Background

An abundance of social science research has sought to elucidate the harmful experiences of African American adolescents residing in low resource, underserved, urban communities, who are often described as “at risk” or “high risk” youth (e.g., [1]). These terms are ubiquitous in the literature yet may describe a diversity of behaviors and experiences. Health disparities include combinations of experiences with alcohol and substance use [2], sexual behaviors [2,3,4], running away [5], school dropout [6,7,8], homelessness [9, 10], gang involvement [5, 11,12,13], dating violence [14], victimization [15,16,17], mental health disorders [3, 4, 18], juvenile delinquency [19], LGBTQ struggles [20], pregnancy [21], sexually transmitted infections (STIs) [22], and neighborhood violence [23,24,25]. Clearly many of these factors co-occur [26] or intersect [6, 27], and the timing and correlation renders them potentially challenging to sort out. Determining what is a risk factor or protective factor [28] and what is the outcome can quickly become misunderstood, mislabeled, and stigmatizing, especially for an ill-defined “high risk” population. Such aggregation fails to recognize that these young people have both negative and, more importantly, positive influences in their lives that affect their behavior, health, and well-being. Decomposing, delineating, and quantifying the heterogeneity of positive forces and risks can help schools, social services, medical services, and communities in general pinpoint adolescents’ needs.

Acknowledging and disentangling the concept of “at risk” youth is not new. Swahn and Bossarte [29], for example, compared the prevalence of measures of violence and delinquency (e.g., owning a gun), suicide, substance use, parental monitoring, and school (low grades, skipping school, teachers care) among 9th graders using data from three studies: (1) LINKAGES conducted in a school district located in a poor neighborhood; (2) 2003 Youth Risk Behavior Survey (a national probability sample); and (3) Wave 1 of the National Longitudinal Study of Adolescent Health (Add Health) (a national survey of in-school youth). Although most of the violence-related variables such as suicidal thoughts were more prevalent among youth in the LINKAGES study, alcohol use was more prevalent in the nationally representative studies. The authors make the distinction between high risk behavior and living in a high risk environment and recommend avoiding these terms unless specifically quantified [29].

Houck et al. [30] also conducted a study to differentiate risk profiles among the youth recruited from reproductive health clinics and considered at high risk for sexually transmitted infections (STIs) and unintended pregnancy because the eligibility criteria included reporting having sex without a condom in the previous 90 days. Other eligibility criteria included 15–21 years of age, not pregnant, and not living with HIV. Using latent class analysis, participants were classified into one of three risk clusters. The highest risk cluster for female youth was characterized by sexual behaviors that increase the likelihood of STIs and pregnancy. Contrary to the authors’ hypothesis, African-American adolescents accounted for the highest proportion in the lowest risk cluster. This finding is consistent with another cluster analysis of Wave 3 of Add Health that also created sexual risk profiles [31]. Although African American women had the highest prevalence of STIs, they had the lowest risk profiles for STIs. High endemic prevalence of STIs likely accounts for these disparities [31]. Thus, African American adolescents and young women in both a nationally representative sample and from a clinic sample were not necessarily “at risk” or “high risk” as often conceived in the literature. To best develop programs, social services, and interventions requires understanding that the needs for all African American young people are not universal. The question remains, which youth are at risk and what are they at risk for?

In light of the complexities and vague yet pervasive use of “at risk,” coupled with findings from our formative qualitative interviews [6], we hypothesize that some African American female youth living in underserved, low wealth communities have more experiences than their peers with risk behaviors, or poor health, or risk environments, or any combination of the three domains [6, 32, 33]. In other words, some African American youth are “in risk” or at greater risk than others.

This analysis sought to disentangle the constellation of behaviors and experiences among a sample of African American female adolescents recruited from underserved neighborhoods in two cities in North Carolina to test a behavioral intervention. This analysis strived to distinguish and describe differences among adolescents who were “in risk” within a sample of “at risk” youth.

