By Abinav Sankaranthi, February 2020.
In many regions of the US, access to healthcare is limited. Even Houston, home of the world’s largest medical center, is no exception. As part of an investigative research project that I conducted last semester at Rice University, I became aware of healthcare access and outcome issues in Houston neighborhoods located close to petrochemical factories but farther from medical facilities. After being involved in a “toxic tour” of the communities surrounding these factories, I did more research on this topic. One such community was the neighborhood located near Galena Park, which had suffered the effects of the Houston oil industry and consisted of people from a low socio-economic background. I found out that people living in these areas not only have exposure to environmental contaminants that may lead to chronic diseases, but were located farther away from medical services. Additionally, during Rice’s Urban Immersion program, I attended a presentation by the staff of the METRO. They were spreading awareness about the issue of some people in Houston being affected by transportation barriers to healthcare. These exposures further drove my interest in studying the health-related effects of “distance to doctors.” Due to large establishments of healthcare services such as primary care, emergency care, and other specialty care being located in urban areas such as the Texas Medical Center in the heart of Houston, many Americans who live away from these healthcare agglomerations experience poor health outcomes. So, I propose the question: How does the proximity of healthcare services affect people’s
attitudes towards healthcare and how do these attitudes towards healthcare in turn influence the frequency of healthcare visits? In this paper, I will discuss this research question along with demographic analyses and a plan for possible sociological research methods.
My first step will be to try to understand the demographic landscape of the Texas Medical Center (TMC) neighborhood and Galena Park neighborhood by detailing population, race, and family structure demographics. With Houston’s population growing each year it was not shocking that the TMC had a population density of 2,376.2 people per square mile and a total population of 3,561 citizens(Social Explorer, 2018). On the eastern side of Harris County, I noticed a population density and a total population of 1,518 people per square mile and 2,095 people respectively. Noticeably, the TMC neighborhood has a much higher population density. The racial dynamics between TMC and Galena Park neighborhoods are extremely different. The TMC neighborhood has a much lower percentage of African Americans in their population, at 14.24% compared to Galena Park’s 50.45%. The number of Asians in Galena Park is little to none, with that group consisting of 1.15% of the population. The white population is higher but different in both neighborhoods, with 64.15% of citizens being white in the Texas Medical Center and 41.91% in Galena Park. To add on, Galena Park has around 10% more married-couple families and 13.15% more single-parent families compared to the TMC neighborhood. All of these statistics were important because they provided a base of comparison when distinguishing between the neighborhoods.
Further demographic analysis lies in the domain of education, socioeconomic status, and occupation. There is an educational advantage for the TMC neighborhood as 48.46% of employed civilians take part in the Educational Services, Health Care, and Social Assistance compared to 28.72% in Galena Park. Consequently, the population of 25 years or older who have a Bachelor’s degree or better is 80.89% for TMC, rather than 12.78% for Galena Park. In the TMC neighborhood, the average household income is $109,382 with housing being 70.81% renter-occupied and 29.19% owner-occupied. In Galena Park, the average household income is $41,126 and 58.54% for owner-occupied housing. Evidently, the 70.81% renter-occupied housing in the TMC as compared to 41.46% of Galena Park shows that the TMC contains more easily rentable options such as apartments and condos for people who work in the vicinity. In 2016, Galena Park had 38.55% of families with income below the poverty level while the TMC had 1.92%(Social Explorer,2016). The clear disparity between socioeconomic status of these two neighborhoods can imply a greater wealth level for those living in the TMC.
This socioeconomic disparity could also impact certain health-related demographics. Harris County has around 2,509 primary care physicians. Specifically to Harris county, the infant mortality is 2,909 individuals and the premature age-adjusted mortality is 37,937 individuals (Social Explorer, 2016). Another interesting data point is related to health insurance and healthcare coverage. In the TMC, 86.17% of those with health insurance have private health insurance and 14.92% have public health care coverage. For Galena Park, 38.76% of those with health insurance have private, while 44.11% of these individuals have public health coverage. Income and insurance availability could be significant barriers to healthcare access. The data links back to socioeconomic disparity as those in the TMC might have the financial resources to afford private health care, unlike Galena Park residents.
While performing demographic analysis using data from the Social Explorer, I got to understand the characteristics and distribution of two neighborhoods in Houston, one close to the Texas Medical Center and the other away. I was intrigued by how the populations in each neighborhood had their health care access impeded by varying distances from the TMC and differing socioeconomic status. The aforementioned problems are further exacerbated by the closure of hospitals in rural areas of the country. A study conducted by the University of North Carolina revealed that 166 rural hospitals were closed since 2005 (Spleen et al.). These so-called “hospital desert” areas exist in all parts of the US with bigger areas in the western rural sides of the US. Another study published by the National Institutes of Health reports that close to 30 million people do not live within an hour to a trauma care health facility in the US (Carr et. al.) Unfortunately, many Americans living in low-income and rural areas experience more barriers to healthcare access. These geographic, demographic, and socio-economic barriers could play a role in people’s attitudes or opinions about health care.
As you can see, many sociological questions that are factual, theoretical, comparative or developmental arise from examining these neighborhoods. Some of these questions include, “How does living in close proximity to health centers affect the health and wellbeing of people there?”, “Why does poor healthcare access and outcomes exist in certain Houston neighborhoods in spite of the existence of one of the world’s largest medical centers in Houston city?”, “What aspects or patterns in urban neighborhoods are determinants of better health? What are the likely effects on poverty levels and health outcomes of expanding urban spaces across the state of Texas”, “What are the social determinants of health in high-income and low-income communities within close proximity to healthcare facilities?”
