Peer Reviewed Journals on Drug Addiction in America
Curr Psychiatry Rep. Author manuscript; available in PMC 2011 Jul 27.
Published in final edited form as:
PMCID: PMC3144502
NIHMSID: NIHMS310277
Substance Corruption in the United States: Findings From Contempo Epidemiologic Studies
Abstruse
Recent enquiry on the epidemiology of substance utilize disorders (SUDs) has provided important insights into these conditions and their impact on public health. In the United States, annual surveys of drug utilize in household and school populations serve every bit one of the primary sources of information almost the distribution of illicit drug use. This research has demonstrated continued shifts in trends in illicit drug utilize in the Us and chosen attention to rising rates of prescription drug misuse and abuse. Findings have likewise continued to highlight the substantial comorbidity of SUDs with other psychiatric disorders and with the ongoing HIV epidemic. Edifice on these foundations, future challenges for inquiry in substance abuse epidemiology will include using novel methodologic approaches to further unravel the complex interrelationships that link private vulnerabilities for SUDs, including genetic factors, with social and environmental gamble factors.
Introduction
Recent progress in the epidemiology of substance use disorders (SUDs) has been substantial and continues to provide important insights into these conditions and their impact on public health. Selected highlights reviewed in this article focus on recent findings and the systematic monitoring of trends in the landscape of drug utilize in the United states, the examination of the substantial comorbidity between SUDs and other psychiatric disorders, and the association of drug use with other high-chance behaviors and the spread of HIV. In addition, this article highlights important new directions in drug abuse epidemiology research, including the increasing integration of new methodologies into epidemiologic studies that promise to provide major advances in understanding the complex nature of drug apply disorders. The future of substance abuse epidemiology depends on the successful application of these integrated approaches to the study of complex human behaviors. These multifactorial models for agreement SUDs build on the foundations of traditional substance abuse research and contemporary trends in epidemiology and increasingly incorporate a wide spectrum of methodologies from molecular genetics and neuroscience to social epidemiology [i,two].
Trends in Substance Utilise
Large-scale population surveys such equally the household-based National Survey on Drug Use and Wellness and the school-based Monitoring the Future (MTF) study have provided rich data on substance use in the United states of america and pointed out ongoing shifts in trends of illicit drug employ [three•,iv•]. Overall illicit drug use reached a peak in the late 1970s, declined during the 1980s, rose again in the 1990s, and has remained relatively stable during the by several years (Fig. 1) [3•,four•]. Despite some variation in the absolute rates found in the major surveys of drug utilise in the United States, these epidemiologic studies indicate that illicit drug use remains very common and typically begins during boyhood. The 2007 National Survey on Drug Use and Health data indicate that about 46.i% of individuals 12 years of age and older in the United States—an estimated 114 million individuals—have tried any illicit drug at least in one case in their lifetime, 40.half-dozen% have used marijuana, and 29.vii% have used other illicit drugs [four•]. Reflecting the emergence of substance use in boyhood, the 2008 MTF establish that nineteen.6% of students have tried an illicit drug by eighth grade, 34.1% by 10th grade, and 47.4% by twelfth course (Fig. i) [3•]. The nearly recent findings from the MTF study also demonstrated that marijuana remains by far the near commonly used illicit drug, with 14.6% of eighth graders, 29.ix% of 10th graders, and 42.6% of twelfth graders reporting having tried information technology [3•]. A nearly universal finding across such studies is that drug use increases from adolescence to immature adulthood, and then gradually declines [3•,4•].
Trends in lifetime and annual illicit drug utilise amidst eighth, 10th, and twelfth graders. A, Per centum who used whatever illicit drug in their lifetime. B, Percentage who used any illicit drug during the previous 12 months. C, Pct who used any illicit drug other than marijuana in their lifetime. D, Percentage who used any illicit drug other than marijuana during the previous 12 months. Note that beginning in 2001, revised sets of questions on other hallucinogen and tranquilizer use were introduced. Thus, data for "whatsoever illicit drug other than marijuana" were affected by these changes. (From Johnston et al. [3•]; with permission.)
