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Latent model analysis of substance use and HIV risk behaviors among high-risk minority adults.


Objectives: This study evaluated substance use and HIV risk profile using a latent model analysis based on ecological theory, inclusive of a risk and protective factor framework, in sexually active minority adults (N=1,056) who participated in a federally funded substance abuse and HIV prevention health initiative from 2002 to 2006.

Methods: Data were collected locally from community-based organizations using a common baseline instrument that was administered within 30 days of program entry. The latent variables included were social support; neighborhood attachment; family cohesion; intimate abuse; alcohol tobacco/other drugs (ATOD) use; and HIV risk behaviors.

Results: The model-fit indices met acceptable standards for African Americans (CFI = 0.962, TLI = 0.956, RMSEA = 0.033) and for Hispanic/Latinos (CFI = 0.927, TLI = 0.917, RMSEA = 0.047). For African Americans, neighborhood attachment was significantly related to intimate abuse (coefficient = .126, p<.01) and family cohesion (coefficient = .281, p<.01). Social support was not significantly related to either family cohesion or intimate abuse. Family cohesion was negatively related to ATOD use, which was also related to sex with risk partners and drug-related sex. For Hispanics, neighborhood attachment was significantly related to intimate abuse (coefficient = .209, p<.01) and family cohesion (coefficient = .209, p<.01). Social support was significantly related to family cohesion (coefficient = .274, p<.01), but not related to intimate abuse. Intimate abuse was negatively related to ATOD use.

Conclusions: The results support the inclusion of protective factors as a standard implementation approach for prevention programs targeted to the reduction of ATOD use and HIV risk among sexually active minority adults.


Since the first report of HIV 25 years ago, worldwide more than 65 million persons have been infected with HIV and more than 25 million have died of AIDS (Merson, 2006). Moreover, AIDS is now the leading cause of premature death among people 15 to 59 years of age. Through 2005, a total of 249,950 persons were reported as having HIV infection (not AIDS) and 956,019 persons had been reported as having AIDS in the United States (CDC, 2005). Among the several routes of transmission, drug use/abuse has been an important mode of transmission of HIV/ AIDS in the United States and around the world. Persons who use substances participate in behaviors that place them and others at substantial risk for HIV/AIDS infections (Brown et al, 2006; Francis, 2003). Drug use behaviors that contribute to HIV transmission include sharing contaminated injection equipment, risky sexual behaviors among injection drug users or their noninjecting sex partners, and perinatal transmission to their offspring (Winstanley, Gust, & Strathdee, 2006). For example, injection drug use was the mode of transmission in approximately 17% of the HIV diagnoses reported among adolescents and young adults aged 13 to 24 (Center for Disease Control and Prevention, 2004). Previous studies have attempted to identify risk factors for needle sharing among injection drug users. Most studies, however, have focused on demographic and psychosocial characteristics of the individual (Unger et al, 2006). In addition, correlational research suggests that substance use is associated with increased HIV-related risk taking (Carey et al, 2003). The study by Carey and colleagues (2004) found that intoxicated men had less favorable condom attitudes and reported lower self-efficacy to initiate condom use in comparison to their sober counterparts. In a follow-up study, they found that men who drank alcohol demonstrated a lower skillfulness in negotiating for condom use relative to their sober counterparts. Finally, in a recent study, results indicated that men who drank alcohol had poorer negotiation skills and greater intentions to engage in risky sex than those who did not consume alcohol (Maisto et al 2004a; 2004b). In light of the involvement with risky behaviors and the rising numbers of new HIV infections and the number of people who have used illicit drugs, there is an urgent need to address this epidemic. Therefore, research to analyze and intervene in substance use and to interrupt HIV/ AIDS risky behaviors in advance is of the utmost importance in preventing the spread of HIV/AIDS.

In the United States, disparities in health status and health outcomes exist among subpopulations such as African Americans, Hispanics, and women, and HIV/AIDS prevalence is not excluded from these disparities (2006; Estrada, 2005; Qian et al, 2006). Despite increasing efforts in substance abuse prevention to reduce risky behaviors related to HIV/AIDS incidence, the prevalence remains high among ethnic minorities (2006; Rangel et al, 2006; Steele, Richmond-Reese, & Lomax, 2006). A CDC Morbidity and Mortality Weekly Report (2007) showed that of the estimated 184,991 adult and adolescent HIV infections diagnosed during 2001-2005, more (51%) occurred among Blacks than among all other racial/ethnic populations combined. The report also illustrated that during 2001-2005, Blacks had the largest percentage of HIV/AIDS diagnoses in all age groups and in the injection drug use (IDU) and high-risk heterosexual transmission categories. By transmission category, Blacks had the highest average rates for all categories during 2001-2004 (CDC, 2004). For cases among male-to-male sexual contact (MSM), the rate for Blacks was 69.0 per 100,000, compared with 13.9 for whites, 37.8 for Hispanics, 8.2 for Asians/Pacific Islanders (A/PIs), and 12.1 for American Indians/Alaska Natives (AI/ANs). For cases among males reporting injection drug use, the rate for Blacks was 26.9 per 100,000, compared with 1.7 for whites, 12.0 for Hispanics, 1.6 for A/PIs, and 2.7 for AI/ANs. For cases among males with high-risk heterosexual contact, the rate for Blacks was 35.5 per 100,000, compared with 1.1 for whites, 10.9 for Hispanics, 2.3 for A/PIs, and 2.4 for AI/ANs. Similar rates were also found for their female counterparts. Therefore public health surveillance and education related to HIV/AIDS and IDU should place an emphasis on African Americans and Hispanic/Latinos.

