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Addictive diseases and depression comorbidity: Age trajectory and gender comparison
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Abstracts / Drug and Alcohol Dependence 171 (2017) e2–e226
Addictive diseases and depression comorbidity: Age trajectory and gender comparison Eduardo Butelman 1,∗ , Silvia Bacciardi 2 , Angelo G.I. Maremmani 2 , Maya Darst-Campbell 1 , Brenda M. Ray 1 , Elizabeth Ducat 1 , Mary Jeanne Kreek 1 1 Laboratory on the Biology of Addictive Diseases, The Rockefeller University, New York, NY, United States 2 “VP Dole” Dual Diagnosis Unit, Santa Chiara University Hospital of Pisa, Pisa, Italy
Aims: To determine how exposure to specific drugs of abuse (as quantified dimensionally with the KMSK scales) can affect age- and gender-related aspects of psychiatric comorbidity. Methods: This is a case–control study, with two consecutive cohorts. Cohort 1 (n = 617) was ascertained 2002–2005, and Cohort 2 (n = 579) was ascertained 2005-2013. Male and female adults were ascertained with SCID-I/DSM IV criteria, and KMSK scales for heroin, cocaine, alcohol and cannabis. Exposure to each drug was analyzed in three KMSK score “bins” (low, medium and high exposure). The highest KMSK score bin for each drug had the highest relative concurrent validity with the respective DSM IV diagnoses of dependence. Results: (a) Overall, females had a greater proportion of depression diagnoses, versus males. (b) Age of onset of heaviest use, in persons with highest exposure to each of these drugs, did not differ according to depression diagnosis. (c) There were typically increasing proportions of depression diagnoses with increasing exposure to each drug. Overall, both males and females with greatest exposure to each drug had the greatest probability of a depression diagnosis. Conclusions: Age of onset of heaviest exposure to heroin, cocaine, alcohol or cannabis did not differ by depression status. For each of these drugs, increasing exposure was typically associated with greater risk of depression diagnoses. While females were more likely to have depression diagnoses overall, the aforementioned association of exposure and probability of depression was typically observed in both genders. Financial support: NIH-NIDA Grants, and NIH-CTSA funding to the Rockefeller University Hospital (5UL1TR000043). We are grateful to the Dr. Miriam and Sheldon Adelson Medical Research Foundation. The authors thank Dr. Joel Correa da Rosa, Biostatistician (NIH-CTSA at the Rockefeller University Hospital). http://dx.doi.org/10.1016/j.drugalcdep.2016.08.095 Characteristics of pain patients related to risk of aberrant opioid medication behaviors Stephen F. Butler ∗ , Ryan A. Black, Theresa A. Cassidy, Kevin L. Zacharoff, Simon H. Budman Inflexxion, Inc., Newton, MA, United States Aims: Examine characteristics of patients evaluated for pain treatment related to scores on the SOAPP, a screener for risk of aberrant opioid medication behaviors. Methods: Self-report data were collected during the clinic workflow using the Pain Assessment Interview Network – Clinical Assessment System (PainCAS), a comprehensive, electronic assessment for pain-related treatment. At intake and follow-up visits, patients self-report on pain, medical/family history, medications and other treatments, social/emotional functioning, and opioid risk; generating reports for providers and patients. Linear regression examined the range of SOAPP scores against age, gender,
race, body area(s) affected by pain, validated measures of functioning and psychiatric problems, pain-related litigation, and pain ratings at worst, now, least and average. Results: De-identified data are uploaded and analyzed in real time. By October, 2015, 4795 assessments were collected at 18 clinics in 16 states; 73% from unique patients. Follow-up visits ranged from 2 visits to 11, suggesting potential for tracking outcomes. Most patients (60%) were female, white (80%) and 45 to 64 years old (51%). Back/neck pain was reported most (70%), followed by hip/leg pain (46%), shoulder/arm (24%), head (10%) and front torso (8%), with 25% reporting more than one body area. Mean pain rating for past-week-average was 6.2, worst-8.2, and least-4.9 (0–10). Among the unique patients, 75% (n = 2639) received some version of the SOAPP, of which 25% were positive for opioid risk. Regression analysis revealed a significant R2 = .29 (p < .001) demonstrating higher SOAPP scores associated with greater psychiatric problems (standardized