WARD ET AL.HIV/AIDS RISK PERCEPTION

PERCEPTION OF HIV/AIDS RISKAMONG URBAN, LOW–INCOMESENIOR-HOUSING RESIDENTSElijah G. Ward, William B. Disch, Judith A. Levy,and Jean J. Schensul

Despite the rising number of cases of HIV in adults over age 50, older personsrarely are considered to be at risk for HIV/AIDS, and even though they may beinvolved in risky behavior, such as unprotected penetrative sex, they may notconsider themselves vulnerable to becoming infected. Informed awareness of riskis essential to making positive decisions about adopting preventive measures. Weexamined demographic, sociobehavioral, and contextual factors that predict ur-ban, low–income older adults’ perception of HIV/AIDS risk. Logistic regressionresults from 398 residents aged 50–93 living in six buildings in two American cit-ies found that males, younger participants (aged 50–61), those living in higherrisk buildings, and those who worried more about contracting HIV/AIDS weremore likely to perceive themselves to be at HIV/AIDS risk. Findings accountedfor 32% of the variance and the prediction success rate was 72%. Results pointto the importance of considering sociodemographic characteristics and environ-mental (contextual) factors as they influence heuristic decision making in under-standing HIV/AIDS risk perception among low–income urban older adults andwhen designing HIV/AIDS education and intervention strategies targeting thispopulation.

Perception of risk for HIV/AIDS, defined for the purposes of this article as individuals’subjective perceptions of their own likelihood of contracting the virus, has interestedboth researchers and interventionists because of the centrality of risk perception tohealth beliefs, and cognitive–behavioral and social learning models of health behavior(Ajzen & Fishbein, 1980; Bandura, 2001; Prochaska & DiClemente, 1986; Rogers,1983). These models presume that the individual’s perception of risk is a necessary an-tecedent to self–protective changes in behavior. According to these models, increasedknowledge and awareness of the dangers of HIV infection through personal behaviormotivates individuals to select self–protective or less risky actions (e.g., Catania,

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AIDS Education and Prevention, 16(6), 571–588, 2004© 2004 The Guilford Press

Elijah G. Ward and Judith A. Levy are with the University of Illinois at Chicago, School of Public Health.William B. Disch and Jean J. Schensul are with the Institute for Community Research, Hartford, CT.This research was supported by National Institute on Aging Grant R01–AG16564 to Jean J. Schensul,Ph.D., principal investigator, and Judith A. Levy, Ph.D., co–principal investigator. Special appreciation toKim Radda, M.A., R.N., project director, and the field research teams in Chicago (McKenzie Smith, M.A.,and Milton Armston, M.A.) and Hartford (Kenneth Brockman, Evelyn Baez, Pablo Feliciano, and GustavoLopez).Address correspondence to Elijah G. Ward, Institute for Health Research and Policy, 1747 West RooseveltRd. #558, Chicago, IL 60608–1264; e–mail: ELIJAHAL@UIC.EDU.

Kegeles, & Coates, 1990; Corby & Wolitski, 1996; Fisher & Fisher, 1992; Gerrard,Gibbons, & Bushmen, 1996). Understanding which factors predict the individual’sperception of risk (including personal risk) is therefore essential to designing effectiveHIV/AIDS prevention programming.

This article presents findings from the AIDS Risk in Older Urban Adult SeniorHousing Residents study, which was designed to identify factors exposing olderadults in senior housing to HIV/AIDS risk. An objective of the study was to identifypotentially effective strategies to reduce risk behaviors and HIV transmission in thispopulation. Identifying factors that influence residents’ perception of risk constitutesan important step toward meeting this goal.

HIV/AIDS AMONG OLDER ADULTSHIV infection among people over age 50 remains largely unrecognized by scientistsand AIDS preventionists despite a steady increase over the last decade in the preva-lence of HIV in this age group. Until 1995, adults aged 50 and older made up approxi-mately 10% of each year’s new cases of AIDS. This percentage grew from 11% in1995 to 14% in 1999. In 2000, the rate of AIDS cases diagnosed per 100,000 adultsaged 50 and older was 8.2 (Centers for Disease Control and Prevention [CDC], 2003).Current estimates indicate that today over 50,000 older Americans are living withAIDS (Mack & Ory, 2003).

As with HIV/AIDS in general, AIDS in adults aged 50 and older occurs dispropor-tionately among ethnic minorities. The 2000 AIDS Public Information data set indi-cates that African Americans, Latinos, and all ethnic minorities collectively in theUnited States, aged 50 years and older, constituted 49%, 19%, and 69%, respectively,of all new AIDS cases reported for this age category during 1999 (Mack & Ory,2003). This is so, even though African Americans, Latinos, and all ethnic minoritiescollectively account only for 12%, 13%, and 25%, respectively, of the U.S. popula-tion, according to U.S. Census Data for 2000. To prevent further acceleration of HIVinfection in older minority adults, as well as older adults in general, we must under-stand more about the conditions under which they are exposed to HIV and the atti-tudes, beliefs, and practices that promote or reduce the risk of transmission.

RISK PERCEPTIONAlthough evidence shows that risk perception may shape HIV/AIDS risk–related be-havior (e.g., Corby & Wolitski, 1996; Gerrard et al., 1996), little is known aboutwhat shapes risk perception. The bases and processes of decision making that influ-ence self–assessment are poorly understood and may be unknown (Brown, Outlaw, &Simpson, 2000; Kowalewski, Henson, & Longshore, 1997; Prohaska, Albrecht,Levy, Sugrue, & Kim, 1990). Although the literature reports a number of factors to beassociated with risk perception, findings often conflict across studies and produce in-consistent and inconclusive results that preclude effective synthesis. Kowalewski et al.(1997) attributed this lack of consensus to (a) measurement inconsistencies acrossstudies that prevent cross–study comparisons, (b) subpopulation and behavioral dif-ferences among subjects that are inadequately addressed in research study designs andimplementation, and (c) unexamined but critical contextual factors shaping perceivedrisk.