Numerous studies have been conducted in an attempt to reduce risky behaviors such as substance use and HIV risks (Knowlton, Hua, & Latkin, 2005; O'Leary et al, 2005; Winstanley, Gust, & Strathdee, 2006). An ecological systems model (Bronfenbrenner, 1979; Bronfenbrenner, 1986) integrated with a risk and resiliency framework (Dekovic, 1999; Rutter, 1987) is appropriate to examine the mechanism by which individuals may decrease their engagement in risk behaviors with strengthened protective factors. This model stipulates multilevel interventions, including individual, interpersonal, and organizational community. The ecological systems perspective considers the individual's behavior and how behavior interacts with the immediate environment and how aspects of larger contextual settings influence the individual and his or her immediate environment. On the other hand, another approach is the resiliency or protective process model that speculates about the conditions which facilitate positive behaviors (Bogenschneider, 1996). According to Rutter (1987), protective processes do not directly lead to an outcome per se, but rather operate when a risk is present.

Most recent reviews of studies, however, analyzed the relationship of independent variables (e.g., individual, family, neighborhood, and community) and the risk behavior outcome (e.g., substance abuse and HIV risky behavior) applying correlation analysis, and results were typically coefficients or odds ratios (Ebrahim et al, 2004; LaLota et al, 2005; Latkin et al, 2004; Ward et al, 2004). This "correlation" approach deviates from the ecological model so that interrelationships among individual, interpersonal, and environmental factors are stressed. Furthermore, distal factors such as neighborhood influence and proximal influences such as family cohesion cannot be differentiated at the same time in analysis models such as logistic regression or linear regression. As a result, the interactions and multiple levels of influence of individual, interpersonal, and environmental factors underlying the behavioral ecological model are not reflected.

Within this ecological perspective, the objective of this study was to test a risk- and protective-factor framework in relation to substance use and HIV-related risks using a latent model analysis among a group of African American and Hispanic/Latino adults who participated in the Center for Substance Abuse Prevention (CSAP)'s 2002-2006 Minority Substance Abuse and HIV/AIDS Prevention Initiative, also referred to as the Minority AIDS Initiative (MAI) in the literature (CSAP, 2002).

Latent modeling offers several advantages in examining protective factors under the ecological model (Bentler, 1995; Wang et al, 2005). First, a theory or structure of relationships among a set of latent protective variables can be hypothesized and tested (J6reskog, 1993). Second, the application of latent modeling provides increased statistical control over random measurement error and measurement biases (Bentler, 1995). Third, latent modeling allows simultaneous examination of interrelated constructs without the disadvantages of a multivariate analysis of covariance approach (Spoth, Redmond, & Shin, 1998). Because multiple factors influence health behavior, it is necessary to identify the interrelationships and pathways among these factors that may lead to risky behaviors that place a person at risk for contracting HIV. To date there have been a limited number of studies using latent modeling to examine multiple risk and protective factor influences on HIV risk behavior among minority subgroups such as African Americans and Hispanics. Copenhaver and Lee (2006) focused on an information-motivation-behavior model whereas the study of Bryan et al focused on individual components (Bryan, Schmiege, & Broaddus, 2006), but there is a paucity of studies employing multilevel factors (i.e., individual components, family components, neighborhood components, and community components) at the same time.

As shown in Figure 1, the present model includes neighborhood attachment and social support (Marsiglia, 2001) as distal factors that affect the local level as implied by the ecological model (McLeroy, 1988). At the second level, proximal factors (family cohesion and intimate abuse) relate to the outcome factor (substance use). Furthermore, the literature indicates a strong relationship between substance use and HIV risky behaviors; consequently, HIV factors such as condom use, multiple sex partners, and drug-related sex were also included in the model as related constructs to substance use (Boyer, 1999; Capaldi, 2002; Donnelly, 2001). The development of these paths also was based on previous work examining the effects of family-based interventions on youth risk behaviors (Kumpfer, Alvarado, & Whiteside, 2003; Liddle, 1999). Although intimate abuse has not been a common protective factor, its relationship with both substance use and HIV risk behaviors has been studied extensively (Brown-Peterside, et al., 2002; Lichtenstein, 2005). As a result, we included an intimate abuse scale in conjunction with family cohesion to examine how these "family relationship" factors may predict substance use. It was hypothesized that a high level of neighborhood attachment and social support would be associated with a greater family cohesion and less intimate abuse, which would predict less substance use. Less substance use was expected to predict low HIV risky behaviors.


Adult Participants

The data were collected locally from sites funded from September 2002 to September 2006 by the Center for Substance Abuse Prevention (CSAP), Substance Abuse and Mental Health Services (SAMHSA) under the Minority Substance Abuse and HIV/AIDS Prevention Initiative. The Substance Abuse and HIV/AIDS Prevention Initiative competitively funded 48 sites in 2002 as 3-year cooperative agreements, geographically located nationwide; 34 of these sites agreed through data-sharing agreements with CSAP to participate in a standardized data collection and submission protocol that used common process, dosage, and outcome instruments in order to evaluate their local prevention interventions. Each site received institutional review board (IRB) approval from their respective institutions. CSAP grant recipients funded under this initiative were responsible for recruiting and retaining in prevention programs persons who were at risk or high risk for substance use and risky behaviors associated with HIV transmission, particularly within minority populations. Most typically, recruitment focused on communities that were characterized by high levels of risk, such as poverty, crime rates, or ambient substance use rates that were known to associate with higher than average levels of substance use and risk for HIV transmission in minority adults.

