Validity of the DSM-5 craving criterion for alcohol, tobacco, cannabis, cocaine, heroin, and non-prescription use of prescription painkillers (opioids).

BACKGROUND: Although the DSM-5 was adopted in 2013, the validity of the new substance use disorder (SUD) diagnosis and craving criterion has not been investigated systematically across substances. METHODS: Adults (N = 588) who engaged in binge drinking or illicit drug use and endorsed at least one DSM-5 SUD criterion were included. DSM-5 SUD criteria were assessed for alcohol, tobacco, cannabis, cocaine, heroin, and opioids. Craving was considered positive if "wanted to use so badly that could not think of anything else" (severe craving) or "felt a very strong desire or urge to use" (moderate craving) was endorsed. Baseline information on substance-related variables and psychopathology was collected, and electronic daily assessment queried substance use for the following 90 days. For each substance, logistic regression estimated the association between craving and validators, i.e. variables expected to be related to craving/SUD, and whether association with the validators differed for DSM-5 SUD diagnosed with craving as a criterion v. without. RESULTS: Across substances, craving was associated with most baseline validators (p values<0.05); neither moderate nor severe craving consistently showed greater associations. Baseline craving predicted subsequent use [odds ratios (OR): 4.2 (alcohol) - 234.3 (heroin); p's ⩽ 0.0001], with stronger associations for moderate than severe craving (p's < 0.05). Baseline DSM-5 SUD showed stronger associations with subsequent use when diagnosed with craving than without (p's < 0.05). CONCLUSION: The DSM-5 craving criterion as operationalized in this study is valid. Including craving improves the validity of DSM-5 SUD diagnoses, and clinical relevance, since craving may cause impaired control over use and development and maintenance of SUD.

Do DSM-5 substance use disorder criteria differ by user care settings? An item response theory analysis approach.

AIM: To examine differences in the psychometric characteristics of diagnostic criteria for Substance Use Disorders (SUD) between substance users in harm reduction settings (HR) and substance users seeking treatment (Tx). METHODS: Differential Item and Test Functioning (DIF & DTF) analysis were performed to examine differences in the difficulty of endorsement and in discrimination of the 11 diagnostic criteria and to test if the criteria set as a whole (the "test") functioned differently by care settings (Tx vs. HR) for alcohol, cocaine, cannabis, opiates and tobacco. To test uniform and nonuniform DIF, multiple indicator multiple cause (MIMIC) structural equation models were used. RESULTS: Regardless of the substance, the DSM-5 criteria "craving", "large amount", "time spent", "tolerance" and "activities given up" had similar functioning by care settings. Little evidence for DIF was found for other criteria. The criteria set as a whole did not function differently by care settings for alcohol, cocaine and tobacco. At the same trait severity, compared to HR, the Tx subgroup had a greater number of endorsed criteria for cannabis and a smaller number of endorsed criteria for opioids. CONCLUSION: The unidimensionality of the 11 DSM-5 criteria and applicability of all criteria and diagnosis was confirmed in this large sample of problematic substance users. While the majority of the criteria related to loss of control of substance use, functioned well in both care settings, the criteria related to consequences of substance use had several differential functioning.

Validity of proposed DSM-5 diagnostic criteria for nicotine use disorder: results from 734 Israeli lifetime smokers.

BACKGROUND: The fifth edition of the diagnostic and statistical manual of mental disorders (DSM-5) proposes aligning nicotine use disorder (NUD) criteria with those for other substances, by including the current DSM fourth edition (DSM-IV) nicotine dependence (ND) criteria, three abuse criteria (neglect roles, hazardous use, interpersonal problems) and craving. Although NUD criteria indicate one latent trait, evidence is lacking on: (1) validity of each criterion ; (2) validity of the criteria as a set ; (3) comparative validity between DSM-5 NUD and DSM-IV ND criterion sets ; and (4) NUD prevalence. METHOD: Nicotine criteria (DSM-IV ND, abuse and craving) and external validators (e.g., smoking soon after awakening, number of cigarettes per day) were assessed with a structured interview in 734 lifetime smokers from an Israeli household sample. Regression analysis evaluated the association between validators and each criterion. Receiver operating characteristic analysis assessed the association of the validators with the DSM-5 NUD set (number of criteria endorsed) and tested whether DSM-5 or DSM-IV provided the most discriminating criterion set. Changes in prevalence were examined. RESULTS: Each DSM-5 NUD criterion was significantly associated with the validators, with strength of associations similar across the criteria. As a set, DSM-5 criteria were significantly associated with the validators, were significantly more discriminating than DSM-IV ND criteria, and led to increased prevalence of binary NUD (two or more criteria) over ND. CONCLUSIONS: All findings address previous concerns about the DSM-IV nicotine diagnosis and its criteria and support the proposed changes for DSM-5 NUD, which should result in improved diagnosis of nicotine disorders.

Epidemiology and factor analysis of obesity, type II diabetes, hypertension, and dyslipidemia (syndrome X) on the Island of Kosrae, Federated States of Micronesia.

OBJECTIVES: Obesity, type II diabetes, hypertension, and dyslipidemia are major causes of morbidity and mortality throughout the world. Though these disorders often cluster in individuals and families and are collectively known as syndrome X, the basis for this aggregation is not well understood. To further understand the pathogenesis of syndrome X, a comprehensive epidemiological study was undertaken on the Pacific Island of Kosrae, Federated States of Micronesia (FSM). METHODS: The entire adult (>20 years of age) population of Kosrae underwent a clinical evaluation that included a questionnaire that noted the participants' sex, family data including listing of biological parents, siblings, and children, smoking status, village of residence, age and health status. The medical evaluation included: anthropometric measures (weight, height, waist, hip), serum chemistries (leptin, fasting blood sugar (FBS), insulin, total cholesterol (TC), triglycerides (TG), and apolipoproteins B and A-I (apo B and apo A-I) and blood pressure (BP) measurements. RESULTS: Obesity (BMI >/=35) was found in 24%, diabetes (FBS >/=126 or 2-hour oral glucose tolerance test >/=200) in 12%, hypertension (SBP >/=140 or DBP >/=90) in 17%, and dyslipidemia (TC >/=240 or TG >/=200 or apo B >/=120 or apo A-I

Genome scans for Q1 and Q2 on general population replicates using Loki.

The Markov Chain Monte Carlo linkage package Loki was used to perform a genome scan under realistic conditions (using a 10-cM marker map without marker data on unsampled individuals, analyzing each chromosome separately, and without knowing the answers) for traits Q1 and Q2 on general population replicate 1. Using this approach we detected and correctly localized MG1 for Q1 and MG3 for Q2. We then repeated the analyses on replicate 1 and the "best replicate" (42) adding more information (using marker data on everyone, fitting a polygenic effect, and analyzing multiple chromosomes jointly) to see the effect on the detection of trait loci. We found that adding more data often improves the quality of the linkage signal, and reduces the false positive rate, but did not allow the detection of trait loci missed by the initial analysis. We also investigated the convergence of the sampler by repeating one multi-chromosome analysis six times with different random number seeds. We concluded that a strategy of performing a single chromosome scan using a moderate number of sampling iterations, followed by a multi-chromosome analysis of all chromosomes with linkage signals detected in the first scan using a longer sampling run, was an effective way of performing a genome scan on this data set.