Assessing the modification impact of vaccination on the relationship of the Discomfort Index with hand, foot, and mouth disease in Guizhou: A multicounty study.

BACKGROUND: Hand, foot, and mouth disease (HFMD) is a major public health issue in China while temperature and humidity are well-documented predictors. However, evidence on the combined effect of temperature and humidity is still limited. It also remains unclear whether such an effect could be modified by the enterovirus 71 (EV71) vaccination. METHODS: Based on 320,042 reported HFMD cases during the summer months between 2012 and 2019, we conducted a study utilizing Distributed Lag Non-Linear Models (DLNM) and time-varying DLNM to examine how China's HFMD EV71 vaccine strategy would affect the correlation between meteorological conditions and HFMD risk. RESULTS: The incidence of HFMD changed with the Discomfort Index in an arm-shaped form. The 14-day cumulative risk of HFMD exhibited a statistically significant increase during the period of 2017-2019 (following the implementation of the EV71 vaccine policy) compared to 2012-2016 (prior to the vaccine implementation). For the total population, the range of relative risk (RR) values for HFMD at the 75th, 90th, and 99th percentiles increased from 1.082-1.303 in 2012-2016 to 1.836-2.022 in 2017-2019. In the stratified analyses, Han Chinese areas show stronger relative growth, with RR values at the 75th, 90th, and 99th percentiles increased by 14.3%, 39.1%, and 134.4% post-vaccination, compared to increases of 22.7%, 41.6%, and 38.8% in minority areas. Similarly, boys showed greater increases (24.4%, 47.7%, 121.5%) compared to girls (8.1%, 28.1%, 58.3%). Additionally, the central Guizhou urban agglomeration displayed a tendency for stronger relative growth compared to other counties. CONCLUSIONS: Although the EV71 vaccine policy has been implemented, it hasn't effectively controlled the overall risk of HFMD. There's been a shift in the main viral subtypes, potentially altering population susceptibility and influencing HFMD occurrences. The modulating effects of vaccine intervention may also be influenced by factors such as race, sex, and economic level.

The origin and spread of HIV-1 CRF59_01B epidemic in China: A molecular network and phylogeographic analysis.

Human immunodeficiency virus type 1 CRF59_01B, identified in China in 2013, has been detected nationwide, exhibiting notably high prevalence in Guangzhou and its vicinity. This study aimed to unravel its origin and migration. A data set was established, incorporating all available CRF59_01B pol gene sequences and their metadata from Guangzhou and the public database. Bayesian phylogeographic analysis demonstrated that CRF59_01B originated in Shenzhen, the neighboring city of Guangzhou, around 1998 with posterior probability of 0.937. Molecular network analysis detected 1131 transmission links and showed a remarkably high clustering rate (78.9%). Substantial inter-city transmissions (26.5%, 300/1131) were observed between Shenzhen and Guangzhou while inter-region transmissions linked Guangzhou with South (46) and Southwest (64) China. The centre of Guangzhou was the hub of CRF59_01B transmission, including the inflow from Shenzhen (3.57 events/year) and outflow to the outskirts of Guangzhou (>2 events/year). The large-scale analysis revealed significant migration from Shenzhen to Guangzhou (5.08 events/year) and North China (0.59 events/year), and spread from Guangzhou to Central (0.47 events/year), East (0.42 events/year), South (0.76 events/year), Southwest China (0.76 events/year) and Shenzhen (1.89 events/year). Shenzhen and Guangzhou served as the origin and the hub of CRF59_01B circulation, emphasizing inter-city cooperation and data sharing to confine its nationwide diffusion.

The development of a performance evaluation index system for Chinese Centers for Disease Control and Prevention: a Delphi consensus study.

BACKGROUND: The performance evaluation of the Centers for Disease Control and Prevention (CDC) is crucial for enhancing the quality of public health services. With the ongoing reform of the CDC system in China, the existing performance evaluation system faces challenges. This study used the Delphi method to develop a new performance evaluation system for China's provincial, city, and county-level CDC. METHODS: Following the "Structure-Process-Outcome" model, assessment indicators were systematically collected. Indicators were modified and screened through two Delphi rounds based on CDC responsibilities, health development, and national policies. Twenty-four experts provided ratings and recommendations, and the research team evaluated questionnaire reliability, expert positivity, expert authority, and opinion consistency. RESULTS: The preliminary index system identified through the literature review and pre-survey included 11 primary, 30 secondary, and 64 tertiary indicators. After the first round of consultation, two secondary indicators and 11 tertiary indicators were removed and 22 tertiary indicators were added. After the second round of consultation, three secondary indicators and 11 tertiary indicators were removed and three tertiary indicators were added, at which point the p-value of the test for Kendall's coefficient of concordance W was < 0.001 and the coefficient of variation was within acceptable limits (< 0.25), so the consultation was concluded. The final index system included 11 primary, 25 secondary, and 67 tertiary indicators. CONCLUSIONS: This study responded to the CDC system reform by developing a comprehensive performance evaluation index system for provincial, city, and county-level CDC in China. The index system is both scientifically grounded and practical, serving as an effective tool for promoting the high-quality work of CDC organizations.

