Triggering of cardiovascular hospital admissions by fine particle concentrations in New York state: Before, during, and after implementation of multiple environmental policies and a recession

How community vulnerability factors jointly affect multiple health outcomes after catastrophic storms

BACKGROUND

While previous studies uncovered individual vulnerabilities to health risks during catastrophic storms, few evaluated the population vulnerability which is more important for identifying areas in greatest need of intervention.

OBJECTIVES

We assessed the association between community factors and multiple health outcomes, and developed a community vulnerability index.

METHODS

We retained emergency department visits for several health conditions from the 2005-2014 New York Statewide Planning and Research Cooperative System. We developed distributed lag nonlinear models at each spatial cluster across eight counties in downstate New York to evaluate the health risk associated with Superstorm Sandy (10/28/2012-11/9/2012) compared to the same period in other years, then defined census tracts in clusters with an elevated risk as "risk-elevated communities", and all others as "unelevated". We used machine-learning techniques to regress the risk elevation status against community factors to determine the contribution of each factor on population vulnerability, and developed a community vulnerability index (CVI).

RESULTS

Overall, community factors had positive contributions to increased community vulnerabilities to Sandy-related substance abuse (91.35%), injuries (70.51%), cardiovascular diseases (8.01%), and mental disorders (2.71%) but reversely contributed to respiratory diseases (-34.73%). The contribution of low per capita income (max: 22.08%), the percentage of residents living in group quarters (max: 31.39%), the percentage of areas prone to flooding (max: 38.45%), and the percentage of green coverage (max: 29.73%) tended to be larger than other factors. The CVI based on these factors achieved an accuracy of 0.73-0.90 across outcomes.

CONCLUSIONS

Our findings suggested that substance abuse was the most sensitive disease susceptible to less optimal community indicators, whereas respiratory diseases were higher in communities with better social environment. The percentage of residents in group quarters and areas prone to flooding were among dominant predictors for community vulnerabilities. The CVI based on these factors has an appropriate predictive performance.

Weather effects on hand, foot, and mouth disease at individual level: a case-crossover study

BACKGROUND

Hand, foot, and mouth disease (HFMD) raises an urgent public health issue in the Asia-Pacific region, especially in China. The associations between weather factors and HFMD have been widely studied but with inconsistent results. Moreover, previous studies utilizing ecological design could not rule out the bias of exposure misclassification and unobserved confounders.

METHODS

We used case-crossover analysis to assess the associations of weather factors on HFMD. Individual HFMD cases from 2009 to 2012 in Guangdong were collected and cases located within 10 km of the meteorological monitoring sites were included. Lag effects were examined through the previous 7 days. In addition, we explored the variability by changing the distance within 20 km and 30 km.

RESULTS

We observed associations between HFMD and weather factors, including temperature and relative humidity. An approximately U-shaped relationship was observed for the associations of temperature on HFMD across the same day and the previous 7 days, while an approximately exponential-shaped was seen for relative humidity. Statistically significant increases in rates of HFMD were associated with each 10-unit increases in temperature [Excess rate (ER): 7.7%; 95% Confidence Interval (CI): 3.9, 11.7%] and relative humidity (ER: 1.9%; 95% CI: 0.7, 3.0%) on lag days 0-6, when assessing within 10 km of the monitoring sites. Potential thresholds for temperature (30.0 °C) and relative humidity (70.3%) detected showed associations with HFMD. The associations remained robust for 20 km and 30 km.

CONCLUSIONS

Our study found that temperature and relative humidity are significantly associated with the increased rates of HFMD. Thresholds and lag effects were observed between weather factors and HFMD. Our findings are useful for planning on targeted prevention and control of HFMD.

Changes in triggering of ST-elevation myocardial infarction by particulate air pollution in Monroe County, New York over time: a case-crossover study

BACKGROUND

Previous studies have reported that fine particle (PM_2.5) concentrations triggered ST elevation myocardial infarctions (STEMI). In Rochester, NY, multiple air quality policies and economic changes/influences from 2008 to 2013 led to decreased concentrations of PM_2.5 and its major constituents (SO₄^2-, NO₃^-, elemental and primary organic carbon). This study examined whether the rate of STEMI associated with increased ambient gaseous and PM component concentrations was different AFTER these air quality policies and economic changes (2014-2016), compared to DURING (2008-2013) and BEFORE these polices and changes (2005-2007).

