Major changes in prevalence and genotypes of rotavirus diarrhea in Beijing, China after RV5 rotavirus vaccine introduction.

To analyze the epidemiological characteristics of group A rotavirus (RVA) diarrhea in Beijing between 2019 and 2022 and evaluate the effectiveness of the RV5 vaccine. Stool specimens were collected from patients with acute diarrhea, and RVA was detected and genotyped. The whole genome of RVA was sequenced by fragment amplification and Sanger sequencing. Phylogenetic trees were constructed using Bayesian and maximum likelihood methods. Descriptive epidemiological methods were used to analyze the characteristics of RVA diarrhea. Test-negative design was used to evaluate the vaccine effectiveness (VE) of the RV5. Compared with 2011-2018, RVA-positive rates in patients with acute diarrhea under 5 years of age and adults decreased significantly between 2019 and 2022, to 9.45% (249/634) and 3.66% (220/6016), respectively. The predominant genotype of RVA had changed from G9-VIP[8]-III between 2019 and 2021 to G8-VP[8]-III in 2022, and P[8] sequences from G8-VP[8]-III strains formed a new branch called P[8]-IIIb. The complete genotype of G8-VP[8]-III was G8-P[8]-I2-R2-C2-M2-A2-N2-T2-E2-H2. The VE of 3 doses of RV5 was 90.4% (95% CI: 28.8%-98.7%) against RVA diarrhea. The prevalence of RVA decreased in Beijing between 2019 and 2022, and the predominant genotype changed to G8P[8], which may be related to RV5 vaccination. Continuous surveillance is necessary to evaluate vaccine effectiveness and improve vaccine design.

Development of family resource indicators for people with schizophrenic disorder in community by modified Delphi method in Beijing, China.

INTRODUCTION: Most people with schizophrenia in China are supported by their family members in community. The patient's family is confronted with severe care burden and pressure, which directly affects the caregiver's own health and social life, and indirectly affects the patient's rehabilitation. Adequate family resources can reduce the burden and pressure on families. But there is an absence of systematic family resource indicators for people with schizophrenic disorder in China. OBJECTIVES: This study aimed to develop a set of family resource indicators for people with schizophrenic disorder in China. DESIGN: Preliminary family resource indicators were generated and refined by literature review and an expert consultation meeting. Two rounds of email-based Delphi survey were carried out to identify family resource indicators. SETTING: Two rounds of email-based Delphi survey were performed from July to September 2021 in Beijing, China. PARTICIPANTS: There were 15 mental health doctors from community health service centres and four psychiatrists from tertiary hospitals, and two primary care researchers from universities in the first and second rounds Delphi survey. RESULTS: All the 21 experts participated in both rounds of Delphi survey. A total of 46 indicators achieved consensus for inclusion in the final set of indicators after two rounds of Delphi survey. The final set of indicators was grouped into 10 domains: financial support (three indicators), psychological and spiritual support (eight indicators), medical treatment (three indicators), information and education (three indicators), structural support (two indicators), external family resources included social resources (five indicators), cultural resources (two indicators), economic resources (seven indicators), environmental resources (four indicators) and medical resources (nine indicators). CONCLUSIONS: A set of 46 family resource indicators for people with schizophrenic disorder in community was identified by an iterative Delphi process in Beijing, China. However, the indicators still need to be validated by testing in further studies.

Postpartum depression and risk factors among working women one year after delivery in Beijing, China: a cross-sectional study.

