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Article Excerpt
HIV was the seventh-leading cause of death among U.S. 15-24-year-olds in 2002, and at least half of all newly infected persons in the country are younger than 25. (1) This represents about 20,000 new HIV infections among youth annually. (2) In addition, adolescents and young adults are at higher risk than other age-groups for sexually transmitted diseases (STDs) that can increase the risk of HIV infection. (3) These troubling patterns exist even though youth are increasingly postponing sexual initiation and using condoms once they become sexually active. (4)
Females and non-Hispanic blacks are disproportionately affected by STDs. For example, in 2001, the gonorrhea infection rate among 15-19-year-old black females was almost twice as high as that for black males, and 18 times as high as the rate for white females; the reported rate was lowest among white males. For the same year, the rate of chlamydia among 15-19-year-old black females was 5-6 times as high as those for black males and white females of the same ages; again, the rate was lowest among white males. (5) Among youth aged 13-24, 56% of HIV diagnoses occur in blacks.
Racial disparities are large among disadvantaged youth. For example, among U.S. Job Corps entrants in the 1990s, the HIV infection rate among young black women was seven times as high as that among young white women. (6) Such disparity is also particularly marked for young black men who have sex with men. In a large survey of young, urban men who have sex with men, the prevalence of HIV infection was 14% among blacks, compared with 3% among whites. (7)
In adolescents and young adults, HIV infections are mostly acquired through sexual activity, although drug use also puts young people at risk. (8) Sharing needles is the direct drug-related route; however, persons with drug addiction may have sex with multiple partners to obtain drugs or money to buy drugs, thereby infecting otherwise love-risk individuals. Moreover, noninjection-drug use may reduce inhibitions, resulting in sexual risk-taking, although research on this has been mixed regarding adolescents. (9)
These risk behaviors tend to covary; in adolescent and young adult populations, substance use is positively related to sexual initiation, frequency and risk-taking. (10) Covariation is important because it indicates that targeting single STD risk behaviors may be ineffective. Furthermore, demonstration of a single or predominant pattern of behavioral covariation would imply that different risk behaviors share causal antecedents; after these common antecedents are identified, targeting them in prevention and intervention efforts should reduce STD risk. However, relatively little research has systematically investigated whether a single pattern adequately captures risk behavior covariation, and whether that pattern is similar across genders and races. (11) Identification of multiple patterns of risk behavior covariation would suggest potential differences in the risk of STDs, including HIV, among adolescents showing those patterns and the possibility that distinct developmental pathways culminate in different patterns of risk behavior. Identifying distract patterns of risk and understanding the particular processes leading to those patterns are critical steps in developing and targeting risk prevention efforts.
Some research shows that the consistency and magnitude of covariation among risk behaviors related to sex and drug use vary across adolescent populations; in particular, associations between substance use and sexual risk-taking are less strong for black youth than for white youth. (12) Given the overrepresentation of black youth among STD cases, an understanding is critically needed regarding differences between blacks and whites in the patterns of risk-taking that underlie these outcomes. However, studies have shown conflicting results regarding racial differences in risk behavior covariation; this is explained, in part, by a lack of nationally representative adolescent samples, and by differences in study design or statistical adjustment for important factors confounded with race, such as socioeconomic status. However, findings have been inconsistent even among samples with similar socioeconomic status. For example, Stanton and colleagues found that sexual activity typically did not covary with drug activities of low-income, urban black adolescents, whereas Farrell and colleagues found similar covariations for low-income blacks and whites. (13)
Adolescent risk behavior covariation also differs between genders. For example, at any adolescent age, engagement in risk behaviors, and in multiple risk behaviors, is more likely among males than among females. (14) Findings also suggest that sexual risk behavior covariation with substance use is less likely among females than among males, again suggesting different dynamics of risk-taking. (15)
The first steps toward understanding the processes that lead to different risk behavior patterns and, ultimately, reducing STD risk are to identify the patterns of drug use and risky sexual activity that exist among youth, determine if these behavioral patterns and associated STD risk are similar for the groups who are the most and the least likely to be affected by STDs (blacks and non-Hispanic whites, respectively), and examine the association between behavioral patterns and STD risk. These steps can be facilitated by applying a person-centered analytic approach--that is, by examining, through cluster analysis, how people group together on the basis of the similarity of their risk behavior patterns. Similar to factor analysis, which groups variables together, cluster analysis groups individuals, on the assumption that risk behaviors often occur together and interact with each other. By combining individuals with similar behavior patterns, cluster analysis allows an examination of the interaction of all the behaviors, resulting in a parsimonious model and a holistic strategy for understanding youth behavior. (16) Such person-oriented approaches may capture reliable patterns of problem behavior that reflect distinct causes with differing implications for later risk; by so doing, they may improve efforts to identify adolescents with a particularly high STD risk, and may increase the specificity and the sensitivity of prevention interventions.
Conceptually and empirically derived typologies have been used to examine variation in common adolescent problem behaviors. (17) For example, Zweig and colleagues, using data on high school students participating in Wave 1 of the National Longitudinal Study of Adolescent Health (Add Health), generated four clusters, distinguished by patterns of eight diverse health risk behaviors examined. (18) The authors concluded that multiple "problem behavior syndromes" exist, and that these syndromes differ for males and females. Although risk groups differed significantly by race and ethnicity, Zweig and colleagues noted that race and ethnicity, age and family income contributed little to prediction of risk group membership. However, the authors did not report how much of the variance in risk behavior the four-cluster solution accounted for; therefore, the adequacy of the cluster solution and the reliability of associations with it are unclear.
We used a similar analytic approach to identify adolescent groups sharing behavioral risk patterns that put them at risk for STDs other than HIV and, consequently, for HIV infection. We performed a detailed examination of risk behaviors specifically related to STDs to identify adolescents who are members of small but high-risk groups. The analysis consequently allows for a relatively, large number...
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