The Brief Addiction Science Information Source (BASIS)

Addiction & the Humanities Vol. 3(8) - Examining racial and ethnic substance use differences following exposure to disaster.

Disasters, such as recent hurricanes and floods in North America, earthquakes in Indonesia, the 2004 tsunami in Southeast Asia, and the New York City World Trade Center attack, have killed thousands and exposed thousands more to ongoing trauma.  Survivors probably manage the aftermath of such disasters by utilizing coping methods dependent upon their current situation; specific strategies vary by culture. For example, researchers have found differences in social support and coping among different racial and ethnic groups (Pole et al., 2005; Kim et al., 2007.)  This week, Addictions and the Humanities considers whether people exposed to the World Trade Center attack from different racial, ethnic, and cultural backgrounds experienced different addiction-related health outcomes.

Unfortunately, it is difficult to conduct disaster research for a number of reasons. Disasters vary in many ways: geographic size, mortality rates, elapsed time, and displacement among others. Such differences make studying the effect and generalizability of findings related to disasters and their aftermath challenging.

To study the effect of the World Trade Center attack (WTC attack) on increased cigarette and alcohol use, Wu et al. (2006) drew a stratified random sample of all high school students in New York City and had the students complete a survey about their exposure (direct, family or media) and their cigarette and alcohol use after the WTC attack.  Researchers examined participants’ self-reports that they “started” or “increased” smoking/drinking after the WTC attack.  Analyses revealed that students directly exposed to the attack reported increased alcohol use after the WTC attack, Odds Ratio (OR)  1.8 (95% CI, 1.1-2.8).  Researchers compared African Americans, Asian American and Hispanic American students to their non-Hispanic white counter parts; these minority groups were protected from increased alcohol use after the WTC attack.  The OR for African American students was 0.4 (95% CI, 0.2-0.7), for Asian American students the OR was 0.5 (95% CI, 0.3-0.9), and for Hispanic American students the OR was 0.6 (95% CI, 0.3-0.9) (see Table 1).

There are several limitations to discuss.  The study is not longitudinal; therefore, it is impossible to determine if exposure to the WTC attack precipitated the change in smoking and drinking behavior.  Second, the population studied was high school students in New York City.  Consequently, the results should only be generalized to adolescents involved in disasters where displacement is minimal, as was the case in NY.  Finally, researchers asked only if subjects initiated or increased use of alcohol and cigarettes but not other substances of abuse.  This makes it difficult to determine the degree to which substance use increases after a disaster.

The finding that Asian, Hispanic and African-American students drank alcohol less than non-Hispanic whites is interesting and warrants further study.  This finding contrasts with results from the Youth Risk Behavior Surveillance System, which identified higher alcohol use prevalence rates among Hispanic and non-Hispanic white students compared to African-American students (Eaton et al., 2006).  It is possible that certain cultural values might have lead to protection against alcohol abuse or that certain cultures abuse other substances not measured in response to disasters.  Future studies must use comprehensive measures of substance use, focus more on cultural differences, and follow up with students over a longer period of time.  Researchers also must study whether coping mechanisms manifest differently in various geographical areas and cultures. If more research identifies cultural coping differences, these results should inform public health strategies and interventions.

What do you think?  Comments can be addressed to John Kleschinsky.

References
Eaton, D. K., Kann, L., Kinchen, S., Ross, J., Hawkins, J., Harris, W. A., et al. (2006). Youth risk behavior surveillance--United States, 2005. MMWR Surveillance Summaries, 55(5), 1-108.

Kim, J. H., Knight, B. G., & Longmire, C. V. (2007). The role of familism in stress and coping processes among African American and White dementia caregivers: Effects on mental and physical health. Health Psychology, 26(5), 564-576.

Pole, N., Best, S. R., Metzler, T., & Marmar, C. R. (2005). Why are hispanics at greater risk for PTSD? Cultural Diversity and Ethnic Minority Psychology, 11(2), 144-161.

Wu, P., Duarte, C. S., Mandell, D. J., Fan, B., Liu, X., Fuller, C. J., et al. (2006). Exposure to the World Trade Center attack and the use of cigarettes and alcohol among New York City public high-school students. American Journal of Public Health, 96(5), 804-807.

ASHES Vol. 3(8) - Pregnant and Smoking: Differences from Women who Abstain

Conventional medical care discourages pregnant women from smoking. However, quitting might be more difficult for some than others. For example, people with psychiatric disorders are more likely to smoke tobacco (Breslau, Kilbey, & Andreski, 1993; Gonzalez-Pinto et al., 1998), possibly because of self-medicating features of nicotine (Pomerleau, Marks, & Pomerleau, 2000). This week’s ASHES examines research detailing rates of various psychiatric disorders and certain demographic features of pregnant women who smoke, women who quit smoking because of their pregnancy, and pregnant women who never smoked.