Methods

This analysis uses baseline data from the 237 participants of the Young Women’s CoOp, a randomized trial that tested the efficacy of an adapted evidence-based behavioral intervention to reduce alcohol and other drug (AOD) use, increase condom use and safer sexual behaviors, reduce violence, and set positive personal goals [34]. The control group received an equal-attention intervention for improving nutrition and physical activity. The Centers for Disease Control and Prevention (CDC) Adopting and Demonstrating Adaptation Prevention Techniques (ADAPT-2) initiative supported the study [35]. The trial phase of the study took place in the cities of Raleigh and Durham, North Carolina, from May 2010 to October 2012. The methods of the Young Women’s CoOp study have been described in previous publications [32, 34, 36] and are summarized here.

The eligibility criteria were designed to reach African American female adolescents at risk of STIs, alcohol or drug misuse or addiction, and violence. Female youth were eligible if they were Black/African American; 16 to 19 years of age; had ever dropped out of school or considered dropping out; did not have a high school diploma or GED; had vaginal sex with a male partner in the previous 3 months; used alcohol or other drugs in the previous 3 months; and planned to remain in the area for the 6-month duration of the study. A convenience sample was recruited from underserved neighborhoods through a combination of street outreach, collaboration with community-based service providers, flyers, Facebook marketing, and participant referral using recruitment coupons. The Institutional Review Board at RTI International approved all study procedures and waived obtaining parental consent for minors; the study obtained a Certificate of Confidentiality issued by the CDC. CDC staff did not have any interaction with participants.

Measures

The extensive baseline questionnaire was both interviewer- and self-administered for the sensitive topics using audio computer-assisted self-interviewing (ACASI) software. It assessed sexual behaviors; alcohol and drug use; physical, sexual, and emotional abuse; gang violence; neighborhood violence; psychosocial measures; and markers of poverty.

Socioeconomic status variables included housing insecurity (moved ≥ 2 times in the past 6 months, ever been homeless, and ever run away from home), food insecurity (not having enough money to buy food), whether the participant had a child and had ever been arrested. Participants were classified as having run away if they stated that running away was one of the reasons they dropped out of school or if they responded yes to the question, “During the past 3 months, have you run away from home?”

We used a combination of questions from the Alcohol Use Disorders Identification Test (AUDIT) [37] to create a variable indicating heavy alcohol use, defined as drinking at least two times per month and at least three drinks each time. On the basis of a previous analysis of these data examining the relationship between gang membership and marijuana [36], we defined substance abuse as smoking marijuana at least 70–90 days during the past 90 days.

Sexual behavior measures included: two or more sex partners during the previous 30 days, know or suspect main partner had multiple partners in the previous 30 days, AOD use at last sex, partner AOD use at last sex, and condomless sex at last episode of vaginal sex.

Measures of abuse included history of physical abuse, unwanted sexual touching, oral sex, or anal/vaginal sex. The survey also asked participants if they were currently experiencing emotional abuse from their main partner.

Perceived neighborhood violence was measured with a scale (α = 0.92) ranging from 0 to 36 that asked the participant how often she observed or was aware of violent events (e.g., murder, fights with weapons).

On the basis of the findings from the formative phase of this study, we developed two assessments to measure material support (α = 0.81) and emotional support (α = 0.60). The questionnaire asked, “When you need money and other things, how helpful is/are your …” for 12 types of people such as boyfriends, parents, and friends (options included “not at all helpful,” “somewhat helpful,” and “a great deal helpful”). The scale for emotional support asked participants “When you go to talk about a personal problem, how helpful is/are your …,” using the same series of types of people. Internal consistency estimates were established using Cronbach’s α. Estimates of 0.60 are sufficient for initial item set use and associated analyses. The Center for Epidemiologic Studies Depression Scale (CES-D) assessed depression [38].

