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International Journal of Environmental Research and Public Health logoLink to International Journal of Environmental Research and Public Health
. 2016 Nov 11;13(11):1126. doi: 10.3390/ijerph13111126

Trends in HIV Testing among Adults in Georgia: Analysis of the 2011–2015 BRFSS Data

Benjamin E Ansa 1,*, Sashia White 2, Yunmi Chung 1, Selina A Smith 1,3
Editors: Ronald L Braithwaite, Mario De La Rosa
PMCID: PMC5129336  PMID: 27845740

Abstract

Georgia is ranked fifth highest among states for rates of human immunodeficiency virus (HIV) diagnosis. About 4% of persons living with HIV infection in the United States reside in Georgia, and almost 19% of these people do not know their HIV status. The present study examined the trends and associated factors of HIV testing among adults in Georgia between 2011 and 2015 by analyzing data of the Behavioral Risk Factor Surveillance System (BRFSS). A total of 31,094 persons aged ≥18 years were identified who responded to the question “Have you ever been tested for HIV?” Overall, there were 11,286 (44.2%) respondents who had been tested for HIV, compared to 19,808 (55.8%) who had not. There was a slight decrease in the percentage of respondents who have ever tested for HIV, from 45.6% in 2011 to 43.7% in 2015 (APC (annual percent change) = −0.98, not significant). Factors associated with HIV testing were being female (p = 0.004), black (p < 0.001), younger than 55 years (p < 0.001), single (p < 0.001), attaining education level above high school (p < 0.001), and earning annual income of $50,000 or less (p = 0.028). Overall in Georgia, there has been a slight decline in the temporal trend of HIV testing, and more than half of adults have never been tested for HIV. For reducing HIV transmission in Georgia, enhancing access and utilization of HIV testing should be a public health priority.

Keywords: HIV/AIDS, testing, trends, Behavioral Risk Factor Surveillance System, socio-demographic, Georgia

1. Introduction

Human immunodeficiency virus (HIV) testing contributes to the prevention and control of HIV/AIDS. Following HIV diagnosis, risk behaviors tend to decrease [1,2,3]; people diagnosed with HIV can make decisions that potentially lower HIV transmission risk by avoiding risk behaviors such as unprotected sex and needle sharing [4]. Also, people who test negative for HIV can make decisions to protect themselves from HIV by engaging in safer sex behaviors and in some cases, taking pre-exposure prophylaxis [4]. Enabling individuals to become diagnosed early is a public health priority [5], as late diagnosis of HIV infection can lead to increased morbidity, mortality, and healthcare costs [5].

According to the Centers for Disease Control and Prevention (CDC), an estimated 1.2 million people in the United States (U.S.) are living with HIV, and 13% (156,300) of these do not know they are infected [6]. Each year, nearly 45,000 people are diagnosed with HIV, with 30% of new HIV infections being transmitted by people who are living with undiagnosed HIV [4]. Geographically, the burden of HIV is not evenly distributed. In 2014, the rates (per 100,000 people) of persons diagnosed with HIV infection were the highest in the South (18.5), followed by the Northeast (14.2), the West (11.2), and the Midwest (8.2) [6].

Georgia (GA) with a population of 10,214,860 in 2015, is the second most populous state in the southeast of the U.S. [7]. The population is made up of 62% whites, 32% blacks/African Americans, 9.0% Hispanics/Latinos, and 5.0% other races/ethnicities [7]. With a rate of 27 per 100,000, GA is ranked fifth highest among states in regard to rates of HIV diagnosis. According to the CDC, 1 in 51 Georgians will be diagnosed with HIV in their lifetime (compared to 1 in 670 residents of North Dakota) [8]. Despite comprising only 3.1% of the U.S. population in 2014, 6.4% (2640) of new HIV diagnoses and 4.4% (53,230) of persons living with HIV infection in the U.S. were recorded in GA [9]. About 19% of those living with HIV are unaware of their HIV status, and almost 23% of persons in the state of GA were diagnosed with AIDS within three months, as a result of late testing for HIV [9,10]. This means that they harbored the virus for a long period of time without receiving appropriate treatment that would have prevented further deterioration of their immune system.

In 2006, the CDC recommended that, as part of routine health care, everyone between the ages of 13 and 64 be tested for HIV at least once, with yearly HIV testing for high-risk individuals, in line with the National HIV/AIDS Strategy goal of increasing by 2015 the percentage (to 90%) of persons living with HIV who know their serostatus [11,12]. The purpose of the present investigation was to evaluate the progress in HIV testing in GA by examining the temporal trends and factors associated with testing for HIV among adults residing in GA between 2011 and 2015.

