Eric O. Johnson

Genetic and environmental influences on drug use and abuse/dependence in male and female twins

Twins were recruited through alcohol and drug treatment programs. With structural equation modeling, genetic and environmental estimates were obtained for use and DSM-III abuse/dependence of sedatives, opioids, cocaine, stimulants, and cannabis as well as any illicit drug. Analyses were conducted separately for males and females. Models included thresholds based on population prevalence of use or abuse/dependence and ever having been in treatment. Genetic influences were found for most measures. They were generally stronger for males than females and for clinical diagnoses of abuse/dependence compared to use. Common environmental influences played a greater role in use than abuse/dependence.

Sleep problems and substance use in adolescence

Longitudinal studies of adults have reported finding insomnia to significantly predict onset of substance abuse. This study estimated the association between sleep problems and substance use among adolescents in the context of psychiatric problems. Data come from the US National Household Survey on Drug Abuse 1994-1996 that included 13,831 adolescents. Use of cigarettes, alcohol and any illicit drug were each associated with adolescents reports of having frequent sleep problems, adjusting for age, sex, race and family income (odds ratios ranging from 1.5 to 3.8). Adjusting for internalizing (e.g. depression and anxiety) and externalizing (e.g. deviance and aggression) problems reduced the associations between sleep problems and use of these substances, suggesting that part of the association is attributable to psychiatric problems. The part of the association not attributable to psychiatric problems was limited to the associations between sleep problems and use of illicit drugs. These results suggest that the relationship between sleep problems and drug use/abuse must be viewed in the context of psychiatric problems. Longitudinal research that employs more specific measures of sleep problems is indicated. Such research may provide information on the relationship of sleep problems to the immediate health and well being of adolescents, as well as their trajectories into adulthood.

Trouble sleeping and anxiety/depression in childhood

The purpose of this report was to estimate the association between childrens trouble sleeping and anxiety/depression at ages 6 and 11, cross-sectionally and prospectively. Data come from a study of the psychiatric sequelae of low birth weight (LBW: <2500 g). LBW and normal birth weight children were randomly selected from the 1983-1985 newborn lists of an urban and a suburban hospital. Eight hundred and twenty-three children participated at age 6 and, of those, 717 (87.1%) participated at age 11. Achenbachs Child Behavior Checklist (CBCL) and the Teacher Report Form (TRF) were used to obtain ratings of psychiatric problems. The CBCL asked if the child had trouble sleeping during the past 6 months. Children with trouble sleeping had significantly increased odds of anxiety/depression based on mothers reports (OR=6.9, 95% CI 4.1-11. 4) but not teachers reports (OR=1.1, 95% CI 0.4-2.7). There was a greater association between sleep and depression at age 11 than at age 6, and among suburban than among urban children. These findings remained when adjusted for birthweight, sex, and mothers history of major depressive disorder. Profile analysis indicated a stronger association of trouble sleeping with anxiety/depression than other psychiatric problems. The association of trouble sleeping at age 6 with incidence of depression at age 11 was not statistically significant (suburban children RR=2.22, 95% CI 0.53-9.23; urban children RR=0.92, 95% CI 0.20-4.18).

Increased risk of learning disabilities in low birth weight boys at age 11 years

BACKGROUNDnFew studies have examined learning disabilities among low birth weight (< or =2500 g) children, and those that have, have focused on very low birth weight children (<1500 g). We tested the hypothesis that low birth weight increases the risk of reading and math disabilities, examined possible sex differences in the effect of low birth weight, and assessed risk across the entire range of low birth weight.nnnMETHODSnLow birth weight and normal birth weight children were randomly selected from the 1983-1985 newborn lists of an urban and a suburban hospital in southeast Michigan. Children with neurological impairments were excluded. Children were evaluated at age 6 years and at age 11 years. Of the 823 children in the initial assessment, 717 (87.1%) participated in the second assessment. The Wechsler Intelligence Scale for Children--Revised and the Woodcock-Johnson Psycho-Educational Battery--Revised were used to identify children with learning disabilities. Learning disabilities were estimated in 574 children with IQs of > or =85.nnnRESULTSnLow birth weight was associated with increased risk for reading and math disability in male children (odds ratio = 3.3 and odds ratio = 6.5, respectively) but not in female children. The increased risk of learning disabilities among male children applied to the entire range of low birth weight and was observed in both the urban and suburban communities.nnnCONCLUSIONSnThe effect of low birth weight on learning disabilities appears to be specific to male children. Although this sex-specific effect is consistent with previous findings of a greater vulnerability of male children to pregnancy and birth complications, it remains to be replicated and clarified.

