Ambient air quality and spatio-temporal patterns of cardiovascular emergency department visits

Geospatial analysis of short-term exposure to air pollution and risk of cardiovascular diseases and mortality-A systematic review

The cardiovascular risk associated with short-term ambient air pollution exposure is well-documented. However, recent advancements in geospatial techniques have provided new insights into this risk. This systematic review focuses on short-term exposure studies that applied advanced geospatial pollution modelling to estimate cardiovascular disease (CVD) risk and accounted for additional unconventional neighbourhood-level confounders to analyse their modifier effect on the risk. Four databases were investigated to select publications between 2018 and 2023 that met the inclusion criteria of studying the effect of particulate matter (PM2.5 and PM10), SO2, NOx, CO, and O3 on CVD mortality or morbidity, utilizing pollution modelling techniques, and considering spatial and temporal confounders. Out of 3277 publications, 285 were identified for full-text review, of which 34 satisfied the inclusion criteria for qualitative analysis, and 12 of them were chosen for additional quantitative analysis. Quality assessment revealed that 28 out of 34 included articles scored 4 or above, indicating high quality. In 30 studies, advanced pollution modelling techniques were used, while in 4 only simpler methods were applied. The most pertinent confounders identified were socio-demographic variables (e.g., socio-economic status, population percentage by race or ethnicity) and neighbourhood-level built environment variables (e.g., urban/rural area, percentage of green space, proximity to healthcare), which exhibited varying modifier effects depending on the context. In the quantitative analysis, only PM 2.5 showed a significant positive association to all-cause CVD-related hospitalisation. Other pollutants did not show any significant effect, likely due to the high inter-study heterogeneity and a limited number of cases. The application of advanced geospatial measurement and modelling of air pollution exposure, as well as its risk, is increasing. This review underscores the importance of accounting for unconventional neighbourhood-level confounders to enhance the understanding of the CVD risk associated with short-term pollution exposure.

The Effect of Sustained Poor Air Quality on EMS Call Volume and Characteristics: A Time-Stratified Case-Crossover Study

OBJECTIVES

As wildfires and air pollution become more common across the United States, it is increasingly important to understand the burden they place on public health. Previous studies have noted relationships between air quality and use of Emergency Medical Services (EMS), but until now, these studies have focused on day-to-day air quality. The goal of this study is to investigate the effect of sustained periods of poor air quality on EMS call characteristics and volume.

METHODS

Using a time-stratified case-crossover design, the effect of exposure to periods of poor air quality on number and type of EMS calls in California, USA from 2014-2019 was observed. Poor air quality periods greater than three days were identified at the United States Environmental Protection Agency's (EPA's) Air Quality Index (AQI) levels of Unhealthy for Sensitive Groups (AQI 100) and Unhealthy (AQI 150). Periods less than three days apart were combined. Each poor air quality period was matched with two one-week controls, the first being the closest preceding week that did not intersect a different case. The second control was the closest week at least three days after the case and not intersecting with a different case. Due to seasonal variation in EMS usage, from the initial cases, cases were used only if it was possible to identify controls within 28 days of the case. A conditional Poisson regression calculated risk ratios for EMS call volume.

RESULTS

Comparing the case periods to the controls, significant increases were found at AQI >100 for total number of calls, and the primary impressions categories of emotional state or behavior, level of consciousness, no patient complaint, other, respiratory, and abdominal. At an AQI >150, significance was found for the primary impressions categories of other, pain, respiratory, and digestive.

CONCLUSION

These data demonstrate increased EMS calls during sustained poor air quality, and that several EMS primary impression categories are disproportionately affected. This study is limited by the imprecision of the primary impression's classification provided by the EMS clinician responding to the EMS call. More research is needed to understand the effects of periods of poor air quality on the EMS system for more efficient deployment of resources.

Exposure to urban green space may both promote and harm mental health in socially vulnerable neighborhoods: A neighborhood-scale analysis in New York City

BACKGROUND

There is growing evidence that exposure to green space can impact mental health, but these effects may be context dependent. We hypothesized that associations between residential green space and mental health can be modified by social vulnerability.

