Data on HIV Project

HEALTH DATA ANALYSIS

Public Health Data Analysis: The HIV Project

Part One: Descriptive Epidemiology

The data set selected for analysis is that of HIV. It presents the prevalence of HIV/AIDS among 359 cases by among other things, gender, ethnicity, city of residence, state, age, and sexual orientation.

Place: the highest occurrence of HIV/AIDS is reported in the City of Atlanta, which accounts for 47.5 percent of HIV/AIDS cases among the 359 cases. The second-highest occurrence is reported in College Park at 8.93 percent, followed by Alpharetta at 7.27 percent. The lowest HIV/AIDS occurrence is reported in Hapeville and Johns Creek, both of which report a prevalence rate less than 2 percent. Fig 1 below presents the frequency table showing the frequency of viral load by city of residence. The visual representation of viral load by city is presented in the pie chart labeled as Chart 1.

Fig 2: Viral Load by City of Residence

 

 

 

 

 

 

 

 

Current form: C:\\Users\\Susan\\Epi Info 7\\Projects\\HIV\\HIV.prj:Case

 

 

Record count: 359 (Deleted records excluded) Date: 19/06/2022 21:48

 

 

 

 

 

 

 

 

 

 

Frequency

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Frequency variable: City

 

 

 

 

 

 

 

Weight variable: ViralLoad

 

 

 

 

 

 

 

Include missing: False

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

City

Frequency

Percent

Cum. Percent

Wilson 95% LCL

Wilson 95% UCL

 

 

Alpharetta

120542

7.27%

7.27%

7.23%

7.31%

 

 

Atlanta

781961.9

47.16%

54.43%

47.08%

47.23%

 

 

Chattahoochee Hills

62698.54

3.78%

58.21%

3.75%

3.81%

 

 

College Park

148125.2

8.93%

67.14%

8.89%

8.98%

 

 

East Point

69566.55

4.20%

71.34%

4.16%

4.23%

 

 

Fairburn

66910.42

4.04%

75.37%

4.01%

4.07%

 

 

Hapeville

25385.23

1.53%

76.90%

1.51%

1.55%

 

 

Johns Creek

31241.46

1.88%

78.79%

1.86%

1.90%

 

 

Milton

41332.94

2.4fi9%

81.28%

2.47%

2.52%

 

 

Mountain Park

45780.39

2.76%

84.04%

2.74%

2.79%

 

 

Palmetto

38759.7

2.34%

86.38%

2.31%

2.36%

 

 

Roswell

48467.13

2.92%

89.30%

2.90%

2.95%

 

 

Sandy Springs

80543.07

4.86%

94.16%

4.82%

4.89%

 

 

Union City

96891.95

5.84%

100.00%

5.81%

5.88%

 

 

TOTAL

1658206

100.00%

100.00%

 

 

 

 

Chart 1: Viral Load by City of Residence

Person: the viral load is higher among females at 51.62 percent, as compared to males, who report a viral rate frequency of 48.38 percent. These findings are summarized in frequency table 2 below. Figure 3 summarizes the person characteristics of the dataset by ethnic grouping. African Americans report a higher viral load frequency as compared to Asians and Alaskan Natives. This is despite the fact that whites form the biggest percentage of the sample as shown in the combined frequency table in figure 4.

Figure 2: Frequency Table of Viral Load against Gender

Frequency

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Frequency variable: Sex

 

 

 

 

 

 

 

Weight variable: ViralLoad

 

 

 

 

 

 

 

Include missing: False

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Sex

Frequency

Percent

Cum. Percent

Wilson 95% LCL

Wilson 95% UCL

 

 

F-Female

999086.9

51.62%

51.62%

51.55%

51.69%

 

 

M-Male

936274.4

48.38%

100.00%

48.31%

48.45%

 

 

TOTAL

1935361

100.00%

100.00%

 

 

 

 

 

Figure 3: Frequency Table by Grouping

 

 

 

 

 

 

 

Figure 5: Comparing Viral Load by American Indian/Alaskan Natives by Antigen

The means table indicates that the mean viral load among American Indian/Alaskan natives was 5,280, as compared to an average of 4,500 for non-American Indian/Alaskan natives. Thus, generally, as per the mean viral load, Indian/Alaskan natives report a higher load than the general American population.

Part Two: Analytical Epidemiology

The hypothesis developed for this part of the assignment is:

Age significantly influences HIV viral load, with younger people reporting higher viral loads

A linear regression will be used to test the above hypothesis. A linear regression is used to predict the relationship between variables and the effect of one variable (the independent variable) on another (the dependent variable) (CDC, n.d). The above hypothesis focuses on determining the degree to which age influences the HIV viral load. A linear regression is preferred to a logistic regression because the outcome (dependent) variable is a numerical, continuous variable (CDC, n.d). The logistic regression is preferred in cases where the outcome variable is binary, taking on two values, such as yes or no (CDC, n.d.). The continuous nature of the outcome variable makes a linear regression the most plausible advanced statistics test (CDC, n.d.). A logistic regression is only used in cases where the outcome variable is binary. The complex sample means test may show what age categories have the highest viral loads based on the calculated mean by viral load per age group. However, it would not show the strength of the relationship between the variables.