One of the characteristics that makes risk perception both theoretically and prac-tically of interest is the wide variation in the percentage of respondents, ranging from

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18% to 85%, who see themselves at some level of risk. Research by Brown (2000);Dolcini, Catania, Choi, Fullilove, and Coates (1996); Facente (2001); Ford andNorris (1993); Holtzman, Bland, Lansky, and Mack (2001); Inman (1999); Maurierand Northcutt (2000); and Prohaska et al. (1990) has suggested that factors such asage, marital status, work, and differences in individual and group social circumstancemay account for broad variation in the risk perception reported across populations.

From the standpoint of both scientific and heuristic decision making,sociodemographic categories such as age, gender, ethnicity, religion and education, aswell as sociocognitive and behavioral factors including worry, HIV/AIDS knowledge,number of sex partners and condom use, have been found to predict risk perceptionfor HIV/AIDS in some but not all studies. For example, Liverpool, McGhee, Lollis,Beckford, and Levine (2002) and Newman and Zimmerman (2000) found gender tobe associated with risk perception, whereas as Prohaska et al. (1990) did not. Para-doxically, Stevenson, Gay, and Josar (1995) found a positive relationship betweenperceived risk and HIV/AIDS knowledge, yet others found a negative relationship(Burkholder, Harlow, & Washkwich, 1999; Melkote & Muppidi, 1999). Thus, re-sults from studies using sociodemographic and sociobehavioral variables to predictperception of risk for HIV/AIDS are mixed and in some instances contradictory (e.g.,Dolcini et al., 1996; Holtzman et al., 2001; Liverpool et al., 2002; Maurier &Northcutt, 2000; McBride, Weatherby, Inciardi, & Gillespie, 1999; Miller & Gur,2002; Singer, Dai, Weeks, & Malave, 1998). Many of these investigators agree thatpeople’s perceptions of risk are based at least in part on factors that do not necessarilyreflect objective reality or scientific fact.

THE ROLE OF HEURISTICSTheoretical approaches, which presume that community and reference group mem-bership produce distinctive ways of viewing the world, can help to explain commonpatterns of risk perception among individuals of similar background (Wight, 1999).Shared worldviews engender particular heuristic understandings (common senseframeworks or intuitive tools) based on shared experience, culture, or other forms ofgroup self–identity that in turn shape risk behaviors. For example, rather than con-front the mathematical challenges of scientifically predicting low–probability eventssuch as contracting HIV/AIDS, individuals may rely instead on personal heuristics,derived though culture and other group membership, to make sense of and calculatethe likelihood of experiencing various risks encountered in daily life (Alario &Freudenberg, 2003; Douglas, 1985; Fischhoff & De Bruin, 1999).

Some cognitive theorists have begun to use heuristic categories to explain riskperception (Kowalewski et al., 1997; Prohaska et al., 1990). In doing so, they under-score the mediating role of cultural factors in people’s social construction of realityand in their lay interpretations of health and illness. In this view, demographic vari-ables form reference categories that define group membership and in turn forge mem-bers’ expectations about their own current and future health and well–being. Forexample, a 32-year-old Puerto Rican male, encountering media messages identifyingmaleness, youth, and Puerto Rican ethnicity as high–risk categories, is more inclinedto perceive his own behavior as being at risk for HIV/AIDS than would a White femaleof similar age upon hearing this same message. Such identification may occur whetheror not the listener actually engages in risky behavior. Thus, demographic factors canshape subjective risk perception indirectly by affecting one’s view of self or othersthrough popular assumptions about group categorization and/or cultural interpreta-

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tions of HIV/AIDS risk typographies (Kowalewski et al., 1997; Lowy & Ross, 1994;Prohaska et al., 1990).

MEASURING AND PREDICTING HIV/AIDS RISK PERCEPTIONThe current study adds to the growing body of literature and debate over mixed find-ings by examining risk perception among older men and women who share the com-mon characteristics of being over age 50, residents of low–income housing, andmostly members of U.S. racial/ethnic minorities. The age of our sample, which is no-ticeably older than the samples of most commonly cited studies of HIV/AIDS risk per-ception, offers insight into a demographic category (older adulthood) at increasingHIV/AIDS risk that has received little scientific attention to date (Schensul, Levy, &Disch, 2003). Based on Davis, Duncan, Turner, and Young’s (2001) findings thatolder adults believe their vulnerability to HIV and STDs declines with age and reducedsexual activity, it was expected that the proportion of the sample who perceived them-selves to be at risk for HIV/AIDS would be lower than figures reported in the literaturefor younger adults. In addition, based on findings reported for younger individuals, itwas hypothesized that younger (aged 50–61) male residents would see themselves athigher risk than would older male residents (aged 62–93) and all females. It was alsoexpected that despite comparatively lower rates, Latinos might view themselves atgreater risk for infection than African Americans because of language and other cul-tural barriers that might restrict access to accurate information about HIV/AIDS andits prevention (Dolcini et al., 1996; Singer et al., 1998). As with younger samples, itwas also anticipated that risk perception would be higher for those with less formaleducation and HIV/AIDS knowledge, greater involvement in sexually risky behavior,and those who worried more about contracting the virus because they may have goodreason to do so.

The current study also extends the literature on understanding risk perception forHIV/AIDS by assessing the influence of environment (sociospatial context) onHIV/AIDS risk. Residential buildings, in this case senior- or public-housing buildings,vary on many dimensions including physical size, ownership, administrative struc-ture, tenant policies, and such neighborhood features as proximity to or involvementin criminal activity, commercial sex trade, and/or active drug trafficking (Schensul etal., 2003). Thus, different buildings carry different degrees of health risk for their resi-dents. It was expected that residents living in buildings that offered greater exposureto crime, commercial sex, and/or the drug trade (i.e., greater proximity to HIV/AIDSrisk factors) would be more likely to see themselves at risk for HIV/AIDS than thoseliving in buildings where exposure to HIV/AIDS was lower.