All participants were asked to complete a baseline questionnaire (the Adult Baseline Questionnaire). The questions included risk factors related to past month alcohol, tobacco, and illicit drug use; use of substances while engaging in sexual behaviors; and recent history of emotional, physical, or sexual abuse. Most sites did not record the refusals of participants approached; thus refusal rates are unavailable for all sites and will not be reported here.

Study Sample

Response data from the Adult Baseline Questionnaire was the source for this study. Thirteen out the 34 funded sites included minority adults who completed the baseline questionnaire. Minority adults (N=1,056) who self-reported as African American or Hispanic/Latino were selected for this current study sample. A larger number of women (n=750) than men (n=306) were represented with an age range from 16 to 64. The mean age was 34 with 75 percent of the sample under the age of 46. The mean age and range did not significantly vary across race, ethnicity, or gender groups.


A paper-and-pencil adult survey questionnaire was administered either in a small group or individual format. Demographic variables such as age, race, ethnicity, sexual orientation, household composition, stability of living situation, education attainment, employment status, and household income were obtained.

The list of survey questionnaire items used in the latent model analysis is presented in Table 1. The construct variables are:

1. Neighborhood Attachment--The items were developed specifically for this CSAP initiative. The response categories were a 4-choice Likert scale: strongly agree, agree, disagree, and strongly disagree. Two of the three items were recoded. A higher value on this construct was considered positive. The internal consistency reliability for neighborhood attachment construct was 0.76.

2. Availability of Social Support--Availability of social support was measured using the items developed specifically for the CSAP initiative. The categories were: people to talk to about health; people to talk to about sex; and people to talk to about personal matters. The response categories were a 4-choice Likert scale: yes, there are many I can talk with; yes, there are some I can talk with; yes, there are one or two I can talk with; and no, there is no one to talk with. A higher value on this construct was considered positive. The internal consistency reliability for the social support construct was 0.86.

3. Family Cohesion--The questions were modified specifically for this CSAP initiative from Moos's Family Environment Scale question items (Moos, 1974). Departing from Moos, the question items were placed on a 4-point Likert scale instead of the original true or false scale to allow for variations across a continuum about the nature of family relationships. The response categories were a 4-choice Likert scale: strongly agree, agree, disagree, and strongly disagree. A higher value on this construct was considered positive. The internal consistency reliability for the family cohesion construct was 0.87.

4. Intimate Abuse--Three items asked respondents about: how often they were emotionally abused; how often they were physically abused; how often they were sexually abused. The response scale categories were: currently/ always; often; sometimes; rarely; and never. The category coding was reversed so that a higher value indicates less abuse. The internal consistency reliability for the family cohesion construct was 0.751.

5. Alcohol, Tobacco, Other Drugs (ATOD) 30-Day Use--Question items were used from the CSAP Government Performance Results Act (GPRA) (1) Tool to measure participant outcomes. Each of the ATOD measures consisted of three questions: ever use; age of first use; and past 30-day use. The participant had to answer "yes" to "ever use" before he/she was asked the remaining two questions: "age of first use" and "past 30-day use." Only those who reported past 30-day use were defined as a user. Substance items included tobacco, alcohol, marijuana, and inhalants. Other illicit drugs (cocaine, ecstasy, methamphetamine, and injected drugs) with smaller prevalence were grouped into Other Illicit Drug. A scale of ATOD was created to reflect all substance use behavior. A high value on this construct indicated more use. The internal consistency reliability for the ATOD 30-day use construct was 0.71.

6. HIV Risky Behavior--The five major items to determine HIV risky behavior were developed specifically for this CSAP initiative. However, the preliminary analyses indicated that these five items fell into two categories: sex with risk partner and drug-related sex. Sex with risk partner consisted of three items: During the past 3 months, did you have unprotected sex with partner with an STD?
 During the past 3 months, did you have unprotected sex with partner
 with HIV/AIDS? During the past 3 months, did you have unprotected
 sex with partner using injection drugs? Drug-related sex consisted
 of two items: During the past 3 months, did you have unprotected
 sex for money, drugs, shelter? During the past 3 months, did you
 have sex under influence of alcohol or drugs?

A high value on these HIV risk behaviors was considered more risky. Considering that specific questions were used to determine distinct HIV risk behaviors, rather than a specific HIV risk behavior scale, internal consistency reliability was not calculated.


To assure the quality of data collection across the project sites, a design and analysis advisory group was developed to build an integrated approach to the multisite evaluation. The advisory group led by the CSAP project officer included contract staff, senior research evaluators, and consultants along with several representatives from funded Initiative study sites.

The instrument was pilot tested, and results were first reviewed by the advisory group and presented to all the study sites for comment. Together with the administration guide, the evaluation contractor finalized the instrument to allow for optical scanning of responses. A multisite baseline database was developed with a system for identifying data errors and facilitating subsequent corrections with the project sites. The baseline data were collected 30 days before services were provided to clients. A common process data-collection protocol was developed. The format for survey administration to adults was one that was fully proctored to allow for clarification of questions that may be confusing. For adults with limited reading abilities, the proctor read the questions aloud so that they could follow along and answer at a reasonable pace. Survey instruments were available in either English or Spanish. When data collection was closed for a given administration (e.g., the baseline for a specific cohort), all completed questionnaires were submitted to the project data manager. Project sites then received a cleaned electronic data set in order for them to conduct site-specific analysis. Participants were assured that their participation was voluntary with the right to withdraw from the evaluation study at any time. Evaluation procedures were discussed, and written informed consent was obtained from participants prior to participation. On average, each project site provided the participants with a $20 to $30 gift certificate to a local store or equivalent for their participation in the evaluation.

