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.

Air Pollutants and Mortality Risk in Patients with Aortic Dissection: Evidence from a Clinical Cohort, Single-Cell Sequencing, and Proteomics.

We aimed to evaluate the association between air pollutants and mortality risk in patients with acute aortic dissection (AAD) in a longitudinal cohort and to explore the potential mechanisms of adverse prognosis induced by fine particulate matter (PM2.5). Air pollutants data, including PM2.5, PM10.0, nitrogen dioxide (NO2), carbon monoxide (CO), sulfur dioxide (SO2), and ozone (O3), were collected from official monitoring stations, and multivariable Cox regression models were applied. Single-cell sequencing and proteomics of aortic tissue were conducted to explore the potential mechanisms. In total, 1,267 patients with AAD were included. Exposure to higher concentrations of air pollutants was independently associated with an increased mortality risk. The high-PM2.5 group carried approximately 2 times increased mortality risk. There were linear associations of PM10, NO2, CO, and SO2 exposures with long-term mortality risk. Single-cell sequencing revealed an increase in mast cells in aortic tissue in the high-PM2.5 exposure group. Enrichment analysis of the differentially expressed genes identified the inflammatory response as one of the main pathways, with IL-17 and TNF signaling pathways being among the top pathways. Analysis of proteomics also identified these pathways. This study suggests that exposure to higher PM2.5, PM10, NO2, CO, and SO2 are associated with increased mortality risk in patients with AAD. PM2.5-related activation and degranulation of mast cells may be involved in this process.

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.

Persistence of severe global inequalities in the burden of blindness and vision loss from 1990 to 2019: findings from the Global Burden of Disease Study 2019.

AIMS: To assess the global burden and economic inequalities in the distribution of blindness and vision loss between 1990 and 2019. METHODS: A secondary analysis of the Global Burden of Diseases, Injuries and Risk Factors Study (GBD) 2019. Data for disability-adjusted life-years (DALYs) due to blindness and vision loss were extracted from the GBD 2019. Data for gross domestic product per capita were extracted from the World Bank database. Slope index of inequality (SII) and concentration index were computed to assess absolute and relative cross-national health inequality, respectively. RESULTS: Countries with high, high-middle, middle, low-middle and low Socio-demographic Index (SDI) had decline of age-standardised DALY rate of 4.3%, 5.2%, 16.0%, 21.4% and 11.30% from 1990 to 2019, respectively. The poorest 50% of world citizens bore 59.0% and 66.2% of the burden of blindness and vision loss in 1990 and 2019, respectively. The absolute cross-national inequality (SII) fell from -303.5 (95% CI -370.8 to -236.2) in 1990 to -256.0 (95% CI -288.1 to -223.8) in 2019. The relative inequality (concentration index) for global blindness and vision loss remained essentially constant between 1991 (-0.197, 95% CI -0.234 to -0.160) and 2019 (-0.193, 95% CI -0.216 to -0.169). CONCLUSION: Though countries with middle and low-middle SDI were the most successful in decreasing burden of blindness and vision loss, a high level of cross-national health inequality persisted over the past three decades. More attention must be paid to the elimination of avoidable blindness and vision loss in low-income and middle-income countries.

Associated adverse health outcomes of polypharmacy and potentially inappropriate medications in community-dwelling older adults with diabetes.

Aim: This study aimed to identify the association of chronic polypharmacy and potentially inappropriate medications (PIMs) with adverse health outcomes (AHOs) in community-dwelling older adults with diabetes in China. Methods: A 2-year retrospective cohort study was conducted using 11,829 community-followed older adults with diabetes and medical records from 83 hospitals and 702 primary care centers in Shenzhen, China. Chronic polypharmacy and PIMs were identified from prescription records using Beers' criteria, and their associated AHO was analyzed using multivariable logistic regression analysis. Results: The prevalence of chronic polypharmacy and at least one PIM exposure was 46.37% and 55.09%, respectively. The top five PIMs were diuretics, benzodiazepines, first-generation antihistamines, sulfonylureas, and insulin (sliding scale). Chronic polypharmacy was positively associated with all-cause hospital admission, admission for coronary heart disease, admission for stroke, admission for dementia, and emergency department visits. Exposure to PIMs was positively associated with all-cause hospital admission, admission for heart failure (PIMs ≥2), admission for stroke (PIMs ≥3), emergency department visits, bone fracture, constipation, and diarrhea. Conclusion: Chronic polypharmacy and PIMs were prevalent in older adults with diabetes in Chinese communities. Iatrogenic exposure to chronic polypharmacy and PIMs is associated with a higher incidence of different AHOs. This observational evidence highlights the necessity of patient-centered medication reviews for chronic polypharmacy and PIMs use in older patients with diabetes in primary care facilities in China and draws attention to the caution of polypharmacy, especially PIM use in older adults with diabetes in clinical practice.