beta = .52), giving higher “least-pain” rating (beta = .12), and male gender (beta = −.08). Other predictors dropped out. Conclusions: This exploratory analysis suggests that PainCAS data, collected in real-time from patients who are not participants in formal trials may be useful to further understand clinical presentations associated with higher risk scores for opioid aberrant medication behaviors. Financial support: Inflexxion. http://dx.doi.org/10.1016/j.drugalcdep.2016.08.096 Commuting distance to Miami’s club scene and binge substance use and related problems among young adults Mance E. Buttram 1,∗ , Maria Pagano 2 , Steven P. Kurtz 1 1 Center for Applied Research on Substance Use and Health Disparities, Nova Southeastern University, Miami, FL, United States 2 Department of Psychiatry, Division of Child Psychiatry, Case Western Reserve University, Cleveland, OH, United States
Aims: To examine the association between commuting distance (miles between place of residence and primary club) and binge substance use, sexual risk behaviors, and related problems among young adults in Miami’s club scene. Methods: Data are drawn from baseline assessments in an ongoing behavioral intervention trial (N = 498). Eligible participants were 18–39 and reported recent (past 90 days) and regular use of club drugs (cocaine, ecstasy, LSD, GHB, ketamine, or methamphetamine) and prescription drug misuse. Hierarchal linear regressions examined the impact of commuting distance on risk behaviors, controlling for demographics and social network substance use. Results: Participants were Hispanic (N = 320), Black (N = 104), White (N = 60), and other race/ethnicity (N = 14). Mean age was 25 and nearly half of the sample was female (N = 222). A majority of participants (62%) traveled ≥10 miles to their primary club. As the commuting distance increases participants more frequently reported substance dependence (p < .05), binge alcohol (p < .01), binge cocaine (p < .05) and condomless vaginal sex (p < .001). As commuting distance decreases, participants more frequently reported histories of arrest (p < .05). Conclusions: The results demonstrate that participants living further from their primary club more frequently report binge substance use and related risks than participants living nearer. Greater commuting distance suggests intermittent, rather than regular
Abstracts / Drug and Alcohol Dependence 171 (2017) e2–e226
Addictive diseases and depression comorbidity: Age trajectory and gender comparison Eduardo Butelman 1,∗ , Silvia Bacciardi 2 , Angelo G.I. Maremmani 2 , Maya Darst-Campbell 1 , Brenda M. Ray 1 , Elizabeth Ducat 1 , Mary Jeanne Kreek 1 1 Laboratory on the Biology of Addictive Diseases, The Rockefeller University, New York, NY, United States 2 “VP Dole” Dual Diagnosis Unit, Santa Chiara University Hospital of Pisa, Pisa, Italy
Aims: To determine how exposure to specific drugs of abuse (as quantified dimensionally with the KMSK scales) can affect age- and gender-related aspects of psychiatric comorbidity. Methods: This is a case–control study, with two consecutive cohorts. Cohort 1 (n = 617) was ascertained 2002–2005, and Cohort 2 (n = 579) was ascertained 2005-2013. Male and female adults were ascertained with SCID-I/DSM IV criteria, and KMSK scales for heroin, cocaine, alcohol and cannabis. Exposure to each drug was analyzed in three KMSK score “bins” (low, medium and high exposure). The highest KMSK score bin for each drug had the highest relative concurrent validity with the respective DSM IV diagnoses of dependence. Results: (a) Overall, females had a greater proportion of depression diagnoses, versus males. (b) Age of onset of heaviest use, in persons with highest exposure to each of these drugs, did not differ according to depression diagnosis. (c) There were typically increasing proportions of depression diagnoses with increasing exposure to each drug. Overall, both males and females with greatest exposure to each drug had the greatest probability of a depression diagnosis. Conclusions: Age of onset of heaviest exposure to heroin, cocaine, alcohol or cannabis did not differ by depression status. For each of these drugs, increasing exposure was typically associated with greater risk of depression diagnoses. While females were more likely to have depression diagnoses overall, the aforementioned association of exposure and probability of depression was typically observed in both genders. Financial support: NIH-NIDA Grants, and NIH-CTSA funding to the Rockefeller University Hospital (5UL1TR000043). We are grateful to the Dr. Miriam and Sheldon Adelson Medical Research Foundation. The authors thank Dr. Joel Correa da Rosa, Biostatistician (NIH-CTSA at the Rockefeller University Hospital). http://dx.doi.org/10.1016/j.drugalcdep.2016.08.095 Characteristics of pain patients related to risk of aberrant opioid medication behaviors Stephen F. Butler ∗ , Ryan A. Black, Theresa A. Cassidy, Kevin L. Zacharoff, Simon H. Budman Inflexxion, Inc., Newton, MA, United States Aims: Examine characteristics of patients evaluated for pain treatment related to scores on the SOAPP, a screener for risk of aberrant opioid medication behaviors. Methods: Self-report data were collected during the clinic workflow using the Pain Assessment Interview Network – Clinical Assessment System (PainCAS), a comprehensive, electronic assessment for pain-related treatment. At intake and follow-up visits, patients self-report on pain, medical/family history, medications and other treatments, social/emotional functioning, and opioid risk; generating reports for providers and patients. Linear regression examined the range of SOAPP scores against age, gender,
race, body area(s) affected by pain, validated measures of functioning and psychiatric problems, pain-related litigation, and pain ratings at worst, now, least and average. Results: De-identified data are uploaded and analyzed in real time. By October, 2015, 4795 assessments were collected at 18 clinics in 16 states; 73% from unique patients. Follow-up visits ranged from 2 visits to 11, suggesting potential for tracking outcomes. Most patients (60%) were female, white (80%) and 45 to 64 years old (51%). Back/neck pain was reported most (70%), followed by hip/leg pain (46%), shoulder/arm (24%), head (10%) and front torso (8%), with 25% reporting more than one body area. Mean pain rating for past-week-average was 6.2, worst-8.2, and least-4.9 (0–10). Among the unique patients, 75% (n = 2639) received some version of the SOAPP, of which 25% were positive for opioid risk. Regression analysis revealed a significant R2 = .29 (p < .001) demonstrating higher SOAPP scores associated with greater psychiatric problems (standardized beta = .52), giving higher “least-pain” rating (beta = .12), and male gender (beta = −.08). Other predictors dropped out. Conclusions: This exploratory analysis suggests that PainCAS data, collected in real-time from patients who are not participants in formal trials may be useful to further understand clinical presentations associated with higher risk scores for opioid aberrant medication behaviors. Financial support: Inflexxion. http://dx.doi.org/10.1016/j.drugalcdep.2016.08.096 Commuting distance to Miami’s club scene and binge substance use and related problems among young adults Mance E. Buttram 1,∗ , Maria Pagano 2 , Steven P. Kurtz 1 1 Center for Applied Research on Substance Use and Health Disparities, Nova Southeastern University, Miami, FL, United States 2 Department of Psychiatry, Division of Child Psychiatry, Case Western Reserve University, Cleveland, OH, United States
Aims: To examine the association between commuting distance (miles between place of residence and primary club) and binge substance use, sexual risk behaviors, and related problems among young adults in Miami’s club scene. Methods: Data are drawn from baseline assessments in an ongoing behavioral intervention trial (N = 498). Eligible participants were 18–39 and reported recent (past 90 days) and regular use of club drugs (cocaine, ecstasy, LSD, GHB, ketamine, or methamphetamine) and prescription drug misuse. Hierarchal linear regressions examined the impact of commuting distance on risk behaviors, controlling for demographics and social network substance use. Results: Participants were Hispanic (N = 320), Black (N = 104), White (N = 60), and other race/ethnicity (N = 14). Mean age was 25 and nearly half of the sample was female (N = 222). A majority of participants (62%) traveled ≥10 miles to their primary club. As the commuting distance increases participants more frequently reported substance dependence (p < .05), binge alcohol (p < .01), binge cocaine (p < .05) and condomless vaginal sex (p < .001). As commuting distance decreases, participants more frequently reported histories of arrest (p < .05). Conclusions: The results demonstrate that participants living further from their primary club more frequently report binge substance use and related risks than participants living nearer. Greater commuting distance suggests intermittent, rather than regular