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A Community Risk Assessment of the 90806 Zip Code

A Community Risk Assessment of the 90806 Zip Code. Mariana Estrada California State University, Long Beach May 2012. Introduction. Substance Use and Delinquency 10% of adolescents (12-17) were current illicit drug users ( SAMHSA , 2011). Marijuana use among teens increased in 2010.

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A Community Risk Assessment of the 90806 Zip Code

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  1. A Community Risk Assessment of the 90806 Zip Code Mariana Estrada California State University, Long Beach May 2012

  2. Introduction • Substance Use and Delinquency • 10% of adolescents (12-17) were current illicit drug users (SAMHSA, 2011). • Marijuana use among teens increased in 2010. • One in 16 high school seniors currently used marijuana on a daily or nearly daily basis (Monitoring the Future, 2010). • 13,120,947 youth (under 18) were arrested nationwide (FBI’s Uniform Crime Reporting Program, 2010). • 295 juveniles per 100,000 were detained in residential placements. • In California, 351 per 100,000 youth resided in detention or correctional facilities (Sickmund, Sladky & Kang, 2006). • Risk Factors • Substance use and delinquency are inter-related and youth who engage in these behaviors are also at increased risk for involvement in other adolescent problem behaviors (Vaugh et. al., 2005; Ford, 2005; Elickson & McGuigan, 2000; D’Amico, Edelen, Miles, & Morral, 2008). • Youths’ use of substances places them at risk of engaging in risky sexual behavior, early parenthood and pregnancy, educational challenges as well as negative outcomes as adults (Cavazo-Rehg et. al., 2011; Connell, Gilreath, & Hansen, 2009; Elickson et. al., 2003; Huizinga et. al., 1993; Engberg & Morral,2006; Ryan, 2010; McCarty, Ebel, Garrison, DiGiuseppe, Christakis & Rivara, 2004; McGue & Iacono, 2008). • Adolescents who engage in delinquency are more likely to experience negative outcomes such as school dropout, health risking sexual behaviors, teen parenting, mental health challenges, poor occupational attainment, as well as continued delinquency and incarceration (Hirschfield, 2009; Hair, Park, Ling, & Moore, 2009; Crosnoe, 2006; Wei, Loeber, and Stouthamer-Loeber, 2002; Hope, Wilder, & Watt, 2003; Leve & Chamberlain, 2004; Jordahl & Lohman, 2009; Aalsma, Tong, Wiehe, & Tu, 2010; Paternoster, Brame, & Farrington, 2001; Moffitt & Caspi, 2001; Wiesner & Windle, 2006; Wiesner, Capaldi & Kim, 2011).

  3. Prevention Research • Preventive interventions which focus on reducing empirically supported risk factors and promoting protective factors can reduce adolescent involvement in substance use, violence, and delinquency (Hawkins, Catalano & Arthur, 2002; Wong et. al., 1996). • Risk Factors for Substance Use and Delinquency • Availability of drugs and firearms • Community laws and norms favorable towards drug use, firearms and crime • Transitions and mobility • Low neighborhood attachment and community disorganization • Extreme economic deprivation • Family history of the problem behavior • Family management problems • Family conflict • Favorable parental attitudes and involvement in the problem behavior • Academic failure beginning in late elementary school • Lack of commitment to school • Early and persistent antisocial behavior • Rebelliousness • Friends who engage in the problem behavior • Gang involvement • Favorable attitudes toward the problem behavior • Early initiation of the problem behavior • Constitutional factors • (Wong et. al., 1996; Hawkins & Catalano, 2005).

