Daily Emergency Department Visits Research Articles

Development of a Health-Based Index to Identify the Association between Air Pollution and Health Effects in Mexico City

Health risks from air pollution continue to be a major concern for residents in Mexico City. These health burdens could be partially alleviated through individual avoidance behavior if accurate information regarding the daily health risks of multiple pollutants became available. A split sample approach was used in this study to create and validate a multi-pollutant, health-based air quality index. Poisson generalized linear models were used to assess the impacts of ambient air pollution (i.e., fine particulate matter (PM2.5), nitrogen dioxide (NO2), and ground-level ozone (O3)) on a total of 610,982 daily emergency department (ED) visits for respiratory disease obtained from 40 facilities in the metropolitan area of Mexico City from 2010 to 2015. Increased risk of respiratory ED visits was observed for interquartile increases in the 4-day average concentrations of PM2.5 (Risk Ratio (RR) 1.03, 95% CI 1.01–1.04), O3 (RR 1.03, 95% CI 1.01–1.05), and to a lesser extent NO2 (RR 1.01, 95% CI 0.99–1.02). An additive, multi-pollutant index was created using coefficients for these three pollutants. Positive associations of index values with daily respiratory ED visits was observed among children (ages 2–17) and adults (ages 18+). The use of previously unavailable daily health records enabled an assessment of short-term ambient air pollution concentrations on respiratory morbidity in Mexico City and the creation of a health-based air quality index, which is now currently in use in Mexico City.

Air pollution and emergency department visits for urticaria

Abstract Introduction. This study investigates associations between air pollution and emergency department (ED) visits for urticaria in Toronto, Canada. Aim. To verify the hypothesis that urticaria are related to air pollution. Material and methods. The National Ambulatory Care Reporting System database is used to draw the daily ED visits. The L50 section of the International Classification of Disease 10th Revision is applied to extract ED visits whose primary causes was urticaria-related skin condition. Statistical models (condition Poisson regression) using daily counts of ED visits are constructed for urticaria (health response) with ambient air pollution concentrations and weather factors as independent variable. Two air quality health indexes and six ambient air pollutants: fine particulate matter PM2.5, O3, CO, NO2, SO2, and maximum 8-hour average ozone are considered as an exposure. Results. A total of 176 statistically significant (P-Value <0.05) positive correlations were identified over the 15 day lag period (0-14 days). For daily average of ambient ozone, 74 positive correlations were observed with the following relative risks (RR) for a one interquartile range (IQR=12.8 ppb) increase: RR=1.361 (95% confidence interval: 1.302, 1.404), 1.359 (1.299, 1.401), 1.351 (1.281, 1.404) in the warm season (April-September), lag 0, and RR=1.019 (1.013, 1.025), 1.023 (1.016, 1.030), 1.014 (1.007, 1.021), lag 1, in the cold period (October-March), for all, females, and males, respectively. 10, 45 and 45 positive correlations were also obtained for sulfur dioxide, fine particulate matter, and daily maximum 8-hour average ozone concentrations, respectively. Conclusions. The results indicate that urban ambient air pollution could influence the numbers of ED visits for urticaria. Ambient ozone was determined as the main environmental factor contributing to these associations.

Particulate matter (PM10) as a newly identified environmental risk factor for acute gout flares: A time-series study.

This study aimed to investigate the effect of short-term exposure to ambient particulate matter less than 10μm in diameter (PM10) on occurrence of acute gout flares in the general population and identify susceptible groups accordingly. The data of emergency department (ED) cases with acute gout flare in Incheon city, Korea between January 1st 2008 and December 31st 2015 were collected from the National Health Insurance Service claims data. The levels of PM10 and meterological measurements were provided by the Ministry of Environment and the National Meterological Office, respectively. To estimate the risk of daily ED visits due to acute gout flare, these time-series data set were analyzed using generalized additive models with Poisson distribution, including daily average PM10 level, temperature, relative humidity, day of the week, national holiday, season, and date. The risk of daily ED visits for acute gout flares per interquartile range increment of the average daily PM10 levels significantly increased in the cumulative lag 0-7 model (relative risk, 1.018; 95% confidence interval, 1.008-1.027, P<0.001). In particular, men aged≥40 years and those with a history of diabetes mellitus or gout were significantly at a high risk of acute gout flares by subgroup analysis. Our time-series study demonstrated a modest, but significant effect of short-term exposure to PM10 on ED visits for acute gout flares. Ambient PM10 may be a newly identified environmental risk factor for acute gout flares.