Another key finding derived from these ongoing surveys is that the number of individuals who study misuse of prescription drugs has been increasing in contempo years [5]. In particular, the past few years have seen a marked increase in the misuse of prescription opioid medications, such as oxycodone and hydrocodone, along with a substantial increase in problems associated with such use, including fatal and nonfatal opioid overdose [5–7]. In 2008, marijuana remained the almost normally used category of driveling substance among twelfth graders (32.4% past yr prevalence), but prescription drugs emerged as the second most common category (15.4% past year prevalence) [3•]. Much of the attention paid to this epidemic of prescription drug abuse is a result of the increasing recognition of the problem among teens in the U.s.a. [5,8,9]. Other concerning changes in recent years include increases in marijuana employ, especially amid younger blacks and Hispanics, which may be related to an increase in marijuana authority [10]; shifts in the epidemiology of methamphetamine use, with continued rising rates in the rural United states [4•,11,12]; and increased availability of high-purity heroin and a rise in heroin use via smoking and other noninjection routes [thirteen].
Drug Abuse and Dependence
In addition to tracking trends in drug use, several ongoing, large-calibration epidemiologic studies, such as the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC), accept assessed diagnostic categories of drug corruption and dependence as defined in the DSM-4. Contempo findings from the NESARC point that virtually 2.0% of adults living in Us households had a DSM-IV drug apply disorder in the prior 12 months (1.4% abuse, 0.6% dependence), and 10.3% reported a drug use disorder at any signal in their lifetime (7.vii% abuse, two.6% dependence) [14••]. In add-on, drug abuse and dependence were associated with significant disability, including missed work days and repeated hospitalizations [14••]. Drug apply disorders thus correspond a widespread and substantial public wellness problem in the Usa. Of annotation, rates of drug abuse and dependence were significantly greater amidst men than women, a finding consequent with results of several previous epidemiologic surveys [iv•,fourteen••,15,16]. Several other sociodemographic correlates were as well generally associated with greater risk of DSM-IV drug abuse and dependence on a 12-month and lifetime basis, including Native American ethnicity, younger age, having never been married, depression income, and residing in the Westward [fourteen••]. Other correlates were establish to be specific for abuse or dependence or for the specific fourth dimension period examined. For instance, rates of 12-month drug dependence, merely not 12-month drug abuse, were significantly greater amid those with an education level less than a high school degree. These findings highlight the importance of disaggregating drug corruption from drug dependence and lifetime from current disorders. They also showed an especially loftier prevalence of drug use disorders among Native Americans, with 18.4% reporting a drug use disorder at some point in their lifetime (11.half-dozen% abuse, 6.9% dependence) [fourteen••]. These findings are consistent with regional studies among Native Americans [17,xviii] and highlight the acute need of this community to gain access to substance abuse prevention and treatment services. Farther detailed analyses of the NESARC data and other similar data are needed to examine the underlying reasons for these sociodemographic disparities within the context of the multifactorial nature of drug use disorders [xiv••].
Younger age is consistently associated with drug utilise disorders [4•,14••,16]. However, information from the NESARC besides advise increased rates amidst individuals thirty to 44 years of age who grew upwards in the wake of the 1970s US drug epidemic [fourteen••]. These results indicate the potential for continued increases in rates of drug use disorders amidst older cohorts as the current baby boomer generation ages [19,20]. Findings from the NESARC too suggested that onset of drug abuse and drug dependence typically occurred during belatedly boyhood or early on adulthood, with onset later on in life beingness rare [14••]. Thus, adolescence is a particularly vulnerable period for the onset of drug use disorders and an of import target for connected etiologic and prevention research.
Comorbid Psychiatric Disorders
In addition to demonstrating a high prevalence of SUDs, recent epidemiologic research has provided consistent findings demonstrating the substantial comorbidity of SUDs with other psychiatric disorders. Findings from the Epidemiologic Catchment Surface area Survey [21], the National Comorbidity Survey [22], the National Longitudinal Alcohol Epidemiologic Survey [23], and the NESARC [14••,24] all showed that mood, anxiety, and personality disorders are strongly associated with drug apply disorders. Epidemiologic surveys of adults likewise consistently show that anxiety, mood, and hating personality disorders are more strongly associated with drug dependence than drug corruption [25,26]. For example, recent reports from the NESARC institute that the odds ratios between lifetime psychiatric and drug utilize disorders are higher for drug dependence than drug abuse among those with any anxiety disorder (four.nine and 1.7, respectively), mood disorder (seven.1 and 2.iii, respectively), and antisocial personality disorder (16.7 and 5.4, respectively) [27,28]. Findings from the NESARC also document the importance of controlling for other psychiatric disorders when examining associations between drug use disorders and specific psychiatric disorders [fourteen••]. When analyses controlled for the presence of other comorbid psychiatric disorders, the strength of the associations between individual psychiatric disorders and drug use disorders was reduced but by and large remained strong (Tabular array 1). The decreased magnitude of these associations suggests that common causal pathways may underlie drug use disorders and other psychiatric disorders— findings that are consistent with twin and genetic studies [29]. These findings highlight the importance of continued enquiry on both shared and unique adventure factors underlying the comorbidity of psychiatric and drug use disorders.
