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.

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.

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 (β = -0.15, P < 0.001), older than 60 years (β = 0.23, P < 0.01), non-healthcare workers (β = -0.60, P < 0.001), rich self-rated income level (β = 0.59, P < 0.001), having underlying disease (β = 0.51, P < 0.001), living alone (β = -0.19, P < 0.05), depressive symptoms (β = 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.

[A survey on the current situation of serum vitamin A and vitamin D levels among children aged 2-<7 years of 20 cities in China]

Objective: To investigate serum vitamin A and vitamin D status in children aged 2-<7 years in 20 cities in China. Methods: A cross-sectional study was conducted. A total of 2 924 healthy children aged 2-<7 years were recruited from September 2018 to September 2019 from 20 cities in China, categorized by age groups of 2-<3 years, 3-<5 years, and 5-<7 years. The demographic and economic characteristics and health-related information of the enrolled children were investigated. Body weight and height were measured by professional staff members. The serum vitamin A and vitamin D levels were detected by high-performance liquid chromatography-tandem mass spectrometry. Chi-square test and Logistic regression were applied to analyze the association between vitamin A and vitamin D deficiency and insufficiency as well as their underlying impact factors. Results: The age of the 2 924 enrolled children was 4.33 (3.42, 5.17) years. There were 1 726 males (59.03%) and 1 198 females (40.97%). The prevalences of vitamin A and vitamin D deficiency in enrolled children were 2.19% (64/2 924) and 3.52% (103/2 924), respectively, and the insufficiency rates were 29.27% (856/2 924) and 22.20% (649/2 924), respectively. Children with both vitamin A and vitamin D deficiencies or insufficiencies were found in 10.50% (307/2 924) of cases. Both vitamin A (χ2=7.91 and 8.06, both P=0.005) and vitamin D (χ2=71.35 and 115.10, both P<0.001) insufficiency rates were higher in children aged 3-<5 and 5-<7 years than those in children aged 2-<3 years. Vitamin A and vitamin D supplementation in the last 3 months was a protective factor for vitamin A and D deficiency and insufficiency, respectively (OR=0.68 and 0.22, 95%CI 0.49-0.95 and 0.13-0.40, both P<0.05). The rates of vitamin A and D insufficiency was higher in children with annual household incomes <60 000 RMB than in those with annual household incomes ≥60 000 RMB (χ2=34.11 and 10.43, both P<0.01). Northwest and Southwest had the highest rates of vitamin A and vitamin D insufficiency in children aged 2-<7 yeas, respectively (χ2=93.22 and 202.54, both P<0.001). Conclusions: Among 20 cities in China, children aged 2-<7 years experience high rates of vitamin A and vitamin D insufficiency, which are affected by age, family economic level, vitamin A and vitamin D supplementation, and regional economic level. The current results suggest that high level of attention should be paid to vitamin A and vitamin D nutritional status of preschool children.

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.

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.

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.

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.

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.

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 of long-term air pollution with lung cancer incidence: From the perspectives of mortality and hospital admission in a large cohort study in southern China

Evidence on the potential causal links of long-term air pollution exposure with lung cancer incidence (reflected by mortality and hospital admission) was limited, especially based on large cohorts. We examined the relationship between lung cancer and long-term exposure to particulate matter (PM, including PM2.5 , PM10 and PM10-2.5 ) and nitrogen dioxide (NO2 ) among a large cohort of general Chinese adults using causal inference approaches. The study included 575 592 participants who were followed up for an average of 8.2 years. The yearly exposure of PM and NO2 was estimated through satellite-based random forest approaches and the ordinary kriging method, respectively. Marginal structural Cox models were used to examine hazard ratios (HRs) of mortality and hospital admission due to lung cancer following air pollution exposure, adjusting for potential confounders. The HRs of mortality due to lung cancer were 1.042 (95% confidence interval [CI]: 1.033-1.052), 1.032 (95% CI:1.024-1.041) and 1.052 (95% CI:1.041-1.063) for each 1 μg/m3 increase in PM2.5 , PM10 and NO2 , respectively. In addition, we observed statistically significant effects of PMs on hospital admission due to lung cancer. The HRs (95%CI) were 1.110 (1.027-1.201), 1.067 (1.020-1.115) and 1.079 (1.010-1.153) for every 1 μg/m3 increase in PM2.5 , PM10 , PM10-2.5 , respectively. Furthermore, we found larger effect estimates among the elderly and those who exercised more frequently. We provided the most comprehensive evidence of the potential causal links between two outcomes of lung cancer and long-term air pollution exposure. Relevant policies should be developed, with special attention to protecting the vulnerable groups of the population.

Intravesical chemotherapy synergize with an immune adjuvant by a thermo-sensitive hydrogel system for bladder cancer

Surgical resection remains the prefer option for bladder cancer treatment. However, the effectiveness of surgery is usually limited for the high recurrence rate and poor prognosis. Consequently, intravesical chemotherapy synergize with immunotherapy in situ is an attractive way to improve therapeutic effect. Herein, a combined strategy based on thermo-sensitive PLEL hydrogel drug delivery system was developed. GEM loaded PLEL hydrogel was intravesical instilled to kill tumor cells directly, then PLEL hydrogel incorporated with CpG was injected into both groins subcutaneously to promote immune responses synergize with GEM. The results demonstrated that drug loaded PLEL hydrogel had a sol-gel phase transition behavior in response to physiological temperature and presented sustained drug release, and the PLEL-assisted combination therapy could have better tumor suppression effect and stronger immunostimulating effect in vivo. Hence, this combined treatment with PLEL hydrogel system has great potential and suggests a clinically-relevant and valuable option for bladder cancer.

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.

Long-term particulate matter exposure and the risk of neurological hospitalization: Evidence from causal inference of a large longitudinal cohort in South China

With limited evidence on the neurological impact of particulate matter (PM) exposure in China, particularly for PM1 which is smaller but more toxic, we conducted a large Chinese cohort study using causal inference approaches to comprehensively clarify such impact. A total of 36,271 participants in southern China were recruited in 2015 and followed up through 2020. We obtained the neurological hospitalizations records by linking the cohort data to the electronic reports from 418 medical institutions across the study area. By using high-resolution PM concentrations from satellite-based spatiotemporal models and the cohort data, we performed marginal structural Cox models under causal assumptions to assess the potential causal links between time-varying PM exposure and neurological hospitalizations. Our findings indicated that increasing PM1, PM2.5, and PM10 concentrations by 1 μg/m³ were associated with higher overall neurological hospitalization risks, with hazard ratios (HRs) of 1.10 (95% confidence interval (CI) 1.04-1.16), 1.09 (95% CI 1.04-1.14), and 1.03 (95% CI 1.00-1.06), respectively. PM1 appeared to have a stronger effect on neurological hospitalization, with a 1% and 7% higher impact compared to PM2.5 and PM10, respectively. Additionally, each 1-μg/m3 increase in the annual PM1 concentration was associated with an elevated risk of hospitalizations for ischemic stroke (HR: 1.15; 95% CI, 1.06-1.26), which tended to be larger than the estimates for PM2.5 (HR: 1.13, 95% CI, 1.04-1.23) and PM10 (HR: 1.05, 95% CI, 1.00-1.09). Furthermore, never-married or female individuals tended be at a greater risk compared with their counterparts. Our study provides important insights into the health impact of particles, particularly smaller particles, on neurological hospitalization risk and highlights the need for clean-air policies that specifically target these particles.

The complex role of air pollution on the association between greenness and respiratory mortality: Insight from a large cohort, 2009-2020

BACKGROUND

Although emerging studies have illuminated the protective association between greenness and respiratory mortality, efforts to quantify the potentially complex role of air pollution in the causal pathway are still limited. We aimed to examine the potential roles of air pollution in the causal pathway between greenness and respiratory mortality in China.

METHODS

We used data from a community-based prospective cohort of 654,115 participants in southern China (Jan 2009-Dec 2020). We evaluated the greenness exposure as a three-year moving average Normalized Difference Vegetation Index (NDVI) within the 500 m buffer around the residence. Cox proportional hazards model was applied to estimate the association between greenness and respiratory mortality. Causal mediation analysis combined with a four-way dimensional decomposition method was utilized to simultaneously quantify the interaction and mediation role of air pollution including PM2.5, PM10, or NO2 on the greenness-respiratory mortality relationship.

