperm morphology, and progressive motility) at 0–9, 10–14, 15–69, 70–90, and 0–90 days before semen examination, and the interaction between temperature and PM_2.5. Results: The associations between ambient temperature and sperm quality were an inverted U-shape at five exposure windows, except for a lag of 0–9 days for sperm concentration. A 1 °C increase in ambient temperature above the thresholds was associated with a 2.038 (1.292 ~ 2.783), 1.814 (1.217 ~ 2.411), 1.458 (1.138 ~ 1.777), 0.934(0.617 ~ 1.251) and 1.604 (1.258 ~ 1.951) decrease in the percentage of normal sperm morphology at lag 0–9, lag 10–14, lag 15–69, lag 70–90, and lag 0–90 days, respectively. The interaction p-values of PM_2.5 and temperature were mostly less than 0.05 at five exposure windows. When ambient temperature exposure levels were above the thresholds, a 0.979 (0.659–1.299) and 3.559 (0.251 ~ 6.867) decrease in percentage of normal sperm morphology per 1 °C increase in temperature at lag 0–90 days was observed in the PM_2.5 ≤ P₅₀ group and PM_2.5 > P₅₀ group, respectively. Conclusions: Our results indicate that exposure to ambient temperature has a threshold effect on sperm quality, and PM_2.5 enhances the effect of temperature on sperm quality when temperatures are above the threshold.

Wuhan encountered a serious attack in the first round of the coronavirus disease 2019 (COVID-19) pandemic, which has resulted in a public health social impact, including public mental health. Based on the Weibo help data, we inferred the spatial distribution pattern of the epidemic situation and its impacts. Seven urban factors, i.e., urban growth, general hospital, commercial facilities, subway station, land-use mixture, aging ratio, and road density, were selected for validation with the ordinary linear model, in which the former six factors presented a globally significant association with epidemic severity. Then, the geographically weighted regression model (GWR) was adopted to identify their unevenly distributed effects in the urban space. Among the six factors, the distribution and density of major hospitals exerted significant effects on epidemic situation. Commercial facilities appear to be the most prevalently distributed significant factor on epidemic situation over the city. Urban growth, in particular the newly developed residential quarters with high-rise buildings around the waterfront area of Hanyang and Wuchang, face greater risk of the distribution. The influence of subway stations concentrates at the adjacency place where the three towns meet and some near-terminal locations. The aging ratio of the community dominantly affects the hinterland of Hankou to a broader extent than other areas in the city. Upon discovering the result, a series of managerial implications that coordinate various urban factors were proposed. This research may contribute toward developing specific planning and design responses for different areas in the city based on a better understanding of the occurrence, transmission, and diffusion of the COVID-19 epidemic in the metropolitan area.

Background. Few studies have explored the relationship between the level of physical activity and the occurrence or prevalence of obesity and hypertension among people residing in urbanised areas. Method. A cross-sectional study involving a sample of 1,001 adults was conducted. Descriptive statistics were used to describe sociodemographic variables, physical activity levels, body mass index (BMI), and prevalence of hypertension. Logistic regression models were adopted to investigate the relationship between these factors. Results. A total of 939 respondents who provided valid responses were included. Among them, 56.5 of the participants reported engaging in high levels of physical activity. However, 40.4 of the respondents were classified as overweight or obese, and 31.9 had diagnosed hypertension. After adjusting for sociodemographic factors, logistic regression analysis revealed that physical activity levels were negatively correlated with the prevalence of BMI (OR=0.564, 95 CI: 0.3520.905; OR=0.583, 95 CI: 0.3750.907) and hypertension (OR=0.556, 95 CI: 0.3480.888). Conclusions. Our study confirms recent evidence regarding the amount of physical activity that is associated with lower prevalence of obesity and hypertension in Pingshan District. Furthermore, different physical activities of various intensity levels had different effects on hypertension. Residents should be encouraged to engage in physical activities and maintain a healthy weight to improve their quality of life.

Amid rapid urbanisation, the health effects of the built-environment have been widely studied, while research on elderly-supportive infrastructure and its interaction with PM_2.5 (PM, Particulate Matter) exposure remains limited. To examine the effect of PM_2.5 on cardiovascular hospitalisation risk among the elderly and the moderating role of elderly-supportive infrastructure in Wuhan, a city undergoing rapid urbanisation. A time-stratified case-crossover design was adopted in which the K-means cluster analysis was applied to categorize elderly-supportive infrastructure. The correlation of PM_2.5 with cardiovascular hospitalisations and the moderating role of elderly-supportive infrastructure were elucidated through the conditional logistic regression and z-test. Nonlinear relationships among variables were determined using restricted cubic splines. 173,486 case days and 589,188 control days were included. The cumulative lag effect of PM_2.5 increased over time, peaking at 5 days. For every 10 µg/m³ increase in PM_2.5, the risk of hospitalisation rose by 1.5% (OR = 1.0150, 95% CI: 1.0113-1.0190). The aforementioned effect of PM_2.5 exposure on health did not differ among varying levels of elderly-supportive infrastructure within a 300 m buffer zone. When the buffer zone was extended to 500 and 1000 m, a higher level of elderly-supportive infrastructure mitigated the adverse effects of short-term PM_2.5 exposure on cardiovascular hospitalisations (p = 0.013), particularly for stroke (p = 0.017) and ischaemic heart disease (p = 0.026). Our findings suggest that high-level elderly-supportive infrastructure may protect against the adverse effects of PM_2.5 on cardiovascular hospitalisation, highlighting the need to optimize elderly-supportive infrastructure for its health benefits in the elderly.