Table i
Adapted odds ratios for 12-calendar month DSM-4 drug apply disorders and other psychiatric disorders (decision-making for demographic characteristics and comorbid psychiatric disorders) in the NESARC study
| ORs adjusted for demographic characteristics* | ORs adjusted for demographic characteristics and other psychiatric disorders† | |||||
|---|---|---|---|---|---|---|
| | | |||||
| Comorbid disorder | Drug utilize disorder (99% CI) | Drug corruption (99% CI) | Drug dependence (99% CI) | Drug use disorder (99% CI) | Drug abuse (99% CI) | Drug dependence (99% CI) |
| Booze use disorder | ix.0 (6.94–11.70) | 6.4 (4.75–8.65) | xv.0 (8.57–26.59) | five.6 (4.28–7.42) | 4.5 (iii.25–6.25) | seven.0 (iii.89–12.48) |
| Booze abuse | 2.7 (i.98–3.71) | iii.1 (2.18–4.50) | 1.6 (0.88–3.01) | 4.2 (iii.03–5.85) | iv.2 (two.87–6.xiii) | 3.7 (1.79–7.58) |
| Alcohol dependence | nine.7 (7.13–13.10) | 5.7 (3.95–viii.27) | 18.vii (10.83–32.34) | 6.8 (4.86–9.63) | 4.eight (3.11–seven.31) | 9.0 (iv.66–17.16) |
| Nicotine dependence | five.viii (four.41–seven.63) | 4.0 (2.86–5.69) | 11.0 (6.89–17.56) | 3.2 (ii.38–iv.38) | 2.half-dozen (i.76–3.79) | 4.4 (two.63–7.42) |
| Whatever mood disorder | 3.5 (2.66–iv.53) | i.ix (1.34–2.70) | viii.5 (5.27–13.64) | 1.8 (1.33–2.41) | ane.1 (0.73–i.67) | 3.3 (1.92–five.56) |
| Major depressive disorder | ii.2 (ane.56–3.07) | 1.4 (0.88–2.32) | three.8 (ii.18–6.48) | one.4 (0.97–one.96) | 1.0 (0.63–1.69) | ii.ii (1.20–iv.ten) |
| Bipolar I disorder | 5.1 (3.35–7.lxxx) | 2.iv (1.38–iv.21) | 10.3 (5.75–18.62) | 2.3 (i.49–iii.67) | 1.2 (0.61–2.24) | 4.2 (2.14–8.35) |
| Bipolar II disorder | 2.four (i.23–four.49) | 2.1 (1.02–iv.32) | 2.vi (0.92–7.33) | 1.2 (0.58–ii.63) | 1.2 (0.50–2.68) | 1.4 (0.40–four.59) |
| Dysthymia | 4.0 (2.17–vii.20) | ii.1 (0.85–5.25) | 6.9 (iii.28–14.67) | 2.1 (1.15–3.84) | i.v (0.62–3.76) | 2.8 (1.16–half dozen.67) |
| Any feet disorder | 2.7 (2.05–iii.67) | ane.half dozen (1.xv–2.25) | 6.0 (iii.74–nine.55) | one.two (0.88–1.73) | 0.ix (0.62–1.34) | 1.ix (1.07–3.24) |
| Any panic disorder | 3.9 (two.58–v.87) | 1.nine (ane.02–3.62) | 7.8 (iv.31–14.05) | i.5 (0.91–2.39) | 1.0 (0.49–ii.10) | 1.8 (0.85–3.81) |
| Panic with agoraphobia | 5.6 (3.01–ten.34) | three.2 (1.20–8.33) | 9.2 (iii.98–21.24) | 1.7 (0.fourscore–3.57) | 1.four (0.51–4.03) | 1.5 (0.44–four.93) |
| Panic without agoraphobia | three.ane (1.87–5.xiv) | ane.4 (0.62–3.32) | 6.4 (three.21–12.58) | 1.three (0.75–2.28) | 0.8 (0.32–2.13) | ane.8 (0.85–three.94) |
| Social phobia | ii.half-dozen (ane.69–4.15) | one.7 (0.94–3.00) | four.5 (2.53–8.16) | 1.2 (0.71–one.93) | i.1 (0.58–2.04) | i.2 (0.58–ii.48) |
| Specific phobia | 2.iii (1.65–3.21) | 1.6 (1.06–2.47) | 3.8 (two.fourteen–6.73) | 1.0 (0.68–ane.41) | 0.ix (0.58–one.46) | ane.0 (0.53–two.00) |