Increased Firearm Injury During the COVID-19 Pandemic: A Hidden Urban Burden

BackgroundPublic health measures were instituted to reduce COVID-19 spread. A decrease in total emergency department volume followed, but the impact on injury is unknown. With lockdown and social distancing potentially increasing domicile discord, we hypothesized that intentional injury increased during COVID-19, driven primarily by an increase in penetrating trauma.Study DesignA retrospective review of acute adult patient care in an urban Level I trauma center assessed injury patterns. Presenting patient characteristics and diagnoses from 6 weeks pre to 10 weeks post statewide stay-at-home orders (March 16, 2020) were compared, as well as with 2015-2019. Subsets were defined by intentionality (intentional vs nonintentional) and mechanism of injury (blunt vs penetrating). Fisher exact and Wilcoxon tests were used to compare proportions and means.ResultsThere were 357 trauma patients that presented pre stay-at-home order and 480 that presented post stay-at-home order. Pre and post groups demonstrated differences in sex (35.6% vs 27.9% female; p = 0.02), age (47.4 ± 22.1 years vs 42 ± 20.3 years; p = 0.009), and race (1.4% vs 2.3% Asian; 63.3% vs 68.3% Black; 30.5% vs 22.3% White; and 4.8% vs 7.1% other; p = 0.03). Post stay-at-home order mechanism of injury revealed more intentional injury (p = 0.0008). Decreases in nonintentional trauma after adoption of social isolation paralleled declines in daily emergency department visits. Compared with earlier years, 2020 demonstrated a significantly greater proportion of intentional violent injury during the peripandemic months, especially from firearms.ConclusionsUnprecedented social isolation policies to address COVID-19 were associated with increased intentional injury, especially gun violence. Meanwhile, emergency department and nonintentional trauma visits decreased. Pandemic-related public health measures should embrace intentional injury prevention and management strategies.

Examining Heat-Related Emergency Department Visits in North Carolina, 2009-2017

Background: Climactic changes in heat are expected to affect patterns of heat-related illness (HRI) in North Carolina. In order to understand patterns in HRI over time, we assessed the frequency and distribution of HRI emergency department (ED) visits across North Carolina during 2009-2017. Methods: Using a previously validated ICD-9/ICD-10 and chief complaint-based case definition, we identified visits from the North Carolina Disease Event Tracking and Epidemiologic Collection Tool (NC DETECT) from January 1, 2009 to December 31, 2017. The analysis used a generalized linear model for time series of counts with R package tscount. A poisson model was used with response variable as number of daily HRI ED visits. We assessed whether number of peaks (i.e., aberrations) increased annually from 2009 to 2017. Finally, to assess whether length of the heat season increased annually 2009 to 2017, the duration between date of the first peak and last peak were compared annually. Results: Most emergency department visits occurred during summer months. Monthly distributions for each year were similar. During 2010 and 2015, the monthly highs occurred slightly earlier than other years. In the Poisson model, controlling for maximum monthly temperature, the coefficient for year was positive with a significant p-value, suggesting an expected increase in the number of HRI ED visits over time. No significant distribution in the number of peaks by year or duration of heat season was observed. Conclusions: The model demonstrated a significant increase in the number of HRI ED visits over time. The results of this study reinforce the strong relationship between increasing temperatures and HRI, and suggests that as temperatures continue to increase, the incidence of HRI will likewise increase.

