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.

Potential causal links of long-term exposure to PM2.5 and its chemical components with the risk of nasopharyngeal carcinoma recurrence: A 10-year cohort study in South China.

There is a lack of evidence from cohort studies on the causal association of long-term exposure to ambient fine particulate matter (PM2.5) and its chemical components with the risk of nasopharyngeal carcinoma (NPC) recurrence. Based on a 10-year prospective cohort of 1184 newly diagnosed NPC patients, we comprehensively evaluated the potential causal links of ambient PM2.5 and its chemical components including black carbon (BC), organic matter (OM), sulfate (SO4 2-), nitrate (NO3 -), and ammonium (NH4 +) with the recurrence risk of NPC using a marginal structural Cox model adjusted with inverse probability weighting. We observed 291 NPC patients experiencing recurrence during the 10-year follow-up and estimated a 33% increased risk of NPC recurrence (hazard ratio [HR]: 1.33, 95% confidence interval [CI]: 1.02-1.74) following each interquartile range (IQR) increase in PM2.5 exposure. Each IQR increment in BC, NH4 +, OM, NO3 -, and SO4 2- was associated with HRs of 1.36 (95%CI: 1.13-1.65), 1.35 (95%CI: 1.07-1.70), 1.33 (95%CI: 1.11-1.59), 1.32 (95%CI: 1.06-1.64), 1.31 (95%CI: 1.08-1.57). The elderly, patients with no family history of cancer, no smoking history, no drinking history, and those with severe conditions may exhibit a greater likelihood of NPC recurrence following exposure to PM2.5 and its chemical components. Additionally, the effect estimates of the five components are greater among patients who were exposed to high concentration than in the full cohort of patients. Our study provides solid evidence for a potential relationship between long-term exposure to PM2.5 and its components and the risk of NPC recurrence.

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.

The efficacy and safety of adding PD-1 blockade to induction chemotherapy and concurrent chemoradiotherapy (IC-CCRT) for locoregionally advanced nasopharyngeal carcinoma: an observational, propensity score-matched analysis.

BACKGROUND: Despite the success of PD-1 blockade in recurrent/metastatic nasopharyngeal carcinoma (NPC), its effect for locoregionally advanced NPC (LANPC) remains unclear. This study aimed to evaluate the benefit of adding PD-1 blockade to the current standard treatment (gemcitabine and cisplatin IC  plus cisplatin CCRT ) for LANPC patients. METHODS: From January 2020 to November 2022, 347 patients with non-metastatic high-risk LANPC (stage III-IVA, excluding T3-4N0) were included. Of the 347 patients, 268 patients were treated with standard treatment (IC-CCRT), and 79 received PD-1 blockade plus IC-CCRT (PD-1 group). For the PD-1 group, PD-1 blockade was given intravenously once every 3 weeks for up to 9 cycles (3 induction and 6 adjuvant). The primary endpoint was disease-free survival (DFS) (i.e. freedom from local/regional/distant failure or death). The propensity score matching (PSM) with the ratio of 1:2 was performed to control confounding factors. RESULTS: After PSM analysis, 150 patients receiving standard treatment and 75 patients receiving additional PD-1 blockade remained in the current analysis. After three cycles of IC, the PD-1 group had significantly higher rates of complete response (defined as disappearance of all target lesions; 24% vs. 9%; P = 0.006) and complete biological response (defined as undetectable cell-free Epstein-Barr virus DNA, cfEBV DNA; 79% vs. 65%; P = 0.046) than that in the standard group. And the incidence of grade 3-4 toxicity during IC was 47% in the PD-1 group and 41% in the standard group, with no significant difference (P = 0.396). During follow-up period, additional PD-1 blockade to standard treatment improved 3-year DFS from 84 to 95%, with marginal statistical significance (HR, 0.28; 95%CI, 0.06-1.19; P = 0.064). CONCLUSION: Additiaonl PD-1 blockade to gemcitabine and cisplatin IC and adjuvant treatment results in significant improvement in tumor regression, cfEBV DNA clearance, superior DFS, and comparable toxicity profiles in high-risk LANPC patients.

