One in every four deaths in the United States is attributed to heart disease. While the ethnic variations have not been momentous, the socioeconomic disparities of heart disease incidence need to be further investigated. Moreover, exposure to air pollutants has been documented to cause heart disease. This secondary-data study investigates the effects of air pollutants as well as socioeconomic factors on hospitalization rate of heart disease in Texas. The rates for the five sub-diagnoses of cardiovascular disease, heart attack, stroke, hypertension and heart disease were linked to ozone, fine particulate matter, carbon monoxide, nitrogen dioxide, sulphur dioxide and socioeconomic status factors at the county level. These were college education attainment, households with female heads, percentage of users of food stamps, ethnicities, living near a park and living in houses with severe housing problems. Spatial lag modelling was conducted to estimate the statistical significance of the independent variables on the five sub-diagnoses of heart disease. Fine particulate matter, sulphur dioxide and being African American were significant to all the outcomes. Living in a household with female head was significant to stroke and hypertension. Using food stamps was significant to cardiovascular disease, heart attack and heart disease. Fine particulate matter and sulphur dioxide increase the risk of heart disease by a factor of three to twenty two times, respectively. Whereas low socioeconomic status increases the risk of heart disease by a factor of up to four times. The results of the effect of particulate air and sulphur dioxide pollution among people in low social class especially African Americans. The vicious cycle of heart disease and low socioeconomic status call for societal and policy makers’ attention through methodical interventions to address the two significant issues of industrial facilities site allocation and stationary emission resources.
More than 610,000 people die of heart disease in the United States (US) every year. Risk factors include diabetes, obesity, diet, physical activity and excessive alcohol use. It refers to several heart conditions including cardiovascular disease (CVD), heart attack, stroke, hypertension and heart disease [
Levels of air pollutants individually or combined contribute to the adverse cardiac health effects. The five air pollutants of carbon monoxide (CO), nitrogen dioxide (NO2), ozone (O3), fine particulate matter (particles with aerodynamic diameter <2.5 μm, PM2.5) and sulphur dioxide (SO2) are especially associated with high heart disease morbidity and mortality. The American Cancer Society cohort estimated that for each 10-μg/m3 increase in annual mean exposure to PM2.5, cardiopulmonary mortality was increased by approximately 6% [
Texas has few of the most severe ozone non-attainment areas in the United States (US). The eight-county Houston-Galveston area (HGA), the nine-county Dallas-Fort Worth (DFW), Beaumont-Port Arthur Area (BPA), the El Paso area, and other metropolitan areas in Texas have a long history of ozone and particulate matter non- attainment. Despite the impressive progress in Texas air quality over the past decade, many challenges persist especially with the recent stricter standards. In addition, the latest technology advances related to oil and gas production in the State has complicated emission inventory activities related to O3 precursors (nitrogen oxides, volatile organic compounds) and other pollutants (e.g.; benzene) [
Air pollutants and especially SO2 levels decrease with increased distance from the source. Thus, majority of research on its health effects are of small scale [
Hospital discharge rates by county in Texas, for all ages in 2013 were obtained from the website for the Centers for Disease Control and Prevention (CDC) [
Variable | Resource |
---|---|
Hospital Discharge Rate for Cardiovascular Disease (ICD-9 codes 390 - 459) | CDC |
Hospital Discharge Rate for Heart Attack ( ICD-9 code 410) | CDC |
Hospital Discharge Rate for Stroke (ICD-9 codes 430-434 or 436 - 438) | CDC |
Hospital Discharge Rate for Hypertension (ICD-9 codes 401 - 405) | CDC |
Hospital Discharge Rate for Heart Disease (ICD-9 codes 390 - 398, 402, 404, or 410 - 429) | CDC |
Annual Average Ambient Concentrations of CO (ppm) | EPA |
Annual Average Ambient Concentrations of NO2 (ppb) | EPA |
Annual Average Ambient Concentrations of O3 (ppm) | EPA |
Annual Average Ambient Concentrations of PM2.5 (μg/m3) | EPA |
Annual Average Ambient Concentrations of SO2 (ppb) | EPA |
Percentage without 4+ Years College (%) | US Census |
Families with Female Head of Household (%) | US Census |
Percentage Food Stamp/Supplemental Nutrition Assistance Program Recipients (%) | US Census |
Percentage Living in Poverty All Ages (%) | US Census |
Percentage of Population with Native Origins (%) | US Census |
Percentage of Population of Asian Origins (%) | US Census |
Percentage of Population That Is African American (%) | US Census |
Percentage of Population of Hispanic Origins (%) | US Census |
Percentage of White Population (%) | US Census |
Percentage of Population Living Within Half a Mile of a Park | US Census |
Percentage of Households Living with Severe Housing Problems (%) | US Census |
the largest number of 310,335 followed by heart disease (194,032), then stroke (49,974), then heart attack (37,032) and finally hypertension (23,903).
