Age, Race and Gender Spatiotemporal Disparities of COPD Emergency Room Visits in Houston, Texas

Abstract

Chronic obstructive pulmonary disease (COPD) is one of the major causes of morbidity and mortality in the United State. The investigation of the continuing increase in its prevalence and mortality has increased attempts to further understand its causes and how to manage it. Understanding the spatial and temporal distribution of COPD emergency room (ER) visits in Harris County (Houston) can guide these efforts in a uniform yet diverse setting like this one. The objectives of this study were to identify the temporal and spatial variations of COPD emergency room visits adjusted by age, gender, ethnicity, day of the week, month, and year, and to estimate the odds ratio of COPD emergency room visits adjusted by the six risk factors. The dataset used were extracted from two resources: ER Utilization Study and Harris County centroid coordinates. Exploratory statistical analyses were conducted to study the spatiotemporal disparities and investigate associations. Logistic regression was performed to estimate the odds ratio of COPD primary diagnosis adjusted for age, race, gender, day of the week, month, and year. The number of COPD ER visits kept increasing from 2004 throughout 2009 but there was a significant increase after the year 2005. Spring and summer had lower visits compared to winter and autumn. Lowest visits were during June and July and higher during December and January. Tuesdays had the highest number of visits compared to the remaining days of the week with Saturdays having had the lowest number of visits. Temporal analyses show the continuous increase in COPD ER visits in Houston as well as the consistent spatial disparities between zip regions. After adjustment for age, race, gender, day of the week, month, and year, there were statistically significant associations between emergency room chronic obstructive pulmonary disease diagnoses in Houston, Texas, with these six predictors.

Application of Multivariate Geostatistics in Environmental Epidemiology: Case Study from Houston, Texas

“…Similar to CVD ER visits. COPD ER visits had positive significant associations with the being African American male, relative humidity, O3 of the same day, and PM2.5 of the same day [5]. Pair-wise correlations between the variables are given in Table 2.…”

“…The persistent increase in CVD and COPD ER visits (Figure 3) in Houston, Texas could be attributed to variations in data coverage and completeness as well as socioeconomic factors including immigrations due to severe weather disasters where the majority of movers are usually those who belong to the traditionally under-served under-represented groups [5] [6]. The previous models were univariate, i.e.…”

“…Application of multivariate geostatistical techniques can assist in this regards because it has the advantage of making use of the spatial correlations between observations pertinent to neighborhoods to predict values at unsampled places [3] [4]. This study capitalizes on previous studies which assess the effect of ozone and particulate matter on CVD and COPD ER visits in Harris County, Texas from 2004 to 2009 [5] [6] by studying the effect of joint exposure to air pollutants and other factors like temperature and relative humidity on both health outcomes instead of univariate modeling. The use of multivariate geostatistics has been useful in other applications like mining, but with the increased quality of spatial health data, their relevance is gradually increasing.…”

The Effect of Air Pollutants and Socioeconomic Status on Asthma in Texas

“…The majority of asthma-related mortality occurs in lower income countries [3] [4]. Research on environmental effects on asthma has demonstrated strong associations between asthma presentation and concentrations of criteria air pollutants: carbon monoxide (CO), nitrogen dioxide (NO 2 ), ozone (O 3 ), fine particulate matter (PM2.5), and sulfur dioxide (SO 2 ) [5]- [11]. Asthma symptoms include coughing, wheezing, chest tightness, and shortness of breath.…”

“…Moreover, studies focusing on the impact of socioeconomic status (SES) on asthma have demonstrated varying degrees of associations with factors like income, college education attainment, and living in urban or rural areas. These associations varied with demographic factors such as age and ethnicity [5] [7] [12] [13]. The effect of SES on asthma morbidity and mortality is attributed to factors such as living conditions, working environment, proximity to air pollutant discharge, and psychosomatic stress [7] [14].…”