Summation of concentration-response shapes by lagged exposureSummation of concentration-response shapes by lagged exposure

Aim: Air pollutants may negatively affect a large spectrum of human health conditions. Among the statistical methods used to assess the impact of concentrations of ambient air pollutants on health are the time-series and case-crossover methods. Traditionally, both methods estimate risk in linear forms. Recent studies indicate that non-linear representations are more adequate and accurate. Methods: We investigate the association between daily emergency department (ED) visits for all respiratory conditions and daily concentration of ambient ozone. We retrieve ED data for Edmonton, Canada, for the period April 1992 - March, 2002, (3,652 days) using the ICD-9 codes 460-519. The case-crossover technique is realized as a conditional Poisson regression. We test lags from 0 to 8 days and determine 9 concentration-response (c-r) shapes. Results: 292,285 ED visits were identified and used in the study. Lagged exposures result in positive and statistically significant associations between ozone concentration and ED visits for respiratory conditions. The concentration-response shapes change according to the lags considered. Various forms of c-r shapes are observed, such as an almost linear shape, an S-profile, and others. The amalgamated by used lags c-r function provides a good tool to summarize the risk relating to the concentration of the considered air pollutant. In general, the results are non-linear parametric risk functions of the concentrations. Conclusion: The estimated functions allow the identification of concentrations with various intensities of impact on health. In some cases, these functions indicate a potential threshold concentration.

Near real-time modeling of daily asthma emergency department visits syndrome as a function of air pollution, weather, and other environmental risk factors in New York City, 2010-2019

Background: Research has shown that asthma morbidity is associated with multiple temporally-varying environmental risk factors including air pollution, weather, pollen, and viral infections. Predicting its temporal variation near real-time is useful for situational awareness as the relative importance of these risk factors changes across seasons.Methods: We developed a regression model to predict daily asthma emergency department (ED) visits based on chief complaint text and diagnosis code (i.e., syndrome) available from previous day since 2010 at the New York City Health Department. The 2010-2018 data were used to develop a quasi-Poisson model for a 121-day moving time window for each day of 2019 for ages 5-17, with predictors including: day-of-year; day-of-week; temperature; citywide average fine particles (PM2.5) and ozone (warm season only); ED visits syndromes for allergy (proxy for spring pollen impact) and flu; school-opening date (proxy for fall rhinovirus infections); and holidays, considering non-linear distributed lags when multi-day impacts were observed. Point estimates and prediction intervals are produced along with the observed values in a dashboard to facilitate daily assessment.Results: The model goodness of fit varied across seasons, with the best fit occurring in the fall season (e.g., % deviance explained up to 85%) and the worst in the spring (e.g., ~ 40%). Daily absolute percent errors, with a median of 15% for the 2019 prediction period, were also higher in the spring, because the peak tree pollen impacts were not fully captured. PM2.5 associations were mostly limited to cold months, with diminished predictive power during the warm period when ozone was a better predictor.Conclusion: The dynamic near real-time prediction model for asthma ED syndrome for young age group developed in this study provides a useful tool for evaluating the impacts of current events. Further model improvement will consider spatially-resolved predictors (e.g., satellite-derived air pollution data).

The Impact of Heat Waves on Emergency Department Visits in Roanoke, Virginia

The Impact of Heat Waves on Emergency Department Visits in Roanoke, Virginia

The air quality health index and emergency department visits for injury

Abstract Introduction. The purpose of this study was to investigate the associations of ambient air quality with emergency department (ED) visits for injury. Aim. To explore correlations between ED visits for injury and ambient air pollution. Materials and methods. Considered health outcomes are ED visits for injury (ICD-9 codes: 800-999) in Edmonton, Canada, for the period from April 1998 to March 2002 (1,444 days). Air pollution concentration in the ambient air is represented as a daily maximum of the Air Quality Health Index (AQHI). The AQHI value encapsulates levels of three urban ambient air pollutants (ozone, nitrogen dioxide and fine particulate matter), weighted by constant risk coefficients. A time-stratified casecrossover design, using conditional logistic regression and conditional Poisson regression, was realized to assess the associations. The risk, reported as odds ratio and relative risk, was estimated using log-linear models and parametric non-linear concentrationresponse functions. Results. The strongest effects were observed for young male patients in the cold season (October-March). Lagged exposures were found to have positive statistically significant associations. Discussion. The study results indicate that air quality was associated with increased risk of daily ED visits for injury. This study determined concentration-response functions which allow one to assess the effects for various levels of the AQHI.