Protective effectiveness of previous infection against subsequent SARS-Cov-2 infection: systematic review and meta-analysis.

Background: The protective effectiveness provided by naturally acquired immunity against SARS-CoV-2 reinfection remain controversial. Objective: To systematically evaluate the protective effect of natural immunity against subsequent SARS-CoV-2 infection with different variants. Methods: We searched for related studies published in seven databases before March 5, 2023. Eligible studies included in the analysis reported the risk of subsequent infection for groups with or without a prior SARS-CoV-2 infection. The primary outcome was the overall pooled incidence rate ratio (IRR) of SARS-CoV-2 reinfection/infection between the two groups. We also focused on the protective effectiveness of natural immunity against reinfection/infection with different SARS-CoV-2 variants. We used a random-effects model to pool the data, and obtained the bias-adjusted results using the trim-and-fill method. Meta-regression and subgroup analyses were conducted to explore the sources of heterogeneity. Sensitivity analysis was performed by excluding included studies one by one to evaluate the stability of the results. Results: We identified 40 eligible articles including more than 20 million individuals without the history of SARS-CoV-2 vaccination. The bias-adjusted efficacy of naturally acquired antibodies against reinfection was estimated at 65% (pooled IRR = 0.35, 95% CI = 0.26-0.47), with higher efficacy against symptomatic COVID-19 cases (pooled IRR = 0.15, 95% CI = 0.08-0.26) than asymptomatic infection (pooled IRR = 0.40, 95% CI = 0.29-0.54). Meta-regression revealed that SARS-CoV-2 variant was a statistically significant effect modifier, which explaining 46.40% of the variation in IRRs. For different SARS-CoV-2 variant, the pooled IRRs for the Alpha (pooled IRR = 0.11, 95% CI = 0.06-0.19), Delta (pooled IRR = 0.19, 95% CI = 0.15-0.24) and Omicron (pooled IRR = 0.61, 95% CI = 0.42-0.87) variant were higher and higher. In other subgroup analyses, the pooled IRRs of SARS-CoV-2 infection were statistically various in different countries, publication year and the inclusion end time of population, with a significant difference (p = 0.02, p < 0.010 and p < 0.010), respectively. The risk of subsequent infection in the seropositive population appeared to increase slowly over time. Despite the heterogeneity in included studies, sensitivity analyses showed stable results. Conclusion: Previous SARS-CoV-2 infection provides protection against pre-omicron reinfection, but less against omicron. Ongoing viral mutation requires attention and prevention strategies, such as vaccine catch-up, in conjunction with multiple factors.

Association of long-term exposure to PM2.5 and its chemical components with the reduced quality of sleep.

Poor sleep quality is a widespread concern. While the influence of particle exposure on sleep disturbances has received considerable attention, research exploring other dimensions of sleep quality and the chemical components of the particles remains limited. We employed a marginal structural model to explore the association of long-term exposure to PM2.5 and its chemical components with poor sleep quality. The odds ratio (95 % CI) for poor sleep quality was 1.335 (1.292-1.378), 1.097 (1.080-1.113), 1.137 (1.100-1.174), 1.197 (1.156-1.240), and 1.124 (1.107-1.140) per IQR increase in the concentration of PM2.5, SO42-, NO3-, NH4+, and BC, respectively. The score (and 95 % CI) of sleep latency, use of sleep medication, habitual sleep efficiency, subjective sleep quality, and daytime dysfunction were affected by PM2.5, with an increase of 0.059 (0.050-0.069), 0.054 (0.049-0.059), 0.011 (0.008-0.014), 0.011 (0.005-0.018), and 0.026 (0.018-0.034) per IQR increase in PM2.5 concentrations, respectively. This study supports the association of long-term exposure to PM2.5 and its chemical components with poor sleep quality.

How long-term PM exposure may affect all-site cancer mortality: Evidence from a large cohort in southern China.

