Data on drug overdose death rates, by drug type and selected population characteristics. Please refer to the PDF or Excel version of this table in the HUS 2019 Data Finder (https://www.cdc.gov/nchs/hus/contents2019.htm) for critical information about measures, definitions, and changes over time. SOURCE: NCHS, National Vital Statistics System, numerator data from annual public-use Mortality Files; denominator data from U.S. Census Bureau national population estimates; and Murphy SL, Xu JQ, Kochanek KD, Arias E, Tejada-Vera B. Deaths: Final data for 2018. National Vital Statistics Reports; vol 69 no 13. Hyattsville, MD: National Center for Health Statistics.2021. Available from: https://www.cdc.gov/nchs/products/nvsr.htm. For more information on the National Vital Statistics System, see the corresponding Appendix entry at https://www.cdc.gov/nchs/data/hus/hus19-appendix-508.pdf.

This short report uses data from the 2010 and 2011 National Surveys on Drug Use and Health (NSDUHs), the 2010 Treatment Episode Data Set (TEDS), the 2010 National Survey of Substance Abuse Treatment Services (N-SSATS), and the 2011 Drug Abuse Warning Network (DAWN) to present facts about adolescent substance use, including information on the initiation of substance use, past year substance use, emergency department visits, and receipt of substance use treatment.

Additional File 3. Provides data to support the results pertaining to the percentage change analyses reported in the main text of the manuscript

Rank, number of deaths, percentage of deaths, and age-specific mortality rates for the leading causes of death, by age group and sex, 2000 to most recent year.

Opioid overdose deaths, deaths from other causes, and people alive at end of study follow-up period (2008–2015), MDAC Study.

Abstract (en): The Drug Use Among Young Indians: Epidemiology and Prediction study is an annual surveillance effort assessing the levels and patterns of substance use among American Indian (AI) adolescents attending schools on or near reservations. In addition to annual epidemiology of substance use, data pertaining to the normative environment for adolescent substance use were also obtained. For this data collection data comes from annual in-school surveys completed between the years 1993 to 2006, and 2009 to 2013. Students completed the surveys at school during a specified class period. The dataset contains 534 variables for 26,451 students in grades 7 to 12. This study was part of an ongoing surveillance of the levels and patterns of substance abuse among American Indian (AI) adolescents who attended schools on or near AI reservations. The purpose was to accurately describe the epidemiology of substance use, observe changes over time, and to assess trends. In addition to substance use epidemiology, a secondary purpose was to investigate the etiology of substance use. Various risk factors associated with adolescent substance use are included in the survey. Almost every variable falls into one of four response types: Yes / No; Marked / Not marked; Four or five point categorical scales; Categorized numbers to show frequency; Some of the major topics covered by the survey include: Attitudes and experiences of substance use; Attitudes and experiences of school; Interaction and influences of friends and family; Delinquency; Victimization; Perceptions of self; Activities; Cultural activity and tradition; No weight variable exists in the dataset. ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection: Standardized missing values.; Created online analysis version with question text.; Checked for undocumented or out-of-range codes.. Presence of Common Scales: American Drug and Alcohol Survey; Prevention Planning Survey; Response Rates: Response rates are not available from the Principal Investigator for the years of 1993 to 2000. For the remaining years they are as follows: 2001-2002: 65 percent; 2002-2003: 76 percent; 2003-2004: 80 percent; 2004-2005: 65 percent; 2005-2006: 83 percent; 2009-2010: 76 percent; 2010-2011: 83 percent; 2011-2012: 76 percent; 2012-2013: 79 percent; The overall response rate for the study was about 76 percent. Students in grades 7 through 12 attending schools on or near American Indian reservations with at least 20 percent American Indian students. Smallest Geographic Unit: Randomized, de-identified community codes Each year of the funding period a survey was completed by a sample of students in the 7th to 12th grades. The sampling frame consisted of schools with at least 20 percent American Indian (AI) students on or near American Indian reservations, stratified by region. The sampling scheme was based on geographic regions in which reservation-based AI's reside. It was a modified version of the geographic regions described by Snipp (2005). A more complete description, along with a table describing the Principal Investigator's modification of Snipp's regions, is included in the PDF codebook. 2015-06-18 An additional 9,861 cases were added to the dataset from data collected between 1993 and 2000. An additional five variables were also added to the file (A848A, PPS44A, PPS44B, PPS44C, and PPS44D).2015-01-07 ICPSR added variables RACE and HISPANIC to the dataset 35062-0001 in order to facilitate online analysis using Quick Tables.2014-08-05 Added Randall Swaim to the Principal Investigator's list. Funding insitution(s): United States Department of Health and Human Services. National Institutes of Health. National Institute on Drug Abuse (R01 DA003371). on-site questionnaire Three distinct time periods of data collection occurred for this data collection: 1993 to 2000; 2001 to 2006; 2009 to 2013; The variable WAVE was created by ICPSR to distinguish these three periods. The data were collected primarily under two separate questionnaires - the American Drug and Alcohol Survey (ADAS) and the Prevention Planning Survey (PPS). The first two data collection periods utilized multiple vers...

