Relationships among green space, ambient fine particulate matter, and cancer incidence in Taiwan: A 16-year retrospective cohort study.

INTRODUCTION: Green space and air pollution have been recognized as vital health determinants. There is a paucity of studies examining the interplay between green space, fine particulate matter (PM2.5), and the incidence of specific cancers. OBJECTIVE: We aimed to explore the contributions of green space and ambient PM2.5 to the risk of specific cancers in terms of the most common cancers based on incidence or mortality rate in Taiwan and to ascertain the interaction between green space and PM2.5 and their role in cancer risk. MATERIALS AND METHODS: This retrospective longitudinal cohort study included 407,415 participants. Data were obtained from the 2000-2015 Mei Jau Health Examination Database linked to the Taiwan Cancer Registry and Causes of Death datasets. All participants were aged ≥20 years and had no history of cancer. The environmental exposure were the normalized difference vegetation index (NDVI) and the 2-year average PM2.5 at baseline. Multivariate adjusted hazard ratios (HRs) were calculated using Cox proportional hazards models. We adjusted for covariates including demographics, anthropometrics, comorbidities, health behaviors, biochemical data, and environmental factors. RESULTS: During a median follow-up of 10.37 years, 11,576 cancer cases were reported. PM2.5 exposure increased the risk of all cancers (HR: 1.11, [95% CI: 1.06-1.15]), stomach cancer (HR: 1.27, [1.02-1.58]), endocrine gland cancer (HR: 2.13, [1.39-3.26]), breast cancer (HR: 1.12, [1.03-1.22]), and lung cancer (HR: 1.12, [1.01-1.24]). An increase in NDVI reduced the risk of prostate cancer (HR: 0.93, [0.88-0.99]) and lung cancer (HR: 0.95, [0.91-0.99]). NDVI influenced the incidence of prostate and all cancers by reducing PM2.5 concentrations. CONCLUSION: Long-term PM2.5 exposure is associated with an increased risk of some types of cancers. In contrast, an increase in environmental green space exposure is associated with lowering of the risk of prostate and lung cancer.

Enhancing Raman signals through electromagnetic hot zones induced by magnetic dipole resonance of metal-free nanoparticles.

In this study, we found that the large area of electromagnetic field hot zone induced through magnetic dipole resonance of metal-free structures can greatly enhance Raman scattering signals. The magnetic resonant nanocavities, based on high-refractive-index silicon nanoparticles (SiNPs), were designed to resonate at the wavelength of the excitation laser of the Raman system. The well-dispersed SiNPs that were not closely packed displayed significant magnetic dipole resonance and gave a Raman enhancement per unit volume of 59 347. The hot zones of intense electric field were generated not only within the nonmetallic NPs but also around them, even within the underlying substrate. We observed experimentally that gallium nitride (GaN) and silicon carbide (SiC) surfaces presenting very few SiNPs (coverage: <0.3%) could display significantly enhanced (>50%) Raman signals. In contrast, the Raman signals of the underlying substrates were not enhanced by gold nanoparticles (AuNPs), even though these NPs displayed a localized surface plasmon resonance (LSPR) phenomenon. A comparison of the areas of the electric field hot zones (E 2 > 10) generated by SiNPs undergoing magnetic dipole resonance with the electric field hot spots (E 2 > 10) generated by AuNPs undergoing LSPR revealed that the former was approximately 70 times that of the latter. More noteworthily, the electromagnetic field hot zone generated from the SiNP is able to extend into the surrounding and underlying media. Relative to metallic NPs undergoing LSPR, these nonmetallic NPs displaying magnetic dipole resonance were more effective at enhancing the Raman scattering signals from analytes that were underlying, or even far away from, them. This application of magnetic dipole resonance in metal-free structures appears to have great potential for use in developing next-generation techniques for Raman enhancement.

Online platform for applying space-time scan statistics for prospectively detecting emerging hot spots of dengue fever.