2. Materials and Methods

2.1. Study Design

This cross-sectional study was done by analyzing nationally representative datasets.

2.2. Data Source, Study Participants, and Sampling

The Behavioral Risk Factor Surveillance System (BRFSS) is a nationally representative cross-sectional survey that collects data on U.S. residents in all 50 states, the District of Columbia, and three U.S. territories, regarding their health-related risk behaviors, chronic health conditions, and use of preventive services [13]. GA has been part of the system since it was established in 1984 [14]. Surveys are conducted through phone interviews (landline and cellphone) and more than 400,000 adult interviews are conducted each year, making it the largest continuously conducted health survey system in the world and a useful tool for addressing and developing health promotion activities [13].

Although conducted in different time periods, the surveys used identical methods for recruitment. GA is among the participating BRFSS states that utilize disproportionate stratified sample (DSS) design for their landline samples [15]. Telephone numbers are divided into two groups, or strata, which are sampled separately. The high-density and medium-density strata contain telephone numbers that are expected to belong mostly to households. Whether a telephone number goes into the high-density or medium-density stratum is determined by the number of listed household numbers in its hundred block, or set of 100 telephone numbers with the same area code, prefix, and first two digits of the suffix and all possible combinations of the last two digits. BRFSS puts numbers from hundred blocks with one or more listed household numbers (1 + blocks, or banks) in either the high-density stratum (listed 1 + blocks) or medium-density stratum (unlisted 1 + blocks). The BRFSS samples the two strata to obtain a probability sample of all households with telephones. Cellular telephone sampling frames are commercially available and the system can call random samples of cellular telephone numbers, but doing so requires specific protocols [15]. The basis of the 2011–2015 BRFSS sampling frame is the Telecordia database of telephone exchanges (e.g., 617-492-0000 to 617-492-9999) and 1000 banks (e.g., 617-492-0000 to 617-492-0999). The vendor uses dedicated cellular 1000 banks, sorted on the basis of area code and exchange within a state. The BRFSS forms an interval (K) by dividing the population count of telephone numbers in the frame (N) by the desired sample size (n). The BRFSS divides the frame of telephone numbers into n intervals of size K telephone numbers. From each interval, the BRFSS draws one 10-digit telephone number at random. In the sample design, each state begins with a single stratum. To provide adequate sample sizes for smaller geographically defined populations of interest, however, many states sample disproportionately from strata that correspond to substate regions.

Response rates for BRFSS were calculated using standards set by the American Association of Public Opinion Research (AAPOR) Response Rate Formula 4 [16]. The median survey response rate (%) for all states and Washington, DC, in 2011 was 49.7, and ranged from 33.8 to 64.1 [17]; in 2012 was 45.2, and ranged from 27.7 to 60.4 [18]; in 2013 was 46.4, and ranged from 29.0 to 60.3 [19]; in 2014 was 47.0, and ranged from 25.1 to 60.1 [20]; and in 2015 was 47.2, and ranged from 33.9 to 61.1 [21]. Response rates (%) for GA included in this analysis had a weighted AAPOR response rate of 49.9 in 2011 [17], 53.5 in 2012 [18], 46.5 in 2013 [19], 48.8 in 2014 [20], and 47.6 in 2015 [21].

Secondary analyses of the BRFSS 2011–2015 data were performed to identify persons in GA aged ≥18 years who reported having ever been tested for HIV.

2.3. Measures

Respondents were categorized under socio-demographic variables of gender (male or female); age in years (18–24, 25–34, 35–44, 45–54, 55–64, or 65+); race (non-Hispanic (NH) white, NH black, Hispanic, NH other, or NH multiracial); education (<high school, high school/General Educational Development (GED), some post high school, or college graduate); annual income in United States Dollar (USD (<$15,000, $15,000–<$25,000, $25,000–<$35,000, $35,000–<$50,000, or $50,000+)); marital status (married, divorced, widowed, separated, never married, or a member of an unmarried couple); healthcare coverage (yes/no); and HIV high-risk situations (yes/no). HIV high-risk situations included engaging in any of the following behaviors for the past year: use of intravenous drugs, treatment for sexually transmitted disease, giving or receiving money or drugs for sex, or having anal sex without a condom. The type of health coverage was only assessed for the year 2014 these data were available. The outcome variable was participants’ response to the question “Have you ever been tested for HIV?” (yes/no).