FINDINGS

We observed 6954 respiratory deaths during 12 years of follow-up. Increasing NDVI level from the lowest to the highest quartile is associated with a 19 % (95%CI: 13-25 %) reduction in the respiratory mortality risk. For the total protective effect, the proportion attributable to the overall negative interaction between greenness and air pollution (PM2.5, PM10, or NO2) was 2.2 % (1.7-3.2 %), 3.5 % (0.4-3.7 %), or 25.0 % (22.8-27.1 %), respectively. Simultaneously, we estimated 25.5 % (20.1-32.0 %), 49.5 % (32.5-71.9 %), or 1.0 % (0.8-1.2 %) of the total protective association was mediated through a reduction in PM2.5, PM10, or NO2, respectively.

INTERPRETATION

Increased greenness exposure mitigated respiratory mortality through both the antagonistic interaction and mediation pathway of air pollution (PM2.5, PM10, or NO2).

[Comparison of BCR::ABL (P210) mRNA levels detected by dPCR and qPCR methods in patients with chronic myeloid leukemia]

Objective: To compare digital polymerase chain reaction (dPCR) and real-time quantitative PCR (qPCR) measurements of BCR::ABL (P210) mRNA expression in patients with chronic myeloid leukemia (CML) . Methods: In this non-interventional, cross-sectional study, BCR::ABL (P210) mRNA was simultaneously measured by dPCR and qPCR in peripheral blood samples collected from patients with CML who underwent tyrosine kinase inhibitor therapy and who achieved at least a complete cytogenetic response from September 2021 to February 2023 at Peking University People's Hospital. The difference, correlation, and agreement between the two methods were evaluated using the Wilcoxon signed-rank test, Spearman's correlation, and Bland-Altman analysis, respectively. Results: In total, 459 data pairs for BCR::ABL mRNA expression measured by dPCR and qPCR from 356 patients with CML were analyzed. There was a significant difference in BCR::ABL mRNA expression between the two methods (P<0.001). When analyzed by the depth of the molecular response (MR), a significant difference only existed for patients with ≥MR4.5 (P<0.001). No significant difference was observed for those who did not achieve a major MR (no MMR; P=0.922) or for those who achieved a major MR (MMR; P=0.723) or MR4 (P=0.099). There was a moderate correlation between the BCR::ABL mRNA expression between the two methods (r=0.761, P<0.001). However, the correlation gradually weakened or disappeared as the depth of the MR increased (no MMR: r=0.929, P<0.001; MMR: r=0.815, P<0.001; MR4: r=0.408, P<0.001; MR4.5: r=0.176, P=0.176). In addition, the agreement in BCR::ABL mRNA expression between the two methods in those with MR4.5 was weaker than other groups (no MMR: ▉= 0.042, P=0.846; MMR:▉=0.054, P=0.229; MR4:▉=-0.020, P=0.399; MR4.5:▉=-0.219, P<0.001) . Conclusions: dPCR is more accurate than qPCR for measuring BCR::ABL (P210) mRNA expression in patients with CML who achieve a stable deep MR.

[Evaluation of the application value of seven tumor-associated autoantibodies in non-small cell lung cancer based on machine learning algorithms]

Objective: Based on the diagnostic model established and validated by the machine learning algorithm, to investigate the value of seven tumor-associated autoantibodies (TAABs), namely anti-p53, PGP9.5, SOX2, GAGE7, GBU4-5, MAGEA1 and CAGE antibodies in the diagnosis of non-small cell lung cancer (NSCLC) and to differentiate between NSCLC and benign lung nodules. Methods: This was a retrospective study of clinical cases. Model building queue: a total of 227 primary patients who underwent radical lung cancer surgery in the Department of Thoracic Surgery, Shengjing Hospital of China Medical University, from November 2018 to June 2021 were collected as the NSCLC group, and 120 cases of benign lung nodules, 122 cases of pneumonia and 120 healthy individuals were selected as the control groups. External validation queue: a total of 100 primary patients who underwent radical lung cancer surgery in the Department of Thoracic Surgery, Shengjing Hospital of China Medical University, from May 2022 to December 2022 were collected as the NSCLC group, and 36 cases of benign lung nodules, 32 cases of pneumonia and 44 healthy individuals were selected as the control groups. In addition, NSCLC was divided into early (stage 0-ⅠB) and mid-to-late (stage ⅡA-ⅢB) subgroups. The levels of 7-TAABs were detected by enzyme immunoassay, and serum concentrations of CEA and CYFRA21-1 were detected by electrochemiluminescence. Four machine learning algorithms, XGBoost, Lasso logistic regression, Naïve Bayes, and Support Vector Machine are used to establish classification models. And the best performance model was chosen based on evaluation metrics and a multi-indicator combination model was established. In addition, an online risk evaluation tool was generated to assist clinical applications. Results: Except for p53, the levels of rest six TAABs, CEA and CYFRA21-1 were significantly higher in the NSCLC group (P<0.05). Serum levels of anti-SOX2 [1.50 (0.60, 10.85) U/ml vs. 0.8 (0.20, 2.10) U/ml, Z=2.630, P<0.05] and MAGEA1 antibodies [0.20 (0.10, 0.43) U/ml vs. 0.10 (0.10, 0.20) U/ml, Z=2.289, P<0.05], CEA [3.13 (2.12, 5.64) ng/ml vs. 2.11 (1.25, 3.09) ng/ml, Z=3.970, P<0.05] and CYFRA21-1 [4.31(2.37, 7.14) ng/ml vs. 2.53(1.92, 3.48) ng/ml, Z=3.959, P<0.05] were significantly higher in patients with mid-to late-stage NSCLC than in early stages. XGBoost model was used to establish a multi-indicator combined detection model (after removing p53). 6-TAABs combined with CYFRA21-1 was the best combination model for the diagnosis of NSCLC and early NSCLC. The optimal diagnostic thresholds were 0.410, 0.701 and 0.744, and the AUC was 0.828, 0.757 and 0.741, respectively (NSCLC vs. control, NSCLC vs. benign lung nodules, early NSCLC vs. benign lung nodules) in model building queue, and the AUC was 0.760, 0.710 and 0.660, respectively (NSCLC vs. control, NSCLC vs. benign lung nodules, early NSCLC vs. benign lung nodules) in external validation queue. Conclusion: In the diagnosis of NSCLC, 6-TAABs is superior to that of traditional tumor markers CEA and CYFRA21-1, and can compensate for the shortcomings of traditional tumor markers. For the differential diagnosis of NSCLC and benign lung nodule, "6-TAABs+CYFRA21-1" is the most cost-effective combination, and plays an important role in prevention and screening for early lung cancer.

Performance of Adaptive Deep Learning Models for Dose Predictions on High-Quality Cone-Beam Computed Tomography Images

PURPOSE/OBJECTIVE(S)

Online plan generation remains a patient-specific and time-consuming process that can place a significant burden on clinics strained with staffing shortages. As previous research show that dose-volume histogram (DVH) prediction plays a crucial role in automatic treatment planning, the objective of this study is to assess the capability of adaptive deep learning models in predicting dose information in volumetric modulation radiotherapy plans using the high-quality CBCT images and contour information of organs-at-risk (OARs).

MATERIALS/METHODS

The relationship between dose-volume histograms (DVHs) in radiotherapy plans and the geometric information of organs-at-risk (OAR) and planning target volume (PTV) has been well established. To evaluate the performance of the current state-of-the-art convolutional neural network (CNN) models including VIT3D and Unet3D, and intuitive machine learning methods (i.e., SVM and MLP), we implemented those models for dose prediction and conducted a comprehensive analysis with treatment plans created from images acquired from patients who consented to participate an IRB-approved imaging study designed to evaluate the imaging performance of the system. In total, 20 plans created by certified medical dosimetrists were employed in this study, with 15 used for training the machine-learning models and the remaining 5 used for performance testing. Two evaluation metrics were used: 1) root mean square error (RMSE) of the predicted dose and true dose and 2) time spent on dose prediction.

RESULTS

The results of the analysis showed that the ViT-3D (Transformer) model had the lowest RMSE of 3.682 ±0.010, followed by the Unet-3D (CNN) model with an RMSE of. 3.973 ±0.021 The MLP model had an RMSE of 8.007 ±0.019 while the SVM model had the highest RMSE of 9.156 ±0.032. For a fair comparison, we use 4-fold cross validation (each has 15 training plans and 5 testing plans), and report the mean value with standard deviation. All models are optimized with Adam optimizer of a learning rate 0.01, and the training process is stopped after 100 epochs. These findings indicate that the ViT-3D (Transformer) model performed the best in terms of predicting the dose information in volumetric modulation radiotherapy plans based on the CBCT images and contour information of OARs. For tested plan which contains 81 CT images (512 × 512 resolution), the inference time to predict dose information with a general CPU machine (6-Core Intel Core i7) is about 1.5 minutes. With GPU resources, such as NVIDIA A100, the inference process can be finished within seconds.

