Heart Disease, Race, and Income: A Statistical Analysis
This paper investigates the relationship between race, household income, and heart disease history using a dataset of 100 respondents from the Western Governor Township. The study begins with a literature review covering prevalence, risk factors, racial disparities, socioeconomic influences, and public health interventions related to heart disease in the United States. Two inferential statistical tests are then applied using SPSS: a chi-square test to assess whether race and heart disease history are independent, and a one-way ANOVA to determine whether household income differs significantly across racial groups. Both tests yield non-significant results, leading to the retention of both null hypotheses and prompting discussion of the findings in relation to existing research.
- Introduction: Heart disease burden and study overview
- Background: Literature on risk factors, race, income, and policy
- Hypothesis: Chi-square and ANOVA null and alternative hypotheses
- Methods: Justification of statistical tests and sample description
- Results: Descriptive stats, cross-tabulations, and test outcomes
- Conclusion: Findings summarized and limitations acknowledged
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What makes this paper effective
- The paper clearly states both null and alternative hypotheses for each statistical test before presenting results, making the inferential logic easy to follow.
- The background section draws on authoritative sources — including the CDC, the American Heart Association, and the WHO — to contextualize the quantitative findings within broader public health literature.
- Raw SPSS output is accurately translated into narrative interpretation, demonstrating competence in both data analysis and written reporting of statistical results.
Key academic technique demonstrated
The paper demonstrates hypothesis-driven quantitative research: hypotheses are formally stated, appropriate tests are selected and justified (chi-square for two categorical variables; ANOVA for comparing group means), statistical criteria are applied (p > 0.05 threshold), and conclusions are explicitly tied back to the null hypothesis decision. This mirrors the standard structure of an empirical research report.
Structure breakdown
The paper follows a conventional IMRaD-adjacent structure: an Introduction framing the public health problem; a Background section synthesizing existing literature on risk factors, race, income, and policy; a Hypothesis section formally presenting both sets of null and alternative hypotheses; a Methods section justifying test selection; a Results section presenting descriptive statistics, cross-tabulations, and inferential output with supporting tables; and a Conclusion that synthesizes findings, compares them to the literature, and acknowledges limitations.
Introduction
Heart disease has been an enormous challenge in the United States. The most common form is Coronary Heart Disease (CHD), though many other forms exist. Heart disease accounts for approximately 1 in 4 deaths in the US — a figure high enough to demand serious intervention. Experts have attributed the sharp rise in heart disease deaths to Americans' lifestyles and limited health awareness. Although heart disease can affect anyone at any age, some experts argue that it affects older adults more severely than other age groups.
This paper examines the relationship between heart disease and several other variables. The first section provides background on heart disease in the United States, drawing on multiple studies. Following the literature review, hypotheses are formulated and tested using a heart disease dataset from the Western Governor Township. SPSS software is used to perform the statistical tests, and the results are discussed in detail. A conclusion is then drawn based on the study's output.
References
AHA 2019 Heart Disease and Stroke Statistics — American College of Cardiology. (2019). AHA 2019 Heart Disease and Stroke Statistics. American College of Cardiology. https://www.acc.org/latest-in-cardiology/ten-points-to-remember/2019/02/15/14/39/aha-2019-heart-disease-and-stroke-statistics
Centers for Disease Control and Prevention — CDC. (2020, September 8). Heart disease facts. https://www.cdc.gov/heartdisease/facts.htm
Centers for Disease Control and Prevention — CDC. (2020, May 19). High blood pressure symptoms and causes. https://www.cdc.gov/bloodpressure/about.htm
Holtz, C. (2020). Global healthcare: Issues and policies. Jones & Bartlett Learning.
Mastroianni, A. C., Kahn, J. P., & Kass, N. E. (2019). The Oxford handbook of public health ethics. Oxford University Press.
NEDARC. (2019). Hypothesis testing.
Virani, S. S., Alonso, A., Benjamin, E. J., Bittencourt, M. S., Callaway, C. W., Carson, A. P., Chamberlain, A. M., Chang, A. R., Cheng, S., Delling, F. N., Djousse, L., Elkind, M. S. V., Ferguson, J. F., Fornage, M., Khan, S. S., Kissela, B. M., Knutson, K. L., Kwan, T. W., Lackland, D. T., & Lewis, T. T. (2020). Heart disease and stroke statistics — 2020 update: A report from the American Heart Association. Circulation, 141(9).
World Health Organization: WHO. (2019, June 11). Cardiovascular diseases. https://www.who.int/health-topics/cardiovascular-diseases#tab=tab_1
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