2.4. Statistical Analyses

Descriptive statistics of socio-demographic variables and HIV high-risk situations related to HIV testing were generated for each year, using frequencies and proportions. Data were weighted using the iterative proportional fitting weighting method (i.e., raking) to adjust for noncoverage, nonresponse, and for differences between sample and population characteristics [22]. Weighted percentages of respondents who had ever been tested for HIV were calculated for each variable category for each year. Joinpoint Trend Analysis software [23,24] was used to calculate the annual percent change (APC) over time. The model is linear on the log of the response for calculating annual percentage rate change. An APC is computed for each of those trends by means of generalized linear models assuming a Poisson distribution. The tests of significance use a Monte Carlo Permutation method. Significant changes include changes in direction or in the rate of increase or decrease. Logistic regression analyses were conducted to examine the association between socio-demographic variables and HIV testing. The model included data for the five years under review (2011–2015), and data were adjusted for gender, age, race, education, income, marital status, and healthcare coverage. Some of the variables were merged and then compared with the reference category. For example, the variable marital status was re-categorized into single and couple; those that were divorced, widowed, separated and never married were grouped as single, and compared to those that were in a couple relationship (married, and a member of an unmarried couple). Similarly for age, the categories were collapsed into three (18–34—young adults; 35–54—middle age; and ≥55—older adults). The same was done for race, education, and income. Odds ratios and related 95% confidence intervals were derived from regression analysis. Pair-wise rate differences were examined using bivariate survey-weighted logistic regression. Chi-square test and Monte Carlo Permutation method were used to obtain p values. The significance level was set at p < 0.05, and all tests were two-sided. Unweighted counts, weighted percentages, and logistic regression analyses were performed using the IBM SPSS Complex Samples version 24 (IBM Corp., Armonk, NY, USA) [25].

2.5. Ethical Considerations

BRFSS datasets are publicly accessible and do not contain personally identifiable information. CDC ensures that the process of data collection and release are governed by appropriate rules, regulations, and legislative authorizations [26].

3. Results

3.1. Socio-Demographic Characteristics and HIV Risk Situations of Respondents

In the BRFSS database, between 2011 and 2015, 31,094 adults in GA responded to the question “Have you ever been tested for HIV?” The respondents were ≥18 years old, predominantly female (63.0%, n = 19,545), white (66.7%, n = 20,743), college graduates (34.9%, n = 10,837), married (51.4%, n = 15,988), with an annual income of ≥$50,000 (35.5%, n = 11,032), and with some form of healthcare coverage (86.0%, n = 26,731) (Table 1). In addition, for the years data were available (2011 and 2012), 97.6% (n = 14,142) of respondents did not engage in HIV high-risk behaviors. For all the years under review, the results of the descriptive analyses of socio-demographic categories and having been tested for HIV were statistically significant (p < 0.001).

Table 1.

Socio-demographic characteristics and HIV risk situations of survey respondents to the question “Have you ever been tested for HIV?” in Georgia: 2011–2015 BRFSS data.