Psychometric evaluation of daytime sleepiness and nocturnal sleep onset scales in a representative community sample

BACKGROUNDnThe public health importance of daytime sleepiness as a risk factor for accidents, interpersonal problems, and decreased productivity has been recognized. However, epidemiologic research on this topic has been limited by the reliance on laboratory measures (i.e., the Multiple Sleep Latency Test-MSLT). Two scales, daytime sleepiness and nocturnal sleep onset, have been identified from the self-report Sleep-Wake Activity Inventory (SWAI) in a clinic sample and validated against the MSLT. This study evaluates the replicability of the two scales in a population sample and assesses potential thresholds in scale scores that distinguish normal from pathologic levels of daytime sleepiness and difficulty falling asleep.nnnMETHODSnThe sample consisted of 2181 subjects 18-45 years old in the Detroit metropolitan area. All sleep characteristic information covered the 2 weeks prior to interview. Split-half sample factor analyses were conducted to assess replicability of the results. Distribution of scale scores and their relation to construct validity variables were used to evaluate possible thresholds.nnnRESULTSnA two-factor model appeared to best account for the variation among the 12 items from the SWAI. The two factors accounted for 50% of the variance in both split-half sample analyses. The revised eight-item daytime sleepiness and two-item nocturnal sleep onset scales showed good and fair internal consistency respectively across both split-half samples. There appeared to be a natural break in daytime sleepiness scale scores that was associated with a substantial and consistent change in number of hours slept. No breaks appeared in nocturnal sleep onset scores.nnnCONCLUSIONSnThis study replicated the results of the clinic-based study and suggested a potentially useful diagnostic threshold for self-report excessive daytime sleepiness. Epidemiology of sleep depends on the ability to move from the laboratory to population surveys in reliable and valid ways. Development of self-report is a step in that direction.

Comorbidity of depression with levels of smoking: An exploration of the shared familial risk hypothesis

Comorbidity of depression and smoking is well recognized, but results from studies that have assessed alternative explanations have varied by the level of smoking and the study method. We examined all 13 etiology models of comorbidity described by Neale and Kendler (American Journal of Genetics, 57, 935-953, 1995) for depression and each of four levels of smoking to shed light on the role that differing definitions might have played in generating the conflicting findings. Data came from 979 young adults aged 26-35 years who participated in an epidemiological cohort study in southeastern Michigan. Respondent and family history data on parental smoking and depression were analyzed using the biometric modeling method for family data, which Rhee and colleagues (Journal of Child Psychology and Psychiatry and Allied Disciplines, 44, 612-636, 2003; Behavior Genetics, 34, 251-265, 2004) have shown to be valid more frequently than traditional prevalence analyses. Results of the biometric model fitting suggested that for ever smoking, the comorbidity with depression may be related to chance or a high liability threshold for smoking only. In contrast, a correlated liabilities model fit the data best for the comorbidity of depression with daily, heavy, and nicotine-dependent smoking. The familial correlations accounted for 73%-95% of the total variance shared between depression and these levels of smoking. These results differ from analyses of these data using a traditional prevalence approach, which found no evidence of shared familial liability. The conflicting findings of the studies that have examined the relationship between smoking and depression may be attributable to differences in definition of the disorders and the methods used to analyze them.