CONCLUSION

The study demonstrated that current state-of-the-art machine-learning models can achieve promising accuracy in dose prediction using high-quality CBCT images. A well-trained machine-learning model could offer clinicians a quick and reliable prediction of the true dose to patients in the case of significant anatomical changes or provide patient-specific optimization objectives if replanning is warranted.

Accuracy of Electron Density and Planning Dosimetry in a Novel High-Quality CBCT Imaging System

PURPOSE/OBJECTIVE(S)

A high-quality Cone-Beam Computed Tomography (CBCT) imaging system has been FDA approved for imaging guidance and dose calculation in radiotherapy. This study aims to evaluate the accuracy of the relative electron density in CBCT images acquired in this CBCT imaging system in a phantom study and its dosimetric impact on treatment planning in a patient study.

MATERIALS/METHODS

Astoichiometric CT calibration was performed with a CIRS phantom (SunNuclear, Model 062M) to generate the HU-electron density curve for two tube voltages, 125kVp and 140 kVp, respectively. The phantom has a longitudinal length of 26.5 cm and is equipped with interchangeable inserts of various compositions, supplied by the vendor. Measurements were taken with solid water plates added to both ends of the phantom to allow adequate scattering and repeated for various clinical protocols with different combinations of tube voltages and exposures. The accuracy of the relative electron density of the CBCT imaging system was verified by comparing the calculated electron density from the Hounsfield Units (HU) measurements obtained from a Gammex phantom to the relative electron densities provided in vendor's specifications. To benchmark the relative electron density of the CBCT imaging system against a standard helical CT simulator, ten clinical plans that were created on CT simulation images were copied and recalculated on the CBCT images acquired immediately after the CT simulation, the latter of which was a standard procedure in current radiotherapy care for all patients who had given their consent to participate in the IRB-approved imaging study. The dose grids used in these calculations were 2.5mm x 2.5mm x 3mm. The Gamma passing rate was calculated using a standard 3mm/3% criterion with a 10% threshold.

RESULTS

Ourresults showed the difference between the averaged CBCT calibration curves acquired at tube voltages of 125 kVP and 140 kVp was less than 2%. The mean discrepancy of the relative electron densities from vendor's specification was 0.0045 with a range between -0.02 and 0.04. Relative electron densities in all inserts were within 2% from the vendor's specifications except the cortical bone insert. Gamma passing rate was between 96.02% and 98.49% with mean value of 97.4% and a standard deviation of 0.95%. We consider this reflects the fact that the CT simulation and CBCT imaging were performed in separated rooms, which resulted in slight anatomical deformation that could negatively impact the Gamma passing rate.

CONCLUSION

The CBCT imaging system provides sufficient accuracy of electron density for dose calculation, and the dose distribution calculated on the CBCT images is clinically equivalent to those calculated on helical CT images. The enhanced imaging quality of CBCT could further extend the role of imaging guidance to planning for adaptive radiotherapy, potentially reducing the need for re-simulation and interruptions in the radiotherapy course.

An In Silico study of a One-Day One-Machine Workflow for Definitive Radiotherapy Cases on a Novel Simulation and Treatment Platform

PURPOSE/OBJECTIVE(S)

The workflow in Radiotherapy (RT) has largely unchanged for the past three decades, despite increasing evidence suggesting that delayed access to RT, including the wait time between consultation, simulation, and treatment appointments, can negatively impact clinical outcomes. In this pilot study, we present preliminary results of an in silico study that demonstrate the feasibility of a novel RT platform, which integrates simulation into the treatment process and enables patients to receive immediate RT after their initial RT consultation.

MATERIALS/METHODS

A prospective clinical study has been approved to assess the capabilities of a novel RT platform with a high quality CBCT system for imaging guidance as well as planning. This new platform enables a novel clinical workflow that allows clinicians to review contours and plans created on diagnostic CT images prior to the initial RT consultation and allow them to approve new plans adapted on the actual simulation dataset acquired on the first treatment fraction. Four patients receiving standard of care RT (three abdomen and one thorax) consented for this study and underwent additional experimental CBCT simulation on the new platform in addition to their standard CT simulation. The CBCT simulation was taken in two setups: with a specific mold on a flat couch and without a mold on a curved couch. To demonstrate the equivalence of the new workflow to the current standard of care, the plan created on the most recent diagnostic CT images was compared to the plans adapted on the experimental simulation images and the standard CT simulation images, using a knowledge-based model. Contours were propagated from approved datasets to the new datasets through deformable image registration.

RESULTS

All experimental simulations were completed between 14 and 21 minutes with the assistance of two therapists. The contouring, editing, and replanning process took less than one hour in all cases, in line with our experience and peer-reviewed literature. Despite notable anatomical changes observed, the dose-volume histograms (DVH) were consistent, as shown in Table 1.

CONCLUSION

The novel workflow presented herein was feasible and demonstrates that the integration of simulation with image-guided RT on one single platform may unlock the potential of accelerating the RT workflow and reducing the wait time for treatment from weeks to hours.

Proton Online Adaptation Using Novel Cone-Beam Computed Tomography System

PURPOSE/OBJECTIVE(S)

Cone beam computed tomography (CBCT) has been used in clinic frequently to provide quick, online, and handy three-dimensional images. However, due to its significant artifacts and inaccurate Hounsfield values (HU), CBCT based online proton adaptation is infeasible. Recently, a novel in-room imaging solution was developed to allow larger images, better contrast and faster CBCT imaging acquisition. Our work demonstrated for the first time the feasibility of using this novel CBCT images for direct intensity modulated proton planning.

MATERIALS/METHODS

Three patients and three CIRS phantoms were scanned using novel imaging technique (CBCTp) for this work. CT curves were acquired by scanning a CIRS electron density phantom. Stopping power ratio was computed using the stoichiometric method. Proton plans were made on treatment simulation CT and further evaluated on CBCTp to compare the differences.

RESULTS

The table below shows three patients and three phantoms plan comparisons. Multiple sites and dose levels were studied. The planning target volume (PTV) coverage (D95%) and mean dose difference between simulation CT and CBCTp are 0.8% and 0.3%, correspondingly. Dosimetrically, phantom and patient plans are almost identical between two imaging techniques. Lung patient plan show the largest variation due to patient tumor change and the quality of breathing.

CONCLUSION

The novel and high quality of CBCT is feasible for direct proton planning with accurate CT calibration. It provides a reliable alternative solution for proton online adaptive therapy.

Is COPD mortality in South China causally linked to the long-term PM1 exposure? Evidence from a large community-based cohort

BACKGROUND

Long-term ambient particulate matter (PM) exposure has been found associated with chronic obstructive pulmonary disease (COPD) mortality in an increasing body of research. However, limited evidence was available on the potential causal links between PM1 and COPD mortality, especially in highly exposed areas.

OBJECTIVES

To examine the COPD mortality risk following long-term ambient PM1 exposure in south China.

METHODS

The cohort included 580,757 participants recruited during 2009-2015. Satellite-based annual concentrations of PM1 were estimated at a spatial resolution of 1 km × 1 km and assigned to each participant based on their residential addresses. We analyzed the potential causal links between time-varying PM1 exposure and COPD mortality using marginal structural cox models within causal frameworks. Stratified analyses were also performed to identify the potential susceptible groups.

RESULTS

The annual average PM1 concentration continuously decreased over time. After adjusting for confounders, each 1 μg/m3 increase in PM1 concentration corresponded to an 8.1 % (95% confidence interval: 6.4-9.9 %) increment in the risk of COPD mortality. The impact of PM1 was more pronounced among the elderly and those with low exercise frequency, with a 1.9-6.9 % higher risk than their counterparts. We further observed a 0.1-9.7 % greater risk among those who lived in lower greenness settings. Additionally, we observed higher effect estimates in participants with long-term low PM1 exposure compared to the general population.

CONCLUSIONS

COPD mortality risk significantly increased following long term ambient PM1 exposure, particularly among groups with certain demographics or long-term low exposure.

