Summary
USA
(50 states and the District of Columbia)
The National Epidemiologic Survey on Alcohol and Related Conditions-III (NESARC-III) was sponsored, designed and directed by the National Institute on Alcohol Abuse and Alcoholism (NIAAA). Data were collected from April 2012 through June 2013, and analyzed in October 2014.
The goal of NESARC-III was to gather the data needed to assess alcohol use and associated problems in the general population, identify subgroups of the population at risk for alcohol use disorders and other alcohol-related problems, refine etiologic hypotheses, and form the basis of scientific evidence-based policies and prevention programs.
The NESARC-III is a cross-sectional study based on a nationally representative sample of the civilian non-institutionalized population of the United States aged 18 years and older. Veterans of the United States Armed Forces were included in the sample, but excluded were those on active duty in the U.S. Armed Forces, Military Reserves, and National Guard because they are not offered protection under Certificates of Confidentiality.
Fieldwork was conducted by Westat through a contract. A semi-structured questionnaire, called the NIAAA Alcohol Use Disorder and Associated Disabilities Interview Schedule (AUDADIS-5), was used to collect information. NESARC-III collected information on alcohol and drug use and disorders, related risk factors, and associated physical and mental disabilities. NESARC-III included extensive questions on patterns of alcohol consumption as well as items designed to provide psychiatric classification of alcohol and drug use disorders and mental disorders. In addition, the survey contained a variety of questions on family history of alcoholism, alcohol treatment utilization, medical conditions, and sociodemographic information.
The final sample size was 36,309 and included persons living in households and select non-institutional group quarters. In addition, DNA was obtained through saliva samples, of which 22,848 samples were genotyped.
Prior NIAAA national surveys included the 1988 Alcohol Supplement of the National Household Interview Survey (fielded by the National Center for Health Statistics), the 1991-1992 National Longitudinal Alcohol Epidemiologic Survey, the 2001-2002 Wave 1 NESARC, and the 2004-2005 Wave 2 NESARC.
The 2012–2013 NESARC-III and 2001–2002 Wave 1 NESARC cover similar issues in two time periods separated by about 10 years. Although both NESARC surveys were designed to provide nationally representative prevalence estimates for their respective periods, there were differences in the sampling design, incentive procedure, response rates, sample size, and in the instrument of diagnostic interview.
(NESARC-III is a cross-sectional study based on a nationally representative sample of the adult civilian non-institutionalized population of the United States that included extensive questions on patterns of alcohol consumption as well as items designed to provide psychiatric classification of alcohol and drug use disorders and mental disorders.
Among the NESARC-III respondents, 22,848 individuals also provided samples of their DNA. These DNA samples were genotyped on Affymetrix Axiom Exome Array consisting of 319,283 SNPs and 103,404 custom-selected SNPs Array. After filtering out poor quality SNPs using the standard Affymetrix pipeline there are 295,218 SNPs in the NESARC-III genetic data.)
(Saliva samples)
(Not applicable as data collection on NESARC-III has been completed. Data were collected from April 2012 through June 2013, and analyzed in October 2014.)
Prior NESARC surveys included: 2001-2002 Wave 1 NESARC, and 2004-2005 Wave 2 NESARC
However, data were analyzed in October 2014
The NESARC-III target population is the non-institutionalized, civilian population 18 years or older living in the United States (the 50 states and the District of Columbia), including persons residing in non-institutionalized group quarters such as college dormitories, group homes, group quarters, and dormitories for workers.
NESARC-III was developed for the B.R.I.D.G.E. TO DATA site on November 10, 2022; however, since it is a closed database, this profile will no longer be updated unless there is a significant change.
Population Dynamics
(N=36,309)
(N=36,309)
(Not applicable as NESARC-III is a closed database.)
Multistage probability sampling was used to randomly select respondents. Primary sampling units (PSU) were individual counties or groups of contiguous counties, secondary sampling units (SSU) comprised groups of census-defined blocks, and tertiary sampling units were households within SSUs. Finally, eligible adults within sampled households were randomly selected. Hispanics, Blacks, and Asians were oversampled and resulted in a total of 36,309 respondents. All respondents provided informed consent for survey participation. Data were adjusted for oversampling and screener- and person-level nonresponse, then weighted through post-stratification to represent the US civilian population based on the 2012 American Community Survey. These weighting adjustments were found to compensate adequately for nonresponse. Interviewer field methods involved initial structured home study, in-person training, ongoing supervision, and random respondent callbacks to verify data.