Background: Postpartum depression (PPD) is the most common mental illness affecting women after childbirth, and working mothers may be faced with unique challenges. This study aimed to examine the depression status among working postpartum women in 1 year of childbirth and explore the relationship between occupational factors and PPD in urban Beijing, China. Methods: A cross-sectional survey of 554 postpartum women was conducted among ten community health service centers in six urban districts of Beijing, China. Sociodemographic, occupational, childbirth and postpartum information were collected. Depression status was obtained using the Edinburgh Postnatal Depression Scale. Prevalence of postpartum depression (PPD) was assessed in relation to occupational characteristics, and influencing factors were analyzed through logistic regression. Results: Of the postpartum women, 29.42% met the criteria for depression. PPD prevalence was significantly higher among women employed in commercial enterprises (39.81%). The analysis of influencing factors showed that age, family or personal monthly income, maternity leave, feeding methods, and postpartum care affected the psychological health of occupational women after childbirth. Conclusion: PPD prevalence is notably elevated among women employed in commercial enterprises, and specific risk factors contribute to its occurrence. These findings highlight the need for targeted interventions to address these risk factors and prevent PPD in this population.

Short-term prediction of PM2.5 concentration by hybrid neural network based on sequence decomposition.

Accurate forecasting of PM2.5 concentrations serves as a critical tool for mitigating air pollution. This study introduces a novel hybrid prediction model, termed MIC-CEEMDAN-CNN-BiGRU, for short-term forecasting of PM2.5 concentrations using a 24-hour historical data window. Utilizing the Maximal Information Coefficient (MIC) for feature selection, the model integrates Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN), Convolutional Neural Network (CNN), and Bidirectional Recurrent Gated Neural Network (BiGRU) to optimize predictive accuracy. We used 2016 PM2.5 monitoring data from Beijing, China as the empirical basis of this study and compared the model with several deep learning frameworks. RNN, LSTM, GRU, and other hybrid models based on GRU, respectively. The experimental results show that the prediction results of the hybrid model proposed in this question are more accurate than those of other models, and the R2 of the hybrid model proposed in this paper improves the R2 by nearly 5 percentage points compared with that of the single model; reduces the MAE by nearly 5 percentage points; and reduces the RMSE by nearly 11 percentage points. The results show that the hybrid prediction model proposed in this study is more accurate than other models in predicting PM2.5.

Identification and classification of urban employment centers based on big data: A case study of Beijing.

The layout, scale and spatial form of urban employment centers are important guidelines for the rational layout of public service facilities such as urban transportation, medical care, and education. In this paper, we use Internet cell phone positioning data to identify the workplace and residence of users in the Beijing city area and obtain commuting data of the employed to measure the employment center system in Beijing. Firstly, the employment density distribution is generated using the data of the working places of the employed persons, and the employment centers are identified based on the employment density of Beijing. Then, we use the business registration data of employment centers to measure the industrial diversity within the employment centers by using the ecological Shannon Wiener Diversity Index, and combine the commuting links between employment centers and places of residence to measure the energy level of each employment center, analyze the hinterland and sphere of influence of each center, and finally using the industrial diversity index of employment centers and the average commuting time of employed persons, combined with the K-Means clustering algorithm, to classify the employment centers in Beijing. The employment center identification and classification method based on big data constructed in this study can help solve the limitations of the previous employment center system research in terms of center identification and commuting linkage measurement due to large spatial units and lack of commuting data to a certain extent. The study can provide reference for the regular understanding and technical analysis of employment centers and provide help for the employment multi-center system in Beijing in terms of quantifying the employment spatial structure, guiding the construction of multi-center system, and adjusting the land use rules.

Fine particulate matter exposure and systemic inflammation: A potential mediating role of bioactive lipids.