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.

Development of a machine learning-based prediction model for clinical pregnancy of intrauterine insemination in a large Chinese population.

PURPOSE: This study aimed to evaluate the effectiveness of a random forest (RF) model in predicting clinical pregnancy outcomes from intrauterine insemination (IUI) and identifying significant factors affecting IUI pregnancy in a large Chinese population. METHODS: RESULTS: A total of 11 variables, including eight from female (age, body mass index, duration of infertility, prior miscarriage, and spontaneous abortion), hormone levels (anti-Müllerian hormone, follicle-stimulating hormone, luteinizing hormone), and three from male (smoking, semen volume, and sperm concentration), were identified as the significant variables associated with IUI clinical pregnancy in our Chinese dataset. The RF-based prediction model presents an area under the receiver operating characteristic curve (AUC) of 0.716 (95% confidence interval, 0.6914-0.7406), an accuracy rate of 0.6081, a sensitivity rate of 0.7113, and a specificity rate of 0.505. Importance analysis indicated that semen volume was the most vital variable in predicting IUI clinical pregnancy. CONCLUSIONS: The machine learning-based IUI clinical pregnancy prediction model showed a promising predictive efficacy that could provide a potent tool to guide selecting targeted infertile couples beneficial from IUI treatment, and also identify which parameters are most relevant in IUI clinical pregnancy.

The relative contribution of PM2.5 components to the obstructive ventilatory dysfunction-insights from a large ventilatory function examination of 305,022 workers in southern China.

BACKGROUND: The new round of WHO/ILO Joint Estimates of the Work-related Burden of Disease assessment requires futher research to provide more evidence, especially on the health impact of ambient air pollution around the workplace. However, the evidence linking obstructive ventilatory dysfunction (OVD) to fine particulate matter (PM2.5) and its chemical components in workers is very limited. Evidence is even more scarce on the interactive effects between occupational factors and particle exposures. We aimed to fill these gaps based on a large ventilatory function examination of workers in southern China. METHODS: We conducted a cross-sectional study among 363,788 workers in southern China in 2020. The annual average concentration of PM2.5 and its components were evaluated around the workplace through validated spatiotemporal models. We used mixed-effect models to evaluate the risk of OVD related to PM2.5 and its components. Results were further stratified by basic characteristics and occupational factors. FINDINGS: Among the 305,022 workers, 119,936 were observed with OVD. We found for each interquartile range (IQR) increase in PM2.5 concentration, the risk of OVD increased by 27.8 (95 % confidence interval (CI): 26.5-29.2 %). The estimates were 10.9 % (95 %CI: 9.7-12.1 %), 15.8 % (95 %CI: 14.5-17.2 %), 2.6 % (95 %CI: 1.4-3.8 %), 17.1 % (95 %CI: 15.9-18.4 %), and 11 % (95 %CI: 9.9-12.2 %), respectively, for each IQR increment in sulfate, nitrate, ammonium salt, organic matter and black carbon. We observed greater effect estimates among females, younger workers, workers with a length of service of 24-45 months, and professional skill workers. Furthermore, it is particularly noteworthy that the noise-exposed workers, high-temperature-exposed workers, and less-dust-exposed workers were at a 5.7-68.2 % greater risk than others. INTERPRETATION: PM2.5 and its components were significantly associated with an increased risk of OVD, with stronger links among certain vulnerable subgroups.

Hidden danger: The long-term effect of ultrafine particles on mortality and its sociodemographic disparities in New York State.