BACKGROUND: Evidence of a potential causal link between long-term exposure to particulate matter (PM) and all-site cancer mortality from large population cohorts remained limited and suffered from residual confounding issues with traditional statistical methods. AIMS: We aimed to examine the potential causal relationship between long-term PM exposure and all-site cancer mortality in South China using causal inference methods. METHODS: We used a cohort in southern China that recruited 580,757 participants from 2009 through 2015 and tracked until 2020. Annual averages of PM1, PM2.5, and PM10 concentrations were generated with validated spatiotemporal models. We employed a causal inference approach, the Marginal Structural Cox model, based on observational data to evaluate the association between long-term exposure to PM and all-site cancer mortality. RESULTS: With an increase of 1 µg/m³ in PM1, PM2.5, and PM10, the hazard ratios (HRs) and 95% confidence interval (CI) for all-site cancer were 1.033 (95% CI: 1.025-1.041), 1.032 (95% CI: 1.027-1.038), and 1.020 (95% CI: 1.016-1.025), respectively. The HRs (95% CI) for digestive system and respiratory system cancer mortality associated with each 1 µg/m³ increase in PM1 were 1.022 (1.009-1.035) and 1.053 (1.038-1.068), respectively. In addition, inactive participants, who never smoked, or who lived in areas of low surrounding greenness were more susceptible to the effects of PM exposure, the HRs (95% CI) for all-site cancer mortality were 1.042 (1.031-1.053), 1.041 (1.032-1.050), and 1.0473 (1.025-1.070) for every 1 µg/m³ increase in PM1, respectively. The effect of PM1 tended to be more pronounced in the low-exposure group than in the general population, and multiple sensitivity analyses confirmed the robustness of the results. CONCLUSION: This study provided evidence that long-term exposure to PM may elevate the risk of all-site cancer mortality, emphasizing the potential health benefits of improving air quality for cancer prevention.

Global Burden and Trends of Primary Liver Cancer Attributable to Comorbid Type 2 Diabetes Mellitus Among People Living with Hepatitis B: An Observational Trend Study from 1990 to 2019.

BACKGROUND: Type 2 diabetes mellitus (T2DM) increases the risk of liver cancer among people living with hepatitis B virus (HBV). Our study aimed to estimate the global burden and trends of liver cancer attributable to comorbid T2DM among people living with HBV from 1990 to 2019. METHODS: We calculated the population attributable fractions (PAFs) of liver cancer attributable to comorbid T2DM among the burden of HBV-related liver cancer. We applied the PAFs to the burden of HBV-related liver cancer derived from the Global Burden of Disease (GBD) 2019 database to obtain the burden of liver cancer attributable to HBV-T2DM comorbidity. The prevalence, disability-adjusted life year (DALY), and deaths of liver cancer attributable to the comorbidity were assessed at the global, regional, and country levels and then stratified by the sociodemographic index (SDI), sex, and age group. Estimated annual percentage changes (EAPCs) were calculated to quantify the temporal trends. RESULTS: In 2019, the global age-standardized prevalence and DALY rates of liver cancer attributable to HBV-T2DM comorbidity were 9.9 (8.4-11.5) and 182.4 (154.9-212.7) per 10,000,000 individuals, respectively. High-income Asia Pacific and East Asia had the highest age-standardized prevalence and DALY rates of liver cancer attributable to HBV-T2DM comorbidity, respectively. From 1990 to 2019, age-standardized prevalence and DALY rates increased in 16 out of 21 GBD regions. High-income North America had the largest annual increases in both age-standardized prevalence rates (EAPC = 6.07; 95% UI, 5.59 to 6.56) and DALY rates (EAPC = 4.77; 95% UI, 4.35 to 5.20), followed by Australasia and Central Asia. Across all SDI regions, the high SDI region exhibited the most rapid increase in age-standardized prevalence and DALY rates from 1990 to 2019. Additionally, men had consistently higher disease burdens than women across all age groups. The patterns of mortality burden and trends are similar to those of DALYs. CONCLUSIONS: The burden of liver cancer attributable to comorbid T2DM among people living with HBV has exhibited an increasing trend across most regions over the last three decades. Tailored prevention strategies targeting T2DM should be implemented among individuals living with HBV.

Residential greenness and chronic obstructive pulmonary disease in a large cohort in southern China: Potential causal links, risk trajectories, and mediation pathways.