Total (N = 31,094) 2011 (n = 8977) 2012 (n = 5554) 2013 (n = 7010) 2014 (n = 5551) 2015 (n = 4002) p-Value
N n % n % n % n % n %
Gender <0.001
Male 11,549 3162 35.2 2062 37.1 2621 37.4 2132 38.4 1572 37.1
Female 19,545 5815 64.8 3492 62.9 4389 62.6 3419 61.6 2430 62.9
Age (years) <0.001
18–24 1495 309 3.4 283 5.1 428 6.1 290 5.2 185 4.6
25–34 2985 828 9.2 540 9.7 775 11.1 485 8.7 357 8.9
35–44 3914 1170 13.0 697 12.6 943 13.4 658 11.9 446 11.2
45–54 5605 1683 18.8 1037 18.7 1281 18.3 950 17.1 654 16.4
55–64 7248 2177 24.3 1263 22.7 1630 23.2 1260 22.7 918 22.9
65+ 9847 2810 31.3 1734 31.2 1953 27.9 1908 34.4 1442 36.0
Race <0.001
White, NH 20,743 6192 69.0 3687 66.4 4504 64.2 3678 66.2 2682 69.0
Black, NH 7413 2012 22.4 1340 24.1 1766 25.2 1349 24.3 946 22.4
Hispanic 1212 341 3.8 206 3.7 308 4.4 217 3.9 140 3.8
Other, NH 850 216 2.4 187 3.4 210 3.0 120 2.2 117 2.4
Multiracial, NH 445 106 1.2 74 1.3 117 1.7 94 1.7 54 1.2
Do not know/Refused 431 110 1.2 60 1.1 105 1.5 93 1.7 63 1.2
Education <0.001
<High school 3497 997 11.1 694 12.4 771 11.0 615 11.1 420 10.5
High School/GED 8593 2550 28.4 1605 28.9 1923 27.4 1469 26.5 1046 26.1
Some Post High School 8086 2314 25.8 1442 26.0 1825 26.1 1474 26.5 1031 25.8
College Grad 10,837 3090 34.4 1797 32.4 2477 35.3 1980 35.7 1493 37.3
Do not know/Refused 81 26 0.3 16 0.3 14 0.2 13 0.2 12 0.3
Annual Income (USD ($)) <0.001
<15,000 3511 995 11.1 697 12.6 825 11.8 610 11.0 384 9.6
15,000–<25,000 5215 1536 17.1 996 17.9 1122 16.0 930 16.7 631 15.8
25,000–<35,000 3260 998 11.1 595 10.7 738 10.5 564 10.2 365 9.1
35,000–<50,000 3650 1079 12.0 625 11.3 856 12.2 640 11.5 450 11.2
50,000+ 11,032 3142 35.0 1917 34.5 2451 35.0 2043 36.8 1479 37.0
Do not know/Refused 4426 1227 13.7 724 13.0 1018 14.5 764 13.8 693 17.3
Marital status <0.001
Married 15,988 4835 53.9 2845 51.2 3461 49.4 2787 50.2 2060 51.5
Divorced 4571 1313 14.6 798 14.4 1073 15.3 808 14.5 579 14.5
Widowed 4482 1312 14.6 830 14.9 903 12.9 858 15.5 579 14.5
Separated 838 226 2.5 138 2.5 223 3.2 151 2.7 100 2.5
Never married 4430 1090 12.1 824 14.8 1142 16.3 809 14.6 565 14.1
A member of an unmarried couple 648 170 1.9 103 1.9 171 2.4 111 2.0 93 2.3
Refused 137 31 0.4 16 0.3 37 0.5 27 0.5 26 0.6
Healthcare coverage <0.001
Yes 26,731 7680 85.6 4695 84.5 5872 83.8 4866 87.6 3618 90.4
No 4269 1272 14.2 847 15.3 1116 15.9 664 12.0 370 9.2
Do not know/Refused 94 25 0.2 12 0.2 22 0.3 21 0.4 14 0.4
HIV high risk situations N = 14,497 n = 8959 n = 5538 <0.001
Yes 309 185 2.1 124 2.2 N/A N/A N/A N/A
No 14,142 8748 97.6 5394 97.4 N/A N/A N/A N/A
Do not know/Refused 46 26 0.3 20 0.4 N/A N/A N/A N/A

Acronyms: NH—non-Hispanic, GED—General Educational Development, N/A—data not available, USD—United States Dollar.

3.2. Trends in HIV Testing among Adults in GA, 2011–2015

In GA, there were 11,286 (44.2%) respondents who had ever been tested for HIV. The weighted population estimates of those, by year of interview, and the APC for each variable are shown in Table 2. There was a slight decrease in the percentages of respondents who had ever been tested for HIV, from 45.6% in 2011 to 43.7% in 2015 (APC = −0.98, not significant). There was a significant decrease over time in the number of HIV testers among annual income earners of <$15,000 (APC = −2.29). The percentages of HIV testers over time were stable and APCs were not significant among the other categories of socio-demographic variables.

Table 2.

Weighted percentages and annual percent change of adults who have ever been tested for HIV in Georgia by year of interview: 2011–2015 BRFSS data.