Although previous studies have shown increased health risks of particulate matters, few have evaluated the long-term health impacts of ultrafine particles (UFPs or PM0.1, ≤ 0.1 µm in diameter). This study assessed the association between long-term exposure to UFPs and mortality in New York State (NYS), including total non-accidental and cause-specific mortalities, sociodemographic disparities and seasonal trends. Collecting data from a comprehensive chemical transport model and NYS Vital Records, we used the interquartile range (IQR) and high-level UFPs (≥75 % percentile) as indicators to link with mortalities. Our modified difference-in-difference model controlled for other pollutants, meteorological factors, spatial and temporal confounders. The findings indicate that long-term UFPs exposure significantly increases the risk of non-accidental mortality (RR=1.10, 95 % CI: 1.05, 1.17), cardiovascular mortality (RR=1.11, 95 % CI: 1.05, 1.18) particularly for cerebrovascular (RR=1.21, 95 % CI: 1.10, 1.35) and pulmonary heart diseases (RR=1.33, 95 % CI: 1.13, 1.57), and respiratory mortality (borderline significance, RR=1.09, 95 % CI: 1.00, 1.18). Hispanics (RR=1.13, 95 % CI: 1.00, 1.29) and non-Hispanic Blacks (RR=1.40, 95 % CI: 1.16, 1.68) experienced significantly higher mortality risk after exposure to UFPs, compared to non-Hispanic Whites. Children under five, older adults, non-NYC residents, and winter seasons are more susceptible to UFPs' effects.

Ultrafine Particles and Hospital Visits for Chronic Lower Respiratory Diseases in New York State.

RATIONALE: Exposure to particulate matter is associated with various adverse health outcomes. Ultrafine particles are a unique public health challenge due to their size. However, limited studies have examined their impacts on human health, especially across seasons and demographics. OBJECTIVES: To evaluate the effect of ultrafine particle exposure on the risk of visiting the emergency department for a chronic lower respiratory disease in New York State NYS, 2013-2018. METHODS: We used a case-crossover design and conditional logistic regression to estimate how ultrafine particle exposure led to chronic lower respiratory disease-related emergency department visits. GEOS-Chem-APM, a state-of-the-art chemical transport model with a size-resolved particle microphysics model, generated air pollution simulation data. We then matched ultrafine particle exposure estimates to geocoded health records for asthma, bronchiectasis, chronic bronchitis, emphysema, unspecified bronchitis, and other chronic airway obstructions in NYS from 2013-2018. In addition, we assessed interactions with age, ethnicity, race, sex, meteorological factors, and season. MEASUREMENTS AND MAIN RESULTS: Each interquartile range increase in ultrafine particle exposure led to a 0.37% increased risk of a respiratory-related emergency department visit on lag 0-0 (95% CI: 0.23-0.52%) and a 1.81% increase on lag 0-6 (95% CI: 1.58-2.03%). The highest risk was in the subtype emphysema (lag 0-5: 4.18%, 95% CI: 0.16-8.37%), followed by asthma (lag 0-6: 2.00%), chronic bronchitis (lag 0-6: 1.78%), other chronic airway obstructions (lag 0-6: 1.60%), and unspecified bronchitis (lag 0-6: 1.49%). We also found significant interactions between UFP health impacts and season (fall, 3.29%), temperature (<90th percentile, 2.27%), relative humidity (>90th percentile, 4.63%), age (children <18, 3.19%), and sex (men, 2.06%) on lag 0-6. CONCLUSION: In this study, UFP exposure increased chronic lower respiratory disease-related emergency department visits across all seasons and demographics, yet these associations varied according to various factors, which requires more research.

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.

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.

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.

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.

Neoadjuvant chemotherapy plus concurrent chemoradiotherapy versus concurrent chemoradiotherapy alone in elderly patients with stage III-IVa nasopharyngeal carcinoma: A real-world study based on medical comorbidities.