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.

Machine-learning predictive model of pregnancy-induced hypertension in the first trimester.

In the first trimester of pregnancy, accurately predicting the occurrence of pregnancy-induced hypertension (PIH) is important for both identifying high-risk women and adopting early intervention. In this study, we used four machine-learning models (LASSO logistic regression, random forest, backpropagation neural network, and support vector machines) to predict the occurrence of PIH in a prospective cohort. Candidate features for predicting the occurrence of middle and late PIH were acquired using a LASSO algorithm. The performance of predictive models was assessed using receiver operating characteristic analysis. Finally, a nomogram was established with the model scores, age, and nulliparity. Calibration, clinical usefulness, and internal validation were used to assess the performance of the nomogram. In the training set (2258 pregnant women), eleven candidate factors in the first trimester were significantly associated with the occurrence of PIH (P < 0.001 in the training set). Four models showed AUCs from 0.780 to 0.816 in the training set. For the validation set (939 pregnant women), AUCs varied from 0.516 to 0.795. The nomogram showed good discrimination, with an AUC of 0.847 (95% CI: 0.805-0.889) in the training set and 0.753 (95% CI: 0.653-0.853) in the validation set. Decision curve analysis suggested that the model was clinically useful. The model developed using LASSO logistic regression achieved the best performance in predicting the occurrence of PIH. The derived nomogram, which incorporates the model score and maternal risk factors, can be used to predict PIH in clinical practice. We develop a model with good performance for clinical prediction of PIH in the first trimester.

Elevated serum lead and cadmium levels associated with increased risk of dyslipidemia in children aged 6 to 9 years in Shenzhen, China.

Exposure to heavy metals can influence on metabolism, but studies have not fully evaluated young children. We investigated the association between levels of serum lead (Pb), cadmium (Cd), chromium (Cr), and arsenic (As) and risk of dyslipidemia in children. A total of 4513 children aged 6 to 9 years at 19 primary schools in Shenzhen were enrolled. Overall, 663 children with dyslipidemia were matched 1:1 with control by sex and age, and levels of serum Pb, Cd, Cr, and As were detected by inductively coupled plasma-mass spectrometry. Demographic characteristics and lifestyle were covariates in the logistic regression to determine the association of heavy metal levels with risk of dyslipidemia. Serum Pb and Cd levels were significantly higher in children with dyslipidemia than controls (133.08 vs. 84.19 µg/L; 0.45 vs. 0.29 µg/L; all P < 0.05), but this association was not found in Cr and As. We found significant upward trends for the odds ratios (ORs) of dyslipidemia associated with increasing quartiles of Pb and Cd levels (highest quartile of serum Pb OR 1.86, 95% confidence interval (CI) 1.46-2.38; Cd OR 2.51, 95% CI 1.94-3.24). Elevated serum Pb and Cd levels were associated with increased risk of dyslipidemia among children.

Global, regional, and national burden of multiple sclerosis from 1990 to 2019: Findings of global burden of disease study 2019.