METHODS

Using 921 STEMIs treated at the University of Rochester Medical Center (2005-2016) and a case-crossover design, we examined whether the rate of STEMI associated with increased PM_2.5, ultrafine particles (UFP, < 100 nm), accumulation mode particles (AMP, 100-500 nm), black carbon, SO₂, CO, and O₃ concentrations in the previous 1-72 h was modified by the time period related to these pollutant source changes (BEFORE, DURING, AFTER).

RESULTS

Each interquartile range (3702 particles/cm³) increase in UFP concentration in the previous 1 h was associated with a 12% (95% CI = 3%, 22%) increase in the rate of STEMI. The effect size was larger in the AFTER period (26%) than the DURING (5%) or BEFORE periods (9%). There were similar patterns for black carbon and SO₂.

CONCLUSIONS

An increased rate of STEMI associated with UFP and other pollutant concentrations was higher in the AFTER period compared to the BEFORE and DURING periods. This may be due to changes in PM composition (e.g. higher secondary organic carbon and particle bound reactive oxygen species) following these air quality policies and economic changes.

Changes in the acute response of respiratory diseases to PM2.5 in New York State from 2005 to 2016

Prior studies reported that exposure to increased concentrations of fine particulate matter (PM_2.5) were associated with increased rates of hospitalization and emergency department (ED) visits for asthma and chronic obstructive pulmonary disease (COPD). In this study, rates were examined from 2005 to 2016 using a case-crossover design to ascertain if there have been changes in the rates per unit mass exposure given substantial reductions in PM_2.5 concentration and changes in its composition. PM_2.5 concentrations were reduced through a combination of policies designed to improve air quality and economic drivers, including the 2008 economic recession and shifts in the relative costs of coal and natural gas. The study period was split into three periods reflecting that much of the emissions changes occurred between 2008 and 2013. Thus, the three periods were defined as: BEFORE (2005 to 2007), DURING (2008-2013), and AFTER (2014-2016). In general, the number of hospitalizations and ED visits declined with the decreased concentration of PM_2.5. However, the rate of COPD hospitalizations and asthma ED visits associated with each interquartile range increase in ambient PM_2.5 concentration was larger in the AFTER period than the DURING and BEFORE periods. For example, each 6.8 μg/m³ increase in PM_2.5 on the same day was associated with 0.4% (0.0%, 0.8%), 0.3% (-0.2%, 0.7%), and 2.7% (1.9%, 3.5) increases in the rate of asthma emergency department visits in the BEFORE, DURING, and AFTER periods, respectively, suggesting the same mass concentration of PM_2.5 was more toxic in the AFTER period.

Health benefit of air quality improvement in Guangzhou, China: Results from a long time-series analysis (2006-2016)

Numerous epidemiologic studies on adverse health effects of air pollution have been well documented; however, assessment on health benefits of air quality improvement from air pollution control measures has been limited in developing countries. We assessed the mortality benefits associated with air pollution improvement over 11 years in Guangzhou, China (2006-2016). A time series analysis with Generalized additive Poisson models was used to estimate mortality effects of ozone (O₃) and nitrogen dioxide (NO₂), adjusting for time trend, day of week, public holiday, temperature and relative humidity. We further estimated the changes in mortality burden of O₃ and NO₂, including attributable fraction (AF, in %) and attributable mortality (AM, in number of death) during study period. We lastly estimated mortality effects during the 2010 Asian Games (November 12 to December 18, 2010) compared to a baseline period consisting of 4-week before and 4-week after the game. During the study period, average annual concentrations of NO₂ decreased from 42.3 μg/m³ in 2006 to 33.8 μg/m³ in 2016; while O₃ levels remained stable over time. We observed significant increases in mortality of O₃ and NO₂, with approximately linear exposure-response relationships. In specific, each increase of 10 μg/m³ in O₃ and NO₂ at 2 prior days was associated with increases of 0.60% (95% confidence interval (CI): 0.47, 0.74) and 1.89% (95%CI: 1.49, 2.29) in total mortality, respectively. We further estimated that AF on total mortality attributed to NO₂ decreased from 1.38% (95%CI: 1.09, 1.68) in 2006-2010 to 0.43% (95%CI: 0.34, 0.52) in 2011-2016, corresponding to AM on total mortality of 2496 deaths (95%CI: 1964, 3033) to 1073 deaths (95%CI: 846, 1301). During the 2010 Asian Games, we observed decrease in total mortality of 9.3% (95%CI: -15.0, -3.2) in comparison with that observed in the baseline period. Similar mortality benefits in cardiovascular diseases were also observed. Our results showed reduced mortality burden from air pollution improvement in Guangzhou in recent years, which provide strong rationale for continuing to reduce air pollution through comprehensive and rigorous air quality management in the area.