In recent years, researchers have paid increasing attention to the sexual behaviorsof older adults and to understanding associated HIV/AIDS–related behaviors and is-sues (Coleman, 2003; Emlet & Farkas, 2002; Goodroad, 2003; Heckman et al., 2002;Klein et al., 2001; Mack & Bland, 1999). At the same time, there has also been an in-crease in attention to HIV/AIDS–related behaviors and health concerns of minorityolder adults (e.g., Butt et al., 2001; Heckman et al., 2000; Lee, Ross, Mizwa, & Scott,2000; Poindexter & Linsk, 1999; Rodgers–Farmer, 1999; Sellers & Angerame,2002). To date, however, virtually no research has examined perceived risk ofHIV/AIDS in this mature adult population. The present analysis of a sample of mainlyAfrican American and Latino older adults living in senior housing addresses this gap.Results from this study can help health providers better understand and enhance the

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delivery of HIV/AIDS prevention, education, and other HIV/AIDS services for peopleover 50.

METHODData for this analysis were drawn from an epidemiological and qualitative study ofHIV/AIDS that explored drug– and sex–related risk behaviors, environmental(sociospatial) features, social network characteristics, and individual–level factors as-sociated with HIV/AIDS risk exposure in senior housing buildings in two cities: Hart-ford, Connecticut, and Chicago, Illinois. Nine buildings, six in Hartford and three inChicago, were selected for locations within neighborhoods characterized by heavycommercial sex and drug-trafficking activity. An early ethnographic phase of thestudy confirmed that commercial sex workers, drug distributors, and users frequentedthe nine buildings. Such socioenvironmental characteristics are associated with highHIV/AIDS prevalence rates (Schensul et al., 2003).

Data collection involved (a) ethnographic observations of building environmentsand their residents, concentrating on observed behavioral and material evidence ofdrug and sexual risk behaviors, (b) observations and informal interviews with resi-dents to determine any structural features of the buildings that would enable risky be-havior, and (c) an epidemiological survey of each building involving face–to–faceinterviews with residents, including a social network component designed to assesspotential routes of HIV and STI (i.e., sexually transmitted infection) transmission.The goal of this multilevel investigation was to gain sufficient data and understandingto enable effective prevention planning.

To gain social entry into the buildings, and to gain the trust and cooperation ofbuilding residents, we offered interactive educational sessions on medications, nutri-tion, social security, budget management, and chronic diseases in response to residentinterest, as well as bingo games. Before initiating the study, we posted informationand held orientation sessions describing the project and survey. Residents received fly-ers (door to door) before survey initiation and recruitment. To qualify for the study,residents had to be building residents living independently (that is, without conserva-tors or live–in formal assistance). Upon giving written informed consent, they alsowere invited to participate in HIV testing using OraSure—a simple oral, noninvasiveHIV testing option. Enrollment in the study was not contingent upon agreeing to betested. Participation rates in the buildings ranged from 62% to 80% for the surveyand 85% across all buildings for the OraSure test.

PARTICIPANTSThe sample for this article consisted of 398 residents aged 50–93 (Table 1).

Forty–eight percent (n = 192) resided in two large buildings in Chicago and 52% (n =206) were recruited in four smaller buildings or building complexes in Hartford. Themean and median ages of participants were 67 years.

MEASURESA survey instrument elicited information on the following topics: demographics;

risk behaviors (sexual activity and drug use history); knowledge, attitudes, and opin-ions about HIV/AIDS; and social networks. The domains of interest for this article aredelineated below.

Perceived HIV/AIDS Risk. The dependent variable for this analysis, perceivedHIV/AIDS risk, was measured with a single item: “How likely do you think you are to

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become infected with HIV/AIDS?” Response choices were Likert–scaled (1 = not at alllikely, 5 = certain). Forty–five percent of respondents indicated “not at all likely,”30% indicated “unlikely,” 14% responded “somewhat likely,” 5% indicated “verylikely,” and 0.5% said “certain.” An additional 17 participants (4.3%) indicated“don’t know/unsure,” and 4 participants (1%) indicated being already HIV-positive.Because almost half of respondents indicated “not at all likely,” responses weredichotomized into not at risk for HIV/AIDS versus at risk for HIV/AIDS, similar to thecategorization followed by Prohaska et al. (1990). Those who responded “don’tknow/unsure” were included in the at risk group because of their unwillingness to se-lect the “not at all likely” category. The four HIV-positive participants were includedin the at risk group because their situation was deemed to be qualitatively more similarto that of participants who saw themselves to be at risk (especially those whoresponded “certain”) than to that of those who perceived no risk at all.

Demographics. As shown in Tables 1 and 2, demographic variables included age,gender, ethnicity, religious affiliation, education, city, and building residence. Envi-ronmental (sociospatial) context for risk was assessed with an index formed from theresults of ethnographic observations and other evidence of drug, sex, and other riskbehaviors in and around the buildings and surrounding neighborhoods. Buildings (see

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TABLE 1. Demographic Information by Overall, City, and Gender

Overall Chicago Hartford Men WomenVariable N = 398 n = 192 n = 206 n = 203 n = 195Age

Mean (SD) 67.4 (10.6) 67.0 (11.4) 67.7 (9.9) 65.7 (10.1) 69.1 (10.9)Median 67.0 66.5 67.0 65.0 70.0

CityChicago 192 (48%) 98 (48%) 94 (48%)Hartford 206 (52%) 105 (52%) 101 (52%)

GenderMen 203 (51%) 98 (51%) 105 (51%)Women 195 (49%) 94 (49%) 101 (49%)

EthnicityBlack/African American 271 (68%) 190 (99%) 81 (39%) 131 (65%) 140 (72%)Latino 97 (24%) 0 97 (47%) 55 (27%) 42 (22%)Other 30 (8%) 2 (1%) 28 (14%) 17 (8%) 13 (6%)

ReligionCatholic 101 (25%) 14 (7%) 87 (42%) 59 (29%) 42 (22%)Protestant 250 (63%) 150 (79%) 100 (49%) 121 (60%) 129 (66%)Other (including none) 47 (12%) 28 (14%) 19 (9%) 23 (11%) 24 (12%)