Impact and Cost-Effectiveness of Biomedical Interventions on Adult Hepatitis B Elimination in China: A Mathematical Modelling Study

BACKGROUND

China has one of the highest hepatitis B virus (HBV) disease burdens worldwide and tracking progress toward the 2030 HBV elimination targets is essential. This study aimed to assess the impact of biomedical interventions (i.e., adult vaccination, screening and treatment) on the adult HBV epidemic, estimate the time for HBV elimination, and evaluate the cost-effectiveness of the interventions in China.

METHODS

A deterministic compartmental model was developed to project the HBV epidemic from 2022 to 2050 and estimate the time to meet elimination targets under four intervention scenarios. Cost-effectiveness was calculated using incremental cost per quality-adjusted life year (QALY) gained, i.e., average cost-effectiveness ratio (CER).

RESULTS

Under the status quo, there will be 42.09-45.42 million adults living with HBV in 2050 and 11.04-14.36 million HBV-related deaths cumulatively from 2022 to 2050. Universal vaccination would cumulatively avert 3.44-3.95 million new cases at a cost of US$1027-1261/QALY gained. The comprehensive strategy would cumulatively avert 4.67-5.24 million new chronic cases and 1.39-1.85 million deaths, expediting the realization of the elimination targets forward to 2049. This strategy was also cost-effective with an average CER of US$20,796-26,685/QALY and a saved healthcare cost of US$16.10-26.84 per person.

CONCLUSION

China is not on track to meet the elimination targets but comprehensive biomedical interventions can accelerate the realization of the targets. A comprehensive strategy is cost-effective and cost-saving, which should be promoted in primary care infrastructures. Universal adult vaccination may be appropriate in the near future considering practical feasibility.

[Association between different obesity measurement indexes and serum C-reactive protein in adult women]

Objective: To explore the association of different obesity measurement indexes on serum C-reactive protein (CRP) in Chinese adult women. Methods: The data were obtained from baseline and follow-up surveys of the urban Breast Cancer Screening Program in Shuangliu District, Chengdu. A total of 441 adult women were included in the study. A questionnaire survey, physical examination, and laboratory testing were conducted on the subjects. Multivariate logistic regression model, two-level mixed effects logistic regression model, and restricted cubic spline method were used to investigate the linear and nonlinear correlation between different obesity measurement indexes and serum CRP in adult women. Results: For every 1 unit increase in BMI, waist circumference (WC), and adiposity, the risk of elevated serum CRP or exacerbation of chronic low-grade inflammation in adult women increased by 16.5%, 5.0%, and 11.1% (P<0.05), respectively. Both BMI and adiposity were nonlinear correlated with serum CRP. Using BMI=24.0 kg/m2 as the reference point, serum CRP level increased with the increase of BMI when BMI >24.0 kg/m2. Using adiposity=30% as the reference point, serum CRP level increased with the increase of adiposity when adiposity >30%. Conclusions: Overall, obesity reflected by BMI had the strongest association with serum CRP in adult women, followed by body fat content reflected by adiposity, and central obesity reflected by WC had the weakest association with CRP. Adult women with BMI >24.0 kg/m2 or adiposity >30% are at high risk for obesity-related inflammatory manifestations.

[Identification and 3D architecture analysis of the LIPC gene mutation in a pedigree with familial hypercholesterolemia-like phenotype]

Objective: To identify and analyze 3D architecture of the mutational sites of susceptible genes in a pedigree with familial hypercholesterolemia-like phenotype (FHLP). Methods: This is a case series study. A pedigree with suspected familial hypercholesterolemia was surveyed. The proband admitted in Beijing Anzhen Hospital in April 2019. Whole-exome sequencing was performed to determine the mutational sites of susceptible genes in the proband. Polymerase chain reaction (PCR) sequencing was used to verify the pathogenic variant on proband's relatives. The structural and functional changes of the proteins were analyzed and predicted by Discovery Studio 4.0 and PyMol 2.0. Results: The patients in the pedigree showed abnormal lipid profiles, especially elevated levels of total cholesterol(TC). The genetic screening detected the c.1330C>T SNP in the exon 8 of lipase C (LIPC) gene, this mutation leads to an amino acid substitution from arginine to cysteine at position 444 (Arg444Cys), in the proband and proband's father and brother. In this family, members with this mutation exhibited elevated TC, whereas lipid profile was normal from the proband's mother without this mutation. This finding indicated that LIPC: c.1330C>T mutation might be the mutational sites of susceptible genes. The analysis showed that Arg444Cys predominantly affected the ligand-binding property of the protein, but had a limited impact on catalytic function. Conclusion: LIPC: c.1330C>T is a new mutational site of susceptible genes in this FHLP pedigree.

Prevalence and trends of polypharmacy in U.S. adults, 1999-2018

BACKGROUND

Polypharmacy is one of the most important health issues for its potential impacts on disease burden and healthcare costs. The aim of this study was to update a comprehensive picture of prevalence and trends in polypharmacy over 20 years in U.S. adults.

METHODS

Participants included 55,081 adults aged ≥ 20 from the National Health and Nutrition Examination Survey, January 1, 1999, through December 31, 2018. The simultaneously use of ≥ 5 drugs in one individual was defined as polypharmacy. National prevalence and trends in polypharmacy were evaluated among U.S. adults within different demo-socioeconomic status and pre-existing diseases.

RESULTS

From 1999-2000 to 2017-2018, the overall percentages of adults with polypharmacy remained on the rise, increasing from 8.2% (7.2-9.2%) to 17.1% (15.7-18.5%) (average annual percentage change [AAPC] = 2.9%, P = .001). The polypharmacy prevalence was considerably higher in the elderly (from 23.5% to 44.1%), in adults with heart disease (from 40.6% to 61.7%), and in adults with diabetes (from 36.3% to 57.7%). Also, we observed a greater increase rate of polypharmacy in men (AAPC = 4.1%, P < .001), in the Mexican American (AAPC = 6.3%, P < .001), and in the non-Hispanic Black (AAPC = 4.4%, P < .001).

CONCLUSIONS

From 1999-2000 to 2017-2018, the prevalence of polypharmacy is continually increasing in U.S. adults. The polypharmacy was especially higher in the older, in patients with heart disease, or diabetes. The high prevalence urges the healthcare providers and health policymakers to manage polypharmacy among specific population groups.

Interactions between long-term ambient particle exposures and lifestyle on the prevalence of hypertension and diabetes: insight from a large community-based survey

INTRODUCTION

Evidence on the interaction of lifestyle and long-term ambient particle (PM) exposure on the prevalence of hypertension, diabetes, particularly their combined condition is limited. We investigate the associations between PM and these outcomes and whether the associations were modified by various lifestyles.

METHODS

This was a large population-based survey during 2019-2021 in Southern China. The concentrations of PM were interpolated and assigned to participants by the residential address. Hypertension and diabetes status were from questionnaires and confirmed with the community health centres. Logistic regression was applied to examine the associations, followed by a comprehensive set of stratified analyses by the lifestyles including diet, smoking, drinking, sleeping and exercise.

RESULTS

A total of 82 345 residents were included in the final analyses. For each 1 μg/m3 increase in PM2.5, the adjusted OR for the prevalence of hypertension, diabetes and their combined condition were 1.05 (95% CI 1.05 to 1.06), 1.07 (95% CI 1.06 to 1.08) and 1.05 (95% CI 1.04 to 1.06), respectively. We observed that the association between PM2.5 and the combined condition was greatest in the group with 4-8 unhealthy lifestyles (OR=1.09, 95% CI 1.06 to 1.13) followed by the group with 2-3 and those with 0-1 unhealthy lifestyle (P interaction=0.026). Similar results and trends were observed in PM10 and/or in those with hypertension or diabetes. Individuals who consumed alcohol, had inadequate sleep duration or had poor quality sleep were more vulnerable.

CONCLUSION

Long-term PM exposure was associated with increased prevalence of hypertension, diabetes and their combined condition, and those with unhealthy lifestyles suffered greater risks of these conditions.

