Sean D. Kristjansson Andrew C. Heath Andrey P. Anokhin Substance Use Among Older Adolescents: A Latent Class Analysis.

Slides:



Advertisements
Similar presentations
Predictors of Change in HIV Risk Factors for Adolescents Admitted to Substance Abuse Treatment Passetti, L. L., Garner, B. R., Funk, R., Godley, S. H.,
Advertisements

Background: The low retention rates among African Americans in substance abuse treatment (Milligan et al., 2004) combined with the limited number of treatments.
Panic Symptoms, Cigarette Smoking and Drinking in Adolescent Female Twins Michele Pergadia, Andrew C. Heath, Kathleen K. Bucholz, Elliot C. Nelson, Christina.
Effects of childhood exposure to paternal alcoholism on substance use disorders in adolescents and young adults A.E. Duncan,Q. Fu, K.K. Bucholz, J.F. Scherrer,
Early Alcohol Use as a Risk Factor for Drug Use and Dependence.
Fake IDs, Getting Caught, and Heavy Drinking Julia A. Martinez and Kenneth J. Sher University of Missouri-Columbia and the Midwest Alcoholism Research.
Race and Socioeconomic Differences in Health Behavior Trajectories Across the Adult Life Course ACKNOWLEDGEMENTS This research was supported by the grant.
HIV Risk Behaviors and Alcohol Intoxication among Injection Drug Users in Puerto Rico Tomás D. Matos, MS Center for Addiction Studies Universidad Central.
EARLY CIGARETTE USE BEHAVIORS AND ALCOHOL Pamela A.F. Madden, Ph.D.*, Michele Pergadia, Ph.D., Michael Lynskey, Ph.D., and Andrew C. Heath, D.Phil. Washington.
Is Psychosocial Stress Associated with Alcohol Use Among Continuation High School Students? Raul Calderon, Jr. Ph.D., Gregory T. Smith, Ph.D., Marilyn.
Factors Related to Adolescent Alcohol Use Progression Matos TD, Robles RR, Reyes JC, Calderón J, Colón HM, Negrón-Ayala JL CENTER FOR ADDICTION STUDIES,
Trends in Detection Rates of Risky Marijuana Use in CO Healthcare Settings.
Moscow Substance Use Statistics Source: Moscow School District Substance Use and School Climate Surveys 1996,1998, 2000, 2002, 2004, 2006, 2008, 2010.
ALCOHOL USE DISORDERS AND TEENAGE SEXUAL INTERCOURSE A.E. Duncan, J.F. Scherrer, K.K. Bucholz, W.R. True and T. Jacob.
Correlates of Driving Under the Influence of Alcohol in Adolescence A Secondary Data Analysis of the 1992 National Health Behavior Survey Presented at.
Suicidal thoughts and behaviors in African-American and European- American youth in a community family study of alcoholism Ellen L. Edens, Anne L. Glowinski,
THE RELATIONSHIP BETWEEN BMI AND SUICIDALITY IN YOUNG ADULT WOMEN Alexis E. Duncan, Pamela A.F. Madden, and Andrew C. Heath Washington University Department.
THE RELATIONSHIP BETWEEN ADOLESCENT/YOUNG ADULT BMI AND SUBSEQUENT NON- PROBLEM AND PROBLEM ALCOHOL USE Alexis E. Duncan, Kathleen Keenan Bucholz, Pamela.
Table 1 Introduction  Overview  While predictors of recidivism and technical violations are often examined in probation and parole outcome research,
Alaska Youth Risk Behavior Survey A joint project between the Department of Education and Early Development and Department of Health and Social Services.
Does prenatal exposure modify the response to first use of alcohol and tobacco? Valerie S. Knopik, Kathleen K. Bucholz, Michele L. Pergadia, Andrew C.
Parental Alcohol Problems and Early Sexual Debut in Young Adult Women Claudia Gambrah, Alexis E. Duncan, Andrew C. Heath.
Introduction ► College-student drinking remains a significant problem on campuses across the nation. ► It is estimated that 38-44% of college students.
Spacebar to advance slide click the spacebar on your keyboard when you are ready to advance the slide. Spacebar.
Effect of Depression on Smoking Cessation Outcomes Sonne SC 1, Nunes EV 2, Jiang H 2, Gan W 2, Tyson C 1, Reid MS 3 1 Medical University of South Carolina,
Introduction Smoking and Social Networks Joseph R. Pruis, Student Research Collaborator, Rosemary A. Jadack, PhD, RN, Professor Department Of Nursing,
1 Relationship Between Prenatal Maternal Smoking and Drinking and Subtypes of ADHD in Two Population Based Samples of Missouri Twins R.J. Neuman A.C. Health.
Do Sex and Drug Behavior Patterns Account for HIV/STD Racial Disparities? May 8, 2007 Denise Hallfors, Ph.D. Bonita Iritani, M.A.
Jeffrey F. Scherrer, Kathleen K. Bucholz, Pamela A.F. Madden, Andrew C. Heath, Theodore Jacob, Hong Xian The Contribution of Parent, Sibling and Friend.
Jeffrey F. Scherrer (1,2); Hong Xian (2); Andrew C. Heath (1,2); Theodore Jacob (1); William R. True (1,3), Kathleen K. Bucholz (1,2) Smoking in Offspring.
Consistency in Reports of Early Alcohol Use Supported by grants AA009022, AA007728, & AA (NIAAA); HD (NICHD) and DA18660 (NIDA) Carolyn E.
Typologies of Alcohol Dependent Cocaine-using Women Enrolled in a Community-based HIV Intervention Victoria A. Osborne, Ph.D., MSW*, Linda B. Cottler,
