Association between plasma metal exposure and health span in very elderly adults: a prospective cohort study with mixture statistical approach.

BACKGROUND: Metals have been linked to a diverse spectrum of age-related diseases; however, the effects of metal exposure on health span remains largely unknown. This cohort study aims to determine the association between plasma metal and health span in elder adults aged ≥ 90 years. METHODS: The plasma concentrations of seven metals were measured at baseline in 300 elder adults. The end of the health span (EHS) was identified as the occurrence of one of eight major morbidities or mortality events. We used Cox regression to assess hazard ratios (HR). The combined effects of multiple metal mixtures were estimated using grouped-weighted quantile sum (GWQS), quantile g-computation (Q-gcomp), and Bayesian kernel machine regression (BKMR) methods. RESULTS: The estimated HR for EHS with an inter-quartile range (IQR) increment for selenium (Se) was 0.826 (95% confidence interval [CI]: 0.737-0.926); magnesium (Mg), 0.806 (95% CI: 0.691-0.941); iron (Fe), 0.756 (95% CI: 0.623-0.917), and copper (Cu), 0.856 (95% CI: 0.750-0.976). The P for trend of Se, Mg, and Fe were all < 0.05. In the mixture analyses, Q-gcomp showed a negative correlation with EHS (P = 0.904), with the sum of the negative coefficients being -0.211. CONCLUSION: Higher plasma Se, Mg, and Fe reduced the risk of premature end of health span, suggesting that essential metal elements played a role in health maintenance in elder adults.

Could nutrition status predict fatigue one week before in patients with nasopharynx cancer undergoing radiotherapy?

BACKGROUND: Patients with nasopharyngeal carcinoma (NPC) undergoing radiotherapy experience significant fatigue, which is frequently underestimated due to the lack of objective indicators for its evaluation. This study aimed to explore the longitudinal association between fatigue and nutrition status 1 week in advance. METHODS: From January 2021 to June 2022, a total of 105 NPC patients who received intensity-modulated radiation therapy were enrolled in the observational longitudinal study. The significant outcomes, including the Piper Fatigue Scale-12 (PFS-12), the Scored Patient-Generated Subjective Global Assessment (PG-SGA), four body composition indices, and the Hospital Anxiety and Depression Scale (HADS), were assessed weekly from pre-treatment until the completion of radiotherapy (T0-T7) to explore their relationship. RESULTS: The trajectories of PFS-12 and all dimensions for 105 participants reached a peak during the fifth week. Sensory fatigue consistently received the highest scores (T0 = 1.60 ± 2.20, T5 = 6.15 ± 1.57), whereas behavior fatigue exhibited the fastest increase over time (T0 = 1.11 ± 1.86, T5 = 5.47 ± 1.70). Higher PG-SGA scores were found to be weakly explainable for aggravating fatigue (ß = 0.02 ~ 0.04). Unlike generalized additive mixed models, marginal structural models (MSM) produced larger effect values (ß = 0.12 ~ 0.21). Additionally, body composition indices showed weakly negative relationships with fatigue in MSMs one week in advance. CONCLUSIONS: The PG-SGA may be a more accurate predictor of future-week fatigue than individual body composition indicators, particularly when HADS is controlled for as a time-dependent confounder.

Association between patient adherence and treat-to-target in gout: A cross-sectional study.