Statistical Methods

Model description: Latent model analyses were conducted using Mplus software. The models were covariance structural models with multiple indicators for all latent constructs. The analysis employed a 2-step procedure (Ebrahimet al, 2004) using maximum likelihood estimation. The first step was confirmatory factor analysis to test the measurement model. A measurement model describes the nature of the relationship between a number of latent variables and the observed variables corresponding to each of the constructs. The second step tested the structural model, depicted in Figures 1-3 in the Results section. This step represents the theoretically based model where the relationships among exogenous variables (those variables with both emanating paths and receiving paths) and endogenous variables (those variables with mostly receiving paths) can be seen.

Model tit tests: Multiple indices were used to test the model fit, and they include the following: comparative fit indices (CFI), where the value of 0.90 or higher is considered acceptable (Joreskog, 1993); Tucker-Lewis Index (TLI), where the value of 0.90 or higher is considered acceptable (Joreskog, 1993); and the root mean square error of approximation (RMSEA), with the value below 0.05 indicating a good fit (Kalichman, Cherry & Browne-Sperling, 1999).


For all figures presented in this section, the constructs (except for ATOD and HIV risk behaviors) were coded in the same direction: high scores indicate more positive behavior. For ATOD and HIV risk behavior constructs, however, high scores indicate higher risk behavior. For clarification of the diagram, only significant path coefficients are presented. Path coefficients indicate both the magnitude and direction of effect. Additionally, both unstandardized coefficients (in the original measurement scale) and standardized coefficients (in the scale of z scores) are presented in the figures; however, only standardized coefficients are presented within the text.

Overall Model

The hypothesized model for all minority adults fit well with CFI = 0.965, TLI = 0.960, RMSEA = 0.031 (see Figure 1). Neighborhood attachment was significantly related to lower levels of intimate abuse (coefficient = .142, p<.01) and family cohesion (coefficient = .273, p<.01). Social support was significantly related to family cohesion (coefficient = .083, p<.01), but not related to intimate abuse. Both family cohesion and lower levels of intimate abuse were negatively related to ATOD use, indicating that the greater the family cohesion and the less the history of intimate abuse, the less the ATOD use. As ATOD use increased, there was a significant increase in both HIV risk behaviors, sex with risk partners (coefficient =. 157, p<.01) and drug-related sex (coefficient = .536, p<.01; see Figure 1).


African American Model

The hypothesized model for African American adults fit well with CFI = 0.962, TLI = 0.956, RMSEA = 0.033 (see Figure 2). Neighborhood attachment was significantly related to lower levels of intimate abuse (coefficient =. 126, p<.01) and family cohesion (coefficient = .281, p<.01). Social support was not significantly related to either family cohesion or intimate abuse. Family cohesion was negatively related to ATOD use, indicating that the greater the family cohesion, the less the ATOD use. However, the history of intimate abuse was not significantly related to ATOD. As ATOD use increased, there was a significant increase in both HIV risk behaviors, sex with risk partners (coefficient = .133, p<.01) and drug-related sex (coefficient = .492, p<.01; see Figure 2).

Hispanic Model

The hypothesized model for Hispanic adults fit well with CFI = 0.927, TLI = 0.917, RMSEA= 0.047 (see Figure 3). Neighborhood attachment was significantly related to lower levels of intimate abuse (coefficient = .209, p<.01) and family cohesion (coefficient =. 158, p<.01). Social support was significantly related to family cohesion (coefficient = .274, p<.01), but not related to intimate abuse. Intimate abuse was negatively related to ATOD (see Figure 3). However, family cohesion was not significantly predictive of ATOD use. ATOD use was not significantly related to either sex with risk partners or drug-related sex.




The present study focused on evaluating the relationship of substance use and HIV-related risks with risk- and protective-factors based on the ecological approach. Unlike most of the previous studies (Jessor, 1998; Jessor, 1995; Kumpfer, Alvarado & Whiteside, 2003; Liddle, 1999), this study adopted a latent model analysis so that the structural relationship and multiple levels of influence of individual, interpersonal, and environmental factors underlying the behavioral ecological model could be tested. The study found significant factors at every level of the ecological model. First, among distal-level factors, represented by the neighborhood attachment and availability of social support, the neighborhood attachment factor was significantly related to two proximal factors, family cohesion and history of intimate abuse m both the African American population and the Hispanic/Latino population. The availability of social support factor was also positively related to the proximal factor, family cohesion. In addition, both family cohesion and history of intimate abuse were significantly related to the risk behavior (ATOD use). Furthermore, ATOD use served as a pathway to both sexual risky behavior and drug-related sex, which were HIV risk behaviors.

Contrary to expectations, in the African American model, social support was not significantly related to family cohesion. This finding is noteworthy because a large and growing literature supports the direct and indirect influences of social support. There is an extensive body of research demonstrating that perception of social support among adults is related to their physical and emotional well-being (for a review, see Thoits, 1995). Other studies indicate that social support is an important protective factor for the psychological well-being of African Americans. For example, in a mixed-method study of rural African American families, Dressler's (1985) findings indicate that individuals who perceived their informal (extended kin) support network to be more supportive reported fewer symptoms of depression. Also, in a longitudinal study with a low-income, rural sample of mostly African American mothers, Unger and Wandersman (1988) found that both family and partner social support were positively associated with greater satisfaction with life.