EXPERIENCES OF SEXUAL VIOLENCE AMONG ADOLESCENTS IN BOTH URBAN AND RURAL KENYA The 8th Pan-African PCAF Psychotrauma Conference Victoria Mutiso, PhD, Senior.
DrugEpi 6 - Reverse Time Order Module 4 Overview Context Content Area: Interpretation of Epidemiological Evidence Essential Question (Generic): Is the.
Lexington High School Youth Risk Behavior Survey Results Ten Year Trends.
Participants were recruited from 6 drug free, psychosocial treatment (PT) and 5 methadone maintenance (MM) programs (N = 628) participating in a NIDA Clinical.
FIRST REACTIONS TO CIGARETTES AND ALCOHOL Pamela Madden, Ph.D. Andrew C. Heath, D.Phil. Kathleen Bucholz, Ph.D. Christina Lessov, Ph.D. Michele Pergadia,
Introduction Introduction Alcohol Abuse Characteristics Results and Conclusions Results and Conclusions Analyses comparing primary substance of abuse indicated.
Children and Adults with Spina Bifida: Exploring Secondary Psycho-Social Conditions Andrea Hart, Ph.D. Betsy Johnson, M.S.W. and Lorraine McKelvey, Ph.D.
Associations Among Parental Alcohol Problems, Trauma, and Depression in a Twin Sample Vivia V. McCutcheon, MSW; Andrew C. Heath, D.Phil.; Elliot C. Nelson,
Mary Hrywna, MPH Cristine D. Delnevo, PhD, MPH Dorota Staniewska, MS University of Medicine & Dentistry of New Jersey (UMDNJ) School of Public Health (SPH)
Introduction Results and Conclusions Analyses of demographic and social variables revealed that women were more likely to have children, be living in a.
METHODS Sample: The Institute for Survey Research of Temple University conducted face-to-face interviews for the 1995 National Alcohol Survey (NAS). The.
Studying the transition to college: A new prospective study IMPACTS Supported by National Institute on Alcohol Abuse and Alcoholism Grant 4 R37 AA
Introduction Results and Conclusions On counselor background variables, no differences were found between the MH and SA COSPD specialists on race/ethnicity,
Predicting Stage Transitions in the Development of Nicotine Dependence Carolyn E. Sartor, Hong Xian, Jeffrey F. Scherrer, Michael Lynskey, William True,
Substance Use among Older Adults (Age 50+): Current Prevalence and Future Expectations Presented by Joe Gfroerer U.S. DEPARTMENT OF HEALTH AND HUMAN SERVICES.
Genetic and Environmental Influences on Perceived Peer Alcohol Use During Adolescence Julia D. Grant 1, Kathleen K. Bucholz 1, Pamela A.F. Madden 1, Wendy.
Drinking practices and problems in adolescents: Evidence from female and male twins K. K. Bucholz, Ph.D, S.A. Ryan, M.S.P.A., P.A.F. Madden, Ph.D., A.C.
TM Substance Use Transitions from Initial Use to Regular Use to Discontinuance Ralph S. Caraballo, Ph.D., MPH Office on Smoking and Health, CDC, Atlanta.
Disability, Cigarette Smoking And Health-Related Quality Of Life: NYS Adult Tobacco Survey Harlan R. Juster, PhD Larry L. Steele, PhD Theresa M. Hinman,
Transitions in Conjoint Alcohol and Tobacco Use among Adolescents Kristina M. Jackson University of Missouri, Columbia & Missouri Alcoholism Research Center.
Introduction ► Despite efforts to reduce heavy drinking among college students, college-student alcohol use and its negative consequences remains a concern.
Introduction Results and Conclusions Numerous demographic variables were found to be associated with treatment completion. Completers were more likely.
Race, tobacco, and alcohol in a high risk family study Alexis Duncan, Wilma Calvert, Collins Lewis, and Kathleen Bucholz.
Stephen Nkansah-Amankra, PhD, MPH, MA 1, Abdoulaye Diedhiou, MD, PHD, H.L.K. Agbanu, MPhil, Curtis Harrod, MPH, Ashish Dhawan, MD, MSPH 1 University of.
Method Introduction Results Discussion Mean Negative Cigarette Systoli Previous research has reported that across the nation 29% of college students engage.
California Healthy Kids Survey King City Joint Union High School District 2007/08 Results grades 9 & 11.
Research on the relationship between childhood sleep problems and substance use in adolescents and young adults is limited. This knowledge gap has been.
SSDS Inc. Intentional injury in the U.S. Army: Is a college education the answer? Nicole S. Bell, ScD, MPH Thomas C. Harford, PhD Social Sectors Development.
Comparison of Substance Use Trends and Consequences among Virgin Islands Public High School Students and their US Mainland Counterparts: Results of the.
DISCUSSION & CONCLUSIONS
New York State Suicide Prevention Conference
Percentage of Middle School Students Who Rarely or Never Wore a Seat Belt,* by Sex, Grade, and Race/Ethnicity,† 2017 Data for this slide are from the 2017.
1 & 1 Workshop: Latent Transition Analysis
An Introduction to Latent Class Analysis (LCA)
VACS Scientific Meeting Houston, TX February 2004
Types of questions TVEM can answer
Arely M. Hurtado1,2, Phillip D. Akutsu2, & Deanna L. Stammer1
Presentation transcript:

Sean D. Kristjansson Andrew C. Heath Andrey P. Anokhin Substance Use Among Older Adolescents: A Latent Class Analysis

Introduction The use of alcohol, tobacco and illicit substances by adolescents is a major public health concern. Adolescents often use multiple substances concurrently. Prior studies have described heterogeneous profiles of concurrent substance use and abuse in adults. However, few studies have empirically identified the cross-sectional profiles of concurrent alcohol, tobacco and marijuana use in older adolescents.

Goals of the present study: Use latent class analysis (LCA) to identify latent subgroups of adolescents defined by heterogeneous profiles of concurrent alcohol, tobacco and marijuana use. Identify risk factors associated with membership in the latent classes.

1. LCA would identify classes defined by distinct substance use profiles, including: C) Reported depression symptoms D) Reported oppositional defiant disorder (ODD) symptoms A low-risk class (minimal substance use). One or more concurrent substance use classes. Hypotheses: A) Were male B) Were White 2. Classes defined by profiles of concurrent substance use would include higher proportions of members who:

Method: Participants: 1500 Twins ascertained from the Missouri Twin registry. Mean Age: 18.3 years (Range: ). Inclusion criterion: Not yet attending college (n = 1376). Assessments: Semi-structured Interview for the study of the Genetics of Alcoholism (C-SSAGA), administered via telephone. Mailed self-report questionnaires. Assessed: - Demographic information. - Alcohol, tobacco and marijuana use histories. - DSM-IV depression and ODD symptoms. Data were collected near the end of the participants’ senior year in high school.

Ever had 1 drink64.3 % Had 1 drink on 24 or more days29.1 % Ever binge drank (males: 5 drinks in 24hrs. / females: 4 drinks)45.9 % Binge drank (within last year)37.1 % Binge drank (within last 30 days)19.8 % Ever smoked 1 cigarette45.3 % Smoked > 100 cigarettes15.8 % Ever used marijuana30.7 % Used marijuana > 20 times11.3 % Ever felt sick / vomited due to drinking27.5 % Ever blacked out due to drinking13.4 % Substance Use Variables: (dichotomous) % endorsed item (Total n = 1376) Descriptive statistics:

Gender (Male)34.9 % Race (White)82.6 % 3 Depression symptoms10.2 % > 5 ODD symptoms21.5 % Risk Factors: (dichotomous) Total n = 1376 % of total ODD and Depression symptom counts were dichotomized because the distributions were skewed. Cut-offs were chosen to identify participants at relatively high risk for psychopathology. Descriptive statistics:

Analyses: Latent class analyses were computed using Mplus 5.1. The Bayesian Information Criterion (BIC) was used to determine the optimal number of latent classes. The LCAs computed the probabilities of class membership for each individual, and individuals were assigned to the class for which the probability of membership was highest. Risk factors were included in the LCAs as covariates. (latent classes were regressed onto the risk factors using simultaneous multinomial logistic regression). The covariate analyses tested for differences in the proportions of members in each class (relative to a reference class) who were male, white and who reported 3 depression symptoms and 5 or more ODD symptoms.