Inflammation is a key mechanism underlying the adverse health effects of exposure to fine particulate matter (PM2.5). Bioactive lipids in the arachidonic acid (ARA) pathway are important in the regulation of inflammation and are reportedly altered by PM2.5 exposure. Ceramide-1-phosphate (C1P), a class of sphingolipids, is required to initiate ARA metabolism. We examined the role of C1P in the alteration of ARA metabolism after PM2.5 exposure and explored whether changes in the ARA pathway promoted systemic inflammation based on a panel study involving 112 older adults in Beijing, China. Ambient PM2.5 levels were continuously monitored at a fixed station from 2013 to 2015. Serum cytokine levels were measured to assess systemic inflammation. Multiple bioactive lipids in the ARA pathway and three subtypes of C1P were quantified in blood samples. Mediation analyses were performed to test the hypotheses. We observed that PM2.5 exposure was positively associated with inflammatory cytokines and the three subtypes of C1P. Mediation analyses showed that C1P significantly mediated the associations of ARA and 5, 6-dihydroxyeicosatrienoic acid (5, 6-DHET), an ARA metabolite, with PM2.5 exposure. ARA, 5, 6-DHET, and leukotriene B4 mediated systemic inflammatory response to PM2.5 exposure. For example, C1P C16:0 (a subtype of C1P) mediated a 12.9 % (95 % confidence interval: 3.7 %, 32.5 %) increase in ARA associated with 3-day moving average PM2.5 exposure, and ARA mediated a 27.1 % (7.8 %, 61.2 %) change in interleukin-8 associated with 7-day moving average PM2.5 exposure. Our study indicates that bioactive lipids in the ARA and sphingolipid metabolic pathways may mediate systemic inflammation after PM2.5 exposure.

Lag effect of ambient temperature on respiratory emergency department visits in Beijing: a time series and pooled analysis.

BACKGROUND: Although the association between ambient temperature and mortality of respiratory diseases was numerously documented, the association between various ambient temperature levels and respiratory emergency department (ED) visits has not been well studied. A recent investigation of the association between respiratory ED visits and various levels of ambient temperature was conducted in Beijing, China. METHODS: Daily meteorological data, air pollution data, and respiratory ED visits data from 2017 to 2018 were collected in Beijing. The relationship between ambient temperature and respiratory ED visits was explored using a distributed lagged nonlinear model (DLNM). Then we performed subgroup analysis based on age and gender. Finally, meta-analysis was utilized to aggregate the total influence of ambient temperature on respiratory ED visits across China. RESULTS: The single-day lag risk for extreme cold peaked at a relative risk (RR) of 1.048 [95% confidence interval (CI): 1.009, 1.088] at a lag of 21 days, with a long lag effect. As for the single-day lag risk for extreme hot, a short lag effect was shown at a lag of 7 days with an RR of 1.076 (95% CI: 1.038, 1.114). The cumulative lagged effects of both hot and cold effects peaked at lag 0-21 days, with a cumulative risk of the onset of 3.690 (95% CI: 2.133, 6.382) and 1.641 (95% CI: 1.284, 2.098), respectively, with stronger impact on the hot. Additionally, the elderly were more sensitive to ambient temperature. The males were more susceptible to hot weather than the females. A longer cold temperature lag effect was found in females. Compared with the meta-analysis, a pooled effect of ambient temperature was consistent in general. In the subgroup analysis, a significant difference was found by gender. CONCLUSIONS: Temperature level, age-specific, and gender-specific effects between ambient temperature and the number of ED visits provide information on early warning measures for the prevention and control of respiratory diseases.

Analysis of care-seeking and diagnosis delay among pulmonary tuberculosis patients in Beijing, China.

Background: Tuberculosis (TB) remains a significant public health challenge in China. Early detection and diagnosis of TB cases are crucial to interrupt disease transmission and prevent its progression. This study aims to describe the delay in seeking care and diagnosis among patients with pulmonary tuberculosis (PTB) and identify the influencing factors in two counties in Beijing. Methods: A retrospective analysis was carried out to investigate care-seeking and diagnosis delay in two counties in Beijing. Basic information of PTB patients from January 1 to December 31, 2021, was extracted from the Tuberculosis Information Management System of China (TBIMS), and all enrolled patients were interviewed via telephone using a standard questionnaire. Statistical description was performed using the median and interquartile range (IQR). Chi-square test and multivariate logistic regression model were used to analyze the influencing factors. Results: 537 patients were enrolled. The median duration of care-seeking and diagnosis delay was 11 (IQR: 5-26) days and 8 (IQR: 0-18) days, with 41.71 and 35.20% of patients experiencing delays (>14 days). The study found that being asymptomatic (OR = 2.791, 95%CI: 1.710-4.555) before seeking medical care and not attending work during treatment (OR = 2.990, 95%CI: 1.419-6.298) were identified as risk factors for care-seeking delay. Patients who were tracked (OR = 2.632, 95%CI: 1.062-6.521) and diagnosed at tuberculosis control and prevention institutions (OR = 1.843, 95%CI: 1.061-3.202) had higher odds of diagnostic delays. 44.69% of patients presented a total delay (>28 days), with a median duration of 25 (IQR: 13-39) days. A multivariate logistic regression analysis showed that healthy examination (OR = 0.136, 95%CI: 0.043-0.425) was a protective factor for total delay. Conclusion: Public interventions are necessary to improve the efficiency of PTB patients detection and treatment in Beijing. Medical services should focus on the target population and improve access to medical care to further reduce delays for PTB patients.

