Evidence map›Paper›PMID 29049278›Full record

ArticleMorbidity and mortality weekly report. Surveillance summaries (Washington, D.C. : 2002)2017

Illicit Drug Use, Illicit Drug Use Disorders, and Drug Overdose Deaths in Metropolitan and Nonmetropolitan Areas - United States.

Karin A Mack, Christopher M Jones, Michael F Ballesteros

Erratum issuedOpen access · hybridAbstract read
In one paragraph

Article in Morbidity and mortality weekly report. Surveillance summaries (Washington, D.C. : 2002), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 100 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
100citing papers in PubMed, 1 pooled it
26.0field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

100 citing papers in PubMed, 1 synthesis or guideline pooled it, 247 citations in OpenAlex.

  1. Pooled it
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  3. Rural Clients' Continuity Into Follow-Up Substance Use Disorder Treatment: Impacts of Travel Time, Incentives, and Alerts.The Journal of rural health : official journal of the American Rural Health Association and the National Rural Health Care Association · 2020
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40 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

  • Erratum issued
    2017
5 · Who and what money

Authors and funding

3 authors at 2 institutions in 1 country.

Karin A MackNational Center for Injury Prevention and Control, CDC.
Christopher M JonesOffice of the Assistant Secretary for Planning and Evaluation, Office of the Secretary, U.S. Department of Health and Human Services.
Michael F BallesterosNational Center for Injury Prevention and Control, CDC.
National Center for Injury Prevention and Control · USOffice of the Assistant Secretary for Planning and Evaluation · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

problem/conditionDrug overdoses are a leading cause of injury death in the United States, resulting in approximately 52,000 deaths in 2015. Understanding differences in illicit drug use, illicit drug use disorders, and overall drug overdose deaths in metropolitan and nonmetropolitan areas is important for informing public health programs, interventions, and policies. REPORTING PERIOD: Illicit drug use and drug use disorders during 2003-2014, and drug overdose deaths during 1999-2015. DESCRIPTION OF DATA: The National Survey of Drug Use and Health (NSDUH) collects information through face-to-face household interviews about the use of illicit drugs, alcohol, and tobacco among the U.S. noninstitutionalized civilian population aged ≥12 years. Respondents include residents of households and noninstitutional group quarters (e.g., shelters, rooming houses, dormitories, migratory workers' camps, and halfway houses) and civilians living on military bases. NSDUH variables include sex, age, race/ethnicity, residence (metropolitan/nonmetropolitan), annual household income, self-reported drug use, and drug use disorders. National Vital Statistics System Mortality (NVSS-M) data for U.S. residents include information from death certificates filed in the 50 states and the District of Columbia. Cases were selected with an underlying cause of death based on the ICD-10 codes for drug overdoses (X40-X44, X60-X64, X85, and Y10-Y14). NVSS-M variables include decedent characteristics (sex, age, and race/ethnicity) and information on intent (unintentional, suicide, homicide, or undetermined), location of death (medical facility, in a home, or other [including nursing homes, hospices, unknown, and other locations]) and county of residence (metropolitan/nonmetropolitan). Metropolitan/nonmetropolitan status is assigned independently in each data system. NSDUH uses a three-category system: Core Based Statistical Area (CBSA) of ≥1 million persons; CBSA of <1 million persons; and not a CBSA, which for simplicity were labeled large metropolitan, small metropolitan, and nonmetropolitan. Deaths from NVSS-M are categorized by the county of residence of the decedent using CDC's National Center for Health Statistics 2013 Urban-Rural Classification Scheme, collapsed into two categories (metropolitan and nonmetropolitan).

resultsAlthough both metropolitan and nonmetropolitan areas experienced significant increases from 2003-2005 to 2012-2014 in self-reported past-month use of illicit drugs, the prevalence was highest for the large metropolitan areas compared with small metropolitan or nonmetropolitan areas throughout the study period. Notably, past-month use of illicit drugs declined over the study period for the youngest respondents (aged 12-17 years). The prevalence of past-year illicit drug use disorders among persons using illicit drugs in the past year varied by metropolitan/nonmetropolitan status and changed over time. Across both metropolitan and nonmetropolitan areas, the prevalence of past-year illicit drug use disorders declined during 2003-2014. In 2015, approximately six times as many drug overdose deaths occurred in metropolitan areas than occurred in nonmetropolitan areas (metropolitan: 45,059; nonmetropolitan: 7,345). Drug overdose death rates (per 100,000 population) for metropolitan areas were higher than in nonmetropolitan areas in 1999 (6.4 versus 4.0), however, the rates converged in 2004, and by 2015, the nonmetropolitan rate (17.0) was slightly higher than the metropolitan rate (16.2).

interpretationDrug use and subsequent overdoses continue to be a critical and complicated public health challenge across metropolitan/nonmetropolitan areas. The decline in illicit drug use by youth and the lower prevalence of illicit drug use disorders in rural areas during 2012-2014 are encouraging signs. However, the increasing rate of drug overdose deaths in rural areas, which surpassed rates in urban areas, is cause for concern. PUBLIC HEALTH ACTIONS: Understanding the differences between metropolitan and nonmetropolitan areas in drug use, drug use disorders, and drug overdose deaths can help public health professionals to identify, monitor, and prioritize responses. Consideration of where persons live and where they die from overdose could enhance specific overdose prevention interventions, such as training on naloxone administration or rescue breathing. Educating prescribers on CDC's guideline for prescribing opioids for chronic pain (Dowell D, Haegerich TM, Chou R. CDC guideline for prescribing opioids for chronic pain-United States, 2016. MMWR Recomm Rep 2016;66[No. RR-1]) and facilitating better access to medication-assisted treatment with methadone, buprenorphine, or naltrexone could benefit communities with high opioid use disorder rates.

Indexed as

AdolescentAdultChildDrug OverdoseFemaleHealth SurveysHumansIllicit DrugsMaleRural PopulationSubstance-Related DisordersUnited StatesUrban PopulationYoung AdultIllicit Drugs

Identifiers

PMID29049278
PMCPMC5829955
OpenAlexW2765710881

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.