Total 2011 2012 2013 2014 2015
Unwt. N Unwt. N Wt. % (95% CI) Unwt. N Wt. % (95% CI) Unwt. N Wt. % (95% CI) Unwt. N Wt. % (95% CI) Unwt. N Wt. % (95% CI) APC *
Overall GA 11,286 3174 45.6 (44.0, 47.2) 1961 44.3 (42.4, 46.1) 2753 43.6 (42.0, 45.3) 1990 43.7 (41.9, 45.5) 1408 43.7 (41.6, 45.9) −0.98
Gender
Male 4376 1145 45.0 (42.5, 47.6) 746 43.0 (40.1, 45.9) 1101 43.6 (41.1, 46.2) 802 41.9 (39.2, 44.7) 582 43.3 (40.0, 46.5) −1.02
Female 6910 2029 46.1 (44.1, 48.0) 1215 45.5 (43.1, 47.8) 1652 43.6 (41.6, 45.6) 1188 45.4 (43.1, 47.7) 826 44.2 (41.3, 47.0) −0.86
Age (years)
18–24 666 140 42.4 (36.3, 48.8) 352 46.2 (39.9, 52.7) 191 39.5(34.3, 45.0) 122 40.4 (34.5, 46.6) 73 40.1 (32.6, 48.1) −2.43
25–34 1902 540 65.4 (61.1, 69.6) 352 62.5 (57.2, 67.4) 493 62.6 (58.2, 66.9) 297 60.9 (55.8, 65.8) 220 62.9 (56.9, 68.6) −1.03
35–44 2401 712 62.0 (58.4, 65.4) 397 57.2 (52.6, 61.7) 594 60.7 (56.7, 64.6) 411 60.1 (55.5, 64.6) 287 61.8 (56.3, 67.1) 0.43
45–54 2656 769 46.0 (43.0, 49.0) 494 49.3 (45.4, 53.2) 615 44.4 (40.9, 47.9) 461 46.8 (42.9, 50.7) 317 47.9 (43.3, 52.5) 0.29
55–64 2264 653 31.9 (29.4, 34.5) 352 28.8 (25.6, 32.3) 540 33.5 (30.6, 36.6) 406 33.9 (30.6, 37.4) 313 32.6 (29.0, 36.4) 2.09
65+ 1397 360 13.9 (12.3, 15.7) 226 14.6 (12.4, 17.1) 320 16.0 (14.0, 18.2) 293 15.8 (13.9, 18.0) 198 15.6 (13.2, 18.4) 3.15
Race
White, NH 6058 1716 36.9 (35.1, 38.8) 983 33.4 (31.2, 35.6) 1460 36.3 (34.5, 38.2) 978 34.3 (32.2, 36.5) 753 35.2 (32.8, 37.7) −0.68
Black, NH 4201 1127 65.3 (62.1, 68.4) 753 65.6 (62.1, 68.9) 970 59.3 (56.0, 62.6) 772 63.4 (59.9, 66.8) 490 58.3 (53.9, 62.8) −2.58
Hispanic 549 155 40.8 (33.8, 48.1) 88 42.0 (34.0, 50.5) 138 43.9 (37.5, 50.5) 95 38.1 (30.8, 46.0) 67 49.7 (39.5, 60.0) 3.02
Multiracial, NH 237 52 54.2 (41.4, 66.5) 43 59.5 (44.9, 72.7) 60 55.0 (42.2, 67.3) 53 57.1 (42.7, 70.4) 33 69.9 (54.3, 81.6) 4.79
Other, NH 326 79 39.1 (30.6, 48.3) 75 40.2 (31.4, 49.6) 82 29.8 (20.3, 39.3) 49 39.7 (28.4, 51.0) 41 37.1(26.9, 48.5) −1.17
Do not know/Refused 172 45 53.6 (39.8, 66.8) 19 39.3 (22.5, 59.0) 43 45.5 (34.0, 57.6) 43 53.6 (39.9, 66.8) 24 43.2 (26.8, 61.3) -
Education
<High School 1051 280 40.2 (35.5, 45.1) 207 38.0 (32.8, 43.4) 235 36.2 (31.5, 41.3) 181 34.6 (29.4, 40.1) 127 42.0 (35.2, 49.0) −0.06
HS/GED 2722 788 42.0 (39.0, 45.0) 493 40.6 (37.1, 44.1) 628 39.5 (36.5, 42.6) 440 40.1 (36.8, 43.6) 324 40.4 (36.3, 44.5) −0.90
Some Post HS 3371 913 51.8 (48.8, 54.7) 559 47.8 (44.4, 51.3) 820 48.9 (45.9, 52.0) 602 50.3 (47.0, 53.6) 397 46.3 (42.2, 50.4) −1.72
College Grad 4379 1185 46.5 (44.0, 48.9) 696 48.3 (45.3, 51.5) 1066 47.0 (44.5, 49.5) 766 46.0 (43.2, 48.8) 558 45.8 (42.7, 49.1) −0.79