Demographic Data
< 18 years = 0%
≥ 65 years = 17.6%
Males = 48.1%
Females = 51.9%
Data were collected on race and country of heritage / ancestry.
NESARC-III oversampled Hispanics, non-Hispanic Blacks, and non-Hispanic Asians by means of oversampling geographic areas with high concentrations of these minority populations and giving minorities within sampled households greater probabilities of selection than nonminorities. Out of the 36,309 respondents who completed the survey, this sampling strategy resulted in:
- 7,037 Hispanics,
- 7,766 non-Hispanic Blacks,
- 1,801 non-Hispanic Asians or Pacific Islanders,
- 19,194 non-Hispanic Whites, and
- 511 non-Hispanic American Indians/Alaska Natives
Questionnaire included questions on Census region, Urbanicity, Country of birth (and for parents and grandparents), Country of heritage / ancestry, Number of years in the US
Census region:
18.2% Northeast
21.5% Midwest
37.1% South
23.2% West
Urbanicity:
78.8% Urban
21.3% Rural
Only age data were collected
Age of death of parent (or stepparent) was collected
Sociodemographic data included:
- Marital status / Number of marriages
- Current situation
- Education
- Service dates
- Industry / Occupation / Employer
- Income information / WIC benefits program
- Type of healthcare insurance
- Activities
- Religion
- Relatives / Partners / Children
- Orientation
- Raised in institution
- Child of divorce
Physician & Practioner Info
(Not applicable)
(Not applicable)
(Not applicable)
Diagnoses/Signs & Symptoms
AUDADIS-5 was designed to measure DSM-5 criteria for alcohol use disorders, drug use disorders, tobacco use disorder, and selected mood, anxiety, trauma-related, eating, and personality disorders. Side effects from substance abuse were also captured (e.g., nausea, vomiting, restlessness, weakness).
Questions about medical conditions in the past 12 months included:
- Cirrhosis of the liver or any other form of liver disease
- Hardening of the arteries or Arteriosclerosis
- Diabetes or sugar diabetes
- High blood pressure, Hypertension, High cholesterol, or High triglycerides
- Chest pain or Angina
- Rapid heart beat or Tachycardia
- Heart attack, Myocardial infarction, or any other form of heart condition or heart disease
- Stomach ulcer
- Any sexually transmitted diseases or venereal diseases like Gonorrhea, Syphilis, Chlamydia or Herpes
- Epilepsy or seizure disorder
- Arthritis
- Stroke
- Problems falling asleep or staying asleep
- Liver cancer, Breast cancer, Cancer of the mouth, tongue, throat or esophagus, or Any other cancer
- Anemia
- Fibromyalgia, Reflex sympathetic dystrophy (RSD) or Complex Regional Pain Syndrome (CRPS), or any other nerve problem in your legs, arms or back
- Bowel problems, like inflammatory bowel disease (IBD) or irritable bowel syndrome (IBS)
- Osteoporosis
- Lung problems like Chronic bronchitis, Emphysema, Pneumonia, Influenza, or Tuberculosis
- Pancreatitis
- Serious or traumatic brain injury
Other general questions included:
- Did a doctor or other health professional tell you that you had (Name of condition)?
- In the last 12 months, did a doctor or other health professional tell you that you had schizophrenia or a psychotic illness or episode?
- Have you EVER been tested for HIV, the virus that causes AIDS, or tested for AIDS?
- Did you EVER test positive for HIV or AIDS?
- In your ENTIRE life did you EVER attempt suicide?
- How old were you the MOST RECENT time that happened?
(- Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) Version
- NIAAA Alcohol Use Disorder and Associated Disabilities Interview Schedule (AUDADIS-5), a fully structured diagnostic interview instrument (questionnaire) designed for experienced lay interviewers.)