Length of time in building (years)Mean (SD) 7.3 (7.6) 6.7 (6.0) 7.9 (8.7) 6.7 (6.1) 8.0 (8.8)Median 5.0 5.0 6.0 5.0 6.0

Level of educationLess than high school graduation 286 (72%) 122 (64%) 164 (80%) 143 (70%) 143 (73%)

Marital StatusSingle 76 (19%) 36 (19%) 40 (19%) 49 (24%) 27 (14%)Married/Cohabitating 38 (10%) 7 (4%) 31 (15%) 24 (12%) 14 (7%)Separated 66 (17%) 37 (19%) 29 (14%) 41 (20%) 25 (13%)Divorced 93 (23%) 45 (23%) 48 (24%) 56 (28%) 37 (19%)Widowed 125 (31%) 67 (35%) 58 (28%) 33 (16%) 92 (47%)

Work statusNot working 374 (94%) 183 (95%) 191 (93%) 189 (93%) 185 (95%)Monthly income less than $700/mo. 281 (71%) 132 (69%) 149 (72%) 135 (67%) 146 (75%)

Table 2) were coded according to environmental risk with 1 being lowest in risk and 6being highest. Age was grouped into three categories: 50–61, 62–73, and 74–93. Agegroupings were defined on the basis of those in preretirement (ages 50–61), those whomay or may not be retired (ages 62–73), and retirees (ages 74–93).

HIV/AIDS–Related Variables. These variables included worry about contract-ing HIV, which was measured by asking respondents if they agreed or disagreedwith the statement: “I never worry about becoming infected with HIV/AIDS.” Levelof knowledge about HIV/AIDS was assessed using a summation index of correct re-sponses (yes or no) to 12 items drawn from existing HIV/AIDS knowledge scalessuch as “Do you think women can get AIDS by having sex with men, if they don’t usea condom?” and “Do you think you are safe if you stick yourself with a needle that aperson with AIDS has used?” Coefficient alpha was .70. Prior HIV testing was as-sessed by asking participants to respond yes or no to whether they had ever beentested for HIV. Sexual behavior and drug use behavior were measured by askingabout past and current illicit drug and alcohol use, sexual activity (vaginal, oral,anal), condom use, whether or not the informant’s sexual partner had sex with oth-ers, and exchanges of sex for drugs or money including sexual activity withcommercial sex workers.

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TABLE 2. Demographic Information by Building (Ranked by overall cumulative sex and drug risk, 1 =lowest, 6 = highest)

Building 1 Building 2 Building 3 Building 4 Building 5 Building 6n = 26 n = 49 n = 67 n = 120 n = 72 n = 64

Variable Hartford Hartford Hartford Chicago Chicago HartfordAge

Mean (SD) 74.5 (8.0) 68.3 (9.0) 70.9 (9.6) 68.2 (11.7) 65.1 (10.7) 61.0 (7.7)Median 74.0 70.0 71.0 69.0 65.0 60.0

GenderMen 6 (23%) 23 (47%) 36 (54%) 59 (49%) 39 (54%) 40 (62%)Women 20 (77%) 26 (53%) 31 (46%) 61 (51%) 33 (46%) 24 (38%)

EthnicityBlack/African American 22 (84%) 3 (6%) 38 (57%) 118 (98%) 72 (100%) 18 (28%)Latino 2 (8%) 36 (74%) 15 (22%) 0 0 44 (69%)Other 2 (8%) 10 (20%) 14 (21%) 2 (2%) 0 2 (3%)

ReligionCatholic 2 (7%) 34 (69%) 20 (30%) 13 (11%) 1 (1%) 31 (49%)Protestant 20 (77%) 7 (14%) 44 (66%) 89 (75%) 61 (85%) 29 (45%)Other 4 (16%) 8 (17%) 3 (4%) 18 (14%) 10 (14%) 4 (6%)

Length of time in building (years)Mean (SD) 9.0 (17.2) 5.9 (6.5) 10.1 (7.4) 6.8 (6.1) 6.7 (5.9) 6.7 (5.5)Median 5.0 3.0 10.0 5.0 4.0 6.0

Level of educationLess than high school graduation 21 (81%) 36 (73%) 49 (73%) 68 (57%) 54 (75%) 58 (91%)

Marital statusSingle 4 (15%) 7 (14%) 15 (22%) 20 (17%) 16 (22%) 14 (22%)Married/Cohabitating 0 14 (29%) 5 (8%) 3 (3%) 4 (5%) 12 (19%)Separated 2 (8%) 8 (16%) 10 (15%) 22 (18%) 15 (21%) 9 (14%)Divorced 4 (15%) 11 (23%) 18 (27%) 33 (27%) 12 (17%) 15 (23%)Widowed 16 (62%) 9 (18%) 19 (28%) 42 (35%) 25 (35%) 14 (22%)

Work statusNot working 25 (96%) 47 (98%) 58 (87%) 113 (94%) 70 (97%) 61 (95%)

Monthly incomeLess than $700/mo. 13 (50%) 39 (80%) 47 (70%) 81 (68%) 51 (71%) 50 (78%)

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Data analyses were performed using the SPSS statistical software package, Ver-sion 11. Data were screened for assumption violations, as well as possiblemulticollinearity and singularity (Tabachnick & Fidell, 1996), and no transforma-tions were performed. Missing data were fewer than 1% and were randomly scatteredacross the sample. Necessary replacements were made by case–by–case imputationusing similar items highly related to the missing response.