The implementation of a treat-to-target (T2T) approach has been widely recommended for achieving optimal outcomes in gout treatment, as substantiated by a wealth of compelling evidence. However, a paucity of knowledge exists regarding the barriers hindering effective T2T management in China. This study seeks to investigate the factors contributing to treatment failure within the context of the T2T strategy. A cross-sectional, multi-center investigation was conducted, involving the completion of electronic questionnaires by outpatients undergoing urate-lowering treatment for a duration exceeding 6 months. These questionnaires encompassed demographic information, disease-related conditions, comorbid conditions, and management. The study analyzed factors associated with serum uric acid levels exceeding 360 µmol/L, poor disease control, and poor medication adherence. A total of 425 valid questionnaires were collected, representing 90.8% of the patients. The T2T implementation rate was 26.82% (n = 114). Factors linked to serum uric acid levels surpassing 360 µmol/L included moderate medication adherence (odds ratio (OR) = 2.35; 95% confidence interval (CI) 1.17-4.77; P = .016), poor medication adherence (OR = 4.63; 95% CI 2.28-9.51; P < .001), and management by general practitioners (OR = 0.60; 95% CI 0.37-0.97; P = .036). The rate of well-controlled patients was 14.35% (n = 61). Predictors of not well controlled encompassed the presence of tophi (OR = 2.48; 95% CI 1.17-5.61; P = .023), general medication adherence (OR = 2.78; 95% CI 1.28-6.05; P = .009), poor medication adherence (OR = 6.23; 95% CI 2.68-14.77; P < .001), and poor patient's perception of gout (OR = 4.07; 95% CI 1.41-13.91; P = .015). A poor medication adherence rate of 55.29% (n = 235) was observed, with lower rates of poor medication adherence associated with the use of febuxostat (OR = 0.35; 95% CI 0.14-0.83; P = .02), uric acid levels exceeding 360 µmol/L (OR = 3.05; 95% CI 1.84-5.12; P = .00), moderate patient education (OR = 2.28; 95% CI 1.29-4.15; P = .01), moderate diet control (OR = 1.98; 95% CI 1.17-3.41; P = .01), and poor diet control (OR = 3.73; 95% CI 1.26-12.83; P = .02). The rate of T2T implementation in China is notably low among patients undergoing urate-lowering treatment of gout beyond 6 months. Importantly, medication adherence demonstrates a significant association with T2T outcomes.

Short-term associations of particulate matter with different aerodynamic diameters with mortality due to mental disorders and dementia in Ningde, China.

Limited evidence is available regarding the impact of ambient inhalable particulate matter (PM) on mental disorder (MD) or dementia-related deaths, particularly PM1, PM1-2.5, and coarse particles (PM2.5-10). Moreover, individual confounders have rarely been considered. In addition, evidence from low-pollution areas is needed but is inadequate. Using death records from the Death Registration System during 2015-2021 in Ningde, a coastal city in southeast China, we combined a conditional quasi-Poisson model with a distributed lag nonlinear model to estimate the nonlinear and lagged associations of PM exposure with MD or dementia-related deaths in Ningde, China, comprehensively controlling for individual time-invariant confounders using a time-stratified case-crossover design. The attributable fraction and number were calculated to quantify the burden of MD or dementia-related deaths that were related to PMs. We found J-shaped relationships between MD or dementia-related deaths and PMs, with different thresholds of 13, 9, 19, 33 and 12 µg/m3 for PM1, PM1-2.5, PM2.5, PM10 and PM2.5-10. An inter-quartile range increase for PM1, PM1-2.5, PM2.5, PM10 and PM2.5-10 above the thresholds led to an increase of 31.8% (95% confidence interval, 14.3-51.9%), 53.7% (22.4-93.1%), 32.6% (15.0-53.0%), 35.1% (17.7-55.0%) and 25.9% (13.0-40.3%) in MD-related deaths at lag 0-3 days, respectively. The associations were significant in the cool season rather than in the warm season and were significantly greater among people aged 75-84 years than in others. The fractions of MD-related deaths attributable to PM1, PM1-2.5, PM2.5, PM10 and PM2.5-10 were 5.55%, 6.49%, 7.68%, 10.66%, and 15.11%, respectively; however, only some of them could be protected by the concentrations recommended by the World Health Organisation or China grade I standard. Smaller associations and similar patterns were observed between PMs and dementia-related death. These findings suggest stricter standards, and provide evidence for the development of relevant policies and measures.

Interactions of particulate matter with temperature, heat index and relative humidity on pediatric hand, foot, and mouth disease in a subtropical city.