INTRODUCTION: Residential greenness may influence COPD mortality, but the causal links, risk trajectories, and mediation pathways between them remain poorly understood. OBJECTIVES: We aim to comprehensively identify the potential causal links, characterize the dynamic progression of hospitalization or posthospital risk, and quantify mediation effects between greenness and COPD. METHODS: This study was conducted using a community-based cohort enrolling individuals aged ≥ 18 years in southern China from January 1, 2009 to December 31, 2015. Greenness was characterized by normalized difference vegetation index (NDVI) around participants' residential addresses. We applied doubly robust Cox proportional hazards model, multi-state model, and multiple mediation method, to investigate the potential causal links, risk trajectories among baseline, COPD hospitalization, first readmission due to COPD or COPD-related complications, and all-cause death, as well as the multiple mediation pathways (particulate matter [PM], temperature, body mass index [BMI] and physical activity) connecting greenness exposure to COPD mortality. RESULTS: Our final analysis included 581,785 participants (52.52% female; average age: 48.36 [Standard Deviation (SD): 17.56]). Each interquartile range (IQR: 0.06) increase in NDVI was associated with a reduced COPD mortality risk, yielding a hazard ratio (HR) of 0.88 (95 % CI: 0.81, 0.96). Furthermore, we observed per IQR (0.04) increase in NDVI was inversely associated with the risk of multiple transitions (baseline - COPD hospitalization, baseline - death, and readmission - death risks), especially a declined risk of all-cause death after readmission (HR = 0.66 [95 %CI: 0.44, 0.99]). Within the observed association between greenness and COPD mortality, three mediators were identified, namely PM, temperature, and BMI (HR for the total indirect effect: 0.773 [95 % CI: 0.703, 0.851]), with PM showing the highest mediating effect. CONCLUSIONS: Our findings revealed greenness may be a beneficial factor for COPD morbidity, prognosis, and mortality. This protective effect is primarily attributed to the reduction in PM concentration.

Unveiling causal connections: Long-term particulate matter exposure and type 2 diabetes mellitus mortality in Southern China.

Evidence of the potential causal links between long-term exposure to particulate matters (PM, i.e., PM1, PM2.5, and PM1-2.5) and T2DM mortality based on large cohorts is limited. In contrast, the existing evidence usually suffers from inherent bias with the traditional association assessment. A prospective cohort of 580,757 participants in the southern region of China were recruited during 2009 and 2015 and followed up through December 2020. PM exposure at each residential address was estimated by linking to the well-established high-resolution simulation dataset. Hazard ratios (HRs) were calculated using time-varying marginal structural Cox models, an established causal inference approach, after adjusting for potential confounders. During follow-up, a total of 717 subjects died from T2DM. For every 1 µg/m3 increase in PM2.5, the adjusted HRs and 95% confidence interval (CI) for T2DM mortality was 1.036 (1.019-1.053). Similarly, for every 1 µg/m3 increase in PM1 and PM1-2.5, the adjusted HRs and 95% CIs were 1.032 (1.003-1.062) and 1.085 (1.054-1.116), respectively. Additionally, we observed a generally more pronounced impact among individuals with lower levels of education or lower residential greenness which as measured by the Normalized Difference Vegetation Index (NDVI). We identified substantial interactions between NDVI and PM1 (P-interaction = 0.003), NDVI and PM2.5 (P-interaction = 0.019), as well as education levels and PM1 (P-interaction = 0.049). The study emphasizes the need to consider environmental and socio-economic factors in strategies to reduce T2DM mortality. We found that PM1, PM2.5, and PM1-2.5 heighten the peril of T2DM mortality, with education and green space exposure roles in modifying it.

Relationships between long-term exposure to major PM2.5 constituents and outpatient visits and hospitalizations in Guangdong, China.