Results 1.Low-risk (n= 592): Minimal substance use. 2. Experimenter (n= 146): Tried alcohol, tobacco and marijuana. 3. Occasional Binger (n= 203): Tried binge drinking, but tended not to use tobacco or marijuana. 4. Regular Binger (n= 228): Binge drank regularly, tried tobacco and marijuana but had not progressed to regular co-use. 5. Smoker (n= 79): Used tobacco regularly, used marijuana frequently but did not binge drink regularly. 6. Polysubstance User (n= 128): Concurrent use of all substances. BIC indicated a 6-class model best fit the data. Classes are described according to the probability that the class endorsed each substance use variable (i.e., item endorsement probability profiles-- substance use patterns). Class Descriptions

Results: Item Endorsement Probability Profiles Ever Had 1 Drink Had 1 Drink on 24 or More Days Ever Binge Drank Binge Drank (Last Year) Binge Drank (Last 30 Days) Ever Smoked 1 Cigarette Smoked 100 or More Cigarettes Ever Used MJ Used MJ More Than 20 Times Ever Felt Sick / Vomited Ever Blacked Out Polysubstance User 9.3% Regular. Binger 16.6% Occasional Binger 14.8% Experimenter 10.6% Smoker 5.7% Low-risk 43.0% Probability of Class Endorsing Item

Low-riskExperimenterOccasional Binger Regular Binger Smoker Polysubstance User Covariate A) Male32.1%32.9%33.0%37.3%25.3%54.7% B) White79.4%55.5%91.6%94.7%88.6%88.3% C) 3 Depression Symptoms6.8%13.7%8.4%14.0%12.7%17.2% D) > 5 ODD Symptoms12.2%28.8%7.9%26.3%60.8%45.3% A) Were male B) Were White Percentage of members in each class who: C) reported at least 3 depression symptoms D) reported 5 or more ODD symptoms For each covariate, one set of analyses tested for differences in the proportions in each of the classes relative to the Low-risk (reference) class. Results: Risk Factors (covariate analyses)

Odds ratios (in rows) with different superscripts differ from each other (p <.05). ExperimenterOccasional Binger Regular Binger SmokerPolysubstance User Covariate A) Male1.15 a.74 b 2.40 c B) White.34 a 3.27 b C) 3 Depression Symptoms1.69 a D) > 5 ODD Symptoms2.48 a.71 b 2.48 a c 5.94 d For each covariate, another set of analyses tested for significant differences among the proportions in the experimenter, occasional binger, regular binger, smoker and polysubstance user classes. Odds ratios that are underlined differ relative to the low-risk class (p <.05). Results: Risk Factors (covariate analyses)

Probability of Class Membership Female White ODD Dep. Male White ODD Dep. Female Non- White ODD Dep. Male Non- White ODD Dep. Female White Male White Female Non- White Male Non- White Results: Probability of being a member of the classes as a function of risk factor combinations. Polysubstance User Regular Binger Occasional Binger Experimenter Smoker

Discussion As expected, the LCA identified latent classes defined by minimal use (low-risk class) and concurrent use of all substances (polysubstance user class). Intermediate classes included experimenters, occasional bingers, regular bingers and smokers. Relative to the low risk class, depression symptoms were associated with a small risk (OR = 1.69) for membership in the intermediate and polysubstance user classes. The risk factors related to the highest probability for being in the polysubstance user class were male gender, White race and ODD symptoms.

Discussion The risk factors related to the highest probability for being in the smoker class were female gender, White race and ODD symptoms. The risk factor related to the highest probability for being in the occasional binger class was White race. The risk factors related to the highest probabilities for being in the regular binger class were White race and ODD symptoms. The risk factors related to the highest probabilities for being in the experimenter class were non-white race and ODD symptoms.

Conclusion Supported by Grant No: AA13989 from the National Institute on Alcohol Abuse and Alcoholism to A.A. The results suggest that heterogeneous profiles of concurrent alcohol, tobacco and marijuana use exist in the older adolescent population, and these profiles are associated with specific risk factors. Knowledge about the typological heterogeneity of substance users in this age group can aid in developing more targeted prevention and intervention strategies.