Genotype Distribution and Prevalence of High-Risk Human Papillomavirus among Pregnant Women and Maternal-Fetal Pregnancy Outcomes in a Tertiary Hospital in Beijing, China.

BACKGROUND: High-risk human papillomavirus (HR-HPV) infection is the primary reason for cervical cancer and precancerous lesions in females. Specific immune alterations in pregnancy led to greater HR-HPV replication and reduced clearance of HR-HPV infection. This study retrospectively obtained and analyzed data from a tertiary hospital in Beijing, China. We aimed to ascertain both the genotype distribution and prevalence of HR-HPV in pregnant females. Moreover, we sought to analyze the association of HR-HPV with maternal-fetal pregnancy outcomes. METHODS: The retrospective observational cohort study was divided into two parts. Part I evaluated the genotype distribution and prevalence of HR-HPV. It encompassed 6285 pregnant women who underwent a routine pregnancy check-up, Thin Prep cytology test (TCT), and HR-HPV diagnosis during weeks 12-14 of gestation between January 1, 2013, and December 31, 2021. Part II analyzed the association between HR-HPV infection and maternal-fetal pregnancy outcome. Through a nearest-neighbor 1:1 propensity score matching (PSM), we matched HR-HPV-positive and HR-HPV-negative pregnant women using caliper width equal to 0.02. After PSM, 171 HR-HPV-positive and 171 HR-HPV-negative pregnant women were included to analyze the association between HR-HPV infection and maternal-fetal pregnancy outcome. RESULTS: In total 737 (11.73%) pregnant women were HR-HPV positive. The five most common genotypes of HR-HPV were HPV-52 (2.90%), HPV-58 (2%), HPV-16 (1.94%), HPV-51 (1.38%), and HPV-39 (1.29%). As for age-specific HPV prevalence, a "U-shaped" pattern was observed. The first and second peaks were detected in pregnant females aged <25 years and those aged ≥35 years, respectively. Our study found no significant difference between the HR-HPV-positive and the HR-HPV-negative pregnant females in the following maternal-fetal pregnancy outcomes: spontaneous abortion (1.2% for HR-HPV positive, 0% for HR-HPV negative, p = 0.478), preterm delivery (4.7% for HR-HPV positive, 5.3% for HR-HPV negative, p = 0.804), premature rupture of membrane (28.8% for HR-HPV positive, 22.8% for HR-HPV negative, p = 0.216), preeclampsia (7.6% for HR-HPV positive, 7.6% for HR-HPV negative, p = 1), oligohydramnios (8.2% for HR-HPV positive, 7% for HR-HPV negative, p = 0.683), fetal growth restriction (1.8% for HR-HPV positive, 0.6% for HPV negative, p = 0.615), placenta previa (1.2% for HR-HPV positive, 0.6% for HR-HPV negative, p = 1), postpartum hemorrhage (8.9% for HR-HPV positive, 11.2% for HR-HPV negative, p = 0.47). There was also no significant difference in delivery mode or birth weight between the two groups. CONCLUSIONS: HPV-16, 52, and 58 were the most prevalent infection genotypes in pregnant females. The study showed no significant differences between HR-HPV-positive and HR-HPV-negative groups in the maternal-fetal pregnancy outcomes.