The associations of hand, foot, and mouth disease (HFMD) with meteorological variables and particulate matter (PM) remain controversial, and limited evidence is available on heat index (HI) and coarse particulate (PM10-2.5). Moreover, temperature and humidity are considered major risk factors but their interaction with PM remains unclear. We combined the distributed lag non-linear and quasi-Poisson models to estimate the non-linear and lagged associations of meteorological variables and PM with HFMD based on reported HFMD during 2015-2019 in Fuzhou, China. The multiplicative term of interaction was used to explore the relationship between HFMD and meteorological variables or PM at different levels of another variable. Stratified analyses were used to identify vulnerable subpopulations. We observed inverted-V-shaped relationships between HFMD and temperature and HI, and the W- and N-shaped for relative humidity (RH) and PM, respectively. Extreme high (i.e., the 95th percentile) temperature, HI and RH increased the HFMD with relative risks (RR) of 4.00 (95% confidence interval, 2.79-5.75), 2.20 (1.71-2.83) and 1.54 (1.35-1.75) referent to the minimum effect value of 10.3 °C, 69.4 and 54.8%, respectively. Higher concentrations of PM rapidly increased the HFMD. Infants under 2 years suffered more from temperature, HI and PM. There were synergistic effects between meteorological variables and PM on HFMD. For instance, the RRs of temperature (30 °C) and RH (40%) on HFMD increased from 3.68 (2.24-6.06) to 6.44 (4.29-9.66) and from 0.45 (0.14-1.47) to 2.15 (0.90-5.12) at low (<25%) and high (>75%) categories of PM2.5, respectively. While the RRs of 70 µg/m3 of PM10 and PM10-2.5 increased from 0.65 (0.32-1.31) to 2.93 (1.63-5.26) and from 0.86 (0.23-3.21) to 3.26 (1.23-8.62) at low and high categories of HI. These findings are essential for the development a prediction and warning systems and prevention and control strategies for HFMD.

A spatiotemporal analysis of the association between carbon productivity, socioeconomics, medical resources and cardiovascular diseases in southeast rural China.

Introduction: With China's rapid industrialization and urbanization, China has been increasing its carbon productivity annually. Understanding the association between carbon productivity, socioeconomics, and medical resources with cardiovascular diseases (CVDs) may help reduce CVDs burden. However, relevant studies are limited. Objectives: The study aimed to describe the temporal and spatial distribution pattern of CVDs hospitalization in southeast rural China and to explore its influencing factors. Methods: In this study, 1,925,129 hospitalization records of rural residents in southeast China with CVDs were analyzed from the New Rural Cooperative Medical Scheme (NRCMS). The spatial distribution patterns were explored using Global Moran's I and Local Indicators of Spatial Association (LISA). The relationships with influencing factors were detected using both a geographically and temporally weighted regression model (GTWR) and multiscale geographically weighted regression (MGWR). Results: In southeast China, rural inpatients with CVDs increased by 95.29% from 2010 to 2016. The main groups affected were elderly and women, with essential hypertension (26.06%), cerebral infarction (17.97%), and chronic ischemic heart disease (13.81%) being the leading CVD subtypes. The results of LISA shows that central and midwestern counties, including Meilie, Sanyuan, Mingxi, Jiangle, and Shaxian, showed a high-high cluster pattern of CVDs hospitalization rates. Negative associations were observed between CVDs hospitalization rates and carbon productivity, and positive associations with per capita GDP and hospital beds in most counties (p < 0.05). The association between CVDs hospitalization rates and carbon productivity and per capita GDP was stronger in central and midwestern counties, while the relationship with hospital bed resources was stronger in northern counties. Conclusion: Rural hospitalizations for CVDs have increased dramatically, with spatial heterogeneity observed in hospitalization rates. Negative associations were found with carbon productivity, and positive associations with socioeconomic status and medical resources. Based on our findings, we recommend low-carbon development, use of carbon productivity as an environmental health metric, and rational allocation of medical resources in rural China.

Association between solid cooking fuel and cognitive decline: Three nationwide cohort studies in middle-aged and older population.

BACKGROUND: Household solid-fuel burning contributes to indoor air pollution and is linked to poor cognitive function, but how solid cooking fuel use leads to cognitive decline over time is not well elaborated. OBJECTIVE: We examine the associations of solid cooking fuel with cognitive function among three nationally representative cohorts. METHODS: This study uses data from the 2010-2018 China Family Panel Studies (CFPS), the 2011-2018 China Health and Retirement Longitudinal Study (CHARLS) and the 2003-2015 Mexican Health and Aging Study (MHAS) in adults over the age of 50. Time varying Cox model was conducted to measure the association between cooking fuel types and cognitive decline. Mediation analysis was used to estimate the potential mediation effects on the associations of cooking fuel types with cognitive decline risk. RESULTS: Respondents in CFPS, CHARLS, and MHAS relied on solid cooking fuel at baseline approximately 56 %, 51 %, and 12 %, respectively. Using solid fuel was consistently associated with higher risk of cognitive decline in three cohorts (CFPS: HR = 1.300 [95 % CI: 1.201, 1.407], CHARLS: HR = 1.179 [95 % CI: 1.059, 1.312], MHAS: HR = 1.237 [95 % CI: 1.123, 1.362]). Compared to those with persistent solid fuel, persistent clean fuel and change from solid fuel to clean fuel were associated with a lower risk of cognitive decline. Hypertension, diabetes, physical activity, dyslipidemia and high-density lipoprotein cholesterol (HDL-C) may partially mediate the cognitive decline caused by solid fuel use. Of the cognitive decline burden, 18.23 % (95 % CI: 12.21 %, 24.73 %) in CFPS, 8.90 % (95 % CI: 2.93 %, 15.52 %) in CHARLS and 2.92 % (95 % CI: 1.52 %, 4.46 %) in MHAS of cognitive decline cases attributable to solid cooking fuel use. CONCLUSION: The use of solid cooking fuel is associated with a higher risk of cognitive decline. It is essential to promote the expanded use of clean fuel to protect cognitive health.