Ambient fine particulate matter (PM2.5) has attracted considerable attention due to its crucial role in the rising global disease burden. Evidence of health risks associated with exposure to PM2.5 and its major constituents is important for advancing hazard assessments and air pollution emission policies. We investigated the relationship between exposure to major constituents of PM2.5 and outpatient visits as well as hospitalizations in Guangdong Province, China, where 127 million residents live in a severe PM2.5 pollution environment. An approach that integrates the generalized weighted quantile sum (gWQS) regression with the difference-in-differences (DID) approach was used to assess the overall mixture effects and relative contributions of each constituent. We observed significant associations between long-term exposure to the mixture of PM2.5 constituents (WQS index) and outpatient visits (IR%, percentage increases in risk per unit WQS index increase:1.73, 95%CI: 1.72, 1.74) as well as hospitalizations (IR%:5.15, 95%CI: 5.11, 5.20). Black carbon (weight: 0.34) and nitrate (weight: 0.60) respectively exhibited the highest contributions to outpatient visits and hospitalizations. The overall mixture effects on outpatient visits and hospitalizations were higher with increased summer air temperatures (IR%: 7.54, 95%CI: 7.33, 7.74 and IR%: 9.55, 95%CI: 8.36, 10.75, respectively) or decreased winter air temperatures (IR%: 1.88, 95%CI: 1.68, 2.08 and IR%: 4.87, 95%CI: 3.73, 6.02, respectively). Furthermore, the overall mixture effects on outpatient visits and hospitalizations were significantly higher in populations with higher socioeconomic status (P < 0.01). It's crucial to address the primary sources of nitrate precursor substances and black carbon (mainly traffic-related and industrial-related air pollutants) and consider the complex interaction effects between air temperature and PM2.5 in the context of climate change. Of particular concern is the need to prioritize healthcare demands in economically disadvantaged regions and to address the health inequalities stemming from the uneven distribution of healthcare resources and PM2.5 pollution.

Analysis of health service utilization and influencing factors due to COVID-19 in Beijing: a large cross-sectional survey.

BACKGROUND: In the wake of China's relaxed zero-COVID policy, there was a surge in coronavirus disease 2019 (COVID-19) infections. This study aimed to examine the infection status and health service utilization among Beijing residents during a widespread outbreak, and to explore the factors that affected utilization of health services due to COVID-19. METHODS: A cross-sectional survey was conducted among Beijing residents from 13 January to 13 February 2023, collecting information on socio-demographic characteristics, health behaviours, COVID-19 infection status, utilization of health services and depressive symptoms. Multivariate Tobit regression was used for data analysis. RESULTS: Among the 53 924 participants, 14.7% were older than 60 years, 63.7% were female and 84.8% were married. In total, 44 992 of the 53 924 individuals surveyed (83.4%) contracted COVID-19 during 2020-2023, and 25.2% (13 587) sought corresponding health services. The majority of individuals (85.6%) chose in-person healthcare, while 14.4% chose internet-based healthcare. Among those who chose in-person healthcare, 58.6% preferred primary healthcare institutions and 41.5% were very satisfied with the treatment. Factors affecting health service utilization include being female (ß = -0.15, P < 0.001), older than 60 years (ß = 0.23, P < 0.01), non-healthcare workers (ß = -0.60, P < 0.001), rich self-rated income level (ß = 0.59, P < 0.001), having underlying disease (ß = 0.51, P < 0.001), living alone (ß = -0.19, P < 0.05), depressive symptoms (ß = 0.06, P < 0.001) and healthy lifestyle habits, as well as longer infection duration, higher infection numbers and severe symptoms. CONCLUSION: As COVID-19 is becoming more frequent and less severe, providing safe and accessible healthcare remains critical. Vulnerable groups such as the elderly and those with underlying conditions need reliable health service. Prioritizing primary healthcare resources and online medical services have played a vital role in enhancing resource utilization efficiency.

Revisiting the complex time-varying effect of non-pharmaceutical interventions on COVID-19 transmission in the United States.

Introduction: Although the global COVID-19 emergency ended, the real-world effects of multiple non-pharmaceutical interventions (NPIs) and the relative contribution of individual NPIs over time were poorly understood, limiting the mitigation of future potential epidemics. Methods: Based on four large-scale datasets including epidemic parameters, virus variants, vaccines, and meteorological factors across 51 states in the United States from August 2020 to July 2022, we established a Bayesian hierarchical model with a spike-and-slab prior to assessing the time-varying effect of NPIs and vaccination on mitigating COVID-19 transmission and identifying important NPIs in the context of different variants pandemic. Results: We found that (i) the empirical reduction in reproduction number attributable to integrated NPIs was 52.0% (95%CI: 44.4, 58.5%) by August and September 2020, whereas the reduction continuously decreased due to the relaxation of NPIs in following months; (ii) international travel restrictions, stay-at-home requirements, and restrictions on gathering size were important NPIs with the relative contribution higher than 12.5%; (iii) vaccination alone could not mitigate transmission when the fully vaccination coverage was less than 60%, but it could effectively synergize with NPIs; (iv) even with fully vaccination coverage >60%, combined use of NPIs and vaccination failed to reduce the reproduction number below 1 in many states by February 2022 because of elimination of above NPIs, following with a resurgence of COVID-19 after March 2022. Conclusion: Our results suggest that NPIs and vaccination had a high synergy effect and eliminating NPIs should consider their relative effectiveness, vaccination coverage, and emerging variants.