BACKGROUND: Cases of dengue fever have increased in areas of Southeast Asia in recent years. Taiwan hit a record-high 42,856 cases in 2015, with the majority in southern Tainan and Kaohsiung Cities. Leveraging spatial statistics and geo-visualization techniques, we aim to design an online analytical tool for local public health workers to prospectively identify ongoing hot spots of dengue fever weekly at the village level. METHODS: A total of 57,516 confirmed cases of dengue fever in 2014 and 2015 were obtained from the Taiwan Centers for Disease Control (TCDC). Incorporating demographic information as covariates with cumulative cases (365 days) in a discrete Poisson model, we iteratively applied space-time scan statistics by SaTScan software to detect the currently active cluster of dengue fever (reported as relative risk) in each village of Tainan and Kaohsiung every week. A village with a relative risk >1 and p value <0.05 was identified as a dengue-epidemic area. Assuming an ongoing transmission might continuously spread for two consecutive weeks, we estimated the sensitivity and specificity for detecting outbreaks by comparing the scan-based classification (dengue-epidemic vs. dengue-free village) with the true cumulative case numbers from the TCDC's surveillance statistics. RESULTS: Among the 1648 villages in Tainan and Kaohsiung, the overall sensitivity for detecting outbreaks increases as case numbers grow in a total of 92 weekly simulations. The specificity for detecting outbreaks behaves inversely, compared to the sensitivity. On average, the mean sensitivity and specificity of 2-week hot spot detection were 0.615 and 0.891 respectively (p value <0.001) for the covariate adjustment model, as the maximum spatial and temporal windows were specified as 50% of the total population at risk and 28 days. Dengue-epidemic villages were visualized and explored in an interactive map. CONCLUSIONS: We designed an online analytical tool for front-line public health workers to prospectively detect ongoing dengue fever transmission on a weekly basis at the village level by using the routine surveillance data.

Spatial decision on allocating automated external defibrillators (AED) in communities by multi-criterion two-step floating catchment area (MC2SFCA).

BACKGROUND: The occurrence of out-of-hospital cardiac arrest (OHCA) is a critical life-threatening event which frequently warrants early defibrillation with an automated external defibrillator (AED). The optimization of allocating a limited number of AEDs in various types of communities is challenging. We aimed to propose a two-stage modeling framework including spatial accessibility evaluation and priority ranking to identify the highest gaps between demand and supply for allocating AEDs. METHODS: In this study, a total of 6135 OHCA patients were defined as demand, and the existing 476 publicly available AEDs locations and 51 emergency medical service (EMS) stations were defined as supply. To identify the demand for AEDs, Bayesian spatial analysis with the integrated nested Laplace approximation (INLA) method is applied to estimate the composite spatial risks from multiple factors. The population density, proportion of elderly people, and land use classifications are identified as risk factors. Then, the multi-criterion two-step floating catchment area (MC2SFCA) method is used to measure spatial accessibility of AEDs between the spatial risks and the supply of AEDs. Priority ranking is utilized for prioritizing deployment of AEDs among communities because of limited resources. RESULTS: Among 6135 OHCA patients, 56.85 % were older than 65 years old, and 79.04 % were in a residential area. The spatial distribution of OHCA incidents was found to be concentrated in the metropolitan area of Kaohsiung City, Taiwan. According to the posterior mean estimated by INLA, the spatial effects including population density and proportion of elderly people, and land use classifications are positively associated with the OHCA incidence. Utilizing the MC2SFCA for spatial accessibility, we found that supply of AEDs is less than demand in most areas, especially in rural areas. Under limited resources, we identify priority places for deploying AEDs based on transportation time to the nearest hospital and population size of the communities. CONCLUSION: The proposed method will be beneficial for optimizing resource allocation while considering multiple local risks. The optimized deployment of AEDs can broaden EMS coverage and minimize the problems of the disparity in urban areas and the deficiency in rural areas.