The effects of aerobic exercise on body composition in overweight and obese patients with gout: a randomized, open-labeled, controlled trial.

BACKGROUND: Overweight and obesity are typical risk factors for the increased prevalence and incidence of gout. The existing guidelines unequivocally indicated that exercise is highly advantageous for patients with gout. Nevertheless, there is still a lack of specific guidance and clinical evidence. The effects of exercise on improving gout, and the optimal frequency, timing, and types of exercise have not been fully clarified. The present trial aims to determine the effects of a specific aerobic exercise program on body composition in overweight and obese patients with gout. METHODS: In this randomized, open-labeled, controlled trial, a total of 60 overweight and obese patients with gout [body mass index (BMI) ≥ 24 kg/m2; age,18-55 years old] are equally randomized (1:1) into two groups (n = 30): moderate-intensity aerobic exercise group (MIAEG), heart rate reserve (HRR) = [(HRmax-HRrest) × 60% intensity] + HRrest, and control group (CG). The moderate-intensity aerobic exercise training program will be conducted for 30-40 min/session and 3 days/week for 12 weeks. Participants in the CG will be asked to avoid making changes in their exercise habits. There will be no limitation in the type of exercise. The primary outcome is the number of patients whose body fat is reduced after 12 weeks. The secondary outcomes include the changes in BMI, waist-to-hip ratio (WHR), insulin resistance index (IRI), serum uric acid (sUA), serum creatinine (SCr), estimated glomerular filtration rate (eGFR), triglycerides (TG), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), hepatic steatosis, and adverse effects after 12 weeks. One-way analysis of variance (ANOVA) will be used to compare the mean values of normally distributed variables between MIAEG and GC. DISCUSSION: The effect and optimal frequency of exercise for improving the status of overweight and obese patients with gout have not yet been determined. We design a 12-week randomized controlled trial and evaluate the effects of individualized aerobic exercise program on patients with gout. The results may assist such patients with a personalized scientific exercise program based on the disease status and motor abilities, so that patients are prone to exercise under the condition of low risk and achieve the greatest benefits. TRIAL REGISTRATION: ChiCTR2200062153. Registered on July 25, 2022, with ChiCTR. http://www.chictr.org.cn/.

Effect of apparent temperature on hospitalization from a spectrum of cardiovascular diseases in rural residents in Fujian, China.

Cardiovascular disease (CVD) is a leading threat to global public health. Although associations between temperature and CVD hospitalization have been suggested for developed countries, limited evidence is available for developing countries or rural residents. Moreover, the effect of apparent temperature (AT) on the spectrum of cause-specific CVDs remains unknown. Based on 2,024,147 CVD hospitalizations for rural residents from eight regions in Fujian Province, China, during 2010-2016, a quasi-Poisson regression with distributed lag non-linear model was fitted to estimate the AT effect on daily CVD hospitalization for each region, and then pooled in a meta-regression that included regional indicators related to rural residents. Stratified analyses were performed according to the cause of hospitalization, sex and age groups. Finally, we calculated the fraction of CVD hospitalizations attributable to AT, as a reflection of the burden associated with AT. The heat effect appeared at lag 0-1 days, with 19% (95% CI, 11-26%) increased risk of CVD hospitalization, which was worse for ischemic heart disease, heart failure, arrhythmias and ischemic stroke. The decreased AT was associated with increase of hemorrhagic stroke at lag 0-28 days. People aged 65 and above suffered more from the heat effect on cardiovascular and cerebrovascular diseases. Regions with a lower gross value of agricultural production, rural residents' per capita net income, number of air conditioners and water heaters were more susceptible. A large number of hospitalizations were attributable to heat for most subcategories. High AT level increased CVD hospitalization, and the subcategories had different susceptibilities. The effects were modified by individual and regional characteristics. These findings have important implications for the development of targeted interventions and for hospital service planning.