Joint effect of multiple air pollutants on daily emergency department visits in Chengdu, China

Existing studies have typically investigated only the association between single pollutants and health outcomes. However, in the real world, people are exposed to multiple air pollutants simultaneously. The effect of air pollutants on emergency department (ED) visits has not been previously studied in the Sichuan Basin, which is one of the most polluted areas. We collected nonaccidental, respiratory and cardiovascular daily ED visits and daily concentrations of PM2.5, PMc, CO, SO2, NO2 and O3 in Chengdu, China, from 2014 to 2016. A weighted variable for the combination of multiple air pollutants was constructed to assess the joint adverse health effects. Each air pollutant was assigned a health-related weight, which indicated the pollutant’s relative contribution to the joint effect. The effects on specific subpopulations (males and females; 15–65 years old and >65 years old) were also examined. With an increase of 10 μg/m3 of the combined multiple air pollutants, the daily ED visits for nonaccidental, respiratory and cardiovascular causes increased by 0.96% (95% CI: 0.51%–1.39%), 1.19% (95% CI: 0.53%, 1.85%) and 4.36% (95% CI: 1.06%, 7.76%) at lag 1, respectively. Males presented more pronounced effects, except for cardiovascular disease, than females. Elderly individuals were found to be more sensitive than young individuals. For nonaccidental and respiratory diseases, the contributions of particulate matter (PM) were dominant among the air pollutants, whereas cardiovascular disease was mainly affected by gaseous air pollutants. The combination of multiple air pollutants was significantly associated with ED visits in the Sichuan Basin, China. The joint effect of the combination of multiple air pollutants was highest for cardiovascular disease at lag 1. The relative contributions of individual pollutants varied by disease and subpopulation. These findings suggest that under different pollution scenarios, preventive strategies should target those with different diseases and different subpopulations.

144 Time Series Analysis and Forecasting Daily Emergency Department Visits Utilizing Facebook's Prophet Method

Emergency department (ED) boarding and crowding have significant implications for patient care. The capability of being able to model ED volumes to optimize staff and hospital resource allocation may lead to significant positive operational and patient care outcomes. The number of daily visits in 24 hours can often be challenging to predict, but over the last few decades, several studies have attempted to develop and deploy several forecasting models including exponential smoothing, and autoregressive integrated moving average models with varying levels of success. The analysis and identification of patterns and trends in large scale data are vital in other industries, such as social media, where several innovative methodologies have been employed to assess pattern recognition and trends. Facebook® uses a novel Bayesian forecasting model known as Prophet to decompose time series factors identifying patterns. This study leveraged this innovative methodology to identify patterns of ED daily visits with the hope of predicting future number of daily ED visits. Data were collected from a single urban community-based hospital in the New York Metropolitan area from January 2016 to December 2018. A time series analysis and decomposition were performed on daily visits using Prophet, which is an open source forecasting time series model based on an additive model where non-linear trends are fit with yearly, weekly, and daily seasonality as well as holiday effects. The model trends were revealed and used for predicting daily ED visits for the first two weeks of January 2019. The Facebook Prophet method identified two distinct seasonal patterns. The resulting dataframe contained fourteen days of forecasted data with corresponding 95% confidence intervals. The model appears to provide insight into the general trend and seasonality in the time series data. Not surprisingly, the busiest day of the week is a Monday and the busiest time of the year is during the late winter season, such as February and March. A quick comparison with the actual visits from the first two weeks in 2019 shows that its predictions are relatively reasonable. The result of our study suggests that the Facebook Prophet model can be used to provide reasonably accurate forecasts and predictions in daily ED visits. However, the limitation was that the data was from a single site with only three years of data. Building on this single site study, future multi-site prospective longitudinal work can assess if such a methodological approach can provide forecasting information useful for departmental administration as well as validation in other hospital sites.View Large Image Figure ViewerDownload Hi-res image Download (PPT)