Primary Composite Variable

On the basis of preliminary analyses, extant literature, and knowledge about “at risk” and “high risk” adolescents, we created a variable that was a composite of three correlated variables representing a continuum of especially adverse outcomes. Figure 1 illustrates the concept of the composite variable. The Venn diagram (i.e.,“the box”) displays the frequencies of three intersecting circles from the baseline questionnaire: (1) ever homeless, (2) ever traded sex, and (3) chronic substance abuse (defined as heavy alcohol consumption and smoking marijuana 70–90 days during the past 90 days). The three-pronged composite variable indicated the participant’s location in the box as within 0, 1, or 2–3 intersecting circles.

Fig. 1
figure 1

The Box of Intersecting Risk Circlesa

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Analysis

Initial analyses comprised descriptive statistics, tabular analysis for dichotomous and categorical variables, and analysis of variance for continuous variables. As alluded to the background, choosing which variable is the dependent versus the independent variable can be arbitrary in cross-sectional studies when most of the variables are correlated. For example, some youth may run away, become homeless, and perhaps join gangs for protection. Or, the sequence of events could occur in a different order. After joining a gang, perhaps they run away from home. Our analyses treated the box location variable as both the outcome and the independent variable. It was the outcome for categorical variables and the independent variable for continuous measures, as detailed below.

For the categorical measures (listed in Table 2), we applied ordinal logistic regression because ordinal regression captures the incremental effects of where participants were classified in the box. The use of ordinal regression, however, hinges on whether an independent variable meets the proportional odds assumption, meaning that the effect estimate is comparable for each level of the outcome. We tested whether each variable met the proportional odds assumption using the Brant test with the omodel function in Stata (version 13, College Station, TX). For categorical variables that did not meet the proportional odds assumption, we performed three logistic regression models. The first model estimated the odds for being in 1 risk circle relative being in zero circles (0➔1). The second model estimated the odds of being in 2 or 3 risk circles relative to zero circles (0➔2 or 3). The last logistic regression estimated the odds of being in 2 or 3 circles relative to one circle (1➔ 2 or 3).

The continuous variables that measured depression and emotional and material support were treated as the outcomes, and the box location was the independent variable in linear regression (i.e.,ordinary least squares). If the outcome and independent variables were reversed (as was done for categorical variables), the coefficients would indicate how a one-unit change in the scale score affects the probability of moving from a lower to a higher risk box location (some scores ranged from 0 to 36). In contrast, treating box location as the independent variable showed the extent that the psychosocial scores changed by box location where being in zero circles was the reference group. Before selecting linear regression, we verified that the continuous variables conformed to a normal distribution with Wilkes-Shapiro tests and visual inspection of the histograms and Q-norm plots.

We did not conduct a multivariable analysis because this comprehensive set of variables has numerous marginal correlations that would be problematic for regression models.

Results

A total of 237 adolescents enrolled in the YWC intervention; Fig. 1 displays the frequencies of where the participants were categorized inside the box. Most participants (n = 141 [59.5%]) were not in any circles; 66 (27.8%) were in 1 circle, and 30 (12.7%) were in 2 or 3 circles.

Table 1 presents participant characteristics overall and stratified by box location. The mean ages across all box locations were between 17.6–17.9 years. The majority of participants (75.9%) had no men living in their household; the proportion was lowest for participants who were not in any circle (67.4%) and highest for those in 2 or 3 circles (92.4%). Of the 16 adolescents who lived with both parents, 15 were not in any circle. As expected, given the eligibility criteria (considered or dropped out of school), 65% of the sample was below the grade level for their age. Most participants had been tested for HIV (73%) and STIs (75.9%), including 90% of those in 2 or 3 intersecting circles.