Flick et al. (2006) administered the Diagnostic Interview Schedule, Version IV (DIS; Robinson & Killen, 1997) to 733 of 878 Medicaid–eligible women they approached (response rate = 83.5%) who were enrolled in the Missouri-based Special Supplemental Nutrition Program for Women, Infants, and Children (WIC).  The researchers also collected information about the women’s educational status, income, and parity (i.e., how many children they already delivered). 

Table 1.  Prevalence of selected psychiatric disorders and demographic variables that yield the greatest difference by smoking status (n=733; adapted from Flick et al., 2006)

 

The sample ranged in age from 13 to 43 (SD 22.3); 42% never finished high school, 42% were white, 42% were having their first child, 59% lived in an urban area, and 78% had never married.   Figure 1 shows that persistent smokers and those who quit were both more likely to have a psychiatric disorder than non-smokers; more specifically, persistent smokers were 2.5 times more likely than non-smokers, and those who quit were 2 times more likely than non-smokers.  However, non-smokers and those who quit were more likely than those who continued smoking to have more education and higher incomes.

This study has some limitations. The study utilized a self report methodology, so smoking rates and psychiatric symptoms risk underreporting.  Further, the researchers conducted interviews at a single point during the pregnancy, so they were unable to account for all changes in smoking status participants might have made during pregnancy (e.g., quitters who resumed smoking).

Compared to abstainers, the higher rates of psychiatric comorbidity among the two groups of smokers, persistent and those who quit, suggest that lifetime smoking status among pregnant women is a predictor of mental health. However, mental health among lifetime smokers could not distinguish persistent smokers from those who quit during pregnancy. Rather, better predictors of quitting smoking during pregnancy included education and means. Interventions that target pregnant women smokers should incorporate aspects of mental health and socioeconomic improvements.

* Adjusted annual median income for a family of four = $8,224.

What do you think?  Comments can be addressed to Leslie Bosworth.

References

Breslau, N., Kilbey, M. M., & Andreski, P. (1993). Vulnerability to psychopathology in nicotine-dependent smokers: An epidemiologic study of young adults. American Journal of Psychiatry, 150, 941-946.

Flick, L. H., Cook, C.A., Horman, S.M., McSweeney, M., Campbell, C., Parnell, L. (2006). Persistent Tobacco Use During Pregnancy and the Likelihood of Psychiatric Disorders. American Journal of Public Health, 96(10), 1799-1807.

Gonzalez-Pinto, A., Gutierrez, M., Ezcurra, J., Aizpuru, F., Mosquera, F., Lopez, P., et al. (1998). Tobacco smoking and bi-polar disorder. Journal of Clinical Psychiatry, 59, 225-228.

Pomerleau, C. S., Marks, J. L., & Pomerleau, O. F. (2000). Who gets what symptom? Effects of psychiatric cofactors and nicotine dependence on patterns of smoking withdrawal symptomatology. Nicotine and Tobacco Research, 2(3), 275-280.

Robinson, T. N., & Killen, J. D. (1997). Do cigarette warning labels reduce smoking? Paradoxical effects among adolescents. Archives of Pediatric & Adolescent Medicine, 151(3), 267-272.

The DRAM Vol. 3(8) - Can In Utero Exposure to Alcohol Lead to Alcohol Disorders During Early Adulthood?

Preliminary reports indicate that maternal drinking during mid pregnancy is (1) an independent contributor to the likelihood of alcohol consumption by age 14 and (2) significantly related to the development of alcohol disorders by age 21(Baer, Barr et al. 1998; Baer, Sampson et al. 2003). This DRAM reviews a longitudinal investigation focusing on the associations between maternal drinking during early and late pregnancy and the development of alcohol disorders during early adulthood among offspring.

Alati, Al Mamun, Williams, O’Callaghan, Najman, and Bor (2006) interviewed 7,223 mothers who had their first antenatal visit at Mater Misericordiae Hospital in Brisbane, Australia between 1981 and 1984.  Throughout the next 21 years, the researchers were able to complete five follow-up visits with 2,555 mother and child pairs (35.4%).  At each interview, mothers recounted the quantity of alcohol they consumed during different stages of pregnancy as well as the amount they were consuming at the time of the interview.

Results indicated that 25% of offspring (n=640) met the DSM-IV criteria for a life-time diagnosis of alcohol disorders by age 21:  13% (n=333) reported the disorder before age 18 (early onset), and 12% (n=307) reported the disorder between ages 18 and 21 (late onset) (See Table 1).  Further analysis indicated that mothers who consumed more than two glasses of alcohol during early pregnancy, at an average of 18 weeks gestation, were 2.47 times more likely to have a child with an early onset alcohol disorder and 2.04 times more likely to have a child with a late onset alcohol disorder compared to mothers who drank two or fewer glasses of alcohol during pregnancy.  Overall, the association between maternal drinking during early pregnancy and having a child with an alcohol disorder was stronger for early onset than for late onset.