Predicting future vaccination habits: The link between influenza vaccination patterns and future vaccination decisions among old aged adults in China.

BACKGROUND: Annual influenza vaccination is crucially recommended for the elderly to maintain humoral immunity. Insufficient coverage requires us to understand the determinants of their influenza behaviors and how these patterns impact vaccination choices. METHODS: Data from 540 Beijing residents aged over 65 were collected through interviews, capturing vaccination history and sociodemographic details. Individual influenza vaccination records from 2016 to 2020 were obtained from China's Immunization Information Systems. A latent class model identified three vaccination patterns. Multinomial logistic regression assessed relative risk ratios (RRRs) for vaccination based on sociodemographic factors. Vaccination patterns were used to predict future vaccination likelihood. RESULTS: The analysis revealed three groups: sporadically vaccinated (63.33%), occasionally vaccinated (18.71%), and frequently vaccinated (17.96%). Factors associated with frequent vaccination included age over 70 (RRR = 2.81), lower income (RRR = 0.39), higher vaccine hesitancy (RRR = 3.10), multiple chronic conditions (RRR = 2.72), and rural residence (RRR = 2.48). The frequently vaccinated group was more likely to sustain regular vaccination habits in subsequent years compared to the occasionally vaccinated group. CONCLUSIONS: Only 17.96% of Beijing's older population exhibited a consistent influenza vaccination pattern. Older age, rural residency, and chronic diseases correlated with repeated influenza vaccination. Segmenting the population based on past vaccination behavior can aid in designing targeted interventions to improve vaccination rates.

Individual and family factors correlated with children's fruit consumption.

Background: Fruits are essential for health, yet their consumption in children is inadequate, with unclear influencing factors. Methods: A cross-sectional study was conducted among students in grades 3-12 in Beijing, China, from September 2020 to June 2021. Fruit consumption in children was surveyed using a self-administered food frequency questionnaire. Additionally, children's food and nutrition literacy and family food environments were assessed using the "Food and Nutrition Literacy Questionnaire for Chinese School-age Children" and the "Family Food Environment Questionnaire for Chinese School-age Children," respectively. Results: Out of 10,000 participating children, 62.5% consumed fruit daily, with a lower frequency among boys (59.3%) compared to girls (65.8%), and among senior students (48.6%) compared to junior (63.6%) and primary students (71.2%). Fruit consumption was positively associated with other healthy foods (vegetables, whole grains, etc.) and negatively with unhealthy foods (sugared soft drinks). Children with higher food and nutrition literacy consumed fruits daily more frequently (82.4% vs. 59.9%, ORs = 2.438, 95%CI: 2.072-2.868). A significant positive correlation was found between children's fruit consumption and a healthy family food environment (66.4% vs. 50.2%, OR = 1.507, 95%CI: 1.363-1.667). Conclusion: The results indicate that individual food and nutrition literacy and family food environment are key positive predictors of children's fruit consumption. Future interventions should focus on educating children and encouraging parents to foster supportive family environments.

Occurrence of rare earth elements in umbilical cord serum and association with thyroid hormones and birth outcomes in newborns.

