Participants

1. Does Anxiety and Depression Prospectively Predict Alcohol Symptoms in Caucasian and Latino Young Adults? Ian K. Villalta, Laurie Chassin, and Armando A. Pina Department of Psychology, Arizona State University, Tempe, AZ Introduction Results Table 1. Means (SD) for PH, NA, PA, and AUD symptoms Results showed that the model depicted in Figure 1 fit the data well [χ2(3) = 6.75, p = .08, SRMR = .02, RMSEA = .04, CFI = .99]. Path coefficients indicate that COA status, sex, age, PH, and NA relate to AUD symptoms at Time 1. In addition, COA status, PA, and Time 1 AUD symptoms predict Time 2 AUD symptoms. • Data from the National Institute on Alcohol Abuse and Alcoholism show that about 18 million Americans suffer from alcohol use disorders (AUD) and National Comorbidity Study data indicate that a significant proportion of those with AUD also suffer from anxiety and depression (37% and 28%, respectively; Li, Hewitt, & Grant, 2004). There also are data showing that in some segments of Latinos there is a higher prevalence of AUD, depression, and anxiety symptoms compared to their Caucasian counterparts (NCLR, 2004). However, little is known about the relations from anxiety and depression to alcohol symptoms, particularly among Latinos. • Thus, the purpose of this study was to examine whether anxiety and depression prospectively and differentially predict alcohol symptoms, particularly among Latinos (mostly Mexican-origin young adults). To examine this issue, secondary analyses of data from Chassin, Rogosch, and Barrera (1991) and Chassin, Pitts, Delucia, and Todd (1999) were used, and anxiety and depression were conceptualized using Clark and Watson’s (1991) tripartite model. • According to Clark and Watson (1991): • High Negative Affect (+NA) is common to both anxiety and depression, low Positive Affect (-PA) is specific to depression and high Physiological Hyperarousal (+PH) to anxiety. • NA is measured as upset, angry, afraid, sad, stressed, guilty, disgusted, and worried. • PA is measured as active, delighted, enthusiastic, proud, and excited about life. • PH is measured as somatic symptoms of tension and anxiety such as feeling dizzy or lightheaded, shortness of breath, trembling, and/or shaking of hands. • Using +NA to denote both anxiety and depression, -PA for depression, and +PH for anxiety, the relations between each of these three components and alcohol symptoms were examined using structural equation modeling (see Figures 1 and 2). Note. AUD = Alcohol Use Disorder. Table 2. Correlations among the study’s variables Solid lines indicate significant paths. Dotted lines indicate non-significant paths. Figure 1. Path analytic model for full sample Note. COA = Children of Alcoholic. *p < .05, **p < .01, ***p < .001. Discussion • Overall, findings indicate that whereas physiological hyperarousal and negative affect are related to AUD symptoms, these factors do not predict AUD symptoms prospectively (over 5 years). Results also show that positive affect prospectively predicts AUD symptoms. These findings suggest that: • with age, young adults may use strategies for coping with anxiety and depression and rely less on alcohol to suppress negative emotionality. • the relation among anxiety, depression, and AUD symptoms becomes null perhaps because anxiety and depression sometimes remit spontaneously. • the positive affect result may reflect young adults’ alcohol use for social enhancement purposes, although its relation to clinical symptoms levels is of public health concern. • In terms of ethnicity, physiological hyperarousal, negative affect, and positive affect were related to AUD symptoms similarly across Caucasian and Latino young adults. These findings may be explained by: • the homogeneity of the Caucasian and Latino samples used in this study (e.g., the majority of participants were born in the U.S., all completed the measures in English). • anxiety and depression not placing Latino young adults at greater risk for AUD symptoms relative to their Caucasian counterparts. The present study has some implications for service providers: (1) clinicians working with clients who present with AUD symptoms should assess for the presence of anxiety and depression (and vise versa), (2) clinicians might need to conduct functional analyses of alcohol use to determine whether alcohol is being use to suppress negative emotionality or increase positive affect, (3) clinicians should consider using anxiety and depression reduction strategies as part of the their AUD treatment plans when working with Caucasian and Latino young adults. Method • Participants • Data corresponding to 660 young adults (50% female) who are participants in a larger ongoing longitudinal study of familial alcoholism were examined in this study (Chassin et al., 1991; Chassin et al., 1999). Among Latino participants, 90.75% reported being born in the U.S., 3% were born in Mexico, and the remaining were born elsewhere (Latin American country: 1%; non-Latin American country: 1%; 4.25% had missing data on this variable). Additional sociodemographic data are as follow: • Measures • Mood and Anxiety Symptom Questionnaire (MASQ; Watson, Clark, et al., 1995) • Child Behavior Checklist – Somatic scale (CBCL; Achenbach & Edelbrock, 1981) • DSM-IV AUD symptom checklist (Chassin et al., 1991; 1999) • Procedures • COAs were identified using court records, health maintenance organization (HMO) wellness questionnaires, and community telephone surveys. Non-COAs were identified using reverse directories to find individuals residing in the same neighborhood as the identified COAs. After providing informed consent (assent for children), measures were administered by trained research assistants and all participants completed the measures in English. Solid lines indicate significant paths. Dotted lines indicate non-significant paths. Figure 2. Path analytic model tested by ethnicity Figure 2 shows a model used to test the relations between the study’s focal variables by ethnicity (Caucasian vs. Latinos). The fit indices pertaining to the model tested by ethnicity, constrained, indicated good model fit [χ2(31) = 33.41, p = .35, SRMR = .04, RMSEA = .02, CFI = .99] [the unconstrained model also showed good fit, χ2(6) = 11.04, p = .09, SRMR = .02, RMSEA = .05, CFI = .99]. A chi-square difference test comparing the fit of the constrained model and unconstrained model showed that the model grouped by ethnicity was invariant [∆χ2(25) = 25.55, p = .43]. Analyses also were conducted with COA status, sex, and age as focal independent variables and results showed invariance across the models corresponding to these variables with one exception: there was variance across sex. However, when the relations among the Time1 variables were freely estimated the model was invariant. Acknowledgement: This research was made possible by a grant from the National Institute of Alcohol Abuse and Alcoholism (AA16213) awarded to Laurie Chassin, Ph.D. and funding from the APA – MFP awarded to Ian K. Villalta.