Long-term PM1 exposure and hypertension hospitalization: A causal inference study on a large community-based cohort in South China.

Limited evidence exists on the effect of submicronic particulate matter (PM1) on hypertension hospitalization. Evidence based on causal inference and large cohorts is even more scarce. In 2015, 36,271 participants were enrolled in South China and followed up through 2020. Each participant was assigned single-year, lag0-1, and lag0-2 moving average concentration of PM1 and fine inhalable particulate matter (PM2.5) simulated based on satellite data at a 1-km resolution. We used an inverse probability weighting approach to balance confounders and utilized a marginal structural Cox model to evaluate the underlying causal links between PM1 exposure and hypertension hospitalization, with PM2.5-hypertension association for comparison. Several sensitivity studies and the analyses of effect modification were also conducted. We found that a higher hospitalization risk from both overall (HR: 1.13, 95% CI: 1.05-1.22) and essential hypertension (HR: 1.15, 95% CI: 1.06-1.25) was linked to each 1 µg/m3 increase in the yearly average PM1 concentration. At lag0-1 and lag0-2, we observed a 17%-21% higher risk of hypertension associated with PM1. The effect of PM1 was 6%-11% higher compared with PM2.5. Linear concentration-exposure associations between PM1 exposure and hypertension were identified, without safety thresholds. Women and participants that engaged in physical exercise exhibited higher susceptibility, with 4%-22% greater risk than their counterparts. This large cohort study identified a detrimental relationship between chronic PM1 exposure and hypertension hospitalization, which was more pronounced compared with PM2.5 and among certain groups.

Predicting the incidence of infectious diarrhea with symptom surveillance data using a stacking-based ensembled model.

BACKGROUND: Infectious diarrhea remains a major public health problem worldwide. This study used stacking ensemble to developed a predictive model for the incidence of infectious diarrhea, aiming to achieve better prediction performance. METHODS: Based on the surveillance data of infectious diarrhea cases, relevant symptoms and meteorological factors of Guangzhou from 2016 to 2021, we developed four base prediction models using artificial neural networks (ANN), Long Short-Term Memory networks (LSTM), support vector regression (SVR) and extreme gradient boosting regression trees (XGBoost), which were then ensembled using stacking to obtain the final prediction model. All the models were evaluated with three metrics: mean absolute percentage error (MAPE), root mean square error (RMSE), and mean absolute error (MAE). RESULTS: Base models that incorporated symptom surveillance data and weekly number of infectious diarrhea cases were able to achieve lower RMSEs, MAEs, and MAPEs than models that added meteorological data and weekly number of infectious diarrhea cases. The LSTM had the best prediction performance among the four base models, and its RMSE, MAE, and MAPE were: 84.85, 57.50 and 15.92%, respectively. The stacking ensembled model outperformed the four base models, whose RMSE, MAE, and MAPE were 75.82, 55.93, and 15.70%, respectively. CONCLUSIONS: The incorporation of symptom surveillance data could improve the predictive accuracy of infectious diarrhea prediction models, and symptom surveillance data was more effective than meteorological data in enhancing model performance. Using stacking to combine multiple prediction models were able to alleviate the difficulty in selecting the optimal model, and could obtain a model with better performance than base models.

Assessing the effectiveness of the expanded hepatitis A vaccination program in China: an interrupted time series design.

INTRODUCTION: China initialised the expanded hepatitis A vaccination programme (EHAP) in 2008. However, the effectiveness of the programme remains unclear. We aimed to comprehensively evaluate the effectiveness of EHAP in the country. METHODS: Based on the provincial data on the incidence of hepatitis A (HepA), the population and meteorological variables in China, we developed interrupted time series (ITS) models to estimate the effectiveness of EHAP with the autocorrelation, seasonality and the meteorological confounders being controlled. Results were also stratified by economic zones, age groups and provinces. RESULTS: We found a 0.9% reduction (RR=0.991, 95% CI: 0.990 to 0.991) in monthly HepA incidence after EHAP, which was 0.3% greater than the reduction rate before EHAP in China. Across the three economic regions, we found a 1.1% reduction in HepA incidence in both central and western regions after EHAP, which were 0.3% and 1.2% greater than the reduction rates before EHAP, respectively. We found a decreased reduction rate for the eastern region. In addition, we found generally increased reduction rate after EHAP for age groups of 0-4, 5-14 and 15-24 years. However, we found decreased reduction rate among the 25-64 and ≥65 years groups. We found a slight increased rate after EHAP in Shanxi Province but not elsewhere. CONCLUSION: Our finding provides comprehensive evidence on the effectiveness of EHAP in China, particularly in the central and western regions, and among the population aged 0-24 years old. This study has important implications for the adjustment of vaccination strategies for other regions and populations.