Rare earth elements (REEs) are emerging contaminants that are increasingly used in high technology products. However, limited information is available regarding exposure to REEs and associated health effects in neonates. This study aimed to investigate the association between REE concentrations and thyroid hormone levels, as well as birth outcomes in 109 newborns in Beijing, China. We measured the concentrations of 16 REEs and thyroid hormones in umbilical cord serum. To assess the impact of exposure to individual REEs and REE mixtures on thyroid hormone levels and birth outcomes, we employed univariate linear regression, least absolute shrinkage and selection operator (LASSO), and weighted quantile sum (WQS) models. We detected 14 REEs at high rates (92.6%-100%), with yttrium exhibiting the highest median (interquartile range) concentration [43.94 (0.33-172.55) ng/mL], followed by scandium [3.64 (0.46-11.15) ng/mL]. Univariate analyses showed that per logarithmic (ln)-unit change of neodymium (Nd) and samarium (Sm) was associated with 0.039 [95% confidence interval (CI): 0.001, 0.007] and 0.031 (95% CI: 0.003, 0.060) increases in free thyroxine (FT4) levels, respectively. Moreover, 14 REEs exhibited significant associations with triiodothyronine (T3) levels, resulting in increases ranging from 0.066 to 0.307. Elevated concentrations of terbium (Tb) [per ln-unit change: -0.021 (95% CI: -0.041, -0.01)] and lutetium (Lu) [-0.023 (95% CI: -0.043, -0.002)] were inversely correlated with birth length in newborns. A further multiple exposure analysis employing the LASSO model identified Sm, Nd, Y, Sc, and Lu as critical factors influencing FT4 and T3 levels. Additionally, WQS analyses showed positive associations between exposure to a mixture of 14 REEs and FT4 (P = 0.046), T3 (P < 0.001), and birth length (P = 0.049). These findings suggest that in utero exposure to REEs might disrupt thyroid hormone homeostasis and impact intrauterine growth. Further studies are warranted to validate these findings and elucidate the underlying mechanisms.

Long- and Intermediate-Term Ambient Particulate Pollution Is Associated with Increased Osteoarthritis Risk: A Population-Based Prospective Analysis.

Recent studies found the intrusion and retention of exogenous fine particles into joints, but epidemiological data for long- and intermediate-term exposure associations are scare. Here, all urban working, retired employee, and rural residents (16.78 million) in Beijing from January 1, 2011 to December 31, 2019 were included to investigate the effects of long- and intermediate-term ambient particulate exposure on development of osteoarthritis. We identified 1,742,067 participants as first-visit patients with osteoarthritis. For each interquartile range increase in annual PM2.5 (23.32 µg/m3) and PM10 (23.92 µg/m3) exposure concentration, the pooled hazard ratios were respectively 1.238 (95% CI: 1.228, 1.249) and 1.178 (95% CI: 1.168, 1.189) for first osteoarthritis outpatient visits. Moreover, age at first osteoarthritis outpatient visits significantly decreased by 4.52 (95% CI: 3.45 to 5.40) days per µg/m3 for annual PM2.5 exposure at below 67.85 µg/m3. Finally, among the six constituents analyzed, black carbon appears to be the most important component associated with the association between PM2.5 exposure and the three osteoarthritis-related outcomes.

Association between synoptic types in Beijing and acute myocardial infarction hospitalizations: A comprehensive analysis of environmental factors.

BACKGROUND: Environmental factors like air pollution and temperature can trigger acute myocardial infarction (AMI). However, the link between large-scale weather patterns (synoptic types) and AMI admissions has not been extensively studied. This research aimed to identify the different synoptic air types in Beijing and investigate their association with AMI occurrences. METHODS: We analyzed data from Beijing between 2013 and 2019, encompassing 2556 days and 149,632 AMI cases. Using principal component analysis and hierarchical clustering, classification into distinct synoptic types was conducted based on weather and pollution measurements. To assess the impact of each type on AMI risk over 14 days, we employed a distributed lag non-linear model (DLNM), with the reference being the lowest risk type (Type 2). RESULTS: Four synoptic types were identified: Type 1 with warm, humid weather; Type 2 with warm temperatures, low humidity, and long sunshine duration; Type 3 with cold weather and heavy air pollution; and Type 4 with cold temperatures, dryness, and high wind speed. Type 4 exhibited the greatest cumulative relative risk (CRR) of 1.241 (95%CI: 1.150, 1.339) over 14 days. Significant effects of Types 1, 3, and 4 on AMI events were observed at varying lags: 4-12 days for Type 1, 1-6 days for Type 3, and 1-11 days for Type 4. Females were more susceptible to Types 1 and 3, while individuals younger than 65 years old showed increased vulnerability to Types 3 and 4. CONCLUSION: Among the four synoptic types identified in Beijing from 2013 to 2019, Type 4 (cold, dry, and windy) presented the highest risk for AMI hospitalizations. This risk was particularly pronounced for males and people under 65. Our findings collectively highlight the need for improved methods to identify synoptic types. Additionally, developing a warning system based on these synoptic conditions could be crucial for prevention.