Do not know/Refused 20 8 44.9 (17.4, 75.8) 6 58.7 (29.5, 82.8) 4 40.2 (14.6, 72.6) 1 3.1 (0.4, 21.7) 2 8.8 (1.4, 39.2) -
Annual income (USD ($))
<15,000 1476 394 52.6 (47.5, 57.6) 308 51.1 (45.6, 56.6) 353 49.9 (45.3, 54.5) 249 47.3 (41.4, 53.2) 150 48.7 (41.4, 56.0) −2.29 *
15,000–<25,000 1995 570 49.7 (45.7–53.6) 350 46.8 (42.3–51.4) 475 46.7 (42.7–50.7) 340 42.6 (38.2, 47.1) 231 46.7 (41.2, 52.3) −2.16
25,000–<35,000 1171 335 45.3 (40.5–50.2) 201 45.0 (39.2–50.9) 267 46.6 (41.5–51.8) 201 46.3 (40.7, 52.0) 111 40.4 (33.7, 47.5) −1.98
35,000–<50,000 1332 377 46.1 (41.6, 50.6) 206 42.3 (37.1, 47.7) 337 47.4 (42.7, 52.1) 232 47.2 (42.0, 52.5) 160 49.4 (43.1, 55.8) 2.51
50,000+ 4461 1197 45.0 (42.5, 47.4) 710 43.5 (40.5, 46.5) 1034 42.5 (40.0, 45.1) 771 43.7 (40.9, 46.5) 562 43.9 (40.6, 47.2) −0.45
Do not know/Refused 1108 301 34.9 (30.3, 39.8) 186 36.1 (30.9, 41.7) 287 32.1 (27.8, 36.7) 197 36.8 (31.8, 42.1) 194 35.1 (29.8, 40.7) -
Marital status
Married 5534 1586 41.1 (39.2, 43.1) 890 36.6 (34.3, 39.0) 1218 38.4 (36.3, 40.5) 919 39.1 (36.8, 41.5) 654 37.6 (34.9, 40.4) −1.11
Divorced 2116 574 51.6 (47.6, 55.6) 346 55.0 (50.1, 59.8) 540 56.4 (51.9, 60.8) 363 53.1 (48.2, 57.8) 257 54.2 (48.6, 59.7) 0.63
Widowed 704 204 21.6 (18.3, 25.2) 127 21.7 (17.4, 26.7) 166 20.6 (17.2, 24.6) 151 22.8 (18.4, 27.9) 98 29.7 (23.8, 36.4) 7.10
Separated 512 143 68.5 (59.4, 76.4) 87 69.5 (58.7, 78.6) 140 68.9 (60.0, 76.6) 88 66.5 (55.4, 76.0) 56 62.5 (49.1, 74.1) −2.25
Never married 2255 553 53.7 (49.5, 57.9) 440 54.8 (50.3, 59.1) 585 50.2 (46.3, 54.1) 400 50.4 (46.0, 54.8) 290 53.3 (47.9, 58.5) −0.98
A member of an unmarried couple 366 100 53.6 (43.9, 63.1) 64 61.5 (48.9, 72.6) 90 50.3 (41.4, 59.1) 59 50.2 (38.8, 61.5) 43 44.2 (33.0, 55.9) −5.72
Refused 56 14 39.5 (18.4, 65.4) 7 35.6 (12.0, 69.1) 14 42.5 (23.5, 64.0) 10 53.4 (28.6, 76.7) 10 29.4 (13.3, 53.1) -
Health care coverage
Yes 9216 2541 43.0 (41.3, 44.7) 1524 41.2 (39.3, 43.2) 2157 40.6 (38.9, 42.3) 1662 42.2 (40.4, 44.1) 1215 42.4 (40.1, 44.6) −0.04
No 2303 629 53.6 (49.6, 57.6) 435 54.8 (50.2, 59.3) 584 53.9 (49.9, 57.8) 324 49.5 (44.6, 54.4) 187 51.2 (44.6, 57.7) −1.91
Do not know/Refused 24 4 12.6 (2.3, 43.3) 2 23.4 (2.6, 77.4) 12 51.0 (20.4, 82.2) 4 37.0 (9.6, 76.4) 6 43.9 (8.0, 71.6) -
HIV high risk situations N = 5114 n = 3164 n = 1950
Yes 211 130 74.0 (63.8, 82.1) 81 69.4 (58.1, 78.7) N/A N/A N/A N/A N/A N/A -
No 4884 3020 44.2 (42.6, 45.8) 1864 43.2 (41.3, 45.1) N/A N/A N/A N/A N/A N/A -
Do not know/Refused 19 14 75.3 (41.8, 90.0) 5 25.0 (6.0, 49.4) N/A N/A N/A N/A N/A N/A -
Overall USA 608,484 132,471 35.9 (35.6, 36.2) 128,927 35.3 (35.0, 35.5) 130,922 35.9 (35.6, 36.2) 115,866 34.4 (34.1, 34.7) 113,779 38.0 (37.7, 38.3) 0.88