However, data were analyzed in October 2014
(Not applicable since NESARC-III used a semi-structured questionnaire)
(Not applicable)
Questions on cancers in NESARC-III included:
- Liver cancer
- Breast cancer
- Cancer of the mouth, tongue, throat or esophagus
- Any other cancer
Information is recorded on the following infections in the past 12 months:
- Any sexually transmitted diseases or venereal diseases like Gonorrhea, Syphilis, Chlamydia or Herpes
- Pneumonia
- Influenza
- Tuberculosis
- Answers to question - Have you EVER been tested for HIV, the virus that causes AIDS, or tested for AIDS?
- Answers to question - Did you EVER test positive for HIV or AIDS?
Behaviors recorded include those related to:
- Alcohol consumption (size, amount, frequency),
- Alcohol abuse / dependence
- Tobacco use,
- Illicit / medicinal drugs use,
- Occupational patterns,
- Sleep patterns,
- Mood and anxiety behaviors
- Eating disorders
- Personality disorders
- Trauma-related behaviors
- Family and social interactions, and
- Suicide ideation / attempts
- High-risk behaviors (driving under the influence, gambling, money spending, sexual behaviors, etc.)
Procedures
However, there are questions pertaining to treatment utilization in the form of counseling, rehabilitation, social services, community agency / Alcoholics Anonymous, detoxification programs, etc.
(Not applicable)
(Not applicable)
(Not applicable)
(Not applicable)
Drug Information
Illicit drugs and medicinal drugs (and specific alcohol exposure questions) only in regards to use outside the bounds of prescription and drug use disorder are recorded.
Drug use disorders for the following were included:
- sedative
- tranquilizer
- cannabis
- amphetamine
- non-prescription stimulants
- cocaine
- club drug
- opioid or heroin
- hallucinogen
- solvent or inhalant
NOTE: Data are for drug use within the last 12 months at time of questionnaire, prior to the last 12 months, or during both time periods.
Some questions specify whether the drug was injected, inhaled, smoked, snorted, sniffed, drunk, breathed, etc. There are also a series of questions on the frequency, e.g., every day, 2-3 times a month, once in the last year, etc.
However, the manufacturer is only known in some cases, e.g., when medications like Tylenol, Advil are mentioned
Dosage is known for alcohol consumption; however, for medicinal drugs, the unit of consumption is based on the type of drug (e.g., number of marijuana joints, grams/lines/ricks for crack cocaine)
(Not applicable)
(For drug measures relating to drug use disorder - data were obtained as a DSM-5 diagnosis codes)
(Not applicable)
Information is available on drugs taken while drinking alcohol, as well as drugs taken for relief from symptoms due to overconsumption of alcohol
Drug use data include: Ever used, age at first use, prior to last 12 months, frequency, number of days since last use, duration of use, amount, amount until desired effect, and side effects (nausea, vomiting, weakness, depression, restlessness, etc.)
Biobanks
Genetic-PGx Data
As of May 2021, the genetic data collected from individuals who participated in NESARC-III became available. DNA was obtained through saliva samples. Among the 36,309 persons living in households and select non-institutional group quarters, 22,848 samples were genotyped.
NESARC-III is a nationally representative Epidemiologic Survey of the U.S. general population, and it consists of rich phenotypic variables (n=4,320). The combination of genotypic data and phenotypic data about substance use and mental health makes NESARC-III unique, as does the survey’s use of diagnostic criteria from the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5).
Public users can access NESARC-III raw genetic data via the dbGaP database. No second analytic data are supported (such as allele frequency, etc.). Exploration of the new genetic dataset with its rich phenotypic and family background variables could yield important insight into the relationships between genes and observable behaviors, including alcohol use disorders, substance use disorders, depression, post-traumatic stress disorder and other conditions, all diagnosed using criteria from the DSM-5.
The NESARC-III genetic dataset is a critical resource for helping scientists to better understand these disorders and develop new diagnostic methods and treatments.
[NESARC-III is a cross-sectional study with a questionnaire for phenotypic data and saliva collection for subsequent DNA isolation and genotyping. The 22,848 subjects in this study were all deeply and consistently phenotyped via structured diagnostic interview. Controls group can be selected for specific disorders from a pool of all samples. Here are numbers of cases for major DSM-5 mental disorders in NESARC-III genetic data: Alcohol use disorder (7,075); Nicotine use disorder (6,641); Drug use disorder (2,570); Major depressive disorder (5,214); Persistent depression(1,429); Bipolar I (543); Anxiety disorders (4,226); PTSD (1,674); Personality disorders (4,014); Eating Disorders (457).]