| Generalized anxiety | iv.v (ii.80–7.09) | ii.0 (0.98–4.00) | 9.v (4.82–18.83) | 1.7 (0.97–two.92) | 1.ane (0.51–2.28) | two.v (i.02–5.88) |
| Any personality disorder | 4.i (3.27–5.15) | 2.6 (one.94–3.49) | 9.6 (6.44–14.43) | 2.2 (1.71–ii.91) | 1.8 (1.26–two.48) | 3.3 (2.00–5.33) |
| Avoidant | 3.4 (2.25–5.12) | 2.0 (1.05–three.69) | vi.0 (3.19–11.34) | 1.3 (0.85–2.05) | one.i (0.56–2.thirty) | 1.3 (0.63–2.lx) |
| Dependent | vii.3 (iii.65–14.54) | 2.4 (0.89–vi.67) | xiv.9 (6.36–34.71) | 2.2 (i.02–4.fourscore) | one.one (0.37–3.xx) | ii.iv (0.75–7.77) |
| Obsessive-compulsive | 2.iii (1.65–3.15) | 1.4 (0.87–ii.17) | four.6 (ii.91–seven.34) | 0.ix (0.57–ane.33) | 0.7 (0.40–1.23) | 1.2 (0.69–2.10) |
| Paranoid | 3.5 (two.49–4.86) | two.0 (1.28–3.00) | half-dozen.7 (four.09–eleven.07) | ane.ane (0.66–one.68) | 0.9 (0.48–one.fifty) | 1.1 (0.59–2.22) |
| Schizoid | iii.4 (2.33–5.03) | ii.i (1.26–3.56) | 5.eight (3.35–10.11) | one.5 (0.88–two.44) | 1.2 (0.66–two.32) | 1.5 (0.74–three.21) |
| Histrionic | 4.5 (2.98–6.77) | 2.5 (1.45–4.21) | 8.4 (4.69–14.92) | i.three (0.79–ii.twenty) | 1.0 (0.58–1.86) | 1.4 (0.63–3.03) |
| Antisocial | 6.4 (4.77–8.56) | 4.3 (ii.84–six.50) | 9.7 (6.29–15.x) | two.9 (2.08–4.12) | 2.5 (ane.57–3.99) | 2.six (1.45–4.53) |
Comorbid HIV Infection
Drug abuse epidemiology research continues to explore the function of substance utilise and SUDs in contributing to the HIV epidemic. Injection drug use continues to be a substantial category of risk for HIV infection, with an estimated 16% of individuals with newly diagnosed HIV infections in the United States in 2006 reporting this every bit a contributing take a chance cistron [30]. In addition to the take chances of HIV infection through sharing injection equipment amid injection drug users, noninjection drug use is associated with increased likelihood to engage in other HIV risk behaviors [31]. For example, drugs such as methamphetamine and related stimulants tin can simultaneously increase libido, lower inhibitions, and cloud judgment, raising the gamble of individuals engaging in unsafe sexual behaviors in which they might not have otherwise engaged [32,33]. In growing recognition of the substantial combined comorbidity of SUDs, HIV, and psychiatric disease, epidemiologic research has focused increasingly on the importance of understanding these conditions as part of a "syndemic" of multiple, linked epidemics that are powerfully influenced by social context [34–36]. This research promises to provide a better understanding of the interrelationships among drug corruption, HIV, other illnesses, and social weather condition such as poverty and structural violence in social club to meliorate explain the disproportionate brunt of these illnesses experienced by some communities [34,37].