A possible explanation is that the construct of social support may have failed to be significantly related to family cohesion because of its multidimensionality. Researchers may need to explore the various dimensions of social support separately to assess whether these dimensions are significantly related to family cohesion. For example, Cameron and Vanderwoerd (1997) deconstructed social support into four dimensions: instrumental, educational, social, and psychological support. They further classified these dimensions into four functional components: 1) concrete/tangible help; 2) support through education, information and/or referral; 3) emotional support; and 4) social integration. Thus, the very specific nature of the social support construct used in this study (i.e., the availability of people to talk to) may obscure the true influence social support may have on family cohesion; whereas more specific dimensions such as emotional, tangible, informal, and formal support as community-level protective factors may provide more consistent relationships to family cohesion among African Americans.

Overall, our results offer support for a multilevel ecological approach to understanding the relationship between substance use and HIV risk behaviors, reinforcing the effect of risk- and protective-factor framework on adult behaviors. For instance, the greater the family cohesion, measured by greater participation in activities with family members and time spent together, stronger communication between family members, and family members assisting each other when in need, the less likely participants were to engage in ATOD use. These findings are generally consistent with the extant literature (Delva & Kameoka, 1999; Kowalyszyn & Kelly, 2003; Lucia & Breslau, 2006), The study results of Finzi-Dottan et al, however, were inconsistent with regard to the descriptions of relation between families and drug abuse. Their findings indicated no difference in relation to perceptions of family cohesion between the drug users and nonusers (Finzi-Dottan et al, 2003). Our findings also reinforce the notion that particular attention must be given to the interaction of ATOD use and HIV infection for those participants who are already sexually active. In other words, the present study suggests that more efforts must be directed to encourage availability of social support to attenuate risky behaviors among minority population, especially Hispanics/ Latinos and African Americans. In general, the results from separate gender analysis showed a similar trend as the overall sample. There were fewer significant path coefficients, however, which could be due to the low power.

Lower levels of intimate abuse, together with family cohesion, was associated with decreased ATOD use, a finding that has been replicated elsewhere (Fonseca et al, 2006). A study by Snow et al demonstrated that greater use of physical violence was strongly related to higher levels of injury among female partners and served to reduce problem drinking (Snow et al, 2006). Another study by Lipsky el al showed a close relations among Blacks, Hispanics, heavy drinking, illicit drug use, and intimate partner abuse (Lipsky et al, 2005). Elsewhere, alcohol consumption has been shown to be a proximal risk factor for partner violence (Murphy et al, 2005). Consistent with the literature, our result demonstrated that intimate abuse also contributes to ATOD use. Thus, it is reasonable to suggest that the relationship between intimate abuse and ATOD use may be bidirectional. Clearly, further study is warranted to verify this claim.

Consequently, as ATOD was positively related to HIV risk behaviors, it may be speculated that a decrease in ATOD use would be directly related to less engagement in unprotected sex (condom use), less likelihood of alcohol or drug use before sex, and less likelihood of having multiple sexual partners. Therefore, increased levels of protective factors such as family cohesion may reduce ATOD use and, in turn, have a direct impact on reducing HIV risk behaviors. All of these findings appear in line with the literature on substance use and HIV risk behaviors (Delva & Kameoka, 1999; Fals-Stewart & Kennedy, 2005; Hoffmann & Cerbone, 2002; Knight et al, 2005; Kumpfer, Alvarado, & Whiteside, 2003).

In conclusion, this study analyzed and illustrated an ecological systems model of the pathways of HIV risk behavior among minority populations. Specifically, the model predicted adults' pathways for two of the most prominent problem behaviors that may lead to HIV infection, substance use and risky sexual practices. By using structural equation modeling, the most likely linkages among constructs and the mediating factors can be empirically examined. This model investigated how protective factors, such as strength of family cohesion and intimate abuse, affected substance use, which, in tum, is related to HIV risky sexual behaviors. To our knowledge, our present study is the one of the first studies that examined an ecological model by employing both risk and protective factors using a latent structural model with regard to factors that may lead to HIV risky sexual practices in minority adult populations.


First, because the study was cross-sectional, the causality of relationships among the constructs cannot be determined. Second, the data to support these findings are based on self-reported questionnaires and may be subject to response bias. Third, respondent age has a wide range in this study and may be of interest in future studies to examine the age effect. However, the sample size in this study was insufficient to break age into several categories. Without conducting theoretical study models such as the latent structural model, however, the mechanisms of interrelationships among factors and the application of these findings to prevention research and to intervention activities or services within programs would not be clear to practitioners.

Future Implications

Prevention efforts must focus on groups at greatest risk for HIV infection; currently those groups are African American and Hispanic/Latino populations. To be successful, HIV prevention programs must include activities that take into account the multiple factors that interact to place minorities at higher risk for such health conditions. In addressing HIV risk, programs must take into account the multiple factors that interact together with other problem behaviors, such as drinking and substance use. Sensitivity to ethnic and cultural factors, such as family or community contexts and dynamics, should be present throughout all prevention activities and not simply addressed through language adaptation or one-shot sessions. Interventions must be relevant to the lives of family units, incorporating activities that support parent/caregiver and community involvement in education and academic achievement.

Furthermore, the significant relationship that neighborhood attachment had to more proximal constructs suggests that the use of community coalitions to mobilize prevention resources and to coordinate HIV and drug use prevention activities should be explored. Community coalitions can play a role in assisting neighborhoods in identifying, planning and adopting effective evidence-based ATOD prevention programs. Because coalitions include stakeholders and other constituents, they become important to the implementation and success of drug abuse prevention programs among minorities (Valente, Chou, & Pentz, 2007). In minority communities, by bringing together members of the community with representatives from the local government health department and other community based organizations, coalitions can be more successful than the work of a single agency in implementing prevention programs.

It is further recommended that developing strategies for the implementation of programs with high risk populations, such as HIV testing as an ongoing/routine health procedure, family communication techniques, and media campaigns or public service announcements that include the most up-to-date trends, statistics, and resources, be done in partnership with the minority population to be served by these programs.