PURPOSE: To evaluate the outcomes and toxicities of adding neoadjuvant chemotherapy (NAC) to concurrent chemoradiotherapy (CCRT) in elderly (≥65 years) patients with locoregionally advanced nasopharyngeal carcinoma (LANPC, stage III-IVa). METHODS AND MATERIALS: Using an NPC-specific database, 245 elderly patients with stage III-IVa NPC, receiving CCRT +/- NAC, and an Adult Co-morbidity Evaluation 27 (ACE-27) score <2 were included. Recursive partitioning analysis (RPA) based on TNM stage and Epstein-Barr virus (EBV) DNA were applied for risk stratification. The primary end point was disease-free survival (DFS). RESULTS: Two risk groups were generated by the RPA model. In the high-risk group (EBV DNA < 4000 copy/ml with stage IVa & EBV DNA ≥4000 copy/ml with stage III-IVa), patients treated with NAC plus CCRT achieved improved 5-year DFS rates compared to those who received CCRT alone (56.9% vs. 29.4%; p = 0.003). But we failed to observe the survival benefit of additional NAC in the low-risk group (EBV DNA <4000 copy/ml with stage III). The most common severe acute toxic effects were leucopenia (46.8% vs. 24.4%) and neutropenia (43.7% vs. 20.2%) in the NAC plus CCRT group versus CCRT group with statistically significant differences. CONCLUSIONS: The addition of NAC to CCRT was associated with better DFS for the high-risk group of elderly LANPC patients with ACE-27 score <2. However, the survival benefit of additional NAC was not observed in low-risk patients.

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.

The joint effects of mixture exposure to multiple meteorological factors on step count: A panel study in China.

The public health burden of increasing extreme weather events has been well documented. However, the influence of meteorological factors on physical activity remains limited. Existing mixture effect methods cannot handle cumulative lag effects. Therefore, we developed quantile g-computation Distributed lag non-linear model (QG-DLNM) by embedding a DLNM into quantile g-computation to allow for the concurrent consideration of both cumulated lag effects and mixture effects. We gathered repeated measurement data from Henan Province in China to investigate both the individual impact of meteorological factor on step counts using a DLNM, and the joint effect using the QG-DLNM. We projected future step counts linked to changes in temperature and relative humidity driven by climate change under three scenarios from the sixth phase of the Coupled Model Intercomparison Project. Our findings indicate there are inversed U-shaped associations for temperature, wind speed, and mixture exposure with step counts, peaking at 11.6 °C in temperature, 2.7 m/s in wind speed, and 30th percentile in mixture exposure. However, there are negative associations between relative humidity and rainfall with step counts. Additionally, relative humidity possesses the highest weights in the joint effect (49% contribution). Compared to 2022s, future step counts are projected to decrease due to temperature changes, while increase due to relative humidity changes. However, when considering both future temperature and humidity changes driven by climate change, the projections indicate a decrease in step counts. Our findings may suggest Chinese physical activity will be negatively influenced by global warming.

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.

The association between outdoor light at night exposure and adult obesity in Northeastern China.

Previous studies have linked exposure to light at night (LAN) with various health outcomes, but evidence is limited for the LAN-obesity association. Thestudy analysed data from 24,845 participants of the 33 Communities Chinese Health Study and obesity (BMI ≥28 kg/m2) was defined according to the Working Group on Obesity in China. The Global Radiance Calibrated Nighttime Lights data were used to estimate participants' LAN exposure. The mixed-effect regression models examined the LAN-BMI and LAN-obesity association. We found that higher LAN exposure was significantly associated with greater BMI and higher risk of obesity. Changes of BMI and the odds ratios (ORs) of obesity and 95% confidence intervals (CIs) for 2nd, 3rd, and 4th against the 1st quartile of LAN exposure were 0.363 (0.208, 0.519), 0.364 (0.211, 0.516) and 0.217 (0.051, 0.383); 1.228 (1.099, 1.371), 1.356 (1.196, 1.538) and 1.269 (1.124, 1.433), respectively. Age and regular exercise showed significant modification effects on the LAN-obesity association.

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.