Table 1 Characteristics of female adolescent participants, stratified by intersecting risk circles,a Young Women’s CoOp study, Raleigh and Durham, NC 2010–2012
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Socioeconomic History

With the exception of having children (29.1% of the full cohort), the incremental odds of reporting low socioeconomic status increased by box location (Table 2 and Fig. 2a). Relative to adolescents in zero circles (26%), the participants in 1 (35%) or 2–3 (53%) circles (Fig. 2a) were 2.09 (95%CI (1.22, 3.57)) times as likely to have moved at least twice in the previous 6 months (Table 2). Participants in 1 or 2–3 circles were more than three times as likely as those who were not in any risk circle, to experience food insecurity (OR = 3.27, 95% CI (1.8, 5.94)), have a past arrest (OR = 3.56 (95%CI (2.08, 6.09)), and run away (OR = 3.3 95%CI (1.79, 6.10)). Past arrest was highly prevalent in this population overall (34%) (Table 2), but varied substantially by box locations including 23%, 44%, and 63% of participants in zero, 1, or 2–3 intersecting risk circles, respectively (Fig. 2a). Although about one fifth of the overall sample (22%) reported food insecurity (Table 2), the prevalence was 14%, 29%, and 43% in box locations zero, 1, or 2–3 intersecting risk circles, respectively (Fig. 2a).

Table 2 Bivariate ordinal and logistic odds ratios of sociodemographic, sexual behaviors, and history of abuse by box locationa
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Fig. 2
figure 2

a Distribution of socioeconomic factors by box location; b Distribution of sexual behaviors by box location; c Physical, sexual, and emotional abuse

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Sexual Behaviors

The prevalence of sexual behaviors also reflected the box phenomenon (Fig. 2b). The prevalences of having sex with two or more partners in the past 30 days were 14%, 24%, and 45% for box locations zero, 1, and 2–3 circles, respectively, corresponding to an increased odds of 2.97 (1.61, 5.48) (Table 2). Similarly, respondents suspecting that their partner had other partners increased in step with box location (OR = 2.10, [1.13, 3.91]). Because the proportional odds assumption was not met for alcohol or drug use at last sex, the incremental binomial odds ratios from logistic regression are presented (Table 2). Participants in 2–3 circles (70%) were 7.64 (3.19, 18.3) and 6.72 (2.59, 17.5) times as likely as those to use alcohol or drugs at their last sexual episode than participants in zero or 1 circle, respectively. Self-report of not using condoms at the last vaginal sex was high across all box locations (45%, 49%, 67% for zero, 1, and 2–3 circles, respectively), and 2.47 (1.08, 5.67) times as likely among participants in the 2–3 circles as compared to zero circles.

Past and Current Abuse

Between 11% and 32% of all participants reported experiences of past physical or sexual abuse, or current emotional abuse from their main partner (Table 2). Figure 2c illustrates that the prevalence of abuse varied substantially and increased for adolescents in each box location. Whereas 28% of the total sample reported past physical abuse, the prevalence was 19%, 38%, and 53% for participants in zero, 1, or 2–3 intersecting circles, respectively. Participants in 1 and 2–3 circles were 2.67 (1.39, 5.15) and 5.01 (2.18, 11.54) times as likely, respectively, as youth in zero circles to report physical abuse. Experiencing emotional abuse from their current partner was approximately 10 percentage points higher for each box position including 20%, 31%, and 39% for participants in zero, 1, and 2–3 circles, respectively (Fig. 2c). Respondents in 2–3 circles were 2.59 (1.08, 6.21) times as likely as those in zero circles to report current emotional abuse.

Psychosocial Assessments

Table 3 displays the mean scores and linear regression coefficients for emotional support, material support, and depression (where box location was the independent variable as explained in the analysis methods).