Genetic Epidemiology
Family history is one of the most consistently and strongly associated risk factors for drug use disorders. Results from family unit studies testify that drug use disorders tend to cluster inside families [38]; twin and adoption studies propose that much of the familial clustering of drug use disorders can be explained by genetic factors [29]. Several controlled family studies demonstrated that substance corruption or dependence in probands (ie, the index instance in genetically informative designs) is associated with a substantial increase in risk for these disorders amongst get-go-degree developed relatives and offspring [39,40]. Furthermore, risk is conferred generally across the various classes of illicit drugs and within specific drug classes [41]. Genetic epidemiologic studies of drug use disorders have yielded consequent results indicating conspicuously that drug employ disorders have genetic and environmental underpinnings in need of farther explication.
Of notation, genetic factors appear to be more strongly associated with drug use disorders than with drug use in and of itself [29]. This finding suggests that genetic factors may be important for identifying individuals at risk for drug use disorders, whereas the prevention of onset of drug use is much more likely to be based on efforts to change environmental adventure factors. As with many other relatively common diseases, the risk for drug use disorders is believed to emerge from a combination of factors, including multiple possible genes exerting small furnishings, factor–gene interactions, gene–environs interactions, and a host of environmental factors and private riskconferring behaviors [29,41–43]. Considering identifying gene–surroundings interactions is likely to prove key to understanding the etiology of drug use disorders [42,43], advances in this of import area will do good from big, prospective, genetically informed studies fatigued from large, representative populations.
Future Directions
The hereafter of substance abuse epidemiology depends on the successful awarding of integrated approaches to the study of complex man behaviors. Such a goal of studying multifactorial models is consistent with current trends in epidemiology [ii] and builds on the rich history of drug corruption epidemiology by incorporating perspectives from molecular genetics and neuroscience into individual and social epidemiology. By integrating these diverse transdisciplinary approaches, prevention and treatment of drug use and drug use disorders will be enhanced [1]. Novel conceptualizations and measurements of social and cultural contexts within theoretically grounded enquiry are suggested because increased understanding of how genetic, biological, social, and contextual phenomena interact to influence behavior will ameliorate inform prevention and treatment for individuals at gamble for drug utilize and drug utilise disorders [44]. Recent research has begun to focus on the complex interactions among a range of such factors, including norms established by family members and public figures, peer group influences, and social and institutional processes [45,46]. Neighborhood and customs level factors, such as residential instability, community cohesion, or other aspects of local environments, as well probable serve as potential adventure or protective factors for drug use behaviors [47•]. Epidemiologic studies of drug use and drug use disorders increasingly will need to examine the complex interaction of these individual and social environmental factors, including firsthand individual factors and cumulative intergenerational effects [47•].
1 of the key challenges for epidemiology will be harnessing selected measures from a range of disciplines, such as sociology and neurobiology, that tin can be applied to large-scale, population-based studies. Measurement technologies that are already increasingly feasible for apply in epidemiologic studies include neuroimaging, serum samples for metabolic studies [48], and specimens for genetic clan studies. For case, as the technology for obtaining genetic specimens through mouthwashes and cheek swabs improves, applying such techniques in broad, population-based samples becomes more viable in terms of cost and acceptability to study participants [49]. Additional promising new epidemiologic techniques include ecological momentary assessment tools that can capture information from cohorts most at the time of its occurrence through participants' use of novel recording devices (eg, personal digital assistants or cellular phones) [50]. Moving into the study of interactions across domains of risk—private susceptibility, social environment, factor–environment interactions—provides great promise for the next generation of drug abuse epidemiology enquiry.
Conclusions
Epidemiology provides the foundation for understanding drug use, abuse, and dependence past demonstrating the distribution and determinants of these disorders. Through population-based studies, central clues every bit to etiologic adventure factors for these disorders are identified for detailed exploration in more refined epidemiologic and nonepidemiologic studies. As the field of epidemiology moves into an integrative era [1,2,47•], the epidemiology of drug utilise and drug use disorders must remain at the forefront. The goal volition increasingly exist to develop integrated models that amend understanding of the complex interrelationships among social factors, environmental agents, genetic predisposition, and other private factors contributing to the adventure of drug use disorders. Achieving this goal will require continued refinement of existing methods and development of new techniques for agreement the individual and the environment. The cognition obtained from such studies will improve the nation'due south public health by promoting integrated approaches to preventing and treating drug abuse and dependence.