METHOD

We conducted an ecological cross-sectional analysis to evaluate the effects of green space exposure on mental disorder related emergency room (ER) visits in New York City at the level of census tract. To objectively represent green space exposure at the neighborhood scale, we calculated three green space exposure metrics, namely proximity to the nearest park, percentage of green space, and visibility of greenness. Using Bayesian hierarchical spatial Poisson regression models, we evaluated neighborhood social vulnerability as a potential modifier of greenness-mental disorder associations, while accounting for the spatially correlated structures.

RESULTS

We found significant associations between green space exposure (involving both proximity and visibility) and total ER visits for mental disorders in neighborhoods with high social vulnerability, but no significant associations in neighborhoods with low social vulnerability. We also identified specific neighborhoods with particularly high ER utilization for mental disorders.

CONCLUSIONS

Our findings suggest that exposure to green space is associated with ER visits for mental disorders, but that neighborhood social vulnerability can modify this association. Future research is needed to confirm our finding with longitudinal designs at the level of individuals.

The short-term association of ambient fine particulate air pollution with hypertension clinic visits: A multi-community study in Guangzhou, China

BACKGROUND

The association of ambient fine particulate pollution with daily outpatient clinic visits (OCV) for hypertension in China remains to be investigated.

OBJECTIVES

This study aimed to examine short-term impacts of exposure to fine particulate matter of aerodynamic diameter < 2.5μm (PM_2.5) on daily OCV for hypertension, using a large-scale multi-center community database in Guangzhou, one of the most densely-populated cities in Southern China.

METHODS

We collected a total of 28,548 individual records of OCV from 22 community healthcare facilities in Guangzhou from January 1st to May 7th 2020. Hourly data on air pollutants and daily information on meteorological factors were obtained. According to the World Health Organization air-quality guidelines, daily excessive concentration hours (DECH) was calculated. PM_2.5 daily mean, hourly-peak concentration and DECH were used as the exposure variables. Based on a case-time-control design, the Cox regression model was applied to evaluate the short-term relative risks (RR) of daily OCV for hypertension. Sensitivity analyses were conducted, with nitrogen dioxide, sulfur dioxide, carbon monoxide, and ozone being adjusted.

RESULTS

Daily mean and hourly-peak of PM_2.5 were significantly associated with daily OCV for hypertension, while weaker associations were observed for DECH. The estimated RRs at lag day 0 were 1.039 (95% confidence interval [CI]: 1.037, 1.040), 1.851 (95%CI: 1.814, 1.888), and 1.287 (95%CI: 1.276, 1.298), respectively, in association with a 1-unit increase in DECH, daily mean, and hourly-peak concentration of PM_2.5. For the lagged effect, lag₄ models estimated the greatest RRs for PM_2.5 DECH and hourly-peak, whereas a lag₂ model produced the highest for PM_2.5 daily mean.

DISCUSSION

This study consolidates the evidence for a positive correlation between ambient PM_2.5 exposure and risks of hypertensive OCV. It also provides profound insight regarding planning for health services needs and establishing early environmental responses to the worsening air pollution in the communities.

A methodological framework for improving air quality monitoring network layout. Applications to environment management

This work aims to provide a methodology framework which allows to improve the performance and efficiency of an air quality monitoring network (AQMN). It requires to be constituted by a minimum and reliable number of measurement sites. Nevertheless, the AQMN efficiency should be assessed over time, as a consequence of the possible emergence of new emission sources of air pollutants, which could lead to variations on their spatial distribution within the target area. PM₁₀ particles data monitored by the Community of Madrid's (Spain) AQMN between 2008 and 2017 were used to develop a methodology to optimize the AQMN performance. The annual spatial distribution of average PM₁₀ levels over the studied period monitored by all current stations vs those more representative was provided by a geographic information system (GIS), and the percentage of similarity between both postulates was quantified using simple linear regression (> 95%). As one innovative tool of this study, the practical application of the proposed methodology was validated using PM₁₀ particles data measured by AQMN during 2007 and 2018, reaching a similitude degree higher than 95%. The influence of temporal variation on the proposed methodological framework was around 20%. The proposed methodology sets criteria for identifying non-redundant stations within AQMN, it is also able to appropriately assess the representativeness of fixed monitoring sites within an AQMN and it complements the guidelines set by European legislation on air pollutants monitoring at fixed stations, which could help to tackle efforts to improve the air quality management.