Triggering of cardiovascular hospital admissions by source specific fine particle concentrations in urban centers of New York State

BACKGROUND

Previous work reported increased rates of acute cardiovascular hospitalizations associated with increased PM2.5 concentrations in the previous few days across urban centers in New York State from 2005 to 2016. These relative rates were higher after air quality policies and economic changes resulted in decreased PM2.5 concentrations and changes in PM composition (e.g. increased secondary organic carbon), compared to before and during these changes. Changes in PM composition and sources may explain this difference.

OBJECTIVES

To estimate the rate of acute cardiovascular hospitalizations associated with increases in source specific PM2.5 concentrations.

METHODS

Using source apportioned PM2.5 concentrations at the same NYS urban sites, a time-stratified case-crossover design, and conditional logistic regression models adjusting for ambient temperature and relative humidity, we estimated the rate of these acute cardiovascular hospitalizations associated with increases in mean source specific PM2.5 concentrations in the previous 1, 4, and 7 days.

RESULTS

Interquartile range (IQR) increases in spark-ignition emissions (GAS) concentrations were associated with increased excess rates of cardiac arrhythmia hospitalizations (2.3%; 95% CI = 0.4%, 4.2%; IQR = 2.56 μg/m3) and ischemic stroke hospitalizations (3.7%; 95% CI = 1.1%, 6.4%; 2. 73 μg/m3) over the next day. IQR increases in diesel (DIE) concentrations were associated with increased rates of congestive heart failure hospitalizations (0.7%; 95% CI = 0.2% 1.3%; 0.51 μg/m3) and ischemic heart disease hospitalizations (0.8%; 95% CI = 0.3%, 1.3%; 0.60 μg/m3) over the next day, as hypothesized. However, secondary sulfate PM2.5 (SS) was not. Increased acute cardiovascular hospitalization rates were also associated with IQR increases in concentrations of road dust (RD), residual oil (RO), and secondary nitrate (SN) over the previous 1, 4, and 7 days, but not other sources.

CONCLUSIONS

These findings suggest a role of several sources of PM2.5 in New York State (i.e. traffic emissions, non-traffic emissions such as brake and tire wear, residual oil, and nitrate that may also reflect traffic emissions) in the triggering of acute cardiovascular events.

Spatial-temporal variations of summertime ozone concentrations across a metropolitan area using a network of low-cost monitors to develop 24 hourly land-use regression models

Ten relatively-low-cost ozone monitors (Aeroqual Series 500 with OZL ozone sensor) were deployed to assess the spatial and temporal variability of ambient ozone concentrations across residential areas in the Monroe County, New York from June to October 2017. The monitors were calibrated in the laboratory and then deployed to a local air quality monitoring site where they were compared to the federal equivalent method values. These correlations were used to correct the measured ozone concentrations. The values were also used to develop hourly land use regression models (LUR) based on the deletion/substitution/addition (D/S/A) algorithm that can be used to predict the spatial and temporal concentrations of ozone at any hour of a summertime day and given location in Monroe County. Adjusted R2 values were high (average 0.83) with the highest adjusted R2 for the model between 8 and 9 AM (i.e. 1-2 h after the peak of primary emissions during the morning rush hours). Spatial predictors with the highest positive effects on ozone estimates were high intensity developed areas, low and medium intensity developed areas, forests + shrubs, average elevation, Interstate + highways, and the annual average vehicular daily traffic counts. These predictors are associated with potential emissions of anthropogenic and biogenic precursors. Maps developed from the models exhibited reasonable spatial and temporal patterns, with low ozone concentrations overnight and the highest concentrations between 11 AM and 5 PM. The adjusted R2 between the model predictions and the measured values varied between 0.79 and 0.87 (mean = 0.83). The combined use of the network of low-cost monitors and LUR modeling provide useful estimates of intraurban ozone variability and exposure estimates that will be used in future epidemiological studies.