  4. Social Work and Cross-Cultural Relevance • Social workers need to understand risk factors specific to each community to be able to assist the population effectively. • Awareness of risk factors for substance use and delinquency can aide social workers in developing and implementing effective prevention programs. • This knowledge can also prove beneficial for social workers who are advocating for increased resources in a community. • Adolescent involvement in substance use and delinquency varies by gender and ethnicity (Williams, Van Dorn, Ayers, Bright, Abbott & Hawkins, 2007; Jackson & Lecroy, 2009; Marsiglia, Kulis, Hecht, & Sills, 2004; Rodriguez, 2010; Bacon, Paternoster, & Brame, 2009; Le & Stockdale, 2011; Roche, Ensminger, & Cherlin, 2007; Farrington, Joliffe, Hawkins, Catalano, Hill, & Kosterman, 2010). • Despite differential level of involvement by ethnicity, gender, and socio-economic status, risk factors seem to be relevant across diverse ethnic groups (Williams et. al., 1999; Barrett & Turner, 2006; Ellickson & McGuigan, 2000; Choi et. al., 2005).

  5. Methods • The Communities That Care (CTC) model was used to assess the community risk factors for the 90806 zip code. • Information was gathered on 43 indicators of the 18 risk factors for substance use and delinquency. • Secondary sources including archival reports and websites were utilized. • Data was collected on the zip code area, local, state, and national locations depending on availability. However, in some instances, data was only available on the zip code and surrounding areas. • CTC Risk Factors • Availability of drugs was assessed using data on the number of retail liquor licenses (Liquor Control Board), percentage of students who reported that it was very easy to get alcohol and marijuana (California Healthy Kids Survey). Availability of firearms was assessed using data on students who reported bringing a gun to school in the past 12 months (California Healthy Kids Survey). • Community laws and norms favorable toward drug use firearms and crime were assessed using the indicator of juvenile arrests for drug offenses and weapons offenses (California Department of Justice). • Transitions and mobility was assessed using the percentage of renter-occupied housing units (U.S. Census Bureau) and the percentage of 5th graders who had moved more than once in the past year (California Healthy Kids Survey). • Low neighborhood attachment and community disorganizations was assessed using the percentage of people who felt safe in their neighborhood , percentage of people who strongly agreed that “neighbors don’t get along” (California Health Interview Survey), and homicide rates per 100,000 (California Department of Justice). • Extreme economic deprivation was analyzed using unemployment rates and the percentage of families living below the poverty line (U.S. Census Bureau). • Family history of the problem behavior was analyzed using adult felony arrest rates (California Department of Justice) and data on the percentage of adults who consumed 3 or more drinks per day (California Health Interview Survey). • Family management problems was assessed using the rate of child maltreatment allegations (Center for Social Services Research), the percentage of 5th graders who were home alone after school, (California Healthy Kids Survey), data on how often any adult was present after school hours and the percentage of parents who knew a lot about the whereabouts of their teens when they went out at night (California Health Interview Survey).

  6. Methods Continued • Risk Factors Continued • Family conflict was assessed using data on the rates of children with entries to foster care (Center for Social Services Research), percentage of grandparents responsible for grandchildren and the population 15 and over who were divorced (U.S. Census Bureau). • Favorable parental attitudes and involvement in the problem behavior was assessed by the percentage of adults who participated in binge drinking in the past year (California Health Interview Survey) and rates for adult felony arrests for violent offenses (California Department of Justice). • Academic failure beginning in late elementary school was assessed using STAR testing scores fore English language and Mathematics among 2nd to 5th graders (California Department of Education). • Lack of commitment to school was analyzed using the percentage of 5th graders who planned to go to college, the percentage of 5th graders who scored high on meaningful participation (California Healthy Kids Survey), high school graduation rates and high school truancy rates (California Department of Education). • Early and persistent antisocial behavior was analyzed using elementary school suspension rates (California Department of Education), percentage of 5th graders who had hit or pushed others (California Healthy Kids Survey). • Rebelliousness and alienation was assessed using the percentage of who had been hit or pushed at school and the percentage of 5th graders who had rumors spread about them at school (California Healthy Kids Survey). • Friends who engage in the problem behavior was assessed using the percentage of 5th graders who had friends who got into trouble most or all of the time and the percentage who scored high on having pro-social peers (California Healthy Kids Survey). • Gang involvement was assessed using the percentage of 7th, 9th, and 11th grade students involved in a gang (California Healthy Kids Survey). • Favorable attitudes toward the problem behavior was assessed using the percentage of students who reported disapproval of weapon possession and the percentage who perceived frequent use of alcohol and marijuana as harmful (California Healthy Kids Survey). • Early initiation of the problem behavior was analyzed using the percentage of people who were 10 years of age when they first smoked a cigarette (California Health Interview Survey), percentage of 5th graders who had ever used alcohol, inhalants or marijuana and the percentage who had brought a weapon on school property (California Healthy Kids Survey).