Potential causal links between long-term ambient particulate matter exposure and cerebrovascular mortality: Insights from a large cohort in southern China

Cohort studies conducted in North America and Europe have linked cerebrovascular mortality to long-term exposure to particulate matter (PM). However, limited evidence from large cohorts in high-exposure areas and the traditional approach of association assessment may cause residual confounding issues. In this study, we aimed to investigate the causal links between cerebrovascular mortality and long-term exposure to PM_2.5, PM₁₀, and PM_2.5-10 in an ongoing cohort study with 580,757 participants in southern China. Using satellite-based estimates of PM concentration at a 1-km² spatial resolution, we assigned exposure levels to each participant and used the marginal structural Cox model to assess the association between PM exposure and cerebrovascular mortality while accounting for time-varying covariates. We also explored the potential modification effects of sociodemographic and behavioral factors on the PM-health associations. Adjusted hazard ratios (HR) for overall cerebrovascular mortality were 1.041 (95% confidence interval (CI): 1.034-1.049) and 1.032 (95% CI: 1.026-1.038) for each 1 μg/m³ increase in PM_2.5, and PM₁₀, respectively. Similar trends were observed in the mortality risk from stroke and ischemic stroke, with HRs ranging from 1.040 to 1.069 and 1.025 to 1.052, respectively, across 2 p.m. exposures. The impact of PM exposure was generally more apparent among women, participants with primary school diplomas and below, and the subgroup under low-exposure. Multiple sensitivity analyses confirmed the robustness of the results. In conclusion, this sizable prospective cohort study hypothesizes causal links between long-term PM exposure and cerebrovascular mortality, particularly among vulnerable participants, supporting the rationale for reducing PM concentration in China to reduce cerebrovascular mortality.

[Comparison of diagnostic performance of Clear Cell Likelihood Score v1.0 and v2.0 for clear renal cell carcinoma]

OBJECTIVE

To compare the performance of Clear Cell Likelihood Score (ccLS) v1.0 and v2.0 in diagnosing clear cell renal cell carcinoma (ccRCC) from small renal masses (SRM).

METHODS

We retrospectively analyzed the clinical data and MR images of patients with pathologically confirmed solid SRM from the First Medical Center of the Chinese PLA General Hospital between January 1, 2018, and December 31, 2021, and from Beijing Friendship Hospital of Capital Medical University and Peking University First Hospital between January 1, 2019 and May 17, 2021. Six abdominal radiologists were trained for use of the ccLS algorithm and scored independently using ccLS v1.0 and ccLS v2.0. Random- effects logistic regression modeling was used to generate plot receiver operating characteristic curves (ROC) to evaluate the diagnostic performance of ccLS v1.0 and ccLS v2.0 for ccRCC, and the area under curve (AUC) of these two scoring systems were compared using the DeLong's test. Weighted Kappa test was used to evaluate the interobserver agreement of the ccLS score, and differences in the weighted Kappa coefficients was compared using the Gwet consistency coefficient.

RESULTS

In total, 691 patients (491 males, 200 females; mean age, 54 ± 12 years) with 700 renal masses were included in this study. The pooled accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of ccLS v1.0 for diagnosing ccRCC were 77.1%, 76.8%, 77.7%, 90.2%, and 55.7%, as compared with 80.9%, 79.3%, 85.1%, 93.4%, 60.6% with ccLS v2.0, respectively. The AUC of ccLS v2.0 was significantly higher than that of ccLS v1.0 for diagnosis of ccRCC (0.897 vs 0.859; P < 0.01). The interobserver agreement did not differ significantly between ccLS v1.0 and ccLS v2.0 (0.56 vs 0.60; P > 0.05).

CONCLUSION

ccLS v2.0 has better performance for diagnosing ccRCC than ccLS v1.0 and can be considered for use to assist radiologists with their routine diagnostic tasks.

Toward discovering a novel family of peptides targeting neuroinflammatory states of brain microglia and astrocytes

Microglia are immune-derived cells critical to the development and healthy function of the brain and spinal cord, yet are implicated in the active pathology of many neuropsychiatric disorders. A range of functional phenotypes associated with the healthy brain or disease states has been suggested from in vivo work and were modeled in vitro as surveying, reactive, and primed sub-types of primary rat microglia and mixed microglia/astrocytes. It was hypothesized that the biomolecular profile of these cells undergoes a phenotypical change as well, and these functional phenotypes were explored for potential novel peptide binders using a custom 7 amino acid-presenting M13 phage library (SX7) to identify unique peptides that bind differentially to these respective cell types. Surveying glia were untreated, reactive were induced with a lipopolysaccharide treatment, recovery was modeled with a potent anti-inflammatory treatment dexamethasone, and priming was determined by subsequently challenging the cells with interferon gamma. Microglial function was profiled by determining the secretion of cytokines and nitric oxide, and expression of inducible nitric oxide synthase. After incubation with the SX7 phage library, populations of SX7-positive microglia and/or astrocytes were collected using fluorescence-activated cell sorting, SX7 phage was amplified in Escherichia coli culture, and phage DNA was sequenced via next-generation sequencing. Binding validation was done with synthesized peptides via in-cell westerns. Fifty-eight unique peptides were discovered, and their potential functions were assessed using a basic local alignment search tool. Peptides potentially originated from proteins ranging in function from a variety of supportive glial roles, including synapse support and pruning, to inflammatory incitement including cytokine and interleukin activation, and potential regulation in neurodegenerative and neuropsychiatric disorders.

The causal links between long-term exposure to major PM2.5 components and the burden of tuberculosis in China

BACKGROUND

We aimed to estimate the causal impacts of long-term exposure to major PM_2.5 components - including black carbon, organic matter, sulfate, nitrate, and ammonium - on the incidence and mortality of tuberculosis in China.

METHODS

We collected annual and provincial-level tuberculosis incidence and mortality, concentrations of PM_2.5 components, and socioeconomic indicators from between 2004 and 2018 in mainland China. We used the difference-in-differences (DID) causal inference approach with a generalized weighted quantile sum (gWQS) regression model to estimate the long-term effects and relative contributions of PM_2.5 components' exposure on tuberculosis incidence and mortality.

RESULTS

We found that long-term multi-components exposure was significantly associated with tuberculosis incidence (WQS index IR%:8.34 %, 95 % CI:4.54 %-12.27 %) and mortality (WQS index IR%:19.49 %, 95 % CI: 9.72 %-30.13 %). Primary pollutants, black carbon and organic matter, contributed most of the overall mixture effect (over 85 %). Nitrate showed a critical role in tuberculosis burden in not-aging provinces and in regions at the Q3 stratum (i.e., the 3rd quartile) of GDP per capita and urbanization rate. Meanwhile the contribution of sulfate to tuberculosis burden in regions at the Q1 stratum of GDP per capita and urbanization rate was the largest among the effect of secondary pollutants (i.e., sulfate, nitrate, and ammonium).

CONCLUSION

The mitigation of black carbon and organic matter pollution may significantly reduce the tuberculosis burden in China. Controlling nitrate emissions and increasing clean energy (i.e., energy sources with limited pollution emissions, such as natural gas and clean coal) may also be effective in certain regions.

Intimate Partner Violence and Willingness to Use Pre-Exposure Prophylaxis Among Men Who Have Sex With Men in Chengdu, China

Intimate partner violence (IPV) is common in men who have sex with men (MSM). MSM also face increased risk of human immunodeficiency virus infection. However, it is not known whether IPV experience of MSM in China would affect their attitudes toward pre-exposure prophylaxis (PrEP) use. A cross-sectional study was conducted to explore the associations between different types of IPV and willingness to use PrEP in a sample of 608 MSM from November 2018 to May 2019 in Chengdu, China. Univariate and multivariate logistic regression analyses were used to explore the associations between different types of IPV and willingness to use PrEP. The average age of the participants was 31.8 ± 12.3 years, 48.9% of them were aware of PrEP before this study, and only 7.2% were aware of long-acting injectable PrEP (LAI-PrEP). The overall willingness to use any type of PrEP in the next 6 months was 82.2%. Approximately one third of the participants (n = 198) had experienced at least one type of IPV. We found that experience of sexual perpetration was negatively associated with the willingness to use on-demand PrEP (adjusted odds ratio [ORa] = 0.33, 95% CI = 0.16-0.67) and the overall willingness to use any type of PrEP (ORa = 0.31, 95% CI = 0.15-0.64). The willingness to use LAI-PrEP also had negative associations with any type of monitoring IPV (ORa = 0.58, 95% CI = 0.38-0.91), controlling victimization (ORa = 0.41, 95% CI = 0.21-0.82), and emotional victimization (ORa = 0.58, 95% CI = 0.35-0.97). The findings of this study demonstrate that IPV experiences are negatively associated with willingness to use PrEP among MSM, suggesting that PrEP promotion programs should consider IPV screening and develop explicit intervention strategies for both perpetrators and victims.

Potential causal links between long-term ambient particulate matter exposure and cardiovascular mortality: New evidence from a large community-based cohort in South China

BACKGROUND

Cardiovascular disease (CVD) mortality is associated with long-term particulate matter (PM) exposure. However, evidence from large, highly-exposed population cohort and observational-data-based causal inference approaches remains limited.