Acknowledgment
The views and opinions expressed in this article are those of the authors and should not exist construed necessarily to represent the views of any of the sponsoring agencies or the Us government.
Footnotes
Disclosure
No potential conflicts of interest relevant to this article were reported.
References and Recommended Reading
Papers of particular interest, published recently, take been highlighted every bit:
• Of importance
•• Of major importance
i. Fishbein D. The importance of neurobiological research to the prevention of psychopathology. Prev Sci. 2000;i:89–106. [PubMed] [Google Scholar]
2. Susser E, Bresnahan Thou. Origins of epidemiology. Ann N Y Acad Sci. 2001;954:6–xviii. [PubMed] [Google Scholar]
three. Johnston LD, O'Malley PM, Bachman JG, et al. Bethesda, Doc: National Found on Drug Abuse; 2009. Monitoring the Future: National Survey Results on Drug Use, 1975–2008. [Google Scholar] . This is an splendid source of epidemiologic data on drug apply among a school-based cohort.
iv. Substance Abuse and Mental Health Services Administration. Results From the 2007 National Survey on Drug Use and Wellness: National Findings. Rockville, MD: United states Section of Health and Human Services; 2008. [Google Scholar] . This is an excellent source of epidemiologic data on drug apply among a household-based cohort.
five. Compton WM, Volkow ND. Major increases in opioid analgesic abuse: concerns and strategies. Drug Alcohol Depend. 2006;81:103–107. [PubMed] [Google Scholar]
vi. Ballesteros MF, Budnitz DS, Sanford CP, et al. Increase in deaths due to methadone in North Carolina. JAMA. 2003;290:40. [PubMed] [Google Scholar]
vii. Hall AJ, Logan JE, Toblin RL, et al. Patterns of abuse among unintentional pharmaceutical overdose fatalities. JAMA. 2008;300:2613–2620. [PubMed] [Google Scholar]
8. Boyd CJ, McCabe SE, Cranford JA, et al. Adolescents' motivations to abuse prescription medications. Pediatrics. 2006;118:2472–2480. [PMC free article] [PubMed] [Google Scholar]
9. McCabe SE, Boyd CJ, Immature A. Medical and nonmedical use of prescription drugs amongst secondary schoolhouse students. J Adolesc Health. 2007;40:76–83. [PMC free article] [PubMed] [Google Scholar]
10. Compton WM, Grant BF, Colliver JD, et al. Prevalence of marijuana use disorders in the United States: 1991–1992 and 2001–2002. JAMA. 2004;291:2114–2121. [PubMed] [Google Scholar]
11. Thomas YF, Compton WM. Rural populations are not protected from drug use and abuse. J Rural Health. 2007;23:1–3. [PubMed] [Google Scholar]
12. Gfroerer JC, Larson SL, Colliver JD. Drug apply patterns and trends in rural communities. J Rural Health. 2007;23:10–15. [PubMed] [Google Scholar]
13. Community Epidemiology Work Group. Epidemiological Trends in Drug Abuse. Washington, DC: National Plant on Drug Abuse; 2004. [Google Scholar]
xiv. Compton WM, Thomas YF, Stinson FS, et al. Prevalence, correlates, disability, and comorbidity of DSM-IV drug abuse and dependence in the Us: results from the National Epidemiologic Survey on Alcohol and Related Conditions. Curvation Gen Psychiatry. 2007;64:566–576. [PubMed] [Google Scholar] . These were detailed analyses of drug corruption and dependence prevalence, correlates, and comorbidity with other Axis I and Ii disorders.