Temperature Variability and Hospital Admissions for Chronic Obstructive Pulmonary Disease: Analysis of Attributable Disease Burden and Vulnerable Subpopulation.

Purpose: Chronic obstructive pulmonary disease (COPD) is a major cause of chronic diseases causing considerable social and economic burden globally. Despite substantial evidence on temperature-COPD association, few studies have investigated the acute effect of temperature variability (TV), a potential trigger of exacerbation of COPD disease, and it remains unknown what fraction of the disease burden of COPD is attributable to TV. Patients and Methods: Based on 71,070 COPD hospitalizations during 2013-2015 in Guangzhou, China, we conducted a time-series analysis using quasi-Poisson regression to assess the association between TV and hospital admission for COPD after adjusting for daily mean temperature. Short-term TV was captured by the standard deviation of hourly or daily temperatures across various exposure days. We also provided the fraction (total number) of COPD attributable to TV. Stratified analyses by admission route, sex, age, occupation, marital status and season were performed to identify vulnerable subpopulations. Results: We found a linear relationship between TV and COPD hospitalization, with a 1°C increase in hourly TV and daily TV associated with 4.3% (95%CI: 2.2-6.4) and 4.0% (2.3-5.8) increases in COPD, respectively. The greater relative risks of TV identified males, people aged 0-64 years, blue collar, and divorced/widowed people as vulnerable population. There were 12.0% (8500 cases) of COPD hospitalization attributable to hourly TV during the study period. Daily TV produced similar estimates of relative effects (relative risk) but grater estimates of absolute effects (attributable fraction) than hourly TV. Conclusion: We concluded that TV was an independent risk factor of COPD morbidity, especially among the susceptible subgroups. These findings would be helpful to guide the development of targeted public intervention.

A nomogram for predicting mortality in patients with COVID-19 and solid tumors: a multicenter retrospective cohort study.

BACKGROUND: Individualized prediction of mortality risk can inform the treatment strategy for patients with COVID-19 and solid tumors and potentially improve patient outcomes. We aimed to develop a nomogram for predicting in-hospital mortality of patients with COVID-19 with solid tumors. METHODS: We enrolled patients with COVID-19 with solid tumors admitted to 32 hospitals in China between December 17, 2020, and March 18, 2020. A multivariate logistic regression model was constructed via stepwise regression analysis, and a nomogram was subsequently developed based on the fitted multivariate logistic regression model. Discrimination and calibration of the nomogram were evaluated by estimating the area under the receiver operator characteristic curve (AUC) for the model and by bootstrap resampling, a Hosmer-Lemeshow test, and visual inspection of the calibration curve. RESULTS: There were 216 patients with COVID-19 with solid tumors included in the present study, of whom 37 (17%) died and the other 179 all recovered from COVID-19 and were discharged. The median age of the enrolled patients was 63.0 years and 113 (52.3%) were men. Multivariate logistic regression revealed that increasing age (OR=1.08, 95% CI 1.00 to 1.16), receipt of antitumor treatment within 3 months before COVID-19 (OR=28.65, 95% CI 3.54 to 231.97), peripheral white blood cell (WBC) count ≥6.93 ×109/L (OR=14.52, 95% CI 2.45 to 86.14), derived neutrophil-to-lymphocyte ratio (dNLR; neutrophil count/(WBC count minus neutrophil count)) ≥4.19 (OR=18.99, 95% CI 3.58 to 100.65), and dyspnea on admission (OR=20.38, 95% CI 3.55 to 117.02) were associated with elevated mortality risk. The performance of the established nomogram was satisfactory, with an AUC of 0.953 (95% CI 0.908 to 0.997) for the model, non-significant findings on the Hosmer-Lemeshow test, and rough agreement between predicted and observed probabilities as suggested in calibration curves. The sensitivity and specificity of the model were 86.4% and 92.5%. CONCLUSION: Increasing age, receipt of antitumor treatment within 3 months before COVID-19 diagnosis, elevated WBC count and dNLR, and having dyspnea on admission were independent risk factors for mortality among patients with COVID-19 and solid tumors. The nomogram based on these factors accurately predicted mortality risk for individual patients.