AIMS

We examined the potential causal links between PM exposure and the CVD mortality in South China.

METHODS

580,757 participants were recruited during 2009-2015 and followed up through 2020. Satellite-based annual concentrations of PM_2.5, PM₁₀, and PM_coarse (i.e., PM₁₀ - PM_2.5) at 1 km² spatial resolution were estimated and assigned to each participant. Marginal structural Cox models with time-varying covariates, adjusted using inverse probability weighting, were developed to evaluate the association between prolonged PM exposure and CVD mortality.

RESULTS

For overall CVD mortality, the hazard ratios and 95% confidence interval for each 1 μg/m³ increase in the annual average concentration of PM_2.5, PM₁₀, and PM_coarse were 1.033 (1.028-1.037), 1.028 (1.024-1.032), and 1.022 (1.012-1.033), respectively. All three PMs were linked to a higher mortality risk for myocardial infarction and ischemic heart disease (IHD). The mortality risk of chronic IHD and hypertension was linked to PM_2.5 and PM₁₀. Significant association between PM_coarse and other heart disease mortality was also observed. The older, women, less-educated participants, or inactive participants exhibited particularly higher susceptibility. Participants who were generally exposed to PM₁₀ concentrations below 70 μg/m³ were more vulnerable to PM_2.5-, PM₁₀- and PM_coarse-CVD mortality risks.

CONCLUSION

This large cohort study provides evidence for the potential causal links between increased CVD mortality and ambient PM exposure, as well as socio-demographics linked to the highest vulnerability.

Long-term exposure to particulate matter and COPD mortality: Insights from causal inference methods based on a large population cohort in southern China

BACKGROUND

Evidence of the association between long-term exposure to particulate matter (PM) and chronic obstructive pulmonary disease (COPD) mortality from large population-based cohort study is limited and often suffers from residual confounding issues with traditional statistical methods. We hereby assessed the casual relationship between long-term PM (PM_2.5, PM₁₀ and PM_10-2.5) exposure and COPD mortality in a large cohort of Chinese adults using state-of-the-art causal inference approaches.

METHODS

A total of 580,757 participants in southern China were enrolled in a prospective cohort study from 2009 to 2015 and followed up until December 2020. Exposures to PM at each residential address were obtained from the Long-term Gap-free High-resolution Air Pollutant Concentration dataset. Marginal structural Cox models were used to investigate the association between COPD mortality and annual average exposure levels of PM exposure.

RESULTS

During an average follow-up of 8.0 years, 2250 COPD-related deaths occurred. Under a set of causal inference assumptions, the hazard ratio (HR) for COPD mortality was estimated to be 1.046 (95 % confidence interval: 1.034-1057), 1.037 (1.028-1.047), and 1.032 (1.006-1.058) for each 1-μg/m³ increase in annual average concentrations of PM_2.5, PM₁₀, and PM_10-2.5 respectively. Additionally, the detrimental effects appeared to be more pronounced among the elderly (age ≥ 65) and inactive participants. The effect estimates of PM_2.5, PM₁₀, and PM_10-2.5 tend to be greater among participants who were generally exposed to PM₁₀ concentrations below 70 μg/m³ than that among the general population.

CONCLUSION

Our results support causal links between long-term PM exposure and COPD mortality, highlighting the urgency for more effective strategies to reduce PM exposure, with particular attention on protecting potentially vulnerable groups.

Projections of Lung Cancer Incidence by 2035 in 40 Countries Worldwide: Population-Based Study

BACKGROUND

The global burden of lung cancer (LC) is increasing. Quantitative projections of the future LC burden in different world regions could help optimize the allocation of resources and provide a benchmark for evaluating LC prevention and control interventions.

OBJECTIVE

We aimed to predict the future incidence of LC in 40 countries by 2035, with an emphasis on country- and sex-specific disparities.

METHODS

Data on LC incidence from 1978 to 2012 were extracted from 126 cancer registries of 40 countries in Cancer Incidence in Five Continents Volumes V-XI and used for the projection. Age-standardized incidence rates (ASRs) per 100,000 person-years and the number of incident cases were predicted through 2035, using the NORDPRED age-period-cohort model.

RESULTS

Global ASRs of the 40 studied countries were predicted to decrease by 23% (8.2/35.8) among males, from 35.8 per 100,000 person-years in 2010 to 27.6 in 2035, and increase by 2% (0.3/16.8) among females, from 16.8 in 2010 to 17.1 in 2035. The ASRs of LC among females are projected to continue increasing dramatically in most countries by 2035, with peaks after the 2020s in most European, Eastern Asian, and Oceanian countries, whereas the ASRs among males will continue to decline in almost all countries. The ASRs among females are predicted to almost reach those among males in Ireland, Norway, the United Kingdom, the Netherlands, Canada, the United States, and New Zealand in 2025 and in Slovenia in 2035 and even surpass those among males in Denmark in 2020 and in Brazil and Colombia in 2025. In 2035, the highest ASRs are projected to occur among males in Belarus (49.3) and among females in Denmark (36.8). The number of new cases in 40 countries is predicted to increase by 65.32% (858,000/1,314,000), from 1.31 million in 2010 to 2.17 million in 2035. China will have the largest number of new cases.

CONCLUSIONS

LC incidence is expected to continue to increase through 2035 in most countries, making LC a major public health challenge worldwide. The ongoing transition in the epidemiology of LC highlights the need for resource redistribution and improved LC control measures to reduce future LC burden worldwide.

A psychometric evaluation of Chinese chronic hepatitis B virus infection-related stigma scale using classical test theory and item response theory

Purpose

To validate the hepatitis B virus infection-related stigma scale (HBVISS) using Classical Test Theory and Item Response Theory in a sample of Chinese chronic HBV carriers.

Methods

Feasibility, internal consistency reliability, split-half reliability and construct validity were evaluated using a cross-sectional validation study (n = 1,058) in Classical Test Theory. Content validity was assessed by COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) criteria. The Item Response Theory (IRT) model parameters were estimated using Samejima's graded response model, after which item response category characteristic curves were drawn. Item information, test information, and IRT-based marginal reliability were calculated. Measurement invariance was assessed using differential item functioning (DIF). SPSS and R software were used for the analysis.

Results

The response rate reached 96.4% and the scale was completed in an average time of 5 min. Content validity of HBVISS was sufficient (+) and the quality of the evidence was high according to COSMIN criteria. Confirmatory factor analysis showed acceptable goodness-of-fit (χ ²/df = 5.40, standardized root mean square residual = 0.057, root mean square error of approximation = 0.064, goodness-of-fit index = 0.902, comparative fit index = 0.925, incremental fit index = 0.926, and Tucker-Lewis index = 0.912). Cronbach's α fell in the range of 0.79-0.89 for each dimension and 0.93 for the total scale. Split-half reliability was 0.96. IRT discrimination parameters were estimated to range between 0.959 and 2.333, and the threshold parameters were in the range-3.767 to 3.894. The average score for test information was 12.75 (information >10) when the theta level reached between-4 and + 4. The IRT-based marginal reliability was 0.95 for the total scale and fell in the range of 0.83-0.91 for each dimension. No measurement invariance was detected (d-R ² < 0.02).

Conclusion

HBVISS exhibited good feasibility, reliability, validity, and item quality, making it suitable for assessing chronic Hepatitis B virus infection-related stigma.

Early detection of SARS-CoV-2 variants through dynamic co-mutation network surveillance

Background

Precise public health and clinical interventions for the COVID-19 pandemic has spurred a global rush on SARS-CoV-2 variant tracking, but current approaches to variant tracking are challenged by the flood of viral genome sequences leading to a loss of timeliness, accuracy, and reliability. Here, we devised a new co-mutation network framework, aiming to tackle these difficulties in variant surveillance.

Methods

To avoid simultaneous input and modeling of the whole large-scale data, we dynamically investigate the nucleotide covarying pattern of weekly sequences. The community detection algorithm is applied to a co-occurring genomic alteration network constructed from mutation corpora of weekly collected data. Co-mutation communities are identified, extracted, and characterized as variant markers. They contribute to the creation and weekly updates of a community-based variant dictionary tree representing SARS-CoV-2 evolution, where highly similar ones between weeks have been merged to represent the same variants. Emerging communities imply the presence of novel viral variants or new branches of existing variants. This process was benchmarked with worldwide GISAID data and validated using national level data from six COVID-19 hotspot countries.

