My first core AIDS assignment was to calculate and analyze the cumulative AIDS rates for my neighborhood in The Bronx. This assignment exposed the fact that the Fordham section had one of the highest cumulative AIDS rates compared to the other parts of the Bronx. I was not surprised by this fact because there were various newspaper articles in the Daily News and the New York Post claiming that the Bronx had one of the highest AIDS related death cases. The variance in race shows that there is a variance in the amount of AIDS cases. The Hispanics had the most accumulation of aids cases since 1980, that amount was 15,624 people, while the black population had the second highest with 12,799 and whites had the lowest number of people with 1,841 people.
A significant correlation between demographic variables exists for coefficient values that are greater than 0.396 at the 95 percent confidence level. Where the degrees of freedom for 25 zip codes would be 23. A value in excess of 0.505 would indicate significance at the 99 percent confidence level.
My first correlation examined the relationship between the Cumulative AIDS rates and the percent of Hispanics, blacks and whites that lived each zip code.. The chart of the cumulative AIDS rate versus the percentage of Hispanics shows a positive correlation of 0.82.(Table 2, Graph 1) The correlation of the statistics of people living with HIV and AIDS also supports that fact that there is a relationship between the population of Hispanics and the rate of people living with HIV and AIDS. The test statistic for the correlation coefficient is 0.858.(Table 2, Graph 2) As a result the statistics show a 99 percent confidence interval that the rate of people living with HIV/AIDS and the cumulative AIDS Rate is directly related to the population of Hispanics, meaning that as the Hispanic population rises so does the two different AIDS rates. The increase in the correlation coefficient of people living with HIV/AIDS being higher than the cumulative AIDS rate shows that there has been an increase in the spread of the disease amongst the Hispanic community in the Bronx.
Alternatively the White residents pose to be the minority population in the Bronx. When the correlation was calculated, the statistics portrayed that there was a negative correlation between the Cumulative AIDS rate and the percentage of white residents in the Bronx. The correlation, which was -0.65, (Table2, Graph3) illustrates that there is a relationship between the percent of whites and the cumulative AIDS rate, even though it is negative. This relationship simply means that as the population of White residents decrease the Cumulative rate of AIDS increases. The correlation for the rates of people living with HIV/AIDS versus the percentage of white residents is -0.71,(Table1, Graph 4) which supports the fact that there is an inverse relationship between the two different rates and the population of whites.
Surprisingly there was no valid correlation between Cumulative AIDS Rate and the Population of Black residents. The Black residents were the intermediate population, where they were neither the majority nor the minority and therefore the correlation was low because the population has no relationship to the cumulative AIDS rate or the rate of people living with HIV/AIDS. For the black population the PLWA rates were 432 people per 100,000 while the cumulative AIDS rates since 1980 was 2725 people per 100,000. The cumulative AIDS correlation coefficient was 0.23, (Table 2 graph 5) while the PLWA correlation coefficient for the black population was 0.27 (Table 1 graph 6). This showed that there was actually no significant relationship between black ethnic group and the amount of HIV/AIDS cases in the Bronx.
The second correlation that was conducted was done in order to find out if there was a correlation between the Median income of each household versus the Cumulative AIDS rate. There was indeed a correlation; it was a negative correlation of -0.87 (Table 3 graphs 7). Aside from there being a negative correlation there was also an outlier, which is a statistic in the data that does not fit in with the rest of the data. The outlier did not correspond with the other data points in the Bronx but even with the outlier in the data set there was still significance to be held, but the fact remains that when the outlier was taken out there was a stronger correlation coefficient. There may be many reasons for the outlier to occur but for this specific median income, the High Bridge are of the Bronx is known to be a low income neighborhood. The median income was very low and cause High Bridge to be an outlier. Other than the outlier the correlation shows that there is an inverse relationship between the median income and the Cumulative AIDS rate. This inverse relationship simply means that the neighborhoods with the lower median income has the higher Cumulative AIDS rate, in other words as the income becomes lower the AIDS rate increases.
The third and last significant correlation in my testing was preformed between the Cumulative AIDS rate and the educational status of the residents. The first educational status that was correlated was the percentage of males and females who did not complete any schooling versus the Cumulative AIDS rates. These two correlations show that for males the correlation was positive, it was 0.85(table 4, graph 8) while the female correlation was also positive it was higher than that of the male. The female correlation was 0.87.(Table 5, graph 9) The correlations showed that there is a strong relationship between the rates and the educational level. The females started to work on the streets and did not get to go to school and it therefore put an outlier in the data. The male outlier was in High Bridge which is know for drug sales, the males start to sell drugs and do not go to school. This lack of education relates directly to the cumulative AIDS rates.
There are many different relationships that can affect the cumulative AIDS rate. Race, income and education are just some of the factors. These correlations prove relationships can be formed.