(Saliva)
(Every lab process is tracked by a printed barcode label with unique numbers. Every sample received and all subsequent samples resulting from its processing are labeled with a unique 2-D barcode that is electronically linked to the unique number for each subject. Additionally, every sample will be directly linked to QA/QC results and release/distribution status in a real-time manner. Magnetic bead technology for extracting saliva samples for the NESARC-III DNA repository was used. The protocol requires a high-throughput, automated, large volume extraction approach for Oragene™ saliva kit samples. This method maximizes DNA yield, enriches for human gDNA and results in an RNA-free, high molecular weight DNA.)
Data are available on gene associations with drugs of abuse are available
Data are available on gene association with alcohol use disorders, substance use disorders, depression, post-traumatic stress disorder and other conditions
As part of the NESARC-III, 22,848 informative samples were genotyped on Affymetrix Axiom Exome Array consisting of 319,283 SNPs and 103,404 custom-selected SNPs Array (refer to the SNP annotation file). The latter array was selected based on the addiction associated genes, the results of 5 GWAS of alcohol and other psychiatric disorders, and animal models with addiction phenotypes. After filtering out poor quality SNPs using the standard Affymetrix pipeline there are 295,218 SNPs in the NESARC-III genetic data.
Axiom® Biobank Genotyping Arrays were designed by and for thought leaders in the human genetics community for high-throughput, high-value genotyping of large sample cohorts to explore the genetics of complex diseases and translational research with a single comprehensive low-cost solution. The arrays feature markers in a number of different categories, outlined below:
-GWAS: Intelligent marker selection enables imputation of millions of additional SNPs.
-Transplant: Content specific for transplantation research including functional variants, loss-of-function markers, and copy number and markers for immune function, including MHC, HLA, and KIR
-Pharmacogenomic markers: Markers were selected to represent phases of absorption, distribution, metabolism, and excretion (ADME)
-Inflammation and HLA: Contains markers with evidence for association with autoimmune and inflammation, covering variants in genes in the HLA and KIR regions known to be important in immune response
-Exome: Rare, non-synonymous coding SNPs and indels in protein coding regions of the genome, mostly comprised of rare variants with a minor allele frequency (MAF) <1%. LOF content, as well as SNPs and InDels from a sequencing initiative of 26K individuals and known disease-causing mutations are included.
-eQTLs: Markers that have known associations to RNA expression traits, capturing unique eQTLs contained in the NCBI Genotype-Tissue Expression (GTEx) eQTL database, GEUVIDAS project, and several other discovery projects
-Human disease: Alzheimer's disease, including coverage of ApoE, blood phenotypes, common cancer variants and cardiometabolic markers are included.
Approximately 103,404 custom-selected SNPs were genotyped. The custom contents of the array were selected from 1) the Addiction-associated genes from Hodgkinson et al. (Alcohol Alcoholism, 2008; 43:505-515), 2) addiction-related phenotypes and alcohol homologs from model organism genes; such as C. elegans (roundworm), drosophila (fruit fly), primates (rhesus monkeys), 3) other study such as Anxiety/PTSD, and 4) top hits from human alcohol GWAS. Five GWA studies were selected to contribute to the human GWAS custom content: (1) the Collaborative Study of Genetics on Alcoholism (COGA); (2) Finish Twin Studies (FT12); (3) Avon Longitudinal Study of Parents and Children (ALSPAC); (4) the Irish Affected Sib Pair Study of Alcohol Dependence (IASPAD); and (5) a meta-analysis of 9 alcohol-dependence studies. Overall, of the 103,404 custom-selected SNPs included, 62,994 were from the non-human homologs, the rest of them were from the human GWAS projects and the Addictions Array.
Step 1 call rates utilized a set of excellent performing QC markers that were determined by Affymetrix. Samples that had a Step 1 call rate > 97% were deemed passing, and were further processed to generate Step 2 call rates.