Objective: A one third reduction of premature deaths from non-communicable diseases by 2030 is a target of the United Nations Sustainable Development Goal for Health. Unlike in other developed nations, premature mortality in the United States (US) is increasing. The state of Oklahoma suffers some of the greatest rates in the US of both all-cause mortality and overdose deaths. Medicaid opioids are associated with overdose death at the patient level, but the impact of this exposure on population all-cause mortality is unknown. The objective of this study was to look for an association between Medicaid spending, as proxy measure for Medicaid opioid exposure, and all-cause mortality rates in the 45–54-year-old American Indian/Alaska Native (AI/AN45-54) and non-Hispanic white (NHW45-54) populations.Methods: All-cause mortality rates were collected from the US Centers for Disease Control & Prevention Wonder Detailed Mortality database. Annual per capita (APC) Medicaid spending, and APC Medicare opioid claims, smoking, obesity, and poverty data were also collected from existing databases. County-level multiple linear regression (MLR) analyses were performed. American Indian mortality misclassification at death is known to be common, and sparse populations are present in certain counties; therefore, the two populations were examined as a combined population (AI/NHW45-54), with results being compared to NHW45-54 alone.Results: State-level simple linear regressions of AI/NHW45-54 mortality and APC Medicaid spending show strong, linear correlations: females, coefficient 0.168, (R2 0.956; P < 0.0001; CI95 0.15, 0.19); and males, coefficient 0.139 (R2 0.746; P < 0.0001; CI95 0.10, 0.18). County-level regression models reveal that AI/NHW45-54 mortality is strongly associated with APC Medicaid spending, adjusting for Medicare opioid claims, smoking, obesity, and poverty. In females: [R2 0.545; (F)P < 0.0001; Medicaid spending coefficient 0.137; P < 0.004; 95% CI 0.05, 0.23]. In males: [R2 0.719; (F)P < 0.0001; Medicaid spending coefficient 0.330; P < 0.001; 95% CI 0.21, 0.45].Conclusions: In Oklahoma, per capita Medicaid spending is a very strong risk factor for all-cause mortality in the combined AI/NHW45-54 population, after controlling for Medicare opioid claims, smoking, obesity, and poverty.

BackgroundTramadol is one of the most prescribed painkillers in the world. It is a synthetic opioid that is an excellent alternative to morphine and its derivatives in African countries. It is an essential drug due to its low cost and constant availability. However, the health consequences of tramadol use due to illicit trafficking, like those caused by fentanyl and methadone in North America, are poorly documented. This scoping review aims to understand the nature and extent of the use and health consequences of the Non-Medical Use (NMU) of tramadol in Africa to guide future research.MethodsDue to the perceived lack of African literature on the subject, our search strategy is based on the simultaneous use of the keywords "tramadol" and Medical Subject Heading (MeSH), such as "Drug abuse," "illicit drugs," or "Prescription Drug Misuse," combined with the term "Africa" and Boolean operators (and, or not) to form our search equations. Two researchers will independently select studies from literature searched in several databases such as Medline, Embase, the Scopus database, Web of Science, the African Journals online database, and for grey literature Google Scholar without any time restriction. All research, in various formats, conducted in Africa, will be included in our study on the prevalence of use in different African population groups or on evidence of addiction, intoxication, seizures and mortality related to NMU of tramadol.ResultsThrough this study, we aim to map consumers and identify risk factors, health consequences, and prevalence of the NMU of tramadol in African countries.DiscussionWe are conducting the first scoping review study to investigate the prevalence and consequences of NMU of tramadol in Africa. Upon completion, our findings will be published in a peer-reviewed journal and presented at relevant conferences and workshops. However, since health is not limited to the lack of disease, our study is likely incomplete without incorporating the studies of the social impact of NMU of tramadol.Systematic review registrationOpen Science Framework: https://osf.io/ykt25/.