Acknowledgments: This research was supported under the Center for Substance Abuse Prevention Contract No. 277-00-6207 to ORC Macro International. Dr. Bellamy worked on this article in her private capacity. The authors wish to thank Dr. Kevin P. Mulvey, CSAP Branch Chief, for his support; and appreciation is extended to all the staff at the grant program sites and participants.

Contents of this article are solely the responsibility of the authors and do not necessarily reflect the opinions, official policy, or position of the US Department of Health and Human Services, the Substance Abuse and Mental Health Service Administration, or the Center for Substance Abuse Prevention.

Correspondence concerning this article shoudl be addressed to: Min Qi Wang, Ph.D., Professor, Department of Public and Community Health, University of Maryland, Suite 2387 Valley Drive, College Park, MD 20742; Tel: (301) 405-6652; Fax: (301) 314-9167; email:


Bentler, P.M. (1995). EQS Structual Equations Program Manual. Encino: Multivariate Software, Inc.

Bogenschneider, K. (1996). An ecological risk/protective theory for building prevention programs, policies, and community capacity to support youth. Family Relations, 45, 127-138.

Boyer, C.B., Tschann, J.M., & Sharer, M.A. (1999). Predictors of risk for sexually transmitted diseases in ninth grade urban high school students. Journal of Adolescent Research, 14(4), 448-465.

Bronfenbrenner, U. (1979). The ecology of human development: Experiments by nature and design. Cambridge, MA: Harvard University Press.

Bronfenbrenner, U. (1986). Ecology of the family as a context for human development: Research perspectives. Developmental Psychology, 22, 723-742.

Brown, L.S., Jr., Kritz, S.A., Goldsmith, R.J., Bini, E.J., Rotrosen, J., Baker, S., Robinson, J., & McAuliffe, P. (2006). Characteristics of substance abuse treatment programs providing services for HIV/ AIDS, hepatitis C virus infection, and sexually transmitted infections: the National Drug Abuse Treatment Clinical Trials Network. Journal of Substance Abuse and Treatment, 30(4), 315-321.

Brown-Peterside, P., Ren, L., Chiasson, M. A., & Koblin, B. A. (2002). Double trouble: violent and non-violent traumas among women at sexual risk of HIV infection. Women Health, 36(3), 51-64.

Bryan, A., Schmiege, S.J., & Broaddus, M.R. (2007). Mediational Analysis in HIV/AIDS Research: Estimating Multivariate Path Analytic Models in a Structural Equation Modeling Framework. AIDS and Behavior, 11(3), 365-383

Cameron, G., & Vanderwoerd, J. (1997). Protecting children and supporting families. New York, NY: Aldine de Gruyter.

Capaldi, D.M., Stoolmiller, M., Clark, S., & Owen, L.D. (2002). Heterosexual risk behaviors in at-risk young men from early adolescence to young adulthood: prevalence, prediction, and association with STD contraction. Developmental Psychology, 38(3), 394-406.

Carey, M.P., Chandra, P.S., Carey, K.B., & Neal, D.J. (2003). Predictors of HIV risk among men seeking treatment for substance abuse in India. Archives of Sex Behavior, 32(4), 339-349.

Carey, M. E, Carey, K.B., Maisto, S. A., Gordon, C. M., Schroder, K. E. & Vanable, P.A. (2004). Reducing HIV-Risk Behavior Among Adults Receiving Outpatient Psychiatric Treatment: Results From a Randomized Controlled Trial. Journal of Consulting Clinical Psychology, 72(2), 252-268.

Centers for Disease Control and Prevention. (2004). HIV/AIDS Surveillance Report, 2003 (Vol. 15). Atlanta: U.S. Department of Health and Human Services, Center for Disease Control and Prevention, 1-46.

Centers for Disease Control and Prevention. (2005). HIV/AIDS surveillance report 2005, (Vol. 17). Atlanta, Georgia: US Department of Health and Human Services, CDC. Retrieved May 8, 2007, from 2005report/pdf/2005SurveillanceReport.pdf

Centers for Disease Control and Prevention. (2007). Racial/ethnic disparities in diagnoses of HIV/AIDS--33 states, 2001-2005. MMWR Morb Mortal Wkly Rep, 56(9), 189-193.

Center for Substance Abuse Prevention (CSAP). (2002). Youth Mentoring and Family Strengthening Program Dissemination Initiative Cross-Site Instrument. U.S. Department of Health and Human Services (Ed.), 1 Choke Cherry Road, Rockville. MD.

Copenhaver, M.M., & Lee, I.C. (2006). Optimizing a community-friendly HIV risk reduction intervention for injection drug users in treatment: A Structural Equation Modeling Approach. Journal of Urban Health, 83(6), 1132-1142.

Dekovic, M. (1999). Risk and protective factors in the development of problem behavior during adolescence. Journal of Youth and Adolescence, 26, 667-685.

Delva, J., & Kameoka, V.A. (1999). Risk for alcohol and drug abuse among ethnically diverse female recipients of public assistance. Ethnicity and Disease, 9(2), 237-245.

Donnelly J, G.E.S., Ferraro, H, et al. (2001). Assessing sexuality attitudes and behaviors and correlates of alcohol and Drugs. Psychological Reports, 88, 849-853.

Dressier, W. (1985). Extended family relationships, social support, and mental health in a southern Black community. Journal of Health and Social Behavior, 26, 39-48.

