The objective of this project is to conduct a preliminary exploration of the Hispanic Established Populations for the Epidemiologic Study of the Elderly (HEPESE) data. HEPESE dataset was obtained via Nation Archive of Computerized Data on Aging. HEPESE was part of the study that was funded by the National Institute of Aging to study the mortality and morbidity of multiple ethnic groups, one of which is Hispanic.

The study sampled 1078 U.S.-Born Hispanic elderly from five southwestern states (Arizona, California, Colorado, New Mexico, and Texas) about their health conditions and other sociodemographic conditions. The dataset (407 variables) was based on a questionaires with 407 questions that was carried out via telephone interview by Harris Interactive Inc.. Hispanic is one of the largest minority group in the United States, and they are often disadvantageous in accessing to healthcare and healcare information. Therefore, I am motivated to learn more about their health conditions, especially chronic diseases.

The objective of this report is to study the assocation between self-rated health and having multiple comorbidity among Hispanic elderly subjects.

Let’s start the exploration of this dataset!

Part-1 Summary of Viarbles and Frequency Analysis

- Self-Rate Health

Self-rated Health Frequency
Excellent 57
Good 289
Fair 529
Poor 199
Sum 1074

- Gender-specific Self-rated Health

As we can see, about half of the Hispanic elderly responder (529/1074) consider themselves to be in fair health condition, and merely 57 out of 1074 responders consider themselves to be healthy. About 67 percent of the responders feel they have fair or worse health status. Additionally, much more females repond to have fair or worse health condition compare to male, which also indicates that the situation might be worse to female. Based on the data, we should have basic understanding of the general understanding of health status of Hispanic elderly population, and why we are interested in this topic becomes clear.

- Diabete

## [1] 686

From figure 1, a bit over one third of the sample Hispanic elderly are diabetic, indicating that diabete is a prevalent chronic conditions that affect large Hispanic population. Among those subjects with diabetes, female seems to take up a greater proportion compared to male.

I then combine several variables that discribe the diabetic complications (amputation, limb blood circulation, eye problem, and kidney problem) into one variable, which tells how many diabetic complications one subject has. From figure 4, we can see that majority of the subjects either don’t have diabetes, or don’t have common diabetic complications aforementioned, which is a good new. However, still fair amount of subjects have one diabetic complication, so awareness should be raised to alleviate those person’s qualities of life.

Using a man-made variable that records if a subject has multiple diabetic complication, we can see about 5% of the sample are suffering from multiple diabetic complciation (more than one condition).

- Comorbidity (Multiple Chronic Conditions)

Comorbidity essentially means having multiple chronic diseases in one person. It is critical to study comorbidity in the hispanic population because comorbidity could impose great deal of distress in the subject as well as his or her family.

From figure 6, we know that it is actually common to see a subject with at least two comorbidity, and in fact, the peak of the barplot centers at “3” for numbers of comorbidity. This should alarms one because that would mean a vast proportion of Hispanic population suffer from many chronic diseases at the same time. More methods should be taken to investigate why that would be the case and how to mitigate this public health situation.

From figure 7, apparently, more than half of our sample suffer from multiple comorbidity, which is defined as having more than 2 chronic conditions simultaneously. We therefore are interested in determing if the a lower self-rated health associate with having multiple comorbidity.

Part-2 Statistical and Regression Analysis for Self-rated Health and Comorbidity

Few Comorbidity Multiple Comorbidity
Excellent 40 17
Good 154 129
Fair 218 303
Poor 46 150 

##        (Intercept) hepese$comorbidity    hepese$SEX7Male 
##          1.0543275          0.7655934          0.9197749

In part 2, I am trying to study if there is an association betweent the self-rated health and comorbidity. I first make the contingency table, along with two figres to visually present the relationship from the contingency table. We can see there is strong evidence, visually, for us to think that there is a connection between two variables. After running the chi-square test for homogeneity, the following result was obtained:

Statistical Analysis Summary Analysis Result
Pearson’s Chi-squared test X-squared = 64.436, df = 4, p-value = 3.382*10-13
Log Regression controled genders Odd Ratio: Comorbidity: 0.77 & Gender: 0.92

Clearly, according to the X2 Test for homogeneity, there is a strong association between the self-rated health and having multiple comorbidity or not among the Hispanic elderly population, from the perspectively of the HEPESE study. However, as the last graph shows, the Logistic Regression doesn’t show a particularly strong correlation between more comorbidity and lower self-rated health, as one would probably expect. The reason for that might be how the variable is structured, or more variables need to be taken into account in terms of regression model.

Hence, having comorbidity does contribute to the distress on the Hispanic elderly to lower thier self-rated health. I hope this report can give some insight to the policy-making regarding mitigating the health well-being of the hispanic population as whole, such as implementing community-based facilities that makes regular healthcare more availible for chronic disease patient.