The question driving my research proposal is: Does the proximity of healthcare services affect people’s attitudes towards healthcare and to what extent these attitudes influence the frequency of proactive and timely healthcare visits? Essentially, I would like to conduct a comparative study between two neighborhoods, a higher income community situated near the Texas Medical Center and a low-income neighborhood located away from medical facilities. Foremost, these two groups can be compared to understand their attitudes towards healthcare influenced by the distance to health centers. Even so I would like to explore socio-economic conditions, education, profession, family structure, race, gender, and religious practices that may contribute to their ability to access and overcome healthcare barriers. Why do people face harsh health outcomes in low-income communities? Do patients demonstrate avoidant behaviors for seeking timely treatment when they have to travel far to the hospital? What do these people do to get well? Does proximity to hospitals enable proactive healthcare? These questions will be examined to observe why low-income neighborhoods located away from medical centers in cities and towns have poor health outcomes. I predict that low-income communities who do not have easy and economical access to healthcare facilities demonstrate avoidant behaviors for seeking timely treatment for their health conditions, and for periodically getting wellness checkups. In order to study this research question, I plan to use a range of sociological methods.
The primary sociological research methods that I plan to use are surveys, interviews, and comparative research to study how the distance to healthcare facilities affect people’s attitudes towards healthcare. Anonymous surveys will be employed to understand the motivations and barriers to seeking healthcare. In addition to questions about transportation, access, medical insurance, these surveys will collect data on socioeconomic status, income, profession, family structure, education level, religious practice related to healthcare. Religious practice-related questions are included in the survey questions because, in some cultural and religious practices, visiting doctors and getting lab tests done are avoided. The surveys would be initiated by the medical providers in Texas Medical Center through email for people in the TMC neighborhood. The same survey will be sent in paper format to the Galena neighborhood residents. As these surveys also ask about health-related questions, they would need to comply with healthcare privacy laws and anonymization process. Therefore, to accomplish this, my research team would visit the clinics and hospitals in TMC and request them to review and send the survey to the communities we specified. Surveys can enable data collection from a large group of people. Moreover, if these surveys are anonymous, participants will provide honest answers and opinions. This collection of information can be used for comparative analysis on how various factors impact healthcare-related access, outcomes, and attitudes of people.
In addition, interviews can be used to ask open-ended questions and gather the motivation and influential factors affecting people’s attitudes toward healthcare. These interviews would be conducted only after requesting their consent to participate in the process. This ethnographic method involving face-to-face field interviews and interactions would help uncover the socioeconomic conditions, distance, cultural and religious factors that may form barriers to healthcare access. With information directly from the participants for open-ended questions, researchers can ask further questions toward the research topic. Consequently, the data collected from these interviews can help contribute to understanding not only the effects of distance to healthcare centers but also socio-economic, cultural and familial factors that affect health outcomes.
Finally, comparison research can be used to understand the changes in the demographic information, health data, employment, mortality, morbidity rates over time in the neighborhoods under study. Further factors and patterns of influences can be found that could be correlated to explain the healthcare-related attitudes and behaviors of people.
Although these methods have strengths in collecting information from larger groups through surveys, conducting direct interviews, and doing comparison research against time, there are many weaknesses in this research design. First, the Hawthorne effect skews the data collected because some individuals change their behavior as a result of being observed (Mccambridge et al.). Altering their answers and opinions could create bias or skewed results. Surveys, on the other hand, are less likely to be altered as they are anonymous. Therefore, using data collected, analyzed, and triangulated from both surveys and interviews in parallel could remove anomalies and skewed results.
In summary, this research proposal would help find answers to why and how people’s attitudes towards healthcare changes when they encounter geographic, socio-economic, demographic barriers to accessing healthcare. The methodology explained can be effective to generate quantitative and personal data to answer the research question. It may be able to address the complexity and nuance of the factors affecting healthcare disparities. Furthermore, by understanding the causal relationship of these factors, we can be able to discern whether differences in healthcare outcomes between areas near and away from medical centers result from not merely distance but other variables like attitude. Accordingly, the research proposal will also drive the distribution of healthcare resources toward areas that need more concentrated and effective care. Hopefully, this research study will help bridge the inequality gap between citizens in cities around the world, not just Houston and Harris County.
Work Cited
“166 Rural Hospital Closures: January 2005 - Present (124 since 2010).” Sheps Center, www.shepscenter.unc.edu/programs-projects/rural-health/rural-hospital-closures/.
Carr, Brendan G., et al. “Disparities in Access to Trauma Care in the United States: A Population-Based Analysis.” Injury, vol. 48, no. 2, 2017, pp. 332–338., doi:10.1016/j.injury.2017.01.008.
Giddens, Anthony, Mitchell Duneier, and Richard P. Appelbaum. 2013. Introduction to Sociology. New York: W.W. Norton & Company, Inc
Mccambridge, Jim, et al. “Systematic Review of the Hawthorne Effect: New Concepts Are Needed to Study Research Participation Effects.” Journal of Clinical Epidemiology, vol. 67, no. 3, 2014, pp. 267–277., doi:10.1016/j.jclinepi.2013.08.015.
Social Explorer, 2016, “Census 2016.” US Census Bureau and Social Explorer, Retrieved February 22, 2020.
Social Explorer, 2018, “Census 2018.” US Census Bureau and Social Explorer, Retrieved February 22, 2020.
Spleen, Angela M., et al. “Health Care Avoidance Among Rural Populations: Results From a Nationally Representative Survey.” The Journal of Rural Health, vol. 30, no. 1, 2013, pp. 79–88., doi:10.1111/jrh.12032.