15. Grant BF. Prevalence and correlates of drug utilize and DSM-4 drug dependence in the The states: results of the National Longitudinal Booze Epidemiologic Survey. J Subst Abuse. 1996;8:195–210. [PubMed] [Google Scholar]
16. Teesson M, Baillie A, Lynskey M, et al. Substance use, dependence and treatment seeking in the United States and Commonwealth of australia: a cross-national comparison. Drug Alcohol Depend. 2006;81:149–155. [PubMed] [Google Scholar]
17. Beals J, Novins DK, Whitesell NR, et al. Prevalence of mental disorders and utilization of mental wellness services in two American Indian reservation populations: mental health disparities in a national context. Am J Psychiatry. 2005;162:1723–1732. [PubMed] [Google Scholar]
eighteen. Gilder DA, Wall TL, Ehlers CL. Comorbidity of select feet and affective disorders with alcohol dependence in southwest California Indians. Alcohol Clin Exp Res. 2004;28:1805–1813. [PubMed] [Google Scholar]
19. Gfroerer J, Penne 1000, Pemberton M, et al. Substance abuse treatment demand among older adults in 2020: the bear upon of the aging babe-nail cohort. Drug Alcohol Depend. 2003;69:127–135. [PubMed] [Google Scholar]
20. Colliver JD, Compton WM, Gfroerer JC, et al. Projecting drug utilize amidst aging infant boomers in 2020. Ann Epidemiol. 2006;16:257–265. [PubMed] [Google Scholar]
21. Regier DA, Farmer ME, Rae DS, et al. Comorbidity of mental disorders with booze and other drug corruption: results from the Epidemiologic Catchment Surface area (ECA) written report. JAMA. 1990;264:2511–2518. [PubMed] [Google Scholar]
22. Warner LA, Kessler RC, Hughes G, et al. Prevalence and correlates of drug use and dependence in the Usa. Results from the National Comorbidity Survey. Arch Gen Psychiatry. 1995;52:219–229. [PubMed] [Google Scholar]
23. Grant BF. Comorbidity between DSM-4 drug utilize disorders and major depression: results of a national survey of adults. J Subst Abuse. 1995;7:481–497. [PubMed] [Google Scholar]
24. Grant BF, Stinson FS, Dawson DA, et al. Prevalence and co-occurrence of substance utilize disorders and independent mood and feet disorders: results from the National Epidemiologic Survey on Alcohol and Related Conditions. Arch Gen Psychiatry. 2004;61:807–816. [PubMed] [Google Scholar]
25. Merikangas KR, Mehta RL, Molnar BE, et al. Comorbidity of substance use disorders with mood and feet disorders: results of the International Consortium in Psychiatric Epidemiology. Addict Behav. 1998;23:893–907. [PubMed] [Google Scholar]
26. Swendsen JD, Merikangas KR. The comorbidity of depression and substance use disorders. Clin Psychol Rev. 2000;20:173–189. [PubMed] [Google Scholar]
27. Conway KP, Compton W, Stinson FS, et al. Lifetime comorbidity of DSM-Four mood and feet disorders and specific drug utilize disorders: results from the National Epidemiologic Survey on Alcohol and Related Conditions. J Clin Psychiatry. 2006;67:247–257. [PubMed] [Google Scholar]
28. Compton WM, Conway KP, Stinson FS, et al. Prevalence, correlates, and comorbidity of DSM-Iv hating personality syndromes and alcohol and specific drug employ disorders in the U.s.: results from the National Epidemiologic Survey on Alcohol and Related Atmospheric condition. J Clin Psychiatry. 2005;66:677–685. [PubMed] [Google Scholar]
29. Kendler KS, Prescott CA, Myers J, et al. The construction of genetic and environmental risk factors for common psychiatric and substance use disorders in men and women. Arch Gen Psychiatry. 2003;60:929–937. [PubMed] [Google Scholar]
31. Woody GE, Donnell D, Seage GR, et al. Non-injection substance use correlates with risky sex among men having sexual activity with men: information from HIVNET. Drug Alcohol Depend. 1999;53:197–205. [PubMed] [Google Scholar]
32. Mansergh G, Purcell DW, Stall R, et al. CDC consultation on methamphetamine apply and sexual risk behavior for HIV/STD infection: summary and suggestions. Public Health Rep. 2006;121:127–132. [PMC free article] [PubMed] [Google Scholar]