TABLE 3. Descriptive Statistics and p–Values for the Significant and Non–SignificantPredictor Variables

No Perceived Yes for PerceivedHIV/AIDS Risk HIV/AIDS Risk

Variable n = 181 (45%) n = 217 (55%) p–ValueAge group p < .01 (χ2)

50-61 years 38 (10%) 95 (24%)62-73 years 63 (16%) 80 (20%)74-93 years 80 (20%) 42 (11%)

Gender p < .01 (χ2)Men 75 (19%) 128 (32%)Women 106 (27%) 89 (22%)

Worry p < .01 (χ2)Worriers 43 (11%) 114 (27%)Nonworriers 138 (35%) 103 (26%)

Building p < .01 (χ2)1 (n = 26) 12 (3%) 14 (4%)2 (n = 49) 8 (2%) 41 (10%)3 (n = 67) 39 (10%) 28 (7%)4 (n = 120) 71 (18%) 49 (12%)5 (n = 72) 37 (9%) 35 (9%)6 (n = 64) 14 (4%) 50 (13%)

Ethnicity p < .01 (χ2)African American 145 (36%) 126 (32%)Latino 25 (6%) 80 (20%)Other 11 (3%) 11 (3%)

Education p = ns (χ2)Less than hs education 131 (33%) 155 (39%)HS graduate/Technical school 34 (9%) 37 (9%)At least some college 16 (4%) 25 (6%)

Monthly Income p = ns (χ2)Less than $700/mo. 125 (32%) 156 (40%)$701 or more/mo. 54 (14%) 58 (15%)

HIV/AIDS knowledge p < .05 (t)Mean = 20.3 Mean = 20.9

SD = 2.6 SD = 2.4Sexual activity p < .01 (χ2)

Sexually active 58 (15%) 110 (28%)Not sexually active 123 (31%) 107 (27%)

Number of sex partners (of n = 168, only those sexually active) p = ns (t)Mean = 1.6 Mean = 1.7

SD = 1.2 SD = 1.6Condom use (of n = 168, only those sexually active, 58 [35%]not at risk, 110 [65%] at risk) p = ns (χ2)

Always uses condom 14 (8%) 20 (12%)Does not always use condom 44 (26%) 90 (54%)

Sex with commercial sex workers (of n = 168, only those sexually active) p < .05 (χ2)Always uses condom 51 (30%) 82 (49%)Does not always use condom 7 (4%) 28 (17%)

RESULTSOf the 398 respondents included in our sample, 217 (55%) saw themselves at somelevel of risk, even if slight, and 181 (45%) perceived themselves to be at no risk forcontracting HIV/AIDS. Binary logistic regression analyses were performed to assesssignificant predictors of perceived HIV/AIDS risk from a set of theoretically basedvariables obtained through a literature search and ethnographic observations. Predic-tors for the first analysis included age group, gender, ethnicity, education, income,building, and the following set of socio–behavioral variables: HIV/AIDS knowledge,worry, sexually active or not, number of partners, condom use, and sex with commer-cial sex workers. Because only 4% of respondents in our study reported having no reli-gious affiliation, we were unable to use religion as a predictor. Similarly, almost norespondents reported injection drug use, a key risk factor for HIV transmission, norany other form of drug use, so drug use was also excluded from the analysis. Of the398 respondents, 168 (42%) reported being sexually active. Four individuals indi-cated being HIV positive at the time of the survey. In addition, four new HIV/AIDScases were identified from the 339 (85%) of participants that OraSure tested.

A second logistic regression was performed using only the significant predictors(age group, building, and worry). Gender, although not significant in the preliminaryanalysis, was included because of the observed differences in risk–related behavior be-tween genders in this population. See Table 3 for descriptive statistics and p values forthe significant and nonsignificant predictor variables.

A test of the full model with the four predictors against a constant–only modelwas statistically significant, χ2 (9, N = 398) = 106.94, p = < .001, indicating that theoverall set of predictors reliably distinguished between participants’ perceptions ofbeing at risk or not being at risk for HIV/AIDS (see Table 3). Total variance accountedfor was moderate (32%), using Nagelkerke’s statistic (pseudo R2). The prediction suc-cess was acceptable, with 70.2% of those perceiving themselves to not be at risk, and73.7% of those perceiving themselves to be at risk being correctly predicted. Theoverall prediction success rate was 72.1%.

According to the Wald criterion, the younger two age groups referenced with theoldest age group (74-93 years), Wald (B/SE) = 22.10, p < .001 for 50- to 61-year-olds,and Wald = 7.06, p < .01, for 62- to 73-year-olds, being male, Wald = 5.61, p < .05, be-ing worried about HIV contraction, Wald = 19.88, p < .001, and being a resident ofthree of the buildings referenced with a high–risk building, Wald = 9.25, p < .01 forBuilding 3, Wald = 7.58, p < .01 for Building 4, and Wald = 5.27, p < .05 for Building5, were significant predictors of perceived risk of contracting HIV/AIDS. Results indi-cate that the overall set of four predictors (gender, age group, worry about HIV/AIDSand building residency) distinguished between participants who reported perceivingthemselves to be at risk for contracting HIV and those who did not.

Odds ratios were calculated to determine the relative likelihood of predictabilityfor participants who saw themselves at risk for HIV/AIDS. See Table 4 for regressioncoefficients, Wald statistics, odds ratios, and 95% confidence intervals for odds ratiosfor the significant predictors. Results indicate that the younger age group (50 to 61years) was 4.4 times more likely, and the mid–older age group (62-73 years) was 2.1times more likely than the older age group (74-93 years) to self–perceive being at riskfor contracting the virus. In addition, men were 1.8 times more likely than women toperceive being at risk. Those who reported greater worries about contractingHIV/AIDS were 3.2 times more likely than lesser worried participants to perceivethemselves at risk for contracting the virus. Finally, residents of higher risk buildings

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were more likely to see themselves at risk. Residents of the three moderate–to–highrisk buildings were 73% (Building 3), 65% (Building 4), and 63% (Building 5) lesslikely to see themselves as being at risk for HIV/AIDS than residents living in ahigh-risk building (Building 6).

DISCUSSIONStudies of HIV/AIDS risk perception cut across a wide spectrum of age, ethnicity, andcontext. Because of wide variation across samples, age groups, and studies with re-spect to the percentage of respondents (18% to 85%) who see themselves at some levelof risk for HIV/AIDS (Brown, 2000; Dolcini et al., 1996; Facente, 2001; Ford &Norris, 1993; Holtzman et al., 2001; Inman, 1999; Mack & Bland, 1999; Maurier &Northcutt, 2000; Prohaska et al., 1990), comparisons of perceived risk across samplesare difficult. However, some brief comparisons may be helpful.