Assessing the impact of comorbid type 2 diabetes mellitus on the disease burden of chronic hepatitis B virus infection and its complications in China from 2006 to 2030: a modeling study.

BACKGROUND: China bears a high burden of both hepatitis B virus (HBV) infection and type 2 diabetes mellitus (T2DM). T2DM accelerates the progression of liver disease among individuals infected with HBV. This study aims to assess the excess disease burden caused by comorbid T2DM among HBV-infected individuals in China. METHODS: We estimated the disease burden of HBV and its complications in China from 2006 to 2030 using individual-based Markov models. The baseline population consisted of 93 million HBV-infected individuals derived from the 2006 National Serological Epidemiological Survey. We developed two models: one incorporated the impact of T2DM on the disease progression of HBV infection, while the other did not consider the impact of T2DM. By comparing the outcomes between these two models, we estimated the excess disease burden attributable to comorbid T2DM among HBV-infected individuals. RESULTS: The incidence of severe HBV complications, including cirrhosis, hepatocellular carcinoma (HCC), and liver-related deaths, exhibited an increasing trend from 2006 to 2030 among the Chinese HBV-infected population. Comorbid T2DM increased the annual incidence and cumulative cases of severe HBV complications. From 2006 to 2022, comorbid T2DM caused 791,000 (11.41%), 244,000 (9.27%), 377,000 (8.78%), and 796,000 (12.19%) excess cases of compensated cirrhosis, decompensated cirrhosis, HCC, and liver-related deaths, respectively. From 2023 to 2030, comorbid T2DM is projected to result in an 8.69% excess in severe HBV complications and an 8.95% increase in liver-related deaths. Among individuals aged 60 and older at baseline, comorbid T2DM led to a 21.68% excess in severe HBV complications and a 28.70% increase in liver-related deaths from 2006 to 2022, with projections indicating a further 20.76% increase in severe HBV complications and an 18.31% rise in liver-related deaths over the next seven years. CONCLUSIONS: Comorbid T2DM imposes a substantial disease burden on individuals with HBV infection in China. Healthcare providers and health policymakers should develop and implement tailored strategies for the effective management and control of T2DM in individuals with HBV infection.

Potential causal links and mediation pathway between urban greenness and lung cancer mortality: Result from a large cohort (2009 to 2020).

Urban greenness, as a vital component of the urban environment, plays a critical role in mitigating the adverse effects of rapid urbanization and supporting urban sustainability. However, the causal links between urban greenness and lung cancer mortality and its potential causal pathway remain poorly understood. Based on a prospective community-based cohort with 581,785 adult participants in southern China, we applied a doubly robust Cox proportional hazard model to estimate the causal associations between urban greenness exposure and lung cancer mortality. A general multiple mediation analysis method was utilized to further assess the potential mediating roles of various factors including particulate matter (PM1, PM2.5-1, and PM10-2.5), temperature, physical activity, and body mass index (BMI). We observed that each interquartile range (IQR: 0.06) increment in greenness exposure was inversely associated with lung cancer mortality, with a hazard ratio (HR) of 0.89 (95 % CI: 0.83, 0.96). The relationship between greenness and lung cancer mortality might be partially mediated by particulate matter, temperature, and physical activity, yielding a total indirect effect of 0.826 (95 % CI: 0.769, 0.887) for each IQR increase in greenness exposure. Notably, the protective effect of greenness against lung cancer mortality could be achieved primarily by reducing the particulate matter concentration.

Spatial-temporal distribution of preterm birth in China, 1990-2020: A systematic review and modelling analysis.