  7. Risk Factors • The data gathered from all the different sources was analyzed. • Data was converted into rates and percentages and graphed to gain an accurate understanding of how the 90806 compared to other localities. • When available data from previous years was graphed to determine whether there was a trend. • The researcher assessed the most crucial indicators of problem behaviors occurring in the 90806 zip code, by comparing risk factor trends to state or national trends, examining the risk factors from a developmental perspective , and identifying any risk factor “clusters” (Wong et. al., 1996).

  8. Discussion • Most salient risk factors for the 90806 • Community domain- extreme economic deprivation • Family domain-family history of the problem, favorable parental attitudes and family management. • School domain- academic failure • Peer and individual domain- friends who engage in the problem behavior and early initiation of the problem behavior.

  9. Discussion Continued • In the 90806, risk factors in all four domains were of concern multiple approaches and intervention programs will be needed to reduce substance use and delinquency rates. • Suggested Evidence-based Programs • CASASTART (National Center on Addiction and Substance Abuse at Columbia University, 2004). • Early Risers “Skills for Success” program (August, Realmuto, Winters, & Hektner, 2001). • Caring School Community program (Battistich, Schaps, &Wilson, 2004). • Adolescents Transitions Program (Dishion & Kavanagh, 2003). • Social Work Implications and Research • Social workers must advocate for community risk assessments to occur and mobilize community stakeholders. • Social workers should lead efforts in educating the community on effective ways to prevent adolescent problem behaviors. • Examining protective factors as well as risk factors is recommended for future research • An inventory of programs already in place would also be beneficial.