Breakdowns of perceived risk/no risk that are relatively similar to the nearly evendistribution in our sample have been found for more than a decade in studies that spanvarious risk categories, methods of data collection, and age groups. These includesamples of youth and young adults (Brown, 2000; Ford & Norris, 1993; Inman,1999), adults aged 18–60 (Prohaska et al., 1990), and adults of all ages (Maurier &Northcutt, 2000). However, other studies of younger samples reveal uneven break-downs of perceived risk/no risk, such as the 18%–89% in Facente’s (2001) mostlywhite, middle–class youth, the 39%–61% in Holtzman et al.’s (2001) adults aged18–49, and the 85%–15% in Dolcini et al.’s (1996) heavily minority, at–risk sampleaged 18–44.

A brief review of medium–to–high perceived risk for HIV/AIDS may offer somecomparative insight. The 20% of the mostly minority low–income older adults in thepresent study who perceived themselves to be at medium–to–high risk is well over the4% for Mack and Bland’s (1999) adults ages 50–64, 8% reported for Maurier &Northcutt’s (2000) Canadian adults of all ages, 8% reported for Holtzman et al.’s(2001) adults aged 18–49, and 10% reported among Brown’s (2000) White and Blackyouth. In fact, the only similar or larger percentages for medium–to–high perceived

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TABLE 4. Regression Coefficients, Wald Statistics, Odds Ratios, and 95% Confidence Intervals forOdds Ratios for the Significant Predictors

Wald Test Odds95% Confidence Interval

for Odds Ratio

Variables B (B/SE) Ratio Lower Upper

50–61 year age group 1.47 22.10* 4.35 2.36 8.04

62–73 year age group 0.76 7.06* 2.14 1.22 3.75

Gender (male) 0.56 5.61* 1.76 1.10 2.80

Worry (worriers) 1.15 19.88* 3.16 1.91 5.24

Building 1 –0.05 0.01 0.96 0.32 2.83

Building 2 0.85 2.52 2.33 0.82 6.60

Building 3 –1.31 9.25* 0.27 0.12 0.63

Building 4 –1.06 7.58* 0.35 0.16 0.74

Building 5 –0.96 5.27* 0.38 0.17 0.87

(Constant) –0.62 2.15

*p < .05.

risk among the studies cited here for which data are available in the literature are the17% reported by Ford and Norris (1993) and the 33% reported by Dolcini et al.(1996) in studies that heavily sampled minority and low–income or at–risk popula-tions of noticeably younger adults. These comparisons of risk perception varianceacross studies demonstrate no clear relationship with age but loosely point to the pos-sibility that heightened perceptions of risk for HIV/AIDS may be more commonamong minorities and/or low–income and at–risk groups. The older adults in oursample who perceived medium–to–high risk had notably higher risk perceptions com-pared with younger samples, perhaps owing to being minority, low–income, and/orliving in a risky environment. It is difficult, however, to draw conclusions about agefrom cross–study comparisons of HIV/AIDS risk perception because samples similarto this one do not yet exist.

Examination of this risk perception variance across studies and within the cur-rent research findings points to an important conclusion. Perceptions of risk forHIV/AIDS differ widely across categories of people, and such calculations do not cor-respond necessarily in degree and directionality to probabilities derived through sci-entific fact. Given this typical mix of conflicting responses, what does predict people’sperceptions of risk?

WHAT SHAPES RISK PERCEPTION?It was hypothesized that personal membership in demographic categories at high

risk for HIV/AIDS heuristically informs older housing residents’ perceptions of riskfor contracting the virus. As expected, based on epidemiological trends, age and gen-der emerged as significant predictors. Younger residents (aged 50–61) were 4.4 timesmore likely than older residents (aged 61–93) to see themselves at risk for contractingHIV/AIDS, and males were almost twice as likely as females to perceive themselves tobe at risk. Both demographic categories, younger age and being male, correspond tohigh–risk groups that commonly are targeted for HIV/AIDS education and preven-tion, and our results echo previous findings that show an association between risk per-ception and these two demographic variables (e.g., Holtzman et al., 2001; Maurier &Northcutt, 2000; Newman & Zimmerman, 2000). It is tempting to conclude that theinverse relationship between age and risk perception may be because the oldest adultswhom we sampled were less likely to be sexually active than their younger,over-age-50 counterparts. Similarly, women were less likely than men to be sexuallyactive. It is essential to note, however, that among those older residents who did reportbeing sexually active, sexual activity, including engaging in high–risk behavior, wasnot statistically significant in predicting increased perception of risk, and celibacy wasno guarantee of residents’ perceptions of little or no risk. Thus, sexual behavior alonedid not appear to translate into a sense of lesser or greater HIV vulnerability.

Our findings suggest that older residents may have identified with the larger de-mographic groups (age and gender) in which they claim categorical membership whencalculating their risk for HIV infection (Douglas & Wildavsky, 1982; Kowalewski etal., 1997; Prohaska et al., 1990). In addition, our findings parallel results from Daviset al. (2001) who found that older people presume themselves to be at low risk for HIVinfection, possibly because they believe they are too old to be infected by HIV andother STIs. Such assumptions may help to explain why even those older adults in oursample who were engaging in high–risk sexual activities, including unprotected sexwith multiple partners and/or commercial sex workers, failed to see themselves at per-sonal risk. In other words, they may have associated HIV/AIDS exclusively with

HIV/AIDS RISK PERCEPTION 581

youth, as portrayed in the media and as the focus of most health education programs,and thus having reached older age, they did not apply the dangers of acquiring HIVthrough risky sex to themselves. However, this may or may not be true for those in theyoungest cohort who were aged 40–45 when HIV/AIDS prevention messages werebeing most aggressively targeted.