Ebrahim, S.H., Anderson, J.E., Weidle, P., & Purcell, D.W. (2004). Race/ethnic disparities in HIV testing and knowledge about treatment for HIV/AIDS: United States, 2001. AIDS Patient Care STDS, 18(1), 27-33.

Estrada, A.L. (2005). Health disparities among African-American and Hispanic drug injectors--HIV, AIDS, hepatitis B virus and hepatitis C virus: a review. Aids, 19 Supplement 3, S47-52.

Fals-Stewart, W., & Kennedy, C. (2005). Addressing intimate partner violence in substance-abuse treatment. Journal of Substance Abuse and Treatment, 29(1), 5-17.

Finzi-Dottan, R., Cohen, O., Iwaniec, D., Sapir, Y., & Weizman, A. (2003). The drug-user husband and his wife: attachment styles, family cohesion, and adaptability. Substance Use and Misuse, 38(2), 271-292.

Fonseca, C.A., Schmaling, K.B., Stoever, C., Gutierrez, C., Blume, A.W., & Russell, M.L. (2006). Variables associated with intimate partner violence in a deploying military sample. Military Medicine, 171(7), 627-631.

Francis, H. (2003). Substance abuse and HIV infection. Top HIV Med, 11(1), 20-24.

Hoffmann, J.P., & Cerbone, F.G. (2002). Parental substance use disorder and the risk of adolescent drug abuse: an event history analysis. Drug and Alcohol Dependence, 66(3), 255-264.

Jessor, R., Turbin, M.S., & Costa, F.M. (1998). Protective factors in adolescent health behavior. Journal of Personality and Social Psychology, 75, 788-800.

Jessor, R., Van Den Bos, J., Vanderryn, J., Costa, F. M., & Turbin, M. S. (1995). Protective factors in adolescent problem behavior: Moderator effects and developmental change.. Developmental Psychology, 31(6), 923-933.

J6reskog, K.G., Bollen, K. A., Long, J. S. (1993). 12. Testing Structural Equation Models. in Testing Structural Equation Models: Sage Publications: Newbury Park. p. 294-316.

Kalichman, S.C., Cherry, C., & Browne-Sperling, F. (1999). Effectiveness of a video-based motivational skills-building HIV risk-reduction intervention for inner-city African American men. Journal of Consulting and Clinical Psychology, 67(6), 959-66.

Knight, K.R., Purcell, D., Dawson-Rose, C., Halkitis, EN., & Gomez, C.A. (2005). Sexual risk taking among HIV-positive injection drug users: contexts, characteristics, and implications for prevention. AIDS Education and Prevention, 17(1 Suppl A), 76-88.

Knowlton, A.R., Hua, W., & Latkin, C. (2005). Social support networks and medical service use among HIV-positive injection drug users: implications to intervention. AIDS Care, 17(4), 479-492.

Kowalyszyn, M., & Kelly, A.B. (2003). Family functioning, alcohol expectancies and alcohol-related problems in a remote aboriginal Australian community: a preliminary psychometric validation study. Drug and Alcohol Review, 22(1), 53-59.

Kumpfer, K.L., Alvarado, R., & Whiteside, H.O. (2003). Family-based interventions for substance use and misuse prevention. Substance Use and Misuse, 38(11-13), 1759-1787.

LaLota, M., Kwan, B.W., Waters, M., Hernandez, L.E., & Liberti, T.M. (2005). The Miami, Florida, Young Men's Survey: HIV prevalence and risk behaviors among urban young men who have sex with men who have ever runaway. Journal of Urban Health, 82(2), 327-338.

Latkin, C.A., Forman-Hoffman, V.L., D'Souza, G., & Knowlton, A.R. (2004). Associations between medical service use and HIV risk among HIV-positive drug users in Baltimore, MD. AIDS Care, 16(7), 901-908.

Lichtenstein, B. (2005). Domestic violence, sexual ownership, and HIV risk in women in the American deep south. Soc Sci Med, 60(4), 701-714.

Liddle, H.A. (1999). Theory development in a family-based therapy for adolescent drug abuse. Journal of Clinical and Child Psychology, 28(4), 521-532.

Lipsky, S., Caetano, R., Field, C.A., & Bazargan, S. (2005). The role of alcohol use and depression in intimate partner violence among black and Hispanic patients in an urban emergency department. American Journal of Drug and Alcohol Abuse, 31(2), 225-242.

Lucia, V.C., & Breslau, N. (2006). Family cohesion and children's behavior problems: a longitudinal investigation. Psychiatry Research, 141(2), 141-149.

Maisto, S.A., Carey, M.P., Carey, K.B., Gordon, C.M., & Schum, J.L. (2004a). Effects of alcohol and expectancies on HIV-related risk perception and behavioral skills in heterosexual women. Experimental and Clinical Psychopharmacology, 12(4), 288-297.

Maisto, S.A., Carey, M.E, Carey, K.B., Gordon, C.M., Schum, J.L., & Lynch, K.G. (2004b). The relationship between alcohol and individual differences variables on attitudes and behavioral skills relevant to sexual health among heterosexual young adult men. Archives of Sex Behaviors, 33(6), 571-584.

Marsiglia, F.F., Kulis, S., Hecht, M.L. (2001). Ethnic labels and ethnic identity as predictors of drug use among middle school students in the Southwest. Journal of Research on Adolescence 11(1), 21-48.

McLeroy, K.R., Bibeau, D., Steckler, A., & Glanz, K. (1988). An ecological perspective on health promotion programs. Health Education Quarterly 15(4), 351-377.

Merson, M.H. (2006). The HIV-AIDS pandemic at 25--the global response. New England Journal of Medicine, 354(23), 2414-2417.