33. Krawczyk CS, Molitor F, Ruiz J, et al. Methamphetamine utilise and HIV risk behaviors among heterosexual men—preliminary results from five northern California counties, December 2001–Nov 2003. MMWR Morb Mortal Wkly Rep. 2006;55:273–277. [PubMed] [Google Scholar]
34. Walkup J, Blank MB, Gonzalez JS, et al. The affect of mental wellness and substance abuse factors on HIV prevention and treatment. J Acquir Immune Defic Syndr. 2008;47 Suppl 1:S15–S19. [PubMed] [Google Scholar]
35. Des Jarlais DC, Semaan Southward. HIV prevention for injecting drug users: the outset 25 years and counting. Psychosom Med. 2008;70:606–611. [PubMed] [Google Scholar]
36. Mustanski B, Garofalo R, Herrick A, et al. Psychosocial health problems increase gamble for HIV among urban young men who take sexual activity with men: preliminary show of a syndemic in demand of attention. Ann Behav Med. 2007;34:37–45. [PMC free commodity] [PubMed] [Google Scholar]
37. Friedman SR, Tempalski B, Cooper H, et al. Metropolitan expanse characteristics, injection drug use and HIV among injectors. In: Thomas YF, Richardson D, Cheung I, editors. Geography and Drug Addiction. Washington, DC: Springer; 2008. pp. 255–265. [Google Scholar]
38. Bierut LJ, Dinwiddie SH, Begleiter H, et al. Familial manual of substance dependence: booze, marijuana, cocaine, and habitual smoking: a report from the Collaborative Study on the Genetics of Alcoholism. Arch Gen Psychiatry. 1998;55:982–988. [PubMed] [Google Scholar]
39. Chassin L, Pitts SC, Prost J. Binge drinking trajectories from boyhood to emerging adulthood in a high-hazard sample: predictors and substance abuse outcomes. J Consult Clin Psychol. 2002;lxx:67–78. [PubMed] [Google Scholar]
40. Moss HB, Lynch KG, Hardie TL, et al. Family unit functioning and peer amalgamation in children of fathers with antisocial personality disorder and substance dependence: associations with problem behaviors. Am J Psychiatry. 2002;159:607–614. [PubMed] [Google Scholar]
41. Compton WM, Cottler LB, Ridenour T, et al. The specificity of family history of alcohol and drug abuse in cocaine abusers. Am J Aficionado. 2002;11:85–94. [PubMed] [Google Scholar]
42. Caspi A, McClay J, Moffitt TE, et al. Office of genotype in the cycle of violence in maltreated children. Science. 2002;297:851–854. [PubMed] [Google Scholar]
43. Foley DL, Eaves LJ, Wormley B, et al. Childhood arduousness, monoamine oxidase a genotype, and risk for conduct disorder. Arch Gen Psychiatry. 2004;61:738–744. [PubMed] [Google Scholar]
44. Galea S, Nandi A, Vlahov D. The social epidemiology of substance apply. Epidemiol Rev. 2004;26:36–52. [PubMed] [Google Scholar]
45. Burton LM, Jarrett RL. In the mix, withal on the margins: the place of families in urban neighborhood and child development research. J Marriage Fam. 2000;62:444–465. [Google Scholar]
46. Sampson RJ, Morenoff JD, Gannon-Rowley T. Assessing "neighborhood effects:" social processes and new directions in research. Ann Rev Sociol. 2002;28:443–478. [Google Scholar]
47. Galea S, Hall C, Kaplan GA. Social epidemiology and complex system dynamic modelling as practical to health behavior and drug use research. Int J Drug Policy. 2009;twenty:209–216. [PMC costless commodity] [PubMed] [Google Scholar] . This article discusses approaches to circuitous system dynamic modeling in drug corruption epidemiology.
48. Immature EA, Breslau N. Cortisol and catecholamines in posttraumatic stress disorder: an epidemiologic community study. Arch Gen Psychiatry. 2004;61:394–401. [PubMed] [Google Scholar]
49. Cozier YC, Palmer JR, Rosenberg 50. Comparison of methods for collection of DNA samples past postal service in the Blackness Women's Health Report. Ann Epidemiol. 2004;fourteen:117–122. [PubMed] [Google Scholar]
fifty. Shiffman S, Stone AA, Hufford MR. Ecological momentary assessment. Annu Rev Clin Psychol. 2008;4:1–32. [PubMed] [Google Scholar]
Source: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3144502/
0 Response to "Peer Reviewed Journals on Drug Addiction in America"
Postar um comentário