Trends in emergency department visits in Lubbock from 2011-2017

To determine trends in daily emergency department (ED) visits, a preliminary retrospective study was done to analyze the relationship of long-term trends, day of week, and month of year to ED volume at University Medical Center in Lubbock, TX. Local data were collected from January 1, 2011, through December 31, 2017. An increase in ED visits from 2011 to 2014 was followed by a decrease in ED visits from 2014 to 2017. The best fit third order polynomial was “ ” with y=number of ED visits and x=cumulative day. The busiest day of the week was Monday with an average of 235.6 visits per day. Throughout the week, ED visits decreased to a minimum value of 201.9 visits per day on Saturday. The differences between each day of the week were significant (p &lt; 0.001). Seasonal trends were present with peaks during February and September. The differences among months were significant (p &lt; 0.001). The total variance of the ED visit data was decreased after adjusting for the long-term trend, day of week, and month of year. These adjustments remove noises not relevant to the study goal and are necessary for further studies testing hypotheses about factors affecting ED visits that may not be uniformly distributed over time.

Association between ambient PM2.5 and emergency department visits for psychiatric emergency diseases

BackgroundWhether or not short-term exposure to particulate matter <2.5 μm in diameter (PM2.5) increases the risk of psychiatric emergency diseases is unclear. MethodsThe study was performed in a metropolis from January 2015 to December 2016. The exposure was PM2.5, and the confounders were weather (temperature and humidity) and other pollutants (PM10, SO2, CO, O3, and NO2). The outcomes were emergency department (ED) visits with psychiatric disease codes (F00-F99 in ICD10 codes). General additive models were used for the statistical analysis to calculate the adjusted relative risks (ARRs) and 95% confidence intervals (95% CIs) for the daily number of ED visits with a lag of 1 to 3 days following a 10 μg/m3 increase in PM2.5. ResultsDuring the study period, a total of 67,561 ED visits for psychiatric diseases were identified and tested for association with PM2.5. Daily ED visits for all psychiatric diseases were not associated with PM2.5 in the model that was not adjusted for other pollutants. The ARR (95% CI) in the model adjusted for SO2 was 1.011 (1.002–1.021) by 10 μg/m3 of PM2.5 on Lag 1 for all psychiatric diseases (F00-F99). The ARR (95% CI) in the model adjusted for O3 was 1.015 (1.003–1.029) by 10 μg/m3 of PM2.5 on Lag 1 for F40-F49 (Neurotic, stress-related and somatoform disorders). ConclusionAn increase in PM2.5 showed a significant association with an increase in ED visits for all psychiatric diseases (F00-F99) and for neurotic, stress-related and somatoform disorders (F40-F49) on lag day 1.

Multiple Determinants of Vulnerability for Emergency Department Visits for Heat-Related Illness in California 2005-2008 Warm Seasons