Moos, R.H.M., Bernice S. (1974). Family Environment Scale Family Environment Scale Palo Alto: Consulting Psychologists Press.

Murphy, C.M., Winters, J., O'Farrell, T.J., Fals-Stewart, W., & Murphy, M. (2005). Alcohol consumption and intimate partner violence by alcoholic men: comparing violent and nonviolent conflicts. Psychology of Addictive Behavior, 19(1), 35-42.

Qian, H.Z., Taylor, R.D., Fawal, H.J., & Vermund, S.H. (2006). Increasing AIDS case reports in the South: U.S. trends from 1981-2004. AIDS Care, 18(7), 6-9.

Rangel, M.C., Gavin, L., Reed, C., Fowler, M.G., & Lee, L.M. (2006). Epidemiology of HIV and AIDS among adolescents and young adults in the United States. Journal of Adolescent Health, 39(2), 156-163.

Rutter, M. (1987). Psychosocial resilience and protective mechanisms. American Journal of Orthopsychiatry, 57, 316-331.

Snow, D.L., Sullivan, T.P., Swan, S.C., Tate, D.C., & Klein, I. (2006). The role of coping and problem drinking in men's abuse of female partners: test of a path model. Violence Victim, 21(3), 267-285.

Spoth, R., Redmond, C., & Shin, C. (1998). Direct and indirect latent-variable parenting outcomes of two universal family-focused preventive interventions: extending a public health-oriented research base. Journal of Consulting and Clinical Psychology, 66(2), 385-399.

Steele, C.B., Richmond-Reese, V., & Lomax, S. (2006). Racial and ethnic disparities in HIV/AIDS, sexually transmitted diseases, and tuberculosis among women. Journal of Womens Health (Larchmt), 15(2), 116-122.

Thoits, P. A. (1995). Stress, coping, and social support processes: Where are we? What next? Journal of Health and Social Behavior, (Extra Issue), 53-79.

Unger, J.B., Kipke, M.D., De Rosa, C.J., Hyde, J., Ritt-Olson, A., & Montgomery, S. (2006). Needle-sharing among young IV drug users and their social network members: The influence of the injection partner's characteristics on HIV risk behavior. Addictive Behavior, 31(9), 1607-1618.

Unger, D. G., & Wandersman, L. P. (1988). The relation of family and partner support to the adjustment of adolescent mothers. Child Development, 59, 1056-1060.

Valente, T. W., Chou, C. P., & Pentz, M. (2007). Community coalitions as a system:Effects of network change on adoption of evidence-based substance abuse prevention. American Journal of Public Health, 97, 880-886.

Wang, M.Q., Matthew, R.F., Bellamy, N., & James, S. (2005). A structural model of the substance use pathways among minority youth. American Journal of Health Behavior, 29(6), 531-541.

Ward, E.G., Disch, W.B., Levy, J.A., & Schensul, J.J. (2004). Perception of HIV/AIDS risk among urban, low-income senior-housing residents. AIDS Education and Prevention, 16(6), 571-588.

Winstanley, E.L., Gust, S.W., & Strathdee, S.A. (2006). Drug abuse and HIV/AIDS: international research lessons and imperatives. Drug Alcohol Dependence, 82 Supplement 1, S1-5.

(1) Public Law 103-62 of 1993 requires all federal departments/agencies to develop strategic plans that specify what they will accomplish over a 3- to 5-year period.

Min Qi Wang, PhD, FAAHB, Resa F. Matthew, MPH, Yu-Wen Chiu, MD, Fang Yan, MD

University of Maryland


Nikki D. Bellamy, PhD

Center for Substance Abuse Prevention
Table 1. Summary of SEM Construct Items

Standardized Questionnaire Item

Neighborhood Attachment (alpha =.76)
0.589 1 would like to get out of my neighborhood
0.934 1 like my neighborhood
0.721 If I had to move, I would miss the neighborhood
 I live in now

Social Support (alpha =.86)
0.820 People to talk to about health
0.867 People to talk to about sex--Baseline
0.855 People to talk to about personal matters--

Family Cohesion (alpha=.87)
0.548 I'm available when others in my family want to
 talk to me
0.537 I listen to what other family members have to
 say, even when I disagree
0.741 Members of my family ask each other for help
0.833 Member of my family like to spend free time
 with each other
0.851 Member of my family feel very close to
 each other
0.842 We can easily think of things to do together
 as a family

Intimacy use (alpha = .71)
0.561 Past 3 months, how often emotionally abused
0.955 Past 3 months, how often physically abused
0.636 Past 3 months, how often sexually abused

Item 1 Used tobacco products during past 30-day
 (cigarettes, smokeless tobacco)
Item 2 Used alcohol during past 30-day
Item 3 Used marijuana during past 30-day
Item 4 Use inhalants during past 30-day
Item 5 Use illegal drugs, during past 30-day

HIV/AIDS Risky Behavior--Two Separate Constructs(explain one
did not have bearing thus dropped

Sex with risk partner
Item 1 During the past 3 months, did you have
 unprotected sex with partner with STD?
Item 2 During the past 3 months, did you have
 unprotected sex with partner with HIV/AIDS?
Item 3 During the past 3 months, did you have
 unprotected sex with partner with injecting

Drug-related sex
Item 1 During the past 3 months, did you have
 unprotected sex for money, drugs, shelter
Item 2 During the past 3 months, did you have sex
 under influence of alcohol or drugs?
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Author:Wang, Min Qi; Matthew, Resa F.; Chiu, Yu-Wen; Yan, Fang; Bellamy, Nikki D.
Publication:Journal of Alcohol & Drug Education
Date:Dec 1, 2007
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