Property Value and Human Health Outcomes Correlation

Background of the Research Topic

Residential property values are assumed to be a reliable indicator of socioeconomic status because it is among the most prized and valuable assets for many people. According to Coffee et al. (2013), the property value is a reliable wealth indicator that could help researchers understand the relationship between socioeconomic status and human health outcomes. In the US alone, the property value is deemed to constitute up to 21% of a household’s net worth (Coffee et al., 2013). For many low-income households, researchers estimate that property value may account for up to 50% of a household’s net worth. Based on this background, there is a potential to understand the incidence of major health issues and property values in Hawaii. Indeed, as Shapiro, Mostashari, Hripcsak, Soulakis, & Kuperman (2011) point out, a society’s wellbeing is mostly dependent on the proper understanding of its housing market structure. Shapiro et al. (2011) allude to this fact because they believe location and property values help to predict disease risk factors that cause many non-communicative diseases such as obesity, hypertension, diabetes, and heart attack. Coffee et al. (2013) reinforce this fact by saying researchers have long established that since the 19th century, socioeconomic status has predominantly been a significant population health risk factor. Pioneering work by researchers such as Louis-Rene Villerme, Rudolf Virchow, and Charles Booth support this fact (Coffee et al., 2013).

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Based on the above findings, socioeconomic status is considered a complex measure of human health outcomes. Traditionally, researchers have used a triad of indicators (education, income, and occupation) to explain this multidimensional concept. Beyond these three factors, some researchers have done more research on the issue and presented socioeconomic status in terms of housing type, housing tenure, car ownership numbers, number of bedrooms present in a house, number of people living in a house, and number of children in the same house (Coffee et al., 2013). These dynamics of housing have a strong link with socioeconomic status and human health outcomes. The data dictionary for the Hawaii housing dataset presents such information, which could be instrumental in understanding the human health outcomes for the target population. This is the main research focus of our study.

Problem Statement and Quantitative Research Question

Problem Statement: Many factors affect human health outcomes. Health agencies and experts have had a difficult time trying to predict these health outcomes based on the multitude of factors influencing human health behaviors. The current tools or health indicators, available for understanding some of these health outcomes are often simplistic and fail to account for the diversity of factors influencing health outcomes. For example, traditionally, researchers have often used income, education, age, and such factors to predict human health outcomes (Shi & Johnson, 2014). However, there is no common denominator available to understand how these different factors interact to influence human health outcomes. Evaluating the same problem from a property value standpoint provides the impetus needed to understand how different socioeconomic factors influence human behavior and ultimately human health outcomes.

Research Question: How do property values predict the incidence of diseases in Hawaii?

How Components of Research Design are Appropriate for Answering Research Question

The above-mentioned research question would be answered using the quantitative research method as the main research approach. This research approach is appropriate for the study because we are using measurable variables -property cost and disease incidences. The correlation research design would be the main premise for undertaking this research approach. It is appropriate for the study because it draws a correlation between property values and human health outcomes (Fink, 2013). Collectively, these aspects of the research approach are instrumental in answering the research question.

Support of Response

In an article written to explain the application of quantitative research designs in human health sciences, Smith et al. (2010) explained that the research approach is instrumental in helping researchers to confirm a hypothesis about a phenomenon. The same is true in our proposed study because the main hypothesis put forward is that researchers could use property value numbers in Hawaii to predict the health outcomes of the population. As mentioned in this study, the quantitative approach is instrumental in confirming this hypothesis because the available data is in the form of numbers and statistical results. CIRT (2014) affirms this fact by saying that the quantitative research method is appropriate for health science studies that incorporate highly structured methods. In other words, it advocates for the use of the approach in instances when data is gathered using reliable quantitative assessment tools and equipment that have led to the production of valid demographic and housing statistics about the location of the study.

The correlation research design is appropriate for this study because we are trying to establish whether two variables – property value and human health outcomes are related. According to Lipowski (2008), three possible outcomes could arise from this study – positive correlation, no correlation, and negative correlation. Although one of these outcomes will suffice, Shi and Johnson (2014) caution us that correlation would not necessarily imply causation. Nonetheless, these two elements of the methodology are appropriate for the selected study because their metrics align with the nature of the proposed research topic.

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References

CIRT. (2014). When to use quantitative methods. Web.

Coffee, N., Lockwood, T., Hugo, G., Paquet, C., Howard, N., & Daniel, M. (2013).

Relative residential property value as a socio-economic status indicator for health research. International Journal of Health Geographics, 12(1), 12-22.

Fink, A. (2013). Research design, validity, and best available evidence. In Evidence-based public health practice. Thousand Oaks, CA: Sage.

Lipowski, E. E. (2008). Developing great research questions. American Journal of Health-System Pharmacy, 65(17), 1667–1670. Web.

Shapiro, J. S., Mostashari, F., Hripcsak, G., Soulakis, N., & Kuperman, G. (2011).

Using health information exchange to improve public health. American Journal of Public Health, 101(4), 616–623. Web.

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Shi, L., & Johnson, J. A. (Eds.). (2014). Novick & Morrow’s public health

administration: Principles for population-based management. Burlington, MA: Jones & Bartlett.

Smith, P. M., Stock, S. R., McLeod, C. B., Koehoorn, M., Marchand, A., & Mustard,

C. A. (2010). Research opportunities using administrative databases and existing surveys for new knowledge in occupational health and safety in Canada, Quebec, Ontario and British Columbia. Canadian Journal of Public Health, 101, 46-52.

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StudyCorgi. (2021, January 14). Property Value and Human Health Outcomes Correlation. Retrieved from https://studycorgi.com/property-value-and-human-health-outcomes-correlation/

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"Property Value and Human Health Outcomes Correlation." StudyCorgi, 14 Jan. 2021, studycorgi.com/property-value-and-human-health-outcomes-correlation/.

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StudyCorgi. "Property Value and Human Health Outcomes Correlation." January 14, 2021. https://studycorgi.com/property-value-and-human-health-outcomes-correlation/.

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StudyCorgi. 2021. "Property Value and Human Health Outcomes Correlation." January 14, 2021. https://studycorgi.com/property-value-and-human-health-outcomes-correlation/.

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StudyCorgi. (2021) 'Property Value and Human Health Outcomes Correlation'. 14 January.

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