Results

A total of 235 co-mutation communities were identified after a 120 weeks' investigation of worldwide sequence data, from March 2020 to mid-June 2022. The dictionary tree progressively developed from these communities perfectly recorded the time course of SARS-CoV-2 branching, coinciding with GISAID clades. The time-varying prevalence of these communities in the viral population showed a good match with the emergence and circulation of the variants they represented. All these benchmark results not only exhibited the methodology features but also demonstrated high efficiency in detection of the pandemic variants. When it was applied to regional variant surveillance, our method displayed significantly earlier identification of feature communities of major WHO-named SARS-CoV-2 variants in contrast with Pangolin's monitoring.

Conclusion

An efficient genomic surveillance framework built from weekly co-mutation networks and a dynamic community-based variant dictionary tree enables early detection and continuous investigation of SARS-CoV-2 variants overcoming genomic data flood, aiding in the response to the COVID-19 pandemic.

[Preliminary study on the effect of fecal microbiota transplantation on neurobehavior and gut microbiota of offspring rats exposed to arsenic]

Objective: To explore the effects of fecal microbiota transplantation (FMT) on neurobehavior and gut microbiota of arsenic-exposed offspring rats. Methods: In April 2021, Thirty-six SPF SD rats aged 8 weeks were seleted, rats were ranked by weight and divided into four groups according to randomized block design, namely control group, arsenic exposure group (As group) , arsenic+normal saline group (As+NaCl group) and As+FMT group, 6 females and 3 males in each group. Fecal microbiota fluid were provided by feces of rats in control group. Rats drank tap water containing 75 mg/L sodium arsenite for one week and then were caged together. The arsenic exposure was terminated until the pups were born. Female rats with vaginal plug were treated with fecal microbiota fluid via gavage during neurodevelopmental teratogenic window period. The volume of gavage was 1 ml/100 g with once every two days, for a total of three times. Weight alterations of offspring rats were recorded every week after weaning, and when offspring rats grew up for 6 weeks, Morris test and open field experiment was used to observe learning and memory abilities, as well as neurobehavioral performance of autonomous exploration and tension, respectively. 16S rDNA sequencing technology was used to detect microbiota diversities in fecal samples of rats in As group and As+FMT group. Results: Compared with the control group, the ratio of swimming distance and staying time in the target quadrant and the times of crossing the platform of rats in As group decreased significantly, and the motor distance, times entering central zone and the number of grid crossing of rats decreased significantly (P<0.05) . Compared with As group, the ratio of swimming distance in target quadrant, the motor distance in central zone and times entering central zone of rats in As+FMT group were evidently increased (P<0.05) . The analysis of fecal microbiota diversities showed that, at the phyla level, the relative abundance of Bacteroidetes in feces of rats in As+FMT group was higher than that in As group (68.34% vs 60.55%) , while the relative abundance of Firmicutes was lower than that in As group (28.02% vs 33.48%) . At the genus level, the relative abundance of Prevotella in As+FMT group was significantly higher than that in As group, becoming the dominant genus (42.08% vs 21.78%) . Additionally, compared with As group, a total of 22 genus were increased with 21 decreased genus in As+FMT group (P<0.05) . LEfSe analysis showed that dominant genuses in As+FMT group were Prevotella and UCG_005, and their relative abundance was significantly higher than that of As group (P<0.05) . Conclusion: FMT may alleviate the impaired learning and memory ability and anxiety like behavior of the offspring rats exposed to arsenic, and improve the disrupted gut microbiota.

The association between wind speed and the risk of injuries among preschool children: New insight from a sentinel-surveillance-based study

BACKGROUND

Injuries among preschool children are an important public health concern worldwide. Significant gaps remain in understanding the potential impact of wind speed on injuries among preschoolers. We aimed to clarify the association and its variation across subgroups to capture the vulnerability features.

METHODS

Using a case-crossover design and conditional logistic regression model, we compared the exposure to wind speed right before the injury events (case period) with that of control periods to determine the excess rate (ER) of injury on each of 0-3 lag days in Guangzhou, 2016-2020. Results were also stratified by sociodemographic characteristics of patients, basic characteristics of injury events, and clinical features of injuries to identify the most vulnerable subgroups of preschoolers.

RESULTS

Higher wind speed was significantly associated with an increased risk of injuries among preschoolers on lag 0, reaching an ER of 2.93 % (95 % confidence interval [CI] = 0.87, 5.03), but not on other lag days. The results of the stratified analyses showed that children under 3-year-old (3.41 %; 95 % CI = 0.36, 6.55), boys (3.66 %; 95 % CI = 1.04, 6.35), and non-locally registered children (3.65; 95 % CI = 0.02, 7.40) were more prone to wind-related injuries. Falls (2.67 %; 95 % CI = 0.11, 5.30) were the main cause of wind-related injuries, and taking transportation was the main activity when injuries occurred (13.16 %; 95 % CI = 4.45, 22.60). Additionally, injuries involving buildings/grounds/obstacles (4.69 %; 95 % CI = 1.66, 7.81) and the occurrence of sprain/strain (7.60 %; 95 % CI = 0.64, 15.04) showed a positive association with wind speed.

CONCLUSIONS

Higher wind speed was associated with a significantly elevated rate of injuries among preschoolers without delayed effects, where children under 3-year-old, boys, and non-locally registered subgroups were more susceptible to wind-related injuries. This study may provide new insights for refining the prevention measures against wind-related injuries among preschoolers.

Estimating causal links of long-term exposure to particulate matters with all-cause mortality in South China

BACKGROUND

The association between long-term particulate matter (PM) exposure and all-cause mortality has been well-documented. However, evidence is still limited from high-exposed cohorts, especially for PM₁ which is smaller while more toxic than other commonly investigated particles. We aimed to examine the potential casual links of long-term PMs exposure with all-cause mortality in high-exposed areas.

METHODS

A total of 580,757 participants in southern China were enrolled during 2009-2015 and followed up to 2020. The annual average concentration of PM₁, PM_2.5, and PM₁₀ at 1 km² spatial resolution was assessed for each residential address through validated spatiotemporal models. We used marginal structural Cox models to estimate the PM-mortality associations which were further stratified by sociodemographic, lifestyle factors and general exposure levels.

RESULTS

37,578 deaths were totally identified during averagely 8.0 years of follow-up. Increased exposure to all 3 PM size fractions were significantly associated with increased risk of all-cause mortality, with hazard ratios (HRs) of 1.042 (95 % confidence interval (CI): 1.037-1.046), 1.031 (95 % CI: 1.028-1.033), and 1.029 (95 % CI: 1.027-1.031) per 1 μg/m³ increase in PM₁, PM_2.5, and PM₁₀ concentrations, respectively. We observed greater effect estimates among the elderly (age ≥ 65 years), unmarried participants, and those with low education attainment. Additionally, the effect of PM₁, PM_2.5, and PM₁₀ tend to be higher in the low-exposure group than in the general population.

CONCLUSIONS

We provided comprehensive evidence for the potential causal links betweenlong-term PM exposureand all-cause mortality, and suggested stronger links for PM₁compared to large particles and among certain vulnerable subgroups.

The risk of injuries during work and its association with precipitation: New insight from a sentinel-based surveillance and a case-crossover design

Background

Injuries during work are often exogenous and can be easily influenced by environmental factors, especially weather conditions. Precipitation, a crucial weather factor, has been linked to unintentional injuries, yet evidence of its effect on work-related injuries is limited. Therefore, we aimed to clarify the impact of precipitation on injuries during work as well as its variation across numerous vulnerability features.

Methods

Records on the work-related injury during 2016-2020 were obtained from four sentinel hospitals in Guangzhou, China, and were matched with the daily weather data during the same period. We applied a time-stratified case-crossover design followed by a conditional logistic regression to evaluate the association between precipitation and work-related injuries. Covariates included wind speed, sunlight, temperature, SO ₂, NO ₂, and PM _2.5. Results were also stratified by multiple factors to identify the most vulnerable subgroups.

Results

Daily precipitation was a positive predictor of work-related injuries, with each 10 mm increase in precipitation being associated with an increase of 1.57% in the rate of injuries on the same day and 1.47-1.14% increase of injuries on subsequent 3 days. The results revealed that precipitation had a higher effect on work-related injuries in winter (4.92%; 95%CI: 1.77-8.17%). The elderly (2.07%; 95%CI: 0.64-3.51%), male (1.81%; 95%CI: 0.96-2.66%) workers or those with lower educational levels (2.58%; 95%CI: 1.59-3.54%) were more likely to suffer from injuries on rainy days. There was a higher risk for work-related injuries caused by falls (2.63%; 95%CI: 0.78-4.52%) or the use of glass products (1.75%; 95%CI: 0.49-3.02%) on rainy days.