The Association between Respiratory Infection and Air Pollution in the Setting of Air Quality Policy and Economic Change

RATIONALE

Fine particulate matter air pollution of 2.5 μm or less in diameter (PM2.5) has been associated with an increased risk of respiratory disease, but assessments of specific respiratory infections in adults are lacking.

OBJECTIVES

To estimate the rate of respiratory infection healthcare encounters in adults associated with acute increases in PM2.5 concentrations.

METHODS

Using case-crossover methods, we studied 498,118 adult New York State residents with a primary diagnosis of influenza, bacterial pneumonia, or culture-negative pneumonia upon hospitalization or emergency department (ED) visit (2005-2016). We estimated the relative rate of healthcare encounters associated with increases in PM2.5 in the previous 1-7 days and explored differences before (2005-2007), during (2008-2013), and after (2014-2016) implementation of air quality policies and economic changes.

RESULTS

Interquartile range increases in PM2.5 over the previous 7 days were associated with increased excess rates (ERs) of culture-negative pneumonia hospitalizations (2.5%; 95% confidence interval [CI], 1.7-3.2%) and ED visits (2.5%; 95% CI, 1.4-3.6%), and increased ERs of influenza ED visits (3.9%; 95% CI, 2.1-5.6%). Bacterial pneumonia hospitalizations, but not ED visits, were associated with increases in PM2.5 and, though imprecise, were of a similar magnitude to culture-negative pneumonia (Lag Day 6 ER, 2.3%; 95% CI, 0.3-4.3). Increased relative rates of influenza ED visits and culture-negative pneumonia hospitalizations were generally larger in the "after" period (P < 0.025 for both outcomes), compared with the "during" period, despite reductions in overall PM2.5 concentrations.

CONCLUSIONS

Increased rates of culture-negative pneumonia and influenza were associated with increased PM2.5 concentrations during the previous week, which persisted despite reductions in PM2.5 from air quality policies and economic changes. Though unexplained, this temporal variation may reflect altered toxicity of different PM2.5 mixtures or increased pathogen virulence.

Space-time trends of PM2.5 constituents in the conterminous United States estimated by a machine learning approach, 2005-2015

Particulate matter with aerodynamic diameter less than 2.5 μm (PM_2.5) is a complex mixture of chemical constituents emitted from various emission sources or through secondary reactions/processes; however, PM_2.5 is regulated mostly based on its total mass concentration. Studies to identify the impacts on climate change, visibility degradation and public health of different PM_2.5 constituents are hindered by limited ground measurements of PM_2.5 constituents. In this study, national models were developed based on random forest algorithm, one of machine learning methods that is of high predictive capacity and able to provide interpretable results, to predict concentrations of PM_2.5 sulfate, nitrate, organic carbon (OC) and elemental carbon (EC) across the conterminous United States from 2005 to 2015 at the daily level. The random forest models achieved high out-of-bag (OOB) R² values at the daily level, and the mean OOB R² values were 0.86, 0.82, 0.71 and 0.75 for sulfate, nitrate, OC and EC, respectively, over 2005-2015. The long-term temporal trends of PM_2.5 sulfate, nitrate, OC and EC predictions agreed well with their corresponding ground measurements. The annual mean of predicted PM_2.5 sulfate and EC levels across the conterminous United States decreased substantially from 2005 to 2015; while concentrations of predicted PM_2.5 nitrate and OC decreased and fluctuated during the study period. The annual prediction maps captured the characterized spatial patterns of the PM_2.5 constituents. The distributions of annual mean concentrations of sulfate and nitrate were generally regional in the extent that sulfate decreased from east to west smoothly with enhancement in California and nitrate had higher concentration in Midwest, Metro New York area, and California. OC and EC had regional high concentrations in the Southeast and Northwest as well as localized high levels around urban centers. The spatial patterns of PM_2.5 constituents were consistent with the distributions of their emission sources and secondary processes and transportation. Hence, the national models developed in this study could provide supplementary evaluations of spatio-temporal distributions of PM_2.5 constituents with full time-space coverages in the conterminous United States, which could be beneficial to assess the impacts of PM_2.5 constituents on radiation budgets and visibility degradation, and support exposure assessment for regional to national health studies at county or city levels to understand the acute and chronic toxicity and health impacts of PM_2.5 constituents, and consequently provide scientific evidence for making targeted and effective regulations of PM_2.5 pollution.