Acronyms: Unwt. N—unweighted counts, Wt. %—weighted population estimates, CI—confidence interval, APC—Annual Percent Change, NH—non-Hispanic, GED—General Educational Development, N/A—data not available. Note: p-values were significant for the association between all the socio-demographic categories and having ever been tested for HIV. * APC was not significantly different from zero at alpha = 0.05 for all the variables, except annual income <$15,000. (-) APC was not calculated for respondents who do not know or refused to respond to questions asked, and for HIV high risk situations. USD—United States Dollar.

Overall, for the period of 2011–2015 (results not shown in Table 2), approximately 60% of persons between the ages of 25 and 44 had been tested for HIV, compared to <50% of those aged 18–24 and greater than 45 years of age (p < 0.001). Also, the highest percentages of testers were among NH black respondents (62.4% vs. 35.2% white and 42.8% Hispanic (p < 0.001). Fewer persons with healthcare coverage compared with those with no coverage (41.9% and 52.8%, respectively, p < 0.001); and almost 50% of respondents with greater than high school education, earning annual income of <$15,000 (50%), separated (67%), or in an unmarried couple relationship (52%) had been tested for HIV. More persons engaged in high-risk behaviors had been tested for HIV than those who had not (71.8% vs. 43.7%; p < 0.001). Data for HIV high-risk activities and for the type of healthcare coverage were available for only 2011–2012 and 2014, respectively. As shown in Figure 1, respondents on the military (Tricare) plan were the highest testers (68.2% (95% CI = 58.9%–76.2%)), followed by those on Medicaid (66.9% (95% CI = 56.1%–76.1%)).

Figure 1.

Figure 1

Weighted percentages of adults who have ever tested for HIV in Georgia based on the type of healthcare coverage: BRFSS 2014 data. Note: Error bars indicate 95% confidence intervals for each estimate.

3.3. Socio-Demographic Determinants of HIV Testing in GA

In Table 3 are the results of logistic regression analyses for the association between socio-demographic factors and the dependent variable, having ever been tested for HIV, after adjusting for all the variables in the model. Excluded from the model is the variable HIV high-risk situations, because data were available only for 2011 and 2012. Except for healthcare coverage, all the variables entered had a significant effect on the model. Females (OR = 1.13 (95% CI = 1.04, 1.23); p = 0.004), NH black/African American respondents (OR = 2.82 (95% CI = 2.54, 3.12); p < 0.001), and respondents of other ethnic groups combined (OR = 0.97 (95% CI = 0.85, 1.12); p = 0.70) were more likely to have been tested than males, and NH white respondents, respectively. People who were younger than 55 (18–54 years) were more likely than older people to have tested for HIV (OR = 2.58 (95% CI = 2.31, 2.89); p < 0.001). The likelihood of being tested for HIV was also associated with levels of education greater than high school (OR = 1.46 (95% CI = 1.31, 1.63); p < 0.001), being single (OR = 1.22 (95% CI = 1.11, 1.34); p < 0.001), and earning annual income of less than $50,000 (OR = 1.18 (95% CI = 1.04, 1.34); p = 0.01 for <$25,000 and OR = 1.14 (95% CI = 1.01, 1.28); p = 0.03 for $25,000–$50,000 annual income), compared to less than high school education, being in a couple relationship, and earning more than $50,000 annually, respectively. Having healthcare coverage was not significantly associated with HIV testing.

Table 3.

Logistic regression analysis of socio-demographic factors associated with having ever been tested for HIV in Georgia: BRFSS 2011–2015.

Variable Odds Ratio 95% CI p-Value
Gender
Female 1.134 1.041, 1.234 0.004
Male Reference
Age (years)
18–34 2.583 2.306, 2.894 <0.001
35–54 2.578 2.344, 2.836 <0.001
≥55 Reference
Race
Black, NH 2.815 2.538, 3.122 <0.001
Others 0.973 0.845, 1.120 0.701
White, NH Reference
Education
College graduate 1.463 1.313, 1.631 <0.001
Some post high school 1.462 1.311, 1.630 <0.001
≤HS Reference
Income
<25,000 1.178 1.035, 1.342 0.013
25,000–50,000 1.138 1.014, 1.277 0.028
>50,000 Reference
Marital status
Single 1.216 1.106, 1.337 <0.001
Couple Reference
Healthcare coverage
No 1.046 0.927, 1.179 0.467
Yes Reference

4. Discussion

BRFSS data from 2011 to 2015 (the years of the most current data) were analyzed to examine the temporal trends and socio-demographic factors associated with HIV testing among adults in GA. Overall in GA, there was a slight decrease in the percentages of respondents who had ever been tested for HIV, from 45.6% in 2011 to 43.7% in 2015, with a non-significant APC. During this time, the annual percentages of those tested were higher for GA compared to the national rates (35.9% in 2011, 38.0% in 2015). The factors associated with HIV testing included being female, black/African American, single, younger than 55 years, having greater than high school education, and earning $50,000 or less annually.