Conclusions

Precipitation was a prominent risk factor for work-related injury, and its adverse effect might endure for 3 days. Certain sub-groups of workers were more vulnerable to injuries in the rain.

The impact of monthly air pollution exposure and its interaction with individual factors: Insight from a large cohort study of comprehensive hospitalizations in Guangzhou area

Background

Although the association between short-term air pollution exposure and certain hospitalizations has been well documented, evidence on the effect of longer-term (e. g., monthly) air pollution on a comprehensive set of outcomes is still limited.

Method

A total of 68,416 people in South China were enrolled and followed up during 2019-2020. Monthly air pollution level was estimated using a validated ordinary Kriging method and assigned to individuals. Time-dependent Cox models were developed to estimate the relationship between monthly PM₁₀ and O₃ exposures and the all-cause and cause-specific hospitalizations after adjusting for confounders. The interaction between air pollution and individual factors was also investigated.

Results

Overall, each 10 μg/m³ increase in PM₁₀ concentration was associated with a 3.1% (95%CI: 1.3%-4.9%) increment in the risk of all-cause hospitalization. The estimate was even greater following O₃ exposure (6.8%, 5.5%-8.2%). Furthermore, each 10 μg/m³ increase in PM₁₀ was associated with a 2.3%-9.1% elevation in all the cause-specific hospitalizations except for those related to respiratory and digestive diseases. The same increment in O₃ was relevant to a 4.7%-22.8% elevation in the risk except for respiratory diseases. Additionally, the older individuals tended to be more vulnerable to PM₁₀ exposure (P _interaction: 0.002), while the alcohol abused and those with an abnormal BMI were more vulnerable to the impact of O₃ (P _interaction: 0.052 and 0.011). However, the heavy smokers were less vulnerable to O₃ exposure (P _interaction: 0.032).

Conclusion

We provide comprehensive evidence on the hospitalization hazard of monthly PM₁₀ and O₃ exposure and their interaction with individual factors.

Art Engagement and Risk of Type 2 Diabetes: Evidence From the English Longitudinal Study of Ageing

Objectives: To examine the prospective association between art engagement and the risk of type 2 diabetes. Methods: Adults aged ≥50 from the English Longitudinal Study of Ageing were asked about the frequency of art engagement, including going to the cinema, the art gallery or museum, and the theatre, a concert, or the opera. Cox proportional hazards regression models were used to examine the risk of type 2 diabetes associated with art engagement. Results: During a median follow-up of 12.2 years, we identified 350 cases of type 2 diabetes from 4,064 participants through interviews. After multivariable adjustment, compared with people who never went to the cinema, those going to the cinema frequently had a significantly lower risk of developing type 2 diabetes (HR = 0.61, 95% CI: 0.44-0.86). After further adjustment for socioeconomic factors, the association was slightly attenuated but remained statistically significant (HR = 0.65, 95% CI: 0.46-0.92). Similar results were found for going to the theatre, a concert, or the opera. Conclusion: Frequent art engagement may be associated with a lower risk of type 2 diabetes, which was independent of individuals' socioeconomic factors.

Polypharmacy, chronic kidney disease, and mortality among older adults: A prospective study of National Health and nutrition examination survey, 1999-2018

Introduction

Polypharmacy might contribute to a range of adverse outcomes, which could get worse in the elderly with chronic kidney disease (CKD). Evidence on polypharmacy, CKD, and mortality is scarce. We aimed to investigate the prospective association between polypharmacy, CKD and all-cause and cause-specific mortality in adults aged ≥65 years.

Methods

A total of 13,513 adults from the National Health and Nutrition Examination Surveys were included, following up from 1999 to 2018 until December 31, 2019. The simultaneous use of ≥5 medications by one individual was defined as polypharmacy. Survey-weighted Cox proportional hazard models were used to estimate the hazard ratio (HRs) for mortality from all-cause, cardiovascular diseases (CVD), and cancer after adjusting for potential confounding factors.

Results

Among the elderly with CKD, we identified 3,825 total deaths (1,325 CVD and 714 cancer) during a median follow-up of 7.7 years. Participants with polypharmacy had a 27% (HR = 1.27 [1.15, 1.39]) and 39% (HR = 1.39 [1.19, 1.62]) higher risk of all-cause and CVD mortality, respectively, but not for cancer mortality. Compared with the elderly with no polypharmacy and no CKD, the corresponding HRs (95%CIs) for all-cause mortality were 1.04 (0.96, 1.14) for those with no polypharmacy but CKD, 1.24 (1.11, 1.39) for with polypharmacy but no CKD, and 1.34 (1.21, 1.49) for those with both polypharmacy and CKD. A similar pattern was detected for CVD mortality.

Discussion

Polypharmacy was associated with elevated risks of all-cause and CVD mortality among the elderly CKD patients. More evidence-based approaches should be promoted for the appropriate deprescribing in the older adults with CKD.

Dynapenic Abdominal Obesity and Risk of Heart Disease among Middle-Aged and Older Adults: A Prospective Cohort Study

OBJECTIVES

The vicious cycle of dynapenia and abdominal obesity may have synergistic detrimental impacts on health. We aim to investigate the prospective association between dynapenic abdominal obesity and the risk of heart disease among middle-aged and older adults.

DESIGN

A prospective cohort study.

SETTING

English Longitudinal Study of Ageing, 2002-2019.

PARTICIPANTS

A total of 4734 participants aged 50 years and older were included.

MEASUREMENTS

Individuals were divided into non-dynapenia/non-abdominal obesity (ND/NAO), non-dynapenia/abdominal obesity (ND/AO), dynapenia/non-abdominal obesity (D/NAO), and dynapenia/abdominal obesity (D/AO) according to grip strength and waist circumference at baseline. The Cox proportional hazards models were used to obtain the hazard ratios (HRs) of incident heart disease associated with dynapenia and abdominal obesity after adjusting for potential confounding factors.

RESULTS

During a median follow-up of 9.5 years, 1040 cases of heart disease were recorded. Compared with ND/NAO group, the multivariable HRs were 1.05 (0.92, 1.21) for ND/AO group, 1.31 (0.96, 1.81) for D/NAO group, and 1.39 (1.03, 1.88) for D/AO group. The significant association of D/AO with incident heart disease was detected in women but not in men [HR = 1.55 (1.07, 2.24) and 1.06 (0.60, 1.88), respectively]. Among middle-aged adults, significant associations of D/NAO and D/AO with incident heart disease were observed [HR = 2.46 (1.42, 4.29) and 1.74 (1.02, 2.97), respectively].

CONCLUSION

Both D/NAO and D/AO might increase the risk of developing heart disease, highlighting the importance of dynapenia and obesity early screening for heart disease prevention.

Implementation and evaluation of crowdsourcing in global health education

BACKGROUND

Current global health course is most set as elective course taught in traditional teacher-taught model with low credit and short term. Innovate teaching models are required. Crowdsourcing characterized by high flexibility and strong application-orientation holds its potential to enhance global health education. We applied crowdsourcing to global health teaching for undergraduates, aiming to develop and evaluate a new teaching model for global health education.

METHODS

Crowdsourcing was implemented into traditional course-based teaching via introducing five COVID-19 related global health debates. Undergraduate students majoring in preventative medicine and nursing grouped in teams of 5-8, were asked to resolve these debates in reference to main content of the course and with manner they thought most effective to deliver the messages. Students' experience and teaching effect, were evaluated by questionnaires and teachers' ratings, respectively. McNemar's test was used to compare the difference in students' experience before and after the course, and regression models were used to explore the influencing factors of the teaching effect.

RESULTS

A total of 172 undergraduates were included, of which 122 (71%) were females. Students' evaluation of the new teaching model improved after the course, but were polarized. Students' self-reported teaching effect averaged 67.53 ± 16.8 and the teachers' rating score averaged 90.84 ± 4.9. Students majoring in preventive medicine, participated in student union, spent more time on revision, and had positive feedback on the new teaching model tended to perform better.

CONCLUSION

We innovatively implemented crowdsourcing into global health teaching, and found this new teaching model was positively received by undergraduate students with improved teaching effects. More studies are needed to optimize the implementation of crowdsourcing alike new methods into global health education, to enrich global health teaching models.