Step 2 call rates were determined after clustering of all SNPs within the batch, and genotypes were called. Data was clustered with all samples from the study in a single batch. Data, including DishQC, Step 1 call rates, and step 2 call rates, was determined for every sample. Samples that failed Axiom data QC (below the threshold of either DishQC or Step 1 call rates) were genotyped again on Axiom arrays. Samples that failed Axiom genotyping twice were considered as terminal failures and PLINK reports were generated for passing samples.
SNP QC was performed after genotyping using SNPolisher (Nicolazzi et al., Bioinformatics Advance Access, July 15, 2014). This tool calculated SNP QC metrics and classifies SNPs into categories. One SNPolisher function (Ps_Mertrics) produced data that contained SNP clustering metrics resulting from inherent cluster properties on a per-marker basis. These metrics divided SNPS into one of 7 classes: “PolyHighResolution”, “MonoHighResolution”, and “NoMinorHom”, “OffTargetVariant”, “CallRateBelowThreshold”, “Hemizygous”, and “Other”. For human Axiom array designs, Affymetrix recommended using probesets with call rates >95%, creating the list of best probesets. The Ps.Classification file identified the best probeset for each SNP marker, and summarizes them in the Ps.Performance.txt file. Both unfiltered and filtered (for SNPs that pass SNPolisher) PLINK reports have been generated for further data analysis.
After filtering out poor quality SNPs using the standard Affymetrix pipeline there are 295,218 SNPs in the NESARC-III genetic data.
Allele frequencies are not provided, but research can estimate the proportion of people with specific genetic variation/sequence at a particular locus using the raw data.
No second analytic data are supported (such as allele frequency, etc.).
Genotype data are available for both cases and healthy controls.
NESARC-III data are now accessible through the National Library of Medicine’s online database of Genotypes and Phenotypes, known as dbGaP, which archives and distributes data from studies that explore the relationships between genetic variations (genotypes) and observable traits (phenotypes). NESARC-III genetic data are also accessible through the Psychiatric Genomic Consortium (PGC) system.
Qualified users can access NESARC-III raw genetic data via the dbGaP database at: https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001590.v2.p1 using the instructions for "Authorized Access" and adhering to the "Data Use Certification Agreement".
Qualified researchers include:
- Senior Investigators (tenure-track professor or senior scientist);
- NIH Investigators (tenure-track investigators, senior investigators, senior scientists, senior clinicians, or staff scientists); or
- NIH extramural scientist with administrative responsibility for the data, have substantial research involvement for the requested data; or need access to carry out unrelated research).
However, the genetic data are linked to the phenotypic data from NESARC-III
(Not applicable)
Economic Data
(Not applicable)
(Not applicable)
(Not applicable)
Validation & Linkage
Phenotype data: Subsamples of respondents who completed the NESARC-III were systematically re-interviewed using a shorter version of AUDADIS-5 and the Psychiatric Research Interview for Substance and Mental Disorders, DSM-5 version (PRISM-5) to assess reliability and procedural validity, respectively (Grant et al., 2015b; Hasin et al., 2015b).
Genetic data: Analytical QC metrics were routinely used in the biobanking community as the sole indicator of DNA sample quality. In order to ensure that NESARC-III saliva DNA samples perform appropriately and also confirm sample identity prior to expensive downstream analyses, the protocol employed an integrated QA and QC program to qualify every DNA. This process was a two-pronged approach, utilizing our Analytical and Functional QC programs. Analytical quality control for the NESARC-III program consists of concentration and purity measurements (Trinean DropSense) optimized for human gDNA, and ultrasound-based, non-contact volume measurements (BioMicroLab VolumeCheck), as described in more detail below. Once a sample passes analytical QC, a comprehensive functional QC program was applied to rapidly determine sample suitability for downstream analysis as well as uniqueness, contamination, gender and ethnicity. Functional analysis was accomplished via the targeted profiling of 96 SNPs using a rapid and sensitive automated platform routinely employed. The evaluated SNPs were the RUID™ panel for DNA QC. The RUID™ panel has been designed to assure three major goals: (i) sample quality (SNPs are located in genomic regions predisposed to specific nuclease and/or non-specific degradation to asses DNA fidelity); (ii) sample uniqueness (the 96 SNP profile only repeats in 2x1024 individuals); (iii) gender determination (there are SNPs dedicated to the Y chromosome to determine gender status).