  10. References August, G. J., Realmuto, G. M., Winters, K. C., & Hektner, J. M. (2001). Prevention of adolescent drug abuse: Targeting high-risk children with a multifaceted intervention model—the early risers “Skills for Success” program. Applied & Preventive Psychology, 10, 135-153. Battistich, V., Schaps, E., Watson, M., Solomon, D., & Lewis, C. (2000). Effects of the child development project on students’ drug use and other problem behaviors. Journal of Primary Prevention, 21, 75-99. Cavazos-Rehg, P. A., Krauss, M. J., Spitznagel, E. L., Schootman, M., Cottler, L. B., & Bierut, L. (2011). Substance use and the risk for sexual intercourse with and without a history of teenage pregnancy among adolescent females. Journal of Studies on Alcohol & Drugs, 72(2), 194-198. Retrieved from EBSCOhost. Connell, C. M., Gilreath, T. D., & Hansen, N. B. (2009). A multiprocess latent class analysis of the co-occurrence of substance use and sexual risk behavior among adolescents. Journal of Studies on Alcohol & Drugs, 70(6), 943-951. Retrieved from EBSCOhost. D'Amico, E., Edelen, M., Miles, J., & Morral, A. (2008). The longitudinal association between substance use and delinquency among high-risk youth. Drug & Alcohol Dependence, 93(1-2), 85-92. Dishion, T. J., & Kavanagh, K. (2003). Intervening in adolescent problem behavior: A family-centered approach.New York: Guilford Press. Ellickson, P. L., & McGuigan, K. A. (2000). Early predictors of adolescent violence. American Journal of Public Health, 90(4), 566-572. Retrieved from EBSCOhost. Ellickson, P., Tucker, J., & Klein, D. (2003). Ten-year prospective study of public health problems associated with early drinking. Pediatrics, 111(5), 949-955. Engberg, J., & Morral, A. (2006). Reducing substance use improves adolescents' school attendance. Addiction, 101(12), 1741-1751. Federal Bureau of Investigations. (2010). Uniform Crime Reporting Program. Retrieved from http://www.fbi.gov/about-us/cjis/ucr/crime-in-the-u.s/2010/crime-in-the-u.s.-2010/persons-arrested Ford, J. A. (2005). Substance use, the social bond, and delinquency. Sociological Inquiry, 75(1), 109-128. doi:10.1111/j.1475-682X.2005.00114.x Hair, E., Park, M., Ling, T., & Moore, K. (2009). Risky behaviors in late adolescence: Co-occurrence, predictors, and consequences. Journal of Adolescent Health, 45(3), 253-261. doi:10.1016/j.jadohealth.2009.02.009 Hawkins, J. D. & Catalano, R. F. (2005) Investing in your community’s youth: an introduction to the communities that care system. Retrieved from http://www.sdrg.org/ctcresource/Community%20Building%20and%20Foundational%20Material/Investing%20in%20Your%20Community%27s%20Youth.pdf Hawkins, J., Catalano, R. F., & Arthur, M. W. (2002). Promoting science-based prevention in communities. Addictive Behaviors, 279(6), 951-976. Hirschfield, P. (2009). Another way out: The impact of juvenile arrests on high school dropout. 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Continuity of binge and harmful drinking from late adolescence to early adulthood. Pediatrics, 114(3), 714-719. McGue, M., & Iacono, W. G. (2008). The adolescent origins of substance use disorders. International Journal of Methods In Psychiatric Research, 17, S30-S38. doi:10.1002/mpr.242 Moffitt, T. E., & Caspi, A. (2001). Childhood predictors differentiate life-course persistent and adolescence-limited antisocial pathways among males and females. Development and Psychopathology, 13(2), 355-375. doi:10.1017/S0954579401002097 National Center on Addiction and Substance Abuse at Columbia University. (2004). CASASTART (Striving Together to Achieve RewardingTomorrows). New York: Author. Paternoster, R., Brame, R., & Farrington, D. P. (2001). On the relationship between adolescent and adult conviction frequencies. Journal of Quantitative Criminology, 17(3), 201. Retrieved from EBSCOhost. Ryan, A. (2010). The lasting effects of marijuana use on educational attainment in midlife. Substance Use & Misuse, 45(4), 554-597. doi:10.3109/10826080802490238 Substance Abuse and Mental Health Services Administration. (2009). Results from the 2008 National Survey on Drug Use and Health: National Findings (Office of Applied Studies, NSDUH Series H-36, HHS Publication No. SMA 09-4434). Rockville, MD. Vaughn, M. G., Howard, M. O., Foster, K. A., Dayton, M. K., & Zelner, J. L. (2005). Substance abuse in a statewide population of incarcerated juvenile offenders. Journal of Evidence-Based Social Work, 2(1/2), 155. doi:10.1300/J394v02n01•09 Wei, E. H., Loeber, R., & Stouthamer-Loeber, M. (2002). How many of the offspring born to teenage fathers are produced by repeat serious delinquents?. Criminal Behaviour & Mental Health, 12(1), 83. Retrieved from EBSCOhost. Wiesner, M., Capaldi, D. M., & Kim, H. K. (2011). Early adult outcomes of male arrest trajectories: Propensity versus Causation Effects. Western Criminology Review, 12(3), 75-89. Wiesner, M., & Windle, M. (2006). Young adult substance use and depression as a consequence of delinquency trajectories during middle adolescence. Journal of Research on Adolescence, 16(2), 239-264. Wong, S. C., Burgoyne, K., Catalano, R. F., Chappell, P. J., Hawkins, J.D. (1996). Communities that care: A comprehensive prevention program. Seattle, WA: Developmental Research and Programs, Inc.

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