Factors influencing length of stay and costs in inpatient cases of human brucellosis as the primary diagnosis over a decade in Beijing, China.

Aims: In the year 2021, human brucellosis ranked fifth in terms of the number of cases among all statutorily notifiable infectious diseases in China, thus remaining a significant concern for public health. This study aims to provide insights into the financial burden of human brucellosis by examining hospital stays and associated costs for affected individuals. Methods: In this retrospective study, we gathered updated data from 467 inpatient cases primarily diagnosed with human brucellosis at eight major tertiary hospitals in Beijing, China, spanning from 2013 to 2023. To comprehensively explore the economic impact on individuals, we not only analyzed the duration of hospital stays and total costs but also examined various charge types, including drug, lab test, medical imaging, medical treatment, surgical procedures, medical supplies and consumables, inpatient bed care, nursing services, and other services costs. Statistical analysis was employed to compare differences among gender, age, ethnicity, type of health insurance, condition at admission, comorbidity index, the performance of surgery, and the site of infection. Results: Both the length of stay and total cost exhibited significant variations among insurance, surgery, and infection site groups. Utilization categories demonstrated significant differences between patients who underwent surgery and those who did not, as well as across different infection sites. Furthermore, multiple linear regression analysis revealed that the condition at admission, Elixhauser comorbidity index, infection site, and surgery influenced both hospital stay and total cost. In addition, age and insurance type were associated with total costs. Conclusion: By delving into various utilization categories, we have addressed a significant gap in the literature. Our findings provide valuable insights for optimizing the allocation and management of health resources based on the influencing factors identified in this study.

Epidemiological characteristics of neuroendocrine neoplasms in Beijing: a population-based retrospective study.

BACKGROUND: The incidence of neuroendocrine neoplasms (NENs) is rising rapidly worldwide. However, there are few reports on these heterogeneous diseases in China. Our study aimed to explore the epidemiological characteristics of NENs in Beijing. METHODS: We conducted a retrospective cohort study using population-based cancer surveillance data in Beijing, China. All data were extracted from the Beijing Cancer Registry with incidence dates from 1 January 1998 to 31 December 2018; the follow-up period was through 31 December 2021. Segi's world standard population was used to estimate the age-standardized rate. Survival was estimated using the Kaplan-Meier method. RESULTS: From 1998 to 2018, the incidence of NENs in Beijing initially showed a significant increasing trend, from 1.07/100,000 to 3.53/100,000; this began to plateau after 2013. The age-specific incidence rate increased with age and peaked in the age group 70-74 years. The incidence in men was significantly higher than that in women (4.41/100,000 vs. 1.69/100,000). The most common sites of NENs were the lung (2.38/100,000) and rectum (0.14/100,000). Most NENs were diagnosed at a late stage. We found that NENs originating from the lung had worse overall survival than extrapulmonary NENs, and male patients had worse survival than female patients. CONCLUSIONS: This study retrospectively analyzed the epidemiological characteristics of NENs in Beijing from 1998 to 2018. Our findings provide a reference regarding the epidemiological statistics of NENs in Beijing to contribute to the prevention, diagnosis, and treatment of these specific tumors.

A comparative study on urban waterlogging susceptibility assessment based on multiple data-driven models.