NESARC-III data are also available from the dbGaP database [and the Psychiatric Genomic Consortium (PGC)]. These external databases include both the genetic and phenotypic NESARC-III data; however, these two phenotypic data have different human sample IDs from the NESARC-III pehynotypic data at NIAAA to protect the privacy of human subjects further. Further, the full NESARC-III pehnotypic data is 36,309 while the genotypic data along with their phenotypic data in dbGaP (and PCG) consist of information for 22,848 samples (i.e., number of samples that were genptyped). In other words, if researchers can access the NESARC-III dbGaP data, they do not need to apply for the NIAAA phenotypic dataset.
Administrative Information
NESARC-III Data Access Committee
Email: NIAAA-DAC@mail.nih.gov
Epidemiology and Biometry Branch
National Institute on Alcohol Abuse and Alcoholism
National Institutes of Health
6700B Rockledge Drive
Bethesda, MD 20892
USA
E-mail: NIAAA-NESARC-III@mail.nih.gov
N/A
(Not applicable)
Data are available under appropriate terms and conditions, in a timely manner to qualified investigators.
Limited access data sets are available for the phenotypic NIAAA-conducted NESARC-III. Data sets distributed under this policy include only “limited access data”, i.e., records with personal identifiers and other variables that might enable individual participants to be identified, such as birth date, removed or otherwise modified. Because it may still be possible to combine the limited access data with other publicly available data and thereby potentially identify individual participants, these data sets are not truly anonymous. They are, therefore, only provided to investigators who agree in advance to adhere to established policies for distribution.
Qualified researchers around the world can now access the NESARC-III genetic dataset and related phenotypic data in dbGaP at: https://www.ncbi.nlm.nih.gov/projects/gap/cgi-bin/study.cgi?study_id=phs001590.v2.p1 using the instructions for "Authorized Access" and adhering to the "Data Use Certification Agreement". Qualified researchers include:
- Senior Investigators (tenure-track professor or senior scientist);
- NIH Investigators (tenure-track investigators, senior investigators, senior scientists, senior clinicians, or staff scientists); or
- NIH extramural scientist with administrative responsibility for the data, have substantial research involvement for the requested data; or need access to carry out unrelated research).
[NESARC-III phenotype data at NIAAA: SAS or STATA data file
Genomic NESARC-III data at dbGaP: genetic data (PLINK data files); phenotypic data (text files and Excel files)]
1: Patel TA, Schubert FT, Hom MA, Cougle JR. Correlates of treatment seeking in individuals with social anxiety disorder: Findings from a nationally representative sample. J Anxiety Disord. 2022 Oct;91:102616.
2: Carter SP, Campbell SB, Wee JY, Law KC, Lehavot K, Simpson T, Reger MA. Suicide Attempts Among Racial and Ethnic Groups in a Nationally Representative Sample. J Racial Ethn Health Disparities. 2022 Oct;9(5):1783-1793.
3: Stevens AK, Gunn RL, Sokolovsky AW, Colby SM, Jackson KM. Examining the heterogeneity of polysubstance use patterns in young adulthood by age and college attendance. Exp Clin Psychopharmacol. 2022 Oct;30(5):701-713.
4: Thornburg B, Bray JW, Wittenberg E. Health Utility of Drinkers' Family Members: A Secondary Analysis of a US Population Data Set. MDM Policy Pract. 2022 Sep 27;7(2):23814683221128507.
5: Elliott M, Ragsdale JM. Stress exposure and well-being: correlates of meeting criteria for bipolar disorder, borderline personality disorder, or both. Soc Psychiatry Psychiatr Epidemiol. 2022 Sep;57(9):1885-1896.
6: Nakic M, Stefanovics EA, Rhee TG, Rosenheck RA. Lifetime risk and correlates of incarceration in a nationally representative sample of U.S. adults with non- substance-related mental illness. Soc Psychiatry Psychiatr Epidemiol. 2022 Sep;57(9):1839-1847.
7: Bommersbach TJ, Rosenheck RA, Petrakis IL, Rhee TG. Why are women more likely to attempt suicide than men? Analysis of lifetime suicide attempts among US adults in a nationally representative sample. J Affect Disord. 2022 Aug 15;311:157-164.