Despite disproportionately high rates of HIV among African Americans and La-tinos (CDC, 2001, 2002), and despite correlations between ethnicity and perceivedrisk in other research (Dolcini et al., 1996; Prohaska et al., 1990; Singer et al., 1998),ethnicity was nonsignificant as a predictor variable in this study. Perhaps, becauseboth ethnic groups are at high risk, between–group differences by race/ethnicity arerelatively insignificant from the perspective of self–assessments of risk. AlthoughProhaska et al. (1990) found that the absence of religious preference could heightenperceptions of risk, only 4% of respondents in this study reported having no religiousaffiliation, leaving us with subgroup ns too small to analyze. This is a reflection of thetraditionally high levels of church affiliation among African Americans and Latinos,especially among women (Levin, Taylor, & Chatters, 1994; Taylor, Mattis, & Chat-ters, 1999). Similarly, the relative educational homogeneity of the present low–in-come sample may account for the nonsignificance of education in our study despiteevidence of a positive association found by Dolcini et al. (1996) and Holtzman et al.(2001). The near–zero prevalence of reported injection drug use precluded examininghow this variable might have affected risk perception.

Turning to sociobehavioral variables, worry about contracting HIV/AIDS wasassociated with higher risk perception. Perhaps as Prohaska et al. (1990) suggested, anegative affective orientation to a possible event heightens one’s belief in its occur-rence and may even be recursively reinforcing. In other words, worrying about con-tracting HIV may increase one’s perception of risk; conversely, perceiving oneself tobe at risk likely generates worry about contracting the disease.

In addition to worry, it was expected that other sociobehavioral factors reportedin the HIV/AIDS literature as predictor variables would be associated with lower orheightened risk perception, yet level of knowledge about HIV/AIDS did not signifi-cantly predict risk perception as expected based on findings from other studies (e.g.,Burkholder et al., 1999; Melkote & Muppidi, 1999). Prohaska et al. (1990) suggestedthat people often base risk calculations on heuristic notions that may or may not cor-respond to heightened knowledge or scientific fact, and it was discovered that partici-pants who scored relatively high on the HIV/AIDS knowledge index relied on mythsand popular misconceptions when assessing personal risk (e.g., “I know the women Ideal with are safe because they’re all stout; they don’t look like they’re sick or noth-ing”). Other researchers have reported similar findings (London & Robles, 2000;Rodgers–Farmer, 1999).

Although some respondents appeared to overestimate their risk, others seemed toperceive themselves to be at low risk or no risk, even though they were having unpro-tected sex with commercial sex workers and knew that risky sex could result in HIVinfection. Such behavior seems irrational from the standpoint of personal safety, butone’s decision to engage in a risky sex act may appear justifiable from their own per-spective if the confluent perceptions, attitudes, and desires of individuals are carefullyexamined (Pinkerton & Abramson, 1992). The choice of safe sex or abstinence maybe the product of a personal calculus weighing the sexual fulfillment expected from agiven behavior against the perceived health risks of that behavior (see Udry & Morris,1971). Misconceptions and erroneous heuristic constructions about HIV transmis-

582 WARD ET AL.

sion, however, may unfairly tip the scales toward decisions carrying greater risk (orgreater loss) by masking or misrepresenting the person’s actual odds of infection(Lowy & Ross, 1994; Prohaska et al., 1990). Such misleading assumptions may varyconsiderably across sociocultural and personal circumstance (Pinkerton &Abramson, 1992). For example, when interviewed, an unmarried 50–year–oldwoman with two children confided that she intended to become celibate for lifebecause she was too terrified of contracting AIDS to engage in sex.

The findings reveal that engaging in sexual behavior, one of the most commonlyrecognized ways of acquiring HIV/AIDS, did not predict older adults’ heightened per-ception of risk for HIV/AIDS. Similarly, three other factors often stressed inHIV/AIDS media prevention campaigns (number of sexual partners, condom use, andhaving sex with commercial sex workers) did not appear to influence respondents’self–assessments. In other words, whether or not they engaged in sex or particularhigh–risk sexual practices did not significantly influence older residents’ HIV/AIDSrisk perceptions.

Meanwhile, when asked why they perceived themselves at some level of risk foracquiring HIV, many celibate participants reported worrying about contracting thevirus through blood transfusions or nonsexual contact with infected body fluids.When asked why she answered “somewhat likely” to the question about her likeli-hood of getting HIV/AIDS, a sexually inactive 54-year-old female responded, “Be-cause I don’t know what might happen if I have to have a blood transfusion orsomething.” Risk estimates based on such heuristic misconceptions can produceoverestimations of personal risk (Prohaska et al., 1990). Such findings reinforce thenotion that behavioral factors (typically used to ascertain actual risk) may not be asimportant in estimating self–risk as heuristics or folk constructions of how HIV/AIDSis transmitted. Kahneman (2003) stressed that laypeople employ many types of toolsand clues rooted in experiential knowledge and sociocultural and cognitive processesto assess risk situations in society. With so many varied forces shaping individuals’perceptions of health hazards such as HIV/AIDS, it is not difficult to understand whythere are discrepancies between perceived risk and actual risk (Prohaska et al., 1990).

Another finding concerns the relationship between residing in a particular build-ing and experiencing either heightened or lowered self–perceived risk. Results indi-cated that residents of Buildings 3, 4, and 5 were significantly less likely toself–perceive as being at risk for HIV/AIDS than residents living in a high–risk build-ing. Indeed, some buildings did rate higher in terms of observed or reported sexual,drug, and environmental risk. Meanwhile, all buildings were associated with com-mercial sex worker activity, nonusage of condoms by male and female residents, andmonthly sexual visits by younger females (typically nonresidents) on social security“check day” when the male residents had extra money to spend. The utility of consid-ering building characteristics as a significant predictor of residents’ perceived risk issupported by broader evidence from a number of studies and perspectives addressingthe impact of neighborhood context upon the health and well–being of residents (e.g.,Aneshensel & Sucoff, 1996; Caughty, O’Campo, & Patterson, 2001; Dunn & Hayes,2000; Elliott, 2000; Kawachi & Berkman, 2000; Kawachi, Kennedy, & Glass, 1999;Krause, 1996; Malmstrom, Sundquist, & Johansson, 1999; Yang, 2000; Yen &Kaplan, 1998, 1999).

