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Estimated probability of becoming a case of drug dependence in relation to duration of drug-taking experience: a functional analysis approach.

ABSTRACT: Measured as elapsed time from first use to dependence syndrome onset, the estimated "induction interval" for cocaine is thought to be short relative to the cannabis interval, but little is known about risk of becoming dependent during first months after onset of use. Virtually all published estimates for this facet of drug dependence epidemiology are from life histories elicited years after first use. To improve estimation, we turn to new month-wise data from nationally representative samples of newly incident drug users identified via probability sampling and confidential computer-assisted self-interviews for the United States National Surveys on Drug Use and Health, 2004-2013. Standardized modules assessed first and most recent use, and dependence syndromes, for each drug subtype. A four-parameter Hill function depicts the drug dependence transition for subgroups defined by units of elapsed time from first to most recent use, with an expectation of greater cocaine dependence transitions for cocaine versus cannabis. This study's novel estimates for cocaine users one month after first use show 2-4% with cocaine dependence; 12-17% are dependent when use has persisted. Corresponding cannabis estimates are 0-1% after one month, but 10-23% when use persists. Duration or persistence of cannabis smoking beyond an initial interval of a few months of use seems to be a signal of noteworthy risk for, or co-occurrence of, rapid-onset cannabis dependence, not too distant from cocaine estimates, when we sort newly incident users into subgroups defined by elapsed time from first to most recent use. Copyright © 2016 John Wiley & Sons, Ltd.

SUBMITTER: Vsevolozhskaya OA

PROVIDER: S-EPMC5199633 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Inter-relationships Linking Probability of Becoming a Case of Nicotine Dependence With Frequency of Tobacco Cigarette Smoking.

Project description:IntroductionOnce smoking starts, some tobacco cigarette smokers (TCS) can make very rapid transitions into tobacco dependence syndromes (TCD). With adjustment for smoking frequency, we posit female excess risk for this rapid-onset TCD. In a novel application of functional analysis for tobacco research, we estimate four Hill function parameters and plot TCD risk against a gradient of smoking frequency, as observed quite soon after smoking onset.MethodsIn aggregate, the National Surveys of Drug Use and Health, 2004-2013, identified 1546 newly incident TCS in cross-sectional research, each with standardized TCD assessment.ResultsHill function estimates contradict our apparently over-simplistic hypothesis. Among newly incident TCS males with only 1-3 recent smoking days, an estimated 1%-3% had become rapid-onset TCD cases; non-overlapping confidence intervals show lower TCD risk for females. In contrast, among daily smokers, closer to 50% of female TCS showed rapid-onset TCD, versus under 20% of male TCS, but a larger sample will be needed to confirm the apparent female excess risk at the daily smoking frequency level.ConclusionsSmoking frequency and TCD onset become inter-dependent quite soon after TCS onset. Feedback loops are expected, and might explain a potential reversal of male-female differences across smoking frequency gradients. These novel epidemiological estimates prompt new thinking and questions about interventions.ImplicationsIn this large sample epidemiological study, with a nationally representative sample of newly incident TCS assessed cross-sectionally, we see a quite rapid onset of tobacco dependence, with an early male excess that fades out at higher levels of smoking frequency. Next steps include development of outreach and intervention for this very rapid-onset tobacco dependence.

| S-EPMC5103934 | biostudies-literature

Prevalence of infertility in the United States as estimated by the current duration approach and a traditional constructed approach.

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| S-EPMC3615032 | biostudies-literature

Antisocial Drug Dependence

Project description:Antisocial Drug Dependence

| PRJNA547655 | ENA

Antisocial Drug Dependence

Project description:Antisocial Drug Dependence

| PRJNA547656 | ENA

Risk-taking in disorders of natural and drug rewards: neural correlates and effects of probability, valence, and magnitude.

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| S-EPMC4305336 | biostudies-literature

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| S-EPMC7720515 | biostudies-literature

Power calculations for genetic association studies using estimated probability distributions.

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| S-EPMC379135 | biostudies-other

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| S-EPMC2926803 | biostudies-literature

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Project description:Rising costs of survey data collection and declining response rates have caused researchers to turn to non-probability samples to make descriptive statements about populations. However, unlike probability samples, non-probability samples may produce severely biased descriptive estimates due to selection bias. The paper develops and evaluates a simple model-based index of the potential selection bias in estimates of population proportions due to non-ignorable selection mechanisms. The index depends on an inestimable parameter ranging from 0 to 1 that captures the amount of deviation from selection at random and is thus well suited to a sensitivity analysis. We describe modified maximum likelihood and Bayesian estimation approaches and provide new and easy-to-use R functions for their implementation. We use simulation studies to evaluate the ability of the proposed index to reflect selection bias in non-probability samples and show how the index outperforms a previously proposed index that relies on an underlying normality assumption. We demonstrate the use of the index in practice with real data from the National Survey of Family Growth.

| S-EPMC7724611 | biostudies-literature

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