The results of the current study show that the HIV testing trends were stable between 2011 and 2015, however, less than half of the adults living in GA had been tested for HIV. Results of earlier studies conducted nationally and in other parts of the U.S. [27,28] show that the percentages of adults who had ever tested for HIV increased significantly between 2000 and 2010 (36.6% in 2000, 45.0% in 2010, p < 0.0001) [27]. A study that analyzed data from the Southeastern Pennsylvania Household Health Survey between 2002 and 2010 to evaluate HIV testing over time, reported that testing trends increased among all demographic groups, but existing differences in testing before 2006 persisted after that year as follows: younger patients, racial/ethnic minorities, and patients on Medicaid were all more likely to get tested than their counterparts [28].

Barriers to HIV testing include HIV-related stigma, sexuality, religion, race, and class, emphasizing responsibility, testing concerns, and media influences [29,30]. The percentages of respondents who had been tested for HIV were highly associated with the presence of HIV risk factors and with self-reported current risks of contracting HIV. Racial minorities, younger persons, especially young black/African American (men having sex with men (MSM)), have the highest risk and prevalence of HIV/AIDS [28]. Gay, bisexual, and other men who have sex with men accounted for an estimated 2% of the total population, and 55.0% of people living with HIV in the United States in 2013 [31]. Georgia is among the states with the highest population of MSM and African Americans [7,32], and this may account for the higher rate of HIV testers in GA, compared to the national rate. HIV risk is associated with low socio-economic status among heterosexual populations [33] and the current study shows that lower income earners and those without healthcare coverage were more likely to test for HIV. However, this does not explain why the participants that attained educational levels greater than high school tested more than those with high school or lesser education. A possible explanation may be that a great proportion of the study participants were educated beyond high school.

A similar study by Handel et al. (2016), analyzed the BRFSS data for 2011–2013, and reported that a national average of 33% of young adults (18–24 years) had tested for HIV [34]; the average for the same age group in GA was approximately 40.0% as reported by the current study. The Handel study also showed that a significant decrease in the prevalence of HIV testing was detected overall from 42.4% in 2011 to 39.5% in 2013 among young adult females nationally, with significant racial/ethnic differences in the rates of decline (9.0% decrease among young adult black females, and 3.3% decrease among young adult white females).

A disadvantage of low HIV testing among persons who are perceived as low-risk is the missing of opportunities to diagnose HIV-infected persons and linking them to care. Reasons for fewer people with healthcare coverage not being tested may be because (a) routine HIV testing is not offered in the places where most people get their health care and (b) awareness of CDC’s 2006 recommendations for HIV screening has been low among primary care providers [35,36]. Release of the United States Preventive Services Task Force recommendations for HIV testing in 2013, and the provision of the Affordable Care Act that both HIV screening and targeted risk-based testing are now covered without cost-sharing as part of the essential benefits package, may boost future HIV testing rates [36].

A strength of the present report is the utilization of the most currently available BRFSS data. It is also among the few studies that have examined the trends of HIV testing with the APCs, and the associated socio-demographic factors of HIV testing and is the only report solely for the state of GA. There are some limitations. The BRFSS data are self-reported by respondents and are subject to recall bias. The survey is based on non-institutionalized populations and excludes persons with the same risk of exposure who are residing elsewhere, such as nursing homes or long-term-care facilities. Since data are collected by telephone, individuals who live in households without a residential telephone or cell phone are not included. Further, the sampling frame of the BRFSS is the entire state; therefore, some rural areas might be represented by relatively few interviews. Because of these limitations, the results might be either underestimated or overestimated. Despite these limitations, data from the BRFSS are reliable and generally valid because the content of the survey questions, questionnaire design, data collection, procedures, interviewing techniques, and data processing have been developed to improve data quality [37].

5. Conclusions

Between 2011 and 2015, the percentage of adults in GA who have ever been tested for HIV has remained stable, with less than 50% now reporting to have been tested. In GA, increasing access to and utilization of HIV testing should be a public health priority, and more programs that will increase awareness to recommendations for testing among healthcare providers are warranted.

Acknowledgments

This work was funded by the National Cancer Institute (1R01CA166785) and the National Institute on Minority Health and Health Disparities (1P20MD006881).

Author Contributions

Benjamin Ansa contributed to the conception, design, statistical analysis, writing, and submission of the manuscript; Yunmi Chung and Sashia White contributed to the statistical analysis and editing of the manuscript; and Selina A. Smith reviewed and edited the manuscript. All authors read and approved the final manuscript.

Conflicts of Interest

The authors declare no conflict of interest.

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