Size, composition and structural changes of TiO2 rutile nanoparticles by pulsed laser ablation in water.

The rutile-type TiO2 powders originally whitish and micrometer in size were successfully reduced in size with accompanied structure, composition and optical property change to become dark bluish by pulsed laser ablation in liquid under 532 nm excitation and 400 mJ per pulse at a specified water depth (5 or 15 mm) for up to 30 min. Transmission electron microscopic observations indicated the newly formed anatase nanoparticles are ca. 5 nm in size with spindle-like shape having well-developed {101} faces and -(001) facets for mutual coalescence into unity. The -(001)-specific coalescence twin of anatase was also observed. There are also amorphous nanoparticles in association with anatase, minor brookite and relic rutile with 2 x (110) superstructure. The resultant colloidal TiO2 nanoparticles are (Ti3+, Ti2+, H+) co-signified according to optical spectroscopic results and have a bimodal minimum band gaps 3.12 and 2.66 eV due to nanocrystals and amorphous phase, respectively, for potential optocatalytic applications in UV-visible range.

Long-Term Exposure to Ambient Fine Particulate Matter and Chronic Kidney Disease: A Cohort Study.

BACKGROUND: Chronic kidney disease (CKD) is a serious global public health challenge, but there is limited information on the connection between air pollution and risk of CKD. OBJECTIVE: The aim of this study was to investigate the association between long-term exposure to particulate matter (PM) with an aerodynamic diameter of less than [Formula: see text] ([Formula: see text]) and the development of CKD in a large cohort. METHODS: A total of 100,629 nonCKD Taiwanese residents age 20 y or above were included in this study between 2001 and 2014. Ambient [Formula: see text] concentration was estimated at each participant's address using a satellite-based spatiotemporal model. Incident CKD cases were identified by an estimated glomerular filtration rate (eGFR) of less than [Formula: see text]. We collected information on a wide range of potential confounders/modifiers during the medical examinations. Cox proportional hazard regression was applied to calculate hazard ratios (HRs). RESULTS: During the follow-up, 4,046 incident CKD cases were identified, and the incidence rate was 6.24 per 1,000 person-years. In contrast with participants with the first quintile exposure of [Formula: see text], participants with the fourth and fifth quintiles exposure of [Formula: see text] had increased risk of CKD development, adjusting for age, sex, educational level, smoking, drinking, body mass index, systolic blood pressure, fasting glucose, total cholesterol, and self-reported heart disease or stroke, with an HR [95% confidence interval (CI)] of 1.11 (1.02, 1.22) and 1.15 (1.05, 1.26), respectively. A significant concentration-response trend was observed ([Formula: see text]). Every [Formula: see text] increment in the [Formula: see text] concentration was associated with a 6% higher risk of developing CKD (HR: 1.06, 95% CI: 1.02, 1.10). Sensitivity and stratified analyses yielded similar results. CONCLUSIONS: Long-term exposure to ambient [Formula: see text] was associated with an increased risk of CKD development. Our findings reinforce the urgency to develop global strategies of air pollution reduction to prevent CKD. https://doi.org/10.1289/EHP3304.

Balancing geo-privacy and spatial patterns in epidemiological studies.

To balance the protection of geo-privacy and the accuracy of spatial patterns, we developed a geo-spatial tool (GeoMasker) intended to mask the residential locations of patients or cases in a geographic information system (GIS). To elucidate the effects of geo-masking parameters, we applied 2010 dengue epidemic data from Taiwan testing the tool's performance in an empirical situation. The similarity of pre- and post-spatial patterns was measured by D statistics under a 95% confidence interval. In the empirical study, different magnitudes of anonymisation (estimated Kanonymity ≥10 and 100) were achieved and different degrees of agreement on the pre- and post-patterns were evaluated. The application is beneficial for public health workers and researchers when processing data with individuals' spatial information.

Minimizing Spatial Variability of Healthcare Spatial Accessibility-The Case of a Dengue Fever Outbreak.