Background: High temperatures are associated with risk of Heat-Related Illness (HRI) and other acute clinical outcomes. Information on HRI risk factors is rarely place-based; decision-makers need local-scale (e.g., neighborhood) data to inform strategies to reduce heat health impacts. Objective: In multi- determinant multi-level models assess relations between daily maximum temperature (Tmax) and emergency department (ED) visits for HRI and vulnerability factors, i.e., biological susceptibility (e.g., sex, age, race), physical environment (e.g., land-use, air quality), or socioeconomic (e.g., neighborhood assets). Methods: CA Office of Statewide Healthcare Planning and Development ED data for 2005-2008, restricted to the warm seasons (May 1-October 31) were used. Cases were defined as a HRI diagnosis (International Classification of Diseases (ICD) ninth revision, clinical modification (ICD9-CM) code 992.0-992.9). Non-HRI cases were retained as controls. Exclusions: If date of visit or residence ZIP code (ZC) was missing. ZC were converted to Zip Code Tabulation Area (ZCTA) to link census tract data to patients. Hierarchical generalized linear models with a logic link (SAS v9.3 PROC GLIMMIX) were used. For each exposure (daily Tmax, daily O3 or PM10) models included both the ZCTA-specific 4-year seasonal mean (Tmaxmn), and ZCTA-day (i.e., ED visit date) deviation from that mean (Tmaxdif). Interaction terms were used to evaluate effect modification. Results: HRI risk was positively associated with Tmaxdif (OR 1.02 95%CI: 1.016, 1.019, p&amp;lt;.0001), and co-exposure to O3 (Tmaxdif*O3dif) increased the risk (OR 1.051 95%CI: 1.043, 1.059, p&amp;lt;.0001). Risk varied by age group, sex and race/ethnicity, with girls (especially those &amp;#8804; 10 years), African American and Hispanic children, and elderly Black at greatest risk. ZCTA %-impervious surfaces, % multi-family homes were positively associated with HRI. These and other results pointed to interventions to reduce HRI risk.

Emergency Department Visits and Ambient Temperature: Evaluating the Connection and Projecting Future Outcomes.

The U.S. Global Climate Change Research Program has identified climate change as a growing public health threat. We investigated the potential effects of changes in ambient daily maximum temperature on hyperthermia and cardiovascular emergency department (ED) visits using records for patients age 64 and younger from a private insurance database for the May–September period for 2005–2012. We found a strong positive relationship between daily maximum temperatures and ED visits for hyperthermia but not for cardiovascular conditions. Using the fitted relationship from 136 metropolitan areas, we calculated the number and rate of hyperthermia ED visits for climates representative of year 1995 (baseline period), as well as years 2050 and 2090 (future periods), for two climate change scenarios based on outcomes from five global climate models. Without considering potential adaptation or population growth and movement, we calculate that climate change alone will result in an additional 21,000–28,000 hyperthermia ED visits for May to September, with associated treatment costs between $6 million and $52 million (2015 U.S. dollars) by 2050; this increases to approximately 28,000–65,000 additional hyperthermia ED visits with treatment costs between $9 million and $118 million (2015 U.S. dollars) by 2090. The range in projected additional hyperthermia visits reflects the difference between alternative climate scenarios, and the additional range in valuation reflects different assumptions about per‐case valuation.

Erratum: Seasonal Cycle and Relationship of Seasonal Rhino- and Influenza Virus Epidemics With Episodes of Asthma Exacerbation in Different Age Groups.

This corrects the article on p. 517 in vol. 9, PMID: 28913991.

Seasonal Cycle and Relationship of Seasonal Rhino- and Influenza Virus Epidemics With Episodes of Asthma Exacerbation in Different Age Groups.

PurposeSeasonal variations in asthma exacerbation (AE) are associated with respiratory virus outbreaks and the return of children to school after vacation. This study aims to elucidate the period, phase, and amplitude of seasonal cycles of AE in 5 different age groups with regard to rhino- and influenza virus epidemics in Korea.MethodsThe number of daily emergency department (ED) visits for AE in all age groups of Korea and the nationwide weekly incidence of rhino- and influenza virus, were obtained for 2008-2012. Fourier regression was used to model rhythmicity, and the Cosinor method was used to determine the amplitude and phase of the cycles in each age group. The cross-correlation function (CCF) between AE and the rhino- and influenza virus epidemics was also calculated.ResultsThere were 157,559 events of AE (0.62 events/1,000 individuals/year) during the study period. There were spring and fall peaks of AE in children and adults, but only 1 winter peak in the elderly. The amplitude of the AE peak in infants was higher in spring than in fall (9.16 vs 3.04, P<0.010), and the fall peak was approximately 1 month later in infants than in school children (October 11 vs November 13, P<0.010). The association between AE and rhinovirus was greatest in school children (rho=0.331), and the association between AE and influenza virus was greatest in those aged ≥60 years (rho=0.682).ConclusionsThe rhythmicity, amplitude, and phase of the annual cycle of AE differed among different age groups. The patterns of AE were related to the annual rhino- and influenza virus epidemics.