CO (ppm) | NO2 (ppb) | O3 (ppm) | SO2 ((ppb) | PM2.5 (μg/m3) | |
---|---|---|---|---|---|
Mean | 0.93 | 26.08 | 0.02 | 5.04 | 8.61 |
Standard Deviation | 0.23 | 4.86 | 0.00 | 0.76 | 1.17 |
Kurtosis | −1.02 | −0.40 | −0.55 | −0.92 | −0.33 |
Skewness | 0.28 | 0.08 | −0.15 | −0.24 | 0.55 |
Minimum | 0.52 | 15.99 | 0.02 | 3.00 | 6.60 |
Maximum | 1.52 | 39.62 | 0.03 | 6.41 | 12.50 |
Percentage of Population without College Education | Female Head | Food Stamp | Poverty | Native | Asian | African American | Hispanic | Caucasian | Park | Percentage of Population with Housing Problems | |
---|---|---|---|---|---|---|---|---|---|---|---|
Mean | 82.26 | 17.08 | 15.58 | 18.15 | 0.30 | 0.85 | 6.18 | 32.89 | 58.43 | 18.48 | 14.13 |
Standard Deviation | 7.22 | 5.31 | 6.53 | 5.65 | 0.58 | 1.71 | 6.71 | 23.09 | 21.17 | 17.81 | 4.30 |
Kurtosis | 2.74 | −0.15 | 2.39 | 1.32 | 125.50 | 41.36 | 1.24 | 0.31 | 0.02 | 0.36 | 2.00 |
Skewness | −1.47 | 0.02 | 1.06 | 0.70 | 9.68 | 5.53 | 1.36 | 1.04 | −0.75 | 1.06 | 0.56 |
Minimum | 50.60 | 3.40 | 2.50 | 6.60 | 0.00 | 0.00 | 0.00 | 2.20 | 1.20 | 0.00 | 0.00 |
Maximum | 94.80 | 32.80 | 43.60 | 43.10 | 8.00 | 17.30 | 33.30 | 98.40 | 96.50 | 74.00 | 32.20 |
status. On average, eighty two percent were without college education, seventeen percent lived in households with female head, sixteen percent used food stamps, eighteen percent were in poverty, eighteen percent lived within half a mile of a park and fourteen percent lived in houses with severe housing problems. On average, about fifty nine percent of the population WAS white, thirty three percent were Hispanic and seven percent were African American.
Statistically significant pair-wise associations were high among the health outcomes (
The statistically significant spatial regression coefficients are presented in
by one percent increased heart attack rate by 0.36, stroke by 0.34 and heart disease by 1.37.
In summary, the recorded hospital discharge rates for cardiovascular disease, heart attack, stroke, high blood pressure and heart disease were 31.03, 3.70, 5.00, 2.39 and 19.40; respectively. In those counties, more than 82% of the population did not have college education, 17% of the households had female heads, more than 15% were on food stamps and more than 18% of the population was in poverty. More than 18% were near a park and more than 14% lived in houses with severe housing problems. As for ethnicities, more than 58% were Caucasian, 32% Hispanics, and 6% African American. High blood pressure was more positively associated with percentage of households with female head than those on food stamps. None of the five sub-diagnoses of heart disease had significant pair-wise association with either SO2 or PM2.5. However, both pollutants as well as being African American were significant to each of the health outcome. Being Hispanic was not significantly associated with any of the five health outcomes.
The current challenges in identifying the precise causes of heart disease disparities have been addressed by few
CVD | Heart Attack | Stroke | High Blood Pressure | Heart Disease | SO2 | PM2.5 | Female Head | Food Stamps | |
---|---|---|---|---|---|---|---|---|---|
Cardiovascular Disease | 1.00 | ||||||||
Heart Attack | 0.66 | 1.00 | |||||||
Stroke | 0.80 | 0.59 | 1.00 | ||||||
High Blood Pressure | 0.51 | 0.29 | 0.31 | 1.00 | |||||
Heart Disease | 0.96 | 0.69 | 0.70 | 0.50 | 1.00 | ||||
SO2 (ppb) | 0.32 | −0.02 | 0.30 | 0.04 | 0.25 | 1.00 | |||
PM25 (μg/m3) | 0.07 | −0.26 | 0.01 | −0.21 | −0.01 | 0.77 | 1.00 | ||
Percentage of Population without College Education | 0.29 | 0.41 | 0.33 | 0.29 | 0.28 | 0.00 | −0.23 | 0.29 | 0.46 |
Female Head | 0.14 | −0.09 | −0.01 | 0.34 | 0.06 | 0.21 | 0.22 | 1.00 | 0.71 |
Food Stamp | 0.23 | 0.13 | 0.12 | 0.32 | 0.16 | 0.14 | 0.02 | 0.71 | 1.00 |
African American | 0.18 | −0.07 | 0.16 | 0.08 | 0.14 | 0.60 | 0.61 | 0.33 | 0.08 |
Caucasian | 0.20 | 0.16 | 0.32 | −0.27 | 0.22 | 0.22 | 0.17 | −0.56 | −0.61 |
Dependent Variable | PM2.5 (μg/m3) | SO2 (ppb) | Female Head | Food Stamp | African American | Caucasian | Percentage of Population without College Education |
---|---|---|---|---|---|---|---|
Cardiovascular Disease | 5.21 | 21.76 | 3.67 | 1.63 | 0.33 | ||
Heart Attack | 2.77 | 5.04 | 0.50 | 0.38 | 0.36 | ||
Stroke | 4.52 | 8.43 | 0.74 | 0.65 | 0.34 | ||
High Blood Pressure | 2.47 | 3.63 | 0.46 | 0.31 | |||
Heart Disease | 3.74 | 14.90 | 1.45 | 1.11 | 1.37 |
opinions. For this study in Texas, four factors persist: exposure to PM2.5, exposure to SO2, socioeconomic status (female head, food stamps, college education) and ethnicity (being African American). These finding are the first of this nature in general and for Texas in particular.