Evaluating the effectiveness of national measles elimination action in mainland China during 2004-2016: A multi-site interrupted time-series study.

BACKGROUND: To block transmission of measles, the China Ministry of Health endorsed the "2006-2012 National Measles Elimination Action Plan (NMEAP)" on November 11, 2006, while no published studies used mathematical models to assess the impact of this action. Also, the problem of residuals autocorrelation due to auto-correlated infectious disease data is often ignored in practice. METHODS: Based on monthly counts of measles in 31 Chinese provinces during 2004-2016, a spatiotemporal auto-correlated mixed model was developed to assess the intervention effects over 10 years after the NMEAP, after controlling for seasonality and time-varying socioeconomic and meteorological factors. The first-order autoregression dynamic relationship was used to adjust the bias of conditional covariance in Quasi-likelihood function due to temporal autocorrelation and the spatial autoregressive term was used to capture the neighbor effects of adjacent provinces. RESULTS: There were a similar seasonal pattern and spatial differences of measles incidence among provinces, yet the spatiotemporal pattern was diminished after the intervention. The introduction of the NMEAP was associated with a reduction of 51.03% [excess risk (ER%) = -51.03%, 95% CI: -62.32% to -36.37%] in measles morbidity on average during the 10-year intervention period. The intervention effect varied with time. The significant effect was observed 15 months after the intervention onset, and then gradually increased to a stable level, but was weakened slightly after 2012. The effect of birth rate and meteorological factors on measles morbidity reduced after the NMEAP. CONCLUSIONS: There was clear evidence that prominent progress towards a goal of measles elimination had been achieved after the intervention, while the resurgence after 2012 indicated the goal for measles elimination by 2012 had not been reached.

Effects of hourly levels of ambient air pollution on ambulance emergency call-outs in Shenzhen, China.

Some researches have shown the associations between air pollution and hospital-based emergency department visits, while the evidence about the acute effects of air pollution on emergency ambulance dispatches for the whole population is rarely available, especially on an hourly time scale. This paper aimed to investigate the effects of hourly concentrations of ambient air pollution on hourly number of ambulance emergency call-outs (AECOs) in Shenzhen, China. AECO data were collected from Shenzhen Emergency Center from January 2013 to December 2016. A time-stratified case-crossover design with conditional Poisson regression was performed to fit the relationship between hourly air pollution and AECOs. The distributed lag model was applied to determine lag structure of the effects of air pollutants. There were a total of 502,862 AECOs during the study period. The significant detrimental effects of SO2, PM2.5, and PM10 appeared immediately with a following harvesting effect after 5 h and the effects lasted for about 96 h. The cumulative effect estimates of four pollutants over 0-96 h were 13.99% (95% CI 7.52-20.85%), 2.07% (95% CI 0.72-3.43%), 1.20% (95% CI 0.54-1.87%), and 2.46% (95% CI 1.63-3.29%), respectively. We did not observe significant effects of O3. This population-based study quantifies the adverse effects of air pollution on ambulance dispatches and provides evidence of the lag structure of the effects on an hourly time scale.

Effects of hourly precipitation and temperature on road traffic casualties in Shenzhen, China (2010-2016): A time-stratified case-crossover study.

BACKGROUND: Although road traffic casualty (RTC) is preventable, it remains the eighth leading cause of death globally, especially in developing countries. Previous studies suggested the association between RTC and monthly or daily weather conditions, while the acute effects of weather conditions on an hourly timescale remains unknown. This study aims to quantify hourly effects of precipitation and temperature on RTC. METHODS: Using ambulance records on RTC during 2010-2016 for the whole population in Shenzhen, China, we conducted a time-stratified case-crossover design which can inherently control for hour of the day, day of the week, seasonality, time trends and potential time-invariant confounders. Conditional quasi-Poisson regression with distributed lag nonlinear model was used to determine the effects of hourly precipitation and temperature on RTC. RESULTS: Light and heavy precipitation increased RTC in current and following 2 h by 8.09% (95% CI: 4.20-12.12%) and 11.62% (95% CI: 5.93-17.62%), respectively. A J-shaped temperature-RTC curve revealed that each 1 °C increment above 17 °C were associated with a 0.87% (0.52-1.22%) increase in RTC. High temperature accounted for 6.44% (95% CI: 3.95-8.91%) of all RTC, with a high fraction of 10.64% (95% CI: 4.33-15.96%) during warm season and 8.30% (95% CI: 4.26-12.66%) in traffic peak hours. Precipitation contributed to 0.68% (95% CI: 0.44-0.92%) of RTC within 3 h. The middle-aged and female suffered more from precipitation-associated RTC, and the younger suffered more from high temperature-associated RTC. CONCLUSIONS: High temperature increased substantially hourly RTC. Precipitation was also a risk factor of RTC and the adverse effect lasted for 3 h. The findings would be helpful to guide the development of targeted intervention to accelerate progress in road traffic safety.

