The DOI matches its Crossref record; 23 of the 23 references it cites were found in a registry or an index.
Age trends in rates of substance use disorders across ages 18–90: Differences by gender and race/ethnicity
Open accessAbstract
Background Although research has documented age differences in substance use, less is known about how prevalence of substance use disorders (SUDs) vary across age and differ by gender and race/ethnicity.Methods Time-varying effect models (TVEMs) were estimated on data from the National Epidemiologic Survey of Alcohol and Related Conditions-III (NESARC III; N=36,309), a nationally representative survey of the adult population. The sample was 44% male; 53% White, 21% Black, 19% Hispanic/Latino, 6% other race/ethnicity. Prevalence of four SUDs (alcohol, tobacco, cannabis and opioid use disorders) were flexibly estimated across ages 18-90 by gender and race/ethnicity.Results Estimated SUD prevalences were generally higher for men compared to women at most ages until the 70s. However, disparities by race/ethnicity varied with age, such that for most SUDs, estimated prevalences were higher for White participants at younger ages and Black participants at older ages.Discussion Results suggest relatively constant disparities by gender across age, and a crossover effect for Black and White participants. Findings demonstrate that Black individuals in midlife may be an important target of intervention programs for some substances.
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“The prevalence of SUDs is high and varies across countries and the type of drugs used (highest for tobacco and alcohol use disor ders) as well as by demographic and socioeconomic character istics of the populations.”
From Substance use disorders: a comprehensive update of classification, epidemiology, neurobiology, clinical aspects, treatment and prevention (2023) · cites this paper as [1]
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“The rates of SUDs are higher for males than females and higher for younger people, with rates decreas ing as both men and women age 1 .”
From Substance use disorders: a comprehensive update of classification, epidemiology, neurobiology, clinical aspects, treatment and prevention (2023) · cites this paper as [1]
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Diagnostic and Statistical Manual of Mental Disorders
Williams, J. B. W., & First, M. B. (2013) · Oxford University Press eBooks · doi:10.1093/acrefore/9780199975839.013.104 · Cited by 109,845
Diagnostic and Statistical Manual of Mental Disorders
(2012) · Springer eBooks · doi:10.1007/springerreference_121117 · Cited by 20,772
Extent of illicit drug use and dependence, and their contribution to the global burden of disease
Degenhardt, L. J., & Hall, W. (2012) · The Lancet · doi:10.1016/s0140-6736(11)61138-0 · Cited by 1,354
Prevalence of marijuana use disorders in the United States between 2001-2002 and 2012-2013.
Hasin, D. S., Saha, T. D., Kerridge, B. T., Goldstein, R. B., Chou, S. P., Zhang, H., Jung, J., Pickering, R. P., Ruan, W. J., Smith, S. M., et al. (2015) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2015.1858 · Cited by 1,086
Grant, B. F., Saha, T. D., Ruan, W. J., Goldstein, R. B., Chou, S. P., Jung, J., Zhang, H., Smith, S. M., Pickering, R. P., Huang, B., et al. (2016) · JAMA Psychiatry · doi:10.1001/jamapsychiatry.2015.2132 · Cited by 877
Johnston, L. D., Miech, R., O'Malley, P., Bachman, J., Schulenberg, J., & Patrick, M. E. (2015) · doi:10.3998/2027.42/150621 · Cited by 850
Textbook, M. (2017) · Cited by 820
Chen, P., & Jacobson, K. C. (2012) · Journal of Adolescent Health · doi:10.1016/j.jadohealth.2011.05.013 · Cited by 663
Possible Contributors to the Gender Differences in Alcohol Use and Problems
Nolen–Hoeksema, S., & Hilt, L. (2006) · The Journal of General Psychology · doi:10.3200/genp.133.4.357-374 · Cited by 366
Grant, B. F., Goldstein, R. B., Smith, S. M., Jung, J., Zhang, H., Chou, S. P., Pickering, R. P., Ruan, W. J., Huang, B., Saha, T. D., et al. (2015) · Drug and Alcohol Dependence · doi:10.1016/j.drugalcdep.2014.11.026 · Cited by 346
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Metadata
- Authors
- Vasilenko, S. A., Evans-Polce, R. J., & Lanza, S. T.
- Affiliations
- Pennsylvania State University (US)
- Corresponding author
- Vasilenko, Sara A.
- Venue
- Drug and Alcohol Dependence
- Publisher
- Elsevier BV
- Published
- 2017-11
- Volume
- 180
- Pages
- 260-264
- ISSN
- 0376-8716 (ISSN-L)
- PMC
- PMC5757874
- OpenAlex
- W2756378480
- Cited by
- 210
- References
- 23
- Citations by year
- 2026: 29 · 2025: 34 · 2024: 41 · 2023: 27 · 2022: 26 · 2021: 20 · 2020: 16 · 2019: 12 · 2018: 4 · 2017: 1
- FWCI
- 7.07
- Type
- journal article
- Language
- en
- Open access
- green
- europepmc.org
- Locations
- Drug and Alcohol Dependence (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institute on Drug AbuseNational Institute on Drug Abuse (NIDA) (R01-DA039854, P50-DA039838, R01 DA037902)
- Topics
- Health Sciences › Medicine › Epidemiology › Substance Abuse Treatment and Outcomes
- Health Sciences › Medicine › Psychiatry and Mental health › Mental Health Treatment and Access
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Opioid Use Disorder Treatment
- Keywords
- substance use disorders, age differences, gender differences, racial and ethnic disparities, alcoholism, tobacco use disorder, cannabis use disorder, opioid use disorder, prevalence, older adults, midlife, NESARC-III
- MeSH terms
- Adult, Aged, Analgesics, Opioid, Cannabis, Ethnicity, Female, Hispanic or Latino, Humans, Male, Prevalence, Substance-Related Disorders, White People, Racial Groups
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