Table 1.  Univariable Associations Between Maternal Alcohol Use and Onset of Alcohol Disorders at Age 21 Years (Alati, Al Mamun et al. 2006) 

There were several limitations to this study.  When researchers asked participants the quantity of alcohol they consumed, no specific measurement was stated as the standard volume of a single drink.  The researchers assumed that the typical drink was 10 grams but participants could have used widely varying quantities.  It is important to remember that only 35.4% of the initial cohort completed all five phases of the study, which increases the possibility that the final sample might not be representative of the total study population.  Additionally, although the authors examined the effect of maternal alcohol and tobacco use during the follow-up period, there are many other unanalyzed risk and protective factors that could mediate the in utero exposure effect.

This study introduces the possibility that in utero alcohol exposure could be predictive of future alcohol disorders.  However, many of the study features, including the lack of controls for additional influences, limits our ability to interpret these findings.

What do you think? Comments can be addressed to Sara Kaplan.

References

Alati, R., A. Al Mamun, et al. (2006). "In utero alcohol exposure and prediction of alcohol disorders in early adulthood " Arch Gen Psychiatry 63: 1009-1016.

Baer, J. S., H. M. Barr, et al. (1998). "Prenatal alcohol exposure and family history of alcoholism in the etiology of adolescent alcohol problems." Journal of Studies on Alcohol 59: 533-543.

Baer, J. S., P. D. Sampson, et al. (2003). "A 21-year longitudinal analysis of the effects of prenatal alcohol exposure on young adult drinking." Archives of General Psychiatry 60: 377-385.

The WAGER Vol. 12(8) - In the face of adversity: Do protective factors prevent risky behavior?

Researchers have focused much attention on identifying high risk populations and risk factors involved in addictive behaviors such as disordered gambling.  Less attention has been paid to resilience and the role it plays in preventing risky behavior in adolescent populations.  Luthar and Cicchetti (2000) define resilience as a person’s ability to adapt positively (e.g., not exhibit emotional, behavioral, and social problems) in the face of adversity (i.e., negative life events). In this edition of The WAGER we examine research by Lussier, Derevensky, Gupta, Bergevin, & Ellenbogen (2007) that investigated resilience and youth gambling behavior.

Researchers recruited 1,273 participants aged 12 to 19 from 12 schools across Montreal, Quebec, Canada.  Students responded to a 300 item anonymous survey during a 50 minute class period.  The survey included: the Gambling Activities Questionnaire (GAQ; Gupta & Derevensky, 1996) and the Diagnostic and Statistical Manual of Mental Disorders Multiple Response Juvenile (DSM-IV-MR-J; Fisher, 2000)  to ascertain gambling activity, as well as the Individual Protective Factors Index (IFPI; Springer & Phillips, 1992)  to assess protective and risk factors.

Analyses revealed that 7.2% and 3.2 % of the sample were classified as at-risk and probable pathological gamblers (PPGs) respectively.  The researchers used tertile splits of both the protective and risk factors and retained only the extreme highest and extreme lowest scores to form four groups of subjects: vulnerable (high risk-low protective), resilient (high risk-high protective), safe (low risk-low protective), and insulated (low risk-high protective).  Researchers found that among subjects in the vulnerable group, non-gamblers were underrepresented and there were more of the at-risk and PPGs than in the total sample.  In the insulated group, there were more non-gamblers and fewer at-risk and PPGs. (see Table 1).  Further examination revealed that the mean gambling severity score for the resilient group (M=0.3, SD=0.78) was less than a third of that of the vulnerable group (M=1.12 SD 1.74), even though the groups had similar levels of risk.

The results are promising, but the study has a few limitations.  The research design is cross-sectional and does not allow researchers to establish a temporal relationship.  Surveys were anonymous, but often conducted under the supervision of a teacher.  This might lead to underreporting of risk factors and gambling behavior.  Despite these limitations, the finding that the resilient group, although at high risk for developing problems, resembled the low risk groups in its prevalence of disordered gamblers , suggests that this group was indeed protected.  This is important from a public health perspective because it is easier to modify protective factors such as personal competence than it is to remove certain familial or environmental risk factors.  Future prevention efforts should focus more attention on increasing protective factors to prevent addictive behaviors.

What do you think?  Comments can be addressed to John Kleschinsky.

References

Fisher, S. (2000). Developing the DSM-IV criteria to identify adolescent problem gambling in non-clinical populations. Journal of Gambling Studies, 16(253-273).

Gupta, R., & Derevensky, J. L. (1996). The relationship between gambling and video game playing behavior in children and adolescents. Journal of Gambling Behavior, 12, 375-394.

Lussier, I., Derevensky, J. L., Gupta, R., Bergevin, T., & Ellenbogen, S. (2007). Youth gambling behaviors: An examination of the role of resilience. Psychology of Addictive Behaviors, 21(2), 165-173.

Luthar, S. S., & Cicchetti, D. (2000). The construct of resilience: implications for interventions and social policies. Development and Psychopathology, 12(4), 857-885.

Springer, J. F., & Phillips, J. L. (1992). Extended national youth sports program, 1991-1992 evaluation: II. Individual protective factors index (IFPI) and risk assessment study. Folsom, CA: EMT Associates.