8. Zhang H, Grant BF, Hodgkinson CA, Ruan W, Kerridge BT, Huang B, Saha TD, Fan AZ, Wilson V, Jung J, Parsian A. Strong and weak cross-inheritance of substance use disorders in a nationally representative sample. Molecular Psychiatry. 2022 Mar;27(3):1742-53.
9. Grant BF, Goldstein RB, Saha TD, Chou SP, Jung J, Zhang H, Pickering RP, Ruan WJ, Smith SM, Huang B, Hasin DS. Epidemiology of DSM-5 Alcohol Use Disorder: Results From the National Epidemiologic Survey on Alcohol and Related Conditions III. JAMA Psychiatry. 2015 Aug;72(8):757-66.
10. Grant BF, Goldstein RB, Chou SP, et al. The Alcohol Use Disorder and Associated Disabilities Interview Schedule–Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition Version (AUDADIS-5). Rockville, MD: National Institute on Alcohol Abuse and Alcoholism; 2011.
Database Contact
NESARC-III Data Access Committee
Email: NIAAA-DAC@mail.nih.gov
Epidemiology and Biometry Branch
National Institute on Alcohol Abuse and Alcoholism
National Institutes of Health
6700B Rockledge Drive
Bethesda, MD 20892
USA
E-mail: NIAAA-NESARC-III@mail.nih.gov
Literature References
1: Patel TA, Schubert FT, Hom MA, Cougle JR. Correlates of treatment seeking in individuals with social anxiety disorder: Findings from a nationally representative sample. J Anxiety Disord. 2022 Oct;91:102616.
2: Carter SP, Campbell SB, Wee JY, Law KC, Lehavot K, Simpson T, Reger MA. Suicide Attempts Among Racial and Ethnic Groups in a Nationally Representative Sample. J Racial Ethn Health Disparities. 2022 Oct;9(5):1783-1793.
3: Stevens AK, Gunn RL, Sokolovsky AW, Colby SM, Jackson KM. Examining the heterogeneity of polysubstance use patterns in young adulthood by age and college attendance. Exp Clin Psychopharmacol. 2022 Oct;30(5):701-713.
4: Thornburg B, Bray JW, Wittenberg E. Health Utility of Drinkers' Family Members: A Secondary Analysis of a US Population Data Set. MDM Policy Pract. 2022 Sep 27;7(2):23814683221128507.
5: Elliott M, Ragsdale JM. Stress exposure and well-being: correlates of meeting criteria for bipolar disorder, borderline personality disorder, or both. Soc Psychiatry Psychiatr Epidemiol. 2022 Sep;57(9):1885-1896.
6: Nakic M, Stefanovics EA, Rhee TG, Rosenheck RA. Lifetime risk and correlates of incarceration in a nationally representative sample of U.S. adults with non- substance-related mental illness. Soc Psychiatry Psychiatr Epidemiol. 2022 Sep;57(9):1839-1847.
7: Bommersbach TJ, Rosenheck RA, Petrakis IL, Rhee TG. Why are women more likely to attempt suicide than men? Analysis of lifetime suicide attempts among US adults in a nationally representative sample. J Affect Disord. 2022 Aug 15;311:157-164.
8. Zhang H, Grant BF, Hodgkinson CA, Ruan W, Kerridge BT, Huang B, Saha TD, Fan AZ, Wilson V, Jung J, Parsian A. Strong and weak cross-inheritance of substance use disorders in a nationally representative sample. Molecular Psychiatry. 2022 Mar;27(3):1742-53.
9. Grant BF, Goldstein RB, Saha TD, Chou SP, Jung J, Zhang H, Pickering RP, Ruan WJ, Smith SM, Huang B, Hasin DS. Epidemiology of DSM-5 Alcohol Use Disorder: Results From the National Epidemiologic Survey on Alcohol and Related Conditions III. JAMA Psychiatry. 2015 Aug;72(8):757-66.
10. Grant BF, Goldstein RB, Chou SP, et al. The Alcohol Use Disorder and Associated Disabilities Interview Schedule–Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition Version (AUDADIS-5). Rockville, MD: National Institute on Alcohol Abuse and Alcoholism; 2011.