Background: The global rising prevalence and incidence of multiple sclerosis (MS) has been reported during the past decades. However, details regarding the evolution of MS burden have not been fully studied. This study aimed to investigate the global, regional, and national burden and temporal trends in MS incidence, deaths, and disability-adjusted life years (DALYs) from 1990 to 2019 using the age-period-cohort analysis. Methods: We performed a secondary comprehensive analysis of incidence, deaths, and DALYs of MS by calculating the estimated annual percentage change from 1990 to 2019 obtained from the Global Burden of Disease (GBD) 2019 study. The independent age, period, and birth cohort effects were evaluated by an age-period-cohort model. Results: In 2019, there were 59,345 incident MS cases and 22,439 MS deaths worldwide. The global number of incidences, deaths, and DALYs of MS followed an upward trend, whereas the age-standardized rates (ASR) slightly declined from 1990 to 2019. High socio-demographic index (SDI) regions had the highest ASR of incidences, deaths, and DALYs in 2019, while the rate of deaths and DALYs in medium SDI regions are the lowest. Six regions which include high-income North America, Western Europe, Australasia, Central Europe, and Eastern Europe had higher ASR of incidences, deaths, and DALYs than other regions in 2019. The age effect showed that the relative risks (RRs) of incidence and DALYs reached the peak at ages 30-39 and 50-59, respectively. The period effect showed that the RRs of deaths and DALYs increased with the period. The cohort effect showed that the later cohort has lower RRs of deaths and DALYs than the early cohort. Conclusion: The global cases of incidence, deaths, and DALYs of MS have all increased, whereas ASR has declined, with different trends in different regions. High SDI regions such as European countries have a substantial burden of MS. There are significant age effects for incidence, deaths, and DALYs of MS globally, and period effects and cohort effects for deaths and DALYs.

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.

Prevalence of potentially inappropriate medications and association with comorbidities in older adults with diabetes in an outpatient visitation setting.

Aims: Potentially inappropriate medications had been found associated with adverse drug events such as falls, emergency department admissions and hospital readmissions. There is lack of information about the prevalence of potentially inappropriate medications and associated chronic conditions in older patients with diabetes in China. This study aimed to assess the prevalence of potentially inappropriate medications in older adults with diabetes in an outpatient visitation setting and the association with polypharmacy due to comorbidities. Materials and methods: This was a 3-year repeated cross-sectional study which conducted in outpatient setting of 52 hospitals in Shenzhen, China, using 2019 Beers criteria. The prevalence of potentially inappropriate medications, polypharmacy and comorbidities in older adults with diabetes in an outpatient setting was expressed as percentages. Logistic models were used to investigate the association between potentially inappropriate medication exposure and age, sex, polypharmacy and comorbidities. Results: Among the 28,484 older adults with diabetes in 2015, 31,757 in 2016 and 24,675 in 2017, the prevalence of potentially inappropriate medications was 43.2%, 44.88% and 42.40%, respectively. The top five potentially inappropriate medications were diuretics (20.56%), benzodiazepines (13.85%), androgens (13.18%), non-steroidal anti-inflammatory drugs (12.94%) and sulfonylureas (6.23%). After adjustment for age and polypharmacy, the probability of potentially inappropriate medication exposure was associated with chronic gastrointestinal diseases, followed by osteoarthritis and rheumatoid arthritis, chronic pulmonary disease, chronic kidney disease, tumor, dementia, chronic liver disease, hypertension, cardiovascular disease, cerebrovascular disease and hyperlipemia. Conclusion: Potentially inappropriate medications were common in older patients with diabetes in an outpatient visitation setting. Higher probability of potentially inappropriate medication exposure was associated with the comorbidity chronic gastrointestinal diseases as well as osteoarthritis and rheumatoid arthritis. To ensure that iatrogenic risks remain minimal for older adults with diabetes, the clinical comorbidities should be considered.

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.

Combination of Quantitative Susceptibility Mapping and Diffusion Kurtosis Imaging Provides Potential Biomarkers for Early-Stage Parkinson's Disease.

Purpose: This study aimed to detect changes in iron deposition and neural microstructure in the substantia nigra (SN), red nucleus (RN), and basal ganglia of Parkinson's disease (PD) patients at different stages using quantitative susceptibility mapping and diffusion kurtosis imaging to identify potential indicators of early-stage PD. Methods: We enrolled 20 early-stage and 15 late-stage PD patients, as well as 20 age- and sex-matched controls. All participants underwent quantitative susceptibility mapping and diffusion kurtosis imaging to determine magnetic susceptibility (MS), fractional anisotropy (FA), mean diffusivity (MD), and mean kurtosis (MK) in several brain regions. Results: Compared with the control group, MS and MK values in the SN were significantly increased in the early- and late-stage PD group, whereas MS values in the red nucleus (RN), globus pallidus (GP), and caudate nucleus (CN), FA value in the CN and GP, and MK value in the CN and putamen (PU) were significantly increased in the late-stage PD group. There were positive correlations between MS and MK values in the CN and MS and FA values in the GP. Furthermore, the combination of MS and MK values in the SN provided high accuracy for distinguishing early-stage PD patients from controls. Conclusions: This study identified MS and MK in the SN as potential indicators of early-stage PD.