The association between socioeconomic status and mobility reductions in the early stage of England's COVID-19 epidemic

This study uses mobile phone data to examine how socioeconomic status was associated with the extent of mobility reduction during the spring 2020 lockdown in England in a manner that considers both potentially confounding effects and spatial dependency and heterogeneity. It shows that socioeconomic status as approximated through income and occupation was strongly correlated with the extent of mobility reduction. It also demonstrates that the specific nature of the association of socioeconomic status with mobility reduction varied markedly across England. Finally, the analysis suggests that the spatial differentiation in the ability to restrict everyday mobility in response to a national lockdown is an important topic for future research.

Vulnerable road-user deaths in Brazil: a Bayesian hierarchical model for spatial-temporal analysis

Reducing the road traffic injuries burden is relevant to many sustainable development goals (SDG), in particular SDG3 - to establish good health and well-being. To describe the spatial-temporal trends and identify hotspot regions for fatal road traffic injuries, a Bayesian hierarchical Poisson model was used to analyze data on vulnerable road users (bicyclist, motorcyclist and pedestrians) in Brazil from 1999 to 2016. During the study period, mortality rates for bicyclists remained almost unchanged (0.6 per 100,000 people) but rose dramatically for motorcyclists (from 1.0 in 1999 to 6.0 per 100,000 people in 2016) and decreased for pedestrians (from 6.3 to 3.0 per 100,000 people). Spatial analyses accounting for socio-economic factors showed that the central and northeastern microregions of Brazil are hotspot areas for fatal injuries among motorcyclists while the southern areas are for pedestrians.

Short-term impacts of ambient fine particulate matter on emergency department visits: Comparative analysis of three exposure metrics

BACKGROUND

Research argued that daily excessive concentration hours (DECH) could be more informative through accounting for within-day variations, when assessing population-level exposure to ambient fine particle (PM_2.5). However, few studies have comparatively investigated PM_2.5-associated risks using DECH and two common metrics of daily mean and hourly peak concentration.

METHODS

We collected daily records of all-cause emergency department visits (EDVs) and hourly data on air pollutants and meteorological factors from Shenzhen, China, 2015-2018. According to guidelines proposed by the World Health Organization, DECH was calculated by summing up daily concentrations exceeding 25 μg/m³. Based on time-stratified case-crossover design, we adopted conditional logistic regression models to assess short-term attributable risks of EDVs associated with PM_2.5 using three exposure metrics.

RESULTS

DECH and daily average of PM_2.5 strongly elevated risks of EDVs, while less evident associations were observed using hourly peak metric. Estimated excess relative risks at lag 0 day were 0.56% (95% confidence interval [CI]: 0.21 to 0.91), 0.69% (95% CI: 0.25 to 1.13) and 0.37% (95% CI: 0.02 to 0.76), respectively, associated with an interquartile range increase in DECH (420.2 μg/m³), 24-h average (24.9 μg/m³) and hourly peak concentration (38 μg/m³). More emergency visits could be attributed to DECH than daily mean PM_2.5, with attributable fractions of 2.02% (95% CI: 1.42 to 2.61) and 1.09% (95% CI: 0.69 to 1.49), respectively.

CONCLUSIONS

This study added evidence for increased risk of EDVs associated with exposure to ambient PM_2.5. DECH was a potential alternative exposure metric for PM_2.5 assessment, which may have implications for future revision of air quality standards.

Low Levels of Air Pollution and Health: Effect Estimates, Methodological Challenges, and Future Directions

PURPOSE OF REVIEW

Fine particle (PM2.5) levels have been decreasing in the USA over the past decades. Our goal was to assess the current literature to characterize the association between PM2.5 and adverse health at low exposure levels.

RECENT FINDINGS

We reviewed 26 papers that examined the association between short- and long-term exposure to PM2.5 and cardio-respiratory morbidity and mortality. There is evidence suggesting that these associations are stronger at lower levels. However, there are certain methodological and interpretational limitations specific to studies of low PM2.5 levels, and further methodological development is warranted. There is strong agreement across studies that air pollution effects on adverse health are still observable at low concentrations, even well below current US standards. These findings suggest that US standards need to be reevaluated, given that further improving air quality has the potential of benefiting public health.