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Aims: To estimate obesity prevalence among drug-dependent individuals and to compare prevalence across different types of drug dependence.Methods: 1596 opioid- and/or stimulant-dependent participants were extracted from six clinical trials within the National Drug Abuse Treatment Clinical Trials Network of the National Institute on Drug Abuse (NIDA CTN) to estimate obesity prevalence among drug-dependent users. Age-, sex-, and race-matched National Health and Nutrition Examination Survey (NHANES) samples were used as a general population reference. Standardized prevalence ratios (SPRs) were calculated to compare the CTN sample to NHANES as well as to compare within the CTN sample. Logistic regression estimated associations between the type of drug dependence and obesity.Results: The standardized obesity prevalence among the drug-dependent CTN trial participants was 67% of expected for age-, sex- and race-matched NIHANES participants (SPR = 0.67, 95% CI: 0.60-0.74). Obesity was least prevalent among opioid-dependent-only participants (SPR = 0.36, 95% CI: 0.27-0.46 compared to the NHANES, and SPR = 0.33, 95% CI: 0.23-0.46 compared to the stimulant-dependent-only participants). Compared to stimulant-dependent-only users (p < 0.0001), the odds of obesity were 67% lower among opioid-dependent-only users (adjusted odds ratio [AOR] = 0.33, 95% CI: 0.23-0.46) and 33% lower among opioid and stimulant-co-dependent users (AOR = 0.67, 95%CI: 0.49-0.90) after controlling for age, sex, race, education and employment pattern.Conclusions: The prevalence of obesity among drug-dependent clinical trial participants was lower than the general population, and lowest among opioid-dependent-only users, suggesting an inverse relationship between obesity prevalence and drug dependence, most notable among opioid-dependent-only users. [ABSTRACT FROM AUTHOR]

Aim: To investigate associations between substance dependence and obesity., Methods: Obesity (body mass index ≥ 30 kg/m 2 ) status and the status of dependence on heroin, stimulant, marijuana, nicotine and alcohol (past-month status for nicotine and past-year status for all others) were identified from the U.S. National Survey on Drug Use and Health (NSDUH, 2015-2017) datasets. SAS Surveylogistic regression was used to estimate adjusted odds ratio (AOR) for the association between each substance dependence and obesity, adjusting for potentially confounding effects of sociodemographic factors and health condition., Results: It was estimated that 10.6 % of noninstitutional U.S. residents aged 12 years or older were nicotine-dependent, 3.0 % alcohol-dependent, 1.0 % marijuana-dependent, 0.6 % stimulant-dependent, and 0.2 % heroin-dependent. Heroin-dependent individuals had 59 % lower odds of obesity relative to their non-dependent counterparts (AOR = 0.41; 95 % CI: 0.28-0.60; p < 0.0001). Lower odds of obesity were also noted for marijuana-dependent (AOR = 0.64; 95 % CI: 0.56-0.73; p < 0.0001), nicotine-dependent (AOR = 0.68; 95 % CI: 0.64-0.72; p < 0.0001) and alcohol-dependent (AOR = 0.77, 95 % CI: 0.69-0.84; p < 0.0001) individuals, but not statistically significant for stimulant-dependent individuals (AOR = 0.84; 95 % CI: 0.68-1.02; p = 0.0825)., Conclusions: Heroin, marijuana, nicotine and alcohol dependence were associated with lower odds of obesity than their non-dependence counterparts. Main findings based on 2015-2017 NSDUH are consistent with findings from our prior report based on clinical trials data from National Institute on Drug Abuse Clinical Trials Network, and other epidemiological evidence in the literature. These findings can alert substance abuse treatment professionals to monitor weight change, especially among weight-concerned substance abusers., (Copyright © 2020 Elsevier B.V. All rights reserved.)

Background: There are many benefits of data sharing, including the promotion of new research from effective use of existing data, replication of findings through re-analysis of pooled data files, meta-analysis using individual patient data, and reinforcement of open scientific inquiry. A randomized controlled trial is considered as the 'gold standard' for establishing treatment effectiveness, but clinical trial research is very costly, and sharing data is an opportunity to expand the investment of the clinical trial beyond its original goals at minimal costs., Purpose: We describe the goals, developments, and usage of the Data Share website (http://www.ctndatashare.org) for the National Drug Abuse Treatment Clinical Trials Network (CTN) in the United States, including lessons learned, limitations, and major revisions, and considerations for future directions to improve data sharing., Methods: Data management and programming procedures were conducted to produce uniform and Health Insurance Portability and Accountability Act (HIPAA)-compliant de-identified research data files from the completed trials of the CTN for archiving, managing, and sharing on the Data Share website., Results: Since its inception in 2006 and through October 2012, nearly 1700 downloads from 27 clinical trials have been accessed from the Data Share website, with the use increasing over the years. Individuals from 31 countries have downloaded data from the website, and there have been at least 13 publications derived from analyzing data through the public Data Share website., Limitations: Minimal control over data requests and usage has resulted in little information and lack of control regarding how the data from the website are used. Lack of uniformity in data elements collected across CTN trials has limited cross-study analyses., Conclusions: The Data Share website offers researchers easy access to de-identified data files with the goal to promote additional research and identify new findings from completed CTN studies. To maximize the utility of the website, ongoing collaborative efforts are needed to standardize the core measures used for data collection in the CTN studies with the goal to increase their comparability and to facilitate the ability to pool data files for cross-study analyses.