Finally, differences among buildings as vortices of risk or perceived risk may betraced, in part, to dissimilarities in building management and policy. The HartfordPublic Housing Authority ran three of the Hartford buildings; the fourth was pri-

HIV/AIDS RISK PERCEPTION 583

vately owned. Meanwhile, both buildings in Chicago were administered by the Chi-cago Housing Authority and differed organizationally from the Hartford sites in thattheir tenants’ associations were more formally organized. Tighter social structure inthe Chicago buildings permitted greater social control of resident behavior and al-lowed the tenant associations and management rulings to operate as a protective in-fluence, guarding residents against both internal and outside social risks, or allowingresidents to perceive themselves to be more protected against risks, including the riskof HIV/AIDS.

LIMITATIONSOne possible limitation of this study is that a single item measured risk percep-

tion, a methodological convention that has been criticized in the literature. Somescholars such as Kowalewski et al. (1997) have suggested that indices summing sev-eral items for a total score are preferable to single items because they may offer greaterreliability by measuring the strength of a respondent’s risk perceptions over several di-mensions. Many investigators do, however, utilize analyses involving single-item vari-ables rather than scales (Dolcini et al., 1996; Maurier & Northcutt, 2000; Newmann& Zimmerman, 2000), and such a strategy has been endorsed by methods experts(Robinson, Shaver, & Wrightsman, 1991). Because other categorizations are possi-ble, a second limitation to the study may lie in our decision to recode the five–responseLikert item measuring respondents’ perceived risk into “not at all likely” versus allother responses. In this, we followed the lead of Prohaska et al. (1990) and Londonand Robles (2000). Almost half of the sample saw themselves to be at no risk forHIV/AIDS, and we wanted to preserve this modal category in our analysis. Anotherpossible limitation is that the affective dimension of “worry” was used as a potentialpredictor of risk perception. Some argue that although likelihood and worry are con-ceptually and empirically distinct as social constructs, nonetheless they represent thecognitive versus emotional dimensions of perceived risk (Dolcini et al., 1996) and maybe too highly correlated to permit independent measurement. Although we appreciatethe logic informing this argument, we are satisfied that each construct represents a dis-tinct and measurable dimension that varies independently from the other in how peo-ple respond to the threat of illness. For example, most people are likely to perceive thatsooner or later they will catch a cold, yet few expend much daily time worrying aboutit. Conversely, some people report little perceived likelihood of catching AIDS yet stillindicate that they spend time worrying about it happening (Prohaska et. al, 1990).

SUMMARY AND CONCLUSIONSWe conclude that demographic factors such as age and gender form a central basis forlay constructions about HIV/AIDS as a disease condition, including decisions madeabout the likelihood of transmission and infection. Sociospatial context and relatedsocial–psychological factors influence older adults’ perceptions of risk, and emotionalfactors such as worry about HIV/AIDS also enter into the equation. These variablesare only some of the many factors that likely influence risk perception but we leave itto other studies to investigate the remaining mechanisms.

Our findings have several implications for HIV/AIDS prevention educationamong older adults. We found that people over 50 appear to rely on some scientifi-cally accurate information about the likelihood of risk, such as age and gender, butnot other information typically mentioned in AIDS prevention programming. More-over, older adults engaging in high–risk behavior did not necessarily equate their own

584 WARD ET AL.

acts with being at elevated HIV/AIDS risk. At the same time, it is unfortunate that somany older adults who appear to be at low or no risk (they are sexually inactive and donot use drugs) needlessly worry about contracting the virus. HIV/AIDS prevention ed-ucation for older adults would do well to target older persons in both risk categories.

In epidemiological terms, the rate of HIV infection in the U.S. population ofadults aged 50 and older is small, and it appears that most older Americans typicallyoverestimate the probability of actual risk of HIV infection by several orders of mag-nitude (Cohen & Bruce, 1997). The older adults that were sampled had relativelyheightened perceptions of risk when compared with results reported for younger sam-ples yet actually engaged in comparatively lower levels of risky behavior. Program-ming for preventing and treating HIV/AIDS among older adults nonetheless iswarranted, given that over 90,000 adults aged 50 and older have contracted HIV sincethe start of the epidemic (Mack & Ory, 2003) and that most older adults living withHIV/AIDS are diagnosed late in the disease trajectory (Funnye, Akhtar, & Biamby,2002; Goodroad, 2003). Meanwhile, infection rates, though low for older adults, aresomewhat higher for minority older adults and perhaps higher still for those living inhigh–risk environments (CDC, 2003; Mack & Ory, 2003; Schensul et al., 2003) andwho may have been exposed to high-risk drug or sex behaviors. HIV/AIDS educationefforts would do well to target such especially vulnerable populations.

Education interventions designed for older adults must emphasize that it is be-haviors that put people at risk, and not who they are or perceive themselves to be. Fur-thermore, persisting misconceptions about the transmission of HIV/AIDS should beidentified and explicitly addressed, especially in older populations for whom languageand other cultural barriers result in low access to prevention messages deliveredthrough mainstream media communications. Meanwhile, erroneous beliefs aboutrisk and transmission lull some risk–taking older adults into feeling safe fromHIV/AIDS while encouraging others who are at low or no risk to presume that theyare at risk of exposure. To design effective educational interventions for minorityolder adults, it is important that future research systematically explore various typesof misconceptions about HIV transmission and the ways in which these misconcep-tions and misunderstandings vary across different racial/ethnic and linguistic/culturalgroups. Finally, in support of these efforts, it is essential to explore and find ways to di-rectly measure how older adults may be using everyday heuristic assumptions to cal-culate personal risks for HIV/AIDS. These decision–making mechanisms mustbecome a basic point of departure for debunking myths and promoting accurateHIV/AIDS information that will help curb further transmission among this vulnerableage group.

HIV/AIDS RISK PERCEPTION 585

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