BACKGROUND: Little is known about the long-term trends of preterm birth rates in China and their geographic variation by province. OBJECTIVES: To estimate the annual spatial-temporal distribution of preterm birth rates in China by province from 1990 to 2020. DATA SOURCES: We searched PubMed, EMBASE, Web of Science, CNKI, WANFANG and VIP from January 1990 to September 2023. STUDY SELECTION AND DATA EXTRACTION: Studies that provided data on preterm births in China after 1990 were included. Data were extracted following the Guidelines for Accurate and Transparent Health Estimates Reporting. SYNTHESIS: We assessed the quality of each survey using a 9-point checklist. We estimated the annual preterm birth risk by province using Bayesian multilevel logistic regression models considering potential socioeconomic, environmental, and sanitary predictors. RESULTS: Based on 634 survey data from 343 included studies, we found a gradual increase in the preterm birth risk in most provinces in China since 1990, with an average annual increase of 0.7% nationally. However, the preterm birth rates in Inner Mongolia, Hubei, and Fujian Province showed a decline, while those in Sichuan were quite stable since 1990. In 2020, the estimates of preterm birth rates ranged from 2.9% (95% Bayesian credible interval [BCI] 2.1, 3.8) in Inner Mongolia to 8.5% (95% BCI 6.6, 10.9) in Jiangxi, with the national estimate of 5.9% (95% BCI 4.3, 8.1). Specifically, some provinces were identified as high-risk provinces for either consistently high preterm birth rates (e.g. Jiangxi) or relatively large increases (e.g. Shanxi) since 1990. CONCLUSIONS: This study provides annual information on the preterm birth risk in China since 1990 and identifies high-risk provinces to assist in targeted control and intervention for this health issue.

The impact of long-term PM1 exposure on all-cause mortality and its interaction with BMI: A nationwide prospective cohort study in China.

BACKGROUND: China has a serious air pollution problem and a high prevalence of obesity. The interaction between the two and its impact on all-cause mortality is a public health issue of great concern. OBJECTIVES: This study aimed to investigate the association between long-term exposure to particulate matter with aerodynamic diameter ≤ 1 µm (PM1) and all-cause mortality, as well as the interaction effect of body mass index (BMI) in the association. METHODS: A total of 33,087 participants from 162 counties in 25 provinces in China were included, with annual average PM1 exposure being estimated based on the county address. The PM1-mortality relation was evaluated using the time-varying Cox proportional hazards models, with the dose-response relationship being fitted using the penalized splines. Besides, the potential interaction effect of BMI in the PM1-mortality relation was evaluated. RESULTS: The incidence of all-cause deaths was 76.99 per 10,000 person-years over a median of 8.2 years of follow-up. After controlling for potential confounders, the PM1-mortality relation was approximately J-shaped. The full-adjustment analysis observed the hazard ratio (HR) of all-cause mortality was 1.114 [95 % confidence interval (CI): 1.017-1.220] corresponding to a 10 µg/m3 rise in PM1 concentration. Further stratified analyses suggested the adverse effects of PM1 might be more pronounced among the underweight. DISCUSSION: Higher PM1 concentrations were associated with an increase in all-cause mortality. The BMI might further alter the relation, and the underweight population was the sensitive subgroup of the population that needed to be protected.

The role of illness-related cognition in the relationships between resilience and depression/anxiety in nasopharyngeal cancer patients.

OBJECTIVE: Resilience has been reported as an important predictor of better mental health and prognoses in cancer patients, while its mechanisms were not clearly elucidated. In this study, we surveyed a large sample of nasopharyngeal carcinoma patients to investigate the mediating role of illness-related cognition (illness perception, stigma and meaning in life) on the associations between resilience and symptoms of anxiety and depression. METHODS: This cross-sectional study involved 773 participants diagnosed with nasopharyngeal carcinoma. Participants completed a self-reported structured questionnaire to assess their illness perception, stigma and meaning in life, resilience and symptoms of anxiety and depression. Structural equation models (SEM) were employed to explore the relationship between resilience and symptoms of anxiety and depression in the entire sample, as well as in two subgroups: Subgroup I (0-1 year since diagnosis), and Subgroup II (over 1 year since diagnosis). RESULTS: In the entire sample, after adjusting for potential confounders, illness perception, stigma and meaning in life were found to mediate the protective effect of resilience on symptoms of depression (mediating effect proportion: 65.25%) and anxiety (mediating effect proportion: 67.63%). In Subgroup I, direct effects were dominant in the associations between resilience and symptoms of anxiety (mediating effect proportion: 37.95%) and depression (mediating effect proportion: 29.13%). However, in Subgroup II, the associations between resilience and symptoms of anxiety (mediating effect proportion: 98.92%) and depression (mediating effect proportion: 81.04%) were completely mediated. CONCLUSIONS: Our study suggests that direct and indirect effects of resilience on depression and anxiety dominate in early periods (0-1 year) and long-term periods (over 1 year) following the cancer diagnosis, respectively. The findings indicate that comprehensive intervention considering both the direct effect of resilience in early stages (e.g., health education prescription and social support groups) and the indirect effects of illness cognition in long-term periods (e.g., cognitive behavioral therapies) are likely to yield the most favorable outcomes for cancer patients.