Accurate identification of urban waterlogging areas and assessing waterlogging susceptibility are crucial for preventing and controlling hazards. Data-driven models are utilized to forecast waterlogging areas by establishing intricate relationships between explanatory variables and waterlogging states. This approach tackles the constraints of mechanistic models, which are frequently complex and unable to incorporate socio-economic factors. Previous research predominantly employed single-type data-driven models to predict waterlogging locations and evaluation of their effectiveness. There is a scarcity of comprehensive performance comparisons and uncertainty analyses of different types of models, as well as a lack of interpretability analysis. The chosen study area was the central area of Beijing, which is prone to waterlogging. Given the high manpower, time, and economic costs associated with collecting waterlogging information, the waterlogging point distribution map released by the Beijing Water Affairs Bureau was selected as labeled samples. Twelve factors affecting waterlogging susceptibility were chosen as explanatory variables to construct Random Forest (RF), Support Vector Machine with Radial Basis Function (SVM-RBF), Particle Swarm Optimization-Weakly Labeled Support Vector Machine (PSO-WELLSVM), and Maximum Entropy (MaxEnt). The utilization of diverse single evaluation indicators (such as F-score, Kappa, AUC, etc.) to assess the model performance may yield conflicting results. The Distance between Indices of Simulation and Observation (DISO) was chosen as a comprehensive measure to assess the model's performance in predicting waterlogging points. PSO-WELLSVM exhibited the highest performance with a DISOtest value of 0.63, outperforming MaxEnt (0.78), which excelled in identifying areas highly susceptible to waterlogging, including extremely high susceptibility zones. The SVM-RBF and RF models demonstrated suboptimal performance and exhibited overfitting. The examination of waterlogging susceptibility distribution maps predicted by the four models revealed significant spatial differences due to variations in computational principles and input parameter complexities. The integration of four WSAMs based on logistic regression has been shown to significantly decrease the uncertainty of a single data-driven model and identify the most flood-prone areas. To improve the interpretability of the data model, a geographical detector was incorporated to demonstrate the explanatory capacity of 12 variables and the process of waterlogging. Building Density (BD) exhibits the highest explanatory power in relation to explain waterlogging susceptibility (Q value = 0.202), followed by Distance to Road, Frequency of Heavy Rainstorms (FHR), DEM, etc. The interaction between BD and FHR results in a nonlinear increase in the explanatory power of waterlogging susceptibility. The presence of waterlogging susceptibility risk in the research area can be attributed to the interactions of multiple factors.

Characterization and health risks of short- and medium-chain chlorinated paraffins in the gas and size-fractionated particulate phases in ambient air.

Short-chain and medium-chain chlorinated paraffins (SCCPs and MCCPs) have garnered significant attention because they have persistence and potential toxicity, and can undergo long-distance transport. Chlorinated paraffins (CPs) inhaled in the size-fractionated particulate phase and gas phase can carry different risks to human health due to their ability to accumulate in different regions of the respiratory tract and exhibit varying deposition efficiencies. In our study, large-volume ambient air samples in both the size-fractionated particulate phase (Dp < 1.0 µm, 1.0-2.5 µm, 2.5-10 µm, and Dp ≥ 10 µm) and gas phase were collected simultaneously in Beijing using an active sampler. The overall levels of SCCPs and MCCPs were relatively high, the ranges being 57-881 and 30-385 ng/m3, respectively. SCCPs tended to be partitioned in the gas phase (on average 75% of the ΣSCCP concentration), while MCCPs tended to be partitioned in the particulate phase (on average 62% of the ΣMCCP concentration). Significant correlations were discovered between the logarithm-transformed gas-particle partition coefficients (KP) and predicted subcooled vapor pressures (PL0) (p < 0.01 for SCCPs and MCCPs) and between the logarithm-transformed KP values and octanol-air partition coefficients (KOA) (p < 0.01 for SCCPs and MCCPs). Thus, the slopes indicated that organic matter absorption was the dominant process involved in gas-particle partitioning. We used the ICRP model to calculate deposition concentrations for particulate-associated CPs in head airways region (15.6-71.4 ng/m³), tracheobronchial region (0.8-4.8 ng/m³), and alveolar region (5.1-21.9 ng/m³), then combined these concentrations with the CP concentrations in the gas phase to calculate estimated daily intakes (EDIs) for inhalation. The EDIs for SCCPs and MCCPs through inhalation of ambient air for the all-ages group were 67.5-184.2 ng/kg/day and 19.7-53.7 ng/kg/day, respectively. The results indicated that SCCPs and MCCPs in ambient air do not currently pose strong risks to human health in the study area.