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Summer OUS 2007 Core 116: AIDS |
Paper 2 | |||||||||||||||||||||||||||
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Intro On this second assignment, I was asked to find relationships between the AIDS rate within the Bronx and different aspects of the Bronx community. As one would expect, there are many aspects that make up the Bronx community. Of all these aspects (heritage, nationality, religion and so forth) only a few really stood out. In my analysis they were: Public Assistance percentages, Unemployment percentages, Methods of Transportation, Education levels, Family income and Financial status relative to the Poverty Line. Due to past observations, I expected that those were the aspects that would have the strongest relationship with the AIDS rate. I tested the strength of each aspect and the AIDS rate by finding correlations between them. For strong correlations, I needed a coefficient of about .0396 or higher. My results follow:
I listed the correlations in order from strongest to weakest, positive to negative and the strongest positive correlation was between Percent of Individuals on Public Assistance and the AIDS rate.
Percent of Individuals on Public Assistance When I found the correlation between the Percent of Individuals on Public Assistance and the AIDS rate, my result was 0.931923. I was not all too surprised when I received this correlation, since it meant that as the number of Individuals who received Public Assistance increased so did the AIDS rate. To my understanding, those on public assistance would be the individuals whose income is relatively low. With less money, the less likely that individual is willing that individual is to spend it on preventative measures such as condoms, especially since a condom would not be as important as paying the rent or buying groceries. To see if this correlation is still occurring today, I correlated the Percent of individuals on Public Assistance with recent HIV rates. I received a correlation of .954238. This means that as more individuals receive Public Assistance the HIV rates go up as well.
Percent of Individuals Below the Poverty Line The second strongest positive correlation, 0.928717 was between the Percent of Individuals below the Poverty Line and AIDS rate. What this means is that as the number of Individuals below the Poverty Line increased, so did the AIDS rate for that zip code. This ties in closely to those who are on Public Assistance. If you look at the graph below, you can see that most of the zip codes with 30% or higher or the population below the Poverty Line also had 10% or higher of the population on Public Assistance. With such a close relationship, I would suspect that the reasoning behind such a strong Poverty Line correlation is the same as the reasoning behind the strong correlation between the AIDS rate and the Percent of Individuals on Public Assistance. That reasoning is that without the funds to support a healthy lifestyle the individual is left unprotected to numerous hazards.
Unemployment Unemployment had a correlation of 0.83038, the third strongest positive correlation with AIDS rate. This means that as the percentages of Unemployed Individuals raises, so does the AIDS rate for that zip code. I would once again suspect that the reasoning behind this is the same as above. However, I also would guess that in zip codes where the unemployment and AIDS rates were high, those individuals pursued activities that were unhealthy and less productive. These activities would most likely include increased unprotected sex practices and drug use. It was after I made this correlation that I regretted not finding the percentages of injected drug use per zip code. If I had that data I would probably see that the zip codes with the highest injected drug use also had some of the highest unemployment rates.
Median Family Income Median Family income had the strongest negative correlation, -0.83802. This means that as the amount of Family income is decreased the AIDS rate will increase. If we take a look at the graph below we can see that for zip codes with Median Family Incomes averaging above $30,000 their percentages of Individuals on Public Assistance was below 15%. Zip codes 10451-10460 had Public Assistance percentages far above 15 and thus had the highest AIDS rate in the Bronx. My findings with the Unemployment, Public Assistance and Poverty line correlations have indicated that higher AIDS rates exist in select zip codes as a result of less money. Therefore after finding the Median Family Income versus AIDS rate correlation, I am lead to believe that of all the aspects that compose the Bronx community, finance has to be one of the most significant reasons behind high AIDS rates.
Private Auto *The category of Private Auto includes cars, trucks, carpooling, motorcycles and bikes. I chose to look at the transportation aspect of the Bronx community, particularly Private Auto; mainly because I figured that individuals who drove to their destinations were less likely to encounter areas with “negative influences”. To me “negative influences” are situations which solicit health jeopardizing activates such as drugs, prostitution and gangs. Thus my decision to choose this aspect is primarily based on personal experience. My zip code, 10472, is considered to be one of the “hottest spots” in the Bronx. What this means is that in my area there are a significant number of drug-money transactions that take place. I consider these events to be negative influences, and I usually avoid these influences by catching a taxi right outside of my apartment. Therefore I surmised that if others are able to avoid these situations by driving to their destinations then that should, in effect, lower the AIDS rate. I was right, the correlation between the percent of Individuals who used Private Auto and the AIDS rate was -0.59256. This means that within each zip code, as more individuals utilized private means of transportation, the lower the AIDS rate would be.
Employed Earlier I looked at the correlation between the Unemployed and the AIDS rate. I found that as the percentage of the Unemployed increased so did the AIDS rate. At this point, I assumed that the opposite would apply for the percentage of Employed individuals; however I still did the correlation just to be sure. After correlating the percentage of Employed individuals and the AIDS rates my result was -0.439657. This means that as the percentage of Employed individuals increased, the AIDS rates decreased. Employment provides a stable income to the household and as seen in the chart below, zip codes with high Employment percentages had higher Median Family Incomes; as well as lower AIDS rates and percentages of Individuals on Public Assistance. As well, employment through some jobs can also come with exclusive health benefits such as health insurance and health committees. These benefits work with employees to make sure they get drug tests, eat healthy and so forth. In some cases, these health benefits provide incentives for the employee to follow their program. With this level of outside help it makes sense why employed individuals are much less likely to contract HIV/AIDS.
Males with Some College Since transportation by Private Auto had so much success in lowering AIDS rate, I revisited the idea of “avoiding negative influences’. Once again I drew on personal experience as how this could be done and choose the education aspect. Receiving an education can teach individuals about AIDS, how it is contracted; and eventually help individuals to recognize and avoid situations where AIDS contraction is a high possibility (i.e. unprotected sex, injected drug use and so forth). However, the type of education (i.e. a college education which includes campus residency) can temporarily remove individuals from these negatively influencing areas or at least occupy more of their time. When I correlated the percent of Males Who Have Obtained One or More Years of College with the AIDS rate I received a correlation of -0.42552. This means that as the number of males in that zip code Who Obtained One Year or More of College increased, the AIDS rate decreased. Ultimately this means that my idea of avoiding areas with negative influences, by almost any means, is correct.
Conclusion After this analysis of my Bronx data it seems that one of the biggest influences on the AIDS rate is finance. As the percentage of Unemployed individuals increases, the lower the Median Family Income will be for that zip code. The lower the Median Family Income is, the higher the percentage will be of those individuals on Public Assistance; as well as those whose financial status is Below the Poverty Line. All this, will then lead to an increase in the AIDS rate for that zip code. As well, the more Employed individuals there are; the higher the Median Family Income will be for that zip code and thus resulting in a lower AIDS rate. Also, with a stable income arrives the ability to afford college and private transportation. The higher the percentage of individuals who are able to avoid negative situations either through Private Auto or a college Education, the lower the AIDS rate will be for that zip code. It now seems that everything is beginning to come together, and the sources of the problem are becoming clearer. However as this is happening I am left asking myself, “What can I do to expose this issue and stop it?”
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