Outbreaks of infectious diseases or multi-casualty incidents have the potential to generate a large number of patients. It is a challenge for the healthcare system when demand for care suddenly surges. Traditionally, valuation of heath care spatial accessibility was based on static supply and demand information. In this study, we proposed an optimal model with the three-step floating catchment area (3SFCA) to account for the supply to minimize variability in spatial accessibility. We used empirical dengue fever outbreak data in Tainan City, Taiwan in 2015 to demonstrate the dynamic change in spatial accessibility based on the epidemic trend. The x and y coordinates of dengue-infected patients with precision loss were provided publicly by the Tainan City government, and were used as our model's demand. The spatial accessibility of heath care during the dengue outbreak from August to October 2015 was analyzed spatially and temporally by producing accessibility maps, and conducting capacity change analysis. This study also utilized the particle swarm optimization (PSO) model to decrease the spatial variation in accessibility and shortage areas of healthcare resources as the epidemic went on. The proposed method in this study can help decision makers reallocate healthcare resources spatially when the ratios of demand and supply surge too quickly and form clusters in some locations.

Spatial Variation and Resuscitation Process Affecting Survival after Out-of-Hospital Cardiac Arrests (OHCA).

BACKGROUND: Ambulance response times and resuscitation efforts are critical predictors of the survival rate after out-of-hospital cardiac arrests (OHCA). On the other hand, rural-urban differences in the OHCA survival rates are an important public health issue. METHODS: We retrospectively reviewed the January 2011-December 2013 OHCA registry data of Kaohsiung City, Taiwan. With particular focus on geospatial variables, we aimed to unveil risk factors predicting the overall OHCA survival until hospital admission. Spatial analysis, network analysis, and the Kriging method by using geographic information systems were applied to analyze spatial variations and calculate the transport distance. Logistic regression was used to identify the risk factors for OHCA survival. RESULTS: Among the 4,957 patients, the overall OHCA survival to hospital admission was 16.5%. In the multivariate analysis, female sex (adjusted odds ratio:, AOR, 1.24 [1.06-1.45]), events in public areas (AOR: 1.30 [1.05-1.61]), exposure to automated external defibrillator (AED) shock (AOR: 1.70 [1.30-2.23]), use of laryngeal mask airway (LMA) (AOR: 1.35 [1.16-1.58]), non-trauma patients (AOR: 1.41 [1.04-1.90]), ambulance bypassed the closest hospital (AOR: 1.28 [1.07-1.53]), and OHCA within the high population density areas (AOR: 1.89 [1.55-2.32]) were positively associated with improved OHCA survival. By contrast, a prolonged total emergency medical services (EMS) time interval was negatively associated with OHCA survival (AOR: 0.98 [0.96-0.99]). CONCLUSIONS: Resuscitative efforts, such as AED or LMA use, and a short total EMS time interval improved OHCA outcomes in emergency departments. The spatial heterogeneity of emergency medical resources between rural and urban areas might affect survival rate.

(Zn,H)-codoped copper oxide nanoparticles via pulsed laser ablation on Cu-Zn alloy in water.

Nanosized (5 to 10 nm) amorphous and crystalline nanocondensates, i.e., metallic α-phase of Zn-Cu alloy in face-centered cubic structure and (Zn,H)-codoped cuprite (Cu2O) with high-pressure-favored close-packed sublattice, were formed by pulsed laser ablation on bulk Cu65Zn35 in water and characterized by X-ray/electron diffractions and optical spectroscopy. The as-fabricated hybrid nanocondensates are darkish and showed photoluminescence in the whole visible region. Further dwelling of such nanocondensates in water caused progressive formation of a rice-like assembly of (Zn,H)-codoped tenorite (CuO) nanoparticles with (001), (100), and {111} preferred orientations, (111) tilt boundary, yellowish color, and minimum bandgap narrowing down to ca. 2.7 eV for potential photocatalytic applications.