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.

Effect of Exposure to Paternal Smoking on Overweight and Obesity in Children: Findings from the Children Lifeway Cohort in Shenzhen, Southern China.

INTRODUCTION: Paternal smoking associated with childhood overweight and obesity has been a concern, but studies have not investigated smoking exposure and smoking details. We investigated the association of exposures from paternal smoking as well as smoking details on offspring overweight/obesity. METHODS: A total of 4,513 children (aged 7-8 years) in Shenzhen were enrolled. Four different exposures from paternal smoking as well as smoking quantity, duration of smoking, and age of starting smoking details were the exposure variables and demographic characteristics, and circumstances of birth, dietary intake, lifestyle, and nonpaternal-smoking exposure were covariates in the logistic regression analysis to determine the effect of paternal smoking on childhood overweight/obesity, estimating odds ratios (ORs), and 95% confidence intervals (CIs). RESULTS: Paternal smoking was positively associated with childhood overweight/obesity (p < 0.05). Moreover, only preconception exposure, and both pre- and postconception exposure were significantly associated with childhood overweight/obesity (OR 1.54 [95% CI: 1.14-2.08] and OR 1.73 [95% CI: 1.14-2.61], respectively), restricted to boys but not girls. Furthermore, for children with only preconception paternal-smoking exposure, the dose-response relation was positive between smoking quantity, duration of smoking, age at starting, and overweight/obesity for boy offspring (p trend <0.001). We did not find any significant association between only postnatal exposure to paternal smoking and childhood overweight/obesity (p > 0.05). CONCLUSIONS: Our findings suggest that paternal smoking is associated with boys' overweight/obesity, and this association may be due to the paternal-smoking exposure before conception rather than the postnatal exposure to paternal smoking. Reducing paternal-smoking exposure before conception might help reduce overweight/obesity in boys.

Association of Interpregnancy Interval With Adverse Birth Outcomes.

Importance: Many studies have reported an association of interpregnancy interval (IPI) between 2 consecutive births with adverse birth outcomes in low- and middle-income countries. However, most of these studies ignore the implications of some unmeasured confounders. Objective: To explore the association of IPI with adverse perinatal outcomes. Design, Setting, and Participants: This large-scale cohort study used the Guangdong Provincial Women and Children Health Information System in Guangdong Province, China, to obtain birth data recorded between January 1, 2014, and December 31, 2020. Matched-sibling design was used. The final cohort included first-born and second-born sibling pairs delivered by mothers who were permanent residents of Guangdong Province. Exposures: The exposure variable was IPI, which was categorized as follows: less than 6, 6 to 11, 12 to 17, 18 to 23, 24 to 29, 30 to 35, and 36 or more months. Main Outcomes and Measures: The outcome variables were adverse birth outcomes: preterm birth (PTB, gestational age <37 weeks), low birth weight (LBW, <2500 g), and small for gestational age (SGA). Adjusted odds ratio (OR) and interaction odds ratio (IOR) associated with IPI were calculated. Results: The study consisted of 725 392 sibling pairs of multiparous mothers. Among these mothers, 718 111 (99.0%) were aged 20 to 34 years, and 715 583 (98.7%) were of Han Chinese ethnicity. Unmatched analysis showed that a short IPI of less than 6 months was associated with higher risks of PTB (adjusted OR, 1.96; 95% CI, 1.87-2.06), LBW (adjusted OR, 1.88; 95% CI, 1.79-1.98), and SGA (adjusted OR, 1.34; 95% CI, 1.30-1.38) compared with an IPI of 18 to 23 months. These associations were attenuated in the matched-sibling analysis. An association of short IPI (<6 months) with PTB (adjusted IOR, 1.40; 95% CI, 1.30-1.51), LBW (adjusted IOR, 1.30; 95% CI, 1.21-1.40), and SGA (adjusted IOR, 1.16; 95% CI, 1.11-1.22) remained in the matched analysis. For IPI of 36 months or more, the odds of PTB (adjusted OR, 1.08; 95% CI, 1.03-1.14) and LBW (adjusted OR, 1.13; 95% CI, 1.07-1.19) in the unmatched analysis were also greater than the reference interval (18-23 months), but not for SGA (adjusted OR, 0.96; 95% CI, 0.93-0.99). Associations between a long IPI (≥36 months) and PTB (adjusted IOR, 1.10; 95% CI, 1.02-1.19) and LBW (adjusted IOR, 1.16; 95% CI, 1.07-1.26) remained through the sibling comparisons. Conclusions and Relevance: Results of this study indicated that mothers with a short (<6 months) or long (≥36 months) IPI had greater odds of adverse birth outcomes. The findings may inform family planning policies and guide individuals and families who are planning for another pregnancy in China.