Effects of hourly precipitation and temperature on ambulance response time.

BACKGROUND: Longer ambulance response time (ART) delaying treatment would worsen conditions of seriously ill or injured patients, but limited evidence is available on the effects of weather factors on ART. This study aims to assess precipitation- and temperature-ART associations and their potential lagged effects using a novel modeling strategy. METHODS: Based on 779,156 emergency records during 2010-2016 from the whole population in Shenzhen, China, we creatively combined quantile regression with distributed-lag nonlinear models to examine the non-linear and lagged effects of hourly precipitation and temperature on ART at the 50th and 90th percentiles. RESULTS: A linear precipitation-ART association with a delay of 9.01 (95%CI, 7.82-10.20) seconds at median ART for a 1 mm increase in hourly precipitation, and the effects lasted for 5 h with the greatest effect at the current hour. A two linear thresholds temperature-ART association revealed 1 °C decrease below 19 °C caused 1.68 (95%CI, 0.92-2.44) seconds delay in total ART over lag 0-7 h, and 1 °C increase above 24 °C caused 2.44 (95%CI, 1.55-3.33) seconds delay. The hourly call volumes exceeding 54 calls caused 8.79 (95%CI, 8.71-8.86) seconds delay in total ART for 1 more call, but not affected the effects of weather factors. The internal ART suffered more from the hourly call volumes, while the external ART suffered more from precipitation and temperature. The effects were apparently greater on ART at the 90th percentile than median. CONCLUSIONS: Precipitation and temperature are independent risk factors for ambulance services performance, and their lagged effects are notable. The external ART and patients with long ART are vulnerable. More attention should be paid to weather and ART, and these findings may have implications for effective policies to reduce ART to protect public health.

A water-stable terbium-MOF sensor for the selective, sensitive, and recyclable detection of Al3+ and CO32- ions.

A terbium metal-organic framework associated with mixed 4-(pyridin-3-yloxy)-phthalic acid (H2ppda) and oxalic acid (H2ox) has been synthesized under solvothermal conditions, namely [Tb(ppda)(ox)0.5(H2O)2]n (1). Compound 1 is constructed of 1D binuclear [Tb(ppda)]2 chains and is further connected by ox2- ligands, exhibiting a 2D layered structure. It is worth noting that compound 1 exhibits excellent fluorescence stability over a pH range from 2 to 13 in aqueous solution. Interestingly, compound 1 can detect Al3+ ions with high selectivity and sensitivity among diverse inorganic cations in aqueous solution. In addition, compound 1 is also a highly selective sensing material for CO32- ions without interference from other common anions. Therefore, compound 1 is a promising sensor with a fast response time and low limits of detection for simultaneously detecting Al3+ and CO32- ions, at 5.66 µM for Al3+ ions and 0.38 µM for CO32- ions. Compound 1 displays the lowest limit of detection for CO32- ions using a fluorescent MOF sensor reported to date. The luminescence quenching mechanisms for the different analytes are further explored in detail.

A tensor product quasi-Poisson model for estimating health effects of multiple ambient pollutants on mortality.