Seasonal and Environmental Variation of Lower Extremity Cellulitis Incidence Among Emergency Department Patients in Three Geographic Locations

Background Recent investigation has suggested a higher incidence of lower extremity cellulitis (LEC) during the summer, but it is not clear if this phenomenon is limited only to certain climates or locations. We sought to investigate this phenomenon and further elucidate the relationship with environmental climate factors in three different geographic locations.Methods This was a retrospective study of all patients with at least 1 ICD-9 code recorded during an emergency department (ED) visit at Mayo Clinic in Scottsdale, AZ; Jacksonville, FL; and Rochester, MN; between January 1, 2009 and December 12, 2014. Demographics were defined using ICD-9 data. Temperature data was obtained from the National Oceanic and Atmospheric Administration website. The climates of each location were classified according to the Köppen Climate Classification System as hot desert (AZ), humid subtropical (FL) or humid continental (MN) climate types. The primary outcome was LEC (ICD-9 code 682.7) expressed as a proportion of 1000 ED visits (LEC visits/1,000 EDV), to account for seasonal variation in ED usage. Univariate and multivariate regression were performed for analysis.ResultsThere were 627,292 ED visits among 288,349 patients during the study period. The incidence of LEC visits/1,000 EDV was significantly different across sites (9.36 in FL, 7.95 in AZ, and 7.39 in MN, P <0.0001 for any difference). In the humid climate types (FL and MN), the peak incidences of LEC occurred in the warmest month; July in FL (11.77 LEC visits/1,000 EDV) and August in MN (9.69 LEC visits/1000 EDV). In AZ, the peak incidence occurred in November, the fourth coolest month (9.44 LEC visits/1000 EDV) (Figure 1). There was a significant positive correlation between the high daily temperature and the incidence of LEC cellulitis in all three sites (Figure 2). After controlling for total daily ED visits, gender, and age, the high temperature for the day was significantly associated with occurrence of LE cellulitis at each site (P <0.0001).Conclusion The incidence of LEC presenting to the ED is associated with environmental temperature across different geographic locations and climate types, but slight variations in seasonality of infection was observed. Investigation to determine whether other environmental factors, in particular, humidity, are associated with the incidence of LEC is ongoing.Disclosures All authors: No reported disclosures.

GW27-e0890 Effects of Temperature and Air Pollution on Outpatient and Emergency Department Visits for Cardiovascular Diseases in Shanghai, China

We explore the acute effects of temperature and air pollution on the number of daily outpatient and emergency department visits of cardiovascular diseases in shanghai. The air pollution data, temperature data and outpatient and emergency department visits of cardiovascular diseases data were

Susceptibility to Heat-Related Fluid and Electrolyte Imbalance Emergency Department Visits in Atlanta, Georgia, USA.

Identification of populations susceptible to heat effects is critical for targeted prevention and more accurate risk assessment. Fluid and electrolyte imbalance (FEI) may provide an objective indicator of heat morbidity. Data on daily ambient temperature and FEI emergency department (ED) visits were collected in Atlanta, Georgia, USA during 1993–2012. Associations of warm-season same-day temperatures and FEI ED visits were estimated using Poisson generalized linear models. Analyses explored associations between FEI ED visits and various temperature metrics (maximum, minimum, average, and diurnal change in ambient temperature, apparent temperature, and heat index) modeled using linear, quadratic, and cubic terms to allow for non-linear associations. Effect modification by potential determinants of heat susceptibility (sex; race; comorbid congestive heart failure, kidney disease, and diabetes; and neighborhood poverty and education levels) was assessed via stratification. Higher warm-season ambient temperature was significantly associated with FEI ED visits, regardless of temperature metric used. Stratified analyses suggested heat-related risks for all populations, but particularly for males. This work highlights the utility of FEI as an indicator of heat morbidity, the health threat posed by warm-season temperatures, and the importance of considering susceptible populations in heat-health research.