Table 3 Bivariate linear regression of psychosocial measures by box locationa
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For the emotional support and material support scales, higher scores indicate increased support. The coefficients reflect the average reduction in support scores for being in 1 and 2–3 circles relative to being in zero circles. The average reduction in material support was −2.03 points (95%CI [− 3.44, − 0.62]) for youth in 1 circle, and − 3.47 points (95%CI [− 5.37, − 1.57]) for 2–3 circles. Participants in 2–3 circles had a statistically significant reduction in emotional support of − 2.43 points (95%CI [− 4.31, − 0.55]). The mean CES-D values score increased (indicating greater depression) with box location and was significantly higher among youth in 2–3 circles (2.51 points) (95% CI [0.47, 4.56]).

Neighborhood Violence and Crime

The majority of participants (85%) reported that they observed or were aware of violence and crime in their neighborhoods. Because 15% of participants reported no violence (and therefore had a score of zero), the distribution of scores was skewed thereby prohibiting performing linear regression. Figure 3 presents the prevalence of each item in the scale, stratified by box location. Most forms of violence were disproportionately distributed across box locations (Fig. 3) except for gun violence; 52% to 57% of respondents were aware of it occurring in their neighborhood. In general, the prevalence of violence and crime was markedly high for the entire cohort.

Fig. 3
figure 3

Neighborhood violence and crime

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Discussion

This analysis sought to distill behaviors and other traumatic experiences typically paired in the literature with the terms “at risk” or “high risk” among African American female adolescents living in economically disadvantaged urban communities. The data originate from the baseline interview of a behavioral intervention for adolescents designed to reduce alcohol and drug use and sexual behaviors that place them at risk for sexually transmitted infections and pregnancy, and empower them to set personal positive goals.

Similar to Houck et al. [30], the eligibility criteria for this study were chosen to recruit youth who engaged in “high risk” behaviors and who may have experienced traumatic or stressful events that placed them “at risk” for poor social and health outcomes. Houck et al. [30] then used latent class analysis to condense the data and classify their sample of “high risk” youth into three groups of variable risk. Although latent class analysis is statistically rigorous and unbiased, we chose a different approach that was hypothesis-driven to create “the box” on the basis of three intersecting and extremely adverse experiences. Then, the statistical analysis leveraged the ordered nature of the data (i.e., box location).

The largest proportion of participants was not in any intersecting risk circles (59%), which is a somewhat promising finding. That said, the prevalence of traditionally conceived risk factors was elevated for all participants, as expected given the eligibility criteria. Additionally, recruitment took place in underserved neighborhoods. Thus, these young women were “in the box of risk,” whereas the adolescents in the intersecting circles were classified as such if they had reported especially traumatic outcomes: ever been homeless or ever traded sex, or smoked marijuana at least 70 of the 90 previous days and drank alcohol excessively.

The study and analysis have limitations. Social desirability bias may have underestimated the extent of poor outcomes and behaviors. However, the more sensitive questions were self-administered via ACASI to lower the likelihood of this type of bias [39]. Also, the prevalence of affirmative responses to sensitive questions about proscribed behaviors was high. The survey did not measure parental monitoring, which mitigates the likelihood of risk behaviors and delinquency [40, 41]. The sample size was somewhat small. Multiple comparisons and statistical tests may have produced associations that were random noise. Nevertheless, the results show a consistent pattern and generally lead to the same inference that African American female adolescents classified into intersecting circles disproportionately experienced higher prevalence of poor outcomes.

We presented a creative use of traditional risk factor variables to describe a sample of African American adolescents in the southeastern USA. The box classification accounts for the interrelationships among these variables and clearly illuminates how some youth are “in risk” while others are at “high risk.” The findings for emotional and material support were compelling as they revealed that youth who have people in their lives who can help and support them suggest an alternative entry point of interventions that cultivates positive relationships [28, 42]. Thus, interventions designed to help underserved African American youth may not achieve optimal success unless the diverse circumstances occurring at multiple levels and experiences are addressed. Programs that serve adolescents should continue to harness what is good and change the dialogue from vague use of “high risk” to positive language with a focus on youth development and support—i.e., asset or strength-based approach with technology driven methods that may resonate with them.