BACKGROUND: People are exposed to mixtures of highly correlated gaseous, liquid and solid pollutants. However, in previous studies, the assessment of air pollution effects was mainly based on single-pollutant models or was simultaneously included as multiple pollutants in a model. It is essential to develop appropriate methods to accurately estimate the health effects of multiple pollutants in the presence of a high correlation between pollutants. METHODS: The flexible tensor product smooths of multiple pollutants was applied for the first time in a quasi-Poisson model to estimate the health effects of SO2, NO2 and PM10 on daily all-cause deaths during 2005-2012 in Guangzhou, China. The results were compared with those from three other conventional models, including the single-pollutant model and the three-pollutant model with and without first-order interactions. RESULTS: The tensor product model revealed a complex interaction among three pollutants and significant combined effects of PM10, NO2 and SO2, which revealed a 2.53% (95%CI: 1.03-4.01%) increase in mortality associated with an interquartile-range (IQR) increase in the concentrations of all three pollutants. The combined effect estimated by the single-pollutant model was 5.63% (95% CI: 3.96-7.34%). Although the conventional three-pollutant models produced combined effect estimates (2.20, 95%CI, 1.18-3.23%; 2.78, 95%CI: 1.35-4.23%) similar to those of the tensor product model, they distorted the estimates and inflated the variances of the estimates when attributing the combined health effects to individual pollutants. CONCLUSIONS: The single-pollutant model or conventional multi-pollutant model may yield misleading results in the presence of collinearity. The tensor product quasi-Poisson regression provides a novel approach to the assessment of the health impacts of multiple pollutants by flexibly fitting the interaction effects and avoiding the collinearity problem.

A water-stable europium-MOF as a multifunctional luminescent sensor for some trivalent metal ions (Fe3+, Cr3+, Al3+), PO43- ions, and nitroaromatic explosives.

A luminescent Eu-MOF, namely, [Eu2(ppda)2(npdc)(H2O)]·H2O (1) based on the mixed ligands 4-(pyridin-3-yloxy)-phthalic acid (H2ppda) and naphthalene-1,4-dicarboxylic acid (H2npdc) was synthesized under solvothermal conditions. Compound 1 was initially constructed from the 1D binuclear chains of [Ln(npdc)]2 and further connected by ppda2- ligands, forming a 2D layered structure. It is worth noting that compound 1 exhibited excellent fluorescence stability in the pH range of 2-13 in an aqueous solution. It was found that compound 1 could not only detect trivalent Fe3+, Cr3+ and Al3+ ions with high selectivity and recyclability but also serve as an excellent selective sensing material for PO43- ions among some anions. The detection of NACs demonstrated that compound 1 could also behave as a functional probe with high selectivity, sensitivity, and recyclability, and the detection limit of TNP was 2.97 × 10-6 M. Furthermore, the luminescent sensing mechanisms for different analytes were speculated.

Socio-geographic disparity in cardiorespiratory mortality burden attributable to ambient temperature in the United States.

Compared with relative risk, attributable fraction (AF) is more informative when assessing the mortality burden due to some environmental exposures (e.g., ambient temperature). Up to date, however, available AF-based evidence linking temperature with mortality has been very sparse regionally and nationally, even for the leading mortality types such as cardiorespiratory deaths. This study aimed to quantify national and regional burden of cardiorespiratory mortality (CRM) attributable to ambient temperature in the USA, and to explore potential socioeconomic and demographic sources of spatial heterogeneity between communities. Daily CRM and weather data during 1987-2000 for 106 urban communities across the mainland of USA were acquired from the publicly available National Morbidity, Mortality and Air Pollution Study (NMMAPS). We did the data analysis using a three-stage analytic approach. We first applied quasi-Poisson regression incorporated with distributed lag nonlinear model to estimate community-specific temperature-CRM associations, then pooled these associations at the regional and national level through a multivariate meta-analysis, and finally estimated the temperature-AF of CRM and performed subgroup analyses stratified by community-level characteristics. Both low and high temperatures increased short-term CRM risk, while temperature-CRM associations varied by regions. Nationally, the fraction of cardiorespiratory deaths caused by the total non-optimum, low, and high temperatures was 7.58% (95% empirical confidence interval, 6.68-8.31%), 7.15% (6.31-7.85%), and 0.43% (0.37-0.46%), respectively. Greater temperature-AF was identified in two northern regions (i.e., Industrial Midwest and North East) and communities with lower temperature and longitude, higher latitude, and moderate humidity. Additionally, higher vulnerability appeared in locations with higher urbanization level, more aging population, less White race, and lower socioeconomic status. Ambient temperature may be responsible for a large fraction of cardiorespiratory deaths. Also, temperature-AF of CRM varied considerably by geographical and climatological factors, as well as community-level disparity in socioeconomic status.