An ensemble forecast system for tracking dynamics of dengue outbreaks and its validation in China.

As a common vector-borne disease, dengue fever remains challenging to predict due to large variations in epidemic size across seasons driven by a number of factors including population susceptibility, mosquito density, meteorological conditions, geographical factors, and human mobility. An ensemble forecast system for dengue fever is first proposed that addresses the difficulty of predicting outbreaks with drastically different scales. The ensemble forecast system based on a susceptible-infected-recovered (SIR) type of compartmental model coupled with a data assimilation method called the ensemble adjusted Kalman filter (EAKF) is constructed to generate real-time forecasts of dengue fever spread dynamics. The model was informed by meteorological and mosquito density information to depict the transmission of dengue virus among human and mosquito populations, and generate predictions. To account for the dramatic variations of outbreak size in different seasons, the effective population size parameter that is sequentially updated to adjust the predicted outbreak scale is introduced into the model. Before optimizing the transmission model, we update the effective population size using the most recent observations and historical records so that the predicted outbreak size is dynamically adjusted. In the retrospective forecast of dengue outbreaks in Guangzhou, China during the 2011-2017 seasons, the proposed forecast model generates accurate projections of peak timing, peak intensity, and total incidence, outperforming a generalized additive model approach. The ensemble forecast system can be operated in real-time and inform control planning to reduce the burden of dengue fever.

Spatio-Temporal Distribution and Demographic Characteristics of Congenital Heart Defects in Guangdong, China, 2016-2020.

Background: Congenital heart defects are the most common type of birth defects and bring a heavy disease burden in China. Examining the temporal and spatial trends of congenital heart defects epidemics can give some elementary knowledge for succeeding studies. Objective: To characterize the spatial-temporal patterns of the prevalence of congenital heart defects based on a substantial cohort of the perinatal fetus in south China in 2016-2020. Methods: This study was a retrospective population-based cohort study conducted in Guangdong, China from 2016 to 2020. Pregnant women and their infants received birth defect surveillance during pregnancy and seven days after delivery in more than 1,900 midwifery hospitals in 21 cities. Perinatal infants with congenital heart defects were identified and enrolled. The prevalence of congenital heart defects was calculated according to cities, years, urban and rural areas, regions of Guangdong, categories of maternal age at delivery, seasons of delivery, and infant's gender. Results: A total of 8,653,206 perinatal infants and 53,912 total congenital heart defects were monitored in Guangdong, including 46,716 (86.65%) without other defects and 7,736 (13.35%) with other defects. The average prevalence of total congenital heart defects was 62.30/10,000 (95% CI, 61.78/10,000-62.83/10,000), congenital heart defects without other defects was 53.36/10,000 (95% CI, 52.88/10,000-53.85/10,000), and congenital heart defects with other defects was 8.94/10,000 (95%CI, 8.74/10,000-9.14/10,000). From 2016 to 2020, the prevalence of total congenital heart defects was 54.92/10,000, 54.23/10,000, 63.79/10,000, 73.11/10,000, 68.20/10,000, respectively. We observed geographical variations within the prevalence of congenital heart defects. The prevalence of congenital heart defects was much higher in the Pearl River Delta region than in the non-Pearl River Delta region, as well as higher in urban areas than in rural areas. Conclusion: The findings of this study are helpful to the understanding of the etiology and epidemiology characteristics of congenital heart defects in south China. Our data likely reflect a better estimate of the spatiotemporal trends in congenital heart defects prevalence than reported previously.