Contrasting the strongly associated factors of living in a household with female head and using food stamps (ρ = 0.71), shows that being on food stamps has a greater influence on heart disease rates in Texas (increase heart rate from 0.50 to 3.67 per 10,000). Although poverty and being on food stamps are mutually exclusive [
Studying heart disease hospitalization rate racial disparities showed that being African American is positively associated to the five sub-diagnoses. The data analysed cannot determine if this strong relationship is causal or of confounding nature. Nevertheless, the pair-wise associations between being African American and the two significant pollutants (PM2.5 and SO2) point to economic factors related to living in cheaper neighbourhoods, which coincide with locations that are favoured by such facilities [
The association between PM2.5 and SO2 and heart disease expressed as the rate increase per 10,000 in hospital admissions for a unit increase in PM2.5 and SO2 levels exceed most of the documented associations in the US and overseas [
This is the first study to combine the five main diagnoses of heart disease as well as two major factors (air pollution and SES). The results of this research suggest that the number and distribution of PM2.5 and SO2 monitors in Texas are adequate to detect significant links between exposure and the five health outcomes [
The downloaded heart disease data did not include important possible confounders such as age, gender, or lifestyle factors. Lastly, because the discharge data reporting is voluntary for hospitals, heart disease hospitalizations may also be under-represented based on hospital reporting characteristics and data extraction and coding processes used in each location.
The environmental agency for Texas is the Texas Commission on Environmental Quality (TCEQ). It has developed a long list of State Implementation Plans (SIP) and revisions through the air quality management process entailing air monitoring, modelling, planning, rule-making, control strategy, permitting, and inventorying emissions. TCEQ SIPs ensure that The State of Texas is responsible for developing the right plans to comply with the Clean Air Act requirements through the achievement of the NAAQS. As such, SIPs must be continually updated and revised to reflect changes in NAAQS or air quality monitoring data. The steps that are usually followed to develop an SIP are: determining emissions, developing strategy, determining emission changes, modelling to determine changes in air quality, comparison to NAAQS, adjustment of strategy and re-analysis, rule- making to implement strategy, adoption of rules using state process and minimum federal public participation requirements (40 CFR Part 51), submission to the United States Environmental Protection Agency (EPA), and EPA rule-making. In order to understand the cause of non-attainment, develop control strategies to reach attainment, demonstrate that the selected strategies will lead to attainment and assess amount of progress made towards reaching NAAQS, TCEQ uses emission inventories, monitoring data, and air quality models. The State process includes revised SIP, public notices for comment period, public hearings, responding to comments, State-required legislative review, formal adoption, and SIP submittal. The stakeholders of the SIPs development process include federal, state, and local governments; industry; small businesses; environmental groups; and citizens of the state. An SIP revision takes from 18 months to few years and if a revised SIP is not submitted or disapproved, sanctions and other punitive measures are applied [
The NAAQS standard for ozone set in 1997 was 0.08 ppm was revised to 0.075 ppm in 2008 then to 0.070 ppm in 2015 (primary and secondary). The stricter standards resulted in more areas being more likely subject to additional permitting and emissions control requirements. With the decrease in time lapse between the newer standards, the cycle of air quality management process has become more complex, more intense, and more expensive. Despite the efforts exerted to manage air quality in the State, the associations between air pollutant levels and health outcomes have not been addressed in a conclusive manner. This is translated in the negligence of the impact on public health in the process of developing, revising and implementing air quality management processes. Special attention needs to be paid to the permitting of industrial facilities in residential or industrial-to-be locations.
Faye Anderson,Najla N. Al-Thani, (2016) Female Head, Food Stamps, Ethnicity and Air Pollution: Confounders or Causes of Heart Disease in Texas. Open Journal of Epidemiology,06,146-153. doi: 10.4236/ojepi.2016.62015